Genetic polymorphisms associated with stroke, methods of detection and uses thereof Patent application (2023) (2023)

U.S. Patent Application No. 16/814085 was filed with the Patent Office on 12/03/2020 forgenetic polymorphisms associated with stroke, detection methods and their use.The assignee of this patent is CELERA CORPORATION. The invention is credited to James J. DEVLIN, May LUKE.

GENETIC POLYMORPHISMS RELATED TO STROKE, METHODS OF DETECTION AND THEIR USE

Abstract

The present invention provides compositions and methods based on genetic polymorphisms associated with vascular diseases such as stroke. In particular, the present invention relates to genetic polymorphisms useful for such uses as predicting disease risk or predicting an individual's response to a treatment such as statins, including groups of polymorphisms used as a signature marker set for such uses can, as well as nucleic acid molecules containing the polymorphisms, protein variants encoded by such nucleic acid molecules, reagents for detecting the polymorphic nucleic acid molecules and proteins and methods for using the nucleic acid and proteins and methods for using reagents for their detection.

Associated US Patent Documents

Expectations

A method of determining whether a human has an altered risk of stroke, comprising testing nucleic acid from the human for the presence or absence of a polymorphism selected from the group consisting of the polymorphisms represented by position 101 of any of the nucleotide sequences of SEQ ID NOS :436-1566 or its supplement, wherein the polymorphism is indicative of altered risk of stroke.

2-3 (cancelled)

4. The method of claim 1, wherein the changed risk is an increased risk.

5. The method of claim 1, wherein the changed risk is a reduced risk.

The method of claim 1, wherein the nucleic acid is a nucleic acid extract from a human biological sample.

7. The method of claim 6, wherein the biological sample is blood, saliva or buccal cells.

8. The method of claim 6, further comprising preparing the nucleic acid extract from the biological sample prior to the testing step.

9. The method of claim 8, further comprising obtaining the biological sample from the human prior to the preparing step.

10. The method of claim 1, wherein the testing step comprises nucleic acid amplification.

11. The method according to claim 10, wherein the nucleic acid amplification is carried out by polymerase chain reaction.

12. The method of claim 1, further comprising correlating the presence or absence of the polymorphism with an altered risk of stroke.

13. The method of claim 12, wherein the correlating step is performed by computer software.

The method of claim 1, wherein the testing is performed using sequencing, 5' nuclease digestion, molecular beacon assay, oligonucleotide ligation assay, size analysis, single strand conformational polymorphism analysis, or denaturing gradient gel electrophoresis (DGGE).

15. The method according to any one of claims 1 to 14, wherein the testing is performed using an allele-specific method.

16. The method according to claim 15, wherein the allele-specific method is an allele-specific probe hybridization, an allele-specific primer extension or an allele-specific amplification.

17. The method according to claim 16, wherein the method is performed using an allele-specific primer provided in Table 3.

18th (cancelled)

19. The method of claim 1, further comprising correlating the presence of the polymorphism with a reduction in stroke risk by an HMG-CoA reductase inhibitor.

20. The method of claim 19, wherein the correlating step is performed by computer software.

21-25. (cancelled)

26. A method of reducing the risk of stroke in a human comprising administering to the human an effective amount of a therapeutic agent, the human being determined to be at an increased risk of stroke due to the presence or absence of a polymorphism selected from the group Polymorphisms represented by position 101 of any of the nucleotide sequences of SEQ IDNOS: 436-1566 or their complement.

27. The method of claim 26, wherein the method comprises testing nucleic acid from the human for the presence or absence of the polymorphism.

28. The method of claim 26, wherein the therapeutic agent comprises an HMG-CoA reductase inhibitor.

29-41. (cancelled)

Description

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application is a continuation of US non-provisional application Ser. No. 15/790,581, filed October 23, 2017, which is a continuation of U.S. nonprovisional application Ser. No. 14/886,595, filed October 19, 2015, which is a continuation of U.S. nonprovisional application Ser. No. 13/655,905, filed October 19, 2012, which is a continuation of U.S. nonprovisional application Ser. No. 12/389,313, filed February 19, 2009, which assigned priority to US Provisional Application Ser. No. 61/066,584, filed February 20, 2008, the entire contents of which are hereby incorporated by reference into this application.

FIELD OF THE INVENTION

The present invention is in the field of vascular disease, particularly stroke, and drug response, particularly response to statin treatment. In particular, the present invention relates to specific single nucleotide polymorphisms (SNPs) in the human genome and their association with vascular disease, including but not limited to cerebrovascular disease such as stroke, and/or variation in response to statin treatment (including preventive treatment) between different individuals. For example, the SNPs disclosed herein can be used as targets for diagnostic/prognostic reagents as well as therapeutic agents for early detection of stroke risk, to provide clinically important information for the prevention and/or treatment of stroke, to predict the severity or outcome of a stroke in a person , to determine the prognosis of a person's recovery from stroke, to screen and select therapeutics, and to predict a patient's response to therapeutic agents, such as assessing the likelihood that a person will respond favorably to statins, particularly for the treatment or prevention of stroke. The SNPs disclosed herein are also useful for human identification applications. Methods, assays, kits and reagents for detecting the presence of these polymorphisms and their encoded products are provided.

BACKGROUND OF THE INVENTION

Stroke and other vascular diseases

Vascular diseases encompass a number of related pathologies, including cerebrovascular diseases such as stroke, as well as carotid artery disease, coronary artery disease, peripheral artery disease, aortic aneurysm and vascular dementia.

[0005] Stroke is a common and serious cerebrovascular disease. It affects 4.7 million people in the United States, with 500,000 first attacks and 200,000 recurrent cases annually. About one in four men and one in five women by the age of 45 will have a stroke by the age of 85. About 25% of stroke patients die within a year. In fact, stroke is the third leading cause of death in the United States, accounting for 170,000 deaths each year. Among those who survive a stroke, 30 to 50% do not regain their functional independence. Stroke is therefore the leading cause of disability and the second leading cause of dementia (Heart Disease and StrokeStatistics - 2004 Update, American Heart Association).

A stroke occurs when an artery that brings oxygen and nutrients to the brain either ruptures, causing a hemorrhagic stroke, or becomes blocked, causing an ischemic stroke. Ischemic stroke can be caused by thrombus formation at the site of an atherosclerotic plaque rupture (this type of ischemic stroke is referred to interchangeably as a thrombotic or atherothrombotic stroke) or by emboli (clots) that have migrated from another part of the vasculature (this type of ischemic Stroke is referred to as embolic stroke), often from the heart (this type of embolic stroke may be referred to as cardioembolic stroke). In both ischemic and hemorrhagic stroke, a cascade of cellular changes resulting from ischemia or increased intracranial pressure leads to brain cell injury or death. In the United States, the majority (about 80-90%) of stroke cases are ischemic (Rathore, et al., Stroke 33:2718-2721 ((2002))), including 30% thrombotic large vessels (also known as large vessel occlusive) thrombosis of the small vessel), 20% thrombotic small vessel (also known as small vessel occlusive disease), and 30% embolic or cardiogenic (caused by a clot originating from elsewhere in the body, such as carotid artery stenosis). The ischemic form of stroke results from obstruction of the Blood flow in cerebral blood vessels and has a common pathologic etiology with atherosclerosis and thrombosis.

[0007] About 10-20% of stroke cases are of the hemorrhagic type (Rathore, et al., Stroke 33:2718-2721 ((2002))), involving bleeding within or around the brain. Bleeding within the brain is known as a cerebral hemorrhage Hypertension, which is commonly associated with high blood pressure. Bleeding into the meninges surrounding the brain is called an asubarachnoid hemorrhage, which can be caused by a ruptured cerebral aneurysm, arteriovenous malformation, or head injury While about 8% of ischemic stroke cases result in death within 30 days, about 38% result in of cases of hemorrhagic stroke to death within the same time period (Collins, et al., J. Clin. Epidemiol. 56:81-87 (2003)).

Known risk factors for stroke can be divided into modifiable and non-modifiable risk factors. Older age, male gender, Black or Hispanic ethnicity, and a family history of stroke are nonmodifiable risk factors. Modifiable risk factors include hypertension, smoking, elevated insulin levels, asymptomatic carotid disease, cardiovascular disease, and hyperlipidemia.

Several reports based on twin studies (Brass et al., Stroke. 1992; 23:221-223 and Bak et al., Stroke. 2002; 33:769-774) and family studies (Welin L, et al. N. Engl J Med 1987;317:521-526 and Jousilahti et al Stroke 1997;28:1361-136) have shown that genetics contribute to stroke risk independent of conventional risk factors. A number of genetic markers have been reported to be associated with stroke, and some examples of stroke-related markers include MTHFR, ACE, NOTCH3, IL-6, PON1, fibrinogen-beta, and lipoprotein lipase (Casas, et al., Arch. Neurol., 61:1652-1661 (2004)).

The acute nature of stroke leaves physicians little time to prevent or reduce brain damage. Strategies to mitigate the effects of stroke include prevention and treatment with thrombolytic and possibly neuroprotective agents. The success of preventive measures will depend on identifying risk factors in individual patients and ways to modulate their effects.

Although some risk factors for stroke are not modifiable, such as age and family history, other underlying pathologies or risk factors of stroke, such as atherosclerosis, hypertension, smoking, diabetes, aneurysm, and atrial fibrillation, are chronic and amenable to effective life expectancy. Style changes, pharmacological and interventional as well as surgical treatments. Early identification of patients with meaningful risk factors, particularly those with a family history, through non-invasive testing of genetic markers associated with stroke will allow physicians to target those at highest risk for aggressive risk reduction.

[0012] Thus, there is a need to identify new genetic markers that predict an individual's predisposition to developing stroke and other vascular diseases. In addition, the discovery of genetic markers useful in identifying individuals at increased risk of stroke may, for example, lead to better preventive and therapeutic strategies, economic models and health policy decisions.

The reduction in coronary and cerebrovascular events and all-cause mortality by treatment with HMG-CoA reductase inhibitors (statins) has been demonstrated in a series of randomized, double-blind, placebo-controlled prospective studies (Waters, D.D., Clin Cardiol, 2001. 24 (8 Suppl): pp. 1113-7, Singh, B.K. and J.L. Mehta, CurrOpin Cardiol, 2002. 17(5): pp. 503-11). These drugs work primarily by inhibiting hepatic cholesterol synthesis, which causes LDL receptors in the liver to become upregulated. The resulting increase in LDL catabolism leads to a decrease in circulating LDL, a major risk factor for vascular disease.

[0014] In addition to LDL lowering, a variety of potential non-lipid-lowering effects have been suggested to play a role in cardiovascular risk reduction from statins. These include anti-inflammatory effects on various vascular cell types, including foam cell macrophages, enhanced endothelial responses, inhibition of platelet reactivity, thereby reducing hypercoagulability, and many others (Puddu, P., GM Puddu, and A. Muscari, Acta Cardiol, 2001. 56(4) : pp. 225-31, Albert, M.A., et al., JAMA, 2001. 286(1): pp. 64-70, Rosenson, R.S., Curr Cardiol Rep, 1999. 1(3): pp. 225-32 , Dangas, G., et al., Thromb Haemost, 2000. 83(5): pp. 688-92, Crisby, M., Drugs Today (Barc), 2003. 39(2): pp. 137-43, Liao, J.K., Int JClin Pract Suppl, 2003(134): pp. 51-7). However, because hypercholesterolemia is a factor in many of these additional pathophysiological mechanisms that are abolished by statins, many of these statin benefits may be a consequence of LDL lowering.

Statins can be divided into two types according to their physicochemical and pharmacokinetic properties. Statins such as lovastatin, simvastatin, atorvastatin and cerevastatin are hydrophobic in nature and as such diffuse across membranes and are therefore highly cell permeable. Hydrophilic statins such as aspravastatin are more polar, so they use specific cell surface transporters for cellular uptake (Ziegler, K. and W. Stunkel, Biochim Biophys Acta, 1992. 1139(3): pp. 203-9, Yamazaki, M., et al., Am J Physiol, 1993. 264(1 pt. 1): pp. G36-44, Komai, T., et al., Biochem Pharmacol, 1992. 43(4): pp. 667-70). The latter statin uses a transporter, OATP2, whose tissue distribution is restricted to the liver and are therefore relatively hepatospecific inhibitors (Hsiang, B., et al., J Biol Chem, 1999.274(52): p. 37161-8). The former statins, which do not use specific transport mechanisms, are available to all cells and can act directly on a much broader range of cells and tissues. These differences in properties can affect the spectrum of action of each statin. For example, pravastatin has a low myopathic potential in animal models and myocyte cultures compared to other hydrophobic statins (Masters, B.A., et al., Toxicol Appl Pharmacol, 1995. 131(1): p. 163-74. Nakahara, K. et al. , Toxicol Appl Pharmacol, 1998. 152(1): pp. 99-106, Reijneveld, J.C., et al., Pediatr Res, 1996. 39(6): pp. 1028-35).

[0016] Evidence from gene association studies is accumulating to suggest that responses to drugs are indeed under genetic control, at least in part. Therefore, pharmacogenetics—the study of the variability in drug responses attributed to hereditary factors in different populations—can go a long way toward finding answers to this challenge (Roses, A.D., Nature, 2000.405(6788): pp. 857-65, Mooser , V., et al., J Thromb Haemost, 2003.1(7): pp. 1398-1402, Humma, LM and SG Terra, Am. J. HealthSyst Pharm, 2002. 59(13): pp. 1241-52) . Numerous associations between selected genotypes, as defined by SNPs and other sequence variations, and specific responses to cardiovascular drugs have been reported. It has been suggested that polymorphisms in several genes affect responses to statins, including CETP (Kuivenhoven, J.A., et al., N. Engl. J. Med., 1998. 338(2): pp. 86-93), Beta -Fibrinogen (deMaat, M.P., et al., Arterioscler Thromb Vasc Biol, 1998. 18(2): pp. 265-71), hepatic lipase (Zambon, A., et al., Circulation, 2001.103(6): p 792-8), lipoprotein lipase (Jukema, J.W., et al., Circulation, 1996. 94(8): p. 1913-8), glycoprotein Ma (Bray, P.F., et al., Am J Cardiol, 2001. 88 (4): p. 347-52), stromelysin-1 (deMaat, M.P., et al., Am J Cardiol, 1999. 83(6): p. 852-6), and apolipoprotein E (Gerdes, L.U., et al., Circulation, 2000.101(12): pp. 1366-71, Pedro-Botet, J., et al., Atherosclerosis, 2001. 158(1): pp. 183-93). Some of these variants were shown to affect clinical events, while others were associated with changes in surrogate endpoints.

Thus, there is also a need to identify genetic markers to stratify stroke patients based on their likelihood of responding to drug therapy, particularly statin treatment.

[0018] SNPs

[0019] The genomes of all organisms undergo spontaneous mutation during their ongoing evolution, producing different forms of precursor genetic sequences (Gusella, Ann. Rev. Biochem. 55, 831-854 (1986)). A variant form may confer an evolutionary advantage or disadvantage relative to an ancestral form, or may be neutral. In some cases, a variant form confers an evolutionary advantage on the species and eventually becomes incorporated into the DNA of many or most members of the species, effectively becoming the progenitor form. In addition, the effects of a different shape can be both beneficial and detrimental depending on the circumstances. For example, a heterozygous sickle cell mutation confers resistance to malaria, but a homozygous sickle cell mutation is usually fatal. In many cases, both progenitor and variant forms survive and coexist in a species population. The coexistence of multiple forms of a genetic sequence results in genetic polymorphisms, including SNPs.

About 90% of all polymorphisms in the human genome are SNPs. SNPs are single base positions in DNA where different alleles or alternative nucleotides exist in a population. The SNP position (referred to interchangeably herein as SNP, SNP site, SNP locus, SNP marker, or marker) is usually preceded and followed by highly conserved sequences of the allele (e.g., sequences occurring in less than 1/100 or 1 /1000 members vary). the population). An individual can be homozygous or heterozygous for an allele at any SNP position. A SNP may in some cases be referred to as a "cSNP" to indicate that the nucleotide sequence containing the SNP is an amino acid coding sequence.

A SNP can arise from a substitution of one nucleotide for another at the polymorphic site. Substitutions can be transitions or transversions. A transition is the replacement of a purine nucleotide with another purine nucleotide or a pyrimidine with another pyrimidine. A transversion is the replacement of a purine with a pyrimidine or vice versa. A SNP can also be a variant with a single base insertion or deletion, termed an "indel" (Weber et al., "Human diallelic insert/deletion polymorphisms", Am J HumGenet 2002 October;71(4):855– 82).

A synonymous codon change or silent mutation/SNP (terms such as “SNP,” “polymorphism,” “mutation,” “mutant,” “variation,” and “variant” are used interchangeably herein) is one that does not, due to the degeneration of the genetic codes lead to a change in the amino acid. A substitution that changes a codon encoding one amino acid to a codon encoding another amino acid (i.e., an anonymous codon change) is called a missense mutation and a stop codon is formed, resulting in premature termination a polypeptide chain and a truncated protein. A read-through mutation is another type of non-synonymous codon change that causes the destruction of a stop codon, thereby resulting in an elongated polypeptide product. While SNPs can be bi-, tri-, or tetra-allelic, the vast majority of SNPs are bi-allelic and are therefore often referred to as "bi-allelic markers" or "di-allelic markers".

As used herein, references to SNPs and SNP genotypes encompass individual SNPs and/or haplotypes, which are groups of SNPs that are generally inherited together. Haplotypes may show stronger correlations with disease or other phenotypic effects compared to individual SNPs, and therefore may offer increased diagnostic accuracy in some cases (Stephens et al. Science 293, 489-493, July 20, 2001). The term "haplotype" as used herein refers to a set of two or more alleles on a single chromosome. The term "diplotype" refers to a combination of two haplotypes carried by an adiploid individual. The term "double diplotype", also called "two-locus diplotype", refers to a combination of diplotypes at two different loci for an individual.

Causative SNPs are those SNPs that cause changes in gene expression or in the expression, structure and/or function of a gene product and therefore best predict a potential clinical phenotype. One such class includes SNPs that fall within regions of genes that encode a polypeptide product, i. H. cSNPs. These SNPs can result in a change in the amino acid sequence of the polypeptide product (i.e., non-synonymous codon changes) and result in the expression of a defective or other variant protein. Furthermore, in the case of nonsense mutations, a SNP can lead to precocious termination of a polypeptide product. Such product variants can lead to a pathological condition, e.g. B. a genetic disease lead. Examples of genes in which a SNP within a coding sequence causes a genetic disease include sickle cell anemia and cystic fibrosis.

[0025] Causative SNPs do not necessarily have to occur in coding regions; causative SNPs can occur, for example, in any genetic region that can ultimately affect the expression, structure, and/or activity of the protein encoded by a nucleic acid. Such genetic regions include, for example, those involved in transcription, such as SNPs in transcription factor binding domains, SNPs in promoter regions, in areas involved in transcript processing, such as SNPs at intron-exon borders that can cause splicing errors , or SNPs in mRNA processing signal sequences such as polyadenylation signal regions. Some SNPs that are not causative SNPs are nevertheless closely associated with, and therefore disassociate from, a disease-causing sequence. In this situation, the presence of an SNP correlates with the presence of, or a predisposition to, or an increased risk of developing the disease. These SNPs, while not causative, are nonetheless also useful for diagnostics, disease predisposition screening, and other uses.

An association study of an SNP and a specific disorder involves determining the presence or frequency of the SNP allele in biological samples from individuals with the disorder of interest, such as stroke and related pathologies, and comparing the information to that of controls (i.e., Subjects who do not have the disease; control subjects may also be referred to as "healthy" or "normal" subjects) who are preferably of similar age and race. Appropriate selection of patients and controls is important for the success of SNP association studies. Therefore, a pool of individuals with well-characterized phenotypes is highly desirable.

A SNP can be screened in diseased tissue samples or any biological sample obtained from a diseased individual and compared to control samples and selected for its increased (or decreased) incidence in a specific pathological condition, such as stroke. Once a statistically significant association is established between one or more SNP(s) and a pathological condition (or other phenotype) of interest, then the region around the SNP can optionally be thoroughly screened to identify the causative genetic locus/sequence( en) (e.g. causative SNP/mutation, gene, regulatory region, etc.) affecting the pathological condition or phenotype. Association studies can be performed within the general population and are not limited to studies performed on related individuals in affected families (linkage studies).

Clinical trials have shown that patient response to treatment with pharmaceuticals is often heterogeneous. There is a constant need to improve the design and therapy of pharmaceutical agents. In this regard, SNPs can be used to identify patients best suited for therapy with particular pharmaceutical agents (this is often referred to as "pharmacogenomics"). Similarly, SNPs can be used to exclude patients from a particular treatment based on the increased likelihood that the patient will develop toxic side effects or the likelihood that they will not respond to treatment. Pharmacogenomics can also be used in pharmaceutical research to aid in drug development and the selection process. (Linder et al. (1997), Clinical Chemistry, 43,254; Marshall (1997), Nature Biotechnology, 15, 1249; International Patent Application WO 97/40462, Spectra Biomedical; and Schafer et al. (1998), Nature Biotechnology, 16: 3 ).

SUMMARY OF THE INVENTION

The present invention relates to the identification of SNPs, unique combinations of SNPs and haplotypes or diplotypes of SNPs that are associated with stroke (e.g., increased or decreased risk of stroke) and/or drug response. in particular, response to treatment with statins (including preventive treatment), such as B. to treat or prevent a stroke. The polymorphisms disclosed herein are directly useful as targets for the design of diagnostic and prognostic reagents and the development of therapeutic and preventative agents, such as for use in determining an individual's predisposition to stroke and for treating or preventing stroke and related pathologies , such as other vascular diseases, and to predict a patient's response to therapeutic agents such as statins, particularly for the treatment or prevention of stroke. In addition, the polymorphisms disclosed herein can also be used to predict a person's responsiveness to statins for the treatment or prevention of diseases other than stroke, such as cancer, and can also be used to predict a person's responsiveness to drugs other than statins, which used to treat or prevent stroke.

Based on the identification of SNPs associated with stroke and/or statin treatment response, the present invention also provides methods for detecting these variants, as well as the design and manufacture of detection reagents needed to to fulfill this task. In particular, the invention provides, for example, SNPs associated with stroke and/or response to statin treatment, isolated nucleic acid molecules (including DNA and RNA molecules) containing these SNPs, protein variants encoded by nucleic acid molecules encoding such SNPs contain antibodies against the encoded protein variants, computer-based and data storage systems containing the novel SNP information, methods for detecting these SNPs in a test sample, methods for identifying individuals who are at altered (ie, increased or decreased) risk, a first or of having another stroke, methods of predicting the severity or outcome of a stroke, methods of treating a person at increased risk of stroke, and methods of identifying people (e.g., determining the likelihood of a particular person) having a changed (i.e., increased or decreased) ) likely to respond to statin treatment (or more or less likely to experience adverse side effects of treatment), particularly statin treatment of stroke, based on the presence or absence of one or more specific nucleotides (alleles) at one or more SNPs disclosed herein or the Evidence of one or more coded variant products (e.g. B. variant mRNA transcripts). or variant proteins), methods of screening for compounds useful in the treatment or prevention of a disorder associated with a variant gene/protein, compounds identified by these methods, methods of treating or preventing disorders caused by a variant gene/protein mediated, etc. The present invention also provides methods for identifying individuals who possess SNPs associated with an increased risk of stroke and yet may benefit from treatment with statins since statin treatment may reduce their risk of stroke.

The exemplary utilities described herein for the stroke-associated SNPs and statin response-associated SNPs disclosed herein apply to both the first (primary) and recurrent stroke. For example, the SNPs disclosed herein can be used to determine the risk of a first stroke in a person who has never had a stroke in the past, and can also be used to determine the risk of a recurrent stroke in a person who has previously had a stroke had a stroke.

The present invention also provides methods for selecting or formulating a treatment plan (e.g., methods for determining whether to administer statin treatment to a person who has previously had or is at risk of having a stroke has a stroke in the future, methods of selecting a particular statin-based treatment regimen such as dosage and frequency of administration of statin or a particular form/type of statin such as a particular pharmaceutical formulation or statin compound, methods of administering an alternative non-statin-based one treatment to subjects predicted unlikely to respond positively to statin treatment, etc.) and methods of determining the likelihood of experiencing toxicity or other undesirable side effects from statin treatment, etc. The present invention also provides methods of selecting subjects who will be given a statin or other therapeutic based on the subject's genotype and methods of selecting subjects for a clinical trial of a statin or other therapeutic based on the subject's genotypes (e.g. trial in which it is unlikely that they respond positively to statin treatment). The present invention further provides methods for reducing a person's risk of stroke by administering statin treatment, including preventing a first or recurrent stroke by administering statin treatment when the person carries one or more SNPs identified herein as associated with stroke risk or stroke statin response have been identified.

In certain exemplary embodiments of the invention, the SNP is selected from the group consisting of the following (the name of the gene or chromosome containing the SNP is given in parentheses): rs3900940/hCV7425232 (MYH15), rs3814843/hCV11476411 ( CALM1), rs2200733/hCV16158671 (chromosome 4q25), andrs10757274/hCV26505812 (chromosome 9p21), and combinations of any number of these SNPs, and any of these SNPs in combination with other genetic markers. Exemplary embodiments of the invention provide compositions (e.g., detection reagents and kits) and methods of using these SNPs for stroke-related applications, such as determining a person's risk of having a stroke, or whether a person is on treatment with statins or other therapies will benefit. For example, certain embodiments provide methods of using one of the methods rs3900940/hCV7425232 (MYH15), rs3814843/hCV11476411 (CALM1), rs2200733/hCV16158671 (chromosome 4q25), and/or rs10757274/hCV26505812 (chromosome 9q25) and to determine an individual's risk of stroke using rs10757274/hCV26505812 (chromosome 9p21) to determine whether a person will benefit from statin treatment.

[0034] In Tables 1-2, the present invention provides gene information, transcript sequences (SEQ ID NOS: 1-80), encoded amino acid sequences (SEQ ID NOS: 81-160), genomic sequences (SEQ ID NOS: 260-435). . , Transcript-based contextual sequences (SEQ IDNOS: 161-259) and genome-based contextual sequences (SEQ IDNOS: 436-1566) containing the SNPs of the present invention, and extensive SNP information covering observed alleles, allele frequencies, populations/ethnicity groups, in which alleles were observed, information on the nature of the SNP and the corresponding functional effect, and for cSNPs information on the encoded polypeptide product. The transcript sequences (SEQ ID NOS: 1-80), amino acid sequences (SEQ ID NOS: 81-160), genomic sequences (SEQ IDNOS: 260-435), transcript-based SNP context sequences (SEQ IDNOS: 161-259), and genome-based SNP Contextual sequences (SEQ IDNOS: 436-1566) are also provided in the sequence listing.

In certain exemplary embodiments, the invention provides methods for identifying an individual having an altered risk of having a first or recurrent stroke, the method comprising detecting a single nucleotide polymorphism (SNP) in any of the nucleotide sequences of SEQ ID NO:1 -80 and 161-1566, particularly represented by one of the genomic context sequences of SEQ IDNOS: 436-1566, in the nucleic acids of the individual, wherein the SNP is given in Table 1 and/or Table 2 and the presence of the SNP is indicative of one altered risk of stroke in that person. In a particular exemplary embodiment of the present invention, SNPs naturally occurring in the human genome are provided as isolated nucleic acid molecules. These SNPs are associated with stroke and related pathologies such as other vascular diseases. Other vascular diseases include, but are not limited to, cerebrovascular disease, carotid artery disease, coronary artery disease, peripheral artery disease, aortic aneurysm, and vascular dementia. In particular, the SNPs are associated with either an increased or decreased risk of stroke. As such, they can have a variety of uses in the diagnosis and/or treatment of stroke and related pathologies. One aspect of the present invention relates to an isolated nucleic acid molecule comprising a nucleotide sequence in which at least one nucleotide is a SNP proprietary to Applera or Celera. In an alternative embodiment, a nucleic acid of the invention is an amplified polynucleotide produced by amplification of a SNP-containing nucleic acid template. In another embodiment, the invention provides a protein variant encoded by an anucleic acid molecule containing a SNP disclosed herein.

In yet another embodiment of the invention, a reagent for detecting an SNP in association with its naturally occurring flanking nucleotide sequences (which can be either DNA or mRNA, for example) is provided. In particular, such a reagent may take the form, for example, of a hybridization probe or an amplification primer useful for the specific detection of a SNP of interest. In an alternative embodiment, a protein detection reagent is used to detect a protein variant encoded by a nucleic acid molecule containing a SNP disclosed herein. A preferred embodiment of a protein detection reagent is an antibody or an antigen-reactive antibody fragment.

Various embodiments of the invention also provide kits comprising SNP detection reagents and methods of detecting the SNPs disclosed herein using detection reagents. In a specific embodiment, the present invention provides a method for identifying an individual at increased or reduced risk of suffering a stroke by detecting the presence or absence of one or more SNP alleles disclosed herein. Preferably, the SNP allele may be an allele of a SNP selected from the group consisting of the following (the name of the gene or chromosome containing the SNP is given in parentheses): rs3900940/hCV7425232 (MYH15), rs3814843/hCV11476411 ( CALM1 ), rs2200733/hCV16158671 (chromosome 4q25) and rs10757274/hCV26505812 (chromosome 9p21) and combinations of any number of these SNPs and any of these SNPs in combination with other genetic markers.

In another embodiment, a method of diagnosing stroke or related pathologies by detecting the presence or absence of one or more SNPs or SNP alleles disclosed herein is provided. In another embodiment, the invention provides a method for identifying an individual with an altered (either increased or decreased) risk of stroke by detecting the presence or absence of one or more SNPs or SNP alleles disclosed herein. Thus, an exemplary embodiment of the invention provides a method for identifying an individual at increased risk of suffering a stroke by determining which nucleotide (allele) is present at one or more SNPs disclosed herein. An alternative exemplary embodiment of the invention provides a method for identifying an individual who has a reduced risk of suffering a stroke by determining which nucleotide (allele) is present at one or more SNPs disclosed herein.

The nucleic acid molecules of the invention can be inserted into an expression vector to produce, for example, a protein variant in a host cell. Thus, the present invention also provides a vector comprising a SNP-containing nucleic acid molecule, genetically engineered host cells containing the vector, and methods of expressing a recombinant protein variant using such host cells. In another specific embodiment, the host cells, SNP-containing nucleic acid molecules and/or protein variants can be used as targets in a method for screening and identifying therapeutic agents or pharmaceutical compounds useful in the treatment of stroke and related pathologies such as other vascular diseases.

[0040] One aspect of this invention is a method of treating or preventing a first or recurrent stroke in a human, wherein the human carries a SNP, gene, transcript and/or encoded protein identified in Tables 1-2, wherein the method comprises administering to the human subject a therapeutically or prophylactically effective amount of one or more agents (e.g., statins) that counteract the effects of the disease, such as by inhibiting (or stimulating) the activity of the gene, transcript, and/or or encoded proteins identified in Tables 1-2.

Another aspect of this invention is a method for identifying an agent useful in the therapeutic or prophylactic treatment of stroke and related pathologies in a human, wherein the human carries an SNP, gene, transcript and/or encoded protein identified in Tables 1-2 the method comprises contacting the gene, transcript or encoded protein with a candidate agent (e.g. a statin) under conditions appropriate to the formation of a binding complex between the gene, transcript or encoded protein and the candidate agent to allow and detect the formation of the binding complex, the presence of the complex identifying the drug.

Another aspect of this invention is a method of treating stroke and related pathologies in a human, the method comprising:

(i) determining that the human subject carries a SNP, gene, transcript and/or encoded protein identified in Tables 1-2, and

(ii) administering to the subject a therapeutically or prophylactically effective amount of one or more agents (e.g., statins) that counteract the effects of the disease.

Yet another aspect of this invention is a method of assessing a patient's suitability for stroke treatment, comprising determining the patient's genotype with respect to a particular set of SNP markers, the SNP markers comprising a plurality of individual SNPs (e.g B. about 2-7 SNPs) in Tables 1-2, and calculating a score using an appropriate algorithm based on the patient's genotype, the resulting score indicating the eligibility of the patient undergoing stroke treatment.

Another aspect of the invention is a method of treating a stroke patient comprising administering to the stroke patient whose genotype is shown to contain a plurality of SNPs as described in Table 1 or Table 2, in a therapeutically effective amount, a suitable drug.

Another aspect of the invention is a method of identifying a human likely to benefit from statin treatment (as used herein, "treatment" includes both prophylactic and therapeutic treatment), the method comprising detecting the presence of a The associated statin response includes SNP (e.g., an allele associated with increased statin benefit) disclosed herein in human nucleic acids, where the presence of the SNP indicates that the human is likely to benefit from statin treatment.

Another aspect of the invention is a method of identifying a human likely to benefit from statin treatment, the method comprising detecting in human nucleic acids the presence of a SNP encoded in LD with a statin response-associated SNP disclosed herein is available. the presence of the SNP indicating that the human is likely to benefit from statin treatment.

Exemplary embodiments of the invention include methods of using a statin response-associated SNP disclosed herein to determine whether a person will benefit from statin treatment (e.g., determining whether a person should be administered a statin to reduce their likelihood of having a stroke to suffer), -associated SNPs disclosed herein can be used to predict response to any statin (HMG-CoA reductase inhibitors), including but not limited to, pravastatin (Pravachol®), atorvastatin ( Lipitor®), storvastatin, rosuvastatin (Crestor® .), fluvastatin (Lescol ® ), lovastatin (Mevacor ® ) and simvastatin (Zocor ® ) as well as combination therapies containing a statin such as assimvastatin + ezetimibe (Vytorin ® ), lovastatin + niacinextended -Release (Advicor ® ) and atorvastatin + amlodipine besylate (Caduet ® ).

In certain example embodiments of the invention, methods are directed to determining which patients would have greater protection against stroke when given intensive statin treatment compared to standard statin treatment. In certain embodiments, the statin may comprise a statin selected from the group consisting of atorvastatin, pravastatin and storvastatin. In certain embodiments, intensive statin treatment includes administering higher doses of a statin and/or increasing the frequency of statin administration compared to standard statin treatment. In certain further embodiments, intensive statin treatment may use a different type of statin than standard statin treatment; For example, atorvastatin can be used for intensive statin treatment and pravastatin for standard statin treatment.

Many other uses and advantages of the present invention will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiments herein. Merely for the purpose of clarifying the discussion, the invention is described in the following paragraphs by means of non-limiting examples.

Description of the file contained on the CD-R named CD000022ORD-CDR

The CD-R named CD000022ORD-CDR contains the following text file (ASCII):

1) The file SEQLIST_CD000022ORD.txt provides the sequence list. The sequence listing provides the transcript sequences (SEQ ID NOS: 1-80) and protein sequences (SEQ ID NOS: 81-160) as shown in Table 1 and genomic sequences (SEQ ID NOS: 260-435) as shown in Table 2 ready. for any stroke-associated gene containing one or more SNPs of the present invention. Also provided in the sequence listing are contextual sequences flanking each SNP, including both transcript-based contextual sequences as shown in Table 1 (SEQ ID NOS: 161-259) and genome-based contextual sequences as shown in Table 2 (SEQ ID NOS: 436-1566 ). . The context sequences generally provide 100 bp upstream (5') and 100 bp downstream (3') of each SNP, with the SNP located in the middle of the context sequence, for a total of 200 bp of context sequence surrounding each SNP.

The file SEQLIST_CD000022ORD.txt is 21,295 KB and was created on February 18, 2009. A computer-readable format of this sequence listing is also submitted here on a separate CDR labeled CRF. The information recorded in the CRF-CDR is identical to the sequence listing provided on the Duplicate Copy 1 and Duplicate Copy 2 CDR.

The material contained on the CRF marked CD-R is hereby incorporated by reference pursuant to 37 CFR 1.77(b)(4).

TABLE-US-LTS-CD-00001 LONG TABLES The patent application contains a long section of tables. A copy of the table is available in electronic form at the USPTO website (https://seqdata.uspto.gov/?pageRequest=docDetail&DocID=US20200377950A1). An electronic copy of the table is also available from the USPTO upon request and upon payment of the fee specified in 37 CFR1.19(b)(3).

Description of Table 1 and Table 2

Table 1 and Table 2 disclose the SNP and associated gene/transcript/protein information of the present invention. For each gene, Table 1 and Table 2 each provide a header with gene/transcript/protein information, followed by a transcript and protein sequence (in Table 1) or a genomic sequence (in Table 2) and then SNP information for each in SNP found in this gene/transcript.

NOTE: SNPs can be included in both Table 1 and Table 2; Table 1 represents the SNPs relative to their transcript sequences and encoded protein sequences, whereas Table 2 represents the SNPs relative to their genomic sequences (in some cases, Table 2 may also contain: after the last gene sequence, genomic sequences of one or more intergenic regions as well as SNP context sequences and other SNP information for all SNPs that lie within these intergenic regions). SNPs can be easily cross-referenced between tables based on their hCV (or in some cases hDV) identification numbers.

The gene/transcript/protein information includes: - Agene number (1 to n, where n = total number of genes in the table) - Celera hCG and internal UID identification numbers for the gene - a Celera hCT internal identification numbers and UID for the transcript (Table 1 only) A public Genbank accession number (e.g. RefSeq NM number) for the transcript (Table 1 only) Internal identification numbers of Celera hCP and UID for the protein encoded by the hCT - Transcript (Table 1 only) a Genbank public accession number (e.g. RefSeq NP number) for the protein (Table 1 only) a gene symbol known in the art [0068] a gene/protein name known in the art [0069] Position of Celera genome axis (indicates start nucleotide position-stop nucleotide position) [0070] the chromosome number of the chromosome on which the gene is located; to obtain further information regarding the medical importance of each gene Alternative gene/protein name(s) and/or symbol(s) in the OMIM record

NOTE: Due to the existence of alternative splice forms, multiple transcript/protein entries may be provided for a single gene entry in Table 1; i.e. for a single gene number, multiple entries can be provided in series, differing in their transcript/protein information and sequences.

The gene/transcript/protein information is followed by a transcript sequence and a protein sequence (in Table 1) or a genomic sequence (in Table 2) for each gene as follows: Transcript sequence (Table 1 only) (corresponding to SEQ ID NOS: 1-80 des Sequence listing), where SNPs are identified by their IUB codes (transcript sequences may include 5' UTR, protein coding and 3' UTR regions). (NOTE: When there are differences between the nucleotide sequence of the hCT transcript and the corresponding public transcript sequence identified by the Genbank accession number, the hCT transcript sequence (and encoded protein) is provided unless the public sequence is a RefSeq transcript sequence identified by an NM number, in which case the RefSeq NM transcript sequence (and the encoded protein) is provided, whether the hCT transcript or the RefSeq NM transcript as the transcript sequence is used, the disclosed SNPs are represented by their IUB codes within the transcript.) the encoded protein sequence (Table 1 only) (corresponding to SEQ ID NOS: 81-160 of the sequence listing) [0077] the genomic sequence of the gene (Table 2 only ), including 6 kb on each side of gene borders (i.e. 6 kb on the 5' side of the gene plus 6 kb on the 3' side of the gene) (corresponding to SEQ ID NOS: 260-435 of the Sequence Listing).

After the final gene sequence, Table 2 may contain additional genomic sequences from intergenic regions (in such cases these sequences are identified as "intergenic region:" followed by a numeric identification number), as well as SNP context sequences and other SNP information for all SNPs , which lie within each intergenic region (and such SNPs are identified as "INTERGENIC" for the SNP type).

NOTE: The transcript, protein and transcript-based SNP context sequences are provided in both Table 1 and the sequence listing. The genomic and genome-based SNP context sequences are provided in both Table 2 and the sequence listing. SEQ ID NOS are given in Table 1 for each transcript sequence (SEQ ID NOS: 1-80), protein sequence (SEQ ID NOS: 81-160) and transcript-based SNP context sequence (SEQ ID NOS: 161-259) and SEQ ID NOS are in Table 2 given for each genomic sequence (SEQ IDNOS: 260-435) and each SNP context genomic sequence (SEQ IDNOS: 436-1566).

The SNP information includes: contextual sequence (taken from the transcript sequence in Table 1 and taken from the genomic sequence in Table 2) with the SNP represented by its IUB code, including 100 bp upstream (5') from the SNP position plus 100 bp downstream (3') of the SNP position (the transcript-based SNP context sequences in Table 1 are provided in the Sequence Listings as SEQ ID NOS: 161-259; the genome-based SNP context sequences in Table 2 are provided in the Sequence Listing as SEQ ID NOS: 436-1566). Celera hCV internal identification number for the SNP (in some cases an “hDV” number is given instead of an “hCV” number) SNP position [position of the SNP within the given transcript sequence (Table 1) or within the given genomic sequence (Table 2)] SNP source (may include any combination of one or more of the following five codes, depending on which internal sequencing projects and/or public databases the SNP was observed in: "Applera" = SNP observed during resequencing of genes and regulatory Regions from 39 individuals, “Celera” = SNP observed during shotgun sequencing and assembly of the Celera human genome sequence, “Celera Diagnostics” = SNP, observed during resequencing of nucleic acid samples from individuals who have disease, “dbSNP”= SNP observed in the public database dbSNP,"HGBASE"=SNP observed in the public database HGBASE, "HGMD"=SNP observed in the public database Human Gene Mutation Database (HGMD), "HapMap"=SNP observed in the public database of the International HapMap Project , “CSNP” = SNP observed in an internal Applied Biosystems (Foster City, California) database encoding SNPS (cSNPs)) (NOTE: Multiple “Applera” source entries for a single SNP indicate that the same SNP was covered by several overlapping amplification products and the resequencing results (e.g. B. Observed allele number(s) of each of these amplification products are provided).

For the following SNPs provided in Table 1 and/or 2, the SNP source falls into one of the following three categories: 1) SNPs for which the SNP source is only "Applera" and no other, 2) SNPs, for which the SNP source is only "Celera Diagnostics" and no other, and 3) SNPs for which the SNP source is both "Applera" and "Celera Diagnostics" but no other (the hCV identification number and SEQ ID NO for the genomic context sequence of the SNP in Table 2 are indicated): hCV22275299 (SEQ ID NO:482), hCV25615822 (SEQ ID NO:639), hCV25651109 (SEQ ID NO:840), hCV25951678 (SEQ ID NO:1013) and hCV25615822 (SEQ ID NO:1375). These SNPs were not observed in any of the public databases (dbSNP, HGBASE, and HGMD), nor were they observed during shotgun sequencing and assembly of the human Celera genomic sequence (i.e., "Celera" SNP source). Population/allele/allele number information in the format [population1(first_allele, number1second_allele, number)population2(first_all-all, number1second_allele, number) total(first_allele,total|second_allele,total)]. The information in this field includes populations/ethnic groups in which particular SNP alleles have been observed (“cau” = Caucasian, “his” = Hispanic, “chn” = Chinese and “afr” = African American, “jpn” = Japanese, "ind"=Native American,"mex"=Mexican, "ain"="Native American, "cra"=Celera donor,"no_pop"=no population information available), identified SNPalleles and observed allele counts (within each population and total allele counts), where available, ["-" in the allele field represents a deletion allele of an insertion/deletion ("indel") polymorphism (in which case the corresponding insertion allele, which may consist of one or more nucleotides, is in the indicated allele field on the opposite side of the "I"); "-" in count field indicates allele number information is not available]. available in dbSNP): "HISP1" = human individual DNA (anonymized samples) from 23 individuals with self-designated HISPANICheritage; “PAC1” = human individual DNA (anonymized samples) from 24 individuals of self-declared RIM Pacific ancestry; "CAUL1" = human individual DNA (anonymized samples) from 31 individuals of self-described CAUCASIAN ancestry; “AFR1” = human individual DNA (anonymized samples) from 24 individuals of self-described AFRICAN/AFRICAN-AMERICAN heritage; "P1" = human individual DNA (anonymized samples) from 102 individuals with self-described heritage; "PA130299515"; "SC_12_A"=SANGER 12 DNAs of Asian origin from Corielle cell repositories, of which 6 are male and 6 are female; "SC_12_C"=SANGER 12 DNAs of Caucasian origin from Corielle cell repositories from the CEPH/UTAH library. Six male and 6 female; "SC_12_AA"=SANGER 12 DNAs of Afro-American origin from Coriellecell repositories, of which 6 are male and 6 are female; "SC_95_C"=SANGER 95 DNAs of Caucasian origin from Coriellecell repositories from the CEPH/UTAH library; and "SC_12_CA" = Caucasian - 12 DNAs from Corielle cell repositories derived from the CEPH/UTAH library (six males and six females).

NOTE: For SNPs from the SNP source "Applera", genes/regulatory regions from 39 individuals (20 Caucasian and 19 African American) were resequenced, and since each SNP position is represented by two chromosomes in each individual (with the exception of SNPs on X and Y chromosomes in males, for which each SNP position is represented by a single chromosome), up to 78 chromosomes have been genotyped for each SNP position. Thus, the sum of Afro-American ("afr") allele numbers is up to 38, the sum of Caucasian ("cau") allele numbers is up to 40, and the total sum of all allele numbers is up to 78.

(NOTE: Semicolons separate population/allele/enumeration information corresponding to each SNP source specified; i.e. when four SNP sources are specified, such as "Celera", "dbSNP", "HGBASE" and “HGMD”, then population/allele/count information is provided in four groups, separated by semicolons and listed in the same order as the SNP source listing, with each population/allele/count information group corresponding to the respective SNP source based on order, so in this example the first population /allele/count information group would correspond to the first listed SNP source (Celera) and the third population/allele/count information group, separated by semicolon, would be the third listed SNP source (HGBASE), if population/allele/count information is not available for a particular SNP source, then a pair of semicolons is still inserted as a placeholder to indicate consistency between the list of SNP sources and corresponding listing of population/allele/count information) SNP type (e.g. B. location within the gene/transcript and/or predicted functional effect)["MIS-SENSE-MUTATION"=SNP causes a change in the encoded amino acid (i.e., a non-synonymous coding SNP); "SILENT MUTATION" = SNP causes no change in the encoded amino acid (i.e., a synonymous encoding SNP); "STOP CODON MUTATION"=SNP is in a stop codon; "NONSINSE MUTATION"=SNP creates or destroys a stop codon; "UTR5" = SNP located in a 5' UTR of a transcript; "UTR 3" = SNP is in a 3' UTR of a transcript; "PUTATIVE UTR 5" = SNP is in a putative 5' UTR; "PUTATIVE UTR 3" = SNP is in aputative 3' UTR; "DONOR SPLICE SITE" = SNP located in a donor splice site (5' intron boundary); "ACCEPTOR SPLICE SITE" = SNP located at an acceptor splice site (3' intron boundary); "CODINGREGION" = SNP is located in a protein-coding region of the transcript; "EXON"=SNP is in an exon; "INTRON" = SNP is located in an intron; "hmCS"=SNP is located in a human mouse conserved segment; "TFBS" = SNP located in a transcription factor binding site; "UNKNOWN"=SNP type is not defined; "INTERGENIC" = SNP is intergenic, i. H. outside a gene boundary] protein coding information (Table 1 only), where relevant, in the format of [protein SEQ ID NO:#, amino acid position, (amino acid-1, codon1)(amino acid-2, codon2)]. The information in this field includes the SEQ ID NO of the encoded protein sequence, the position of the amino acid residue within the protein identified by SEQ ID NO that is encoded by the codon containing the SNP, amino acids (represented by one-letter amino acid codes) . encoded by the alternative SNP alleles (in the case of stop codons, "X" is used for the one-letter amino acid code), and alternative codons containing the alternative SNP nucleotides encoding the amino acid residues (such as for missense mutation type SNPs are generally indicated at least two different amino acids and at least two different codons, for silent mutation-type SNPs one amino acid and at least two different codons are generally indicated, etc.). Protein-coding region (e.g. in a UTR region) is "none" after the protein SEQ ID NO.

Description of Table 3

[0092] Table 3 provides sequences (SEQ ID NOS: 1567-1914) of exemplary primers that can be used to test certain SNPs by allele-specific PCR, such as for stroke-related uses.

Table 3 provides the following: The column labeled "Marker" provides an hCV identification number for each SNP that can be detected using the appropriate primers. The column labeled "Alleles" designates the two alternative alleles (i.e., nucleotides) at the SNP site. These alleles are targeted by the allele-specific primers (the allele-specific primers are shown as primer 1 and primer 2). Note that alleles in Table 3 may be presented based on a different orientation (i.e., reverse complement) compared to how the same alleles are presented in Tables 1-2. the column labeled "Primer 1 (allele-specific primer)" provides an allele-specific primer specific for an allele designated in the "Alleles" column. The column labeled "Primer 2 (allele-specific primer)" provides an allele-specific primer specific for the other allele labeled in the "Alleles" column. The column labeled "Common Primer" provides a common primer that is used in conjunction with each of the allele-specific primers (i.e., Primer 1 and Primer 2) that hybridizes at a site remote from the SNP position.

All primer sequences are given in the 5' to 3' direction.

Each of the nucleotides labeled in the "Alleles" column matches or is the reverse complement of the 3' nucleotide of the allele-specific primer (i.e., either primer 1 or primer) (depending on the orientation of the primer relative to the designated allele). 2) specific to this allele.

Description of Table 4

Table 4 provides a list of LD SNPs related to and derived from particular queried SNPs. The interrogated SNPs shown in column 1 (which gives the hCV identification numbers of each interrogated SNP) and column 2 (which gives the public rs identification numbers of each interrogated SNP) of Table 4 are statistically significantly associated with stroke, as in shown in the tables. These LD SNPs are provided as an example of SNPs that can also serve as markers for disease association based on being in LD with a queried SNP. The criteria and process for selecting such LD-SNPs, including the calculation of the ther 2 value and the r 2 threshold, are described in Example 8 below.

In Table 4, the column labeled "Interrogated SNP" represents each marker as identified by its unique hCV identification number. The column labeled "Retrieved RS" shows the publicly known identifier RS ​​number for the corresponding hCV number. The column labeled "LD SNP" represents the hCV numbers of the LD SNPs derived from their corresponding interrogated SNPs. The column labeled "LD SNP rs" shows the publicly known rs number for the corresponding hCV number. The column labeled "Power" represents the power level at which the r² threshold is set. For example, if the power is set to 0.51, the threshold r 2 calculated from this is the minimum r 2 that a LD-SNP must have with respect to a queried SNP for the LD-SNP to be classified as a marker with a probability of more than 51% can be associated with a disease phenotype. The column labeled "Threshold r²" represents the minimum value of r² that a LD-SNP must meet relative to a queried SNP in order to qualify as an LD-SNP. The column labeled "r²" shows the actual r² value of the LD SNP relative to the interrogated SNP to which it belongs.

Description of Tables 5-38

Table 5 provides baseline characteristics of ARIC participants in the Ischemic Stroke Study.

Table 6 provides SNPs associated with ischemic stroke in the ARIC study.

See Example One for more information regarding Tables 5-6.

Tables 7, 8 and 9 provide SNPs identified from the 51 SNPs analyzed in ARIC participants predicting ischemic stroke risk identified by Cox proportional hazards analysis, each with a two-tailed p -score of < 0.2 after adjustment for age and sex and a hazard ratio (HRR) > 1.0 in whites (Table 7), blacks (Table 8), and both whites and blacks (Table 9) (those included in p-values ​​shown in Tables 7-9 are two-tailed p-values, so the one-tailed p-values ​​for these SNPs are half of these two-tailed p-values). See the section “Supplementary Analysis of SNPs in the ARIC Study” for more information related to Tables 7-9.

Table 10 provides baseline characteristics of CHS participants in the Ischemic Stroke Study.

Table 11 provides SNPs associated with ischemic stroke in white CHS participants.

Table 12 provides SNPs associated with ischemic stroke in African-American CHS participants.

Table 13 shows that val allele homozygotes of ABCG2Val12Met are associated with an increased risk of ischemic stroke compared to the Met allele carriers in both White and African American CHS participants.

See Example Two for more information related to Tables 10-13.

Table 14 provides three SNPs predicting ischemic stroke risk identified by Cox proportional hazards analysis as each with one-sided p-values ​​<= 0.05 in Whites after adjusting for age and sex and also after adjusting for traditional risk factors have been identified. For more information on Table 14, see the Supplementary Analysis of SNPs in the CHS Study section.

Table 15 provides characteristics of non-cardioembolic stroke and healthy controls in the Vienna Stroke Registry (VSR) study.

Table 16 provides properties of six SNPs tested for association with non-cardioembolic stroke in VSR.

Table 17 provides results of the analysis for the association of six SNPs with non-cardioembolic stroke in VSR. In Table 17, individuals with missing information on genotype or traditional risk factors were excluded from case and control counts; Model 1 was adjusted for age and gender; Model 2 was adjusted for age, gender, smoking, hypertension, diabetes, dyslipidemia, and BMI; and "q" is the value of the false detection rate q.

See Example Three for more information regarding Tables 15-17.

Table 18 provides SNPs (two-tailed p-value of <0.2) with ischemic stroke (labeled “ischemic” in the Outcome column), atherothrombotic stroke (labeled “athero” in the Outcome column), and /or Early-onset stroke (indicated as “early-onset” in the Outcome column) in the VSR study either before or after adjustment for conventional risk factors (results after adjustment are marked “yes” and results before adjustment are marked “no ') in the "Fit?" column) (the p-values ​​shown in Table 18 are two-tailed p-values; thus the one-tailed p-values ​​for these SNPs are half of these two-tailed p-values). Further information on Table 18 can be found in the section "Supplementary analysis of SNPs in the Vienna Stroke Registry".

Table 19 (provided as Tables 19A-C to reduce table width, thus row order corresponds to the same markers and studies across each of Tables 19A-C) provides 61 SNPs associated with stroke risk in the UCSF/CCF study (1-sided p<0.05 or 2-sided p<0.1) and had the same risk allele as in the VSR study. Table 19 contains the stroke association data in both the UCSF/CCF and VSR studies. In Table 19A, the column labeled "RefAllele" refers to the major allele and the column labeled "Allele" to the alternative (minor) allele. If the "OR" (in Table 19C) is greater than one, carrying the minor allele has a greater risk of stroke compared to carrying the major (reference) allele, so the minor allele would be the risk allele. If the "OR" (in Table 19C) is less than one, the major allele would be the risk allele. See Example 4 below for more information regarding Table 19.

[0121] Tables 20-21 provide SNPs that showed a significant association with stroke risk in the German West study (which may be referred to herein interchangeably as the Munster stroke study) with 2-sided p-values ​​that were smaller than 0.1 (corresponding to 1-sided p-values ​​that are less than 0.05), and Table 21 contains SNPs associated with stroke risk that have the samerisk allele and 2-sided p-values ​​that in between are 0.1 and 0.2 (corresponds to one-sided p-values ​​between 0.05 and 0.1). In Tables 20-21, the following abbreviations are used for the endpoints in the column labeled “Outcome”: “ischemic_stk” = ischemic stroke, “nonce_stk” = non-cardioembolic stroke (ischemic stroke that was not cardioembolic in origin), “CE_stk “ = cardioembolic stroke." athero_stk"=atherothrombotic stroke, "lacunar_stk"=lacunar stroke, "nohd_stk"=no stroke with cardiac disease (ischemic stroke cases except cases with a history of cardiac disease), "recurrent_stk"=recurrent stroke (stroke cases who also had a history of stroke) and "EO_stk" = early onset stroke (cases younger than the median of all cases and controls older than the median of all controls). See Example 5 below for more information regarding Tables 20-21.

Tables 22-32 and 37-38 provide SNPs associated with risk of stroke or stroke statin response (SSR) in two pravastatin studies: CARE ("Cholesterol and Recurrent Events" study, which includes subjects who received a MI) and PROSPER ("Prospective Study of Pravastatin in the Elderly at Risk" study, which ofelderly includes subjects with or without a history of cardiovascular disease). SNPs that were significantly associated with stroke risk at CARE are listed in Tables 22, 24 and 26. SNPs that were significantly associated with SSR in CARE are presented in Tables 23, 25, and 27) for association with stroke risk in CARE are presented in Table 28. SNPs that were significantly associated with stroke risk in PROSPER are presented in Table 29 (which lists SNPs with P_all < 0.2, which is the p-value based on the entire study cohort) and Table 30 (where SNPs with P_placebo < 0.2 are listed, which is the p-value based only on the placebo group). SNPs that were significantly associated with SSR in PROSPER are provided in Table 31 (listing SNPs with P int < 0.1) and Table 32 (listing SNPs with P int < 0.2), the results of analyzes of mit Pravastatin-treated patients deliver versus placebo-treated subjects. Tables 37-38 provide the results of further analysis of chromosome 9p21 SNP rs10757274 (hCV26505812) for association with SSR in CARE (Table 37) and PROSPER (Table 38), including both unadjusted and adjusted analyzes (adjusted for factors such as age, gender, smoking). status, hypertension, diabetes, BMI and LDL and HDL levels). Table 37 provides results in CARE, and Table 38 provides results in PROSPER (whether each analysis is unadjusted or adjusted is indicated in the column "adjust" in Table 37 or by the column labels "unadj" and "adj" in Table 38 ).

[0123] Referring to Tables 22-32 and 37-38, those labeled "Genotype" (in Tables 22-28 and 37), "Geno_Placebo" (in Tables 29-30 and 38) and "Geno_Resp" ( in Tables 31-32 and 38) indicate the genotype to which the reported stroke risk or SSR results correspond. All p-values ​​(including P int values) reported in Tables 22-32 and 37-38 are two-tailed p-values ​​(two-tailed p-value cutoff values ​​of 0.1 and 0.2 correspond to a one-tailed p -Value). limits of 0.05 and 0.1 respectively). In Tables 23, 25, 27, 31-32, and 37-38 (which contain results related to SSR), the p-value (labeled "p-value" and with "p_resp" in Tables 31-32 and 38) refers to the significance of statin benefit (i.e. the HR of pravastatin-treated versus placebo-treated carriers of a given genotype), whereas the P int value (which is defined as "pval_intx " in Tables 23, 25, 27 and 37 and denoted as "p_int_resp" in Tables 31-32 and 38) refers to the significance of genotype after treatment interaction, d three genotypes (homozygotes from each of the two alternative alleles plus heterozygotes, as indicated in the column labeled "Genotype" or "Geno") or two groups defined by the carriers and non-carriers of one or the other allele ("Dom" or "Rec", as indicated in the "Mode" column). ). In Tables 29-32 and 38, the columns labeled "LOWER_PLACEBO" and "UPPER_PLACEBO" (Tables 29-30 and 38) and "LOWER_RESP" and "UPPER_RESP" (Tables 31-32 and 38) refer to the lower and upper 95% confidence intervals for the hazard ratios. See Example 6 below for more information regarding Tables 22-32 and 37-38.

[0124] Tables 33-36 provide SNPs that showed a significant association with stroke risk in the Cardiovascular Health Study (CHS). Specifically, SNPs associated with stroke risk in white or black individuals with two-tailed p-values ​​less than 0.1 (corresponding to one-tailed p-values ​​less than 0.05) are shown in Table 33 (white individuals) and Table 34 (black people) listed) and SNPs associated with stroke risk in white or black people with two-tailed p-values ​​between 0.1 and 0.2 (corresponding to one-tailed p-values ​​between 0.05 and 0.1). in Table 35 (white people) and Table 36 (black people). The association was analyzed for three related stroke endpoints, indicated in Tables 33-36 by the following abbreviations in the column labeled "endpt": "stroke" = stroke (all subtypes), "ischemia" = ischemic stroke ( excluding hemorrhagic stroke) and "athero" = atherothrombotic stroke (excludes hemorrhagic stroke and cardioembolic stroke). See example seven below for more information regarding Tables 33-36.

The following abbreviations can be used in the tables: "ProbChiSq" = p-value, "PVALUE_2DF" or "2DF P-VALUE" = p-value with two degrees of freedom, "PVAL_INTX" or "P_INT_RESP" = P int (the significance of the genotype by treatment interaction - see description of Tables 23, 25, 27, 31-32 and 37-38 above), "std.ln(OR)" = the standard deviation of the natural logarithm of the OR, "Hom"=homozygote, "Het" =heterozygote, "cnt"=number, "frq"=frequency, "dom"=dominant, "rec"=recessive, "gen"=genotypic, "add"= additive, "HW" = Hardy-Weinberg, "TIA" = transient ischemic stroke (also known as mini-stroke), "Events" = number of strokes (including TIA) in the study cohort, "DIAB", "DIABADA" or "DIABETES_1"=diabetes, "HTN" or "HYPERTEN_1"= Hypertension, "ENDPT4F1"=endpoint stroke or TIA (official endpoint of the CARES study), "TIMEVAR"=time from baseline to time of event/endpoint, "TIMETO_EP4F1"=time from baseline to time of endpoint ENDPT4F1 (stroke or TIA), "TRF"=traditional risk factors, "BMI"=body mass index, "AGEBL"=age, "GEND01"=gender, "PRESSM" or "CURRSMK"=smoker status, "LDLADJBL" or "BASE_LDL" =Low-density lipoprotein (LDL) cholesterol and "HDL44BL"or "BASE_HDL"=High-density lipoprotein (HDL) cholesterol ("BASE_LDL" and "BASE_HDL" adjustments are based on continuous variables rather than discrete limits ). Two-sided p-values ​​can be referred to interchangeably as two-sided p-values.

In all tables, "HR" or "HRR" refers to the hazard ratio, "OR" refers to the odds ratio, terms like "90% CI" or "95% CI" refer to 90% or 95 % confidence interval (respectively) for the hazard ratio or odds ratio ("CI"/"confidence interval" and "CL"/"confidence limit" may be used interchangeably herein) and terms such as "OR99CI.L" and "OR99CI.U" refer to the lower and upper 99% confidence intervals, respectively, for the odds ratio Hazard ratios ("HR" or "HRR") or odds ratios (OR) greater than one indicate that a particular allele (or combination of alleles such as a haplotype, diplotype, or two-locus diplotype) is a risk allele (which may also be called a susceptibility allele), whereas hazard ratios or odds ratios of less than one indicate that a given allele is a non-risk allele ( this may also be referred to as a protective allele.) For a given risk allele, the other alternative allele at the SNP position (which can be inferred, for example, from the information provided in Tables 1-2) can be considered a non-risk allele. For a given non-risk allele, the other alternative allele at the SNP position can be considered the risk allele.

Thus, with respect to disease risk (e.g., stroke), if the risk estimate (odds ratio or hazard ratio) for a particular allele at a SNP position is greater than one, this indicates that a person with that particular allele is at higher risk for the disease than a person who has the other allele at the SNP position. In contrast, if the risk estimate (odds ratio or hazard ratio) for a particular allele is less than one, this indicates that a person carrying that particular allele has a reduced risk of the disease compared to a person carrying the other allele at the SNP position.

In terms of drug response (e.g. response to a statin), this indicates if the risk estimate (odds ratio or hazard ratio) of those treated with pravastatin compared to those treated with a placebo within a particular genotype is less than one, a person with that particular genotype would benefit from the drug (an odds ratio or hazard ratio equal to one would indicate the drug had no effect). As used herein, the term "benefit" (in relation to preventive or therapeutic drug treatment) is defined as achieving a reduced risk of a disease that the drug is intended to treat or prevent (e.g., stroke) through administration of drug treatment compared to the risk of disease not receiving drug treatment (or receiving placebo instead of drug treatment) for the same genotype. The term "benefit" may be used herein interchangeably with terms such as "respond positively" or "respond positively".

For stroke risk and statin response associations based on samples from the CARE and PROSPER studies described herein, stroke risk is assessed by comparing stroke risk for a given genotype to stroke risk for a reference genotype in either the placebo arm of the study or across the study population of the study, and statin response will be assessed by comparing the risk of stroke in the pravastatin arm of the study to the risk of stroke in the placebo arm of the study for the same genotype.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1a-1b show a comparison of Kaplan-Meier estimates of the cumulative incidence of ischemic stroke among val allele homozygotes of the ABCG2 Val12Met SNP (rs2231137/hCV15854171) and among Met allele carriers in White ( 1a ) and in African Americans (1b) participants from CHS (see example 2).

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS OF THE INVENTION

The present invention provides SNPs associated with risk of stroke and SNPs associated with an individual's responsiveness to therapeutic agents, particularly statins, that can be used to treat (including preventively treat) stroke. The present invention further provides nucleic acid molecules containing SNPs, methods and reagents for detecting the SNPs disclosed herein, uses of these SNPs for the development of detection reagents, and assays or kits using such reagents. The SNPs disclosed herein are useful for diagnosing, prognosticating, screening and assessing predisposition to stroke and related pathologies in humans. The drug response-associated SNPs disclosed herein are particularly useful for predicting, screening and assessing response to statin treatment, particularly the treatment or prevention of stroke using statins, in humans. In addition, such SNPs and their encoded products are useful targets for the development of therapeutic and preventive agents.

[0132] A large number of SNPs were identified by resequencing DNA from 39 individuals and they are given in Tables 1-2 as the "Applera" SNP source. Their allele frequencies observed in each of the Caucasian and African American ethnic groups are given. Additional SNPs included herein were previously identified during shotgun sequencing and human genome assembly, and are identified as the "Celera" SNP source in Tables 1-2. In addition, the information provided in Table 1-2, particularly the allele frequency information obtained from 39 individuals and the identification of the exact position of each SNP within each gene/transcript, allows haplotypes (i.e. groups of SNPs that are inherited together) to be easily inferred. The present invention encompasses SNP haplotypes as well as individual SNPs.

Thus, the present invention provides single SNPs associated with stroke and/or drug response (particularly statin response), as well as combinations of SNPs and haplotypic genetic regions associated with stroke, polymorphic/variant transcript sequences (SEQ ID NOS: 1-80) and genomic sequences (SEQ ID NOS: 260-435), the SNPs, encoded amino acid sequences (SEQ ID NOS: 81-160) and both transcript-based SNP context sequences (SEQ ID NOS: 161-259) and genome-based SNP contain contextual sequences (SEQ ID NOS: 436-1566) (transcript sequences, protein sequences and transcript-based SNP context sequences are provided in Table 1 and the sequence listing; genomic sequences and genome-based SNP context sequences are provided in Table 2 and the sequence listing), methods for detecting these polymorphisms in a test sample, methods of determining a person's risk of having a stroke, methods of determining whether a person is likely to respond to a particular treatment, such as statins (especially used to treat or prevent stroke), methods of screening for useful compounds for Treatment of diseases associated with a gene/protein variant such as stroke, compounds identified by these screening methods, methods of using the disclosed SNPs to select a treatment/prevention strategy or therapeutic agent (eg. e.g., astatine), methods of treating or preventing a variant-associated disease gene/protein, and methods of using the SNPs of the present invention to identify humans.

[0134] Bestimmte Ausführungsformen stellen zum Beispiel Verfahren zur Verwendung von rs3900940/hCV7425232 (MYH15), rs3814843/hCV11476411 (CALM1), rs2200733/hCV16158671 (Chromosom 4q25) und/orrs10757274/hCV16158671 (Chromosom 4q25) und/oderrs10757274/hCV26505812 (Chromosom 1 ) for the determination of prisk in individual.prisk 92 (chromosome 1) and methods for using rs10757274/hCV26505812 (chromosome 9p21) to determine whether an individual will benefit from statin treatment.

Because vascular disorders/diseases share certain similar characteristics that may be due to shared genetic factors involved in their underlying mechanisms, the SNPs identified here as particularly associated with stroke can serve as diagnostic/prognostic markers or therapeutic targets for other vascular disorders such as coronary artery disease (CHD), atherosclerosis, cardiovascular disease, congestive heart failure, congenital heart disease and pathologies and symptoms associated with various heart diseases (e.g. angina pectoris, hypertension), as well as to predict the response to drugs such as statins, which are used to treat cardiovascular diseases.

The present invention also provides methods for selecting or formulating a treatment regimen (e.g., methods for determining whether statin treatment should be administered to a person who has previously had or is at risk of stroke in the future , Methods of selecting a particular statin-based treatment regimen such as dosage and frequency of administration of a statin or a particular form/type of statin such as a particular pharmaceutical formulation or statin compound, methods of administering an alternative non-statin-based treatment to individuals in whom this is predicted unlikely to respond positively to statin treatment, etc.) and methods of determining the likelihood of experiencing toxicity or other undesirable side effects from statin treatment, etc. The present invention also provides methods for selecting subjects to receive a statin or other therapeutic is administered based on the subject's genotype and methods for selecting subjects for a clinical trial of a statin or other therapeutic based on subjects' genotypes (e.g., trial unlikely to test positive for statin treatment speak to).

The present invention provides novel SNPs associated with stroke and related pathologies, as well as SNPs previously known in the art but not previously known to be associated with stroke or response to statin treatment. Accordingly, the present invention provides novel compositions and methods based on the novel SNPs disclosed herein, and also provides novel methods for using the known but previously unassociated SNPs in methods relating to assessing an individual's likelihood of having a first or having recurrent stroke, predicting the severity of a stroke in an individual, or predicting an individual's recovery from stroke, and methods of assessing the likelihood of an individual responding to statin treatment (particularly statin treatment, including stroke prevention). In Tables 1-2, known SNPs are identified based on the public database in which they were observed, which is indicated as one or more of the following SNP types: "dbSNP" = SNP observed in dbSNP, "HGBASE" = in HGBASE observed SNP, and "HGMD" = SNP observed in the Human Gene Mutation Database (HGMD).

[0138] Certain SNP alleles of the present invention may be associated with either an increased risk of stroke (or related pathologies) or a decreased risk of stroke. SNP alleles associated with a reduced risk of stroke may be termed "protective" alleles, and SNP alleles associated with an increased risk of stroke may be termed "susceptibility" alleles, "risk "-alleles or". Risk Factors". While certain SNPs (or their encoded products) can be tested to determine whether an individual possesses an SNP allele that is indicative of an increased risk of stroke (i.e., a susceptibility allele), other SNPs (or their encoded products) be tested to determine whether an individual possesses a SNP allele indicative of a reduced risk of stroke (i.e., a protective allele.) Similarly, certain SNP alleles of the present invention may be associated with either an increased or decreased likelihood of responding to a particular treatment or therapeutic compound (e.g. statins) or an increased or decreased likelihood of experiencing toxic effects from a particular treatment or therapeutic compound The term "modified" may be used herein to mean either of these two possibilities (e.g. an increased or decreased risk/probability).

Those skilled in the art will readily appreciate that nucleic acid molecules can be double-stranded molecules and that reference to a particular site on one strand also refers to the corresponding site on a complementary strand. When defining an SNP position, allele, or nucleotide sequence, reference to anadenine, a thymine (uridine), a cytosine, or a guanine at a particular location on a strand of a nucleic acid molecule also defines thymine (uridine), adenine, guanine , or cytosine at the corresponding position on a complementary strand of the nucleic acid molecule. Thus, each strand can be referred to to refer to a particular SNP position, SNP allele, or nucleotide sequence. Probes and primers can be designed to hybridize to any strand, and the SNP genotyping methods disclosed herein can generally target any strand. Throughout the specification, when identifying a SNP position, reference is generally made to the protein coding strand for convenience only.

[0140] References to variant peptides, polypeptides, or proteins of the present invention include peptides, polypeptides, proteins, or fragments thereof that contain at least one amino acid residue that differs from the corresponding amino acid sequence of the art-known peptide/polypeptide/ protein (the protein known in the art may be referred to interchangeably as "wild-type", "reference" or "normal" protein). Such aberrant peptides/polypeptides/proteins may result from a codon change caused by a non-synonymous nucleotide substitution at a protein-coding SNP position (i.e., a missense mutation) disclosed by the present invention. Variants of peptides/polypeptides/proteins of the present invention may also result from a nonsense mutation, i. H. a SNP that creates a premature stop codon, a SNP that creates a read-through mutation by deletion of a stop codon, or due to any SNP disclosed by the present invention otherwise alters the structure, function/activity or expression of a protein , such as B. a SNP in a regulatory region (z. B. a promoter or enhancer) or a SNP that leads to alternative or defective splicing such. B. an SNP in an intron or an SNP at an exon/intron boundary. As used herein, the terms "polypeptide", "peptide" and "protein" are used interchangeably.

[0141] As used herein, an "allele" can refer to a nucleotide at a SNP position (where there are at least two alternative nucleotides in the population at the SNP position, according to the inherent definition of a SNP) or can refer to refer to an amino acid residue encoded by the codon containing the SNP position (where the alternative nucleotides present in the population at the SNP position form alternative codons encoding different amino acid residues). An "allele" may also be referred to herein as a "variant". Also, an amino acid residue encoded by a codon containing a particular SNP may simply be referred to as being encoded by the SNP.

A phrase such as "as represented by," "as shown by," "as symbolized by," or "as denoted by" may be used herein to refer to an SNP within a sequence (e.g., a polynucleotide context sequence surrounding an SNP). ), as in the context of "a polymorphism as represented by position 101 of SEQ ID NO: X or its complement". Typically, the sequence surrounding an SNP can be quoted when referencing an SNP, however, the sequence is not intended as a structural limitation beyond the specific SNP position itself. Rather, the sequence is given simply as a way of referring to the SNP (in this example "SEQ ID NO:X or its complement" is given to refer to the SNP located at position 101 of SEQ ID NO:X, but SEQ ID NO:X or its complement is not intended as a structural limitation beyond the specific SNP position itself). A SNP is a variation at a single nucleotide position, and therefore it is common to refer to a contextual sequence (e.g. SEQ ID NO: X in this example) surrounding a particular SNP position to uniquely identify the SNP identify and refer to. Alternatively, an SNP may be referenced by a unique identification number, such as an "rs" public identification number or an "hCV" internal identification number, as provided herein for each SNP (e.g., in Tables 1-2).

[0143] Referring to an individual's risk for a disease or predicted responsiveness to drugs (e.g., based on the presence or absence of one or more SNPs disclosed herein in the individual's nucleic acid), terms such as "assign" or " Determine” are used here to characterize the individual risk for the disease.

[0144] As used herein, the term "benefit" (in relation to preventive or therapeutic drug treatment) is defined as achieving a reduced risk of a disease that the drug is intended to treat or prevent (e.g., stroke) by drug treatment is given (e.g. a statin) compared to the risk for the disease not receiving drug treatment (or receiving a placebo instead of drug treatment) for the same genotype. The term “benefit” may be used interchangeably with terms such as “respond positively” or “react positively” herein.

As used herein, the terms "drug" and "therapeutic" are used interchangeably and can include, but are not limited to, small molecule compounds, biologics (e.g., antibodies, proteins, protein fragments, fusion proteins, glycoproteins, etc.) , nucleic acid agents (e.g. antisense, RNAi/siRNA and microRNA molecules, etc.), vaccines, etc. that can be used for therapeutic and/or preventive treatment of a disease (e.g. stroke).

The statin response-associated SNPs disclosed herein are useful with respect to any statin (HMG-CoA reductase inhibitor), including but not limited to pravastatin (Pravachol ® ), atorvastatin (Lipitor ® ), storvastatin, rosuvastatin (Crestor®), fluvastatin (Lescol®), lovastatin (Mevacor®), and simvastatin (Zocor®), as well as combination therapies that include a statin, such as assimvastatin + ezetimibe (Vytorin®), lovastatin + extended-release niacin (Advicor ® ), and atorvastatin + amlodipine besylate (Caduet ® ).

In addition, the drug response-associated SNPs disclosed herein can also be used to predict an individual's response to drugs other than statins used to treat or prevent stroke, and these SNPs can also be used to predict an individual's response on statins used for the treatment or prevention of diseases other than stroke, particularly cancer. For example, the use of statins in the treatment of cancer is discussed in: Hindler et al., "The role of statins in cancer therapy", Oncologist. 2006 March; 11(3):306-15; Demierre et al., "Statins and cancer prevention", Nat Rev Cancer. 2005 December; 5(12):930-42; Stamm et al., "The role of statins in Cancer Prevention and treatment", Oncology. 2005 May; 19(6):739-50; and Sleijfer et al., "The potential of statins as part of anti-cancer treatment", Eur JCancer. 2005 March; 41(4): 516-22, each of which is incorporated herein by reference in its entirety.

The drug response related to statins may be referred to herein as the "stroke statin response" or "SSR".

The various methods described herein, such as correlating the presence or absence of a polymorphism with an altered (eg, increased or decreased) risk (or no altered risk) of stroke (and/or correlating the presence or absence of a polymorphism with the predicted response of an individual to a drug such as astatine) may be performed by automated methods such as the use of a computer (or other apparatus/device such as biomedical devices, laboratory instruments, or other apparatus/devices having a computer processor) programmed to perform each of the perform the procedures described herein. For example, computer software (which may alternatively be referred to herein as a computer program) can perform the step of correlating the presence or absence of apolymorphism in an individual with an altered (e.g., increased or decreased) risk (or no altered risk) of stroke the individual. Computer software may also perform the step of correlating the presence or absence of a polymorphism in an individual with the individual's predicted response to a therapeutic agent (e.g., a statin) or other treatment. Accordingly, certain embodiments of the invention provide a computer (or other device/device) programmed to perform any of the methods described herein.

Reports, programmed computers, business methods and systems

The results of a test (e.g., a person's risk of stroke or a person's predicted drug responsiveness, such as statin response, based on testing one or more SNPs disclosed herein and/or one or more alleles/genotypes of a person one or more SNPs disclosed herein, etc.) and/or any other information relating to a test may be referred to herein as a "report". A specific report may optionally be generated as part of a testing process (which may be referred to interchangeably herein as "reporting" or "providing" a report, "generating" a report, or "generating" a report).

[0152] Examples of tangible reports may include reports in paper form (such as computer-generated printouts of test results) or equivalent formats, and reports stored on a computer-readable medium (such as a CD, USB flash drive, or other removable storage device). , include but are not limited to , computer hard drive or computer network server, etc.). Reports, particularly those stored on a computer-readable medium, may form part of a database, optionally accessible via the Internet (e.g. features that restrict access to the report, e.g. to only show the patient and the allow the patient's physicians to view the report while preventing other unauthorized persons from viewing the report). In addition to or as an alternative to generating a tangible report, reports may also be displayed on a computer screen (or other electronic device or instrument display).

For example, a report may include an individual's risk of stroke, or may include only the allele(s)/genotypes that an individual carries at one or more SNPs disclosed herein, optionally accompanied by information regarding the significance of the allele's presence (s)/genotype at the SNP (e.g., a report on a computer-readable medium such as a network server may contain hyperlinks to one or more journal publications or websites describing the medical/biological implications, such as increased or reduced disease risk, e.g. persons with a certain allele/genotype on the SNP). Thus, for example, the report may include disease risk or other medical/biological significance (e.g. drug response, etc.) and optionally also allele/genotype information, or the report may include allele/genotype information only without including disease risk or other medical/ Biological significance (so that a person viewing the report can use the allele/genotype information to self-determine associated disease risk or other medical/biological significance from a source outside of the report, such as a doctor, a publication, a website, etc.) that can optionally be linked to the report, e.g. e.g. through a hyperlink).

A report may also be "transmitted" or "communicated" (these terms may be used interchangeably herein), for example, to the person tested, a physician (e.g., a physician, a nurse, a clinical laboratory practitioner, a genetic Advisor). etc.), a healthcare organization, clinical laboratory, and/or other party or requester who intends to view or possess the report. The act of “transmitting” or “notifying” a report may be done by any means known in the art based on the format of the report. Additionally, “transmitting” or “communicating” a report may include delivering (“pushing”) a report and/or retrieving (“pulling”) a report. For example, reports may be submitted/communicated in a variety of ways, including physical transmission between parties (e.g., in the case of paper reports), e.g. B. by physical transmission from one party to another, or by electronic transmission or signal form (e.g. mail or via the Internet, by facsimile and/or by any wired or wireless communication method known in the art), such as by retrieval from a database stored on a computer network server, etc.

In certain exemplary embodiments, the invention provides computers (or other devices/devices such as biomedical devices or laboratory instruments) programmed to perform the methods described herein. For example, in certain embodiments, the invention provides a computer programmed to receive (i.e., as input) the identity (e.g., the allele(s) or genotype at a SNP) of one or more SNPs disclosed herein. and provides the disease (i.e., as an output). Risk (eg, an individual's risk of stroke) or other outcome (eg, disease diagnosis or prognosis, drug response, etc.) based on the identity of the SNP(s). Such output (e.g., communication of disease risk, disease diagnosis or prognosis, drug responsiveness, etc.) may be in the form of a report on a computer-readable medium, printed in paper form, and/or displayed on a computer screen or other display.

[0156] In various exemplary embodiments, the invention further provides methods of conducting transactions (with respect to methods of conducting transactions, the terms “individual” and “customer” are used interchangeably herein). For example, example methods of conducting business may include testing one or more SNPs disclosed herein and providing a report that includes, for example, a customer's risk of stroke (based on which allele(s)/genotype in the tested SNP(s) is present) and/or comprising the allele(s)/genotype at the tested SNP(s), optionally linked to information (e.g. journal publications, websites, etc.). related to disease risk or other biological/medical significance, such as a hyperlink (e.g., the report may be made available on a computer network server or other computer-readable medium accessible via the Internet, and the report may be included in a secure database that allows the customer access to their report while preventing other unauthorized persons from viewing the report ) and, optionally, submitting the report. Customers (or another party associated with the customer, such as the customer's doctor) can request/order the test online via the Internet (or by telephone, mail order, in a point of sale/store, etc.). (e.g. buy). ), and a kit may, for example, be sent to the customer (or another party on behalf of the customer, such as the customer's doctor) to collect a biological sample from the customer (e.g., buccal swab to collect cheek cells), and the customer (or a party that collects the customer's biological sample) may submit its biological samples for testing (e.g., to a laboratory or a party associated with the laboratory, such as a party that receives the customer's samples on behalf of the laboratory). , a party for which the laboratory is under the control (e.g., the laboratory performs the assays at the party's request or under a contract with the party), and/or a party that receives at least a portion of the customer's payment receives the test). The report (e.g. results of the assay including e.g. the customer's disease risk and/or alleles/genotypes in the SNPs tested) may be provided to the customer by, for example, the laboratory testing the SNP (s) or a party related to the laboratory (e.g., a party that receives at least a portion of the customer's payment for the assay, or a party that requests the laboratory to perform the assays, or that contracts with the laboratory for the assays to be performed) or a physician or other medical practitioner associated with the laboratory or a party associated with the laboratory (e.g. consultant, hospital, etc.) who optionally forwards the report to the customer. In further embodiments, the customer may be a doctor or other general practitioner, or a hospital, laboratory, health insurance company, or other medical organization that requests/orders (e.g., purchases) tests to provide other people (e.g., their patients or clients) are screened for one or more SNPs disclosed herein and optionally receive a report of the screening results.

In certain example business methods, kits for collecting a biological sample from a customer (e.g., a cheek swab for collecting cheek cells) are made available (e.g., for sale), such as at a point of sale (e.g., a drugstore, a pharmacy). , general store, or any other desirable point of sale), online via the Internet, by mail order, etc., whereby customers receive (e.g., purchase) the kits, collect and submit (e.g., mail/deliver) their own biological samples can. their samples to a laboratory that will test the samples for one or more SNPs disclosed herein (e.g., to determine the customer's stroke risk) and optionally provide the customer with a report (e.g., of the customer's disease risk based on their SNP genotype) or provides the results of the assay to another party (e.g. a doctor, genetic counselor, hospital, etc.) who optionally provides a report to the customer (e.g. about the customer's disease risk based on its SNP genotype).

Certain other embodiments of the invention provide a system for determining a person's risk of stroke or whether a person will benefit from statin treatment (or other therapy) in reducing risk of stroke. Certain exemplary systems include an integrated "loop" in which a person (or their doctor) requests a determination of that person's stroke risk (or drug response, etc.), that determination is made by testing a sample from the person, and then the results are these determination are returned to the requestor. For example, in certain systems, a sample (e.g., blood or cheek cells) is obtained from a person for testing (the sample may be obtained from the person or, for example, from a doctor), the sample is sent to a laboratory (or other location) sent facility) for testing (eg, determining the genotype of one or more SNPs disclosed herein) and then the test results are sent to the patient (which can optionally be done by first sending the results to an intermediary, such as a physician , which then provides or otherwise communicates the results to the individual), thereby forming an integrated loopback system for determining an individual's risk of stroke (or drug response, etc.). The parts of the system in which results are transmitted (e.g., between a testing facility, a physician, and/or the individual) may be communicated by electronic or signal transmission (e.g., by computer, such as email or e-mail). -mail) via the Internet, by making the results available on a website or computer network server, which may optionally be a secure database, by telephone or facsimile, or by other wired or wireless transmission methods known in the art).

Isolated nucleic acid molecules and SNP detection reagents and kits

[0159] Tables 1 and 2 provide a variety of information about each SNP of the present invention associated with stroke, including transcript sequences (SEQ ID NOS: 1-80), genomic sequences (SEQ ID NOS: 260-435) and protein sequences (SEQ IDNOS: 81-160) of the encoded gene products (having the SNPs indicated by IUB codes in the nucleic acid sequences). In addition, Tables 1 and 2 contain SNP context sequences generally comprising 100 nucleotides upstream (5') plus 100 nucleotides downstream (3') of each SNP position (SEQ ID NO: 161-259 correspond to the transcript sequences disclosed in Table 1 based SNP context sequences , and SEQ ID NOS: 436-1566 correspond to genome-based context sequences disclosed in Table 2), the alternative nucleotides (alleles) at each SNP position, and optionally additional information about the variant, such as SNP type (encoding , missense, splice site, UTR, etc.), human populations in which the SNP was observed, observed allele frequencies, information about the encoded protein, etc.

Isolated nucleic acid molecules

The present invention provides isolated nucleic acid molecules containing one or more SNPs disclosed in Table 1 and/or Table 2. Preferred isolated nucleic acid molecules contain one or more SNPs identified as proprietary to Applera or Celera. Isolated nucleic acid molecules containing one or more SNPs disclosed in at least one of Tables 1-2 may be referred to interchangeably as "SNP-containing nucleic acid molecules" throughout this text. Isolated nucleic acid molecules may optionally encode a full-length variant protein or fragment thereof. The isolated nucleic acid molecules of the present invention also include probes and primers (described in more detail below in the section entitled "SNP Detection Reagents") that can be used to assay the disclosed SNPs, and isolated full-length genes, transcripts, cDNA Molecules and fragments thereof that can be used for purposes such as expression of an encoded protein.

[0162] As used herein, an "isolated nucleic acid molecule" is generally one that contains a SNP of the present invention or one that hybridizes to such a molecule, such as a nucleic acid having a complementary sequence, and most other nucleic acids present therein separate is natural source of nucleic acid molecule. Furthermore, an "isolated" nucleic acid molecule, such as a cDNA molecule, containing a SNP of the present invention may be essentially free of other cell material or culture medium when produced by recombinant techniques or chemical precursors or other chemicals when chemically prepared be synthesized. A nucleic acid molecule can be fused to other coding or regulatory sequences and still be considered "isolated". Nucleic acid molecules present in non-human transgenic animals that are not naturally occurring in the animal are also considered "isolated". For example, recombinant DNA molecules contained within a vector are considered "isolated". Additional examples of "isolated" DNA molecules include recombinant DNA molecules maintained in heterologous host cells and purified (partially or substantially) DNA molecules in solution. Isolated RNA molecules include in vivo or in vitro RNA transcripts of the isolated SNP-containing DNA molecules of the present invention. Isolated nucleic acid molecules according to the present invention further include such synthetically produced molecules.

In general, an isolated SNP-containing nucleic acid molecule comprises one or more SNP positions disclosed by the present invention with flanking nucleotide sequences on either side of the SNP positions. A flanking sequence may include nucleotide residues naturally associated with the SNP site and/or heterologous nucleotide sequences. Preferably, the flanking sequence is up to about 500, 300, 100, 60, 50, 30, 25, 20, 15, 10, 8, or 4 nucleotides (or any other length in between) either side of a SNP position or as long B as the full-length gene or the entire protein-coding sequence (or any part thereof, such as an exon), particularly when the SNP-containing nucleic acid molecule is to be used to produce a protein or protein fragment.

For example, for full length genes and entire protein coding sequences, a SNP flanking sequence can be up to about 5 KB, 4 KB, 3 KB, 2 KB, 1 KB on either side of the SNP. Furthermore, in such cases the isolated nucleic acid molecule comprises exonic sequences (including protein-coding and/or non-coding exonic sequences), but may also comprise intronic sequences. Thus, each protein coding sequence can be either contiguous or separated by introns. The important point is that the nucleic acid is isolated from distant and unimportant flanking sequences and is of appropriate length to allow the specific manipulations or uses described herein such as recombinant protein expression, preparation of probes and primers to probe SNP position and other uses specific for the SNP-containing nucleic acid sequences.

An isolated SNP-containing nucleic acid molecule can comprise, for example, a full-length gene or transcript, such as a gene isolated from genomic DNA (e.g., by cloning or PCR amplification), a cDNA molecule, or an mRNA transcript molecule . Polymorphic transcript sequences are provided in Table 1 and the Sequence Listing (SEQ ID NOS: 1-80), and polymorphic genomic sequences are provided in Table 2 and the Sequence Listing (SEQ ID NOS: 260-435). In addition, fragments of such genes and full-length transcripts containing one or more SNPs disclosed herein are also encompassed by the present invention, and such fragments can be used, for example, to express any part of a protein, such as a particular functional domain or an antigenic epitope.

Thus, the present invention also includes fragments of the nucleic acid sequences provided in Tables 1-2 (transcript sequences are provided in Table 1 as SEQ ID NOS: 1-80, genomic sequences are provided in Table 2 as SEQ ID NOS: 260-435 , transcript-based SNP context sequences are provided in Table 1 as SEQ ID NO: 161-259, and genome-based SNP context sequences are provided in Table 2 as SEQ ID NO: 436-1566) and their complements. A fragment typically comprises a contiguous nucleotide sequence of at least about 8 or more nucleotides, more preferably at least about 12 or more nucleotides, and even more preferably at least about 16 or more nucleotides. Furthermore, a fragment could be at least about 18, 20, 22, 25, 30, 40, 50, 60, 80, 100, 150, 200, 250, or 500 (or any other number in between) nucleotides in length. The length of the fragment is based on its intended use. For example, the fragment may encode epitope-bearing regions of a variant peptide or regions of a variant peptide that differ from the normal/wild-type protein, or may be useful as a polynucleotide probe or primer. Such fragments can be isolated using the nucleotide sequences provided in Table 1 and/or Table 2 for the synthesis of a polynucleotide probe. A labeled probe can then be used, for example, to screen an acDNA library, a genomic DNA library, or mRNA to isolate nucleic acid corresponding to the coding region. Furthermore, primers can be used in amplification reactions, such as for testing one or more SNP sites or for cloning specific regions of a gene.

An isolated nucleic acid molecule of the present invention further comprises an SNP-containing polynucleotide that is the product of any of a variety of nucleic acid amplification methods used to increase copy numbers of a polynucleotide of interest in a nucleic acid sample. Such amplification methods are well known in the art, and include polymerase chain reaction (PCR) (U.S. Pat. Nos. 4,683,195; and 4,683,202; PCR Technology: Principles and Applications for DNA Amplification, ed. H. A. Erlich, Freeman Press, but are not limited to that). NY, NY, 1992), ligase chain reaction (LCR) (Wu and Wallace, Genomics 4:560, 1989; Landegren et al., Science 241:1077, 1988), strand displacement amplification (SDA) (U.S. Pat. Nos. 5,270,184; and 5,422,252 ), transcription-mediated amplification (TMA) (U.S. Pat. No. 5,399,491), linked linear amplification (LLA) (U.S. Pat. No. 6,027,923), and the like, and isothermal amplification methods such as amplification (NASBA) and self-sustaining sequence replication (Guatelli et al ., Proc Natl Acad Sci USA 87:1874, 1990). Based on such methodologies, one skilled in the art can readily design primers in any suitable regions 5' and 3' to a SNP disclosed herein. Such primers can be used to amplify DNA of any length long enough to contain the SNP of interest in its sequence.

[0168] As used herein, an “amplified polynucleotide” of the invention is an SNP-containing nucleic acid molecule whose amount has been increased at least two-fold by any in vitro nucleic acid amplification method compared to its starting amount in a test sample. In other preferred embodiments, an amplified polynucleotide is the result of at least a ten-fold, fifty-fold, hundred-fold, thousand-fold, or ten-thousand-fold increase over its starting level in a test sample. In a typical PCR amplification, a polynucleotide of interest is often amplified at least fifty thousand-fold in amount over the unamplified genomic DNA, but the precise amount of amplification required for an assay typically depends on the sensitivity of the detection method subsequently used.

In general, an amplified polynucleotide is at least about 16 nucleotides in length. More typically, an amplified polynucleotide is at least about 20 nucleotides in length. In a preferred embodiment of the invention, an amplified polynucleotide is at least about 30 nucleotides in length. In a more preferred embodiment of the invention, an amplified polynucleotide is at least about 32, 40, 45, 50, or 60 nucleotides in length. In yet another preferred embodiment of the invention, an amplified polynucleotide is at least about 100, 200, 300, 400, or 500 nucleotides in length. While the total length of an amplified polynucleotide of the invention can be as long as an exon, an intron, or the entire gene in which the SNP of interest resides, an amplified product is typically up to about 1,000 nucleotides in length (although certain amplification methods produce amplified products can generate larger than 1000 nucleotides). 1000 nucleotides long). More preferably, an amplified polynucleotide is no longer than about 600-700 nucleotides. It is understood that regardless of the length of an amplified polynucleotide, a SNP of interest can be located anywhere along its sequence.

[0170] In a specific embodiment of the invention, the amplified product is at least about 201 nucleotides in length, comprises one of the transcript-based context sequences or the genome-based context sequences shown in Tables 1-2. Such a product may have additional sequences at its 5' end or 3' end or both. In another embodiment, the amplified product is approximately 101 nucleotides in length and contains a SNP disclosed herein. Preferably, the SNP is located in the middle of the amplified product (e.g. at position 101 in an amplified product 201 nucleotides in length or at position 51 in an amplified product 101 nucleotides in length) or within 1, 2 , 3, 4, 5, 6, 7, 8, 9, 10, 12, 15, or 20 nucleotides from the middle of the amplified product (however, as indicated above, the SNP of interest can be located anywhere along the length of the amplified product) .

The present invention provides isolated nucleic acid molecules comprising, consisting of, or consisting essentially of one or more polynucleotide sequences containing one or more SNPs disclosed herein, complements thereof, and SNP-containing fragments thereof.

Accordingly, the present invention provides nucleic acid molecules consisting of any of the nucleotide sequences shown in Table 1 and/or Table 2 (transcript sequences are provided in Table 1 as SEQ ID NOS: 1-80, genomic sequences are provided in Table 2 as SEQ ID NO: 260-435, transcript-based SNP context sequences are provided in Table 1 as SEQ ID NO: 161-259, and genome-based SNP context sequences are provided in Table 2 as SEQ ID NO: 436-1566) or any nucleic acid molecule containing any of the protein variants provided in Table 1 (SEQ ID NOS: 81-160). A nucleic acid molecule consists of a nucleotide sequence if the nucleotide sequence is the complete nucleotide sequence of the nucleic acid molecule.

The present invention further provides nucleic acid molecules consisting essentially of any of the nucleotide sequences shown in Table 1 and/or Table 2 (transcript sequences are provided in Table 1 as SEQ ID NOS: 1-80, genomic sequences are provided in Table 2 as provided SEQ ID NO: 260-435, transcript-based SNP context sequences are provided in Table 1 as SEQ ID NO: 161-259, and genome-based SNP context sequences are provided in Table 2 as SEQ ID NO: 436-1566) or each any nucleic acid molecule encoding any of the protein variants provided in Table 1 (SEQ ID NOS: 81-160). A nucleic acid molecule consists essentially of a nucleotide sequence if such a nucleotide sequence is present with only a few additional nucleotide residues in the final nucleic acid molecule.

The present invention further provides nucleic acid molecules comprising any of the nucleotide sequences shown in Table 1 and/or Table 2 or a SNP-containing fragment thereof (transcript sequences are provided in Table 1 as SEQ ID NO: 1-80, genomic sequences are provided in Table 2 as SEQ ID NO: 260-435, transcript-based SNP context sequences are provided in Table 1 as SEQ ID NO: 161-259, and genome-based SNP context sequences are provided in Table 2 as SEQ ID NO: 436- 1566), or any nucleic acid molecule encoding any of the protein variants provided in Table 1 (SEQ ID NOS: 81-160). A nucleic acid molecule comprises a nucleotide sequence when the nucleotide sequence is at least part of the final nucleotide sequence of the nucleic acid molecule. Thus, the nucleic acid molecule may be the nucleotide sequence only, or may have additional nucleotide residues, such as residues naturally associated therewith, or heterologous nucleotide sequences. Such a nucleic acid molecule may have one to a few additional nucleotides or may comprise many more additional nucleotides. A brief description of how various types of these nucleic acid molecules can be readily prepared and isolated is provided below, and such techniques are well known to those of ordinary skill in the art (Sambrook and Russell, 2000, Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Press, New York).

The isolated nucleic acid molecules may encode mature proteins plus additional amino- or carboxy-terminal amino acids, or both, or amino acids within the mature peptide (when the mature form has more than one peptide chain, for example). Such sequences may play a role in the processing of a protein from precursor to mature form, facilitate protein transport, lengthen or shorten protein half-life, or facilitate manipulation of a protein for assay or production. As is generally the case in situ, the additional amino acids can be processed away from the mature protein by cellular enzymes.

Thus, the isolated nucleic acid molecules include, but are not limited to, nucleic acid molecules having a sequence encoding only a peptide, a sequence encoding a mature peptide, and additional coding sequences such as a leader or secretory sequence (e.g. B. apre-pro or pro-protein sequence), a sequence encoding a mature peptide with or without additional coding sequences, plus additional non-coding sequences, for example introns and 5' and 3' non-coding sequences such as transcribed but untranslated sequences involved in, for example, transcription, mRNA processing (including splicing and polyadenylation signals), ribosome binding, and/or stability of mRNA. In addition, the nucleic acid molecules can be fused to heterologous marker sequences, for example encoding a peptide that facilitates purification.

Isolated nucleic acid molecules may be in the form of RNA, such as mRNA, or in the form of DNA, including cDNA and genomic DNA, obtained, for example, by molecular cloning, or by chemical synthetic methods, or by a combination thereof (Sambrook and Russell, 2000, Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Press, NY). In addition, isolated nucleic acid molecules, particularly SNP detection reagents such as probes and primers, may also be partially or fully in the form of one or more types of nucleic acid analogues such as peptide nucleic acid (PNA) (US Patent Nos. 5,539,082; 5,527,675). 5,623,049; 5,714,331). The nucleic acid, in particular DNA, can be double-stranded or single-stranded. Single-stranded nucleic acid can be the coding strand (sense strand) or the complementary non-coding strand (antisense strand). For example, DNA, RNA, or PNA segments can be assembled from fragments of the human genome (in the case of DNA or RNA) or single nucleotides, short oligonucleotide linkers, or from a series of oligonucleotides to provide a synthetic nucleic acid molecule. Nucleic acid molecules can be easily synthesized using the sequences provided herein as a reference; Oligonucleotide and PNA oligomer synthesis techniques are well known in the art (see, e.g., Corey, "Peptide Nucleic Acids: Expanding the Scope of Nucleic Acid Recognition", Trends Biotechnol. 1997 June; 15(6):224-9, and Hyrupet al., "Peptide nucleic acids (PNA): synthesis, properties and potential applications", Bioorg Med Chem 1996 Jan;4(1):5-23). bead surface or other solid support) can be readily performed using commercially available nucleic acid synthesizers such as the Applied Biosystems (FosterCity, CA) 3900 High-Throughput DNA Synthesizer or the Expedite 8909 Nucleic Acid Synthesis System and the sequence information provided herein.

The present invention encompasses nucleic acid analogs containing modified, synthetic or non-naturally occurring nucleotides or structural elements, or other alternative/modified nucleic acid chemistries known in the art. Such nucleic acid analogs are useful, for example, as detection reagents (eg, primers/probes) for detecting one or more SNPs identified in Table 1 and/or Table 2. In addition, kits/systems (such as beads, arrays, etc.) comprising these analogs are also encompassed by the present invention. For example, PNA oligomers based on the polymorphic sequences of the present invention are specifically contemplated. PNA oligomers are DNA analogs in which the phosphate backbone is replaced by a peptide-like backbone (Lagriffoul et al., Bioorganic & Medicinal Chemistry Letters, 4:1081-1082 (1994), Petersen et al., Bioorganic & Medicinal Chemistry Letters, 6:793-796 (1996), Kumar et al., Organic Letters 3(9):1269-1272 (2001), WO96/04000). PNA hybridizes to complementary RNA or DNA with higher affinity and specificity than conventional oligonucleotides and oligonucleotide analogs. The properties of PNA enable novel molecular biological and biochemical applications that cannot be reached with conventional oligonucleotides and peptides.

Additional examples of nucleic acid modifications that improve the binding properties and/or stability of a nucleic acid include the use of base analogs such as inosine, intercalators (U.S. 5,801,115). Thus, references herein to nucleic acid molecules include SNP-containing nucleic acid molecules, SNP detection reagents (e.g., probes and primers), oligonucleotides/polynucleotides, PNA oligomers, and other nucleic acid analogs. Other examples of nucleic acid analogs and alternative/modified nucleic acid chemistries known in the art are described in Current Protocols in Nucleic Acid Chemistry, John Wiley & Sons, N.Y. (2002).

The present invention further provides nucleic acid molecules encoding fragments of the polypeptide variants disclosed herein, as well as nucleic acid molecules encoding apparent variants of such polypeptide variants. Such nucleic acid molecules can be naturally occurring, such as paralogues (other locus) and orthologues (other organism), or can be constructed by recombinant DNA methods or by chemical synthesis. Non-naturally occurring variants can be produced by mutagenesis techniques, including those applied to nucleic acid molecules, cells, or organisms. Accordingly, the variants may contain nucleotide substitutions, deletions, inversions and insertions (in addition to the SNPs disclosed in Tables 1-2). Variation can occur in either or both of the coding and non-coding regions. The variations can result in conservative and/or non-conservative amino acid substitutions.

[0181] Additional variants of the nucleic acid molecules disclosed in Tables 1-2, such as naturally occurring allelic variants (as well as orthologues and paralogues) and synthetic variants produced by mutagenesis techniques, can be identified and/or using those well known in the art procedures are produced. Such further variants may comprise a nucleotide sequence that shares at least 70-80%, 80-85%, 85-90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99% sequence identity with a nucleic acid sequence disclosed in Table 1 and/or Table 2 (or a fragment thereof) and comprising a novel SNP allele disclosed in Table 1 and/or Table 2. In addition, variants may comprise a nucleotide sequence encoding a polypeptide at least 70-80%, 80-85%, 85-90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98 Shares % or 99% sequence identity with a polypeptide sequence disclosed in Table 1 (or a fragment thereof) and comprising a novel SNPallele disclosed in Table 1 and/or Table 2. Thus, one aspect of the present invention that is specifically contemplated is isolated nucleic acid molecules that exhibit a certain degree of sequence variation compared to the sequences shown in Tables 1-2, but that contain a novel SNP allele disclosed herein. In other words, as long as an isolated nucleic acid molecule contains a new SNP allele disclosed herein, other parts of the nucleic acid molecule flanking the new SNP allele may, to some extent, differ from the specific transcript, genome shown in Tables 1-2 - and context sequences differ. and may encode a polypeptide that differs to some degree from the specific polypeptide sequences shown in Table 1.

To determine the percent identity of two amino acid sequences or two nucleotide sequences of two molecules that share sequence homology, the sequences are aligned for optimal comparison purposes (e.g., gaps in one or both of a first and second amino acid or nucleic acid acidic sequence can be introduced for optimal alignment and non-homologous sequences can be neglected for comparison purposes). In a preferred embodiment, at least 30%, 40%, 50%, 60%, 70%, 80%, or 90% or more of the length of a reference sequence is aligned for comparison purposes. The amino acid residues or nucleotides at corresponding amino acid positions or nucleotide positions are then compared. If a position in the first sequence is occupied by the same amino acid residue or nucleotide as the corresponding position in the second sequence, then the molecules at that position are identical (as used herein, amino acid or nucleic acid "identity" is equivalent to amino acid or nucleic acid -"homology"). The percent identity between the two sequences is a function of the number of identical positions shared by the sequences, taking into account the number of gaps and the length of each gap that must be introduced for optimal alignment of the two sequences.

Comparing sequences and determining percent identity between two sequences can be accomplished using a mathematical algorithm. (Computational Molecular Biology, Lesk, A.M., ed., Oxford University Press, New York, 1988; Biocomputing: Informatics and Genome Projects, Smith, D.W., ed., Academic Press, New York, 1993; Computer Analysis of Sequence Data, Part 1, Griffin, A.M., and Griffin, H.G., eds., Humana Press, New Jersey, 1994, Sequence Analysis in Molecular Biology, von Heinje, G., Academic Press, 1987, and Sequence Analysis Primer, Gribskov, M. and Devereux J., ed., M. Stockton Press, New York, 1991). In a preferred embodiment, the percent identity between two amino acid sequences is determined using the Needleman and Wunsch (J. Mol. Biol. (48): 444-453 (1970)) algorithm incorporated into the GAP program in the GCG software package became. using either a Blossom 62 matrix or a PAM250 matrix and a gap weight of 16, 14, 12, 10, 8, 6 or 4 and a length weight of 1, 2, 3, 4, 5 or 6.

In yet another preferred embodiment, the percent identity between two nucleotide sequences is determined using the GAP program in the GCG software package (Devereux, J., et al., Nucleic Acids Res. 12(1):387 (1984)). using determines an NWSgapdna.CMP matrix and an agap weight of 40, 50, 60, 70 or 80 and a length weight of 1, 2, 3, 4, 5 or 6. In another embodiment, the percent identity between two amino acids - or nucleotide sequences is calculated using the algorithm of E. Myers and W. Miller (CABIOS, 4:11-17 (1989)) incorporated into the ALIGN program (version 2.0), using a PAM120 weight residue table, a gap length penalty of 12 and determines a gap penalty of 4.

The nucleotide and amino acid sequences of the present invention can also be used as a "query sequence" to conduct a search of sequence databases to identify, for example, other family members or related sequences. Such searches can be performed using the NBLAST and XBLAST (version 2.0) programs by Altschul et al. be performed. (J. Mol. Biol. 215:403-10 (1990)). BLAST nucleotide searches can be performed with the NBLAST program, score = 100, wordlength = 12, to obtain nucleotide sequences homologous to the nucleic acid molecules of the invention. BLAST protein searches can be performed with the XBLAST program, score=50, wordlength=3 to obtain amino acid sequences homologous to the proteins of the invention. To obtain gapped alignments for comparison purposes, Gapped BLAST can be used as described in Altschul et al. (Nucleic Acids Res. 25(17):3389-3402 (1997)). When using BLAST and gap BLAST programs, the default parameters of the respective programs (e.g., XBLAST and NBLAST) can be used. In addition to BLAST, examples of other search and sequence comparison programs used in the art include FASTA (Pearson, Methods Mol. Biol. 25, 365-389 (1994)) and KERR (Dufresne et al., Nat Biotechnol 2002 December;20( 12):1269-71). For more information on bioinformatics techniques, see Current Protocols in Bioinformatics, John Wiley & Sons, Inc., N.Y.

The present invention further provides non-coding fragments of the nucleic acid molecules disclosed in Table 1 and/or Table 2. Preferred non-coding fragments include, but are not limited to, promoter sequences, enhancer sequences, intron sequences, 5'. untranslated regions (UTRs), 3' untranslated regions, gene modulating sequences and gene termination sequences. Such fragments are useful, for example, in controlling heterologous gene expression and in developing screens to identify gene modulating agents.

SNP Detection Reagents

In a specific aspect of the present invention, the SNPs disclosed in Table 1 and/or Table 2 and their associated transcript sequences (provided in Table 1 as SEQ ID NOS: 1-80), genomic sequences (provided in Table 2 as SEQ ID NOS: 260-435) and contextual sequences (transcript-based contextual sequences are provided in Table 1 as SEQ ID NOS: 161-259; genome-based contextual sequences are provided in Table 2 as SEQ ID NOS: 436-1566), can for the design of SNP detection reagents are used. As used herein, an "SNP detection reagent" is a reagent that specifically detects a specific target SNP position disclosed herein, and that is preferably specific for a particular nucleotide (allele) of the target SNP position (i.e., the detection reagent can preferably differentiate between different alternative nucleotides at a target SNP position, thereby allowing the identity of the nucleotide present at the target SNP position to be determined). Typically, such a detection reagent hybridizes to a target SNP-containing nucleic acid molecule through complementary base pairing in a sequence-specific manner and distinguishes the target variant sequence from other nucleic acid sequences, such as is known in the art, in a test sample. An example of a detection reagent is a probe that hybridizes to a target nucleic acid containing one or more of the SNPs provided in Table 1 and/or Table 2. In a preferred embodiment, such a probe can discriminate between nucleic acids having a particular nucleotide (allele). at a target SNP position from other nucleic acids having a different nucleotide at the same target SNP position. In addition, a detection reagent may hybridize to a specific region 5' and/or 3' to a SNP position, particularly a region corresponding to the contextual sequences provided in Table 1 and/or Table 2 (transcript-based contextual sequences are listed in Table 1 as SEQ ID NOS: 161-259; genome-based context sequences are provided in Table 2 as SEQ ID NOS: 436-1566). Another example of a detection reagent is a primer that acts as a starting point for nucleotide elongation along a complementary strand of a target polynucleotide. The SNP sequence information provided herein is also useful for designing primers, e.g. allele-specific primers to amplify each SNP of the present invention (e.g. using PCR).

In a preferred embodiment of the invention, a SNP detection reagent is an isolated or synthetic DNA or RNA polynucleotide probe or primer or PNA oligomer or combination of DNA, RNA and/or PNA attached to a segment of a target nucleic acid molecule hybridizes containing a SNP identified in Table 1 and/or Table 2. A polynucleotide detection reagent may optionally contain modified base analogs, intercalators, or minor groove binders. For example, multiple detection reagents such as probes can be attached to a solid support (e.g. arrays or beads) or supplied in solution (e.g. probe/primer sets for enzymatic reactions such as PCR, RT-PCR, TaqMan assays or primer extension reactions) to form a SNP detection kit.

A probe or primer is typically a substantially purified oligonucleotide or PNA oligomer. Such an oligonucleotide typically comprises a region of complementary nucleotide sequence encoded under stringent conditions with at least about 8, 10, 12, 16, 18, 20, 22, 25, 30, 40, 50, 55, 60, 65, 70, 80, Hybridizes 90, 100, 120 (or any other number in between) or more consecutive nucleotides in a target nucleic acid molecule. Depending on the particular assay, the contiguous nucleotides can either encompass the target SNP position or be a specific region sufficiently close 5' and/or 3' to the SNP position to perform the desired assay.

Other preferred primer and probe sequences can be readily determined using the transcript sequences (SEQ ID NOS: 1-80), genomic sequences (SEQ ID NOS: 260-435) and SNP context sequences (transcript-based context sequences are provided) in Table 1 as SEQ ID NOS: 161-259; genome-based context sequences are provided in Table 2 as SEQ ID NOS: 436-1566) disclosed in the Sequence Listing and Tables 1-2. It will be apparent to those skilled in the art that such primers and probes are useful directly as reagents for genotyping the SNPs of the present invention and can be incorporated into any kit/system format.

[0192] To generate a probe or primer specific for a target SNP-containing sequence, the gene/transcript and/or contextual sequence surrounding the SNP of interest is typically examined using a computer algorithm operating at the 5' or the nucleotide sequence begins at the 3' end. Typical algorithms will then identify oligomers of defined length that are unique to the gene/SNP context sequence, have a GC content within a range suitable for hybridization, lack a predicted secondary structure that may interfere with hybridization, and/or other desired ones Possess properties or lack other undesirable properties.

A primer or probe of the present invention is typically at least about 8 nucleotides in length. In one embodiment of the invention, a primer or probe is at least about 10 nucleotides in length. In a preferred embodiment, a primer or probe is at least about 12 nucleotides in length. In a more preferred embodiment, a primer or probe is at least about 16, 17, 18, 19, 20, 21, 22, 23, 24, or 25 nucleotides in length. While the maximum length of a probe can be as long as the target sequence to be detected, it is typically less than about 50, 60, 65, or 70 nucleotides in length, depending on the type of assay in which it is used. In the case of a primer, it is typically less than about 30 nucleotides in length. In a specific preferred embodiment of the invention, a primer or probe is from about 18 to about 28 nucleotides in length. Nucleic acid arrays and other embodiments where probes are attached to a substrate, the probes may be longer, such as on the order of 30- 70, 75, 80, 90, 100 or more nucleotides in length (see the section below entitled "SNP Detection Kits. and Systems").

[0194] For analyzing SNPs it may be appropriate to use oligonucleotides specific for alternative SNP alleles. Such oligonucleotides which detect single nucleotide variations in target sequences can be referred to by terms such as "allele-specific oligonucleotides", "allele-specific probes" or "allele-specific primers". The design and use of allele-specific probes to analyze polymorphisms is e.g. B. in Mutation Detection A Practical Approach, ed. Cotton et al. Oxford University Press, 1998; Saiki et al., Nature 324:163-166 (1986); Dattagupta, EP235,726; and Saiki, WO 89/11548.

While the design of any allele-specific primer or probe depends on variables such as the exact composition of the nucleotide sequences flanking a SNP position in a target nucleic acid molecule and the length of the primer or probe, another factor in using primers is and probes is the stringency of the condition under which the hybridization between the probe or primer and the target sequence is carried out. Higher stringency conditions use buffers with lower ionic strength and/or a higher reaction temperature and tend to require a more perfect match between the probe/primer and a target sequence to form a stable duplex. However, if the stringency is too high, hybridization may not occur at all. In contrast, lower stringency conditions use buffers with higher ionic strength and/or a lower reaction temperature and allow the formation of stable duplexes with more mismatched bases between a probe/primer and a target sequence. By way of example and not limitation, example conditions for high stringency hybridization conditions using an allele-specific probe are as follows: Prehybridization with a solution containing 5X standard salt phosphate EDTA (SSPE), 0.5% NaDodSO 4 (SDS) at 55°C. and incubating the probe with target nucleic acid molecules in the same solution at the same temperature, followed by washing with a solution containing 2 x SSPE and 0.1% SDS at 55°C. C or room temperature.

Moderate stringency hybridization conditions can be used for allele-specific primer extension reactions with a solution containing e.g. B. contains about 50 mM KCl at about 46 ° C. Alternatively, the reaction can be carried out at an elevated temperature such as 60°C. Alternatively, a moderately stringent hybridization condition suitable for oligonucleotide ligation assay (OLA) reactions, in which two probes are ligated when they are fully complementary to the target sequence, is a solution of about 100 mM KCl at a temperature of Use 46°C. C

In a hybridization-based assay, allele-specific probes can be designed that hybridize to a segment of target DNA from one individual, but do not hybridize to the corresponding segment from another individual, due to the presence of different polymorphic forms (e.g., B. alternative SNP alleles/nucleotides) in the respective DNA segments of the two individuals. Hybridization conditions should be sufficiently stringent that there is a significant detectable difference in hybridization intensity between alleles, and preferably an essentially binary response, with a probe hybridizing to only one of the alleles or significantly more strongly to one allele. While a probe can be designed to hybridize to a target sequence containing an SNP site such that the SNP site aligns anywhere along the probe's sequence, the probe is preferably designed to hybridize to a segment of the target sequence hybridizes such that the SNP site is aligned with a mid-position of the probe (e.g., a position within the probe that is at least three nucleotides from either end of the probe). This probe design generally achieves good discrimination in hybridization between different allelic forms.

In another embodiment, a probe or primer can be designed to hybridize to a segment of the target DNA such that the SNP terminates at either the 5'-most end or the 3'-most end of the probe or the Primers aligned is particularly suitable for use in an oligonucleotide ligation assay (U.S. Patent No. 4,988,617), the 3'-most nucleotide of the probe is aligned with the SNP position in the target sequence.

[0199] Oligonucleotide probes and primers can be prepared by methods well known in the art. Chemical synthesis methods include the phosphotriester method described by Narang et al., 1979, Methods in Enzymology 68:90; the phosphodiester method described by Brown et al., 1979, Methods in Enzymology 68:109; the diethylphosphoamidate method described by Beaucage et al., 1981, Tetrahedron Letters 22:1859; and that in US Pat. No. 4,458,066.

Allele-specific probes are often used in pairs (or more rarely in sets of 3 or 4, such as when a SNP position is known to have 3 or 4 alleles, respectively, or to probe both strands of an anucleic acid molecule for a target SNP allele), and such pairs may be identical except for a one-nucleotide mismatch representing the allelic variants at the SNP position. Typically, one member of a pair is a perfect match for a reference form of a target sequence that has a more common SNP allele (i.e., the allele that is more common in the target population), and the other member of the pair is a perfect match for a form of the target sequence that has it a less common SNP allele (i.e. the allele that is less common in the target population). In the case of an array, multiple pairs of probes can be immobilized on the same support to simultaneously analyze multiple different polymorphisms.

In one type of PCR-based assay, an allele-specific primer hybridizes to a region on a target nucleic acid molecule that overlaps a SNP position and only primes the amplification of an allelic form to which the primer shows perfect complementarity (Gibbs, 1989 , Nucleic Acid Res. 17 2427-2448). Typically, the extreme 3' nucleotide of the primer is aligned with and complementary to the SNP position of the target nucleic acid molecule. This primer is used in conjunction with a second primer that hybridizes at a distal site. Amplification emanates from the two primers, producing a detectable product indicative of which allelic form is present in the test sample. A control is usually performed with a second pair of primers, one showing a single base mismatch at the polymorphic site and the other showing perfect complementarity at a distal site. The single base mismatch prevents amplification or substantially reduces amplification efficiency such that either no detectable product is formed, or it is formed in lower amounts or more slowly. The method generally works most effectively when the mismatch is at the 3' position of the oligonucleotide (i.e. the 3' position of the oligonucleotide is aligned with the target SNP position), since this position is most destabilizing to elongation from the primer (see e.g. WO93/22456). This PCR-based assay can be used as part of the TaqMan assay described below.

In a specific embodiment of the invention, a primer of the invention contains a sequence that is substantially complementary to a segment of a target SNP-containing nucleic acid molecule, except that the primer has a mismatched nucleotide in one of the three 3'-most nucleotide positions end of the primer such that the mismatched nucleotide does not base pair with a particular allele at the SNP site. In a preferred embodiment, the mismatched nucleotide in the primer is the penultimate nucleotide at the 3' position of the primer. In a more preferred embodiment, the mismatched nucleotide in the primer is the last nucleotide at the 3' position of the primer.

In another embodiment of the invention, a SNP detection reagent of the invention is labeled with a fluorogenic reporter dye that emits a detectable signal. While the preferred reporter dye is a fluorescent dye, any reporter dye that can be attached to a detection reagent such as an oligonucleotide probe or a primer is suitable for use in the invention. Such dyes include, but are not specified, Acridine, AMCA, BODIPY, Cascade Blue, Cy2, Cy3, Cy5, Cy7, Dabcyl, Edans, Eosin, Erythrosine, Fluorescein, 6-Fam, Tet, Joe, Hex, Oregon Green, Rhodamine Limited, Rhodol Green, Tamra, Rox, and Texas Red.

In yet another embodiment of the invention, the detection reagent can be further labeled with a quenching dye such as Tamra, particularly when the reagent is used as a self-quenching probe such as TaqMan (US Patent Nos. 5,210,015 and 5,538,848). or MolecularBeacon probe (U.S. Pat. Nos. 5,118,801 and 5,312,728) or other stemless or linear beacon probe (Livak et al., 1995, PCR MethodAppl. 4:357-362; Tyagi et al., 1996, Nature Biotechnology 14: 303-308, Nazarenko et al., 1997, Nucl Acids Res 25:2516-2521, US Patent Nos. 5,866,336 and 6,117,635).

The detection reagents of the invention may also contain other labels including, but not limited to, biotin for streptavidin binding, hapten for antibody binding, and oligonucleotide for binding to another complementary oligonucleotide such as ZIP code pairs.

The present invention also contemplates reagents that do not contain (or are complementary to) any SNP nucleotide identified herein, but that are used to assay one or more SNPs disclosed herein. For example, primers that flank but do not directly hybridize to a target SNP position provided herein are useful in primer extension reactions in which the primers hybridize to a region contiguous to the target SNP position (i.e., within one or several nucleotides from the target SNP site). During the primer extension reaction, a primer is typically unable to extend beyond a target SNP site when a particular nucleotide (allele) is present at that target SNP site, and the primer extension product can be detected to determine which SNP allele is present at the target SNP plot. For example, specific ddNTPs are typically used in the primer extension reaction to terminate primer extension once a ddNTP is incorporated into the extension product (a primer extension product that contains a ddNTP at the most 3' end of the primer extension product and in which the ddNTP is a nucleotide a SNP disclosed herein, is a composition specifically contemplated by the present invention). Thus, reagents that bind to a nucleic acid molecule in a region adjacent to a SNP site and that are used to probe the SNP site, although the bound sequences do not necessarily contain the SNP site itself, are contemplated by the present invention.

[0207] SNP Detection Kits and Systems

[0208] One skilled in the art will recognize that based on the SNP disclosed herein and associated sequence information, detection reagents can be designed and used to assay any SNP of the present invention individually or in combination, and such detection reagents can be readily incorporated into any of the established kit or system formats well known in the art one or more SNP detection reagents in combination with one or more other types of elements or components (e.g. other types of biochemical reagents, containers, packaging such as packaging intended for commercial intended for sale, substrates to which SNP detection reagents are attached, electronic hardware components, etc.). Accordingly, the present invention further provides SNP detection kits and systems, including but not limited to packaged probe and primer sets (e.g., TaqMan probes/primer sets), arrays/microarrays of nucleic acid molecules, and beads that contain one or more probes, primers or other detection reagents for detecting one or more SNPs of the present invention. The kits/systems may optionally include various electronic hardware components; for example, arrays ("DNA chips") and microfluidic systems ("lab-on-a-chip" systems) provided by various manufacturers typically include hardware components. Other kits/systems (e.g. probe/primer sets) may not contain electronic hardware components but may consist of, for example, one or more SNP detection reagents (along with optional other biochemical reagents) packaged in one or more containers .

In some embodiments, a SNP detection kit typically contains one or more detection reagents and other components (e.g., a buffer, enzymes such as DNA polymerases or ligases, chain-elongating nucleotides such as deoxynucleotide triphosphates, and in the case of Sanger-type DNA sequencing reactions, B. chain-terminating nucleotides , positive control sequences, negative control sequences and the like) required for performing an assay or reaction such as amplification and/or detection of a SNP-containing nucleic acid molecule. A kit may further include means for determining the amount of a target nucleic acid and means for comparing the amount to a standard, and may include instructions for using the kit to detect the SNP-containing nucleic acid molecule of interest. In one embodiment of the present invention, kits are provided containing the necessary reagents to perform one or more assays to detect one or more SNPs disclosed herein. In a preferred embodiment of the present invention, SNP detection kits/systems are in the form of nucleic acid arrays or compartmentalized kits, including microfluidic/lab-on-a-chip systems.

For example, SNP detection kits/systems can contain one or more probes or pairs of probes that hybridize to a nucleic acid molecule at or near each target SNP position. Multiple pairs of allele-specific probes can be included in the kit/system to simultaneously test a large number of SNPs, at least one of which is a SNP of the present invention. In some kits/systems, the allele-specific probes are immobilized on a substrate such as an array or bead. For example, the same substrate can include allele-specific probes to detect at least 1; 10; 100; 1000;10,000; 100,000 (or any other number in between) or substantially all of the SNPs shown in Table 1 and/or Table 2.

The terms "arrays", "microarrays" and "DNA chips" are used interchangeably herein to refer to an array of different polynucleotides attached to a substrate such as glass, plastic, paper, nylon or other types of membranes, filters, chip or any other suitable solid support. The polynucleotides can be synthesized directly on the substrate or synthesized separately from the substrate and then attached to the substrate. In one embodiment, the microarray is made and used according to the methods described in US Pat. No. 5,837,832, Chee et al., PCT Application WO95/11995 (Chee et al.), Lockhart, D.J. et al. (1996; Nat. Biotech. 14:1675-1680) and Schena, M. et al. (1996; Proc. Natl. Acad. Sci. 93:10614-10619), all of which are incorporated herein by reference in their entirety. In other embodiments, such arrays are provided by the methods described by Brown et al., US Pat. No. 5,807,522.

Nucleic acid arrays are discussed in the following references: Zammatteo et al., "New chips for molecular biology and diagnostics", Biotechnol Annu Rev. 2002; 8:85-101; Sosnowski et al., "Active microelectronic array system for DNA hybridization, genotyping, and pharmacogenomic applications," Psychiatr Genet. 2002December; 12(4):181-92; Heller, "DNA microarray technology: devices, systems and applications", Annu Rev Biomed Eng. 2002;4:129-53. Epub 2002 March 22; Kolchinsky et al., "Analysis of SNPs and other genomic variations using gel-based chips", Hum Mutat. Apr 2002; 19(4):343-60; and McGall et al., "High-density genechipolynucleotide probe arrays", Adv Biochem Eng Biotechnol. 2002;77:21-42.

Any number of probes, such as allele-specific probes, can be implemented in an array, and each probe or pair of probes can hybridize to a different SNP position. In the case of polynucleotide probes, they can be synthesized on a substrate at specific areas (or synthesized separately and then attached to specific areas) using a light-directed chemical process. For example, each DNA chip may contain thousands to millions of individual synthetic polynucleotide probes arranged in a grid-like pattern and miniaturized (e.g., to the size of a dime). Preferably, probes are attached to a solid support in an ordered, addressable array.

[0214] A microarray can be composed of a large number of unique single-stranded polynucleotides, usually either synthetic antisense polynucleotides or fragments of cDNAs, affixed to a solid support. Typical polynucleotides are preferably about 6-60 nucleotides in length, more preferably about 15-30 nucleotides in length, and most preferably about 18-25 nucleotides in length. For certain types of microarrays or other detection kits/systems it may be preferable to use oligonucleotides that are only about 7-20 nucleotides long. In other types of arrays, such as arrays used in conjunction with chemiluminescent detection technology, preferred probe lengths may be, for example, about 15-80 nucleotides long, preferably about 50-70 nucleotides long, more preferably about 55-65 nucleotides long, most preferably a length of about 60 nucleotides. The microarray or detection kit may contain polynucleotides covering the known 5' or 3' sequence of a gene/transcript or target SNP site, sequential polynucleotides covering the complete sequence of a gene/transcript; or unique polynucleotides selected from particular regions along the length of a target gene/transcript sequence, particularly regions corresponding to one or more SNPs disclosed in Table 1 and/or Table 2 (e.g., specific to a particular SNP allele a target SNP site or specific for particular SNP alleles at several different SNP sites) or specific for a polymorphic gene/transcript or genes/transcripts of interest.

[0215] Hybridization assays based on polynucleotide arrays rely on the differences in the hybridization stability of the probes to perfectly matched and mismatched target sequence variants. For SNP genotyping, it is generally preferable that the stringency conditions used in hybridization assays are high enough that nucleic acid molecules that differ from one another at only a single SNP position can be distinguished (e.g., a given nucleotide is at a SNP position present but does not occur if an alternative nucleotide is present at that SNP position). Such highly stringent conditions may be preferred when, for example, nucleic acid arrays of allele-specific probes are used for SNP detection. Such highly stringent conditions are described in the previous section and are well known to those skilled in the art and can be found, for example, in Current Protocols in Molecular Biology, John Wiley & Sons, N.Y. (1989), 6.3.1-6.3.6.

In other embodiments, the arrays are used in conjunction with chemiluminescent detection technology. The following patents and patent applications, all of which are hereby incorporated by reference, provide additional information pertaining to chemiluminescent detection: US Patent Application Ser. Nos. 10/620,332 and 10/620,333 describe chemiluminescence approaches for microarray detection; US Pat. Nos. 6,124,478, 6,107,024, 5,994,073, 5,981,768, 5,871,938, 5,843,681, 5,800,999 and 5,773,628 describe methods and compositions of dioxetane for performing chemiluminescent detection; and published US application US2002/0110828 discloses methods and compositions for microarray controls.

In one embodiment of the invention, a nucleic acid array may comprise an array of probes about 15-25 nucleotides in length. In further embodiments, a nucleic acid array may comprise any number of probes in which at least one probe is capable of detecting one or more SNPs disclosed in Table 1 and/or Table 2, and/or at least one probe comprises a fragment of one of the sequences selected from the group consisting of the sequences disclosed in Table 1, Table 2, the sequence listing and complementary thereto, wherein the fragment comprises at least about 8 contiguous nucleotides, preferably 10, 12, 15, 16, 18, 20, more preferably 22, 25 , 30, 40, 47, 50, 55, 60, 65, 70, 80, 90, 100 , or more consecutive nucleotides (or any number in between) and contain (or are complementary to) a new SNP allele found in Table 1 and/or Table 2 is disclosed. In some embodiments, the nucleotide complementary to the SNP site is within 5, 4, 3, 2, or 1 nucleotide of the center of the probe, more preferably at the center of the probe.

A polynucleotide probe can be synthesized on the surface of the substrate using a chemical coupling method and an inkjet applicator as described in PCT application WO95/251116 (Baldeschweiler et al.), which is incorporated herein by reference in its entirety . In another aspect, a "grid" array analogous to a dot (or slit) blot can be used to array and surface cDNA fragments or oligonucleotides using a vacuum system, thermal, UV, mechanical, or chemical binding methods to bind a substrate. An array such as those described above can be prepared by hand or using available devices (slot blot or dot blot devices), materials (any suitable solid support) and machines (including robotic instruments) and can be 8, 24, 96, 384, 1536, 6144 or more polynucleotides, or any other number that lends itself to the efficient use of commercially available instruments.

[0219] Using such arrays or other kits/systems, the present invention provides methods for identifying the SNPs disclosed herein in a test sample. Such methods typically involve incubating a test sample of nucleic acids with an array comprising one or more probes corresponding to at least one SNP position of the present invention and testing for binding of a nucleic acid from the test sample with one or more of the probes. Conditions for incubating an SNP detection reagent (or a kit/system employing one or more such SNP detection reagents) with a test sample vary. The incubation conditions depend on such factors as the format used in the test, the detection methods used, and the type and nature of the detection reagents used in the test. One skilled in the art will recognize that any of the commonly available hybridization, amplification, and array assay formats can be readily adapted to detect the SNPs disclosed herein.

[0220] A SNP detection kit/system of the present invention may include components used to produce nucleic acids from a test sample for subsequent amplification and/or detection of an SNP-containing nucleic acid molecule. Such sample preparation components can be used to prepare nucleic acid extracts (including DNA and/or RNA), proteins or membrane extracts from any body fluid (such as blood, serum, plasma, urine, saliva, mucus, gastric juice, semen, tears, sweat, etc.) , skin, hair, cells (especially nucleated cells), biopsies, cheek cells (e.g. obtained from cheek swabs) or tissue samples. The test samples used in the methods described above will vary based on such factors as the assay format, the type of detection method, and the specific tissues, cells, or extracts used as the test sample to be tested. Methods for preparing nucleic acids, proteins and cell extracts are well known in the art and can be easily adapted to obtain a sample compatible with the system used. Automated sample preparation systems for extracting nucleic acids from a test sample are commercially available and examples are Qiagen's BioRobot 9600, Applied Biosystems' PRISM™. 6700 Sample Prep System and COBAS AmpliPrepSystem from Roche Molecular Systems.

[0221] Another form of kit contemplated by the present invention is a compartmentalized kit. A compartmentalized kit includes all kits whose reagents are contained in separate containers. Such containers include, for example, small glass containers, plastic containers, plastic, glass or paper strips, or assembly materials such as silica. Such containers allow reagents to be efficiently transferred from one compartment to another so as not to cross-contaminate the test samples and reagents, or from one container to another container not included in the kit, and the reagents or solutions of each container to add quantitatively from one compartment to another or to another vessel. Such containers can include, for example, one or more containers holding the test sample, one or more containers containing at least one probe or other SNP detection reagent for detecting one or more SNPs of the present invention, one or more containers containing wash reagents (such as phosphate buffered saline, Tris buffer, etc.) and one or more containers containing the reagents used to detect the presence of the bound probe or other SNP detection reagents. The kit can optionally further comprise compartments and/or reagents for, for example, nucleic acid amplification or other enzymatic reactions such as primer extension reactions, hybridization, ligation, electrophoresis (preferably capillary electrophoresis), mass spectrometry and/or laser-induced fluorescence detection. The kit may also include instructions for using the kit. Exemplary compartmentalized kits include microfluidic devices known in the art (see, e.g., Weigl et al., "Lab-on-a-chip for drug development", Adv Drug Deliv Rev. 2003 Feb. 24; 55(3): 349-77). ). In such microfluidic devices, the containers may be referred to as microfluidic "compartments", "chambers" or "channels", for example.

Microfluidic devices, which may also be referred to as "lab-on-a-chip" systems, biomedical microelectromechanical systems (BioMEMs), or multi-component integrated systems, are exemplary kits/systems of the present invention for analyzing SNPs. Such systems miniaturize and compartmentalize processes such as Probe/target hybridization, nucleic acid amplification, and capillary electrophoresis reactions in a single functional device. Such microfluidic devices typically use detection reagents in at least one aspect of the system, and such detection reagents can be used to detect one or more SNPs of the present invention. An example of a microfluidic system is disclosed in US Pat. No. 5,589,136, which describes the integration of PCR amplification and capillary electrophoresis into chips. Exemplary microfluidic systems include a pattern of microchannels designed on a glass, silicon, quartz, or plastic wafer contained on a microchip. The movements of the samples can be controlled by electrical, electroosmotic, or hydrostatic forces applied across different areas of the microchip to create functional microscopic valves and pumps with no moving parts. Varying the voltage can be used as a means of controlling liquid flow at intersections between the micromachined channels and changing the liquid flow rate for pumping across different sections of the microchip. See, for example, US Pat. No. 6,153,073, Dubrow et al., and U.S. Pat. No. 6,156,181, Parce et al.

[0223] For genotyping of SNPs, an exemplary microfluidic system can integrate, for example, nucleic acid amplification, primer extension, capillary electrophoresis, and a detection method such as laser-induced fluorescence detection. In a first step of an exemplary method for using such an exemplary system, nucleic acid samples are amplified, preferably by PCR. Then the amplification products are subjected to automated primer extension reactions using ddNTPs (specific fluorescence for each ddNTP) and the appropriate oligonucleotide primers to perform primer extension reactions that hybridize just upstream of the target SNP. Once the 3' end extension is complete, the primers are separated from the unincorporated fluorescent ddNTPs by capillary electrophoresis. The separation medium used in capillary electrophoresis can be, for example, polyacrylamide, polyethylene glycol or dextran. The ddNTPs incorporated into the single nucleotide primer extension products are identified by laser-induced fluorescence detection. Such an exemplary microchip can be used to process, for example, at least 96 to 384 samples or more in parallel.

[0224] Uses of Nucleic Acid Molecules

[0225] The nucleic acid molecules of the present invention have a variety of uses, particularly in the diagnosis and treatment of stroke and related pathologies. For example, the nucleic acid molecules are useful as hybridization probes, such as for genotyping SNPs in messenger RNA, transcript, cDNA, genomic DNA, amplified DNA, or other nucleic acid molecules, and for isolating full-length cDNA and genomic clones encoding the peptide variants disclosed in Table 1 and their orthologs.

A probe can hybridize to any nucleotide sequence along the entire length of a nucleic acid molecule provided in Table 1 and/or Table 2. Preferably, a probe of the present invention hybridizes to a region of a target sequence that encompasses an SNP position set forth in Table 1 and/or Table 2. More preferably, a probe hybridizes in a sequence-specific manner to an SNP-containing target sequence such that it targets the target sequence from other nucleotide sequences that differ from the target sequence only by which nucleotide is present at the SNP site. Such a probe is particularly useful for detecting the presence of an SNP-containing nucleic acid in a test sample or for determining which nucleotide (allele) is present at a particular SNP site (i.e., genotyping the SNP site).

[0227] A nucleic acid hybridization probe can be used to determine the presence, extent, form and/or distribution of nucleic acid expression. The nucleic acid whose amount is determined can be DNA or RNA. Accordingly, probes specific to the SNPs described herein can be used to determine the presence, expression, and/or gene copy number in a given cell, tissue, or organism. These uses are relevant to the diagnosis of disorders involving an increase or decrease in gene expression relative to normal levels. In vitro techniques for detecting mRNA include, for example, Northern blot hybridization and in situ hybridization. In vitro techniques for detecting DNA include Southern blot hybridization and in situ hybridization (Sambrook and Russell, 2000, Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Press, Cold Spring Harbor, N.Y.).

Probes can be used as part of a diagnostic test kit to identify cells or tissues in which an aberrant protein is expressed, such as by measuring the level of an aberrant protein-encoding nucleic acid (e.g., mRNA) in a sample of cells of a subject or determining whether a polynucleotide contains a SNP of interest.

[0229] Thus, the nucleic acid molecules of the invention can be used as hybridization probes to detect the SNPs disclosed herein, thereby determining whether an individual having the polymorphisms is at risk for stroke and related pathologies. Detection of an SNP associated with a disease phenotype provides a diagnostic tool for active disease and/or a genetic predisposition to disease.

In addition, the nucleic acid molecules of the invention are therefore useful for detecting a gene (gene information is disclosed, for example, in Table 2) containing a SNP disclosed herein and/or products of such genes, such as expressed mRNA transcript molecules (transcript information is disclosed, for example disclosed in Table 1) and are thus useful for detecting gene expression. The nucleic acid molecules can optionally be implemented, for example, in an array or kit format for use in detecting gene expression.

The nucleic acid molecules of the invention are also useful as primers to amplify any given region of a nucleic acid molecule, particularly a region containing an SNP identified in Table 1 and/or Table 2.

The nucleic acid molecules of the invention are also useful for constructing recombinant vectors (described in more detail below). Such vectors include expression vectors expressing part or all of any of the variant peptide sequences provided in Table 1. Vectors also include insertion vectors used to integrate into another nucleic acid molecule sequence, such as into the cellular genome, to alter in situ expression of a gene and/or gene product. For example, an endogenous coding sequence can be replaced via homologous recombination with all or part of the coding region containing one or more specifically introduced SNPs.

The nucleic acid molecules of the invention are also useful for expressing antigenic portions of protein variants, particularly antigenic portions that contain a variant amino acid sequence (e.g., an amino acid substitution) caused by an SNP disclosed in Table 1 and/or Table 2 .

The nucleic acid molecules of the invention are also useful for constructing vectors containing a gene regulatory region of the nucleic acid molecules of the present invention.

The nucleic acid molecules of the invention are also useful for designing ribozymes corresponding to all or part of an mRNA molecule expressed from a SNP-containing nucleic acid molecule described herein.

The nucleic acid molecules of the invention are also useful for constructing host cells that express part or all of the nucleic acid molecules and peptide variants.

The nucleic acid molecules of the invention are also useful for constructing transgenic animals expressing all or part of the nucleic acid molecules and peptide variants. For example, the production of recombinant cells and transgenic animals with nucleic acid molecules containing the SNPs disclosed in Table 1 and/or Table 2 allows for effective clinical design of treatment compounds and dosage regimens.

The nucleic acid molecules of the invention are also useful in drug screening assays to identify compounds that modulate, for example, nucleic acid expression.

The nucleic acid molecules of the invention are also useful in gene therapy in patients whose cells have aberrant gene expression. Thus, recombinant cells, including cells from a patient that have been manipulated ex vivo and returned to the patient, can be introduced into a subject where the recombinant cells produce the desired protein to treat the subject.

[0240] SNP genotyping method

The process of determining which specific nucleotide (i.e. allele) is present at each of one or more SNP positions, e.g. B. an SNP position in a nucleic acid molecule disclosed in Table 1 and / or Table 2, is referred to as SNP genotyping. The present invention provides methods for SNP genotyping, such as e.g. for use in determining predisposition to stroke or related pathologies, or determining responsiveness to a treatment, or in genome mapping or SNP association analysis, etc.

Nucleic acid samples can be genotyped to determine which allele(s) is/are present in any given genetic region (e.g., SNP position) of interest by methods well known in the art. The adjacent sequence can be used to design SNP detection reagents such as oligonucleotide probes, which can optionally be implemented in a kit format. Exemplary SNP genotyping methods are described in Chen et al., "Single nucleotide polymorphism genotyping: biochemistry, protocol, cost and throughput", Pharmacogenomics J. 2003; 3(2):77-96; Kwok et al., "Detection of single nucleotide polymorphisms", Curr Issues Mol Biol. April 2003; 5(2):43-60; Shi, "Individual genotyping technologies: detecting genetic polymorphisms in drug targets and disease genes," Am JPharmacogenomics. 2002; 2(3):197-205; and Kwok, "Methods for genotyping single nucleotide polymorphisms", Annu Rev Genomics HumGenet 2001; 2:235-58. Exemplary techniques for high-throughput SNP genotyping are in Marnellos, "High-throughput SNPanalysis for genetic Association studies", Curr Opin Drug DiscovDevel. 2003 May; 6(3):317-21. Common SNP genotyping methods include TaqMan assays, molecular beacon assays, nucleic acid arrays, allele-specific primer extension, allele-specific PCR, arrayed primer extension, homogeneous primer extension assays, primer extension with detection by Mass spectrometry, pyrosequencing, multiplex, but not limited to, primer extension sorted genetic arrays, ligation with rolling circle amplification, homogeneous ligation, OLA (US Patent No. 4,988,167), multiplex ligation reaction sorted on genetic arrays, restriction fragment length polymorphism , single base extension tag assays, and the invader assay. Such methods can be used in combination with detection mechanisms such as luminescence or chemiluminescence detection, fluorescence detection, time-resolved fluorescence detection, fluorescence resonance energy transfer, fluorescence polarization, mass spectrometry, and electrical detection.

Various methods for detecting polymorphisms include, but are not limited to, methods that use protection from cleaving agents to detect mismatched bases in RNA/RNA or RNA/DNA duplexes (Myers et A., Science 230 : 1242 (1985), Cotton et al., PNAS 85:4397 (1988) and Saleeba et A., Meth. Orita et al PNAS 86:2766 (1989), Cottonet A Mutat Res 285:125-144 (1993) and Hayashi et al Genet Anal Tech Appl 9:73-79 (1992). )), and the study of the movement of polymorphic or wild-type fragments in polyacrylamide gels containing a gradient of denaturant using denaturation gradient gel electrophoresis (DGGE) (Myers et al., Nature 313:495 (1985)). RNase and 51 protection or chemical cleavage methods.

In a preferred embodiment, SNP genotyping is performed using the TaqMan assay, also known as the 5' nuclease assay (US Patent Nos. 5,210,015 and 5,538,848). The TaqMan Assay detects the accumulation of a specific amplified product during PCR. The TaqMan Assay uses an oligonucleotide probe labeled with a fluorescent reporter dye and a quencher dye. The reporter dye is excited by irradiation with an appropriate wavelength and transfers energy to the quencher dye in the same probe via a process called fluorescence resonance energy transfer (FRET). When bound to the probe, the excited reporter dye does not emit a signal. The proximity of the quencher dye to the reporter dye in the intact probe maintains reduced fluorescence for the reporter. The reporter dye and quencher dye can be the 5'-most and 3'-most, respectively, or vice versa. Alternatively, the reporter dye can be located at the extreme 5' or 3' end while the quencher dye is attached to an internal nucleotide, or vice versa. In yet another embodiment, both the reporter and the quencher may be attached to internal nucleotides at a distance from each other such that the fluorescence of the reporter is reduced.

[0245] During PCR, the 5' nuclease activity of DNA polymerase cleaves the probe, separating the reporter dye and quencher dye, resulting in increased fluorescence of the reporter. Accumulation of the PCR product is detected directly by monitoring the increase in fluorescence of the reporter dye. The DNA polymerase cleaves the probe between the reporter dye and the quencher dye only when the probe hybridizes to the target SNP-containing template that is amplified during PCR, and the probe is designed to cleave to the target only then -SNP site hybridizes when a particular SNP allele is present.

Preferred TaqMan primer and probe sequences can be readily determined using the SNP and associated nucleic acid sequence information provided herein. A number of computer programs such as B. Primer Express (Applied Biosystems, Foster City, CA) can be used to quickly obtain optimal primer/probe sets. Those skilled in the art will appreciate that such primers and probes for detecting the SNPs of the present invention are useful in assays for determining susceptibility to stroke and related pathologies and can be easily incorporated into a kit format. The present invention also encompasses modifications of the Taqman assay that are well known in the art, such as the use of Molecular Beacon probes (U.S. Patent Nos. 5,118,801 and 5,312,728) and other format variations (U.S. Patent Nos. 5,866,336 and 6,117,635) .

Another preferred method of genotyping the SNPs of the present invention is to use two oligonucleotide probes in an OLA (see, e.g., US Patent No. 4,988,617). In this method, a probe hybridizes to a segment of a target nucleic acid with its 3' end aligned with the SNP site. A second probe hybridizes to an adjacent segment of the target nucleic acid molecule just 3' of the first probe. The two juxtaposed probes hybridize to the target nucleic acid molecule and are ligated in the presence of a linking agent such as a ligase when there is perfect complementarity between the 3'-most nucleotide of the first probe and the SNP site. If there is a mismatch, no ligation would occur. After reaction, the ligated probes are separated from the target nucleic acid molecule and detected as indicators of the presence of an SNP.

The following patents, patent applications, and published international patent applications, all incorporated herein by reference, provide additional information describing techniques for performing various types of OLA:U.S. Beat. Nos. 6,027,889, 6,268,148, 5,494,810, 5,830,711 and 6,054,564 describe OLA strategies for performing SNP detection; WO 97/31256 and WO 00/56927 describe OLA strategies for performing SNP detection using universal arrays, wherein a zip code sequence can be introduced into one of the hybridization probes and the resulting product or amplified product can be hybridized to a universal zip code array; US application US01/17329 (and serial number 09/584,905) describes OLA (or LDR) followed by PCR, wherein zip codes are incorporated into OLA probes and amplified PCR products are determined by electrophoresis or universal reading of a zip code array; Applications 60/427,818, 60/445,636 and 60/445,494 describe SNPlex methods and software for multiplex SNP detection using OLA followed by PCR, incorporating zip codes into OLA probes and amplified PCR products with a zipchute reagent and the identity of the SNP determined by electrophoretic reading of the zip. In some embodiments, OLA is performed prior to PCR (or other nucleic acid amplification method). In other embodiments, PCR (or other nucleic acid amplification method) is performed prior to OLA.

Another method for SNP genotyping is based on mass spectrometry. Mass spectrometry uses the unique mass of each of the four nucleotides in DNA. SNPs can be unequivocally genotyped by mass spectrometry, by measuring the differences in mass of nucleic acids with alternative SNP alleles. MALDI-TOF (Matrix Assisted Laser Desorption Ionization – Time of Flight) mass spectrometry technology is used for extremely precise molecular mass determinations such as B. SNPs, preferred. Numerous approaches to SNP analysis have been developed based on mass spectrometry. Preferred methods for SNP genotyping based on mass spectrometry include primer extension assays, which can also be used in combination with other approaches, such as e.g. B. traditional gel-based formats and microarrays can be used.

Typically, the primer extension assay involves designing and annealing a primer to a template PCR amplicon upstream (5') of a target SNP position. A mixture of dideoxynucleotide triphosphates (ddNTPs) and/or deoxynucleotide triphosphates (dNTPs) is added to a reaction mixture containing a template (eg, a SNP-containing nucleic acid molecule that has typically been amplified, such as by PCR), primers, and contains DNA polymerase. Extension of the primer ends at the first position in the template where a nucleotide complementary to one of the ddNTPs in the mixture occurs. The primer can be either immediately adjacent (i.e., the nucleotide at the 3' end of the primer hybridizes to the nucleotide adjacent to the target SNP site) or two or more nucleotides from the SNP position. If the primer is several nucleotides away from the target SNP position, the only limitation is that the template sequence between the 3' end of the primer and the SNP position cannot contain a nucleotide of the same type as that to be detected, otherwise this will result in a premature termination of the extension primer. Alternatively, if all four ddNTPs alone, without dNTPs, are added to the reaction mixture, the primer is only ever extended by one nucleotide corresponding to the target SNP position. In this case, primers are designed to bind a nucleotide upstream from the SNP position (i.e. the nucleotide at the 3' end of the primer hybridizes to the nucleotide immediately adjacent to the target SNP site on the 5' side the target SNP location). . The extension by only one nucleotide is preferable because it minimizes the total mass of the extended primer and thereby increases the resolution of mass differences between alternative SNP nucleotides. In addition, mass-tagged ddNTPs can be used in the primer extension reactions in place of unmodified ddNTPs. This increases the mass difference between primers extended with these ddNTPs, providing increased sensitivity and fidelity, and is particularly useful for typing heterozygous base positions. Mass labeling also reduces the need for intensive sample preparation procedures and reduces the required resolving power of the mass spectrometer.

The extended primers can then be purified and analyzed by MALDI-TOF mass spectrometry to determine the identity of the nucleotide present at the target SNP position. In one analysis method, the products from the primer extension reaction are combined with light absorbing crystals that form a matrix. The matrix is ​​then struck with an energy source such as a laser to ionize and desorb the nucleic acid molecules into the gas phase. The ionized molecules are then ejected into a flight tube and accelerated down the tube to a detector. The time between the ionization event, such as a laser pulse, and the collision of the molecule with the detector is the time of flight of that molecule. The time of flight correlates closely with the mass to charge ratio (m/z) of the ionized molecule. Smaller m/z ions travel faster through the tube than larger m/z ions and therefore the lighter ions reach the detector before the heavier ions. The flight time is then converted into a corresponding and highly precise m/z. In this way, SNPs can be identified based on the subtle mass differences and the corresponding time-of-flight differences inherent in nucleic acid molecules with different nucleotides at a single base position. For more information regarding the use of primer extension assays in conjunction with MALDI-TOF mass spectrometry for SNP genotyping, see e.g. B. Wise et al., "A standard protocol for single nucleotide primer extension in the human genome using matrix-assisted laser desorption/ionization time-of -flight mass spectrometry", Rapid Commun Mass Spectrom.2003; 17(11):1195-202.

The following references provide further information describing mass spectrometry-based methods for SNP genotyping: Bocker, "SNP and mutation discovery using base-specific cleavage and MALDI-TOF mass spectrometry", Bioinformatics. 2003 July; 19Supplement 1:144-153; Storm et al., "MALDI-TOF mass spectrometry-based SNP genotyping", Methods Mol Biol. 2003; 212:241-62; Jurinke et al., "The use of Mass ARRAY technology for high throughput genotyping", Adv Biochem Eng Biotechnol. 2002; 77:57-74; and Jurinke et al., "Automated genotyping using the DNA Mass Array technology", Methods Mol Biol. 2002; 187:179-92.

[0253] SNPs can also be evaluated by direct DNA sequencing. A variety of automated sequencing methods can be used ((1995) Biotechniques 19:448), including sequencing by mass spectrometry (see, e.g., PCT International Publication No. WO94/16101; Cohen et al., Adv. Chromatogr. 36:127-162 ). (1996) and Griffin et al., Appl. biochem. biotech. 38:147-159 (1993)). The nucleic acid sequences of the present invention enable one of ordinary skill in the art to easily design sequencing primers for such automated sequencing methods. Commercial instruments such as Applied Biosystems (Foster City, CA) 377, 3100, 3700, 3730 and 3730xl DNA analyzers are commonly used in the art for automated sequencing.

Other methods that can be used to genotype the SNPs of the present invention include single strand conformational polymorphism (SSCP) and denaturing gradient gel electrophoresis (DGGE) (Myer et al., Nature 313:495 (1985)). SSCP identifies base differences by altering the electrophoretic migration of single-stranded PCR products, as described in Orita et al., Proc. nat. Acad. Single-stranded PCR products can be generated by heating or otherwise denaturing double-stranded PCR products. Single-stranded nucleic acids can refold or form secondary structures that depend in part on base sequence. The different electrophoretic mobilities of single-stranded amplification products are related to base sequence differences at SNP positions. DGGE distinguishes SNP alleles based on the different sequence-dependent stabilities and melting properties inherent in polymorphic DNA and the corresponding differences in electrophoretic migration patterns in a denaturing gradient gel (Erlich , eds., PCR Technology, Principles and Applications for DNA Amplification, W. H. Freeman and Co , New York, 1992, Chapter 7).

[0255] Sequence-specific ribozymes (US Patent No. 5,498,531) can also be used to score SNPs based on the development or loss of an aribozyme cleavage site. Perfectly matched sequences can be distinguished from mismatched sequences by nuclease digestion assays or by differences in melting temperature. If the SNP affects a restriction enzyme cleavage site, the SNP can be identified by changes in the digestion patterns of restriction enzymes and the corresponding changes in the lengths of the nucleic acid fragments are determined by gel electrophoresis

For example, SNP genotyping can include the steps of collecting a biological sample from a human subject (e.g., sample of tissues, cells, fluids, secretions, etc.), isolating nucleic acids (e.g., genomic DNA, mRNA or both). from the cells of the sample, contacting the nucleic acids with one or more primers that specifically hybridize to a region of the isolated nucleic acid containing a target SNP, under conditions such that hybridization and amplification of the target nucleic acid region occurs, and determining the Nucleotide present at the SNP position of interest, or, in some assays, detecting the presence or absence of an amplification product (assays can be designed such that hybridization and/or amplification only occurs when a particular SNP allele is present or not present). In some assays, the size of the amplification product is detected and compared to the length of a control sample; for example, deletions and insertions can be detected by a change in the size of the amplification product compared to a normal genotype.

[0257] SNP genotyping is useful for numerous practical applications, as described below. Examples of such applications include, but are not limited to, SNP disease association analysis, disease predisposition screening, disease diagnosis, disease prognosis, monitoring of disease progression, determination of therapeutic strategies based on an individual's genotype ("pharmacogenomics"), development of therapeutic agents based on SNP genotypes associated with a disease or likelihood of response to a drug, stratification of a patient population for a clinical trial for a treatment regimen, prediction of the likelihood that an individual will experience toxic side effects of a therapeutic, and human identification applications such as e.g. B. Forensics.

[0258] Analysis of the genetic association between SNPs and phenotypic traits

[0259] SNP genotyping for disease diagnosis, disease predisposition screening, disease prognosis, determination of drug susceptibility (pharmacogenomics), drug toxicity screening, and other uses described herein typically rely on the initial establishment of an agenetic association between one or more specific SNPs and the particular phenotypic trait of interest.

Various study designs can be used for genetic association studies (Modern Epidemiology, Lippincott Williams & Wilkins (1998), 609-622). The most common are observational studies, which do not affect patient response. The first type of observational study identifies a sample of people who have the suspected cause of the disease and another sample of people who do not have the suspected cause. and then the frequency of disease development in the two samples is compared. These sample populations are called cohorts and the study is a prospective study. The other type of observational study is a case-control or retrospective study. In typical case-control studies, samples are collected from individuals with the phenotype of interest (cases) as specific manifestations of a disease and from individuals without the phenotype (controls) in a population (target population) from which conclusions are to be drawn. The possible causes of the disease are then examined retrospectively. Because the time and cost of sample collection in case-control studies is significantly less than in prospective studies, case-control studies are the most commonly used study design in genetic association studies, at least during the exploration and discovery phase.

[0261] In both types of observational studies, there may be potential confounding factors that should be considered. Confounders are those associated with both the true cause(s) of the disease and the disease itself, and include demographic information such as age, gender, ethnicity, and environmental factors. When confounding factors in cases and controls in a study do not match and are not properly controlled, spurious association results can result. If potential confounders are identified, they should be controlled using the analytical methods outlined below.

In a genetic association study, the cause of interest to be tested is a particular allele or SNP, or a combination of alleles, or a haplotype of multiple SNPs. Thus, tissue samples (e.g., whole blood) can be collected from the removed individuals and genomic DNA genotyped for the SNP(s) of interest. In addition to the phenotypic trait of interest, other information such as demographic (eg, age, sex, ethnicity, etc.), clinical, and environmental information that may affect the trait's outcome may be collected to further characterize and define the sample set. In many cases these factors are known to be associated with disease and/or SNP allele frequencies. There are likely also gene-environment and/or gene-gene interactions. Analytical methods for addressing gene-environment and gene-gene interactions (for example, the effects of the presence of both susceptibility alleles in two different genes may be greater than the effects of the individual alleles in two genes combined) are discussed below.

After all relevant phenotypic and genotypic information has been obtained, statistical analyzes are performed to determine if there is any significant correlation between the presence of an allele or genotype with an individual's phenotypic characteristics. Preferably, data inspection and cleansing is performed first before performing statistical tests for genetic association. Epidemiological and clinical data from the samples can be summarized using descriptive statistics with tables and graphs. Data validation is preferably performed to check for data completion, inconsistent entries, and outliers. Chi-square tests and t-tests (Wilcoxon rank sum tests when the distributions are not normal) can then be used to test for significant differences between cases and controls for discrete and continuous variables, respectively. To ensure the quality of genotyping, Hardy-Weinberg imbalance tests can be performed separately on cases and controls. Significant deviations from Hardy-Weinberg equilibrium (HWE) in both cases and controls for individual markers can indicate genotyping errors. If HWE is violated in a majority of markers, this indicates a population substructure that should be investigated further. In addition, the Hardy-Weinberg imbalance can indicate a genetic association of the markers with the disease only in cases (Genetic Data Analysis, Weir B., Sinauer (1990)).

To test whether an allele of a single SNP is associated with the case or control status of a phenotypic trait, one skilled in the art can compare allele frequencies in cases and controls. Standard chi-square tests and Fisher's exact tests can be performed on a 2 × 2 table (2 SNP alleles × 2 results in the categorical trait of interest). To test whether genotypes of a SNP are associated, chi-square tests can be performed on a 3 × 2 table (3 genotypes × 2 results). Score tests are also performed for genotypic association to compare the three genotypic frequencies (major homozygotes, heterozygotes and minor homozygotes) in cases and controls and to look for trends using 3 different modes of inheritance, namely dominant (with contrast coefficient 2, -1, -1) , additive (with contrast coefficients 1, 0, -1) and recessive (with contrast coefficients 1, 1, -2). Odds ratios for minor versus major alleles and odds ratios for heterozygous and homozygous variants versus wild-type genotypes are calculated with the desired confidence limits, typically 95%.

[0265] To control for confounders and test for interaction and effect modifiers, stratified analyzes can be performed using stratified factors that are likely to be confounding, including demographic information such as age, race, and gender or an interacting element or effect modifier, such as a known major gene (e.g. APOE for Alzheimer's disease or HLA genes for autoimmune diseases) or environmental factors such as smoking in lung cancer. Stratified association tests can be performed using Cochran-Mantel-Haenszel tests, which account for the ordinal nature of genotypes with 0, 1, and 2 different alleles. Exact testing by StatXact can also be performed where computationally feasible. Another way to adjust for confounding effects and test for interactions is to perform stepwise multiple logistic regression analysis using statistical packages such as SAS or R. Logistic regression is a modeling technique in which the best fitting and most parsimonious model is created to describe the relationship between the dichotomous outcome (e.g. getting a certain disease or not) and a set of independent variables (e.g. Genotypes of various associated genes and associated demographic and environmental factors). The most common model is one in which the logit transformation of the odds ratios is expressed as a linear combination of the variables (main effects) and their cross product terms (interactions) (AppliedLogistic Regression, Hosmer and Lemeshow, Wiley (2000)). To test whether a given variable or interaction is significantly associated with the outcome, coefficients in the model are first estimated and then tested for statistical significance of their deviation from zero.

In addition to performing association tests one marker at a time, haplotype association analysis can also be performed to examine a number of markers that are closely related. Haplotype association tests may be more conclusive than genotypic or allelic association tests when the tested markers are not the disease-causing mutations themselves but are in linkage disequilibrium with such mutations. The test is even more powerful when the disease is actually caused by a combination of alleles on one haplotype (eg, APOE is a haplotype composed of 2 SNPs that are very close to each other). To perform haplotype association effectively, marker-marker linkage disequilibrium measures, both D' and R 2 , are typically computed for the markers within a gene to elucidate haplotype structure. Recent studies (Daly et al., Nature Genetics, 29, 232-235, 2001) on linkage disequilibrium indicate that SNPs within a gene are organized in a block pattern and there is a high level of linkage disequilibrium within blocks and very little linkage disequilibrium between blocks. Haplotype association with disease status can be made using such blocks once they have been elucidated.

Haplotype association tests can be performed in a manner similar to allelic and genotypic association tests. Each haplotype in a gene is analogous to an allele in a multiallelic marker. One skilled in the art can either compare haplotype frequencies in cases and controls or test for genetic association with different pairs of haplotypes. It has been suggested (Schaid et al., Am.J.Hum.Genet., 70, 425-434, 2002) that score testing can be performed on haplotypes using the "haplo.score" program. In this method, haplotypes are first inferred by the EM algorithm and score tests are performed using a Generalized Linear Model (GLM) framework that allows for adjustment of other factors.

An important decision when conducting genetic association testing is to determine the level of significance at which a significant association can be declared if the p-value of the testing reaches that level. For example, in an exploratory analysis where positive hits are followed up in subsequent confirmatory tests, an unadjusted p-value < 0.2 (a level of significance on the mild side) can be used to hypothesize for a significant association of a SNP with certain phenotypic traits of a human generate disease. It is preferred that a p-value < 0.05 (a level of significance traditionally used in the art) is achieved for a SNP to be considered associated with a disease. It is more preferred that a p-value < 0.01 (a level of significance on the stringent side) is achieved for an association to be declared. When hits are tracked by post-confirmative analyzes in multiple samples from the same source or indifferent samples from different sources, an adjustment for multiple testing is performed to avoid an excessive number of hits while keeping experimental error rates at 0.05. While there are various methods of adjusting for multiple testing to control for different types of error rates, a commonly used but more conservative method is Bonferroni's correction to control for experimental or familial error rate (multiple comparisons and multiple testing, Westfall et al. , SAS Institute (1999)). Permutation tests to control false discovery rates, FDR, may be more powerful (Benjamini and Hochberg, Journal of the Royal StatisticalSociety, Series B 57, 1289-1300, 1995, Resampling-based MultipleTesting, Westfall and Young, Wiley (1993)) . Such multiplicity control methods would be preferred when the tests are dependent and control for false detection rates is sufficient, as opposed to control for experimental error rates.

In replication studies using samples from different populations, after statistically significant markers have been identified in the exploratory phase, meta-analyses can then be performed by combining evidence from different studies (Modern Epidemiology, Lippincott Williams & Wilkins, 1998, 643-673 ). If available, association results known in the art for the same SNPs can be included in the meta-analyses.

Because both genotyping and disease status classification can contain errors, sensitivity analyzes can be performed to see how odds ratios and p-values ​​would change with different estimates of genotyping and disease classification error rates.

[0271] It is well known that subpopulation-based sampling variances between cases and controls can lead to erroneous results in case-control association studies (Ewens and Spielman, Am. J. Hum. Genet. 62, 450-458, 1995) when prevalence The presence of the disease is associated with different subpopulations. Such bias can also lead to a loss of statistical power in genetic association studies. To detect population stratification, Pritchard and Rosenberg (Pritchard et al. Am. J. Hum. Gen. 1999, 65:220-228) proposed typing markers not associated with the disease and using the results from Association tests on these markers to determine whether there is population stratification. If stratification is found, the genomic control (GC) method proposed by Devlin and Roeder (Devlin et al. Biometrics 1999, 55:997-1004) can be used to compensate for the inflation of test statistics due to population stratification. The GC method is robust to changes in population structure levels and is applicable to DNA pooling designs (Devlin et al. Genet. Epidem. 20001, 21:273-284).

[0272] While Pritchard's method recommended the use of 15-20 unlinked microsatellite markers, it suggested the use of more than 30 biallelic markers to obtain enough power to detect population stratification. For the GC method, it has been shown (Bacanu et al. Am. J. Hum. Genet. 2000, 66:1933-1944) that about 60-70 biallelic markers are sufficient to estimate the inflation factor for the test statistic due to population stratification. Therefore, 70 intergenic SNPs can be selected in unconnected regions as indicated in a genome scan (Kehoe et al. Hum. Mol. Genet. 1999, 8:237-245).

Once individual genetic or non-genetic risk factors for disease predisposition have been found, the next step is to set up a classification/prediction scheme to predict the category (e.g. disease or no disease) of an individual will be independent of their genotypes of associated SNPs and other non-genetic risk factors. Logistic regression for discrete features and linear regression for continuous features are standard techniques for such tasks (Applied Regression Analysis, Draper and Smith, Wiley (1998)). In addition, other techniques for establishing the classification can also be used. Such techniques include, but are not limited to, MART, CART, neural networks, and discriminant analysis suitable for use in comparing the performance of different methods (The Elements of Statistical Learning, Hastie, Tibshirani & Friedman, Springer (2002)).

[0274] Disease Diagnosis and Predisposition Screening

[0275] Information about the association/correlation between genotypes and disease-related phenotypes can be used in a number of ways. For example, in the case of a highly statistically significant association between one or more SNPs with a predisposition to a disease for which treatment is available, detection of such a genotypic pattern in an individual may prompt prompt administration of treatment or at least the establishment of regular monitoring of the justify person. Evidence of the susceptibility alleles associated with serious illness in a couple wishing to have children can also be of value to the couple in their reproductive decisions. In the case of a weaker but still statistically significant association between an SNP and a human disease, immediate therapeutic intervention or surveillance after detection of the susceptibility allele or SNP may not be warranted. Despite this, the subject can be motivated to begin simple lifestyle changes (e.g., diet, exercise) that can be accomplished at little or no cost to the person, but have potential benefits in reducing the risk of developing disease to which that person might be at increased risk due to the presence of the susceptibility allele(s).

The SNPs of the invention may contribute to stroke and related pathologies in an individual in different ways. Some polymorphisms occur within a protein coding sequence and contribute to the disease phenotype by affecting protein structure. Other polymorphisms occur in non-coding regions but may indirectly exert phenotypic effects by affecting, for example, replication, transcription and/or translation. A single SNP can affect more than one phenotypic trait. Likewise, a single phenotypic trait can be influenced by multiple SNPs in different genes.

As used herein, the terms "diagnosis", "diagnosis" and "diagnostics" include, but are not limited to, any of the following: detection of a vascular disease that an individual may currently have, predisposition/susceptibility screening (ie. , determining a person's risk of having a stroke (e.g., whether a person has an increased or decreased risk of having a stroke in the future), determining a specific type or subclass of vascular disease or stroke in a person who has a vascular disease or has suffered a stroke, confirmation or reinforcement of a previously made diagnosis of stroke or a vascular disease, pharmacogenomic evaluation of an individual to determine which therapeutic or preventive agent or strategy that individual is most likely to benefit from, or to predict whether a patient is likely to benefit from a particular therapeutic or preventive agent or strategy B. Predict whether a patient is likely to experience toxic or other undesirable side effects of a particular therapeutic or preventive agent or strategy, assess the future prognosis of a A person who has had a stroke or has a vascular disease and determining the risk that a person who has had a stroke will have one or more strokes again in the future (ie. H. recurrent strokes). Such diagnostic uses can be based on the SNPs alone or in combination or SNP haplotypes of the present invention.

[0278] Haplotypes are particularly useful in that, for example, fewer SNPs can be genotyped to determine whether a particular genomic region harbors a locus that affects a particular phenotype, such as in a linkage disequilibrium-based SNP association analysis.

Linkage disequilibrium (LD) refers to the co-inheritance of alleles (e.g. alternative nucleotides) at two or more different SNP sites with frequencies greater than would be due to the separate frequencies of occurrence of each allele in a given population would be expected. The expected frequency of co-occurrence of two alleles that are inherited independently is the frequency of the first allele multiplied by the frequency of the second allele. Alleles occurring simultaneously with expected frequencies are said to be in "linkage equilibrium". In contrast, LD refers to any non-random genetic association between alleles at two or more different SNP sites, generally due to the physical proximity of the two sites along a chromosome. LD can occur when two or more SNP sites on a given chromosome are in close proximity to one another and therefore alleles at those SNP sites tend to remain unseparated for several generations, with the result that a given nucleotide (allele) at one SNP site anon-random association with a particular nucleotide (allele) at another nearby SNP site. Therefore, genotyping one of the SNP sites provides almost the same information as genotyping the other SNP site located in LD.

Different degrees of LD can be encountered between two or more SNPs, with the result that some SNPs are more closely associated (i.e., in stronger LD) than others. In addition, the physical distance that LD extends along a chromosome differs between different regions of the genome, and therefore the degree of physical separation between two or more SNP sites required for LD to occur can vary between different regions Regions of the genome may be different.

For diagnostic purposes and similar uses when a particular SNP site is found to be useful in determining predisposition to stroke and related pathologies (e.g., has a significant statistical association with the condition and/or is considered more causative polymorphism for the condition is detected), then one skilled in the art would recognize that other SNP sites located in LD with that SNP site would also be useful in diagnosing the condition. Therefore, polymorphisms (eg, SNPs and/or haplotypes) that are not the actual disease-causing (causative) polymorphisms but are present in LD with such causative polymorphisms are also useful. In such cases, the genotype of the polymorphism(s) present in LD with the causative polymorphism is predictive of the genotype of the causative polymorphism and consequently predictive of the phenotype (e.g. stroke) induced by the/ the causative SNP(s) is affected. Therefore, polymorphic markers found in LD with causative polymorphisms are useful as diagnostic markers and are particularly useful when the actual causative polymorphism(s) is/are unknown.

[0282] Examples of polymorphisms that may be present in LD with one or more causative polymorphisms (and/or in LD with one or more polymorphisms that have a significant statistical association with a condition) and therefore useful for diagnosing the same condition as the causative/associated SNP(s). ) used for diagnosis include, for example, other SNPs in the same gene, protein-coding, or mRNA transcript-coding region as the causative/associated SNP, other SNPs in the same exon or intron as the causative/associated SNP, other SNPs in the same haplotype block such as the causative/associated SNP, other SNPs in the same intergenic region as the causative/associated SNP, SNPs located outside but close to the agent (eg, within 6 kb on each side, 5' or 3', a gene boundary ) containing a causative/associated SNP, etc. Such useful LD SNPs can be selected from the SNPs disclosed in Table 4, for example.

[0283] Verknüpfungsungleichgewicht im menschlichen Genom wird in den folgenden Literaturstellen besprochen: Wall et al., "Haplotype blocks and linkage disequilibrium in the human genome", Nat. Rev. Genet. 2003August; 4(8):587-97 (August 2003); Garneret al. et al., "Onselecting markers for Association studies: Patterns of linkagedisequilibrium between two and three diallelic loci", GenetEpidemiol. 2003 Januar; 24(1):57-67 (Januar 2003); Ardlie et al. et al., "Patterns of linkage disequilibrium in the human genome", Nat. Rev. Genet. April 2002; 3(4):299-309 (April 2002); (Erratum in Nat. Rev. Genet, Juli 2002; 3(7):566 (Juli 2002); und Remm et al. et al., „High-density genotyping and linkage disequilibrium in thehuman genome using chromosome 22 as a model“, Curr Opin Chem. Soc Biol.2002 February, 6(1):24-30 (Februar 2002), J. B. S. Haldane, „JBS(1919) The Combination of Linkage Values, and the Calculation of Distances between the Loci of Linked Factors“, J Genet 8:299 -309(1919); G. Mendel, G. (1866) Versuche über Pflanzen-Hybriden.Verhandlungen des naturforschenden Vereines in Brunn [(Proceedingsof the Natural History Society of Brunn)] (1866); Lewin B (1990) Genes IV, B. Lewin, Hrsg., Oxford University Press, New York, N. Y. USA (1990), D. L. Hartl, D. L. und A. G. Clark, A. G. (1989), Principles of Population Genetics, 2. Aufl., Sinauer Associates, Inc., MaSunderland, Mass ., USA (1989); J. H. Gillespie JH (2004) Population Genetics: A Concise Guide. 2. Aufl., Johns Hopkins University Press. (2004) USA; R. C. Lewontin, „RC (1964) Theinteraction of selection and linkage . I. Allgemeine Erwägungen; heterotische Modelle", Genetics 49:49-67 (1964); P. G. Hoel, P. G. (1954) Introduction to Mathematical Statistics 2. Aufl., JohnWiley & Sons, Inc., N.Y. New York, USA (1954); R. R. Hudson, RR „(2001) Two-locus sample distributions and their application“, Genetics 159:1805-1817 (2001); A. P. Dempster A. P., N. M. Laird, D. B. N. M., Rubin, „DB (1977 ) Maximale Wahrscheinlichkeit aus unvollständigen Daten über den EM-Algorithmus", J. R. Stat. Soc. 39:1-48 (1977); L. Excoffier, L., M. Slatkin, M. Mol Biol Evol12(5):921–927 (1995); D. A. Tregouet DA, S. Escolano S, L. Tiret L, A. Mallet A, J. L. Golmard, JL „(2004) A new algorithm forhaplotype-based association analysis : the Stochastic-EMalgorithm", Ann Hum Genet 68(Pt 2):165-177 (2004); A. D. Long A Dand C. H. Langley C H, "(1999) The power of Association studies todetect the Contribution of Candidate Genetic Loci to Variation unkomplexe Merkmale". Genome Research 9:720-731 (1999); A. Agresti, A(1990) Categorical Data Analysis., John Wiley & Sons, Inc., N.Y. New York, USA (1990); K. Lange, K (1997) Mathematical and Statistical Methods for Genetic Analysis, Springer-Verlag New York, Inc., N.Y. New York, USA (1997); Das International HapMapConsortium, "(2003) The International HapMap Project,". Nature426:789-796 (2003); Das International HapMap Consortium, „(2005) Ahaplotype map of the human genome,“. Nature 437:1299-1320 (2005);G. A. Thorisson G. A., A. V. Smith, AV., L. Krishnan, L., L. D. Stein, L. D. (2005), „The International HapMap Project Web Site,“. GenomeResearch 15:1591-1593 (2005); G. McVean, C. C. A. G, Spencer C C A, R. Chaix R (2005), „Perspektiven der humangenetischen Variation aus dem HapMap-Projekt“. PLoS Genetics 1(4):413-418 (2005); J. N. Hirschhorn J. N., M. J. Daly, M. J. „(2005) Genomweite Assoziationsstudien für häufige Krankheiten und komplexe Merkmale“. Nat Genet6:95-108 (2005); S. J. Schrodi, "S J (2005) A probabilisticapproach to large-scale Association scans: a semi-bayesian methodto detect disease-predisposing alleles,". SAGMB 4(1):31 (2005); W.Y. S. Wang, W. Y. S., B. J. Barratt, B. J., D. G. Clayton, D. G., J. A. Todd, „J. A. (2005) Genome-wide Association Studies: Theoretische und praktische Bedenken“. Nat. Rev. Genet 6:109–118 (2005); J. K. Pritchard J. K., M. Przeworski, „M (2001) Linkage disequilibrium inhumans: models and data,“. Am J Hum Genet 69:1-14 (2001).

[0284] As discussed above, one aspect of the present invention is the discovery that SNPs that are within a certain LD distance with the interrogated SNP can also be used as valid markers for identifying an increased or decreased risk of having a stroke or to develop, can be used. As used herein, the term "interrogated SNP" refers to SNPs that have been determined to be associated with an increased or decreased risk of disease using genotyping results and analysis or other appropriate experimental methods, such as those described in this Application described working examples are illustrated. The term “LD SNP” as used herein refers to an SNP that has been characterized as being associated with an increased or decreased risk of disease because it aligns in LD with the “interrogated SNP” according to the in the calculation method described in the application. Applicants describe below the computational methods that one of ordinary skill in the art can use to determine whether a particular SNP is in LD with a queried SNP. The parameter r 2 is commonly used in the field of genetics to characterize the extent of linkage disequilibrium between markers (Hudson, 2001). As used herein, the term "in LD with" refers to a particular SNP measured at a sampled SNP above the threshold of a parameter such as r 2 .

It is now common practice to directly observe genetic variants in a sample of chromosomes obtained from a population. Suppose one has genotype data at two genetic markers located on the same chromosome, for markers A and B. Suppose further that two alleles separate at each of these two markers such that alleles A 1 and A 2 take on Marker A can be found and alleles B 1 and B 2 at marker B. Also assume that these two markers are on a human autosome. If one is to examine a particular individual and determine that they are heterozygous at both markers, such that their two-marker genotype is A1A2B1B2, then there are two possible configurations: the individual in question could have the alleles A1B1 on one chromosome and A2B2 on one have the remaining chromosome; alternatively, the individual could have the alleles A 1B 2 on one chromosome and A 2B 1 on the other. The arrangement of alleles on a chromosome is called a haplotype. In this representation, the individual could have haplotypes A1B1/A2B2 or A1B2/A2B1 (see Hartl and Clark (1989) for a more complete description). The concept of linkage equilibrium relates haplotype frequencies to allele frequencies.

Suppose a sample of individuals is selected from a larger population. Considering the two markers described above, each of which has two alleles, there are four possible haplotypes: A1B1, A1B2, A2B1, and A. sub.2B2. Denote the frequencies of these four haplotypes using the following notation.

P 11 = Frequenz (A 1B 1) (1)

P12 = frequency (A1B2) (2)

P 21 = frequency (A 2 ) (3)

P 22 = Frequency (A 2 B 2 ) (4)

The allele frequencies at the two markers are then the sum of different haplotype frequencies, it is easy to write a similar set of equations relating allele frequencies with one marker to haplotype frequencies with two markers:

p 1 = Frequency (A 1 ) = P 11 + P 12 (5)

p 2 = Frequency (A 2 ) = P 21 + P 22 (6)

q 1 = Frequency (B 1 ) = P 1 + P 21 (7)

q 2 = Frequency (B 2 ) = P 12 + P 22 (8)

Note that the four haplotype frequencies and the allele frequencies at each marker must add up to a frequency of 1.

P 11 + P 12 + P 21 + P 22 = 1 (9)

p 1 + p 2 = 1 (10)

q 1 + q 2 = 1 (11)

If there is no correlation between the alleles at the two markers, one would expect that the frequency of the haplotypes would be approximately the product of the composite alleles. For this reason,

P 11 ≈ p 1q 1 (12)

P 12 ≈ p 1q 2 (13)

P 21 ≈ p 2q 1 (14)

P 22 ≈ p 2q 2 (15)

These approximate equations (12)-(15) represent the concept of linkage equilibrium where there is independent choice between the two markers - the alleles at the two markers occur randomly together. These are presented as approximations since linkage balance and linkage disequilibrium are concepts typically considered to be properties of a chromosome sample; and as such they are susceptible to stochastic fluctuations due to the sampling process. Empirically, many pairs of genetic markers will be in linkage equilibrium, but certainly not all pairs.

Having established the concept of binding balance above, Applicants can now describe the concept of binding disequilibrium (LD), which is the deviation from binding balance. Since the frequency of the A 1 B 1 haplotype is approximately the product of the allele frequencies for A 1 and B 1 assuming linkage equilibrium, as indicated mathematically in (12), a simple measure of the amount of deviation from linkage equilibrium is the difference of these two sizes D,

D = P 11 – p 1q 1 (16)

D=0 indicates a perfect bond balance. Significant deviations from D = 0 indicate LD in the examined chromosome sample. Many properties of D are discussed in Lewontin (1964), including the maximum and minimum values ​​that D can take. Mathematically, using basic algebra, it can be shown that D can also only be written in terms of haplotypes:

D = P 11 P 22 – P 12 P 21 (17)

Transforming D by squaring and then dividing by the product of the allele frequencies of A 1 , A 2 , B 1 and B 2 , the resulting quantity, called r 2 , is equal to the square of Pearson's correlation coefficient, commonly used in statistics (e.g. Hoel, 1954).

r 2 = D 2 p 1 p 2 q 1 q 2 ( 18 )

As with D, values ​​of r 2 close to 0 indicate binding equilibrium between the two markers examined in the sample set. When the values ​​of r 2 increase, the two markers are said to be a linkage imbalance. The range of values ​​that r 2 can take is from 0 to 1. r 2 = 1 if there is a perfect correlation between the alleles at the two markers.

In addition, the amounts discussed above are sample specific. Therefore, it is necessary to formulate a notation specific to the samples being studied. In the approach discussed here, three types of samples are of primary interest: (i) a chromosome sample from individuals affected by a disease-associated phenotype (cases), (ii) a chromosome sample from individuals not affected by the disease-associated phenotype ( controls) and (iii) a standard sample set used for construction of haplotypes and calculation of pairwise-linked disequilibrium. For the allele frequencies used in developing the method described below, an additional subscript is added to designate either the case or control sample set.

p1,cs=freq(A1 in cases) (19)

p2,cs=freq(A2 in cases) (20)

q1,cs=freq(B1 in cases) (21)

q2,cs=freq(B2 in cases) (22)

Similar,

[0290] p 1 , ct = Freq (A 1 in Kontrollen) (23)

p2,ct=freq(A2 in Kontrollen) (24)

q 1,ct = frequency (B 1 in controls) (25)

q2,ct=freq(B2 in Kontrollen) (26)

Since a well-accepted sample set is necessary for robust coupling disequilibrium calculations, data obtained from the International HapMap project (The International HapMap Consortium 2003, 2005; Thorisson et al., 2005; McVean et al., 2005) can be used for the calculation of paired r 2 values ​​are used. In fact, the samples genotyped for the International HapMap project were chosen to be representative samples from different human subpopulations with a sufficient number of chromosomes examined to draw meaningful and reliable conclusions from the observed patterns of genetic variation. The International HapMap Project website (hapmap.org) contains a description of the project, methods used and samples examined. It is useful to examine empirical data to get a sense of the patterns present in such data.

[0292] Haplotype frequencies were explicit arguments in equation (18) above. However, knowledge of the 2-marker haplotype frequencies requires that this phase be determined for doubly heterozygous samples. If the phase is unknown in the data examined, various algorithms can be used to infer the phase from the genotype data. This problem was previously discussed where the doubly heterozygous individual with a 2-SNP genotype of A1A2B1B2 could have one of two different chromosome sets: A1/A2 .2B2 or A1B2/A2B1. One such algorithm for estimating haplotype frequencies is the expectation maximization (EM) algorithm, first proposed by Dempster et al. has been formalized. (1977). This algorithm is widely used in genetics to derive haplotype frequencies from genotype data (e.g. Excoffier and Slatkin (1995); Tregouet et al., (2004)). It should be noted that for the case studied here, with two SNPs, EM algorithms have very little error, provided allele frequencies and sample sizes are not too small. The influence on the r 2 values ​​is typically negligible.

[0293] Because correlated genetic markers share information, interrogating SNP markers in LD with a disease-associated SNP marker may also have sufficient power to detect disease association (Long and Langley (1999)). The relationship between the ability to find disease-associated alleles directly and the ability to indirectly detect disease associations was examined by Pritchard and Przeworski (2001). In a direct derivation, it can be shown that the strength to indirectly detect a disease association at a marker locus in a linkage disequilibrium with a disease association locus is approximately the same as the strength to detect a disease association directly at the disease association locus when the sample size becomes large by the factor elevated

1 r 2 ##EQU00002##

(the inverse of Equation 18) at marker versus disease association locus.

Therefore, if one calculates the potency for indirectly detecting a disease association using an experiment with N samples, then an equivalent potency for directly detecting a disease association (at the actual locus of disease susceptibility) would require an experiment using approximately r 2 N samples. This elementary relationship between power, sample size, and linkage disequilibrium can be used to derive an r 2 threshold useful for determining whether genotyping markers in linkage disequilibrium with a SNP marker directly associated with disease status has enough power to indirectly demonstrate disease association.

[0295] To begin deriving the ability to detect disease-associated markers by an indirect process, define the effective chromosomal sample size as

n = 4 N cs N ct N cs + N ct ; ( 27 ) ##EQU00003##

where Ncs and Nct are the number of diploid cases and controls, respectively. This is necessary to deal with situations where the number of cases and controls are not equivalent. For equal case and control sample sizes, Ncs=Nct=N, the effective chromosome number value is simply n=2N—as expected, P values ​​below a are considered statistically significant). Define the standard Gaussian distribution function as .PHI.(.cndot.). Mathematically,

.PHI. ( x ) = 1 2 &pgr; .intg. x - .infin. e - &thgr; 2 2 d &thgr;( 28 ) ##EQU00004##

Alternatively, the following error function notation (Erf) can also be used,

.PHI. ( x ) = 1 2 [ 1 + Erf ( x 2 ) ] ( 29 ) ##EQU00005##

For example, Φ(1.644854) = 0.95. The value of r 2 can be derived to give a predetermined minimum strength for evidence of disease association by indirect interrogation. Therefore, considering that the LD-SNP marker could be the one carrying the disease association allele, this approach represents a lower bound model in which all indirect performance outcomes are expected to be at least as large as those interrogated.

[0297] Denoted by the error rate for not detecting truly disease-associated markers. Therefore, 1-? is the classic definition of statistical power. If the Pritchard-Pzreworski result is used in the sample size, the validity of the evidence of a disease association at a significance level of a results from the approximation

1 - &bgr; .ca. .PHI. [q 1 , cs – q 1 , ct q 1 , cs (1 – q 1, cs ) + q 1 , ct (t – q 1 , ct) r 2 n – Z 1 – &agr; / 2 ] ; (30) ##EQU00006##

where Zu is the reciprocal of the standard cumulative normal distribution evaluated at u (u · di-elec cons. (0,1)). Zu = ? –1 (u), where Φ (Φ -1 (u)) = Φ -1 (Φ (u)) = u. For example, setting α = 0.05 and thus 1 - α/2 = 0.975 gives Z 0.975 = 1.95996. Next, the power is set equal to a minimum power threshold of T,

T = .PHI. [q 1 , cs – q 1 , ct q 1 , cs (1 – q 1 , cs) + q 1 , ct (1 – q 1 , ct) r 2 n – Z 1 – &agr; / 2 ] ( 31 )##EQU00007##

and solving for r² one obtains the following threshold r²:

r T 2 = q 1 , cs ( 1 – q 1 , cs ) + q 1 , ct ( 1 – q 1 , ct ) n ( q1 , cs – q 1 , ct ) 2 [.PHI. – 1 (T) + Z 1 – &agr; / 2 ] 2 Oder, ( 32 ) r T 2 = (Z T + Z 1 – &agr; / 2 ) 2 n [q 1 , cs – (q 1, cs ) 2 + q 1 , ct – (q 1 , ct ) 2 (q 1 , cs – q 1 , ct ) 2 ] (33 ) ##EQU00008##

[0298] Suppose that r 2 is calculated between a sampled SNP and a number of other SNPs with different LD levels with the sampled SNP. The threshold r T 2 is the minimum value of linkage disequilibrium between the interrogated SNP and the potential LD-SNPs such that the LD-SNP still retains a strength greater than or equal to T to detect a disease association. For example, assume that SNP rs200 is genotyped in a case-control disease association study and found to be associated with a disease phenotype. Suppose further that the minor allele frequency was detected at 16% in 1,000 case chromosomes, as opposed to an aminor allele frequency of 10% in 1,000 control chromosomes. Given these measurements, one could have predicted prior to the experiment that the strength of evidence of disease association at the 0.05 significance level was quite high - about 98% using an allelic association test. By applying Equation (32), one can calculate a minimum value of r 2 to indirectly assess disease association, assuming that the minor allele at SNP rs200 is truly disease predisposing to a threshold magnitude level. Setting the performance threshold to 80%, then rt 2 = 0.489 with the same level of significance and chromosome numbers as above. Therefore, any SNP with a pairwise r 2 value with rs 200 greater than 0.489 is expected to have greater than 80% strength to detect disease association. Furthermore, the conservative model is assumed here, in which the LD-SNP is disease-associated only through coupling imbalance with the queried SNP rs200.

[0299] The contribution or association of certain SNPs and/or SNP haplotypes with disease phenotypes such as stroke enables the use of the SNPs of the present invention to develop superior diagnostic tests capable of identifying individuals who have a detectable trait , such as stroke, result from a particular genotype, or individuals whose genotype puts them at increased or reduced risk of developing a detectable trait at a later time point compared to individuals who do not have that genotype. As described herein, diagnostics can be based on a single SNP or a group of SNPs. Combined detection of multiple SNPs (e.g. 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 24, 25 , 30, 32, 48, 50, 64, 96, 100, or any number in between or more of the SNPs provided in Table 1 and/or Table 2 typically increases the likelihood of an accurate diagnosis.For example, the presence of a single SNP from which known to correlate with stroke may indicate a 20% chance that a person is at risk of stroke, while detecting five SNPs, each correlated with stroke, could indicate an 80% chance in that person is at risk of suffering a stroke.To further increase the accuracy of diagnosis or predisposition screening, the analysis of the SNPs of the present invention can be combined with that of other polymorphisms or other stroke risk factors, such as disease symptoms, pathological features, family history, diet, environmental factors, or lifestyle factors, are combined.

Of course, those skilled in the art of treating, preventing, or diagnosing stroke will appreciate that the present invention is not generally intended to provide an absolute identification of individuals at risk (or lesser risk), suffering a stroke, and/or pathologies associated with stroke like other vascular diseases, but to indicate a certain increased (or decreased) degree or likelihood of developing the disease (e.g. a stroke) based on statistically significant association results. However, this information is extremely valuable as it can be used, for example, to initiate preventive treatments or to allow a person carrying one or more significant SNPs or SNPhaplotypes to anticipate warning signs such as minor clinical symptoms, or for regularly scheduled physical examinations for monitoring of the appearance of a disease in order to be able to recognize it early and start treatment. Especially for diseases that are extremely debilitating or fatal if not treated in time, knowledge of a potential predisposition, even if that predisposition is not absolute, would likely contribute in a very significant way to the effectiveness of the treatment.

The diagnostic techniques of the present invention can use a variety of methodologies to determine whether a test subject has an SNP or SNP pattern that is associated with an increased or decreased risk of developing a detectable trait, or whether the subject as As a result of a detectable trait, certain polymorphism/mutation suffers, including, for example, methods that allow analysis of individual chromosomes for haplotyping, family studies, single sperm DNA analysis or somatic hybrids. The feature analyzed using the diagnostics of the invention can be any detectable feature commonly observed in pathologies and disorders associated with stroke.

Another aspect of the present invention relates to a method for determining whether an individual is at risk (or less risk) of developing one or more traits, or if an individual expresses one or more traits as a result of having a particular trait that causes or causes trait influencing allele. These methods generally involve obtaining a nucleic acid sample from an individual and testing the nucleic acid sample to determine which nucleotide(s) is (are) present at one or more SNP positions, wherein the tested nucleotide(s) indicates an increased or decreased risk of development of the trait or indication that the individual is expressing the trait as a result of possession of a particular trait-causing or trait-affecting allele.

In another embodiment, the SNP detection reagents of the present invention are used to determine whether an individual has one or more SNP alleles that affect the level (e.g., the concentration of mRNA or protein in a sample, etc .) or affect the pattern (eg, the kinetics of expression, rate of degradation, stability profile, Km, Vmax, etc.) of gene expression (collectively, the "gene response" of a cell or body fluid). Such a determination can be made by screening for mRNA or protein expression (e.g. using nucleic acid arrays, RT-PCR, TaqMan assays or mass spectrometry), identifying genes with altered expression in a single genotyping of SNPs disclosed in Table 1 and/or Table 2 that could affect the expression of the genes with altered expression (e.g. SNPs located in and/or around the gene(s) with altered expression, SNPs in regulatory/ control regions, SNPs in and/or around other genes involved in signaling pathways that could affect the expression of the gene(s) with altered expression, or all SNPs could be genotyped) and correlating SNP genotypes with altered gene expression. In this way, specific SNP alleles at specific SNP sites that affect gene expression can be identified.

Pharmacogenomics and Therapeutics/Drug Development

[0305] The present invention provides methods for evaluating the pharmacogenomics of a subject carrying particular SNP alleles or haplotypes or diplotypes to a particular therapeutic agent or pharmaceutical compound or class of such compounds involved in response to drugs due to a altered drug disposition and/or abnormal effects in affected individuals. See e.g. B. Roses, Nature 405, 857-865 (2000); Gould Rothberg, Nature Biotechnology 19, 209-211 (2001); Eichelbaum, Clin. Adult Pharmacol. physiol. 23(10-11):983-985 (1996); and Linder, Clin. Chem. 43(2):254-266 (1997). The clinical results of these variations can lead to severe therapeutic drug toxicity in certain individuals or therapeutic drug failure in certain individuals as a result of individual metabolic variations. Thus, a person's SNP genotype can determine the way a therapeutic compound acts on the body or the way the body metabolizes the compound. For example, SNPs in drug metabolizing enzymes can affect the activity of these enzymes, which in turn can affect the intensity and duration of drug action as well as drug metabolism and clearance.

The discovery of SNPs in drug metabolizing enzymes, drug transporters, proteins for pharmaceutical drugs, and other drug targets has explained why some patients fail to achieve expected drug effects, exhibit exaggerated drug effects, or experience serious toxicity from standard drug dosages. SNPs can be expressed in the extensive metabolizer phenotype and in the poor metabolizer phenotype. Accordingly, SNPs can give rise to allelic variants of a protein, in which one or more protein functions in one population differ from those in another population. SNPs and the encoded peptide variants thus represent targets to determine a genetic predisposition that may influence treatment modality. For example, in a ligand-based treatment, SNPs can induce amino-terminal extracellular domains and/or other ligand-binding regions of a receptor that are more or less active upon ligand binding, thereby affecting subsequent protein activation modified to maximize therapeutic effect within a given population that contains particular SNP alleles or haplotypes.

[0307] As an alternative to genotyping, specific variant proteins could be identified that contain variant amino acid sequences encoded by alternative SNP alleles. Thus, pharmacogenomic characterization of an individual allows for the selection of effective compounds and effective dosages of such compounds for prophylactic or therapeutic uses based on the individual's SNP genotype, thereby improving and optimizing the efficacy of therapy. In addition, the production of recombinant cells and transgenic animals containing specific SNPs/haplotypes allows for effective clinical design and testing of treatment compounds and dosing schedules. For example, transgenic animals can be produced that differ only in specific SNP alleles in a gene orthologous to a human disease susceptibility gene.

[0308] Pharmacogenomic uses of the SNPs of the present invention offer several significant advantages in patient care, particularly in the treatment of stroke. Pharmacogenomic characterization of an individual, based on an individual's SNP genotype, can identify those individuals who are unlikely to respond to treatment with a particular drug, thereby allowing physicians to avoid prescribing the ineffective drug to these individuals. On the other hand, SNP genotyping of an individual may allow physicians to select the appropriate medication and dosage that will be most effective based on an individual's SNP genotype. This information increases a physician's confidence in prescribing medication and motivates patients to adhere to their medication regimens. In addition, pharmacogenomics can identify patients susceptible to toxicity and adverse reactions to specific drugs or drug doses. Adverse drug reactions result in more than 100,000 preventable deaths each year in the United States alone, and are therefore a significant cause of hospitalizations and deaths, as well as a significant economic burden on the health care system (Pfoset al., Trends in Biotechnology, August 2000. ). Thus, pharmacogenomics based on the SNPs disclosed here has the potential to both save lives and significantly reduce healthcare costs.

It is also well known in the art that markers that are diagnostically useful to distinguish patients at higher risk for developing a disease (such as stroke) from those who are at reduced risk for developing the disease may be useful in identifying those patients who are at higher risk and are likely to respond to drug treatments that target signaling pathways involving genes in which the diagnostic SNPs are located. See references Gerdes, et al., Circulation, 2000; 101:1366-1371, Kuivenhoven, et al., N Engl J Med 1998; 338:86-93, Stolarz, et al., Hypertension 2004; 44:156-162, Chartier-Harlin, et al., Hum. Mol. Genet. Apr 1994; 3(4):569-74, Roses, et al., The Pharmacogenomics Journal 2006, 1-19.

In this regard, embodiments of the present invention may be very useful in assisting clinicians in selecting individuals who are more likely to have stroke and who are therefore good candidates for therapy to prevent or treat stroke, thereby administering the above is justified -mentioned drug treatments for such persons. On the other hand, using the SNP markers discovered here, individuals thought to be at low risk of suffering a stroke can reduce the aggravation and waste of drug treatment due to the reduced benefit of such treatment in terms of its cost and potential side effects be spared.

Pharmacogenomics in general is further discussed in Rose et al., "Pharmacogenetic analysis of clinically relevant genetic polymorphisms", Methods Mol Med. 2003; 85:225-37. The pharmacogenomics related to Alzheimer's disease and other neurodegenerative diseases is discussed in Cacabelos, "Pharmacogenomics for the treatment of dementia", Ann Med. 2002; 34(5):357-79, Maimone et al., "Pharmacogenomics of neurodegenerative diseases", Eur JPharmacol. Feb 9, 2001; 413(1):11-29, and Poirier, "Apolipoprotein E: a pharmacogenetic target for the treatment of Alzheimer's disease", Mol Diagn. 1999 December; 4(4):335-41. The pharmacogenomics relating to cardiovascular disorders is discussed in Siest et al., "Pharmacogenomics of drugs affecting the cardiovascular system", Clin. Chem. Lab. Med. April 2003; 41(4):590-9, Mukherjee et al., "Pharmacogenomics in cardiovascular diseases", Prog CardiovascDis. 2002 May-June; 44(6):479-98, and Mooser et al., Cardiovascular pharmacogenetics in the SNP era, J Thromb Haemost. July 2003; 1(7):1398-402. Pharmacogenomics related to cancer is discussed in McLeod et al., "Cancer pharmacogenomics: SNPs, chips, and the individual patient", Cancer Invest. 2003;21(4):630-40 and Watters et al., "Cancer pharmacogenomics: current and future applications", Biochim Biophys Acta. 2003 Mar 17;1603(2):99-111.

The SNPs of the present invention can also be used to identify novel therapeutic targets for stroke. For example, genes containing the disease-associated variants ("variant genes") or their products, as well as genes or their products that are directly or indirectly regulated by or interact with these variant genes or their products, may be targeted for the development of therapeutics. which, for example, treat the disease or prevent or delay the onset of the disease. The therapeutics can consist, for example, of small molecules, proteins, protein fragments or peptides, antibodies, nucleic acids or their derivatives, or mimetics that modulate the functions or levels of the target genes or gene products.

[0313] The SNP-containing nucleic acid molecules disclosed herein and their complementary nucleic acid molecules can be used as antisense constructs to control gene expression in cells, tissues and organisms. Antisense technology is well established in the art and is discussed in detail in Antisense Drug Technology: Principles, Strategies, and Applications, Crooke (ed.), Marcel Dekker, Inc.: New York (2001). An antisense nucleic acid molecule is generally designed to be complementary to a region of mRNA expressed by an agent such that the antisense molecule hybridizes to the mRNA and thereby blocks translation of mRNA into protein. Various classes of antisense oligonucleotides are used in the prior art, two of which are cleavers and blockers. By binding to target RNAs, cleavers activate intracellular nucleases (e.g. RNaseH or RNase L), which cleave the target RNA. Blockers that also bind to target RNAs inhibit protein translation by steric hindrance of ribosomes. Exemplary blockers include peptide nucleic acids, morpholinos, latched nucleic acids, and methylphosphonates (see, e.g., Thompson, Drug Discovery Today, 7(17):912-917 (2002)). Antisense oligonucleotides are useful directly as therapeutic agents and are also useful for determining and validating gene function (e.g., ingene knock-out or knock-down experiments).

Antisense technology is further discussed in: Lavery et al., "Antisense and RNAi: powerful tools in drug target discovery and validation", Curr Opin Drug Discov Devel. 2003 July; 6(4):561-9; Stephens et al., "Antisense Oligonucleotide Therapy in Cancer", Curr Opin Mol Ther. April 2003; 5(2):118-22; Kurreck, "Antisense Technologies. Improvement by Novel Chemical Modifications", Eur J Biochem. April 2003; 270(8):1628-44; Dias et al., "Antisense oligonucleotides: basic concepts and mechanisms", Mol Cancer Ther. 2002, March; 1(5):347-55; Chen, "Clinical Development of Antisense Oligonucleotides as Anticancer Therapeutics," Methods Mol Med.2003; 75:621-46; Wang et al., "Antisense anticancer oligonucleotide therapeutics", Curr Cancer Drug Targets. 2001 Nov;1(3):177-96; and Bennett, "Efficiency of antisense oligonucleotide drug discovery", Antisense Nucleic Acid Drug Dev. 2002 June;12(3):215-24.

The SNPs of the present invention are particularly useful for designing antisense reagents specific for particular nucleic acid variants. Based on the SNP information disclosed herein, antisense oligonucleotides can be prepared that specifically target mRNA molecules containing one or more particular SNP nucleotides. In this way, the expression of mRNA molecules containing one or more undesired polymorphisms (e.g. SNP nucleotides resulting in a defective protein, such as an amino acid substitution in a catalytic domain) can be inhibited or blocked completely. Thus, antisense oligonucleotides can be used to specifically bind to a particular polymorph (e.g., an SNP allele encoding a defective protein), thereby inhibiting translation of that form but not to an alternative polymorph bind (e.g. an alternative SNP nucleotide encoding a protein with normal function).

[0316] Antisense molecules can be used to inactivate mRNA to inhibit gene expression and the production of defective proteins. Accordingly, these molecules can be used to treat a disorder, such as stroke, that is characterized by abnormal or unwanted gene expression or expression of certain defective proteins. This technique may involve cleavage using ribozymes that contain nucleotide sequences complementary to one or more regions in the mRNA that attenuate the mRNA's ability to be translated. Possible mRNA regions include, for example, protein-coding regions and in particular protein-coding regions corresponding to catalytic activities, substrate/ligand binding or other functional activities of a protein.

The SNPs of the present invention are also useful for designing RNA interference reagents that specifically target nucleic acid molecules with particular SNP variants. RNA interference (RNAi), also known as gene silencing, is based on the use of double-stranded RNA molecules (dsRNA) to turn off genes. When dsRNAs are introduced into a cell, dsRNAs are processed by the cell into short fragments (generally about 21, 22, or 23 nucleotides long), known as small interfering RNAs (siRNAs), which the cell uses sequence-specifically to form complementary RNAs to detect and destroy (Thompson, Drug Discovery Today, 7 (17): 912-917 (2002)). Accordingly, one aspect of the present invention contemplates specifically isolated nucleic acid molecules that are about 18-26 nucleotides in length, preferably 19-25 nucleotides in length, and more preferably 20, 21, 22 or 23 nucleotides in length, and the use of said nucleic acid Da RNAi- molecules, including siRNAs, act in a sequence-specific manner, the SNPs of the present invention can be used to design RNAi reagents that target nucleic acid molecules with specific SNP alleles/nucleotides (such as production of defective proteins), while nucleic acid molecules with alternative SNP alleles Alleles (such as alleles that code for proteins with normal function) are not affected. As with antisense reagents, RNAi reagents can be useful directly as therapeutics (e.g. knocking out defective, disease-causing genes) and are also useful for characterizing and validating gene function (e.g. in gene knock-out or knock -Down experiments).

The following references provide a further review of RNAi: Reynolds et al., "Rational siRNA design for RNA interference", Nat Biotechnol. 2004 March; 22(3):326-30. Epub Feb 1, 2004; Chi et al., "Genomewide view of gene silencing by small interfering RNAs", PNAS100(11):6343-6346, 2003; Vickers et al., "Efficient Reduction of Target RNAs by Small Interfering RNA and RNase H-dependent Antisense Agents", J. Biol. Chem. 278: 7108-7118, 2003; Agami, “RNAi and Related Mechanisms and Their Potential Use for Therapy,” Curr Opin Chem Biol. 2002 December; 6(6):829-34; Lavery et al., “Antisense and RNAi: powerful tools in drug target discovery and validation,” Curr Opin Drug Discov Devel. 2003 July; 6(4):561-9; Shi Mammalian RNAi for the masses Trends Genet 2003 Jan;19(1):9-12 Shuey et al. RNAi: gene-silencing in therapy intervention Drug Discovery Today 2002 Oct; 7(20):1040-1046; McManus et al., Nat. Rev. Genet, October 2002; 3(10):737-47; Xia et al., Nat Biotechnol 2002 October; 20(10):1006-10; Plasterk et al., Curr Opin Genet Dev 2000 October; 10(5):562-7; Bosher et al., NatCell Biol 2000 February; 2(2):E31-6; and Hunter, Curr Biol 1999 Jun. 17; 9(12):R440-2).

A subject suffering from a pathological condition, such as stroke, that is attributed to an SNP can be treated to correct the genetic defect (see Kren et al., Proc. Natl. Acad. Sci. USA96:10349 –10354 (1999) ). Such a subject can be identified by any method capable of detecting the polymorphism in a biological sample taken from the subject. Such a genetic defect can be permanently corrected by administering to such a subject a nucleic acid fragment containing a repair sequence that provides the normal/wild-type nucleotide at the position of the SNP. This site-directed repair sequence may comprise an RNA/DNA oligonucleotide that acts to promote endogenous repair of a subject's genomic DNA. The site-directed repair sequence is administered in a suitable vehicle, such as a complex with polyethyleneimine encapsulated in anionic liposomes, a viral vector such as an adenovirus, or other pharmaceutical composition that promotes intracellular uptake of the administered nucleic acid. A genetic defect leading to an inherited pathology can then be overcome as the chimeric oligonucleotides induce integration of the normal sequence into the individual's genome. Upon incorporation, the normal gene product is expressed and the surrogate propagated, causing permanent restoration and therapeutic improvement in the subject's clinical condition.

In cases where a cSNP results in a protein variant that is imputed to be a causative or contributing factor to an apathological condition, a method of treating such a condition may involve administration of the wild-type/normal relative of the variant protein. Once administered in an effective dosage regimen, the wild-type relative provides supplementation or remediation of the pathological condition.

The invention further provides a method of identifying a compound or agent that can be used to treat or prevent stroke. The SNPs disclosed herein are useful as targets for the identification and/or development of therapeutic agents. A method for identifying a therapeutic agent or compound typically involves testing the ability of the agent or compound to modulate the activity and/or expression of a SNP-containing nucleic acid or the encoded product, and thus identifying an agent or compound, which can be used to treat a disorder characterized by unwanted activity or expression of the SNP-containing nucleic acid or encoded product. The assays can be performed in cell-based and cell-free systems. Cell-based assays can involve cells that naturally express the nucleic acid molecules of interest or recombinant cells that have been genetically engineered to express particular nucleic acid molecules.

[0322] Differential gene expression in a stroke patient may, for example, either involve the expression of a SNP-containing nucleic acid sequence (e.g., a gene containing a SNP may be transcribed into an mRNA transcript molecule containing the SNP, which in turn may be translated into a protein variant) or altered expression of a normal/wild-type nucleic acid sequence due to one or more SNPs (e.g., a regulatory/control region may contain a SNP that affects the level or pattern of expression of a normal transcript).

[0323] Assays for variant gene expression may involve direct assays of nucleic acid levels (e.g., mRNA levels), expressed protein levels, or by-compounds involved in a signaling pathway. Furthermore, the expression of genes that are up- or down-regulated in response to the signaling pathway can also be tested. In this embodiment, the regulatory regions of these genes may be operably linked to a reporter gene such as luciferase.

[0324] Modulators of variant gene expression can be identified in a method in which, for example, a cell is contacted with a candidate compound/drug and the expression of mRNA is determined. The level of expression of mRNA in the presence of the candidate compound is compared to the level of expression of mRNA in the absence of the candidate compound. The candidate compound can then be identified based on this comparison as a modulator of variant gene expression and used to treat a disease such as stroke that is caused by variant gene expression (eg, either expression of a SNP-containing nucleic acid or altered expression of a normal/wild Nucleic acid) is characterized -type nucleic acid molecule due to one or more SNPs affecting the expression of the nucleic acid molecule) due to one or more SNPs of the present invention. If expression of mRNA is statistically significantly greater in the presence of the candidate compound than in its absence, the candidate compound is identified as a stimulator of nucleic acid expression. If nucleic acid expression is statistically significantly lower in the presence of the candidate compound than in its absence, the candidate compound is identified as an inhibitor of nucleic acid expression.

The invention further provides methods of treatment with the SNP or associated nucleic acid domain (e.g., catalytic domain, ligand/substrate binding domain, regulatory/control region, etc.) or the gene or encoded mRNA transcript as a target, using a compound identified by drug screening as a gene modulator to modulate the nucleic acid expression variant. Modulation can involve either up-regulation (i.e., activation or agonization) or down-regulation (i.e., repression or antagonism) of nucleic acid expression.

[0326] Expression of mRNA transcripts and encoded proteins, either wild-type or variant, may be altered in individuals with a particular SNP allele in a regulatory/control element, such as a promoter or transcription factor-binding domain, that regulates expression . In this situation, as discussed herein, treatment methods and compounds can be identified that regulate or overcome the aberrant regulatory/control element, thereby producing normal or healthy levels of expression of either the wild-type or variant protein.

[0327] The SNP-containing nucleic acid molecules of the present invention are also useful for monitoring the effectiveness of modulating compounds on the expression or activity of a variant gene or encoded product in a clinical trial or in a treatment regimen. Thus, the gene expression pattern can serve as an indicator of the continued efficacy of compound treatment, particularly for compounds to which a patient may develop resistance, and as an indicator of toxicities. The gene expression pattern can also serve as a marker indicating a physiological response of the affected cells to the compound. Accordingly, such monitoring would allow for either increased administration of the compound or administration of alternative compounds to which the patient has not developed resistance. Similarly, if the level of nucleic acid expression falls below a desirable level, administration of the compound could be correspondingly reduced.

In a further aspect of the present invention there is provided a pharmaceutical pack comprising a therapeutic agent (e.g. a small molecule drug, antibody, peptide, antisense or RNA nucleic acid molecule, etc.) and a set of instructions for administering the Therapeutic agent for humans who have been diagnostically tested for one or more SNPs or SNP haplotypes provided by the present invention.

The SNPs/haplotypes of the present invention are also useful to improve many different aspects of the drug development process. For example, one aspect of the present invention includes selecting individuals for clinical trials based on their SNP genotype. For example, people with SNP genotypes that indicate they are likely to respond positively to a drug may be included in the studies, while people whose SNP genotypes indicate that they are less likely to respond to the drug or have no response would, or who are at risk of suffering toxic effects or other side effects, may be excluded from the clinical trials. Not only can this improve the safety of clinical trials, but it can also increase the chances that the trial will show statistically significant efficacy. In addition, the SNPs of the present invention can explain why certain previously developed drugs have performed poorly in clinical trials and can help identify a subset of the population that would benefit from a drug that has previously performed poorly in clinical trials. thereby "rescuing" previously developed drugs and enabling the drug to be made available to a specific population of stroke patients who may benefit from it.

SNPs have many important uses in drug discovery, screening, and drug development. There is a high probability that for any gene/protein selected as a potential drug target, variants of that gene/protein will exist in a patient population. Therefore, determining the impact of gene/protein variants on the selection and administration of a therapeutic agent should be an integral aspect of the drug discovery and development process. (Jazwinska, A Trends Guide to Genetic Variation and Genomic Medicine, March 2002; S30-S36).

Knowledge of variants (e.g., SNPs and any corresponding amino acid polymorphisms) of a given therapeutic target (e.g., a gene, mRNA transcript, or protein) allows parallel screening of the variants to identify therapeutic candidates (e.g., to identify small molecule compounds) (e.g. antibodies, antisense or RNAi nucleic acid compounds, etc.) that show efficacy across variants (Rothberg, Nat Biotechnol 2001 March;19(3):209-11). Such therapeutic candidates would be expected to demonstrate equivalent efficacy over a larger segment of the patient population, leading to a larger potential market for the therapeutic candidate.

[0332] Furthermore, identifying variants of a potential therapeutic target allows the most common form of the target to be used for the selection of therapeutic candidates, thereby ensuring that the experimental activity observed for the selected candidates is actually that expected Activity reflects most of a patient population (Jazwinska, A Trends Guide to Genetic Variation and Genomic Medicine, March 2002; S30-S36).

In addition, screening therapeutic candidates against all known variants of a target may allow early identification of potential toxicities and side effects related to particular variants. For example, variability in drug absorption, distribution, metabolism, and excretion (ADME) caused by, for example, SNPs in therapeutic targets or drug-metabolizing genes can be identified, and this information can be used during the drug development process to predict the Minimize variability in drug disposition and develop therapeutics that are safer for a broader spectrum of a patient population. The SNPs of the present invention, including the protein variants and encoding polymorphic nucleic acid molecules provided in Tables 1-2, are useful in connection with a variety of art-established toxicological methods, such as those described in Current Protocols in Toxicology, John Wiley & Sons, Inc., NY

In addition, therapeutic agents targeting any protein (or nucleic acid molecule, either RNA or DNA) known in the art may cross-react with the protein variants (or polymorphic nucleic acid molecules) disclosed in Table 1, thereby altering the pharmacokinetic properties of the Drug are significantly affected. Accordingly, the protein variants disclosed in Tables 1-2 and the SNP-containing nucleic acid molecules are useful in developing, screening and evaluating therapeutic agents that target corresponding protein forms (or nucleic acid molecules) known in the art. In addition, as discussed above, knowledge of all polymorphic forms of a particular drug target enables the design of therapeutic agents effective against most or all such polymorphic forms of the drug target.

[0335] Pharmaceutical compositions and their administration

[0336] Any of the stroke-associated proteins and encoding nucleic acid molecules disclosed herein can be used as therapeutic targets (or used directly themselves as therapeutic compounds) for the treatment or prevention of stroke and related pathologies, and the present disclosure enables therapeutic compounds (eg, small molecules, antibodies, therapeutic proteins, RNAi and antisense molecules, etc.) that target (or consist of) any of these therapeutic targets.

In general, a therapeutic compound is administered in a therapeutically effective amount by any of the accepted modes of administration for agents that serve similar purposes. The actual amount of the therapeutic compound of this invention, i. H. of the active ingredient, depends on numerous factors, such as the severity of the disease being treated, the age and relative health of the subject, the potency of the compound used, the route and form of administration, and other factors.

[0338] Therapeutically effective amounts of therapeutic compounds may range, for example, from about 0.01-50 mg per kilogram of recipient body weight per day; preferably about 0.1-20 mg/kg/day. For example, for administration to a 70 kg individual, the most preferred dosage range would be about 7 mg to 1.4 g per day.

In general, therapeutic compounds are administered as pharmaceutical compositions by one of the following routes: oral, systemic (e.g., transdermal, intranasal, or by suppository), or parenteral (e.g., intramuscular, intravenous, or subcutaneous). The preferred mode of administration is oral or parenteral using a convenient daily dosage regimen which can be adjusted according to the degree of the disease. Oral compositions may take the form of tablets, pills, capsules, semi-solids, powders, sustained release formulations, solutions, suspensions, elixirs, aerosols, or other suitable compositions.

The choice of formulation depends on various factors such as the mode of drug administration (e.g., for oral administration, tablet, pill or capsule formulations are preferred) and the bioavailability of the drug substance. Recently, pharmaceutical formulations have been developed specifically for drugs that show poor bioavailability based on the principle that bioavailability can be increased by increasing the surface area, i. H. Reducing the particle size, can be increased. For example, US Pat. No. 4,107,288 describes a pharmaceutical formulation with particles ranging in size from 10 to 1000 nm in which the active material is supported on a cross-linked matrix of macromolecules. US Pat.No. 5,145,684 describes the preparation of a pharmaceutical formulation in which the drug substance is pulverized into clay nanoparticles (average particle size of 400 nm) in the presence of a surface modifier and then dispersed in a liquid medium to give a pharmaceutical formulation exhibiting remarkably high bioavailability.

[0341] Pharmaceutical compositions generally consist of a therapeutic compound in combination with at least one pharmaceutically acceptable excipient. Acceptable excipients are non-toxic, aid in administration, and do not adversely affect the therapeutic benefit of the therapeutic compound. Such excipients can be any solid, liquid, semi-solid or, in the case of an aerosol composition, gaseous excipients which are generally available to those skilled in the art.

Solid pharmaceutical excipients include starch, cellulose, talc, glucose, lactose, sucrose, gelatin, malt, rice, flour, chalk, silica gel, magnesium stearate, sodium stearate, glycerol monostearate, sodium chloride, dried skim milk, and the like. Liquid and semi-solid excipients may be selected from glycerol, propylene glycol, water, ethanol and various oils including those of petroleum, animal, vegetable or synthetic origin, e.g. peanut oil, soybean oil, mineral oil, sesame oil, etc. Preferred liquid carriers, particularly for injectable solutions, include water, saline, aqueous dextrose, and glycols.

Compressed gases can be used to disperse a compound of this invention in aerosol form. Suitable inert gases for this are nitrogen, carbon dioxide, etc.

Other suitable pharmaceutical excipients and their formulations are described in Remington's Pharmaceutical Sciences, edited by E.W. Martin (Mack Publishing Company, 18th edition, 1990).

[0345] The amount of therapeutic compound in a formulation may vary within the full range employed by those skilled in the art based on the therapeutic compound of the total formulation, with the remainder being one or more suitable pharmaceutical excipients. Preferably, the compound is present in an amount of about 1-80% by weight.

Therapeutic compounds can be administered alone or in combination with other therapeutic compounds or in combination with one or more other active ingredients. For example, an inhibitor or stimulator of a stroke-associated protein can be administered in combination with another agent that inhibits or stimulates the activity of the same or another stroke-associated protein to thereby counteract the effects of the stroke.

For more information on pharmacology, see Current Protocols in Pharmacology, John Wiley & Sons, Inc., N.Y.

[0348] Human Identification Applications

In addition to their diagnostic, risk assessment, preventive, and therapeutic uses in stroke and related pathologies, the SNPs provided by the present invention are also useful as human identification markers for such applications as forensics, paternity testing, and biometrics (see, B. Gill, " Eine Assessing the utility of single nucleotide polymorphisms (SNPs) for forensic purposes", Int. J. Legal Med. 2001; 114(4-5): 204-10). as genetic markers to identify individuals and to match a biological sample to an individual. Determining which nucleotides occupy a set of SNP positions in an individual identifies a set of SNP markers that distinguishes the individual. The more SNP positions analyzed, the lower the probability that the set of SNPs in one individual is the same as in an unrelated individual. When multiple sites are analyzed, the sites are preferably unrelated (i.e., independently inherited). Thus, preferred sets of SNPs can be selected from the SNPs disclosed herein, which can include SNPs on different chromosomes, SNPs on different chromosome arms, and/or SNPs distributed over significant distances along the same chromosome arm.

Among the SNPs disclosed herein also include preferred SNPs for use in certain forensic/human identification applications SNPs located at degenerate codon positions (i.e., the third position in certain codons that can and still are one of two or more alternative nucleotides encode the same amino acid) since these SNPs do not affect the encoded protein. SNPs that do not affect the encoded protein are expected to be under less selective pressure and therefore more polymorphic in a population, which is typically an advantage for forensic/human identification applications. For certain applications in forensics/human identification, e.g. However, when predicting phenotypic traits (e.g., inferring parentage or inferring one or more physical characteristics of an individual) from a DNA sample, it may be desirable to use SNPs that affect the encoded protein.

[0351] For many of the SNPs disclosed in Tables 1-2 (identified as the "Applera" SNP source), Tables 1-2 provide SNP allele frequencies obtained by resequencing the DNA of chromosomes from 39 individuals (Tables 1-2 also provide allele frequency information for "Celera" source SNPs and, where available, public SNPs from dbEST, HGBASE and/or HGMD). The allele frequencies provided in Tables 1-2 allow these SNPs to be readily used for human identification applications. Although any SNP disclosed in Table 1 and/or Table 2 could be used to identify humans, the closer to 50% the frequency of the minor allele at a particular SNP site is to 50%, the greater the ability of that SNP to be discriminated between different individuals in in a population it becomes increasingly likely that two randomly selected individuals would have different alleles at that SNP site. Using the SNP allele frequencies provided in Tables 1-2, one of ordinary skill in the art could easily select a subset of SNPs for which the frequency of the minor allele is at least 1%, 2%, 5%, 10%, for example. 20%, 25%, 30%, 40%, 45% or 50% or any frequency in between. Since Tables 1-2 provide allele frequencies based on the sequencing of the chromosomes of 39 individuals, a subset of SNPs could easily be selected for human identification, in which the total number of alleles of the minor allele at a given SNP site, for example, is at least 1, 2 , 4, 8, 10, 16, 20, 24, 30, 32, 36 is .38, 39, 40 or any number in between.

[0352] In addition, Tables 1-2 also provide information on population groups (referred to interchangeably herein as ethnic or racial groups) coupled with the detailed allele frequency information. For example, the group of 39 people whose DNA was resequenced consisted of 20 Caucasians and 19 African Americans. This population group information allows further refinement of SNP selection for human identification. For example, preferred SNPs for human identification can be selected from Tables 1-2 that have similar allele frequencies in both the Caucasian and African American populations; for example, SNPs can be selected that have the same selectivity in both populations. Alternatively, SNPs can be selected for which there is a statistically significant difference in allele frequency between the Caucasian and African-American populations (as an extreme example, a particular allele may only be observed in either the Caucasian or African-American population but not in the other population ); such SNPs are useful, for example, to predict the race/ethnicity of an unknown perpetrator from a biological sample, such as a hair or blood stain found at a crime scene. For a discussion of using SNPs to predict ancestry from a DNA sample, including statistical methods, see Frudakis et al., "A Classifier for the SNP-Based Inference of Ancestry," Journal of Forensic Sciences 2003; 48(4):771-782.

[0353] SNPs have numerous advantages over other types of polymorphic markers, such as short tandem repeats (STRs). For example, SNPs can be easily scored and amenable to automation, making SNPs the markers of choice for large forensic databases. SNPs are found in much greater abundance throughout the genome than repeat polymorphisms. Population frequencies of two polymorphs can usually be determined with greater accuracy than that of multiple polymorphs at multiallelic loci. SNPs are more mutation stable than repeat polymorphisms. SNPs are not prone to artifacts such as stutter bands that can hamper analysis. Stutter bands are common when analyzing repetitive polymorphisms and are particularly problematic when analyzing samples such as B. Crime scene samples, which may contain mixtures of DNA from multiple sources. Another significant advantage of SNP markers over STR markers is the much shorter nucleic acid length needed to assess an SNP. For example, STR markers are generally several hundred base pairs in length. On the other hand, a SNP comprises a single nucleotide and generally a short conserved region either side of the SNP position for primer and/or probe binding. This makes SNPs more amenable to typing in severely degraded or aged biological samples, often encountered in forensic casework, where DNA can be fragmented into short pieces.

[0354] SNPs are also not subject to the microvariant and "off-ladder" alleles commonly encountered when analyzing STR loci at the same rate as reference alleles with normal-sized repeat units. When separated by size, such as by electrophoresis on a polyacrylamide gel, microvariants do not align to a reference allelic ladder of standard-sized repeat units, but migrate between the reference alleles. The reference allelic ladder is used to accurately size alleles for allele classification; Therefore, alleles that do not match the reference allelic ladder lead to significant analysis problems. Additionally, analysis of multiallelic repeat polymorphisms will occasionally find an allele composed of more or fewer repeat units than previously seen in the population, or more or fewer repeat alleles contained in a reference allelic ladder. These alleles migrate outside the size range of known alleles in a reference allelic ladder and are therefore referred to as "off-ladder" alleles. In extreme cases, the allele may contain so few or so many repeats that it wanders far out of the range of the reference allelic ladder. In this situation, the allele may not even be observed, or it may migrate within or near the size range for another locus in the multiplex analysis, providing another confounding analysis.

[0355] SNP analysis avoids the problems of microvariants and off-ladder alleles encountered in STR analysis. Importantly, microvariants and off-ladder alleles present significant problems and can be completely overlooked when using analytical methods such as oligonucleotide hybridization arrays, which use oligonucleotide probes specific to certain known alleles, correctly typed, can result in improper statistical analysis analysis as their frequency in the population is generally unknown or poorly characterized and therefore the statistical significance of a matched genotype may be questionable. All of these benefits of SNP analysis are significant given the consequences of most DNA identification cases, which can result in life imprisonment for an individual or reassignment of remains to a deceased person's family.

DNA can be isolated from biological samples such as blood, bone, hair, saliva or semen and compared to DNA from a reference source at specific SNP positions. Multiple SNP markers can be tested simultaneously to increase the distinctiveness and statistical significance of a matched genotype. For example, oligonucleotide arrays can be used to genotype large numbers of SNPs simultaneously. The SNPs provided by the present invention can be tested in combination with other polymorphic genetic markers, such as other SNPs or STRs known in the art, to identify an individual or to match an individual to a particular biological sample.

In addition, the SNPs provided by the present invention may be genotyped for inclusion in a database of DNA genotypes, for example a criminal DNA database such as the FBI's Combined DNA Index System (CODIS) database. A genotype obtained from a biological sample of unknown source can then be queried in the database to find a matching genotype, the SNPs of the present invention providing nucleotide positions at which the known and unknown DNA sequences can be compared for identity. Accordingly, the present invention provides a database comprising novel SNPs or SNP alleles of the present invention (e.g., the database may comprise information indicating which alleles individual members of a population possess at one or more novel SNP sites of the present invention ), such as forensics, biometrics, or other human identification applications. Such a database typically comprises a computerized system in which the SNPs or SNP alleles of the present invention are recorded on a computer-readable medium (see the section of this specification entitled "Computer-Related Embodiments").

The SNPs of the present invention can also be tested for use in paternity testing. The purpose of the paternity test is usually to determine whether a man is the father of a child. In most cases, the child's mother is known and thus the mother's contribution to the child's genotype can be traced. The paternity test examines whether the part of the child's genome that cannot be assigned to the mother matches that of the putative father. Paternity testing can be performed by analyzing sets of polymorphisms in the putative father and child, the SNPs of the present invention providing nucleotide positions at which the DNA sequences of the putative father and child can be compared for identity. If the set of polymorphisms in the child attributable to the father does not agree with the putative father's set of polymorphisms, barring experimental error, it can be concluded that the putative father is not the child's father. If the set of polymorphisms in the child attributable to the father matches the putative father's set of polymorphisms, a statistical calculation can be performed to determine the probability of a random match and a conclusion drawn as to the probability that the alleged father is the true biological father of the child.

[0359] In addition to paternity testing, SNPs are also useful for other types of kinship testing, such as verifying family relationships for immigration purposes or in cases where a person claims to be related to a deceased person in order to obtain an inheritance from the deceased person to claim individual, etc. For more information regarding the usefulness of SNPs for paternity testing and other types of relatedness testing, including methods for statistical analysis, see Krawczak, "Informativity Assessment forbiallelic single nucleotide polymorphisms", Electrophoresis 1999 June; 20(8):1676-81.

The use of the SNPs of the present invention to identify humans also extends to various authentication systems, commonly referred to as biometric systems, which typically convert physical characteristics of humans (or other organisms) into digital data. Biometric systems include various technological devices that measure such unique anatomical or physiological features as finger, thumb or palm prints; hand geometry; vein pattern on the back of the hand; blood vessel pattern of the retina and color and texture of the iris; facial features; language patterns; signature and writing dynamics; andDNA. Such physiological measurements can be used to verify identity and, for example, restrict or allow access based on identification. Examples of applications for biometrics include physical area security, computer and network security, airline passenger check-in and boarding, financial transactions, access to medical records, distribution of government benefits, voting, law enforcement, passports, visas and immigration, prisons, various military applications, and restricted access expensive, dangerous items such as cars or guns (see, for example, O'Connor, Stanford Technology Law Review and US Patent No. 6,119,096).

Groups of SNPs, particularly the SNPs provided by the present invention, can be typed to uniquely identify an individual for biometric applications such as those described above. Such SNP typing can be readily performed using, for example, DNA chips/arrays. Preferably, a minimally invasive means of obtaining a DNA sample is used. For example, PCR amplification allows obtaining sufficient amounts of DNA for analysis from cheek swabs or fingerprints containing DNA-containing skin cells and oils that are naturally transferred upon contact B. Current Protocols in Human Genetics, John Wiley & Sons, N.Y. (2002), 14.1-14.7.

Variants of proteins, antibodies, vectors and host cells and uses thereof

[0362] Protein variants encoded by SNP-containing nucleic acid molecules

The present invention provides SNP-containing nucleic acid molecules, many of which encode proteins that have different amino acid sequences compared to those (i.e., wild-type) proteins known in the art. Amino acid sequences encoded by the polymorphic nucleic acid molecules of the present invention are provided as SEQ IDNOS: 81-160 in Table 1 and the Sequence Listing. These variants are generically referred to herein as variant proteins/peptides/polypeptides or polymorphic proteins/peptides/polypeptides of the present invention. The terms "protein", "peptide" and "polypeptide" are used interchangeably herein.

[0364] A protein variant of the present invention may be encoded, for example, by a non-synonymous nucleotide substitution at any of the cSNP positions disclosed herein. In addition, variant proteins can also include proteins whose expression, structure and/or function is altered by a SNP disclosed herein, such as e.g. a SNP that creates or destroys a stop codon, a SNP that affects splicing, and a SNP in control/regulatory elements, e.g., promoters, enhancers, or transcription factor binding domains.

[0365] As used herein, a protein or peptide is referred to as "isolated" or "purified" when it is essentially free of cellular material or chemical precursors or other chemicals. The protein variants of the present invention can be purified to homogeneity or other lower levels of purity. The degree of cleaning depends on the intended use. The key feature is that the preparation allows the protein variant to perform the desired function even when significant amounts of other components are present.

As used herein, "substantially free of cellular material" includes preparations of the variant protein having less than about 30% (by dry weight) other proteins (i.e., contaminating protein), less than about 20% other proteins, less than about 10% other proteins or less than about 5% other proteins. When the protein variant is produced recombinantly, it can also be essentially free of culture medium, ie. H. the culture medium makes up less than about 20% of the volume of the protein preparation.

The phrase "substantially free of precursor chemicals or other chemicals" encompasses preparations of the variant protein in which it is separated from precursor chemicals or other chemicals involved in its synthesis. In one embodiment, the phrase "substantially free of precursor chemicals or other chemicals" includes preparations of the variant protein having less than about 30% (by dry weight) precursor chemicals or other chemicals, less than about 20% precursor chemicals or other chemicals, less than about 10% precursor chemicals or other chemicals, or less than about 5% precursor chemicals or other chemicals.

An isolated protein variant can be purified from cells that naturally express it, purified from cells engineered to express it (recombinant host cells), or synthesized using known protein synthesis methods. For example, a nucleic acid molecule containing SNP(s) encoding the variant protein can be cloned into an expression vector, the expression vector introduced into a host cell, and the variant protein expressed in the host cell. The variant protein can then be isolated from the cells by any suitable purification scheme using standard protein purification procedures. Examples of these techniques are described in detail below (Sambrook and Russell, 2000, Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y.).

The present invention provides isolated protein variants comprising, consisting of, or consisting essentially of amino acid sequences containing one or more amino acid sequences encoded by one or more codons containing a SNP of the present invention.

Accordingly, the present invention provides variant proteins composed of amino acid sequences containing one or more amino acid polymorphisms (or truncations or lengthening due to the creation or destruction of a stop codon, respectively) other than those provided in Table 1 and/or Table SNPs are encoded 2. A protein consists of an amino acid sequence if the amino acid sequence is the entire amino acid sequence of the protein.

The present invention further provides protein variants consisting essentially of amino acid sequences containing one or more amino acid polymorphisms (or truncations or lengthening due to the creation or destruction of a stop codon, respectively) other than those provided in Table 1 and/or Table SNPs are encoded 2. A protein consists essentially of an amino acid sequence if such an amino acid sequence is present with only a few additional amino acid residues in the final protein.

The present invention further provides protein variants comprising amino acid sequences containing one or more amino acid polymorphisms (or truncations or lengthening due to the creation or destruction of a stop codon, respectively) encoded by the SNPs provided in Table 1 and/or Table 2 become. A protein comprises an amino acid sequence when the amino acid sequence is at least part of the final amino acid sequence of the protein. Thus, the protein may contain only the variant amino acid sequence or may have additional amino acid residues, such as a contiguous coded sequence naturally associated therewith, or heterologous amino acid residues. Such a protein may have a few additional amino acid residues or may include many more additional amino acids. A brief description of how different types of these proteins can be produced and isolated is provided below.

[0373] The protein variants of the present invention can be linked to heterologous sequences to form chimeric proteins or fusion proteins. Such chimeric proteins and fusion proteins comprise a protein variant operably linked to a heterologous protein that has an amino acid sequence that is not substantially homologous to the protein variant. "Operably linked" indicates that the coding sequences for the variant protein and the heterologous protein are ligated in reading frame. The heterologous protein can be fused to the N-terminus or C-terminus of the protein variant. In another embodiment, the fusion protein is encoded by a fusion polynucleotide synthesized by conventional techniques, including automated DNA synthesizers. Alternatively, PCR amplification of gene fragments can be performed using anchor primers that result in complementary overhangs between two consecutive gene fragments, which can then be annealed and reamplified to generate a chimeric gene sequence (see Ausubel et al., Current Protocols in Molecular Biology, 1992). . In addition, many expression vectors are commercially available that already encode a fusion residue (e.g., aGST protein). A nucleic acid encoding a variant protein can be cloned into such an expression vector such that the fusion component is linked in reading frame to the variant protein.

[0374] For many uses, the fusion protein does not affect the activity of the variant protein. The fusion protein may include, but is not limited to, enzymatic fusion proteins, for example, beta-galactosidase fusions, yeast two-hybrid GAL fusions, poly-His fusions, MYC-tagged, HI-tagged, and Ig fusions. Such fusion proteins, particularly poly-His fusions, may facilitate their purification after recombinant expression. In certain host cells (e.g. mammalian host cells), the expression and/or secretion of a protein can be increased by using a heterologous signal sequence "Biochemical basis to commercial systems", Appl Microbiol Biotechnol.2003, January; 60(5): 523-33 Epub 7 Nov 2002 Graddis et al Designing proteins that work using recombinant technologies CurrPharm Biotechnol 2002 December 3(4):285-97 and Nilsson et al Affinity fusion strategies for Detection, purification and immobilization of recombinant proteins", Protein Expr Purif. 1997October; 11(1):1-16.

The present invention also relates to other apparent variants of the polypeptide variants of the present invention, such as naturally occurring mature forms (e.g., allelic variants), non-naturally occurring recombinantly derived variants, and orthologues and paralogues of such proteins that share sequence homology. Such variants can be readily generated using techniques known in the art in the fields of recombinant nucleic acid technology and protein biochemistry. However, it should be understood that variants exclude those known in the prior art prior to the present invention.

[0376] Additional variants of the polypeptide variants disclosed in Table 1 may comprise an amino acid sequence that shares at least 70-80%, 80-85%, 85-90%, 91%, 92%, 93%, 94%, 95%, 96 %, 97%, 98% or 99% sequence identity with an amino acid sequence disclosed in Table 1 (or a fragment thereof) and comprising a new amino acid residue (allele) disclosed in Table 1 (which is encoded by a new SNP allele ). ). Thus, polypeptides that have a certain degree of sequence variation compared to the polypeptide sequences shown in Table 1, but contain a new amino acid residue (allele) encoded by a novel SNP allele disclosed herein, is an aspect of the present invention that is specific is considered. In other words, as long as a polypeptide contains a new amino acid residue disclosed herein, other parts of the polypeptide flanking the new amino acid residue may differ from the polypeptide sequences shown in Table 1 to some degree.

Full-length preprocessed forms, as well as mature processed forms, of proteins comprising any of the amino acid sequences disclosed herein can be readily identified as having complete sequence identity to any of the protein variants of the present invention and encoded by the same genetic locus as the protein variants provided herein.

[0378] Orthologues of a peptide variant can be easily identified because they share some degree of significant sequence homology/identity to at least a portion of a peptide variant, as well as being encoded by a gene from another organism. Preferred orthologues are isolated from non-human mammals, preferably primates, for the development of human therapeutic targets and agents. Such orthologues can be encoded by a nucleic acid sequence that hybridizes to a nucleic acid molecule encoding a peptide variant under moderate to stringent conditions, depending on the degree of relatedness of the two organisms yielding the homologous proteins.

[0379] Protein variants include, but are not limited to, proteins containing deletions, additions and substitutions in the amino acid sequence caused by the SNPs of the present invention. One class of substitutions are conserved amino acid substitutions, in which a particular amino acid in a polypeptide is replaced with another amino acid with similar properties. Typical conservative substitutions are interchanges between the aliphatic amino acids Ala, Val, Leu and Ile; exchange of the hydroxyl residues Serand Thr; Exchange of the acid residues Asp and Glu; substitution between the amide residues Asn and Gln; replacement of the basic residues Lys and Arg; and substitutions among the aromatic residues Phe and Tyr. For guidance on which amino acid changes are likely to be phenotypically silent, see, for example, Bowie et al., Science 247:1306-1310 (1990).

[0380] Variant proteins may be fully functional or involved in one or more activities, e.g. ability to bind another molecule, ability to catalyze a substrate, ability to mediate signaling, etc. Fully functional variants typically contain only conservative variations or variations in non-critical residues or in non-critical regions. Functional variants may also contain substitutions of similar amino acids that result in no or insignificant change in function. Alternatively, such substitutions may positively or negatively affect function to some extent. Non-functional variants typically contain one or more non-conservative amino acid substitutions, deletions, insertions, inversions, truncations, or lengthenings, or a substitution, insertion, inversion, or deletion of a critical residue or in a critical region.

[0381] Amino acids that are essential for the function of a protein can be identified by methods known in the art, such as in particular site-directed mutagenesis or alanine scanning mutagenesis (Cunningham et al., Science 244: 1081-1085 (1989) ). using the amino acid sequence and polymorphism information provided in Table 1. The latter method introduces single alanine mutations at each residue in the molecule. The resulting mutant molecules are then tested for biological activity, such as enzyme activity, or in assays, such as in vitro proliferative activity. Sites critical for binding partner/substrate binding can also be determined by structural analysis such as crystallization, nuclear magnetic resonance, or photoaffinity labeling (Smith et al., J. Mol. Biol. 224:899-904 (1992); de Vos et al Science 255:306-312 (1992)).

Polypeptides may contain amino acids other than the 20 amino acids commonly referred to as the 20 naturally occurring amino acids. In addition, many amino acids, including terminal amino acids, can be modified by natural processes such as B. processing and other post-translational modifications, or by chemical modification methods well known in the art. Accordingly, the protein variants of the present invention also include derivatives or analogs in which a substituted amino acid residue is not encoded by the genetic code, in which a substituent group is contained, in which the mature polypeptide is fused to another compound, such as a compound for increasing the half-life of the polypeptide (e.g. polyethylene glycol) or in which additional amino acids are fused to the mature polypeptide, such as a leader or secretory sequence or a sequence for purification of the mature polypeptide or a proprotein sequence.

Known protein modifications include, but are not limited to, acetylation, acylation, ADP-ribosylation, amidation, covalent attachment of flavin, covalent attachment of a heme moiety, covalent attachment of a nucleotide or nucleotide derivative, covalent attachment of a lipid or lipid derivative, covalent attachment of phosphotidylinositol, crosslinking, Cyclization, formation of disulfide bonds, demethylation, formation of covalent crosslinks, formation of cystine, formation of pyroglutamate, formylation, gamma-carboxylation, glycosylation, GPI anchor formation, hydroxylation, iodination, methylation, myristoylation, oxidation B. proteolytic processing, phosphorylation, prenylation , racemization, selenoylation, sulfation, transfer RNA-mediated addition of amino acids to proteins such as arginylation and ubiquitination.

[0384] Such protein modifications are well known to those skilled in the art and have been extensively described in the scientific literature. Several particularly common modifications, glycosylation, lipid attachment, sulfation, gamma-carboxylation of glutamic acid residues, hydroxylation and ADP-ribosylation, for example, are described in most seminal texts such as Proteins - Structure and Molecular Properties, 2nd ed., T.E. Creighton, W.H. Freeman and Company, New York (1993); Wold, F., Posttranslational Covalent Modification of Proteins, B.C. Johnson, ed., Academic Press, New York 1-12 (1983); Seifter et al., Meth.Enzymol. 182:626-646 (1990); and Rattan et al., Ann. NY Acad.Sci. 663:48-62 (1992).

The present invention further provides fragments of the protein variants, in which the fragments contain one or more amino acid sequence variations (e.g., substitutions or truncations or lengthenings due to the creation or destruction of a stop codon) encoded by one or more SNPs disclosed herein. However, the fragments to which the invention relates are not to be construed as including fragments disclosed in the prior art prior to the present invention.

As used herein, a fragment can comprise at least about 4, 8, 10, 12, 14, 16, 18, 20, 25, 30, 50, 100 (or any other number in between) or more contiguous amino acid residues of a Protein variant wherein at least one amino acid residue is affected by a SNP of the present invention, e.g. B. an amino acid residue variant encoded by a non-synonymous nucleotide substitution at a cSNP position provided by the present invention. The amino acid variant encoded by a cSNP can occupy any residue position along the sequence of the fragment. Such fragments may be selected based on the ability to retain one or more of the variant protein's biological activities or the ability to perform a function, e.g. B. to act as an immunogen can be selected. Particularly important fragments are biologically active fragments. Such fragments typically comprise a domain or motif of a protein variant of the present invention, e.g. B. an active site, a transmembrane domain or a ligand / substrate binding domain. Other fragments include, but are not limited to, domain or motif containing fragments, soluble peptide fragments, and fragments containing immunogenic structures. Predicted domains and functional sites are readily identifiable by computer programs known to those skilled in the art (e.g. PROSITE analysis) (Current Protocols in Protein Science, John Wiley & Sons, N.Y. (2002)).

[0387] Uses of protein variants

The variant proteins of the present invention can be used in a variety of ways including, but not limited to, in assays to determine the biological activity of a variant protein, such as in a panel of multiple proteins for high-throughput screening; produce antibodies or elicit another type of immune response; as a reagent (including the labeled reagent) in assays designed to quantitatively determine levels of the variant protein (or its binding partner) in biological fluids; as a marker for cells or tissues in which it is preferentially expressed (either constitutively or at a particular stage of tissue differentiation or development, or in a disease state); as a target for screening for a therapeutic agent; and as a direct therapeutic agent for administration to a human. Any of the protein variants disclosed herein may be developed for commercialization as a research product in reagent grade or kit format. Methods for performing the uses listed above are well known to those skilled in the art (see, e.g., Molecular Cloning: A Laboratory Manual, Cold SpringHarbor Laboratory Press, Sambrook and Russell, 2000, and Methods in Enzymology: Guide to Molecular Cloning Techniques, Academic Press) . Berger, S.L. and A.R. Kimmel eds., 1987).

In a specific embodiment of the invention, the methods of the present invention include the detection of one or more protein variants disclosed herein. Protein variants are disclosed in Table 1 and in the sequence listing as SEQ ID NOS: 81-160. Detection of such proteins can be done, for example, using antibodies, small molecules, aptamers, ligands/substrates, other proteins or protein fragments, or other protein-binding agents. Preferably, protein detection means are specific for a protein variant of the present invention and can therefore discriminate between a protein variant of the present invention and the wild-type protein or another variant form. This can generally be achieved, for example, by selecting or designing means of detection that bind to the region of a protein that differs between the protein variant and the wild-type protein, such as a region of a protein that encodes one or more amino acid substitutions is/are a non-synonymous cSNP of the present invention, or a region of a protein that follows a nonsense mutation type SNP that generates a stop codon resulting in a shorter polypeptide, or a region of a protein that follows a disruptive SNP from Read-through type mutations are followed by a stop codon, thereby resulting in a longer polypeptide in which part of the polypeptide is present in one version of the polypeptide but not the other.

In another specific aspect of the invention, the protein variants of the present invention are used as targets for diagnosing stroke or determining the predisposition to stroke in a human (e.g., determining whether an individual is at increased or decreased risk, having a stroke). Accordingly, the invention provides methods for detecting the presence or levels of one or more variant proteins of the present invention in a cell, tissue or organism. Such methods typically involve contacting a test sample with an agent (eg, an antibody, small molecule, or peptide) capable of interacting with the protein variant such that specific binding of the agent to the Protein variant can be detected. Such an assay can be provided in a single detection format or a multiple detection format, e.g. B. an array, an antibody or aptamer array (arrays for protein detection can also be referred to as "protein chips"). The variant protein of interest can be isolated from a test sample and tested for the presence of a variant amino acid sequence encoded by one or more SNPs disclosed by the present invention. The SNPs can cause changes in the protein and the corresponding protein function/activity, such as through non-synonymous substitutions in protein coding regions that can lead to amino acid substitutions, deletions, insertions and/or rearrangements; formation or destruction of stop codons; or changing control elements such as promoters. SNPs can also cause inappropriate post-translational modifications.

A preferred means of detecting a variant protein in a sample is an antibody capable of selectively binding to a variant form of the protein (antibodies are described in more detail in the next section). Such samples include, for example, tissues, cells, and biological fluids isolated from a subject, as well as tissues, cells, and fluids present in a subject.

In vitro methods for detecting the stroke-associated protein variants disclosed herein and fragments thereof include, but are not limited to, enzyme-linked immunosorbent assays (ELISAs), radioimmunoassays (RIA), Western blots, immunoprecipitations, immunofluorescence, and Protein arrays/chips (e.g. arrays of antibodies or aptamers). For more information on immunoassays and related protein detection methods, see Current Protocols in Immunology, John Wiley & Sons, N.Y. and Hage, "Immunoassays", Anal Chem. Chem. 1997, 1999, 1997. 15 Jun 1999;71(12):294R -304R.

Additional analytical methods for detecting amino acid variants include, but are not limited to, altered electrophoretic mobility, altered tryptic peptide digestion, altered protein activity in cell-based or cell-free assays, alteration in ligand or antibody binding pattern, altered isoelectric point, and direct amino acid sequencing.

Alternatively, variant proteins can be detected in a subject in vivo by introducing into the subject a labeled antibody (or other type of detection reagent) specific for a variant protein. For example, the antibody can be labeled with a radiolabel, the presence and location of which in a subject can be detected by standard imaging techniques.

Other uses of the peptide variants of the present invention are based on the class or activity of the protein. For example, proteins isolated from humans and their mammalian orthologists serve as targets for identifying agents (eg, small molecule drugs or antibodies) for use in therapeutic applications, particularly for modulating a biological or pathological response in a cell or tissue, expressing the protein. Pharmaceutical agents can be developed that modulate protein activity.

[0396] As an alternative to modulating gene expression, therapeutic compounds can be developed that modulate protein function. For example, many SNPs disclosed herein affect the amino acid sequence of the encoded protein (eg, non-synonymous cSNPs and nonsense mutation-type SNPs). Such changes in the encoded amino acid sequence can affect protein function, particularly when such amino acid sequence variations occur in functional protein domains, such as catalytic domains, ATP-binding domains, or ligand/substrate-binding domains. It is well known in the art that protein variants with amino acid sequence variations in functional domains can cause or affect pathological conditions. In such cases, compounds (e.g., small molecule drugs or antibodies) can be designed that target the protein variant and modulate (e.g., up- or down-regulate) protein function/activity.

The therapeutic methods of the present invention further include methods that target one or more protein variants of the present invention. Aberrant proteins can be attacked, for example, using small molecules, antibodies, aptamers, ligands/substrates, other proteins, or other protein-binding agents. In addition, those skilled in the art will recognize that the new protein variants (and polymorphic nucleic acid molecules) disclosed in Table 1 can themselves be used directly as therapeutics by acting as competitive inhibitors of corresponding proteins (or nucleic acid molecules such as mRNA molecules) known in the art .

The protein variants of the present invention are particularly useful in drug screening assays, in cell-based or cell-free systems. Cell-based systems can use cells that naturally express the protein, a biopsy sample, or cell cultures. In one embodiment, cell-based assays involve recombinant host cells that express the protein variant. Cell-free assays can be used to demonstrate the ability of a compound to bind directly to a variant protein or to the corresponding SNP-containing nucleic acid fragment encoding the variant protein.

A protein variant of the present invention, as well as suitable fragments thereof, can be used in high-throughput screening assays to test candidate compounds for the ability to bind and/or modulate the activity of the protein variant. These candidate compounds can be further screened against a protein with normal function (e.g., a wild-type/non-variant protein) to further determine the effect of the compound on protein activity. Additionally, these compounds can be tested in animal or invertebrate systems to determine in vivo activity/potency. Compounds can be identified that activate (agonists) or inactivate (antagonists) the variant protein, and different compounds can be identified that cause different degrees of activation or inactivation of the variant protein.

[0400] Furthermore, the protein variants can be used to screen a compound for the ability to stimulate or inhibit an interaction between the protein variant and a target molecule that normally interacts with the protein. The target can be a ligand, substrate, or binding partner with which the protein normally interacts (e.g., epinephrine or norepinephrine). Such assays typically include the steps of combining the protein variant with a candidate compound under conditions that allow the protein variant or a fragment thereof to interact with the target molecule and to detect the formation of a complex between the protein and the target or to detect the biochemical consequence thereof Interaction with the protein variant and the target, such as any of the associated signal transduction effects.

Candidate compounds include, for example, 1) peptides, such as soluble peptides, including Ig-tailed fusion peptides and members of random peptide libraries (see, e.g., Lam et al., Nature 354:82-84 (1991); Houghten et al., Nature 354:84-86 (1991)) and combinatorial chemistry-derived molecular libraries of D- and/or L-configuration amino acids; 2) phosphopeptides (e.g., members of random and partially degenerate directed phosphopeptide libraries, see, e.g., Songyang et al., Cell 72:767-778 (1993)); 3) antibodies (e.g., polyclonal, monoclonal, humanized, anti-idiotypic, chimeric, and single-chain antibodies, as well as Fab, F(ab')2, Fab expression library fragments, and epitope-binding fragments of antibodies); and 4) small organic and inorganic molecules (e.g., molecules obtained from combinatorial and natural product libraries).

[0402] A candidate compound is a soluble fragment of the protein variant that competes for ligand binding. Other candidate compounds include mutant proteins or appropriate fragments containing mutations that affect the function of variant proteins and thus compete for the ligand. Accordingly, a fragment that competes for ligand, e.g. with a higher affinity, or a fragment that binds ligand but does not allow release is encompassed by the invention.

The invention further includes other endpoint assays to identify compounds that modulate (stimulate or inhibit) the activity of protein variants. The assays typically involve an assay of events in the signal transduction pathway indicative of protein activity. Thus, the expression of genes that are up- or down-regulated in response to the variant protein-dependent signaling cascade can be tested. In one embodiment, the regulatory region of such genes may be operably linked to an easily detectable marker such as luciferase. Alternatively, the phosphorylation of the variant protein or a variant protein target could also be measured. Any of the biological or biochemical functions mediated by the protein variant can be used as an endpoint assay. These include any biochemical or biological events described herein in the references cited herein, which are incorporated by reference for these endpoint assay targets, and other functions known to those of ordinary skill in the art.

Binding and/or activating compounds can also be screened using chimeric protein variants in which an amino-terminal extracellular domain or parts thereof, an entire transmembrane domain or subregions and/or the carboxy-terminal intracellular domain or parts thereof can be replaced by heterologous domains or subregions. For example, a substrate binding region that interacts with a different substrate than that normally recognized by a protein variant can be used. Accordingly, a different set of signal transduction components is available as an endpoint assay for activation. This allows assays to be performed in a cell other than the specific host from which the protein variant is derived.

[0405] The variant proteins are also useful in competitive binding assays in methods designed to discover compounds that interact with the variant protein. Thus, a compound of a protein variant can be exposed to conditions that allow the compound to bind to or otherwise interact with the protein variant. A binding partner, such as a ligand, that normally interacts with the protein variant is also added to the mixture. When the test compound interacts with the variant protein or its binding partner, it reduces the amount of complex formed or the activity of the variant protein. This type of assay is particularly useful in screening for compounds that interact with specific regions of the variant protein (Hodgson, Bio/technology, 1992, September 10(9), 973-80).

[0406] In order to perform cell-free drug screening assays, it is sometimes desirable to immobilize either the variant protein or a fragment thereof, or its target molecule, to facilitate the separation of complexes from uncomplexed forms of one or both proteins, as well as to to allow automation of the assay. Any method of immobilizing proteins on matrices can be used in drug screening assays. In one embodiment, a fusion protein containing an added domain allows the protein to be attached to a matrix. For example, glutathione-S-transferase/125 I fusion proteins can be adsorbed to glutathione-Sepharose beads (Sigma Chemical, St. Louis, MO) or glutathione-derivatized microtiter plates, which are then mixed with the cell lysates (eg, 125 I ) are combined .35S-labeled) and a candidate compound, such as a drug candidate, and the mixture is incubated under conditions conducive to complex formation (e.g., at physiological salt and pH conditions). After incubation, the beads can be washed to remove any unbound label and the matrix immobilized and the radiolabel determined directly or in the supernatant after the complexes are dissociated. Alternatively, the complexes can be dissociated from the matrix, separated by SDS-PAGE and the amount of bound material found in the bead fraction quantitated from the gel using standard electrophoresis techniques.

Either the variant protein or its target molecule can be immobilized using conjugation of biotin and streptavidin. Alternatively, antibodies reactive with the variant protein but not interfering with the binding of the variant protein to its target molecule can be derivatized into the wells of the plate and the variant protein trapped in the wells by antibody conjugation. Preparations of the target molecule and a candidate compound are incubated in the wells displaying a variant protein and the amount of complex trapped in the wells can be quantified. Methods for detecting such complexes, in addition to those described above for the GST-immobilized complexes, include immunodetection of complexes using antibodies that are reactive with the protein target molecule or that react with protein variants and compete with the target molecule, and enzyme-linked assays that based on the detection anenzymatic activity associated with the target molecule.

[0408] Modulators of variant protein activity identified according to these drug screening assays can be used to treat a subject with a disorder mediated by the protein pathway, such as stroke. These methods of treatment typically include the steps of administering the protein activity modulators in a pharmaceutical composition to a patient in need of such treatment.

The variant proteins disclosed herein, or fragments thereof, can themselves be used directly to treat a disorder characterized by the absence, inappropriate, or undesirable expression or activity of the variant protein. Accordingly, methods of treatment include use of a protein variant disclosed herein or fragments thereof.

In yet another aspect of the invention, variant proteins can be used as "bait proteins" in a two-hybrid assay or three-hybrid assay (see, e.g., U.S. Patent No. 5,283,317; Zervos et al. (1993 ) Cell 72: 223-232, Madura et al (1993) J Biol Chem 268: 12046-12054, Bartel et al (1993) Biotechniques 14: 920-924, Iwabuchi et al (1993) Oncogene 8 : 1693-1696 and Brent WO 94/10300) to identify other proteins that bind to or interact with the variant protein and are involved in the activity of the variant protein. Such variant protein-binding proteins are also likely to be involved in the propagation of signals through the variant proteins or variant protein targets, such as elements of a protein-mediated signaling pathway. Alternatively, such variant protein binding proteins are inhibitors of the variant protein.

The two-hybrid system is based on the modular nature of most transcription factors, which typically consist of separable DNA-binding and activation domains. Briefly, the assay typically uses two different DNA constructs. In one construct, the gene encoding a variant protein is fused to a gene encoding the DNA-binding domain of a known transcription factor (e.g., GAL-4). In the other construct, a DNA sequence from a library of DNA sequences encoding an unidentified protein ("prey" or "sample") is fused to a gene encoding the activation domain of the known transcription factor. When the "bait" and the "prey" proteins are able to interact in vivo and form a variant protein-dependent complex, the DNA-binding and activation domains of the transcription factor are brought into close proximity. This proximity allows for transcription of a reporter gene (e.g., LacZ) operably linked to a transcription regulatory site that is responsive to the transcription factor. Expression of the reporter gene can be detected and cell colonies containing the functional transcription factor can be isolated and used to obtain the cloned gene encoding the protein that interacts with the protein variant.

Antibodies directed against protein variants

The present invention also provides antibodies that selectively bind to the protein variants and fragments thereof disclosed herein. Such antibodies can be used to quantitatively or qualitatively detect the variant proteins of the present invention. As used herein, an antibody selectively binds a target variant protein when it binds the variant protein and does not bind significantly to non-variant proteins, i. H. the antibody does not bind significantly to normal, wild-type, or proteins known in the art that do not contain a variant amino acid sequence due to one or more SNPs of the present invention (variant amino acid sequences may, for example, result from non-synonymous cSNPs, nonsense SNPs, the generate a stop). codon causing truncation of a polypeptide, or SNPs causing read-through mutations resulting in elongation of a polypeptide).

[0414] As used herein, an antibody is defined in terms consistent with those recognized in the art: they are multi-subunit proteins produced by an organism in response to antigen challenge. The antibodies of the present invention include both monoclonal antibodies and polyclonal antibodies, as well as antigen-reactive proteolytic fragments of such antibodies, such as Fab, F(ab)' 2 and Fv fragments. In addition, an antibody of the present invention further includes any of a variety of engineered antigen-binding molecules, such as a chimeric antibody (U.S. Pat. Nos. 4,816,567 and 4,816,397; Morrison et al., Proc. Natl. Acad.Sci. USA, 81) . : 6851, 1984; Neuberger et al., Nature 312:604, 1984), a humanized antibody (U.S. Patent Nos. 5,693,762; 5,585,089; and 5,565,332), a single-chain Fv (U.S. Patent No. 4,946,778; Ward et al., Nature 334:544 , 1989), a bispecific antibody with two binding specificities (Segal et al., J. Immunol. Methods 248:1, 2001; Carter, J. Immunol. Methods 248:7, 2001), a diabody, a triabody, and a tetrabody ( Todorovska et al., J Immunol Methods, 248:47, 2001) as well as a Fab conjugate (dimer or trimer) and an aminobody.

Many methods are known in the art for generating and/or identifying antibodies to a given target antigen (Harlow, Antibodies, Cold Spring Harbor Press, (1989)). In general, an isolated peptide (e.g., a protein variant of the present invention) is used as an immunogen and administered to a mammalian organism such as a rat, rabbit, hamster or mouse. Either a full-length protein, an antigenic peptide fragment (e.g., a peptide fragment containing a region that varies between a protein variant and a corresponding wild-type protein), or a fusion protein can be used. A protein used as an immunogen may be naturally occurring, synthetically or recombinantly produced and may be administered in combination with an adjuvant including but not limited to Freund's (complete and incomplete), mineral gels such as aluminum hydroxide, surfactants such as lysolecithin, pluronic polyols, polyanions , peptides, oil emulsions, keyhole limpethemocyanin, dinitrophenol and the like.

Monoclonal antibodies can be produced by hybridoma technology (Kohler and Milstein, Nature, 256:495, 1975), which immortalizes cells secreting a specific monoclonal antibody. The immortalized cell lines can be generated in vitro by fusing two different cell types, typically lymphocytes, and tumor cells. The hybridoma cells can be cultured in vitro or in vivo. In addition, fully human antibodies can be produced by transgenic animals (He et al., J. Immunol., 169:595, 2002). Fd-phage and Fdphagemid technologies can be used to generate and select recombinant antibodies in vitro (Hoogenboom and Chames, Immunol. Today 21:371, 2000; Liu et al., J. Mol. Biol. 315:1063 , 2002). The complementarity determining regions of an antibody can be identified and synthetic peptides corresponding to such regions can be used to mediate antigen binding (US Patent No. 5,637,677).

Antibodies are preferably raised against regions or discrete fragments of a variant protein that contains a different amino acid sequence compared to the corresponding wild-type protein (e.g., a region of a variant protein that contains an amino acid encoded by a non-synonymous cSNP, a region from a truncation caused by a nonsense SNP that generates a stop codon, or a region resulting from the destruction of a stop codon due to a read-through mutation caused by a SNP). Additionally, preferred regions include those involved in function/activity and/or protein/binding partner interaction. Such fragments can be selected based on a physical property, such as B. fragments corresponding to regions located on the surface of the protein, e.g. hydrophilic regions, or may be selected based on sequence uniqueness or based on the position of the variant amino acid residue(s) encoded by the SNPs provided by the present invention. An antigenic fragment typically comprises at least about 8-10 contiguous amino acid residues in which at least one of the amino acid residues is an amino acid affected by a SNP disclosed herein. However, the antigenic peptide may comprise at least 12, 14, 16, 20, 25, 50, 100 (or any other number in between) or more amino acid residues provided that at least one amino acid is affected by a SNP disclosed herein.

Detection of an antibody of the present invention can be facilitated by coupling (i.e. physically binding) the antibody or an antigen-reactive fragment thereof to a detectable substance. Detectable substances include, but are not limited to, various enzymes, prosthetic groups, fluorescent materials, luminescent materials, bioluminescent materials, and radioactive materials. Examples of suitable enzymes include horseradish peroxidase, alkaline phosphatase, β-galactosidase or acetylcholinesterase; Examples of suitable prosthetic group complexes include streptavidin/biotin and avidin/biotin; Examples of suitable fluorescent materials include umbelliferone, fluorescein, fluorescein isothiocyanate, rhodamine, dichlorotriazinylamine, fluorescein, dansyl chloride, or phycoerythrin; an example of a luminescent material includes luminol; Examples of bioluminescent materials include luciferase, luciferin, and acquorin, and examples of suitable radioactive materials include 125 I, 131 I, 35 S, or 3 H.

Antibodies, particularly the use of antibodies as therapeutic agents, are reviewed in: Morgan, "Antibody therapy for Alzheimer's disease", Expert Rev Vaccines. Feb 2003;2(1):53-9; Ross et al., "Anticancer Antibodies", Am J Clin Pathol. April 2003; 119(4):472-85; Goldenberg, "Advancing Role of Radiolabeled Antibodies in Cancer Therapy", Cancer ImmunolImmunother. 2003 May; 52(5):281-96. Epub Mar 11, 2003; Ross et al., “Antibody-Based Therapeutics in Oncology,” Expert Rev AnticancerTher. 2003 February; 3(1):107-21; Cao et al., "Bispecific antibody conjugates in therapeutics," Adv Drug Deliv Rev. 2003, February 10; 55(2): 171-97; von Mehren et al., "Monoclonal Antibody Therapy for Cancer", Annu Rev. Med. 2003; 54:343-69. Epub 2001 Dec 3; Hudson et al., "Engineered Antibodies", Nat. Med. 2003 January; 9(1): 129-34; Brekke et al., "Therapeutic Antibodies for Human Diseases in the Early 21st Century," Nat Rev Drug Discov. 2003January; 2(1):52-62 (erratum in: Nat Rev Drug Discov. March 2003;2(3):240); Houdebine, "Antibody production in transgenic animals and comparisons with other systems", Curr Opin Biotechnol. 2002December; 13(6):625-9; Andreakos et al., "Monoclonal antibodies in immune and inflammatory diseases", Curr Opin Biotechnol. 2002December; 13(6):615-20; Kellermann et al., "Antibody Discovery: the use of transgenic mice to generate human monoclonal antibodies for therapeutics", Curr Opin Biotechnol. 2002 Dec; 13(6):593-7; Pinie et al., "Phage Display and Colony Filter Screening for high-throughput selection of antibody libraries", Comb Chem High-Throughput Screen. 2002 November; 5(7):503-10; Batra et al., "Pharmacokinetics and biodistribution of genetically engineered antibodies," Curr Opin Biotechnol. 2002 Dec; 13(6):603-8; and Tangri et al., "Rationally engineered proteins or antibodies with absent or reduced immunogenicity", Curr Med Chem. 2002 Dec;9(24):2191-9.

[0420] Uses of Antibodies

Antibodies can be used to isolate the protein variants of the present invention from a natural cell source or from recombinant host cells by standard techniques such as affinity chromatography or immunoprecipitation. In addition, antibodies for detecting the presence of a variant protein of the present invention in cells or tissues are useful to determine the expression pattern of the variant protein in various tissues in an organism and in the course of normal development or disease progression. Furthermore, antibodies can be used to detect a protein variant in situ, in vitro, in a body fluid or in a cell lysate or supernatant to assess the level and pattern of expression. In addition, antibodies can be used to assess abnormal tissue distribution, abnormal expression during development, or expression in an abnormal condition such as stroke. In addition, antibody detection of circulating fragments of the full-length variant protein can be used to identify the turnover.

Antibodies against the protein variants of the present invention are also useful in pharmacogenomic analysis. Thus, antibodies against protein variants encoded by alternative SNP alleles can be used to identify individuals in need of modified treatment modalities.

Furthermore, antibodies can be used to assess expression of the aberrant protein in disease states, such as in active stages of the disease or in an individual with a predisposition to a disease associated with the function of the protein, particularly stroke . Antibodies specific for a variant protein encoded by a SNP-containing nucleic acid molecule of the present invention can be used to test for the presence of the variant protein, such as to screen for predisposition to stroke, such as by its presence of the deviant protein is displayed.

Antibodies are also useful as diagnostic tools for assessing protein variants in conjunction with analysis by electrophoretic mobility, isoelectric point, tryptic peptide digestion, and other physical assays known in the art.

[0425] Antibodies are also useful for tissue typing. Thus, where a specific protein variant has been correlated with expression in a specific tissue, antibodies specific for that protein can be used to identify a tissue type.

Antibodies can also be used to assess aberrant subcellular localization of a protein variant in cells in different tissues. The diagnostic uses can be applied not only to genetic testing but also to the monitoring of a treatment modality. Accordingly, where treatment is ultimately aimed at correcting the level of expression or the presence of a variant protein, or an aberrant tissue distribution or developmental expression of a variant protein, antibodies directed against the variant protein or relevant fragments can be used to increase therapeutic efficacy monitor.

The antibodies are also useful for inhibiting the function of variant proteins, for example by blocking the binding of a variant protein to a binding partner. These uses can also be applied in a therapeutic context where the treatment involves inhibiting the function of an aberrant protein. For example, an antibody can be used to block or competitively inhibit binding to modulate (agonize or antagonize) the activity of a variant protein. associated with a cell or cell membrane. For in vivo administration, an antibody can be linked to an additional therapeutic payload, such as a radionuclide, an enzyme, an immunogenic epitope, or a cytotoxic agent. Suitable cytotoxic agents include, but are not limited to, bacterial toxins such as diphtheria and plant toxins such as ricin. The in vivo half-life of an antibody or fragment thereof can be prolonged by pegylation by conjugation to polyethylene glycol (Leong et al., Cytokine 16:106, 2001).

The invention also includes kits for using antibodies, such as. B. Kits for detecting the presence of a protein variant in a test sample. An exemplary kit can include antibodies, such as a labeled or labelable antibody, and a compound or agent for detecting protein variants in a biological sample; means for determining the amount or presence/absence of protein variants in the sample; means for comparing the amount of variant protein in the sample to a standard; and instructions for use.

Vectors and Host Cells

The present invention also provides vectors containing the SNP-containing nucleic acid molecules described herein. The term "vector" refers to a vehicle, preferably a nucleic acid molecule, capable of transporting an SNP-containing nucleic acid molecule. When the vector is a nucleic acid molecule, the SNP-containing nucleic acid molecule can be covalently linked to the vector nucleic acid. Such vectors include, but are not limited to, a plasmid, a single or double stranded phage, a single or double stranded RNA or DNA, viral vector or artificial chromosome such as a BAC, PAC, YAC or MAC.

A vector can be maintained in a host cell as an extrachromosomal element, where it will replicate and produce additional copies of the SNP-containing nucleic acid molecules. Alternatively, the vector can integrate into the host cell genome and produce additional copies of the SNP-containing nucleic acid acid molecules when the host cell replicates.

The invention provides vectors for the maintenance (cloning vectors) or vectors for the expression (expression vectors) of the SNP-containing nucleic acid molecules. The vectors can function in prokaryotic or eukaryotic cells or in both (shuttle vectors).

Expression vectors typically contain cis-acting regulatory regions operably linked to the SNP-containing nucleic acid molecules in the vector to allow transcription of the SNP-containing nucleic acid molecules in a host cell. The SNP-containing nucleic acid molecules can also be introduced into the host cell with a separate nucleic acid molecule capable of affecting transcription. Thus, the second nucleic acid molecule can provide a trans-acting factor that interacts with the cis-regulatory control region to allow transcription of the SNP-containing nucleic acid molecules from the vector. Alternatively, a trans-acting factor can be provided by the host cell. Finally, a trans-acting factor can be produced from the vector itself. However, it is understood that in some embodiments the transcription and/or translation of the nucleic acid molecules can take place in a cell-free system.

The regulatory sequences to which the SNP-containing nucleic acid molecules described herein can be operably linked include promoters for directing mRNA transcription. These include the bacteriophage X left promoter, the E. coli lac, TRP and TAC promoters, the SV40 early and late promoters, the CMV immediate early promoter, the adenovirus early and late promoters and the long retrovirus a, but not limited to -terminal repeats.

In addition to control regions that promote transcription, expression vectors may also contain regions that modulate tetranscription, such as repressor binding sites and enhancers. Examples include the SV40 enhancer, cytomegalovirus immediateearly enhancer, polyoma enhancer, adenovirus enhancer, and retrovirus LTR enhancer.

In addition to containing sites for transcription initiation and control, expression vectors may also contain sequences necessary for transcription termination and a ribosome binding site for translation in the transcribed region. Other regulatory control elements for expression include initiation and termination codons and polyadenylation signals. One of ordinary skill in the art would be aware of the numerous regulatory sequences useful in expression vectors (see, e.g., Sambrook and Russell, 2000, Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y.). .

[0437] A variety of expression vectors can be used to express a SNP-containing nucleic acid molecule. Such vectors include chromosomal, episomal and virus-derived vectors, for example vectors derived from bacterial plasmids, from bacteriophage, from yeast eposomes, from yeast chromosomal elements including yeast artificial chromosomes, from viruses such as baculoviruses, papovaviruses such as SV40, vaccinia viruses, adenoviruses, poxviruses, pseudorabiesviruses and retroviruses. Vectors can also be derived from combinations of these sources, such as those derived from plasmid and bacteriophage genetic elements, e.g. B. cosmids and phagemids. Suitable cloning and expression vectors for prokaryotic and eukaryotic hosts are described in Sambrook and Russell, 2000, Molecular Cloning: A Laboratory Manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y.

The regulatory sequence in a vector can provide for constitutive expression in one or more host cells (e.g. tissue-specific expression) or can provide for inducible expression in one or more cell types, such as by temperature, nutrient addition or exogenous factor, e.g. B. a hormone or other ligands. A variety of vectors that provide for constitutive or inducible expression of a nucleic acid sequence in prokaryotic and eukaryotic host cells are well known to those of ordinary skill in the art.

[0439] A SNP-containing nucleic acid molecule can be inserted into the vector by methods well known in the art. In general, the SNP-containing nucleic acid molecule that will ultimately be expressed is joined to an expression vector by cleaving the SNP-containing nucleic acid molecule and the expression vector with one or more restriction enzymes and then ligating the fragments together. Procedures for restriction enzyme digestion and ligation are well known to those of ordinary skill in the art.

The vector containing the appropriate nucleic acid molecule can be introduced into an appropriate host cell for propagation or expression using well known techniques. Bacterial host cells include, but are not limited to, E. coli, Streptomyces, and Salmonella typhimurium. Eukaryotic host cells include, but are not limited to, yeast, insect cells such as Drosophila, animal cells such as COS and CHO cells, and plant cells.

[0441] As described herein, it may be desirable to express the variant peptide as a fusion protein. Accordingly, the invention provides fusion vectors that allow the production of the peptide variants. For example, fusion vectors can increase expression of a recombinant protein, increase solubility of a recombinant protein, and aid in purification of the protein, for example, by acting as a ligand for affinity purification. An aproteolytic cleavage site can be introduced at the junction of the fusion moiety so that the desired peptide variant can ultimately be separated from the fusion moiety. Proteolytic enzymes suitable for such use include, but are not limited to, factor Xa, thrombin and enterokinase. Typical fusion expression vectors include pGEX (Smith et al., Gene 67:31-40 (1988)), pMAL (New England Biolabs, Beverly, Mass.), and pRIT5 (Pharmacia, Piscataway, N.J.), the glutathione-S-transferase ( GST) merge. B. maltose E-binding protein or protein A, to the recombinant target protein. Examples of suitable non-fusion E. coli inducible expression vectors include pTrc (Amann et al., Gene 69:301-415 (1988)) and pET11d (Studier et al., Gene Expression Technology: Methods in Enzymology 185:60- 89 (1990)).

[0442] Expression of recombinant proteins can be maximized in a bacterial host by providing a genetic background in which the host cell has an impaired ability to proteolytically cleave recombinant protein (Gottesman, S., Gene Expression Technology: Methods in Enzymology 185, Academic Press, San Diego, California (1990) 119-128). Alternatively, the sequence of the SNP-containing nucleic acid molecule of interest can be altered to provide a preferred codon usage for a specific host cell, such as E. coli (Wada et al., Nucleic Acids Res. 20:2111-2118 (1992)).

[0443] The SNP-containing nucleic acid molecules can also be expressed by expression vectors that function in yeast. 229-234 (1987)), pMFa (Kurjan et al., Cell 30:933-943 (1982)), pJRY88 (Schultz et al., Gene 54:113-123 (1987)), and pYES2 (Invitrogen Corporation, San Diego, CA).

The SNP-containing nucleic acid molecules can also be expressed in insect cells using, for example, baculovirus expression vectors. Baculovirus vectors available for expression of proteins in cultured insect cells (e.g., Sf9 cells) include the pAc series (Smith et al., Mol. Cell Biol. 3:2156-2165 (1983)) and the pVL series (Lucklow et al., Virology 170:31-49 (1989)).

In certain embodiments of the invention, the SNP-containing nucleic acid molecules described herein are expressed in mammalian cells using mammalian expression vectors. Examples of mammalian expression vectors include pCDM8 (Seed, B. Nature 329:840 (1987)) and pMT2PC (Kaufman et al., EMBO J. 6:187-195 (1987)).

The invention also encompasses vectors in which the SNP-containing nucleic acid molecules described herein are cloned into the vector in the reverse orientation, but are operably linked to a regulatory sequence that allows transcription of antisense RNA. Thus, an antisense transcript can be produced to the SNP-containing nucleic acid sequences described herein, including both coding and non-coding regions. The expression of this antisense RNA is subject to each of the parameters described above in relation to the expression of the sense RNA (regulatory sequences, constitutive or inducible expression, tissue-specific expression).

The invention also relates to recombinant host cells containing the vectors described herein. Thus, host cells include, for example, prokaryotic cells, lower eukaryotic cells such as yeast, other eukaryotic cells such as insect cells, and higher eukaryotic cells such as mammalian cells.

[0448] The recombinant host cells can be prepared by introducing the vector constructs described herein into the cells by techniques readily available to those of ordinary skill in the art. These include, but are not limited to, calcium phosphate transfection, DEAE-dextran-mediated transfection, cationic lipid-mediated transfection, electroporation, transduction, infection, lipofection, and other techniques such as those described in Sambrook and Russell, 2000, Molecular Cloning : A Laboratory, Handbook, Cold Spring Harbor Laboratory, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y.).

[0449] Host cells may contain more than one vector. Thus, different SNP-containing nucleotide sequences can be introduced into the same cell in different vectors. Similarly, the SNP-containing nucleic acid molecules can be introduced either alone or with other nucleic acid molecules unrelated to the SNP-containing nucleic acid molecules, such as. B. those that provide trans-acting factors for expression vectors. When more than one vector is introduced into a cell, the vectors can be introduced independently, introduced together, or linked to the nucleic acid molecule vector.

In the case of bacteriophage and viral vectors, these can be introduced into cells as packaged or encapsulated virus by standard methods of infection and transduction. Viral vectors can be replication competent or replication defective. In the case where viral replication is defective, replication can occur in host cells that provide functions that complement the defects.

Vectors generally include selectable markers that allow for selection of the subpopulation of cells containing recombinant vector constructs. The marker can be inserted into the same vector that contains the SNP-containing nucleic acid molecules described herein or can be in a separate vector. Markers include, for example, tetracycline or ampicillin resistance genes for prokaryotic host cells, and dihydrofolate reductase or neomycin resistance genes for eukaryotic host cells. However, any marker that provides selection for a phenotypic trait may be effective.

While the mature variant proteins can be produced in bacteria, yeast, mammalian cells, and other cells under the control of the appropriate regulatory sequences, cell-free transcription and translation systems can also be used to produce these variant proteins using RNA derived from the DNA constructs described herein.

If secretion of the variant protein is desired, which is difficult to achieve with proteins containing multi-transmembrane domains, such as G protein-coupled receptors (GPCRs), appropriate secretion signals can be engineered into the vector. The signal sequence can be endogenous to the peptides or heterologous to these peptides.

If the protein variant is not secreted into the medium, the protein can be isolated from the host cell by standard disruption methods, including freeze/thaw, sonication, mechanical disruption, use of lysing agents, and the like. The variant protein can then be recovered and purified by well known purification methods including, for example, ammonium sulfate precipitation, acid extraction, anion or cation exchange chromatography, phosphocellulose chromatography, hydrophobic interaction chromatography, affinity chromatography, hydroxyapatite chromatography, lectin chromatography, or high performance liquid chromatography.

[0455] It is also understood that depending on the host cell in which the recombinant production of the variant proteins described herein takes place, they may have different glycosylation patterns or may be non-glycosylated as when produced in bacteria. In addition, in some cases, the protein variants may contain an initially modified methionine as a result of a host-mediated process.

For additional information regarding vectors and host cells, see Current Protocols in Molecular Biology, John Wiley & Sons, N.Y.

Uses of vectors and host cells and transgenic animals

[0458] Recombinant host cells expressing the variant proteins described herein have a variety of uses. For example, the cells are useful for producing a variant protein that can be further purified to prepare desired amounts of the variant protein or fragments thereof. Thus, host cells containing expression vectors are useful for the production of protein variants.

Host cells are also useful for conducting cell-based assays involving the variant protein or variant protein fragments such as those described above, as well as other formats known in the art. Thus, a recombinant host cell expressing a variant protein is useful for testing compounds that stimulate or inhibit the function of variant proteins. Such ability of a compound to modulate protein functional variant may not be evident from assays of the compound with the native/wild-type protein or from cell-free assays of the compound. Recombinant host cells are also useful for testing functional changes in the protein variants relative to a known function.

[0460] Genetically engineered host cells can be further used to produce non-human transgenic animals. A transgenic animal is preferably a non-human mammal, for example a rodent such as a rat mouse, in which one or more of the animal's cells contain a transgene. A transgene is exogenous DNA containing a SNP of the present invention which is integrated into the genome of a cell from which a transgenic animal develops and which remains in the genome of the mature animal in one or more of its cell types or tissues. Such animals are useful for studying the function of a variant protein in vivo and for identifying and evaluating modulators of variant protein activity. Other examples of transgenic animals include, but are not limited to, non-human primates, sheep, dogs, cows, goats, chickens, and amphibians. Transgenic non-human mammals such as cows and goats can be used to produce protein variants that can be excreted in the animal's milk and then recovered.

A transgenic animal can be produced by introducing an SNP-containing nucleic acid molecule into the male pronuclei of a fertilized egg, e.g. B. by microinjection or retroviral infection, and the development of the oocyte is allowed in a pseudopregnant female foster animal. Any nucleic acid molecule containing one or more SNPs of the present invention may potentially be introduced into the genome of a non-human animal as a transgene.

Any of the regulatory or other sequences useful in expression vectors may form part of the transgenic sequence. This includes intron sequences and polyadenylation signals if not already included. One or more tissue-specific regulatory sequences can be operably linked to the transgene to direct expression of the variant protein in particular cells or tissues.

Methods for generating transgenic animals by embryo manipulation and microinjection, particularly animals such as mice, have become common in the art and are described, for example, in US Pat. Nos. 4,736,866 and 4,870,009, both to Leder et al., U.S. Pat. No. 4,873,191 to Wagner et al. and in Hogan, B., Manipulating the Mouse Embryo, (Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y., 1986). Similar methods are used to produce other transgenic animals. A transgenic progenitor can be identified based on the presence of the transgene in its genome and/or the expression of transgenic mRNA in tissues or cells of the animals. A transgenic founder animal can then be used to breed additional animals carrying the transgene. In addition, transgenic animals carrying one transgene can be further bred with other transgenic animals carrying other transgenes. A transgenic animal also includes a non-human animal in which the entire animal or tissues in the animal have been produced using the homologously recombinant host cells described herein.

Alternatively, transgenic non-human animals can be produced that contain selected systems that allow for regulated expression of the transgene. An example of such a system is the cre/loxP recombinase system of bacteriophage P1 (Lakso et al. PNAS89:6232-6236 (1992)). Another example of a recombinase system is the S. cerevisiae FLP recombinase system (O'Gorman et al. Science 251:1351-1355 (1991)). When a cre/loxP recombinase system is used to regulate expression of the transgene, animals containing transgenes encoding both the Cre recombinase and a selected protein are generally required. Such animals can be provided by the construction of "double" transgenic animals, e.g. B. by mating two transgenic animals, one containing a transgene encoding a selected protein variant and the other containing a transgene encoding arecombinase.

Clones of the non-human transgenic animals described herein can also be made according to the methods described, for example, in Wilmut, I. et al. Nature 385:810-813 (1997) and PCT International Publication Nos. WO 97/07668 and WO 97/07669. Briefly, a cell (e.g., a somatic cell) from the transgenic animal can be isolated and induced to exit the growth cycle and enter gophase. The resting cell can then z. B. be fused by the use of electrical pulses with an enucleated oocyte from an animal of the same species from which the quiescent cell was isolated. The reconstructed oocyte is then cultured to develop a tomorula, or blastocyst, and then transferred to a pseudopregnant female foster animal. The offspring born of this female foster animal will be a clone of the animal from which the cell (e.g. a somatic cell) was isolated.

[0466] Transgenic animals containing recombinant cells expressing the variant proteins described herein are useful for performing the assays described herein in an in vivo context. Accordingly, the various physiological factors present in vivo that might affect ligand or substrate binding, protein activation of variants, signaling, or other processes or interactions may not be apparent from in vitro cell-free or cell-based assays. Thus, non-human transgenic animals of the present invention can be used to assay in vivo the function of a variant protein, as well as the activities of a therapeutic agent or a compound that modulates the function/activity or expression of a variant protein. Such animals are also useful to assess the effects of null mutations (i.e., mutations that substantially or completely eliminate one or more different protein functions).

For more information regarding transgenic animals see Houdebine, "Antibody Manufacture in transgenic Animals and Comparsions with other Systems", Curr Opin Biotechnol. 2002December; 13(6):625-9; Petters et al., "Transgenic animals as models for human disease", Transgenic Res. 2000; 9(4-5):347-51; Discussion 345-6; Wolf et al., "Using transgenic animals in understanding the molecular mechanisms of toxicity", J Pharm Pharmacol. 1998, June; 50(6):567-74; Echelard, "Recombinant protein production in transgenic animals", Curr Opin Biotechnol. 1996 Oct;7(5):536-40; Houdebine, "Transgenic animal bioreactors", Transgenic Res. 2000; 9(4-5):305-20; Pirity et al., "Embryonic stem cells that produce transgenic animals", Methods Cell Biol. 1998; 57:279-93; and Robl et al., "Artificial chromosome vectors and expression of complex proteins in transgenic animals", Theriogenology. 2003 January 1; 59(1):107-13.

EXAMPLES

The following examples are offered to illustrate but not limit the claimed invention.

Example 1: SNPs associated with stroke in the AtherosclerosisRisk in Communities (ARIC) study

[0469] Overview

[0470] 51 SNPs associated with coronary artery disease (CAD) were analyzed in several previous studies (Bare et al. 2007) to determine whether these SNPs are associated with ischemic stroke in the Atherosclerosis Risk in Communities (ARIC) -Study associated. To conduct this analysis, 495 validated ischemic strokes were identified from the multiracial ARIC cohort of 14,215 individuals by following the cohort for potential cerebrovascular events for an average of 13.5 years. Risk alleles for 51 SNPs were specified based on the results of at least two previous studies in which these SNPs were associated with CAD. As a result of this analysis, Cox proportional hazards models, adjusted for age and gender, identified three SNPs in White/Caucasian (these terms are used interchangeably here) and two SNPs in Black/African American (these terms are used interchangeably here). associated (p<0.05) with stroke and had the same risk allele as reported in the previous studies. The rs11628722 polymorphism in SERPINA9 was associated with ischemic stroke in both whites and blacks. Thus, genetic variation in SERPINA9 has been associated with stroke in both whites and blacks, even after adjusting for traditional risk factors.

[0471] Subjects and Methods

The Atherosclerosis Risk in Communities (ARIC) study

Study participants were selected from the ARIC study, a prospective investigation of atherosclerosis and its clinical consequences that enrolled 15,792 subjects aged 45-64 years (1986-1989). Subjects were selected by probability sampling from four communities: Forsyth County, N.C.; Jackson, miss. (blacks only); Northwest Suburbs of Minneapolis, Minnesota; and Washington County, Maryland. Initial clinical assessments included an at-home interview to assess cardiovascular risk factors, socioeconomic factors, and family history, clinical examination, and blood draws for laboratory determinations. A detailed description of the ARIC study design and methods has been published elsewhere (ARIC Investigators (1989) "The AtherosclerosisRisk in Communities (ARIC) Study: design and objects". American Journal of Epidemiology 129: 687-702).

[0474] Ischemic Stroke Incident

[0475] Ischemic stroke was determined by contacting participants annually to identify hospital admissions in the previous year and by examining discharge lists from local hospitals and death certificates from state vital statistics offices for possible cerebrovascular events (ARIC Investigators (1989) American Journal of Epidemiology 129:687-702, Rosamond et al (1999) Stroke 30:736-743). Hospital records were obtained, abstracted, and classified by computer algorithm and physician review. Details on quality assurance for the detection and classification of ischemic strokes have been published elsewhere (Rosamond et al. (1999) Stroke30: 736-743). Ischemic stroke events were defined as validated definite or probable in-hospital embolic or thrombotic cerebral infarctions. Participants were excluded from this analysis if they had a positive or unknown history of predominant stroke; transient ischemic attack/stroke symptoms or CAD at initial visit; ethnic background other than white or black; an ethnic black background but not from Jackson, Mississippi; Limitations in using their DNA or lack of data for any of the traditional cardiovascular or cerebrovascular risk factors. The remaining 14,215 participants were followed for a median of 13.5 years for ischemic stroke, and 495 cases of ischemic stroke were identified.

Examination and laboratory measures

Cardiovascular risk factors considered in this study were measured at baseline and included age, gender, waist-to-hip ratio, diabetes, hypertension, and smoking status. The ratio of waist (navel height) and hip circumference (maximum bottom) was calculated as a measure of fat distribution. Diabetes was defined by a fasting glucose level ≥ 126 mg/dL, a non-fasting glucose level ≥ 200 mg/dL, or a physician self-reported diagnosis of diabetes or use of diabetes medications. Sitting blood pressure was measured three times with a random-zero sphygmomanometer and the last two measurements were averaged. A questionnaire administered by an interviewer was used to assess the use of antihypertensive drugs. Hypertension was defined as systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg or current use of antihypertensive drugs. Cigarette smoking status was classified as current or not current. The study protocol was approved by the Institutional Review Boards of the collaborating institutions and informed written consent was obtained from each participant.

[0478] SNP selection and genotyping

[0479] Fifty-one functional SNPs that have been associated with CHD in several previous studies other than the ARIC study were included in this study. A detailed description of the previous studies can be found elsewhere (Bare et al., Genetics in Medicine. 2007October; 9(10):682-9). Briefly, risk alleles for 49 SNPs were specified based on a significant association with myocardial infarction in at least two previous case-control studies. These studies included myocardial infarction cases and controls recruited from either the Cleveland Clinic Foundation Heart Center, Cleveland, Ohio (CCF) or the Genomic Resource in Arteriosclerosis at the University of California, San Francisco (UCSF). All cases in these two studies had a history of myocardial infarction and controls did not, and all subjects were self-identified non-Hispanic Caucasians. The risk alleles for two additional SNPs were specified based on an association with CHD in the placebo arms of two CHD prevention studies: the Cholesterol and Recurrent Events (CARE) study (Sacks et al. (1996) New England Journal of Medicine 335: 1001-1009). ) and the West of Scotland Coronary Prevention Study (WOSCOPS) (Packard et al. (2000) New England Journal of Medicine343:1148-1155). One of these SNPs (rs20455 in KIF6) was significantly associated with CHD after correction for multiple testing (Iakoubova et al., Journal of the American College of Cardiology. 2008; 51:435-43). The second SNP associated with CAD in CARE and WOSCOPS was rs11666735 in FCAR (Iakoubova et al. (2006) Arteriosclerosis, Thrombosis and Vascular Biology 26:2763-2768).

[0480] Genotyping of the 51 SNPs in the ARIC study was performed using PCR-based amplification of genomic DNA followed by an allele-specific oligonucleotide ligation assay, similar to a previously described method (Iannone et al. (2000) Cytometry 39 : 131-140). .

[0481] Statistical analyses

[0482] The agreement of genotype frequencies with the Hardy-Weinberg equilibrium expectancies was tested separately in whites and blacks using a .chi 2 test of fit in non-cases stratified by race. Deviation from Hardy-Weinberg equilibrium was determined by a p-value of less than 0.05. Cox proportional hazard models were used to model the time to onset of ischemic stroke. The follow-up time interval was defined as the time between the first clinical visit and the end of follow-up, which was the date of the first ischemic stroke for cases and December 31, 2002, the date of death for non-cases. or last contact date in case tracking is lost. Each model was scored separately in white and black and included a specific SNP (modeled as the additive effect of the pre-specified risk allele), age and sex. Additional risk factors assessed as potential confounders in the Cox proportional hazards models included waist-to-hip ratio, diabetes, hypertension, and smoking status (Folsom et al., (1999) Diabetes Care 22:1077-1083). SNPs and risk factors were assessed for statistical significance in the models of Wald Statistics. A two-sided p-value of 0.05 was used to assess statistical significance in ischemic stroke and no attempt was made to adjust for multiple comparisons within this study.

Results

[0484] Breed proportions, means and standard deviations for the traditional risk factors are presented in Table 5. Means and proportions differed significantly (p<0.03) between cases of incident ischemic stroke and non-cases for all risk factors.

Three SNPs in whites (in SERPINA9, PALLD and IER2) and two SNPs in blacks (in SERPINA9 and EXOD1) were associated with ischemic stroke (p ≤ 0.05) after adjustment for age and sex and had the same risk allele as indicated in the previous studies (Table 6, model 1). An additional SNP in EIF2AK2 was associated with ischemic stroke in whites, but the risk allele in the ARIC study differed from the risk allele identified in the previous CHD studies. The rs11628722 polymorphism in SERPINA9 was associated with ischemic stroke in both races (HRR=1.31 for Whites, 95% CI: 1.00-1.70; HRR for Blacks=1.26, 95% CI: 1.03-1.53).

For the four SNPs associated in each ethnic group, traditional cardiovascular risk factors were included in the Cox proportional hazards models to assess possible confounding. The observed hazard ratios remained essentially unchanged when these risk factors were added to the predictive models (Table 6, model 2).

Discussion

[0488] This study examined whether 51 putative functional SNPs associated with CHD in several previous studies predict ischemic stroke in white and black subjects from the large prospective ARIC study. Three SNPs in whites and two SNPs in blacks were associated with ischemic stroke, even after accounting for established risk factors. The rs11628722 polymorphism in SERPINA9 was associated with ischemic stroke in both white and black subjects in the ARIC study.

It is noteworthy that the association between SERPINA9 and stroke was observed in both whites and blacks in this study. This SNP has been associated with myocardial infarction in two case-control studies, and this study shows an association with stroke in both whites and blacks from the ARIC study. SERPINA9 is a member of group A of the large superfamily of serine peptidase inhibitors known as serpins. Serpins are protease inhibitors that use conformational change to inhibit target enzymes and are involved in many cellular processes such as coagulation, fibrinolysis, complement fixation, matrix remodeling and apoptosis (Law et al. (2006) Genome Biology 7:216). A recent study showed that SERPINA9 was significantly upregulated in the hippocampus of transgenic mice with Alzheimer's disease compared to age-matched controls (Jee et al. (2006) Neurochemistry Research 31:1035-1044). This study suggests that SERPINA9 may also be expressed in the human brain, consistent with the findings herein of an association between polymorphic variation in this gene and ischemic stroke.

In addition to SERPINA9, polymorphisms in palladin (PALLD) and immediate early response 2 (IER2) were associated with ischemic stroke in whites, and a polymorphism in the exonuclease domain containing 1 (EXOD1) was associated in blacks. PALLD encodes a component of the cytoskeleton that controls cell shape and motility. Vascular remodeling can lead to atherosclerosis, and the shape and cytoskeletal organization of endothelial cells is an important part of this process. Mechanical stress and strain also play a role in atherosclerotic vascular remodeling, and immediate response genes have been shown to mediate the mechanical stress-induced pathological process in the blood vessel (Liu et al. (1999) Critical Reviews in Biomedical Engineering 27: 75-148 ). Although little is known about EXOD1, exonucleases have been shown to play a role in both myocardial infarction and stroke. Given their functional roles, PALLD, IER2 and EXOD1 may play a role in atherosclerotic signaling. In addition, PALLD, IER2 and EXOD1 are all expressed in heart and brain.

[0491] A strength of this study is the prospective cohort design. The large sample size allows exposures (e.g. genetic factors) with a moderate effect to be assessed. All analyzes for this study were performed separately for whites and blacks.

Thus, it was found that a small subset of gene variants previously associated with CHD in previous studies were also associated with the occurrence of ischemic stroke in ARIC. Notably, SERPINA9 has been associated with stroke in both whites and blacks, and this association does not appear to be mediated by traditional risk factors.

[0493] Supplementary analysis of SNPs in the ARIC study

In a further analysis of the 51 SNPs in the ARIC participants, SNPs predicting ischemic stroke risk were identified by Cox proportional hazards analysis and SNPs with a two-tailed p-value of <0.2 after adjustment for age and gender and a hazard ratio (HRR) > 1.0. These SNPs are shown in Tables 7-9 (the p-values ​​shown in Tables 7-9 are two-tailed p-values; thus the one-tailed p-values ​​for these SNPs are half of these two-tailed p-values). SNPs predicting ischemic stroke after adjusting for food and gender (two-tailed p-value < 0.2 and HRR > 1.0) in the white ARIC participants and separately in the black ARIC participants are shown in Table 7 (White ) and Table 8 (blacks). SNPs predicting ischemic stroke after adjustment for age and sex in both black and white ARIC populations with the same risk alleles are shown in Table 9.

Example 2: SNPs associated with stroke in the Cardiovascular Health Study (CHS) overview

74 SNPs that have been associated with coronary artery disease (CAD) (Shiffman et al., Arterioscler Thromb Vasc Biol. 2008 Jan;28(1):173-9, incorporated herein by reference in its entirety), were analyzed to determine whether these SNPs are associated with ischemic stroke. To perform this analysis, the risk allele for each of the 74 SNPs was pre-specified based on previous studies of CHD. Cox proportional hazards models, adjusted for traditional risk factors, were used to estimate the associations of these SNPs with ischemic stroke during a 14-year follow-up in a population-based study of older adults termed the Cardiovascular Health Study (CHS). becomes. As a result of this analysis, the predefined risk alleles of 7 of the 74 SNPs (in HPS1, ITGAE, ABCG2, MYH15, FSTL4, CALM1, and BAT2) were associated with an increased risk of stroke in white CHS participants (one-sided P<0.05). , false detection rate (FDR) = 0.42). In African-American participants, the predefined risk alleles of 5 SNPs (inKRT4, LY6G5B, EDG1, DMXL2, and ABCG2) were associated with stroke (one-sided P<0.05, FDR=0.55). The Val12Met SNP in ABCG2 was similar in both white (hazard ratio 1.46, 90% CI 1.05 to 2.03) and African American (hazard ratio 3.59, 90% CI 1.11 to 11.6) CHS participants associated with stroke. Kaplan-Meier estimates of 10-year cumulative incidence of stroke were greater for Val allele homozygotes than for Met allele in both white (10% vs. 6%) and African-American (12% vs. 3%) CHS participants -porters. Thus, the Val12Met SNP in ABCG2 (encoding a transporter of sterols and xenobiotics) was associated with ischemic stroke in White and African-American CHS participants.

Materials and Methods

[0497] Cardiovascular Health Study

[0498] CHS is a prospective population-based study of risk factors for cardiovascular disease, including CHD and stroke, in older adults. Men and women ages 65 and older were recruited from random samples of individuals on Medicare eligibility lists in four United States. Communities (Sacramento County, California; Washington County, Maryland; Forsyth County, N.C.; and Pittsburgh, Allegheny County, Pennsylvania) and by eligible members of the same households hospice care, radiation or chemotherapy for cancer, expected to be in the area for at least three years, or disability to be questioned. CHS enrolled 5201 participants in 1989-90. An additional 687 African American participants joined the cohort in 1992-93. Participants who did not donate DNA or consented to the use of their DNA for studies by private companies (n = 514) and participants who did not have enough DNA samples (n = 130) were excluded, resulting in 5244 participants were available for a genetic study. The institutional review board at each site approved the study methods and all participants provided written informed consent. Details of CHS design 7 and recruitment 8 have been reported.

[0499] Participants completed a baseline clinical assessment that included a history interview, physical examination, and blood draw physician questionnaires.10 Cardiovascular events during follow-up were recorded at bi-annual contacts that alternated between clinic visits and phone calls. Probable events were assessed according to standard criteria by a medical review panel using information from medical records, brain imaging studies11 and, in some cases, interviews with the physician, participant, or proxy informant.12 Medicare usage records were searched to obtain certainty about events that may have been missed... 13

[0500] At baseline, 722 of the 5244 participants available for an agenetic study had a history of stroke or MI. Because the risk of ischemic stroke could be affected by whether a patient had a previous stroke or myocardial infarction, these 722 participants were excluded from the analysis, leaving 4522 (3849 White and 673 African American) participants in this first ischemic stroke genetic study . The baseline characteristics of these 4522 participants are presented in Table 10. During follow-up, 642 participants suffered an unprocedure-related stroke, and 47 of those 642 had a myocardial infarction prior to their stroke, leaving 595 stroke events. Of these 595 stroke events, 72 (12%) were hemorrhagic, 46 (8%) were not classified by type, and the remaining 477 stroke events were classified as ischemic stroke events: the endpoint for this analysis.

[0501] Covariate

[0502] Risk estimates for ischemic stroke were adjusted for the following traditional risk factors: diabetes mellitus (defined by fasting serum glucose levels of at least 126 mg/dL or use of either insulin or oral hypoglycemic medications), impaired fasting glucose (defined as fasting glucose levels between 110 and 125 mg/dl14), hypertension (defined by a systolic blood pressure of at least 140 mmHg, a diastolic blood pressure of at least 90 mmHg, or a medical diagnosis of high blood pressure plus use of antihypertensive medication10), current smoking, LDL cholesterol, HDL cholesterol and Body Mass Index (BMI). Other covariates included atrial fibrillation, carotid intima-media (IMT) thickness, and genotypes. Atrial fibrillation was identified based on resting 12-lead ECGs performed at baseline. Traces were examined for atrial fibrillation or flutter at the CHS electrocardiography reading center. The IMT was defined as the mean of the maximum IMTs of the near and far walls of the left and right carotid arteries. 16 The genotypes of CHS participants were determined by a multiplex method combining PCR, allele-specific oligonucleotide ligation assays, and hybridization tool oligonucleotides coupled to Luminex ® 100 TM xMAP microbeads (Luminex, Austin, TX), followed by detection of the spectral different microspheres on a Luminex 100 instrument (Shiffman et al., Arterioscler Thromb Vasc Biol. 2008 Jan;28(1):173-9).

Pre-specification of risk alleles for 74 SNPs examined in CHS

[0504] For each of the 74 SNPs genotyped in CHS, a risk allele was prespecified based on previous data (Shiffman et al., Arterioscler Thromb Vasc Biol. 2008 Jan;28(1):173-9). Genetic associations with CAD have previously been published for 14 of the 74 SNPs. 28(1):173-9).

[0505] Statistics

Since the risk assessment for gene variants can differ between Whites and African Americans, the association of SNPs with incident ischemic stroke in CHS was examined separately for each race. Analyzes of time to the primary endpoint were performed. Follow-up began at CHS enrollment and ended on the date of stroke of any type, MI, death, loss pending follow-up, or June 30, 2004, whichever came first. The median follow-up time was 11.2 years (11.9 years for the 1989-90 cohort and 10.7 years for the African-American cohort).

[0507] Cox regression models were used to estimate the hazard ratios of each SNP. In model 1, the Cox models were adjusted for baseline age (continuous) and gender. In Model 2, the Cox models for baseline age (continuous), gender, body mass index (continuous), current smoking, diabetes, impaired fasting glucose, hypertension, LDL-cholesterol (continuous), and HDL-cholesterol ( continuous).Risk Estimates were also adjusted for two additional risk factors for ischemic stroke: atrial fibrillation and carotid IMT. The SNP variable in the Cox models was coded as 0 for non-risk homozygotes, 1 for those carrying 1 copy of the risk allele, and 2 for those carrying 2 copies of the risk allele. Thus, the hazard ratios represent the logarithmic additive increase in risk for each additional copy of the at-risk allele a subject carried compared to the non-at-risk homozygotes. Because the hypotheses that the allele associated with increased risk of CAD would also be associated with increased risk of ischemic stroke were tested, a one-tailed P value was used to test the significance of the Cox model coefficients. Accordingly, 90% confidence intervals for the hazard ratios were estimated (for hazard ratios greater than one, there is 95% confidence that a true risk estimate is greater than the lower bound of a 90% confidence interval). In white participants, this study had a power of 80% or more to detect associations between SNPs and ischemic stroke for SNPs having relative risks of 1.3 and 1.5 (in an additive model) and risk allele frequencies of 0.13 and 0.05, respectively, assuming an alpha level of 0.05 and a one-tailed test. In African American participants, this study had a power of 80% or more to detect associations between SNPs and ischemic stroke for SNPs having relative risks of 1.6 and 1.8 (in an additive model) and risk allele frequencies of 0.3 and 0.14, respectively. The cumulative incidence of stroke was estimated using the Kaplan and Meier method. Data were analyzed using Stata Statistical Software 22 . The impact of multiple testing was assessed using the false detection rate (FDR) 23 to estimate the expected proportion of false positives in a group of SNPs with P-values ​​below a given threshold. FDR calculations were performed with R Statistical Software 24

Results

The baseline characteristics of the 3,849 White and 673 African American CHS participants in this ischemic stroke genetic study are presented in Table 10. median of 11.2 years). The association between ischemic stroke and 74SNPs previously associated with coronary artery disease (CAD) in one or more previous studies (Shiffman et al., Arterioscler Thromb Vasc Biol. 2008 Jan; 28(1):173-9 ) was examined. Specifically, for each SNP, it was determined whether the allele associated with increased risk of CHD (the risk allele) was also associated with increased risk of stroke.

[0510] In white CHS participants, the risk alleles of 7 of these 74 SNPs were found to be associated with an increased risk of stroke (P < 0.05) after adjusting for traditional risk factors (age, gender, body mass index, smoking, diabetes, impaired fasting glucose, hypertension, LDL cholesterol and HDL cholesterol). These 7 SNPs were located in HPS1, ITGAE, ABCG2, MYH15, FSTL4, CALM1 and BAT2. The additive (per allele) hazard ratios for stroke ranged from 1.15 to 1.49 (Table 11). In African-American CHS participants, risk alleles of 5 SNPs (in KRT4, LY6G5B, EDG1, DMXL2, and ABCG2) were found to be associated with an increased risk of stroke (P<0.05) after adjusting for traditional risk factors. The hazard ratios for these 5 SNPs ranged from 1.40 to 3.59 (Table 12). Risk estimates for the 11 SNPs associated with stroke in either Whites or African Americans (Tables 11 and 12) remained essentially unchanged when further adjusted for atrial fibrillation and internal carotid artery IMT (data not shown).

To account for multiple comparisons, the FDR 23 was estimated for the set of SNPs found to be associated with incident ischemic stroke in CHS participants. These FDRs were 0.42 for the 7 SNPs in White participants and 0.55 for the 5 SNPs in African-American participants of CHS. ABCG2 Val12Met (rs2231137) was associated with ischemic stroke in both white and African-American CHS participants. The risk of ischemic stroke was higher in Val allele homozygotes than in Met allele carriers. The adjusted hazard ratio for Val allele homozygotes compared to Metallele carriers was 1.50 (90% CI 1.06 to 2.12) in White participants and 3.62 (90% CI 1.11 to 11 ,9) in African American participants (Table 13). The 10-year cumulative incidence of ischemic stroke was greater in Val allelic homozygotes than in Metallele carriers, both white (10% vs. 6%) and African-American (12% vs. 3%, 1a–1b ) participants of CHS.

discussion

[0513] Of 74 genetic variants tested in CHS, 7 were found to be associated with ischemic stroke in White participants and 5 were associated with ischemic stroke in African-American participants. In particular, an association was identified between the Val allele of ABCG2 Val12Met and an increased risk of incident ischemic stroke, and this association was consistent in both Whites and African Americans.

[0514] Three of the 11 gene variants associated with incident ischemic stroke in CHS had particularly notable associations with CHD in previous studies. The first of these 3 gene variants was the Val allele of ABCG2 Val12Met (rs2231137). This gene variant has previously been associated with angiographically defined severe coronary artery disease (CAD) in two case-control studies...20

ABCG2 encodes the ATP binding cassette, subfamily G, member 2, which is a protein belonging to a large family of transporters. It is expressed on the cell surface of stem cells in bone marrow and skeletal muscle, 25 precursor endothelial cells capable of vasculogenesis in adipose tissue, 26 and endothelial cells in blood vessels of the heart 27 and brain 28 . The ABCG2 protein has recently been reported to transport sterols and has been shown to cause lipid disorders such as Tangier disease 31 and sitosterolemia 32 . However, a well-known function of the ABCG2 protein is to act as a multidrug transporter of anticancer drugs, and the ABCG2 protein is overexpressed in drug-resistant cancer cells. 33 The Met variant of ABCG2 has been reported to confer lower drug resistance and an altered localization pattern compared to the Val variant. 34 It is possible that the Met variant of the ABCG2 protein enters the vascular endothelium and have an altered function as a transporter. Homozygotes of the Val allele of ABCG2 (88% White and 88% African American) had a higher risk of stroke than carriers of the Met allele in CHS. Since there were only 16 homozygotes of the Met allele, the Met homozygotes were pooled with heterozygotes and used as a reference group. The Met allele could also be considered a protective allele, since the Met allele carriers had a lower risk of ischemic stroke than the Valallele homozygotes.

The second of the 3 gene variants with notable results from previous studies is the Ala allele of MYH15 Thr1125Ala(rs3900940). In addition to being associated with MI in two previous association studies 6 , it has been associated with an increased risk of developing CHD in the white participants of the Atherosclerosis Risk in Communities study in the tail domain of the MYH15 protein 35

The third gene variant with notable results in precursor studies is the G allele of rs3814843 in the 3' untranslated region in CALM1. This SNP has been associated with angiographically defined severe CAD in two case-control studies. 20 CALM1 encodes calmodulin 1, which binds calcium and functions in various signaling pathways including those involved in cell division, 36 membrane transport, 37 and platelet aggregation. 38

[0518] Thus, it was found that a small subset of gene variants previously associated with CHD in previous studies are also associated with ischemic stroke in CHS. Notably, the Val allele of the Val12Met SNP in ABCG2 (which encodes a sterol and anticancer drug transporter) was associated with an increased risk of ischemic stroke in both white and African-American CHS participants.

REFERENCES (ACCORDING TO EXAMPLE TWO)

1. Brass LM, Isaacsohn JL, Merikagas KR, Robinette CD. A study of twins and stroke. Stroke. 1992; 23:221-223 [0520] 2. BakS, Gaist D, Sindrup SH, Skytthe A, Christensen K. Geneticliability in stroke: a long-term follow-up study of Danish twins. Stroke. 2002; 33:769-774 [0521] 3. Welin L, Svardsudd K, Wilhelmsen L, Larsson B, Tibblin G. Analysis of risk factors for stroke in a cohort of men born in 1913. N Engl J Med 1987; 317:521-526[0522]4. Jousilahti P, Rastenyte D, Tuomilehto J, Sarti C, Vartiainen E. Parental history of cardiovascular disease and risk of stroke. A prospective follow-up of 14371 middle-aged men and women in Finland. Stroke. 1997; 28:1361-1366 [0523] 5. Rosamond W, Flegal K, Friday G, Furie K, Go A, Greenlund K, Haase N, Ho M, Howard V, Kissela B. Kittner S, Lloyd-Jones D, McDermott M, Meigs J, Moy C, Nichol G, O'Donnell CJ, Roger V, Rumsfeld J, Sorlie P, Steinberger J, Thom T, Wasserthiel-Smoller S, Hong Y American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Traffic. 2007; 115:e69-171 [0524] 6. Shiffman D, O'Meara ES, Bare LA, Rowland CM, Louie JZ, Arellano AR, Lumley T, Rice K, Iakoubova O, Luke MM, Young BA, Malloy MJ, Kane JP , Ellis SG, Tracy RP, Devlin JJ, Psaty BM [0525] Association of gene variants with incident myocardial infarction in the cardiovascular health study. Arterioscler Thromb Vasc Biol. 2008;28:173-179 7. Fried LP, Borhani NO, Enright P, Furberg CD, Gardin JM, Kronmal RA, Kuller LH, Manolio TA, Mittelmark MB, Newman A, et al. The cardiovascular health study: design and rationale. Ann Epidemiol. 1991; 1:263-276 [0527] 8. Tell GS, FriedLP, Hermanson B, Manolio TA, Newman AB, Borhani NO. Recruitment of adults 65 years and older as participants in the Cardiovascular Health Study. Ann Epidemiol. 1993; 3:358-366 [0528] 9. Cushman M, Cornell ES, Howard PR, Bovill EG, Tracy RP Laboratory methods and quality assurance in the cardiovascular health study. ClinChem. 1995; 41:264-270 10. Psaty BM, Kuller LH, Bild D, Burke GL, Kittner SJ, Mittelmark M, Price TR, Rautaharju PM, Robbins J. Ann Epidemiol. 1995; 5:270-277[0530] 11. Longstreth W.T., Jr., Bernick C., Fitzpatrick A., Cushman M., Knepper L., Lima J., Furberg CD. Frequency and predictors of death from stroke in 5,888 participants in the Cardiovascular Health Study. Neurology. 2001; 56:368-375 12. Price TR, Psaty B, O'Leary D, Burke G, Gardin J. Assessment of cerebrovascular disease in the Cardiovascular Health Study. Ann Epidemiol. 1993; 3:504-507[0532] 13. Ives DG, Fitzpatrick AL, Bild DE, Psaty BM, Kuller LH, Crowley PM, Cruise RG, Theroux S. Monitoring and determination of cardiovascular events. The Cardiovascular Health Study. Ann Epidemiol. 1995; 5:278-285 [0533] 14. American Diabetes Association. Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. diabetes treatment. 1997;20:1183-1197 [0534] 15. Rautaharju PM, MacInnis PJ, Warren JW, Wolf HK, Rykers PM, Calhoun HP. Methodology of ECG interpretation in the Dalhousie program; NOVACODE ECG classification method for clinical studies and population health surveys. Methods Inf. Med. 1990; 29:362-374 [0535] 16. D.H. O'Leary, J.F. Polak, S.K. Wolfson, Jr., MG Bond, W. Bommer, S. Sheth, BM Psaty, AR Sharrett, TA Manolio the Elder. The Cardiovascular Health Study. CHS Collaborative Research Group. Stroke. 1991; 22:1155-1163 [0536]17. D Shiffman, G Ellis, C M Rowland, M J Malloy, M M Luke, O A Lakoubova, C R Pullinger, J Cassano, Aouizerat B E, Fenwick RG, Reitz R E, Catanese J J, Leong D U, Zellner C, Sninsky J J, Topol E J, Devlin J J , Kane J P. Identification of four gene variants associated with myocardial infarction. Am J Hum Genet.2005; 77:596-605 [0537] 18. D. Shiffman, C.M. Rowland, J.Z. Louie, MM S G, Devlin J J. Gene variants of VAMP8 and HNRPUL1 are associated with early onset myocardial infarction. Arterioscler Thromb Vasc Biol. 2006; 26:1613-1618 [0538] 19. Lakoubova OA, Tong CH H, Chokkalingam AP, Rowland CM M, Kirchgessner TG, Louie J Z, Plowman LM, Sabatine MS, Campos H, Catanese JJ, Leong DU, Young B A, Lew D, Tsuchihashi Z, Luke MM, Packard CJ, Zerba KE, Shaw PM, Shepherd J, Devlin JJ, Sacks FM. The Asp92Asn polymorphism in the myeloid IgAFc receptor is associated with myocardial infarction in two distinct populations: CARE and WOSCOPS. Arterioscler thrombus VascBiol. 2006; 26:2763-2768 20. Luke MM, Kane JP, Liu DM, Rowland CM, Shiffman D, Cassano J, Catanese JJ, Pullinger CR, Leong DU, Arellano AR, Tong CH, Movsesyan I, Naya -Vigne J, C Noordhof, NT Feric, MJ Malloy, EJ Topol, ML Koschinsky, JJ Devlin, SG Ellis. Arterioscler Thromb Vasc Biol. 2007; 27:2030-2036[0540]21. Bare L A, Morrison A C, Rowland C M, Shiffman D, Luke M M, Lakoubova O A, Kane J P, Malloy M J, Ellis S G, Pankow J S, Willerson J T, Devlin J J, Boerwinkle E. Five common gene variants identify an increased genetic risk of coronary artery disease . GenetMed. 2007; 9:682-689 [0541] 22. Stata Corp. Stata StatisticalSoftware: Release 9. 2005 [0542] 23. Benjamini Y, Hochberg Y. Controlling the false detection rate: A new and powerful approach to multiple testing. Journal of the Royal Statistical Society.1995; Serial Numbers B: 1289-1300 [0543] 24. R Development Core Team. R: A Language and Environment for Statistical Computing, Reference Index Version 2.3.0. 2005 [0544] 25. Zhou S, Schuetz JD, Bunting KD, Colapietro AM, Sampath J, Morris JJ, Lagutina I, Grosveld GC, Osawa M, Nakauchi H, Sorrentino BP variety of stem cells and is a molecular one Determinant of Minor Population Phenotype. Nat Med.2001; 7:1028-1034 26. Miranville A, Heeschen C, Sengenes C, Curat CA, Busse R, Bouloumie A. Improvement of postnatal neovascularization by human adipose tissue-derived stem cells. Circulation. 2004; 110:349-355 27. K. Meissner, B. Heydrich, G. Jedlitschky, H. Meyer Zu Schwabedissen, I. Mosyagin, P. Dazert, L. Eckel, S. Vogelgesang, W. Warzok, M. Bohm, Lehmann C, Wendt M, Cascorbi I, Kroemer HK. The ATP-binding cassette transporter ABCG2 (BCRP), a marker for lateral population stem cells, is expressed in the human heart. J Histochem Cytochem. 2006; 54:215-221 [0547] 28. Zhang W, Mojsilovic-Petrovic J, Andrade MF, Zhang H, Ball M, Stanimirovic DB. The expression and functional characterization of ABCG2 in brain endothelial cells and vessels. Faseb J. 2003;17:2085-2087 [0548] 29. Janvilisri T., Venter H., Shahi S., Reuter G., Balakrishnan L., van Veen H.W. Sterol transport by the human breast cancer resistance protein (ABCG2) expressed in Lactococcus lactis .J.Biol.Chem. 2003; 278:20645-20651 [0549] 30. Janvilisri T, Shahi S, Venter H, Balakrishnan L, van Veen HW). Biochem J. 2005; 385:419-426 [0550] 31. Oram JF. Tangier disease and ABCA1. Biochim Biophys Acta. 2000; 1529:321-330 [0551]32. Schmitz G, Langmann T, Heimerl S. Role of ABCG1 and other ABCG family members in lipid metabolism. J Lipidres. 2001; 42:1513-1520[0552] 33. Maliepaard M, van Gastelen MA, de Jong LA, Pluim D, van Waardenburg RC, Ruevekamp-Helmers MC, Floot B G, Schellens JH. Overexpression of the BCRP/MXR/ABCP gene in a topotecan-selected ovarian tumor cell line. cancer res. 1999; 59:4559-4563 34. Mizuarai S, Aozasa N, Kotani H. Single nucleotide polymorphisms result in impaired membrane localization and reduced ATPase activity in multidrug transporter ABCG2. Int J Cancer. 2004;109:238-246 [0554] 35. Desjardins PR, Burkman JM, Shrager JB, Allmond LA, Stedman HH. Evolutionary implications of three new members of the human sarcomeric myosin heavy chain gene family. MolBiol Evol. 2002; 19:375-393 36. Moisoi N, Erent M, Whyte S, Martin S, Bayley PM. Calmodulin-containing substructures of the centrosomal matrix released by microtubule perturbation. J CellSci. 2002; 115:2367-2379 37. Tyteca D, van Ijzendoorn SC, Hoekstra D. Calmodulin modulates liver membrane polarity through protein kinase C-sensitive steps in the basolateral endocytic pathway. Exp cell res. 2005; 310:293-302 38. Oury C, Sticker E, Cornelissen H, De Vos R, Vermylen J, Hoylaerts M F. ATP augments von Willebrand factor-dependent shear-induced platelet aggregation by Ca 2+ -calmodulin and activation of von light chain kinase myosin. J Biol Chem. 2004; 279:26266-26273.

[0558] Supplementary analysis of SNPs in the CHS study

In a further analysis of 77 SNPs, comprising the SNPs analyzed in the CHS study described in Example 2 herein, along with additional SNPs found to be associated with CHD risk in a cholesterol and recurrent event (CARE) study and a WOSCOPS study (Shiffman et al., Arterioscler Thromb Vasc Biol. 2008 January;28(1):173-977), three other SNPs predicting the risk of ischemic stroke were identified by Cox -Proportional hazard analysis identified which had one-sided p-values ​​of <=0.05 in whites after adjusting for age and sex, and also after accounting for all conventional risk factors including smoking, diabetes, hypertension, HDL-C, LDL-C and BMI (similar to Shiffman et al., ArteriosclerThromb Vasc Biol. 2008 Jan;28(1):173-9). These three SNPs are shown in Table 14. In addition, as shown in Table 14, black and white hazard ratios were consistent for SNPs rs2243682/hCV1624173 and rs34868416/hCV25951678.

Example 3: SNPs associated with non-cardioembolic stroke in the Vienna Stroke Registry Review

For SNPs identified in previous studies such as Atherosclerosis Risk in Communities (ARIC) (eg, Bare, et al. (2007), Genet Med9(10):682-9 and McPherson, et al (2007), Science316 (5830):1488-91) carriers of the CHD risk alleles for each SNP in the Vienna Stroke Register (VSR) were analyzed for an increased risk of non-cardioembolic stroke. In a case-control study, 562 non-cardioembolic stroke cases from VSR7 and 815 healthy controls from the city of Vienna8 were genotyped for each of the SNPs. The allele previously associated with CHD risk was prespecified as the risk allele, and this risk allele was tested for association with non-cardioembolic stroke.

It was found that carriers of the CHD risk allele of the following four SNPs had an increased risk of non-cardioembolic stroke (the name of the gene or chromosome containing each SNP is given in parentheses): rs3900940 (MYH15), rs20455 (KIF6), rs1010 (VAMP8) and rs10757274 (chromosome 9p21) (characteristics of these SNPs are presented in Table 16). The odds ratios (OR) for the associations of these SNPs with noncardioembolic stroke were as follows: 1.20 (90% confidence interval 0.95-1.50) for rs10757274 on chromosome 9p21, 1.24 (1.01-1.5 ) for rs20455 in KIF6, 1.31 (1.07-1.60) for rs3900940 in MYH15 and 1.21 (0.99-1.49) for rs1010 in VAMP8.

[0562] Subjects and Methods

[0563] Studienpopulation

The stroke cases in VSR are consecutive Caucasian patients admitted to stroke units in Vienna between October 1998 and June 2001 within 72 hours of the onset of acute ischemic stroke. All patients underwent cranial CT or MRI and were documented according to a standardized protocol including stroke severity and risk factors and medical history 7 . Only patients with non-cardioembolic stroke were included as cases in this study. Controls were unrelated Caucasian participants in a health care program in Vienna, 45 years of age or older, free from arterial vascular disease and reporting no arterial vascular disease in first-degree relatives. Genotypes were determined as previously described 9 . This study was in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the Medical University of Vienna. All subjects gave written informed consent.

[0565] Statistics

[0566] Differences in traditional risk factors between cases and controls were assessed by the Wilcoxon rank sum test (continuous variables) or by the chi-square test (discrete variables). Odds ratios estimated from logistic regression models were adjusted for conventional risk factors such as age (at time of index stroke event for cases, on admission for controls), gender, current smoker (versus not), diabetes mellitus (defined by a physician's diagnosis or use of either insulin or oral) adjusted hypoglycemic medications), hypertension (defined by systolic blood pressure > 140 mmHg, diastolic blood pressure > 90 mmHg, medical diagnosis of hypertension, or use of antihypertensive drugs), dyslipidemia (defined by total cholesterol ≥ 240 mg). / dL (6.2 mmol/L), LDL-C ≥ 160 mg/dL (4.1 mmol/L), HDL-C < 40 mg/dL (1.0 mmol/L) or the use of lipid-lowering drugs ) and body mass index (BMI). Because the purpose of this study was to determine whether the same alleles associated with increased risk of CHD in previous studies are associated with increased risk of noncardioembolic stroke in VSR, one-sided p-values ​​and 90% confidence intervals were used (because 95% confidence that the true risk estimates were greater than the lower bounds of the 90% confidence interval) was used. All other p-values ​​are two-tailed. Effect sizes for carriers of the CHD risk alleles compared to non-carriers, detectable at 90% power, were calculated using QUANTO 10 assuming a one-tailed test and an alpha of 0.05. To account for testing of multiple hypotheses, the q-values ​​of the false detection rate were estimated by the method of Benjamini and Hochberg 11 using the p-values ​​for CHD risk allelic carrier status from the age- and sex-adjusted models. The q-value of a given SNP represents the expected proportion of false positives among the set of SNPs with equal or lower q-values.

Structural software was used to estimate both the number of subpopulations (by ancestry) in this study and the level of ancestry admixture for each individual subject 12 based on genotypes of 130 SNPs whose minor allele frequencies ranged from 0.95 % to 49.8%. The likely level of admixture was included as a covariate in logistic regression models to adjust risk estimates for possible confounding based on population structure. Models assuming one, two, three, or four subpopulations were tested, and repeat runs of the structural program were performed for each model with a burn-in of 20,000 replicates followed by 10,000 replicates using the mixture model with independent allele frequencies and default values ​​for other parameters.

Results

The clinical characteristics of the cases and controls are presented in Table 15. It was determined whether carriers of the alleles of SNPs previously associated with an increased risk of CHD 2,3 were also associated with an increased risk of non-cardioembolic stroke. The genotype distribution of these SNPs does not deviate from the Hardy-Weinberg equilibrium (p > 0.17). Incorrect detection rate q values ​​for the SNPs were estimated to account for multiple testing. Four of the SNPs were found to be associated with non-cardioembolic stroke, with false detection rate q-values ​​at or below 0.15. For these four SNPs, carriers of the CHDrisk allele had an increased risk of non-cardioembolic stroke compared to non-carriers after adjustment for age and sex: the odds ratios were 1.20 (90% confidence interval (CI) 0.95-1 .50) for the C9p21 SNP, 1.24 (CI 1.01-1.52) for the KIF6 SNP, 1.31 (CI 1.07-1.60) for the MYH15 SNP and 1.21 (CI 0.99-1.49) for the VAMP8SNP (Model 1, Table 17). When the homozygous and heterozygous carriers were examined separately, it was shown that the homozygous carriers (OR = 1.59) in particular had an increased risk (OR of the heterozygous carriers = 1.05) for the C9p21SNP. These odds ratios decreased somewhat after adjusting for additional risk factors (smoking, hypertension, diabetes, dyslipidemia, and BMI), with the exception of the odds ratio for the VAMP8 SNP, which increased (Model 2, Table 17). Removal of all cases with a history of myocardial infarction (n=40) from the analysis altered the fully adjusted odds ratios for the C9p21 homozygotes (1.45, CI 1.05-1.99), MYH15 carriers (1.24 , CI 0.99-1.55) and VAMP8 not significant carriers (1.28, CI 1.01-1.61). However, removal of cases with a history of myocardial infarction reduced the odds ratio for KIF6 carriers to 1.15 (CI 0.91-1.45).

Population structure was examined in this study using a Bayesian clustering approach 12 to evaluate models that assumed one, two, three, or four distinct subpopulations. A model that assumes two subpopulations has been found to result in the highest estimated log-likelihood. Using the two-subpopulation model, the level of lineage admixture was estimated for individual subjects. The fully adjusted odds ratios of the SNPs shown in Table 17 were not significantly altered (the largest change was a 0.01 decrease in the odds ratio for C9p21 homozygotes) when further adjusted for the subjects' ancestry.

Discussion

[0572] Four SNPs were found to be associated with non-cardioembolic stroke after adjusting for age and sex when the false detection rate was controlled at 0.15. For these four SNPs, carriers of the CHD risk allele (G from rs10757274 on C9p21, Arg from Trp719Arg (rs20455) in KIF6, Ala from Thr1125Ala (rs3900940) in MYH15 and C from rs1010 in VAMP8) also had an increased risk of non-cardioembolic stroke .

MYH15 encodes myosin heavy polypeptide 15, a motor protein of the class II family of sarcomeric myosin heavy chains. The Thr1125Ala SNP is located in the coiled-coil rod domain of the MYH15 protein and the Thr1125 residue has been shown to be phosphorylated13,14. As the Ala1125 residue could not be phosphorylated, this substitution could impair the function of the MYH15 protein.

[0574] VAMP8 encodes vesicle-associated membrane protein 8, which functions in platelet degranulation pathways 15 . The rs1010 SNP is located in the 3' untranslated region of VAMP8 in a potential microRNA binding site 16 .

Thus, this example shows that carriers of the CHDrisk allele of the SNPs rs20455 in KIF6, rs3900940 in MYH15, rs1010 in VAMP8 and rs10757274 on chromosome 9p21 had an increased risk of non-cardioembolic stroke in VSR.

REFERENCES (ACCORDING TO EXAMPLE THREE)

1. Rosamond W, Flegal K, Furie K, Go A, Greenlund K, Haase N, Hailpern SM, Ho M, Howard V, Kissela B, Kittner S, Lloyd- Jones D, McDermott M, Meigs J, Moy C, Nichol G, O'Donnell C, Roger V, Sorlie P, Steinberger J, Thom T, Wilson M, Hong Y: Heart disease and stroke statistics - 2008 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Edition 2008; 117:e25-146. 2. Bare L A, Morrison A C, Rowland C M, Shiffman D, Luke M M, Lakoubova O A, Kane J P, Malloy M J, Ellis SG, Pankow J S, Willerson J T, Devlin J J, Boerwinkle E: Five common gene variants identifying increased genetic risk for coronary artery disease heart disease. Genet Med 2007; 9:682-689.[0578] 3. McPherson R, Pertsemlidis A, Kavaslar N, Stewart A, Roberts R, Cox DR, Hinds D A, Pennacchio L A, Tybjaerg-Hansen A, Folsom A R, Boerwinkle E, Hobbs H H, Cohen J C: A common allele on chromosome 9 associated with coronary heart disease. Science 2007;316:1488-1491. 4. Morrison AC, Bare LA, Luke MM, Pankow JS, Mosley TH, Devlin JJ, Willerson JT, Boerwinkle E.: Singlenucleotide polymorphisms associated with coronary heart diseasepredict incident ischemic stroke in the Atherosclerosis Risk inCommunities (ARIC) study. Cerebrovascular Disease 2008; 26:420-424.[0580] 5. Zee R Y, Ridker P M: Two common gene variants on chromosome 9 and the risk of atherothrombosis. stroke 2007; 38:e111.[0581] 6. Luke MM, O'Meara ES, Rowland CM, Shiffman D, Bare LA, Arellano AR, Longstreth WT, Jr, Lumley T, Rice K, Tracy RP, Devlin JJ, Psaty BM: Gene Variants Associated With IschemicStroke. The Cardiovascular Health Study. Stroke 2008. [0582] 7.Lang W: The Vienna Stroke Register - goals and methods. The Vienna Stroke Study Group. Vienna Klin Wochenschr 2001; 113:141-147.[0583] 8. Lalouschek W, Lang W, Mullner M: Current strategies of secondary prevention after a cerebrovascular event: the Viennastroke registry. stroke 2001; 32:2860-2866. 9. D Shiffman, S G Ellis, C M Rowland, M J Malloy, M M Luke, O A Lakoubova, CR Pullinger, J Cassano, BE Aouizerat, R G Fenwick, R E Reitz, JJ Catanese, DU Leong, C Zellner, JJ Sninsky, Topol E J, Devlin J J, Kane J P: Identification of four gene variants associated with myocardial infarction. Am J Hum Genet 2005; 77:596-605. 10. QUANTO: Release 1.1 A computer program for power and sample size calculations for genetic epidemiological studies. Gauderman WJMJ.2006. 11. Benjamini Y, Hochberg Y: Controlling the false discovery rate: A new and powerful approach to multiple testing. Journal of the Royal Statistical Society 1995; Serial numbers B: 1289-1300.[0587] 12. Pritchard JK, Stephens M, Donnelly P: Inference of population structure using multilocus genotype data. Genetics 2000;155:945-959. 13. Gnad F, Ren S, Cox J, Olsen JV, Macek B, Oroshi M, Mann M.: PHOSIDA (Phosphorylation Site Database): Management, structural and evolutionary study and prediction of phosphosites. Genome Biol 2007; 8:R250. 14. Olsen JV, Blagoev B, Gnad F, Macek B, Kumar C, Mortensen P, Mann M: Global, in vivo, and site-specific phosphorylation dynamics in signaling networks. cell 2006; 127:635-648. 15. Polgar J., Chung SH, Reed GL: Vesicle-associated membrane protein 3 (VAMP-3) and VAMP-8 are present in human platelets and are required for granule secretion. blood 2002; 100:1081-1083. 16. Shiffman D, Rowland CM, Louie JZ, Luke MM, Bare LA, Bolonick JI, Young BA, Catanese JJ, CF Stiggins, CR Pullinger, EJ Topol, MJ Malloy, JP Kane, SG Ellis, JJ Devlin: Gene variants of VAMP8 and HNRPUL1 are associated with early onset myocardial infarction. Arterioscler Thromb Vasc Biol 2006; 26:1613-1618. 17. Helgadottir et al.: The same sequence variant at 9p21 associated with myocardial infarction, abdominal aortic aneurysm and intracranial aneurysm. Nat Genet 2008; 40:217-224.

[0593] Supplementary analysis of SNPs in the Vienna StrokeRegistry

In a further analysis, the genotype of 19 SNPs (previously determined to be associated with incident CHD in white or black participants in the ARIC study) in the Vienna Stroke Registry ("VSR", approximately 764 ischemic) identified stroke cases, including 562 atherothrombotic stroke cases and 815 controls aged 45 years or older from the same region).

[0595] As shown in Table 18, the risk alleles (associated with CHD in ARIC) for certain of these 19 SNPs (two-sided p-value of <0.2) were found to be associated with ischemic stroke (in the table as “ischemic ') associated are the 'Outcome' column of Table 18), atherothrombotic stroke (labelled 'athero' in the 'Outcome' column of Table 18) and/or early onset stroke (in the 'Outcome' column of Table 18 18 labeled “early onset”) in VSR before and/or after adjustment for traditional risk factors such as age, gender, body mass index, smoking, diabetes, impaired fasting glucose, hypertension, LDL-cholesterol, and HDL-cholesterol (results after adjustment are marked "yes" and pre-fit results are marked "no" in the "Fit?" column of Table 18) (p-values ​​shown in Table 18 are two-tailed p-values; thus, the one-tailed p-values ​​for these SNPs have half of these two-sided p-values).

[0596] Early onset stroke is ischemic stroke that occurs early in life. As used herein, early onset stroke is defined as those stroke events that occurred before the mean stroke age of the ischemic events. The controls for these early-onset cases are those controls whose age was above the median age of all controls in the study (ie, young cases versus old controls was the study design).

Example 4: SNPs associated with stroke in the UCSF/CCF study

In atherothrombotic stroke cases and healthy controls from the Vienna Stroke Registry ("VSR", approximately 562 cases and 815 controls, study ID V0031), the allele frequencies of 25,878 putative functional SNPs and the allele frequencies of approximately 3,300 of these 25,878 were determined. It was found that SNPs are associated with atherothrombotic (non-cardioembolic) stroke (two-tailed p-value less than or equal to 0.05). These 3,300 SNPs were then further tested in a stroke study of cases with a history of stroke and controls with no history of stroke or myocardial infarction from the UCSF and CCF sample sets (Study ID GS41). The allele frequencies of 292 of these 3,300 SNPs were again associated with stroke risk (one-sided p<0.05) in the UCSF/CCF stroke study (approximately 570 cases and 1604 controls), and the risk alleles were the same in VSR and in UCSF/CCF studies. These stroke associations were then confirmed by individual genotyping of the 292 SNPs in VSR patients, and it was again found that 101 of these SNPs were associated with stroke risk (p<0.05 in allelic, additive, dominant, or recessive modes). These 101 SNPs were then genotyped in the UCSF/CCF stroke study and it was found that 61 of these SNPs were still associated with stroke in the UCSF/CCF study (1-sided p<0.05 or 2-sided p < 0.1) and have the same risk allele as in the VSR study.

These 61 SNPs and the stroke association data in both the UCSF/CCF and VSR studies are provided in Table 19. These SNPs were further analyzed in additional sample sets, as discussed below in Examples five, six and seven.

Example Five: SNPs Associated with Stroke in the German West Study

The identification of 61 SNPs associated with stroke in both of two case-control studies (Vienna Stroke Registry and the UCSF/CCF Stroke Study) is described in Example 4 above. Here, Example 5 describes the analysis of these 61 SNPs, plus 17 additional SNPs, in the German West Study (which may be referred to herein interchangeably as the "Münster" stroke study).

The German West study, which is a stroke case-control study, included 1,300 cases of ischemic stroke and 1,000 healthy controls. The cases of ischemic stroke were further classified into several stroke subtypes by TOAST criteria, allowing analyzes of the association of genotypes of the tested SNPs with the following endpoints: 1) ischemic stroke (result: "ischemic_stk" in Tables 20-21) , 2) non-cardioembolic stroke (Result: "nonce_stk" in Tables 20-21; ischemic stroke not of cardioembolic origin), 3) cardioembolic stroke (Result: "CE_stk" in Tables 20-21), 4) atherothrombotic stroke ( Result: "athero_stk" in Tables 20-21), 5) lacunar stroke (Result: "lacunar_stk" in Tables 20-21), 6) stroke without heart disease (Result: "nohd_stk" in Tables 20-21; cases of ischemic stroke, excluding those with a history of heart disease), 7) recurrent stroke (score: "recurrent_stk" in Tables 20-21; stroke cases that also included a history of stroke), and 8) early stroke (score: "EO_stk" in Tables 20-21; cases younger than the mean age of all cases and controls older than the mean age of all controls).

[0601] The potential population stratification was also adjusted (in addition to the traditional risk factors) when assessing the risk estimates of the SNPs. The risk allele of each of the SNPs tested in this study was pre-specified to be the same as in previous studies, and a two-sided p-value less than 0.1 (equivalent to one-sided p-values ​​less than 0.05) or 2 one-tailed p-values ​​less than 0.2 (corresponding to one-tailed p-values ​​less than 0.1) were used as cut-offs for statistical significance.

[0602] SNPs that showed a significant association with stroke risk in the German West study are provided in Tables 20-21. Table 20 provides stroke-associated SNPs that share the same risk allele and two-sided p-values ​​less than 0.1 (corresponding to one-sided p-values ​​of less than 0.05), and Table 21 provides stroke-associated SNPs who have the same risk allele and 2-sided p-values ​​that range from 0.1 to 0.2 (equivalent to 1-sided p-values ​​that range from 0.05 to 0.1).

[0603] Supplementary analysis of SNPs in the German West study

[0604] Overview and results

[0605] The German West study also identified SNPs associated with non-cardioembolic stroke in three large study populations (the German West study and the Vienna and UCSF/CCF studies described above). A case-control study design was used: the Vienna study, the UCSF/CCF study, and the German West study (728 non-cardioembolic stroke cases, 1,041 controls). It was determined whether the alleles of those SNPs that were associated with increased risk in both the Vienna and the UCSF/CCF study were also associated with increased risk in the German-West study (therefore one-tailed significance tests were used) . Logistic regression analysis adjusting for age, sex, hypertension and diabetes was performed.

[0606] Four SNPs were found to be associated with non-cardioembolic stroke (p<0.05) in the Deutsch-West study (before correction for multiple tests - 46 SNPs and 3 genetic models) as well as with non-cardioembolic stroke were associated in the UCSF/CCF and Vienna studies described above. These four SNPs (and the genes they are in or near) are as follows: rs544115 in NEU3, rs1264352 near DDR1, rs10948059 in GNMT, andrs362277 in HD. An increased risk of non-cardioembolic stroke was observed in carriers of the following genotypes compared to non-carriers for each of these four SNPs (with carrier frequency in controls, odds ratio and 90% confidence interval given): CT or CC carriers of rs544115 (96 .0% of controls). , OR 2.39, CI 1.31-4.36), CG or CC carriers of rs1264352 (23.9% of controls, OR 1.38, CI 1.08-1.76), CT or CC carriers of rs10948059 (77% of controls, OR 1.38, CI 1.06-1.79) and CC carriers of rs362277 (80.0% of controls, OR 1.39, CI 1.05-1 ,84). After correcting for multiple tests, this set of 4 SNPs had a false detection rate (FDR) of 0.67.

[0607] Topics and Methods

[0608] Fields of study

[0609] Subjects in all three studies (the Deutsch-West study, as well as the Vienna and UCSF/CCF studies) were unrelated males and females of European descent and provided written informed consent for stroke cases that were not of cardioembolic origin, including stroke large and small vessels) were drawn from the Vienna Stroke Register (VSR). Stroke cases in VSR were consecutive Caucasian patients admitted to stroke units in Vienna between October 1998 and June 2001 within 72 hours of the onset of acute ischemic stroke. All patients underwent cranial CT or MRI and were documented according to a standardized protocol including stroke severity, risk factors and medical history. Controls were unrelated Caucasian participants in a health care program in Vienna, 45 years of age or older, free of arterial vascular disease and reporting no arterial vascular disease in first-degree relatives. This study was in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the Medical University of Vienna.

The UCSF/CCF study included 416 cases and 977 controls drawn from Genomic Resource at the University of California San Francisco (UCSF) and 154 cases and 627 controls drawn from the Genebank of Cleveland Clinic Foundation (CCF ) were drawn. Cases in the UCSF/CCF study did not include stroke subtype information. To enrich the cases of non-cardioembolic stroke, patients with a history of stroke who also had a history of cardiac arrhythmia or heart valve disease that could have led to cardioembolic stroke or surgery were excluded. Controls from UCSF had no history of stroke, atherectomy, or CHD (including coronary artery stenosis, myocardial infarction, or coronary revascularization procedures). Cases and controls of CCF were patients who had coronary angiography. The cases had a history of stroke and no history of atrial fibrillation, heart valve disease, or surgery. Controls had no history of stroke or CHD (including myocardial infarction, greater than 50% coronary artery stenosis, peripheral vascular disease, or revascularization procedures).

The Deutsch-West Study included 728 non-cardioembolic cases (ischemic strokes that were not of cardio-embolic origin) from the Westphalian Stroke Registry and 1,041 controls from the same region of Germany recruited from the Dortmund Health Study for non-cardioembolic stroke analysis. For the analysis of cardioembolic stroke, 462 cardioembolic strokes (ischemic strokes of cardioembolic origin), which were also included in the Westphalian Stroke Registry, were compared with the same 1401 controls from the Dortmund Health Study.

[0612] Statistics

[0613] Differences in traditional risk factors between cases and controls were assessed by the Wilcoxon rank sum test (continuous variables) or by the chi-square test (discrete variables). Odds ratios for the Vienna study or the UCSF/CCF study were not adjusted, and odds ratios for the German-West study were estimated from logistic regression models and adjusted for traditional risk factors such as age (at the time of the index stroke event for cases, at registration for controls), gender, diabetes mellitus (defined by a medical diagnosis or use of either insulin or oral hypoglycemic medication), hypertension (defined by a systolic blood pressure > 140 mmHg, a diastolic blood pressure > 90 mmHg, a medical diagnosis of hypertension, or the use of antihypertensive drugs). In order to account for several hypothesis tests, the q-values ​​of the false detection rate (FDR) were calculated according to the method of Benjamini and Hochberg (Journal of the Royal Statistical Society 1995; Serials B: 1289-1300) using the p-values ​​for the risk- Genotype carrier status estimated from the model adjusted for age, sex, hypertension and diabetes.

Example 6: SNPs associated with stroke or statin response in CARE or PROSPER studies

The identification of 61 SNPs associated with stroke in both of two case-control studies (Vienna Stroke Registry and the UCSF/CCF Stroke Study) is described in Example 4 above. Example 5 above describes the analysis of these 61 SNPs plus 17 additional SNPs in the West German study. Here, Example 6 describes the analysis of SNPs for association with stroke risk and stroke statin response (SSR) in two pravastatin studies: CARE (Cholesterol and Recurrent Events study, which includes people who had previously had MI) and PROSPER (“Prospective Study of Pravastatin in the Elderly at Risk” study, which includes elderly people with or without a history of cardiovascular disease (CVD).

In CARE, SNPs were analyzed for association with stroke risk SSR. SNPs that were significantly associated with stroke risk or SSR in CARE (which were also associated with stroke risk in the German West study described above in Example 5) are provided in Table 22 (stroke risk) and Table 23 (SSR). Additional SNPs that were significantly associated with stroke risk or SSR in CARE are listed in Table 24 (stroke risk) and Table 25 (SSR). Additional SNPs that were significantly associated with stroke risk or SSR in CARE are listed in Table 26 (stroke risk) and Table 27 (SSR).

Table 26 shows that, for example, individuals in CARE who were G/G homozygotes at the CALM1 SNP (rs3814843/hCV11474611) had an increased risk of stroke (HR = 7.54 with a two-sided p-value of 0.0441 for genotypic ). Mode and adjusted for statin use, HR=7.43 with a two-sided p-value of 0.0455 for recessive mode and adjusted forstatin use, HR=6.64 with a two-sided p-value of 0.0606 for genotypic mode and not adjusted and HR = 6.67 with a two-sided p-value of 0.0599 for recessive mode and unadjusted).

Results of analysis of the MYH15 SNP (rs3900940/hcv7425232) for association with stroke risk in CARE are provided in Table 28 /hcv7425232) had an increased risk of stroke (HR=1.403 with a two-sided p-value of 0.153, adjusted). for statin use; HR=1.51 with a two-sided p-value of 0.086, adjusted for traditional risk factors, BMI, and statin use, and HR=1.49 with a two-sided p-value of 0.094 when for CHD, traditional risk factors, BMI and statin use adjusted). All p-values ​​(including P int -values) provided in Tables 22-28 are two-tailed p-values.

[0618] In PROSPER, SNPs were scored for association with stroke risk or SSR in the entire study cohort (strata: "ALL") or in the subgroup with a CVD history (strata: "hist") or without a CVD history (strata: " no hist")). SNPs were considered to be significantly associated with stroke risk if they met the p-value cut-offs and shared the same risk allele as in previous studies (e.g., as described in Examples four, five, and six herein), and those SNPs that significantly associated with stroke risk are provided in Tables 29-30. Specifically, Table 29 lists SNPs associated with stroke risk that have P_all < 0.2 (that is the p-value based on the entire study cohort), and Table 30 lists SNPs associated with stroke risk that have P_placebo < 0.2 (that is is the p-value based on only the placebo arm of the study). For SSR, the results of the analyzes of pravastatin-treated versus placebo-treated subjects are provided in Table 31 (listing SNPs with Pint < 0.1) and Table 32 (listing SNPs with Pint < 0.2). All p-values ​​(including P int values) provided in Tables 29-32 are two-tailed p-values ​​(two-tailed p-value cutoffs of 0.1 and 0.2 are equivalent to one-tailed p-value cutoffs of 0, 05 and 0.1). ,or).

Table 30 shows that, for example, individuals in PROSPER who were A/G heterozygotes on chromosome 9p21 SNP (rs1075727/hCV26505812) had an increased risk of stroke (HR=1.464 with a two-sided p-value of 0.035, based ). in the placebo group; see the first row for rs10757274/hCV26505812 in Table 30).

Table 30 also shows that, for example, individuals in PROSPER who were T/T homozygotes at chromosome 4q25 SNP (rs2200733/hCV16158671) had an increased risk of stroke (HR=3.711 with a two-sided p-value of 0.025). based on the placebo group).

Also in the CARE and PROSPER studies, chromosome 9p21 SNPrs10757274 (hCV26505812) was further analyzed for association with SSR, including unmatched and matched analysis. The adjusted analysis in CARE (Table 37) was adjusted for age, gender, smoking status, hypertension, diabetes, body mass index (BMI), and LDL and HDL levels, and the adjusted analysis in PROSPER (Table 38) was adjusted for country, gender, age, LDL, HDL, smoking status (current vs. past or never), history of hypertension and diabetes. Table 37 provides results in CARE, and Table 38 provides results in PROSPER (whether each analysis is unadjusted or adjusted is indicated in the column "adjust" in Table 37 or by the column labels "unadj" and "adj" in Table 38 indicated). All p-values ​​(including P int -values) provided in Tables 37-38 are two-tailed p-values.

In CARE, among the three genotypes of SNP rs1075727 (homozygous carriers of each of the two alternative alleles plus heterozygous carriers), the heterozygous carriers of SNP rs10757274 (49% genotype frequency) had the largest reduction in the number of stroke events (HR = 0.61 ) after treatment with pravastatin after adjustment for conventional risk factors (two-tailed p-value = 0.034, and the genotype after treatment interaction had a two-tailed p-interaction value (“pval_intx” or P int ) = 0.44; see the 13th row under the column headings in Table 37). In PROSPER, heterozygous carriers of the G allele (allele at risk) at SNP rs1075727 in the placebo arm had an increased risk of stroke (see, for example, the first row for rs10757274/hCV26505812 in Table 30), as indicated above. In addition, in PROSPER, after stratification by rs10757274 genotype, heterozygous carriers of this SNP (51% of the population) also had the largest reduction in the number of stroke events (unadjusted HR=0.777) in the pravastatin-treated compared to the placebo-treated arms of the study (two-tailed p-value =0.066, see 3rd row under column headings in Table 38) whether unadjusted or adjusted for common risk factors.

Example 7: SNPs associated with stroke in the Cardiovascular Health Study (CHS)

The identification of 61 SNPs associated with stroke in both of two case-control studies (Vienna Stroke Registry and the UCSF/CCF Stroke Study) is described in Example 4 above. Example 5 above describes the analysis of these 61 SNPs plus 17 additional SNPs in the West German study. Here, example seven describes the analysis of SNPs previously found to be associated with stroke (e.g., in examples four, five, and/or six above) for association with stroke events in the Cardiovascular Health Study (CHS), which was a population-based Study of is older white or black participants in United States. The association was analyzed for three related stroke endpoints: stroke (all subtypes) (endpoint: “stroke” in Tables 33-36), ischemic stroke (excluding hemorrhagic stroke) (endpoint: “ischem” in Tables 33-36) and atherothrombotic stroke (includes hemorrhagic stroke and cardioembolic stroke) (endpoint: “athero” in Tables 33-36).

The results of the CHS study are provided in Tables 33-36. Specifically, SNPs associated with stroke risk in white or black individuals with two-tailed p-values ​​less than 0.1 (equivalent to one-tailed p-values ​​less than 0.05) are shown in Table 33 (white individuals ) and Table 34 (Black individuals), and SNPs associated with stroke in White or Black individuals with two-sided p-values ​​between 0.1 and 0.2 (corresponding to one-sided p-values ​​between 0.05 and 0.2) are associated 0.1) are given in Table 35 (white people) and Table 36 (black people).

Example 8: Additional LD-SNPs associated with stroke

[0625] A further study was performed to identify SNPs in linkage disequilibrium (LD) with certain "interrogated SNPs" found to be associated with stroke, as described herein and shown in the Tables. The SNPs queried are shown in column 1 (giving the hCV identification numbers of each queried SNP) and column 2 (giving the public identification numbers of each queried SNP) of Table 4. The methodology is described earlier in the present application. To summarize briefly, the power threshold (T) has been set to an appropriate level, such as B. 51% to detect disease association using LD markers. This performance threshold is based on Equation (31) above, which includes allele frequency data from previous disease association studies, the predicted error rate for failure to detect true disease-associated markers, and a significance level of 0.05. Using this power calculation and the sample size, a threshold LD or r 2 value was derived for each sampled SNP (r T 2 , equations (32) and (33) above), the threshold r T 2 is the minimum value of the coupling imbalance between the queried SNP and its LD-SNPs, possibly such that the unqueried SNP still retains a strength greater than or equal to T to detect disease association.

Based on the above methodology, LD-SNPs were found for the queried SNPs. Several example LD-SNPs for the queried SNPs are listed in Table 4; each LD-SNP is associated with its respective queried SNP. Also shown are the public SNP IDs (RS numbers) for the polled and LD SNPs, if available, and the threshold r 2 and power used to determine this and the r 2 value of the coupling imbalance between the queried SNP and its corresponding LD SNP. As an example in Table 4, the interrogated stroke-associated SNP was calculated to be rs11580249(hCV11548152) in LD with rs12137135(hCV30715059) at an r 2 value of 0.4781, based on a 51% power calculation, making the latter SNP is also established as a marker for strokes.

[0627] In general, the threshold r T 2 can be adjusted such that one of ordinary skill in the art would consider that any two SNPs have an r 2 value greater than or equal to the threshold r. The sup.2 value would be in sufficient LD to each other that each SNP is useful for the same uses, such as determining a person's risk of stroke. For example, in various embodiments, the threshold r T 2 is used to classify SNPs as being in sufficient LD with a queried SNP (so that these LD SNPs can be used for the same benefits as the queried SNP, e.g. B. to determine of stroke risk) for example to 0.7, 0.75, 0.8, 0.85, 0.9, 0.95, 0.96, 0.97, 0.98, 0.99, 1 etc. (or any other r² value in between) values). Threshold r T 2 values ​​can be used with or without consideration of performance or other calculations.

All publications and patents cited in this specification are incorporated herein by reference in their entirety. Various modifications and variations of the described compositions, methods and systems of the invention will be apparent to those skilled in the art without departing from the scope and spirit of the invention. Although the invention has been described in connection with specific preferred embodiments and certain working examples, it should be understood that the claimed invention should not be unduly limited to such specific embodiments. Indeed, various modifications of the above described modes for carrying out the invention which are obvious to those skilled in the art of molecular biology, genetics and related fields are intended to fall within the scope of the following claims.

TABLE-US-00001 TABLE 3 CD000022WORD Marker Allele Primer 1 (Allele-Specific Primer) Primer 2 (Allele-Specific Primer) CommonPrimer hCV1022614 C/T CTGCAGCCTCTCCTACG (SEQ ID NO: 1567)CCTGCAGCCTCTCCTACA (SEQ ID NO: TTGATA8) (TTGATA8). ID NO: 1569) hCV1053082 C/T TTGCAGAGAAGCGTTCC (SEQ ID NO: 1570) CTTTGCAGAGAAGCGTTCT (SEQ ID NO: 1571) CTGAGCTTTGTGAAGAGAAACTGA (SEQID NO: 1572) hCV1116757 C/T GACAAACTGAGGGACAACG:15 SEQ ID NO: 1572; 1574 ) CCTCTGACAGACGCTTCTTGA (SEQ IDNO: 1575) hCV1116793 C/T GGAAGGTCATCCTGGG (SEQ ID NO: 1576)GGAAGGTCATCCTGGA (SEQ ID NO: 1577) CGAAGAGTTTCTGTGTGGTACAG (SEQ IDNO: 1578) hCV11354788 C/T TGAGACGGGTGGTAACC (SEQ ID NO: 1579)TTGAGACGGGTGGTAACT ( SEQ CAGCTTTGAAGGGCATCCATATGA (SEQ ID NO: 1581) hCV11425801 C/T TCCCACACCACCTGC (SEQ ID NO: 1582) CTCCCACACCACCTGT (SEQ ID NO: 1583) GCCACCACAATGTCTCTCAATAC (SEQ ID NO: 1584) hCV114Q258GACACG42 C/T ID15: CGCAA (SEQ ID NO: 1583) SEQ ID NO:1587) hCV11450563 G/T TAAAGAATGCATAAATTAGTGTGG (SEQ IDTTAAAGAATGCATAAATTAGTGTGT (SEQ ID NO: 1589)GATCCTAATTGGATTTGAAGACTTA (SEQ ID NO: 1590) NO: 1588) hCV11474611G/T ATCGCCCATGTGCTG (SEQ ID NO: 1591) CATCGCCCATGTGCTT (SEQ ID NR: 1592) TCAAACCAGGAACCCTATCT (SEQ ID NR: 1593) hCV11548152 G/TCTGTAAACGCTGGTCTGG (SEQ ID NR: 1594) ACTGTAAACGCTGGTCTGT (SEQ ID NR: 1595) CCTTGTCCCTGATTGCTTCTTCA (SEQ ID NR: 1596) hCV11738775 C/AA IDTC (TCCGSE: CGTCQ: CGTCQ 1597) TCCCCGCTTCAACACA (SEQ ID NO:1598) AACTTCATTCGGCACTTGCTACAA (SEQ ID NO: 1599) hCV11758801 C/GAGTACCTCTTGGTCTCTCTCC (SEQ ID NO: 1600) AGTACCTCTTGGTCTCTCTCG (SEQID NO: 1601) GCATGTTGTGTTTCTGATTGTAC (SEQ ID NO: 1602) hCV11861255A/G AAAGGGCCGAGCTGATA (SEQ ID NO : 1603) AGGGCCGAGCTGATG (SEQ ID NO: 1604) GGGAGGTTTGGAGAGAGAGTAT (SEQ ID NO: 1605) hCV12071939 G/TGACCGTGGTCCCTTG (SEQ ID NO: 1606) TGACCGTGGTCCCTTT (SEQ ID NO: 1607) CGCCCGGAGACAGAA (SEQ ID NO: 1609) hC028 /TTAGCAACTGCTATCAATGACAG ( SEQ ID NO: 1609) TAGCAACTGCTATCAATGACAT (SEQ ID NO: 1610) AGTGAAGGAGTTAACTGAGTGTGTA (SEQ ID NO: 1611)hCV1262973 A/G TGGGTCCCAAGCTCAT (SEQ ID NO: 1612) TGGGTCCCAAGCTCAC (SEQ ID NO: 16131) ID NO: 3 TSEQ . hCV1305848 A/GACATTTATACCATTTCCCGAGT (SEQ ID NO: 1615) ACATTTATACCATTTCCCGAGC(SEQ ID NO: 1616) GCCTAACAACAGTACCTACTCCATAGG (SEQ ID NO: 1617)hCV1348610 A/G CATTTGTCCTAAAAGTACCTCTCT (SEQ IDCATTTGTCCTAAAAGTACCTCTCC (SEQ ID NO: 1619 ) CAAGGCTAAGCATGCTGAACACA(SEQ ID NO : 1620) NR: 1618) hCV1408483 C/T TGCTAAGGCCTGTGAAC (SEQ ID NR: 1621) TTGCTAAGGCCTGTGAAT (SEQ ID NR: 1622)TCTGTTTTCGCTGGAGTCTT (SEQ ID NR: 1623) hCV1452085 A/CACACCCTGACACCTCACCTACT (SEQ ID NR: 162 1625) CGTTCCAGTCCATATTCACAT (SEQ ID NO: 1626) hCV1463226 C/TATTTCCTCCCTCACATGATAC (SEQ ID NO: 1627) ATTTCCTCCCTCACATGATAT (SEQID NO: 1628) TCAAAGAATGAAGAGTGAAGACA (SEQ ID NO: 1629) hCV15752716C/T ACGCTGCTGTTCCG (SEQ ID NO : 1630) ACGCTGCTGTTCCA (SEQ ID NO:1631) CAGACAGACAACAATTCAGAAGAA (SEQ ID NO: 1632) hCV15770510 G/TTGAAGACTGATTGTTGTACTTGC (SEQ ID CTGAAGACTGATTGTTGTACTTGA (SEQ IDNO: 1634) TGGTGGAGAGGGTTGTAGAA (SEQ ID NO: 1635) NO: 1633)hCV15851766 A/G GAGTTTTCGCCATCCACT (SEQ ID NO: 1636 )GTTTTCGCCATCCACC (SEQ ID NO: 1637 ) GAATCTGCTTCATTTGAATCTCT (SEQ IDNO: 1638) hCV15854171 C/T TTGGTGTTTCCTTGTGACAC (SEQ ID NO: 1639)TTGGTGTTTCCTTGTGACAT (SEQ ID NO: 1640) hCV15857769 C/T CACTCCTAAGTGAGCAGC (SEQ ID NO:1642) ATCACTCCTAAGTGAGCAGT ( SEQ ID NO: 1643)CTGCTTCAGTGTTATCTCAGTCTT ( SEQ ID NO: 1644) hCV15879601 C/TCCACCAGGATGTAACAGTCC (SEQ ID NO: 1645) CCCACCAGGATGTAACAGTCT (SEQID NO: 1646) TGTGGATGCAGCAGTGAC (SEQ ID NO: 1647) hCV16093418 A/GCAAGAAGTTCACAGCTGAAGA (SEQ ID NO: 1648 ) AAGAAGTTCACAGCTGAAGG (SEQID NO: 1649) CCTGCTGGAGAGACAGAGTG (SEQ ID NO: 1650) hCV16134786 A/GGGCAGGGGTGAGATTGA (SEQ ID NO: 1651) GGCAGGGGTGAGATTGG (SEQ ID NO:1652) GTCGTGAGGTCAGATGCTATGAG (SEQ ID NO: 1653) hCV16158671 C/TCTTAAATATTACCTGTTCTAATTTTCTCTG (SEQ IDCCTTAAATATTACCTGTTCTAATTTTCTCTA (SEQ IDGAAATGCTGTGGGAACATAAACTAACTAGG (SEQ ID NO: 1654) NO: 1655) NO:1656) hCV16164743 NC GAGCAATAGTAAGTATACACAATGAAATAA (SEQ IDGAGCAATAGTAAGTATACACAATGAAATAC (SEQ ID GATCACGGGCCTCTAGATTGATTACA(SEQ ID NO: 1659) NO : 1657) NO: 1658) hCV1619596 A/GGAGGAGCCCGTTGCA (SEQ ID NR: 1660) AGGAGCCCGTTGCG (SEQ ID NO. SEQ : 1666) CCCCTCAAGCACTCTGAT (SEQ ID NO:1667) TCTGCCCCTCGTCTTTCTCT (SEQ ID NO: 1668) hCV1690777 A/GGGCTTTACAGAAGGAAATGCT (SEQ ID NO: 1669) GCTTTACAGAAGGAAATGCC (SEQID NO: 1670) GCATGCGCTGAATTTTATATAG (SEQ ID NO: 1671) hCV1723718A/G CAGCCGTTTCTTCATATAATCCA ( SEQ ID NO: 1673) CTTGCTAATTCATTCTGTGACCTCAAT (SEQ ID NO: 1674) NO: 1672) hCV1746715 A/G GCGCCTTTCTGTGTAGTT (SEQ ID NO: 1675) hCV1754669 A/G TTCAGGCCATCTTGCAAAT (SEQ ID NO: 1678) TCAGGCCATCTTGCAAAC (SEQ ID NO: 1679)CTCATGGCCCGATGATTTTCAGTTA (SEQ ID NO: 1680) hCV1846459 C/TCAGGCTCGTCTTGAACTC (SEQ ID NO: 1681) CAGGCTCGTCTTGAACTT (SEQ ID NO: 1682) CAAGAGGGTGA.TTGGT NR: 1683) hCV1958451 G/TGTGGGAGTCTTATGTTTGTAGATG (SEQ ID GTGGGAGTCTTATGTTTGTAGATT (SEQ ID NR: 1685) GCTTGACAATGCGCAGTTGT (SEQ ID NR: 1686) NR: 1684)hCV2091644 C/T TTCTCAGGGGCATACAACG (SEQ ID NR: 1687 IDACTT: 1687 IDACTT) AGGGACAACCCTCCATAAA (SEQ ID NO: 1689) hCV2121658 A/G AGTGGAGATTTAGCACCAGA (SEQ ID NO: 1690)GTGGAGATTAGCACCAGG (SEQ ID NO: 1691) GTACATTTTGGATTGGGAGAGGAT (SEQ ID NO: 1692) hCV2169762 G/T CGAGTCGGTC NOCTGC (SEQ ID NO: 16CTAC9GCT) (TCCQ IDGCT) ID NO: ID NO: 1695) hCV2192261 C/T CCTACCTTGAATTCACCTATCTG (SEQ ID NO: 1697) CATTTCCAATCAGAAACATGA (SEQ ID NO: 1698) NO: 1696) hCV22275299 C/G ID NO: 1696 169GTT 1 SEQ NOGACTTGA ID NO: 1698; GTGCTGTCACACCCAAGAAGTAC (SEQ ID NO: 1701) hCV2358247 A/GGGTTGGGCGTAAGGGTT (SEQ ID NO: 1702) GGTTGGGCGTAAGGGTC ( SEQ ID NO:1703) CCCTAGCTTTGCATAAATCATAC (SEQ ID NO: 1704) hCV2390937 A/CGTGGAAATGCAAGCTCTTCA ( SEQ ID NO: 1705) TGGAAATGCAAGCTCTTCC (SEQ IDNO : 1706) CCAGATCGCTTTGGTAAAGGATTAA (SEQ ID NO: 1707) hCV2442143C/T ATTTAAGCATCATAGCATACCAC (SEQ ID ATTTAAGCATCATAGCATACCAT (SEQ IDNO: 1 709) TGGTACACCATAAATCTTGACTTAC (SEQ ID NO: 1710) NO: 1708)hCV25473186 C /T ATCTTCACAGTGTTCCACATC (SEQ ID NO: 1711) ATCTTCACAGTGTTCCACATT (SEQ ID NO: 1712) TTCTGACCTCCAGGTTCTTT (SEQ ID NO: 1713) hCV25596936 C/T GGCAGGCGAAGAGTCAC (SEQ ID NO: 1714)GGCAGGCGAAGAGTCAT (SEQ ID NO: 1711) GGQAGGTCAATAC 1716) hCV25609987 A/G TGAGCAGGTAGCCTGTATTT (SEQ ID NO: 1717 )TGAGCAGGTAGCCTGTATTC (SEQ ID NO: 1718) TGCTGCCTTGGTTGTGA (SEQ IDNO: 1719) hCV25615822 C /T CGGATCTTCTCCAGCG (SEQ ID NO: 1720)CCGGATCTTCTCCAGCA (SEQ ID NO: 1721) TGAAGCCACATCCTTCTTTAT (SEQ ID NO: 1722) hCV25623804 A/G TTTCAAGCTGTCTCCTACCAT ( SEQ ID NO: 1723)TTTCAAGCTGTCTCCTACCAG (SEQ ID NO: 1723) 1725) hCV25637605 A/G GCGGCTCTGCACAT (SEQ ID NO: 1726)GCGGCTCTCTGCACAC (SEQ ID NO: 1723)GCGGCTTCCTGCACAC (SEQ ID NO: 1723) (SEQ ID NO:1728 ) hCV25651109 C/G GGTCCTGCTTGATGCG (SEQ ID NO: 1729)AGGTCCT1GCTTGATGCC NO:1728) CGACCATGGACATTCACAT (SEQ ID NO:1731) hCV25742059 A/G CTGCCTCTTCTGCATTAGA (SEQ ID NO: 1732)TGCCTCTTCTGCATTAG (SEQ ID NO:1729)TGCCTCTTCTGCATTAG: 1733) CCTTCACTGCCTGTTTCTCT (SEQ IDNO: 1734) hCV25924894 A/G GGGAAGTTCTTTCTTGTATATTCAA (SEQ IDGGGAAGTTCTTTCTTGTATATTCAG (SEQ ID NO: 1736) TGCTGTCTTTGCCTCACTAAT(SEQ ID NO: 1737) NO: 1735) hCV25925481 A/G AATCAGCATTTTTGTCAAAGA(SEQ ID NO: 1738) ATCAGCATTTTTGTCAAAGG ( SEQ ID NO: 1739) GGCTTGTGACCTCATTGTTT (SEQ ID NO: 1740) hCV25951678 A/GAATGCAGCTGCTCAAAGA (SEQ ID NO: 1741) ATGCAGCTGCTCAAAGG (SEQ ID NO: 1742) GTTCCCGGGCTCACA (SEQ ID NO: 1743) hCV25952089 A/CCCCTGACCSE: 1744) CCCTGCCTCTGTCTGACTC (SEQ IDNO : 1745) AAGACAAGCCCAGGTTCA (SEQ ID NO: 1746) hCV25983294 GTACCATCATTTACTCCTACCGC (SEQ ID NO: 1747) CCCATCATTTACTCCTACCGT (SEQID NO: 1748) GCCGAGCGGTCTGAG (SEQ ID NO: 1749) hCV2637554 C/TACATCCCAATAAAAGAGCAGG (SEQ ID NO: 1750) AAACATCCCAATAAAAGAGCAGA(SEQ ID NO: 1751) ACTTTGTTTCTTTCAGTATTTATGGCAGTGG (SEQ ID NO: 1752)hCV26478797 A/G GAAATCCTCCCACTGATGA ( SEQ ID NO: 1753)AAATCCTCCCACTGATGG (SEQ ID NO: 1754) GCCAGATAGAATGACTTTATTGTAGA(SEQ ID NO: 1755) hCV26505812 A/G GTCAAATCTAAGCTGAGTGTTGA (SEQ IDTCAAATCTAAGCTGAGTGTTGG (SEQ ID NR: 1757) GCTTTCCCAGATGCACTGTATTGT (SEQ ID NR: 1758) NR: 1756) hCV26682080 A/G TCTCGGGTAGACCACACT (SEQ ID NR: 1759) CTCGGGTAGACCACACC (SEQ ID NR: 1760 ID NR: 1760AGGCCAG6GGT hCV26881276 A/GGAGTTGCTCACAAAAGGCA (SEQ ID NO: 1762 ) AGTTGCTCACAAAAGGCG (SEQ IDNO: 1763) GCAGGCCATGTGAATAGACATAC (SEQ ID NO: 1764) hCV27077072 C/TATCCTGGTATGGCCCC (SEQ ID NO: 1765) CATCCTGGTATGGCCCT (SEQ ID NO:1766) GTCACACAAGCCAAGAAGAATTAGA (SEQ ID NO : 1767) hCV2741051 C/TGCAGCCAGTTTCTCCC (SEQ ID NO: 1768) TGCAGCCAGTTTCTCCT (SEQ ID NO:1769) CATGAAATGCTTCCAGGTATT ( SEQ ID NO: 1770) hCV27473671 C/TCTGACCTCCTGAATAATCCATC (SEQ ID NO: 1771) TCTGACCTCCTGAATAATCCATT(SEQ ID NO: 1772) CAGGGCTTCCCTAGCAGATAG (SEQ ID NO: 1773)hCV27494483 C/ T AACAGGANOCCCTCCTTTGTCC: 1775) CCAGAAGCAGATGAAATGAGTAC (SEQ ID NO: 1776) hCV27504565 C/G GCTCCCAACACTGGACAG (SEQ ID NO: 1777)GCTCCCAACACTGGACAC (SEQ ID NO: 1777CT NO: 1778) GGT

hCV27511436 C/T GGCCCCCATACATTACAAC (SEQ ID NO: 1780)GGCCCCCATACATTACAAT (SEQ ID NO: 1781) TGGAGGAAAGTTCTGGACAGTTA (SEQID NO: 1782) hCV2769503 A/G GGATTCGAGCCGACATCT (SEQ ID NO: 1783)GATTCGAGCCGACATCC (SEQ ID NO: 1784) TTGAGGATTAGCCTAGAACCACACA (SEQID NR: 1785) hCV27830265 A/G CGACCCATGAGAGAATCAGA (SEQ ID NR: 1786) CGACCCATGAGAGAATCAGG (SEQ ID NR: 1787) GCAGGTCCAGCCAGTGAA (SEQ ID NR: 1788) hCV27892569 C/T ATGTGAAATTGCATGCACTTAG (SEQ ID NR: 1789)CATGATGTSEGA )TGTGTGTACAACACCTATACATGTGTGT (SEQ ID NO: 1791) hCV28036404 A/TCATGAGACTCAACTTCTTAGGAAA (SEQ ID CATGAGACTCAACTTCTTAGGAAT (SEQ IDNO: 1793) GCACCAGCCAAGGTTTACTTTATAG (SEQ ID NO: 1794) NO: 1792)hCV2851380 C/G CTTGCTACCAATTCCATTTTCC (SEQ ID NO: 1795)CTTGCTACCAATTCCATTTTCG (SEQ ID NO: 1796) GGATCTCAGGGGCAAGTCTT (SEQID NO: 1797) hCV2862873 C/T TCAACAAATGTATTGATCAGCAAAC (SEQ IDCTCAACAAATGTATTGATCAGCAAAT (SEQ ID NO: 1799)CAGACAGGAGGAGTGGGATTCAT (SEQ ID NO: 1800) NO: 1798) hCV2930693 A/CGAAGAAGTACAACCCACAT (SEQ ID NO: 1801) GAAGAAGTACAACCCACAG (SEQ IDNO: 1802) GACACATGTAAGTTCCACTCATATG (SEQ ID NO: 1803) hCV29401764C/T AAGGTGAGCTTGCCAATC (SEQ ID NO: 1804) AAGGTGAGCTTGCCAATT (SEQ IDNO: 1805) CATGGCGAGGAAGACACATAT (SEQ ID NO: 1806) hCV29480044 C/TGGTGGGCCTTTTGAAATAAAC (SEQ ID NO: 1807) TGGTGGGCCTTTTGAAATAAAT (SEQID NO: 1808) CTTGAAGTGAAGGCACCTGTCAT (SEQ ID NO: 1809) hCV29537898C/T ACCACAGCTGTCCCTC (SEQ ID NO: 1810) TACCACAGCTGTCCCTT (SEQ IDNO: 1811) GCCTCCCAGTGGGAATCT (SEQ ID NO: 1812) hCV29539757 A/CTCCAGTTAGGGATAAAGAAAGGA (SEQ ID CCAGTTAGGGATAAAGAAAGGC (SEQ ID NO :1814) CCAGGCTGATCTCGAACTTCT (SEQ ID NO: 1815) NO: 1813) hCV29566897C/T GAAGATAGATTCTGCCAAATCATTC (SEQ ID GAAGATAGATTCTGCCAAATCATTT(SEQ ID NO: 1817) GGTAAACTCCTGTTGCCTCAGTA (SEQ ID NO: 1818) NO:1816) hCV2959482 A/ G ACACCTGCGGTTAGATTGA (SEQ ID NO: 1819)CACCTGCGGTTAGATTGG (SEQ ID NO: 1820) CGAAGCTTCACAGATGACATC (SEQ ID NO: 1821) hCV29881864 C/G CTTTCTTGACATCAGTGCTTC (SEQ ID NO: 1822)CTTTCTTGACATCAGTGCTTG (SEQ ID NO: 1823) CAAAGTQCCTCT 1824) hCV302629 A/G AGCTGCTGCTTGCTAAATAT (SEQ ID NO:1825) AGCTGCTGCTTGCTAAATAC (SEQ ID NO: 1826)CCTGGAAAGGTCATGCTACTCATACT (SEQ ID NO: 1827) hCV30308202 C/GTGGCAGGAGATGGATGTAC (SEQ ID NO: 1828) TGGCAGGAGATGGATGTAG (SEQ IDNO: 1829) CCAGTTACTTGACTTTTGGCGTTTCT ( SEQ ID NO: 1830) hCV30454150C/T TCTAGCAGATTTGTATCAGAACC (SEQ ID TAATCTAGCAGATTTGTATCAGAACT (SEQ ID NO: 1832) GCGACCCTCTCTGGTTAAACA (SEQ ID NO: 1833) NO: 1831)hCV3054550 C/T TCCTGTCTCTGTCCCTTTC (SEQ ID NO: 1831) 1835) CGGAGTGCCCTCTTGTCT (SEQ IDNO: 1836) hCV3054799 A/G TGACTCCCAGCATGAAT (SEQ ID NO: 1837)TGACTCCCAGCATGAAC (SEQ ID NO: 1838) TGGCTTATCAAGAGACATGAGA (SEQ IDNO: 1839) hCV3082219 A/G AGAGATAGTGGAAGCTTTGACA (SEQ ID NO: 1840)GAGATAGTGGAAGCTTTGACG ( SEQ ID NO: 1841) CCTGCAT4 IDCACTCACTSE (TTGTA4) hCV31137507 C/G CCTGGGCAACAAAGTCAC (SEQ ID NO: 1843) CCTGGGCAACAAAGTCAG (SEQ ID NO: 1844)CAAGAATATTGGCCTGCTTCAAACTAG (SEQ ID NO: 1845) hCV312277507 : 1846) TCCTTGGGGTAGTCCCT (SEQ ID NO:1847) GCTGGAGTCCCACTGAGA (SEQ ID NO: 1848) hCV31573621 C /TTGTAATTGGCCCAGAACAC (SEQ ID NO: 1849) ATGTAATTGGCCCAGAACAT (SEQ IDNO: 1850) CCTTCCAGGCTTCTCTCTGAT (SEQ ID NO: 1851) hCV31705214 A/TGTTGGTGAAGAAGGATTTGTAGT ( SEQ ID GTTGGTGAAGAAGGATTTGTAGA (SEQ ID NO: 1853) GCTGGAAGCTTGACACTTGTTGAA (SEQ ID NO: 1854) NO: 1852 ) hCV32160712 A/T TGTGCCTTCCACATCTCA (SEQ ID NO: 1855) TGTGCCTTCCACATCTCT (SEQ ID NO: 1856) A/G GCATACATCACATTTTCTTTACCT (SEQ IDGCATACATCACATTTTCTTTACCC (SEQ ID NO: 1859)GTTCATTGCAGCATTTTCCCCAATAC (SEQ ID NO: 1860) NO: 1858) hCV323071A/G AAACCAGGATATCAGAACATTTTA (SEQ ID ACCAGGATATCAGAACATTTTG (SEQ IDNO: 1862) GGTCTTAGGAATTATCTGACATCTT (SEQ ID NO: 1863) NO: 1861)hCV435733 C/G CAACTACTCGGGAGACAG (SEQ ID NO: 1864)CAACTACTCGGGAGACAC (SEQ ID NO: 1865) CCTCTCAGCCCTCTCTCCATAAAG (SEQID NO: 1866) hCV454333 C/T GTATGGGCTTGAGGAAATCAC (SEQ ID NO: 1867)GTATGGGCTTGAGGAAATCAT (SEQ ID NO: 1868) TGCACAGATGGCTTCTGTATGT (SEQID NO: 1869) hCV540056 C/T AACTACTTCTGGATGGTCAGC (SEQ ID NO: 1870)AAACTACTTCTGGATGGTCAGT (SEQ ID NO: 1871) GGGTCCTGCAAGTAGACACTAAG(SEQ ID NO: 1872) hCV7425232 C/T TCAAAATTATTTCTTGCTACAGG (SEQ IDGTCAAAATTATTTCTTGCTACAGG (SEQ ID NO: 1874) TCCTCCAGCCTCTCATTC (SEQ ID NO: 1875) NO: 1873) hCV7917138 A/G CATALOG(SEQ ID NO: 1877)NOGGTTAAGCCATCSE:TTCTCCACTQ 1876) NO: 1878)hCV8147903 A/G ID9GCATCGA (SEQ ID NO: 1877) GGCTCTCTCGTGAGCG(SEQ ID NO: 1880) GAAGGGGCACAGTGCCTTTTAG (SEQ ID NO: 1881) hCV8754449 C/T GCAGCTGAGGAGCATTAGCGA (SEQ ID NO: 18CT8 (SEQ ID 2): NR: 1883) CAGAGCAAGACCCTGTCTCTAA (SEQ ID NR: 1884) hCV8757333 C/T CGTACTC (TT5CT NO )CGTCAGCTCCTTTTGACAT (SEQ ID NO: 1886) CCCCAGAGGGTCCAAATTTCT (SEQ IDNO: 1887) hCV8820007 A/T CTTGGATAGCCTGAACCAATAA (SEQ ID NO: 1888)CTTGGATAGCCTGAACCAATAT ( SEQ ID NO: 1889) CGTGAATAGGGTCCAGAGTCTA(SEQ ID NO: 1890) hCV8942032 G /G TTTGGACATGGGCAAGC ( SEQ ID NO:1891) CTTTGGACATGGGCAAGG (SEQ ID NO: 1892) CCCTGCATGGAAAGGTAAGAAAGT(SEQ ID NO: 1893) hCV9296529 A/G CTCATCCTTAATATTGTTTACTTGTGAT (SEQID CTCATCCTTAATATTGTTTACTTGTGAC (SEQ ID NO: 1895CAAGACAGCCGCCTACAAGA (SEQ ID NO: 1896) NO: 1894 hCV9324316 C/TGCAGGGGTTTCTCACC (SEQ ID NO: 1897) TGCAGGGGTTTCTCACT (SEQ ID NO: 1898) NO: 1900) CTGACCGA (SEQ ID NO: 1901) NO: 1902) hCV945276 G/TCGCCACAAA (SEQ ID NO: 1903) CGCCACAAACACATACCTT (SEQ ID NO: 1904) CCGCTGCTTGGAACAG (SEQ ID NO: 1905) hCV9473891 C/TAGACTTTGATGCCA IDACGA NO: 1906) CAGACTTTGATGCCAACGAA (SEQ ID NO: 1907) CCAAGCACATTTATTGAGCACTCAA (SEQ ID NO: h92166) T CAAACAGTGATGCAAATCAATTTC (SEQ ID ACAAACAGTGATGCAAATCAATTTA (SEQID NO: 1910) GAAGGGGGACGAAGAAGCTAGAA (SEQ ID NO: 1911) NO: 1909)hDV77718013 C/T GGGACCCTATAGGAGCTTC ( SEQ ID NO: 1912)GGGACCCTATAGGAGCTTT (SEQ ID NO: 1913) TCATTCTTGGGGGAGAGGCTATTC (SEQID NO: 1914 ) .

TABLE-US-00002 TABLE 4 Interrogated SNP Interrogated rs LD SNP LDSNP rs Power Threshold r.sup.2 r.sup.2 hCV11548152 rs11580249hCV30715059 rs12137135 0.51 0.477953358 0.4781 hCV11548152rs11580249 hCV31574252 rs12128312 0.51 0.477953358 0.6764hCV11738775 rs6754561 hCV27153776 rs10164837 0.51 0.66106443 0.8444hCV11738775 rs6754561 hCV3232568 rs3795880 0.51 0.66106443 0.8552hCV11758801 rs11841997 hCV30023295 rs9591381 0.51 0.58648249 1hCV1408483 rs17070848 hCV1408479 rs12961976 0.51 0.685992147 0.8832hCV1408483 rs17070848 hCV1408480 rs11663275 0.51 0.685992147 0.8379hCV1408483 rs17070848 hCV1408481 rs11152374 0.51 0.685992147 0.8946hCV1408483 rs17070848 hCV1408515 rs12967026 0.51 0.685992147 0.7306hCV1408483 rs17070848 hCV29202466 rs7234941 0.51 0.685992147 0.8379hCV1408483 rs17070848 hCV31494763 rs7242542 0.51 0.685992147 0.9429hCV1408483 rs17070848 hCV31494861 rs12970840 0.51 0.6859921470.8379 hCV15857769 rs2924914 hCV1379455 rs2942805 0.51 0.9483846171 hCV15857769 rs2924914 hCV1379456 rs2978341 0.51 0.948384617 1hCV15857769 rs2924914 hCV15857755 rs2924920 0.51 0.948384617 0.9584hCV15857769 rs2924914 hCV15857780 rs2924912 0.51 0.948384617 0.9584hCV15857769 rs2924914 hCV15878591 rs2978339 0.51 0.948384617 0.9594hCV15857769 rs2924914 hCV15878604 rs2978352 0.51 0.948384617 0.9594hCV15857769 rs2924914 hCV16167752 rs2930285 0.51 0.948384617 1hCV15857769 rs2924914 hCV27184738 rs2942808 0.51 0.948384617 1hCV15857769 rs2924914 hCV29765690 rs9644266 0.51 0.948384617 0.9582hCV15879601 rs2275769 hCV11396361 rs9370261 0.51 0.394289193 0.6541hCV15879601 rs2275769 hCV15879602 rs2275770 0.51 0.394289193 1hCV15879601 rs2275769 hCV16113165 rs2792634 0.51 0.394289193 1hCV15879601 rs2275769 hCV2140762 rs2792638 0.51 0.394289193 1hCV15879601 rs2275769 hCV2140766 rs1340667 0.51 0.394289193 1hCV15879601 rs2275769 hCV2140769 rs1150875 0.51 0.394289193 1hCV15879601 rs2275769 hCV2140770 rs2792635 0.51 0.394289193 1hCV15879601 rs2275769 hCV2140772 rs11963558 0.51 0.394289193 1hCV15879601 rs2275769 hCV25929027 rs6934690 0.51 0.394289193 1hCV15879601 rs2275769 hCV25930618 rs10484648 0.51 0.394289193 1hCV15879601 rs2275769 hCV26548331 rs2145761 0.51 0.394289193 1hCV15879601 rs2275769 hCV26548343 rs2754795 0.51 0.394289193 1hCV15879601 rs2275769 hCV26548347 rs2754798 0.51 0.394289193 1hCV15879601 rs2275769 hCV29161504 rs6914051 0.51 0.394289193 0.5561hCV15879601 rs2275769 hCV29161551 rs6924913 0.51 0.394289193 1hCV15879601 rs2275769 hCV29649198 rs9885975 0.51 0.394289193 1hCV15879601 rs2275769 hCV29649199 rs9474772 0.51 0.394289193 1hCV15879601 rs2275769 hCV29667033 rs9474754 0.51 0.394289193 1hCV15879601 rs2275769 hCV29703373 rs9474766 0.51 0.394289193 1hCV15879601 rs2275769 hCV29703374 rs9283919 0.51 0.394289193 1hCV15879601 rs2275769 hCV29721486 rs9370254 0.51 0.394289193 0.5549hCV15879601 rs2275769 hCV29721492 rs9474762 0.51 0.394289193 1hCV15879601 rs2275769 hCV29811423 rs10484647 0.51 0.394289193 1hCV15879601 rs2275769 hCV29902056 rs9464034 0.51 0.394289193 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rs553352 0.510. 400661237 1 hCV8147903 rs680014 hCV11788533 rs4799084 0.510.400661237 0.6566 hCV8147903 rs680014 hCV12091565 rs629084 0.510.400661237 0.5434 hCV8147903 rs680014 hCV1731571 rs580675 0.510.400661237 1 hCV8147903 rs680014 hCV26871521 rs12605631 0.510.400661237 1 hCV8147903 rs680014 hCV2744994 rs2510276 0.510.400661237 1 hCV8147903 rs680014 hCV2745000 rs2680752 0.510.400661237 1 hCV8147903 rs680014 hCV2745001 rs1788659 0.510.400661237 1 hCV8147903 rs680014 hCV27516223 rs3786238 0.510.400661237 0.7292 hCV8147903 rs680014 hCV27877725 rs4799077 0.510.400661237 0.8788 hCV8147903 rs680014 hCV29779584 rs4799081 0.510.400661237 0.9183 hCV8147903 rs680014 hCV3068685 rs3859321 0.510.400661237 0.7991 hCV8147903 rs680014 hCV3068718 rs673590 0.510.400661237 1 hCV8147903 rs680014 hCV3068726 rs685665 0.510.400661237 1 hCV8147903 rs680014 hCV3068731 rs522723 0.510.400661237 0.9587 hCV8147903 rs680014 hCV3068735 rs517479 0.510.400661237 1 hCV8147903 rs680014 hCV3068736 rs485400 0.510.400661237 1 hCV8147903 rs680014 hCV3068738 rs503615 0.510.400661237 1 hCV8147903 rs680014 hCV3068739 rs603957 0.510.400661237 1 hCV8147903 rs680014 hCV3068757 rs3826573 0.510.400661237 0.4225 hCV8147903 rs680014 hCV3068760 rs585571 0.510.400661237 0.8509 hCV8147903 rs680014 hCV805999 rs649763 0.510.400661237 1 hCV8147903 rs680014 hCV806002 rs681631 0.510.400661237 1 hCV8147903 rs680014 hCV806008 rs655609 0.510.400661237 0.8402 hCV8147903 rs680014 hCV806012 rs671424 0.510.400661237 0.4335 hCV8147903 rs680014 hCV806021 rs618342 0.510. 400661237 0.4335 hCV8147903 rs680014 hCV8155000 rs605183 0.510.400661237 1 hCV8147903 rs680014 hCV8155010 rs570029 0.510.400661237 1 hCV8147903 rs680014 hCV8155011 rs589394 0.510.400661237 1 hCV8147903 rs680014 hCV8831345 rs529195 0.510.400661237 1 hCV8147903 rs680014 hCV8831346 rs1239783 0.510.400661237 1 hCV8147903 rs680014 hCV8831352 rs500795 0.510.400661237 0.4335 hCV8942032 rs1264352 hCV11196362 rs3129820 0,510,674510346 0,6961 hCV8942032 rs1264352 hCV11690723 rs886424 0,510,674510346 0,9461

hCV8942032 rs1264352 hCV15885725 rs2532923 0.51 0.674510346 0.8224hCV8942032 rs1264352 hCV15947385 rs2233980 0.51 0.674510346 0.7828hCV8942032 rs1264352 hCV16027870 rs2517578 0.51 0.674510346 0.8297hCV8942032 rs1264352 hCV2437063 rs3131060 0.51 0.674510346 0.9468hCV8942032 rs1264352 hCV2437065 rs3129985 0.51 0.674510346 0.9468hCV8942032 rs1264352 hCV2437122 rs3095337 0.51 0.674510346 0.7947hCV8942032 rs1264352 hCV2437158 rs2284174 0.51 0.674510346 0.8428hCV8942032 rs1264352 hCV2452431 rs3132625 0.51 0.674510346 0.6845hCV8942032 rs1264352 hCV25606044 rs7750641 0.51 0.674510346 0.6923hCV8942032 rs1264352 hCV25606244 rs3130247 0.51 0.674510346 0.7442hCV8942032 rs1264352 hCV25966128 rs9262135 0.51 0.674510346 0.7934hCV8942032 rs1264352 hCV26544258 rs1634726 0.51 0.674510346 0.7745hCV8942032 rs1264352 hCV26546104 rs8233 0.51 0.674510346 0.7955hCV8942032 rs1264352 hCV26546345 rs2535332 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV26546351 rs2263298 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV27452306 rs3094032 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27452307 rs3094036 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27452310 rs3094057 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27452312 rs3094061 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27452313 rs3094064 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27452317 rs3094034 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27452321 rs3094031 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27452331 rs3094086 0.51 0.674510346 0.8942hCV8942032 rs1264352 hCV27452332 rs3094035 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27452369 rs3094127 0.51 0.674510346 0.7955hCV8942032 rs1264352 hCV27452387 rs3094222 0.51 0.674510346 0.7571hCV8942032 rs1264352 hCV27452568 rs3094703 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27452590 rs3094717 0.51 0.674510346 0.6845hCV8942032 rs1264352 hCV27452726 rs3095329 0.51 0.674510346 0.7945hCV8942032 rs1264352 hCV27452728 rs3095336 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV27452739 rs3095330 0.51 0.674510346 0.8339hCV8942032 rs1264352 hCV27452751 rs3095338 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV27452792 rs3095153 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV27452821 rs3095340 0.51 0.674510346 0.8428hCV8942032 rs1264352 hCV27462338 rs3130353 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27462341 rs3130374 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27462390 rs3130660 0.51 0.674510346 0.7934hCV8942032 rs1264352 hCV27462600 rs3131050 0.51 0.674510346 0.942hCV8942032 rs1264352 hCV27462601 rs3131064 0.51 0.674510346 0.9485hCV8942032 rs1264352 hCV27462862 rs3131788 0.51 0.674510346 0.7415hCV8942032 rs1264352 hCV27462962 rs3129812 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27462963 rs3129815 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27462964 rs3129818 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27462981 rs3129973 0.51 0.674510346 0.8435hCV8942032 rs1264352 hCV27462982 rs3129984 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV27462996 rs3130123 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27463014 rs3130352 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27463047 rs3130782 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV27463445 rs3131783 0.51 0.674510346 0.7423hCV8942032 rs1264352 hCV27463454 rs3131934 0.51 0.674510346 0.7955 hCV8942032 rs1264352 hCV27463630 rs3130557 0.51 0.674510346 0.7415hCV8942032 rs1264352 hCV27463637 rs3130641 0.51 0.674510346 0.942hCV8942032 rs1264352 hCV27463692 rs3132580 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV27463694 rs3132610 0.51 0.674510346 0.7442hCV8942032 rs1264352 hCV27463813 rs3131044 0.51 0.674510346 0.9447hCV8942032 rs1264352 hCV27464298 rs3132600 0.51 0.674510346 0.7998hCV8942032 rs1264352 hCV27464300 rs3132605 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV27464304 rs3132630 0.51 0.674510346 0.6845hCV8942032 rs1264352 hCV27464305 rs3132631 0.51 0.674510346 0.6845hCV8942032 rs1264352 hCV27464307 rs3132645 0.51 0.674510346 0.7345hCV8942032 rs1264352 hCV27465359 rs3129978 0.51 0.674510346 0.8905hCV8942032 rs1264352 hCV27465360 rs3129980 0.51 0.674510346 0.942hCV8942032 rs1264352 hCV27465386 rs3130350 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27465389 rs3130364 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27465407 rs3130544 0.51 0.674510346 0.7218hCV8942032 rs1264352 hCV27465417 rs3130673 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV27465853 rs3132634 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV27465855 rs3132649 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV29486333 rs3132584 0.51 0.674510346 0.7955hCV8942032 rs1264352 hCV29504305 rs3094712 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV29522452 rs3095334 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV29540580 rs3094067 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV29558680 rs3132599 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV29594803 rs9262204 0.51 0.674510346 0.9398hCV8942032 rs1264352 hCV29666963 rs3130363 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV29666973 rs9262130 0.51 0.674510346 0.7768hCV8942032 rs1264352 hCV29703261 rs3095155 0.51 0.674510346 0.8696hCV8942032 rs1264352 hCV29721426 rs3132616 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV29775548 rs3132647 0.51 0.674510346 0.6952hCV8942032 rs1264352 hCV29847742 rs3129809 0.51 0.674510346 0.7345hCV8942032 rs1264352 hCV29883892 rs3132581 0.51 0.674510346 0.8865hCV8942032 rs1264352 hCV29992126 rs3094627 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV29992140 rs9262200 0.51 0.674510346 0.9468hCV8942032 rs1264352 hCV30028026 rs3130372 0.51 0.674510346 0.6845hCV8942032 rs1264352 hCV30045930 rs3095326 0.51 0.674510346 0.8435hCV8942032 rs1264352 hCV30045931 rs3131055 0.51 0.674510346 0.8951hCV8942032 rs1264352 hCV30172261 rs3130365 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV30190135 rs3094621 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV30262083 rs3094050 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV30262102 rs3130665 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV30280013 rs3094024 0.51 0.674510346 0.7442hCV8942032 rs1264352 hCV30352101 rs3129821 0.51 0.674510346 0.6845hCV8942032 rs1264352 hCV30424437 rs9262143 0.51 0.674510346 0.7934hCV8942032 rs1264352 hCV30442461 rs9262141 0.51 0.674510346 0.7768hCV8942032 rs1264352 hCV30496055 rs3130117 0.51 0.674510346 0.7442hCV8942032 rs1264352 hCV30622443 rs3129823 0.51 0.674510346 0.6845hCV8942032 rs1264352 hCV3273752 rs3130370 0.51 0.674510346 0.6845hCV8942032 rs1264352 hCV7926405 rs3130126 0.51 0.674510346 0.6961hCV8942032 rs1264352 hCV8692767 rs1264376 0.51 0.674510346 0.9468hCV8942032 rs1264352 hCV8692768 rs1264377 0.51 0.674510346 0.8951 hCV8942032 rs1264352 hCV8692796 rs1059612 0.51 0.674510346 0.7934hCV8942032 rs1264352 hCV8692806 rs1064627 0.51 0.674510346 0.7955hCV8942032 rs1264352 hCV8941738 rs1634721 0.51 0.674510346 0.8435hCV8942032 rs1264352 hCV8941879 rs1264308 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV8941918 rs1049633 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV8941930 rs886422 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV8941940 rs1264322 0.51 0.674510346 0.8905hCV8942032 rs1264352 hCV8941988 rs2535340 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV8942006 rs1264341 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV8942015 rs1264347 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV8942025 rs1264349 0.51 0.674510346 0.8946hCV8942032 rs1264352 hCV8942026 rs1264350 0.51 0.674510346 0.8812hCV8942032 rs1264352 hCV8942038 rs1264353 0.51 0.674510346 0.9427hCV8942032 rs1264352 hCV9481170 rs886423 0.51 0.674510346 1hCV8942032 rs1264352 hDV75255684 rs2517546 0,51 0,6745103460,6985

TABLE-US-00003 TABLE 5 Baseline Characteristics of ARIC Participants in the Ischemic Stroke Study White (N=10401) Black (N=3814) Cases Non-Cases Cases Non-Cases (N=275) (N=10126) (N=220) (N=3594) Characteristics Mean (SD) Mean (SD) p-value* Mean (SD) Mean (SD) p-value* Age 57.59 (5.32) 54.10 (5, 69) <0.0155.21 (5.79) 53.25 (5.79) <0.01 waist-to-hip ratio 0.96 (0.07) 0.92 (0.08) <0.01 0.94 (0.07) 0.92 (0.08) <0.01 N (%) N (%) p-value* N (%) N (%) p-value* Male 162 (59) 4569 (45) <0.01 97 (44) 1318 (37) 0.03 Hypertensive 137 (50) 2516 (25) <0.01 168 (77) 1903 (53) <0.01 Diabetic 55 (20) 799 ( 8) <0.01 94 (44) 596 (17) <0.01 Smokers 90 (33) 2455 (24) <0.01 81 (37) 1036 (29) 0.01 *p-value represents a comparison between cases and non-cases within an ethnic group

TABLE-US-00004 TABLE 6 SNPs associated with the ischemic stroke event in the ARIC study Risk-Risk-Increasing Reduction Model 1Δdolch. Model 2.dolch-dbl. Allele Allele 95% p- 95% p gene Symbol SNP ID Function* (frequency) (frequency) HRR CI valueHRR CI value White SERPINA9 rs11628722 Nonsynonym G (0.84) A(0.16) 1.31 1, 00-1.70 0.05 1.32 1.02-1.72 0.03 Ala348Val PALLDrs7439293 Intronic A (0.62) G (0.38) 1.24 1.03-1.49 0.02 1.211.01-1.46 0.04 IER2 rs1042164 Nonsynonymous T (0.1.164) C (0.83) 1.381.12-1.71 0.003 1.39 1.12-1.72 0.003 Val133Ala Blacks SERPINA9rs11628722 Nonsynonymous G (0.45 ) A (0.55) 1.26 1.03–1.53 0.02 1.271.04–1.54 0 .02 Ala348Val EXOD1 rs3213646 Intronic C (0.16) T (0.84) 1.29 1.01-1.64 0.04 1.29 1.01-1.65 0.04 Dagger model 1 was on Age and gender adjusted. dagger-dbl. Model 2 was adjusted for age, gender, waist-to-hip and diabetes, hypertension, and smoking status.

TABLE-US-00005 TABLE 7 p-value Risk White (two- Black p-value hCV number rs number gene symbol allele HRR 95% CI one-sided) HRR 95% CI (two-sided) hCV2091644 rs1010 VAMP8 C 1.16 0, 97–1,38 0,1 0,90 .74-1.10 0.3 hCV25925481 rs11628722 SERPINA9 G 1.31 1.00-1.70 0.051.26 1.03-1.53 ​​​​0.02 hCV323071 rs7439293 PALLD A 1.24 1.03-1.49 0.021.2 0.93-1.56 0.16 hCV7425232 rs3900940 MYH15 C 1.18 0.98-1.42 0.081.1 0.85-1.43 0.49 hCV9326822 rs1042164 IER2 T 1.38 1.12-1.71 00.54 0.27-1.09 0.08 hCV15770510 rs3027309 ALOX12B T 1.17 0.95-1.460.14 1.25 0.88-1.77 0.21 hCV9626088 rs943133 LOC391102 A 1.130.94-1.36 0.19 1 0.69-1.45 1

TABLE-US-00006 TABLE 8 p-value gene risk white (two-black p-value hCV number rs number symbol allele HRR 95% KI-sided) HRR 95% KI (two-sided) hCV25924894 rs17090921 SERPINA9 A 1.12 0, 93-1.35 0.231. 19 0.92-1.52 0.18 hCV1690777 rs12684749 NFIB G 0.99 0.64-1.530.97 1.68 0.90-3.13 0.1 hCV25925481 rs11628722 SERPINA9 G 1.311.00-1.70 0.05 1.26 1.03-1.53 ​​​​0.02 hCV323071 rs7439293 PALLD A 1.241.03-1.49 0.02 1.2 0.93- 1.56 0.16 hCV25609987 rs10817479 WDR31 A0.93 0.65-1.32 0.67 5.15 0.72-36.78 0.1

TABLE-US-00007 TABLE 9 p-value risk White (two- Black p-value hCV number rs number gene symbol allele HRR 95% CI-sided) HRR 95% CI (two-sided) hCV25924894 rs17090921 SERPINA9 A 1.12 0 .93-1.35 .231. 19 0.92-1.52 0.18 hCV25925481 rs11628722 SERPINA9 G 1.311.00-1.70 0.05 1.26 1.03-1.53 ​​0.02 hCV323071 rs7439293 PALLD A 1.241.03-1.49 0 .02 1.9

TABLE-US-00008 TABLE 10 Baseline Characteristics of CHS Participants in Ischemic Stroke Study African Characteristics White Americans Number of Subjects in This Analysis 3849 673 Male 1575 (41) 243 (36) Age, mean (SD), years 72.7 (5.6) 72.9 (5.7 ) BMI, mean (SD), kg/m2 26.3 (4.5) 28.5 (5.6) Smoking, current 423 (11) 113 (17) Diabetes 511 (13) 151 (23) Impaired fasting glucose 522 (14) 92 (14) Hypertension 2110 (55) 490 (73) LDL cholesterol, mean (SD), mg/dL 130 (36) 129 (36) HDL Cholesterol, mean (SD), mg/dL 54 (16) 58 (15 ) Total cholesterol, mean (SD), mg/dL 212 (39) 210 (39) Data are presented as number of participants (%) unless otherwise stated specified.

TABLE-US-00009 TABLE 11 SNPs Associated with Ischemic Stroke Incident in White Participants of CHS Prespecified Risk Allele GendbSNP Risk Allele Frequency HR (90% CI)* P HPS1 rs1804689 T 0.301.23 (1.09 -1.40) 0.003 ITGAE rs220479 C 0.82 1.26 ( 1.08-1.48) 0.008ABCG2 RS2231137 C 0.95 1.46 (1.05-2.03) 0.03 MYH15 RS3900940 C 0.291.15 (1.02-1.31) 0.03 FSTL4 RS13183672 A 0.02-1.17 (1.03) 0.04) 0.02.2.101.1.17 (1.01.01.35). BAT2 rs11538264 G 0.971.49 (1.02-2.16) 0.04 *Hazard ratios (HR) are adjusted for baseline, gender, body mass index, current smoking, diabetes, impaired fasting blood glucose, hypertension, LDL cholesterol and baseline HDL cholesterol. Hazard ratios are per copy of the risk allele.

TABLE-US-00010 TABLE 12 SNPs Associated with Ischemic Stroke in African-American CHS Participants Pre-Risk Specified Allele Gene dbSNP Risk Allele Frequency HR (90% CI)* P KRT4 rs89962T 0.11 2.08 (1.48-2.94) <0.001 LY6G5B rs11758242 C 0.89 2.28 (1.20-4.33) 0.02 EDG1 RS2038366 G 0.73 1.59 (1.08-2.35) 0.02 DMXL2RS12102203 G 0.47 1.40 (1.03-1.90) 0.04 ABCG2 RS2231137 C 0.95 (1.11-1.59). , sex, body mass index, current smoking, diabetes, impaired fasting glucose, hypertension, LDL-cholesterol, and HDL-cholesterol at baseline. Hazard ratios are per copy of the risk allele.

TABLE-US-00011 TABLE 13 The val allele homozygotes of ABCG2Val12Met (rs2231137) are associated with an increased risk of ischemic stroke in both White and African American participants in CHS ABCG2 events compared to the Met allele carriers TotalModel 1* Model 2* Genotypes n HR (90% CI) P HR (90% CI) P WhiteValVal 370 3398 1.58 (1.12-2.23) 0.02 1.50 (1.06-2, 12) 0.03 ValMet+ MetMet 24 335 1 (reference) 1 (reference) ValMet 23 321 MetMet 114 Af. Am. ValVal 66 592 3.80 (1.16-12.4) 0.03 3.62 (1.11-11.9)0.04 ValMet + MetMet 2 70 1 (reference) 1 (reference) ValMet 2 69MetMet 0 1 *Model 1 was adjusted for age and gender at baseline. Model 2 was adjusted for baseline age, gender, body mass index, current smoking, diabetes, impaired fasting glucose, hypertension, LDL-cholesterol, and HDL-cholesterol.

TABLE-US-00012 TABLE 14 HR (90% CI) Risk AgeSex p-value Genes rs #hCV# allelic mode (whites) (whites) CENPE rs2243682 hCV1624173 A dom1.2 (1.02, 1.42) 0.034 FCRLB rs34868416 hCV25951601 A rec 2.034 A 1.07, 3.76) 0.034 FSTL4 rs3749817 hCV25637605 G dom 2.04 (1.2, 3.45) 0.013 HR (90% CI) HR (90% CI) HR (90% CI) Full p-value Age Gender Exp-Value Complete p-value Gene (White) (White) (Black) (Black) (Black) (Black) CENPE 1.2 (1.01, 1.42) 0.037 0.98 (0.51, 1, 9) 0.5171.17 (0.6, 2.28) 0.352 FCRLB 2.18 (1.16, 4.09) 0.021 1.52 (0.84, 2.74) 0.122 1.82 (0, 97;3.44) 0.06 FSTL4 2.04 (1.2;3.46) 0.013 (90% CI) Full” = hazard ratio (with 90% confidence intervals, fully adjusted for all traditional risk factors including smoking, diabetes , hypertension, HDL-C, LDL-C and BMI

TABLE-US-00013 TABLE 15 Characteristics of Non-Cardioembolic Stroke and Healthy Controls in VSR Cases Controls Characteristics n=562 n=815 p Age (SD) 66.0 (14) 58.8 (8.5) < 0.0001 Male 326 (58.0) 397 (48.7) 0.0007 Smoking 172 (32.0) 147 (18.7) <0.0001 Hypertension 400 (71.2) 403 (49.5) <0.0001 Diabetes 191 (34.0) 36 (4.4) < 0.0001 Dyslipidemia 347 (61.7) 464 (56.9) 0.07 BMI (SD) 26.8 (4.9) ) 26.0 ( 3.8) 0.004 Age and BMI are presented as mean (standard deviation, SD). Other risk factors are presented as a number (%) with the risk factor

TABLE-US-00014 TABLE 16 Properties of six SNPs tested for association with noncardioembolic stroke in VSR. CHD risk frequency in frequency in gene allelic VSR controls ARIC Whites* ChromLoc+ dagger. SNP ID SNP Type SNP Source MyH15 C 0.29 0.303Q13.13 RS3900940 Thr1125Ala Bare et al Kif6 G 0.37 0.36 6p21.2RS20455 Trp719Arg Bare et al.

TABLE-US-00015 TABLE 17 Adjusted Association of Six SNPs with Noncardioembolic Stroke in the VSR Locus Case-Control Model 1 Model 2Genotype n (%) n (%) OR (90% CI) p q OR (90% CI) p C9p21 GG+GA386 (76.7) 568 (72.4) 1.20 (0.95-1.50) 0.10 0.15 1.14 (0.89-1.46)0.20 GG 139 ( 27.6) 154 (19.6) 1.59 (1.20-2.11) 0.004 1.45 (1.06-1.98) 491 (1.06-1.98) 0.0 (52 .8) 1.05 (0.82-1.34) 0.381.02 (0.78-1.33) 0.45 AA 117 (23.3) 216 (27.6) Ref Ref KIF6 GG + GA327 ( 64.8) 475 (60.7) 1.24 (1.01-1.52) 0.05 1.23 (2) 0.98-1.54) 0.07 GG 73 (14.5) 102 (13.0) 1.24 (0.91-1.69) 0.13 1.30 (0.93-1.83) 0.10 GA 254 (50.3) 373 (47.7) 1, 24 (1.00-1.53) 0.05 1.20 (0.3) 0.10AA 178 (35.3) 307 (39.3) ref ref MYH15 CC + CT 281 (55.6) 390 (49.8) 1.31 (1.07-1.60) 0.01 0.06 1.25 (1.00-1.56) 0.05CC 56 (11.1) 72 (9.2 ( ) 1.5.2 () 1.06-2.11) 0.03 1.19 (0.80-1.75) 0.24CT 225 (44.5) 318 (40.6) 1.27 ( 1.03-1.56) 0.03 1.26 (1.00-1.59)0.05 TT 225 (44.5) 394 (50.3) Ref Ref VAMP 326 (64.4) 483 ( 61.6) 1.21 (0.99-1.49) 0.06 0.12 1.33 (1.06-1.67) 0.02 CC 77 (15.2) 112 (14.3) 1.27 (0.93-1.72) 0.10 1.37 (0.98-1.94) 0.029 CT 371 (47.3) 1.20 (0.96-1.49) 0.09 1.32 (1.04-1.68) 0.03TT 180 (35.6) 301 (38.4) Ref Ref

Tabelle-us-00016 Tabelle 18 p-Wert oder unterer oder oberer (Zwei-SNP-Genoutcome-Einstellung? Mode-Genotyp oder 90% CI 90% CI Sided) HCV1116793ZNF132 ISCHIMIS NO GEN TC 0,83 0,693755593926667515 0,08693222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222. .053 hCV1116793 ZNF132 ISCHEMIC NO DOM TC or TT 0.819 0.6892236220.973935207 0.0578 hCV16093418 LOC646377 ISCHEMIC NO GEN AA 1.4830.912916828 2.408756165 0.1815 hCV16093418 LOC646377 ISCHEMIC NOADD A 1.16 0.992191149 1.356678591 0.118 hCV16093418 LOC646377ISCHEMIC NO DOM AG or AA 1.161 0.968083437 1.392968387 0.1766hCV1754669 Chr 9 ISCHEMIC NO GEN AG 0.849 0.694898144 1.03809780.1806 hCV1754669 Chr 9 ISCHEMIC NO GEN AA 0.704 0.5534380260.894406866 0.016 hCV1754669 Chr 9 ISCHEMIC NO ADD A 0.8390.744293003 0.946031417 0.0161 hCV1754669 Chr 9 ISCHEMIC NO DOM AGor AA 0.802 0.663035663 0.970180153 0.0566 hCV1754669 Chr 9ISCHEMIC NO REC AA 0.785 0.643446754 0.957447873 0.0451 hCV25637605FSTL4 ISCHEMIC NO DOM AG or AA 1.141 0.96474641 1.349440416 0.1959hCV26505812 Chr 9 ISCHEMIC NO GEN GG 1.434 1.126756329 1.8251405540.0139 hCV26505812 Chr 9 ISCHEMIC NO ADD G 1.193 1.0576886411.345699564 0.0159 hCV26505812 Chr 9 ISCHEMIC NO DOM GA or GG 1.1750. 971230942 1.421611376 0.1636 hCV26505812 Chr 9 ISCHEMIC NO REC GG1.362 1.115126666 1.663679973 0.0111 hCV7425232 MYH15 ISCHEMIC NOGEN CT 1.207 1.013056501 1.437676114 0.0772 hCV7425232 MYH15ISCHEMIC NO ADD C 1.138 1.002467038 1.290637136 0.0933 hCV7425232MYH15 ISCHEMIC NO DOM CT or CC 1.207 1.022059286 1.424442487 0.0628hCV1116793 ZNF132 ISCHEMIC YES GEN TC 0.703 0.562477582 0.8775722420.0091 hCV1116793 ZNF132 ISCHEMIC YES ADD T 0.75 0.6246083290.899631989 0.0093 hCV1116793 ZNF132 ISCHEMIC YES DOM TC or TT0.701 0.565686919 0.867894166 0.0063 hCV16093418 LOC646377 ISCHEMICYES GEN AA 1.866 1.045328301 3.330322013 0.0766 hCV16093418LOC646377 ISCHEMIC YES ADD A 1.162 0.960599702 1.404663117 0.1948hCV16093418 LOC646377 ISCHEMIC YES REC AA 1.841 1.0345396033.275411467 0.0815 hCV1754669 Chr 9 ISCHEMIC YES GEN AA 0.760.568372651 1.01549685 0.1192 hCV1754669 Chr 9 ISCHEMIC YES ADD A0.87 0.752699651 1.006107576 0.1151 hCV1754669 Chr 9 ISCHEMIC YESDOM AG or AA 0.805 0.638680148 1.014657888 0.1232 hCV2091644 VAMP8ISCHEMIC YES GEN CT 1.401 1.120353768 1.751995633 0.0131 hCV2091644VAMP8 ISCHEMIC YES GEN CC 1.38 1.009559907 1.885674346 0.0901hCV2091644 VAMP8 ISCHEMIC YES ADD C 1.221 1.052766014 1.4164857780.0267 hCV2091644 VAMP8 ISCHEMIC YES DOM CT or CC 1.396 1.1292565551.725713348 0.0096 hCV26505812 Chr 9 ISCHEMIC YES GEN GG 1.3881.036839351 1.858599041 0.0645 hCV26505812 Chr 9 ISCHEMIC YES ADD G1.171 1.011727737 1.355459485 0.0756 hCV26505812 Chr 9 ISCHEMIC YESREC GG 1.398 1.096801262 1.782473489 0.0232 hCV945276 KRT5 ISCHEMICYES REC TT 1.232 0.957897979 1.585681051 0.1725 hCV1116793 ZNF132ATHERO NO GEN TC 0.787 0.646590569 0.95833488 0.0454 hCV1116793ZNF132 ATHERO NO ADD T 0.819 0.696165402 0.962297139 0.0419hCV1116793 ZNF132 ATHERO NO DOM TC or TT 0.784 0.6486645940.947280056 0.0344 hCV1754669 Chr 9 ATHERO NO GEN AG 0.8330.670269439 1.034455809 0.165 hCV1754669 Chr 9 ATHERO NO GEN AA0.676 0.520352663 0.878840811 0.014 hCV1754669 Chr 9 ATHERO NO ADDA 0.823 0.72208458 0.937642062 0.0141 hCV1754669 Chr 9 ATHERO NODOM AG or AA 0.782 0.636551788 0.960683278 0.0493 hCV1754669 Chr 9ATHERO NO REC AA 0.764 0.614147286 0.950963593 0.043 hCV26505812Chr 9 ATHERO NO GEN GG 1.571 1.210420113 2.038944965 0.0044hCV26505812 Chr 9 ATHERO NO ADD G 1.251 1.097125415 1.4260473130.005 hCV26505812 Chr 9 ATHERO NO DOM GA or GG 1.218 0.9877318751. 501018684 0.1217 hCV26505812 Chr 9 ATHERO NO REC GG 1.4851.199236975 1.839906031 0.0024 hCV7425232 MYH15 ATHERO NO GEN CT1.291 1.06621554 1.562183465 0.028 hCV7425232 MYH15 ATHERO NO GENCC 1.36 0.995974126 1.856019239 0.1044 hCV7425232 MYH15 ATHERO NOADD C 1.209 1.05488262 1.385651602 0.0221 hCV7425232 MYH15 ATHERONO DOM CT or CC 1.304 1.087542975 1.562799868 0.0161 hCV945276 KRT5ATHERO NO GEN TT 1.226 0.944746161 1.589848931 0.1986 hCV1116793ZNF132 ATHERO YES GEN TC 0.639 0.501790288 0.814951237 0.0024hCV1116793 ZNF132 ATHERO YES ADD T 0.698 0.570892416 0.8531281570.0032 hCV1116793 ZNF132 ATHERO YES DOM TC or TT 0.64 0.5071109310.808823546 0.0017 hCV16093418 LOC646377 ATHERO YES GEN AA 1.7620.928367604 3.34386559 0.1459 hCV16093418 LOC646377 ATHERO YES RECAA 1.74 0.920040581 3.292138982 0.1527 hCV1754669 Chr 9 ATHERO YESGEN AA 0.765 0.558483335 1.046582925 0.1596 hCV1754669 Chr 9 ATHEROYES ADD A 0.874 0.746743893 1.022073084 0.1568 hCV2091644 VAMP8ATHERO YES GEN CT 1.322 1.038739023 1.682015035 0.0569 hCV2091644VAMP8 ATHERO YES GEN CC 1.366 0.976758835 1.910405456 0.126hCV2091644 VAMP8 ATHERO YES ADD C 1.2 1.023536718 1.4073886980.0592 hCV2091644 VAMP8 ATHERO YES DOM CT or CC 1.332 1.060217421.673849394 0.0388 hCV26505812 Chr 9 ATHERO YES GEN GG 1.4491.059805605 1.98082713 0.0512 hCV26505812 Chr 9 ATHERO YES ADD G1.201 1.025903307 1.405546929 0.056 hCV26505812 Chr 9 ATHERO YESREC GG 1.431 1.106229626 1.851215592 0.022 hCV3054799 KIF6 ATHEROYES ADD G 1.156 0.984174559 1.356831226 0.1385 hCV3054799 KIF6ATHERO YES DOM GA or GG 1.226 0.976764207 1.538041725 0.1403hCV323071 PALLD ATHERO YES GEN GA 0.822 0.647104489 1.0444051620.178 hCV7425232 MYH15 ATHERO YES GEN CT 1.263 1.0027748431.590469093 0.0961 hCV7425232 MYH15 ATHERO YES ADD C 1.1520.973983418 1.361464556 0.1655 hCV7425232 MYH15 ATHERO YES DOM CTor CC 1.248 1.002130266 1.555305517 0.0966 hCV1116793 ZNF132EARLY-ONSET NO GEN TC 0.721 0.555259615 0.93717945 0.0401hCV1116793 ZNF132 EARLY-ONSET NO ADD T 0.742 0.596550429 0.92310850.0246 hCV1116793 ZNF132 EARLY-ONSET NO DOM TC or TT 0.7090.550475956 0.912444516 0.025 hCV16093418 LOC646377 EARLY-ONSET NOGEN AA 2.279 1.165213696 4.458870577 0.0434 hCV16093418 LOC646377EARLY-ONSET NO REC AA 2.283 1.172006222 4.448126516 0.0417hCV1754669 Chr 9 EARLY-ONSET NO GEN AA 0.638 0.4495705430.904532087 0.0342 hCV1754669 Chr 9 EARLY-ONSET NO ADD A 0.8050.677020314 0.957005634 0.0392 hCV1754669 Chr 9 EARLY-ONSET NO RECAA 0.657 0.491043284 0.880225636 0.0181 hCV26505812 Chr 9EARLY-ONSET NO GEN GG 1.454 1.031679957 2.049942 0.0727 hCV26505812Chr 9 EARLY-ONSET NO ADD G 1.205 1.015074491 1.431092302 0.0737hCV26505812 Chr 9 EARLY-ONSET NO DOM GA or GG 1.257 0.9542701231.654681429 0.1722 hCV26505812 Chr 9 EARLY-ONSET NO REC GG 1.3080.984656431 1.736831541 0.1199 hCV3054799 KIF6 EARLY-ONSET NO GENGA 1.256 0.968081501 1.629118384 0.1499 hCV3054799 KIF6 EARLY-ONSETNO DOM GA or GG 1.215 0.949308931 1.553982515 0.1942 hCV7425232MYH15 EARLY-ONSET NO GEN CC 1.411 0.92477899 2.153297741 0.18hCV7425232 MYH15 EARLY-ONSET NO ADD C 1.188 0.989106766 1.426969550.1219 hCV7425232 MYH15 EARLY-ONSET NO DOM CT or CC 1.2270.964448349 1.560176569 0.1624 hCV1116793 ZNF132 EARLY-ONSET YESGEN TC 0.569 0.383972632 0.843482605 0.0184 hCV1116793 ZNF132EARLY-ONSET YES GEN TT 0.257 0.07724157 0.857115583 0.0635hCV1116793 ZNF132 EARLY-ONSET YES ADD T 0.551 0.3903576140.77793835 0.0045 hCV1116793 ZNF132 EARLY-ONSET YES DOM TC or TT0.536 0.36534707 0.78765705 0.0076 hCV1116793 ZNF132 EARLY-ONSETYES REC TT 0.312 0.09554036 1.01979997 0.1057 hCV1754669 Chr 9EARLY-ONSET YES GEN AA 0.531 0.310682745 0.90627091 0.0515hCV1754669 Chr 9 EARLY-ONSET YES ADD A 0.754 0.5825693760.975219212 0.071 hCV1754669 Chr 9 EARLY-ONSET YES REC AA 0.4710.300175493 0.740364979 0.0061 hCV26505812 Chr 9 EARLY- ONSET YESGEN GA 1.613 1.036095685 2.50964297 0.0756 hCV26505812 Chr 9EARLY-ONSET YES GEN GG 1.607 0.955315621 2.704490393 0.1335hCV26505812 Chr 9 EARLY-ONSET YES ADD G 1.267 0.9804731671.638072097 0.129 hCV26505812 Chr 9 EARLY-ONSET YES DOM GA or GG1.611 1.056911526 2.455300114 0.0627 hCV3054799 KIF6 EARLY-ONSETYES GEN GA 1.469 0.997042382 2.16444072 0.1027 hCV3054799 KIF6EARLY-ONSET YES DOM GA or GG 1.423 0.980591812 2.063903309 0.1192hCV323071 PALLD EARLY-ONSET YES GEN GA 0.722 0.4900604641.064203359 0.1673 hCV323071 PALLD EARLY-ONSET YES DOM GA or GG0.74 0.515454368 1.061949638 0.1704

TABLE-US-00017 TABLE 19A Ref ALL Case Case Control Study MarkerGene rs Allele Allele cnt ALL frq cnt frq cnt UCSF hCV1053082 NEU3rs544115 C T 884 0.2039 216 0.1898 668 CCF VSR hCV1053082 NEU3rs544115 C T 500 0.1836 177 0.1615 323 UCSF hCV1116757 rs3794971 TC 844 0.1946 206 0.181 638 CCF VSR hCV1116757 rs3794971 T C 4540.1695 164 0.1513 290 UCSF hCV11425801 PEX6 rs3805953 T C 20680.4763 570 0.5009 1498 CCF VSR hCV11425801 PEX6 rs3805953 T C 13200.4857 554 0.5064 766 UCSF hCV11425842 GNMT rs10948059 C T 20480.4723 513 0.4516 1535 CCF VSR hCV11425842 GNMT rs10948059 C T 12580.4618 485 0.4425 773 UCSF hCV11548152 rs11580249 G T 707 0.1631210 0.1845 497 CCF VSR hCV11548152 rs11580249 G T 413 0.1513 1840.1673 229 UCSF hCV11738775 rs6754561 T C 1616 0.3725 394 0.34621222 CCF VSR hCV11738775 rs6754561 T C 1025 0.3766 387 0.3531 638UCSF hCV11758801 GUCY1B2 rs11841997 C G 131 0.0302 44 0.0387 87 CCFVSR hCV11758801 GUCY1B2 rs11841997 C G 87 0.0319 44 0.04 43 UCSFhCV11861255 GRIK3 rs529407 A G 1038 0.2392 260 0.2285 778 CCF VSRhCV11861255 GRIK3 rs529407 A G 674 0.2506 245 0.226 429 UCSFhCV12071939 rs1950943 G T 929 0.2142 221 0.1942 708 CCF VSRhCV12071939 rs1950943 G T 532 0.1952 193 0.1755 339 UCSF hCV1209800CLIC5 rs35067690 G T 207 0.0477 38 0.0335 169 CCF VSR hCV1209800CLIC5 rs35067690 G T 111 0.0406 34 0.0309 77 UCSF hCV1262973PLEKHG3 rs229653 G A 382 0.088 114 0.1002 268 CCF VSR hCV1262973PLEKHG3 rs229653 G A 277 0.1024 127 0.118 150 UCSF hCV1348610C9orf46 rs3739636 G A 2013 0.4645 559 0.4921 1454 CCF VSRhCV1348610 C9orf46 rs3739636 G A 1223 0.4567 512 0.4794 711 UCSFhCV1408483 BCL2 rs17070848 C T 719 0.1657 209 0.1837 510 CCF VSRhCV1408483 BCL2 rs17070848 C T 526 0.1931 232 0.2117 294 UCSFhCV1452085 TRIM22 rs12223005 C A 468 0.1078 111 0.0975 357 CCF VSRhCV1452085 TRIM22 rs12223005 C A 279 0.1021 98 0.0889 181 UCSFhCV15851766 APC rs2229995 G A 87 0.0201 14 0.0123 73 CCF VSRhCV15851766 APC rs2229995 G A 59 0.022 15 0.0139 44 UCSFhCV15857769 rs2924914 C T 1314 0.3029 368 0.3234 946 CCF VSRhCV15857769 rs2924914 C T 786 0.2883 331 0.3015 455 UCSFhCV15879601 C6orf142 rs2275769 C T 333 0.0767 70 0.0615 263 CCF VSRhCV15879601 C6orf142 rs2275769 C T 171 0.0628 59 0.0537 112 UCSFhCV16134786 rs2857595 G A 774 0.1785 226 0.1989 548 CCF VSRhCV16134786 rs2857595 G A 510 0.1868 227 0.2064 283 UCSF hCV1619596FKBP1A rs1048621 G A 1198 0.2764 337 0.2961 861 CCF VSR hCV1619596FKBP1A rs1048621 G A 675 0.2474 297 0.27 378 UCSF hCV16336 HDrs362277 C T 469 0.108 107 0.094 362 CCF VSR hCV16336 HD rs362277 CT 294 0.1079 97 0.0885 197 UCSF hCV1723718 UMODL1 rs12481805 G A1336 0.3081 377 0.3313 959 CCF VSR hCV1723718 UMODL1 rs12481805 G A779 0.2858 336 0.306 443 UCSF hCV1958451 MIER1 rs2985822 G T 10730.2475 256 0.225 817 CCF VSR hCV1958451 MIER1 rs2985822 G T 6760.2487 248 0.2271 428 UCSF hCV2121658 rs1187332 G A 534 0.1232 1200.1058 414 CCF VSR hCV2121658 rs1187332 G A 331 0.1226 119 0.1104212 UCSF hCV2358247 SPINT4 rs415989 A G 290 0.0669 88 0.0775 202CCF VSR hCV2358247 SPINT4 rs415989 A G 150 0.0549 77 0.0699 73 UCSFhCV2390937 LOC441108 rs739719 C A 318 0.0733 70 0.0615 248 CCF VSRhCV2390937 LOC441108 rs739719 C A 185 0.0678 60 0.0545 125 UCSFhCV25473186 NPY2R rs2880415 T C 2044 0.4708 566 0.4974 1478 CCF VSRhCV25473186 NPY2R rs2880415 T C 1181 0.4336 509 0.4653 672 UCSFhCV25596936 EPHA1 rs6967117 C T 308 0.0709 92 0.0808 216 CCF VSRhCV25596936 EPHA1 rs6967117 C T 241 0.0884 118 0.1073 123 UCSFhCV25615822 DHODH NONE C T 114 0.0263 35 0.0308 79 CCF VSRhCV25615822 DHODH NONE C T 113 0.0414 56 0.0508 57 UCSF hCV25983294EDG2 rs3739709 G A 821 0.1892 190 0.1673 631 CCF VSR hCV25983294EDG2 rs3739709 G A 541 0.1988 197 0.1794 344 UCSF hCV2637554 CHPT1rs3205421 T C 1293 0.2985 368 0.3245 925 CCF VSR hCV2637554 CHPT1rs3205421 T C 842 0.3109 363 0.3336 479 UCSF hCV26478797 CHSY-2rs2015018 G A 1100 0.2537 266 0.2337 834 CCF VSR hCV26478797 CHSY -2rs2015018 G A 721 0.2653 270 0.2473 451 UCSF hCV26881276 C11orf47rs2344829 A G 1429 0.3297 392 0.3451 1037 CCF VSR hCV26881276C11orf47 rs2344829 A G 963 0.3527 418 0.38 545 UCSF hCV27077072rs8060368 C T 1429 0.3293 353 0.3102 1076 CCF VSR hCV27077072rs8060368 C T 911 0.3339 346 0.3145 565 UCSF hCV27473671 C9orf4rs3750465 T C 1270 0.2925 357 0.3137 913 CCF VSR hCV27473671 C9orf4rs3750465 T C 738 0.2709 324 0.2945 414 UCSF hCV27494483 SLC22A15rs3748743 C T 226 0.0521 72 0.0633 154 CCF VSR hCV27494483 SLC22A15rs3748743 C T 127 0.0466 63 0.0573 64 UCSF hCV27504565 MUTYHrs3219489 C G 1135 0.2618 277 0.2434 858 CCF VSR hCV27504565 MUTYHrs3219489 C G 594 0.2174 213 0.1933 381 UCSF hCV27511436 FZD1rs3750145 T C 687 0.1592 157 0.1389 530 CCF VSR hCV27511436 FZD1rs3750145 T C 474 0.1736 173 0.1573 301 UCSF hCV2769503 rs4787956 AG 1495 0.3445 426 0.3743 1069 CCF VSR hCV2769503 rs4787956 A G 8910.3317 393 0.3666 498 UCSF hCV27892569 NRXN3 rs4903741 T C 10220.2364 289 0.2544 733 CCF VSR hCV27892569 NRXN3 rs4903741 T C 6260.23 268 0.2432 358 UCSF hCV28036404 RBL1 rs4812768 T A 875 0.2017216 0.1905 659 CCF VSR hCV28036404 RBL1 rs4812768 T A 511 0.1879182 0.1667 329 UCSF hCV2851380 rs12445805 G C 450 0.1037 99 0.0871351 CCF VSR hCV2851380 rs12445805 G C 320 0.1173 113 0.1027 207UCSF hCV29401764 LOC646588 rs7793552 C T 1402 0.3233 347 0.30491055 CCF VSR hCV29401764 LOC646588 rs7793552 C T 913 0.3357 3370.3086 576 UCSF hCV29537898 rs6073804 C T 393 0.0907 120 0.1056 273CCF VSR hCV29537898 rs6073804 C T 216 0.0796 100 0.0921 116 UCSFhCV29539757 KCNQ3 rs10110659 C A 1311 0.3022 312 0.2746 999 CCF VSRhCV29539757 KCNQ3 rs10110659 C A 870 0.3191 318 0.2896 552 UCSFhCV302629 UBAC2 rs9284183 A G 1247 0.2876 359 0.316 888 CCF VSRhCV302629 UBAC2 rs9284183 A G 763 0.2815 319 0.2932 444 UCSFhCV30308202 LAMA2 rs9482985 G C 917 0.2115 219 0.1924 698 CCF VSRhCV30308202 LAMA2 rs9482985 G C 549 0.2017 200 0.1828 349 UCSFhCV3054550 AIG1 rs1559599 C T 641 0.1476 189 0.1661 452 CCF VSRhCV3054550 AIG1 rs1559599 C T 434 0.1589 189 0.1715 245 UCSFhCV3082219 RFXDC1 rs1884833 G A 505 0.1164 148 0.1301 357 CCF VSRhCV3082219 RFXDC1 rs1884833 G A 344 0.127 159 0.147 185 UCSFhCV31137507 CLOCK rs7660668 G C 1165 0.2683 328 0.2882 837 CCF VSRhCV31137507 CLOCK rs7660668 G C 741 0.272 317 0.2892 424 UCSFhCV31227848 HIVEP3 rs11809423 C T 172 0.0396 61 0.0536 111 CCF VSRhCV31227848 HIVEP3 rs11809423 C T 120 0.044 64 0.0583 56 UCSFhCV31573621 SKAP1 rs11079818 T C 1223 0.2817 295 0.2592 928 CCF VSRhCV31573621 SKAP1 rs11079818 T C 739 0.2751 276 0.2575 463 UCSFhCV31705214 LOC645397 rs12804599 A T 984 0.2266 283 0.2487 701 CCFVSR hCV31705214 LOC645397 rs12804599 A T 596 0.2183 266 0.2418 330UCSF hCV32160712 rs11079160 A T 743 0.1713 221 0.1942 522 CCF VSRhCV32160712 rs11079160 A T 432 0.1595 191 0.1752 241 UCSF hCV435733rs10276935 C G 1346 0.3103 383 0.3366 963 CCF VSR hCV435733rs10276935 C G 819 0.3004 345 0.3142 474 UCSF hCV454333 NVLrs10916581 C T 590 0.136 139 0.1224 451 CCF VSR hCV454333 NVLrs10916581 C T 324 0.1194 110 0.0998 214 UCSF hCV540056 SPHK1rs346802 C T 163 0.0376 32 0.0281 131 CCF VSR hCV540056 SPHK1rs346802 C T 90 0.033 26 0.0237 64 UCSF hCV7917138 OR5H8P rs9822460A G 860 0.1984 255 0.2241 605 CCF VSR hCV7917138 OR5H8P rs9822460 AG 538 0.1981 231 0.2115 307 UCSF hCV8147903 FLJ25715 rs680014 G A971 0.2237 225 0.1977 746 CCF VSR hCV8147903 FLJ25715 rs680014 G A577 0.2124 214 0.1963 363 UCSF hCV8754449 TESK2 rs781226 C T 11260.2596 277 0.2434 849 CCF VSR hCV8754449 TESK2 rs781226 C T 6060.2226 218 0.1989 388 UCSF hCV8820007 rs938390 T A 1055 0.2432 2650.2333 790 CCF VSR hCV8820007 rs938390 T A 651 0.2399 234 0.2135417 UCSF hCV8942032 DDR1 rs1264352 G C 610 0.1406 179 0.1573 431CCF VSR hCV8942032 DDR1 rs1264352 G C 366 0.1343 165 0.1505 201Control ALL ALL Case Case Control Control Study Marker frq Allelecnt frq cnt frq cnt frq UCSF hCV1053082 0.2089 C 3452 0.796 9220.8102 2530 0.7911 CCF VSR hCV1053082 0.1984 C 2224 0.816 9190.8385 1305 0.8016 UCSF hCV1116757 0.1994 T 3494 0.805 932 0.8192562 0.8006 CCF VSR hCV1116757 0.1819 T 2224 0.831 920 0.8487 13040.8181 UCSF hCV11425801 0.4675 T 2274 0.524 568 0.4991 1706 0.5325CCF VSR hCV11425801 0.4717 T 1398 0.514 540 0.4936 858 0.5283 UCSFhCV11425842 0.4797 C 2288 0.528 623 0.5484 1665 0.5203 ​​CCF VSRhCV11425842 0.4748 C 1466 0.538 611 0.5575 855 0.5252 UCSFhCV11548152 0.1555 G 3627 0.837 928 0.8155 2699 0.8445 CCF VSRhCV11548152 0.1405 G 2317 0.849 916 0.8327 1401 0.8595 UCSFhCV11738775 0.3819 T 2722 0.628 744 0.6538 1978 0.6181 CCF VSRhCV11738775 0.3924 T 1697 0.623 709 0.6469 988 0.6076 UCSFhCV11758801 0.0272 C 4207 0.97 1092 0.9613 3115 0.9728 CCF VSRhCV11758801 0.0264 C 2643 0.968 1056 0.96 1587 0.9736 UCSFhCV11861255 0.243 A 3302 0.761 878 0.7715 2424 0.757 CCF VSRhCV11861255 0.2671 A 2016 0.749 839 0.774 1177 0.7329 UCSFhCV12071939 0.2212 G 3409 0.786 917 0.8058 2492 0.7788 CCF VSRhCV12071939 0.2085 G 2194 0.805 907 0.8245 1287 0.7915 UCSFhCV1209800 0.0527 G 4133 0.952 1098 0.9665 3035 0.9473 CCF VSRhCV1209800 0.0472 G 2621 0.959 1068 0.9691 1553 0.9528 UCSFhCV1262973 0.0837 G 3958 0.912 1024 0.8998 2934 0.9163 CCF VSRhCV1262973 0.0921 G 2427 0.898 949 0.882 1478 0.9079 UCSFhCV1348610 0.4547 G 2321 0.536 577 0.5079 1744 0.5453 CCF VSRhCV1348610 0.4416 G 1455 0.543 556 0.5206 899 0.5584 UCSFhCV1408483 0.1594 C 3619 0.834 929 0.8163 2690 0.8406 CCF VSRhCV1408483 0.1806 C 2198 0.807 864 0.7883 1334 0.8194 UCSFhCV1452085 0.1115 C 3872 0.892 1027 0.9025 2845 0.8885 CCF VSRhCV1452085 0.111 C 2453 0.898 1004 0.9111 1449 0.889 UCSFhCV15851766 0.0228 G 4245 0.98 1122 0.9877 3123 0.9772 CCF VSRhCV15851766 0.0274 G 2621 0.978 1061 0.9861 1560 0.9726 UCSFhCV15857769 0.2956 C 3024 0.697 770 0.6766 2254 0.7044 CCF VSRhCV15857769 0.2795 C 1940 0.712 767 0.6985 1173 0.7205 UCSFhCV15879601 0.0821 C 4009 0.923 1068 0.9385 2941 0.9179 CCF VSRhCV15879601 0.0689 C 2553 0.937 1039 0.9463 1514 0.9311 UCSFhCV16134786 0.1712 G 3562 0.822 910 0.8011 2652 0.8288 CCF VSRhCV16134786 0.1736 G 2220 0.813 873 0.7936 1347 0.8264 UCSFhCV1619596 0.2694 G 3136 0.724 801 0.7039 2335 0.7306 CCF VSRhCV1619596 0.2322 G 2053 0.753 803 0.73 1250 0.7678 UCSF hCV163360.113 C 3873 0,892 1031 0,906 2842 0,887

CCF VSR hCV16336 0.121 C 2430 0.892 999 0.9115 1431 0.879 UCSFhCV1723718 0.2999 G 3000 0.692 761 0.6687 2239 0.7001 CCF VSRhCV1723718 0.2721 G 1947 0.714 762 0.694 1185 0.7279 UCSFhCV1958451 0.2555 G 3263 0.753 882 0.775 2381 0.7445 CCF VSRhCV1958451 0.2632 G 2042 0.751 844 0.7729 1198 0.7368 UCSFhCV2121658 0.1294 G 3800 0.877 1014 0.8942 2786 0.8706 CCF VSRhCV2121658 0.1307 G 2369 0.877 959 0.8896 1410 0.8693 UCSFhCV2358247 0.0631 A 4046 0.933 1048 0.9225 2998 0.9369 CCF VSRhCV2358247 0.0448 A 2582 0.945 1025 0.9301 1557 0.9552 UCSFhCV2390937 0.0775 C 4022 0.927 1068 0.9385 2954 0.9225 CCF VSRhCV2390937 0.0767 C 2545 0.932 1040 0.9455 1505 0.9233 UCSFhCV25473186 0.4613 T 2298 0.529 572 0.5026 1726 0.5387 CCF VSRhCV25473186 0.4123 T 1543 0.566 585 0.5347 958 0.5877 UCSFhCV25596936 0.0674 C 4034 0.929 1046 0.9192 2988 0.9326 CCF VSRhCV25596936 0.0756 C 2485 0.912 982 0.8927 1503 0.9244 UCSFhCV25615822 0.0247 C 4224 0.974 1101 0.9692 3123 0.9753 CCF VSRhCV25615822 0.035 C 2617 0.959 1046 0.9492 1571 0.965 UCSFhCV25983294 0.1969 G 3519 0.811 946 0.8327 2573 0.8031 CCF VSRhCV25983294 0.2118 G 2181 0.801 901 0.8206 1280 0.7882 UCSFhCV2637554 0.2892 T 3039 0.702 766 0.6755 2273 0.7108 CCF VSRhCV2637554 0.2957 T 1866 0.689 725 0.6664 1141 0.7043 UCSFhCV26478797 0.2608 G 3236 0.746 872 0.7663 2364 0.7392 CCF VSRhCV26478797 0.2774 G 1997 0.735 822 0.7527 1175 0.7226 UCSFhCV26881276 0.3243 A 2905 0.67 744 0.6549 2161 0.6757 CCF VSRhCV26881276 0.3344 A 1767 0.647 682 0.62 1085 0.6656 UCSFhCV27077072 0.336 C 2911 0.671 785 0.6898 2126 0.664 CCF VSRhCV27077072 0.3471 C 1817 0.666 754 0.6855 1063 0.6529 UCSFhCV27473671 0.285 T 3072 0.708 781 0.6863 2291 0.715 CCF VSRhCV27473671 0.2549 T 1986 0.729 776 0.7055 1210 0.7451 UCSFhCV27494483 0.0481 C 4114 0.948 1066 0.9367 3048 0.9519 CCF VSRhCV27494483 0.0394 C 2599 0.953 1037 0.9427 1562 0.9606 UCSFhCV27504565 0.2683 C 3201 0.738 861 0.7566 2340 0.7317 CCF VSRhCV27504565 0.2337 C 2138 0.783 889 0.8067 1249 0.7663 UCSFhCV27511436 0.1665 T 3627 0.841 973 0.8611 2654 0.8335 CCF VSRhCV27511436 0.1847 T 2256 0.826 927 0.8427 1329 0.8153 UCSFhCV2769503 0.3339 A 2845 0.656 712 0.6257 2133 0.6661 CCF VSRhCV2769503 0.3086 A 1795 0.668 679 0.6334 1116 0.6914 UCSFhCV27892569 0.2299 T 3302 0.764 847 0.7456 2455 0.7701 CCF VSRhCV27892569 0.221 T 2096 0.77 834 0.7568 1262 0.779 UCSFhCV28036404 0.2057 T 3463 0.798 918 0.8095 2545 0.7943 CCF VSRhCV28036404 0.2021 T 2209 0.812 910 0.8333 1299 0.7979 UCSFhCV2851380 0.1096 G 3890 0.896 1037 0.9129 2853 0.8904 CCF VSRhCV2851380 0.1271 G 2408 0.883 987 0.8973 1421 0.8729 UCSFhCV29401764 0.3299 C 2934 0.677 791 0.6951 2143 0.6701 CCF VSRhCV29401764 0.3538 C 1807 0.664 755 0.6914 1052 0.6462 UCSFhCV29537898 0.0854 C 3941 0.909 1016 0.8944 2925 0.9146 CCF VSRhCV29537898 0.0713 C 2496 0.92 986 0.9079 1510 0.9287 UCSFhCV29539757 0.312 C 3027 0.698 824 0.7254 2203 0.688 CCF VSRhCV29539757 0.3391 C 1856 0.681 780 0.7104 1076 0.6609 UCSFhCV302629 0.2775 A 3089 0.712 777 0.684 2312 0.7225 CCF VSRhCV302629 0.2737 A 1947 0.719 769 0.7068 1178 0.7263 UCSFhCV30308202 0.2183 G 3419 0.789 919 0.8076 2500 0.7817 CCF VSRhCV30308202 0.2144 G 2173 0.798 894 0.8172 1279 0.7856 UCSFhCV3054550 0.1411 C 3701 0.852 949 0.8339 2752 0.8589 CCF VSRhCV3054550 0.1503 C 2298 0.841 913 0.8285 1385 0.8497 UCSFhCV3082219 0.1115 G 3835 0.884 990 0.8699 2845 0.8885 CCF VSRhCV3082219 0.1138 G 2364 0.873 923 0.853 1441 0.8862 UCSFhCV31137507 0.2612 G 3177 0.732 810 0.7118 2367 0.7388 CCF VSRhCV31137507 0.2604 G 1983 0.728 779 0.7108 1204 0.7396 UCSFhCV31227848 0.0347 C 4168 0.96 1077 0.9464 3091 0.9653 CCF VSRhCV31227848 0.0344 C 2608 0.956 1034 0.9417 1574 0.9656 UCSFhCV31573621 0.2896 T 3119 0.718 843 0.7408 2276 0.7104 CCF VSRhCV31573621 0.2869 T 1947 0.725 796 0.7425 1151 0.7131 UCSFhCV31705214 0.2188 A 3358 0.773 855 0.7513 2503 0.7812 CCF VSRhCV31705214 0.2025 A 2134 0.782 834 0.7582 1300 0.7975 UCSFhCV32160712 0.1631 A 3595 0.829 917 0.8058 2678 0.8369 CCF VSRhCV32160712 0.1489 A 2276 0.841 899 0.8248 1377 0.8511 UCSFhCV435733 0.3009 C 2992 0.69 755 0.6634 2237 0.6991 CCF VSRhCV435733 0.2912 C 1907 0.7 753 0.6858 1154 0.7088 UCSF hCV4543330.1408 C 3748 0.864 997 0.8776 2751 0.8592 CCF VSR hCV454333 0.1328C 2390 0.881 992 0.9002 1398 0.8672 UCSF hCV540056 0.0409 C 41770.962 1106 0.9719 3071 0.9591 CCF VSR hCV540056 0.0394 C 2634 0.9671072 0.9763 1562 0.9606 UCSF hCV7917138 0.1893 A 3474 0.802 8830.7759 2591 0.8107 CCF VSR hCV7917138 0.189 A 2178 0.802 861 0.78851317 0.811 UCSF hCV8147903 0.233 G 3369 0.776 913 0.8023 2456 0.767CCF VSR hCV8147903 0.2232 G 2139 0.788 876 0.8037 1263 0.7768 UCSFhCV8754449 0.2653 C 3212 0.74 861 0.7566 2351 0.7347 CCF VSRhCV8754449 0.2386 C 2116 0.777 878 ​​0.8011 1238 0.7614 UCSFhCV8820007 0.2467 T 3283 0.757 871 0.7667 2412 0.7533 CCF VSRhCV8820007 0.2577 T 2063 0.76 862 0.7865 1201 0.7423 UCSFhCV8942032 0.1347 G 3728 0.859 959 0.8427 2769 0.8653 CCF VSRhCV8942032 0.1233 G 2360 0.866 931 0.8495 1429 0.8767

Tabelle-us-00018 Tabelle 19b alle Fall-Case-Kontrollkontrolle Allstudy-Marker RS ​​Genot CNT FRQ CNT FRQ CNT FRQ Genot CNT All FRQUCSFCCF HCV1053082 RS5444115 T T T 98 0,0452 17 0,0299 81 0,0507 T C688 0,3173 VSR HCV105308241588 0 0.2907 UCSFCCF hCV1116757 rs3794971 C C 85 0.0392 240.0422 61 0.0381 C T 674 0.3107 VSR hCV1116757 rs3794971 C C 410.0306 13 0.024 28 0.0351 C T 372 0.2778 UCSFCCF hCV11425801rs3805953 C C 499 0.2298 143 0.2513 356 0.2222 C T 1070 0.4929 VSRhCV11425801 rs3805953 C C 319 0.2347 140 0.2559 179 0.2204 C T 6820.5018 UCSFCCF hCV11425842 rs10948059 T T 486 0.2242 111 0.1954 3750.2344 T C 1076 0.4963 VSR hCV11425842 rs10948059 T T 283 0.2078104 0.1898 179 0.2199 T C 692 0.5081 UCSFCCF hCV11548152 rs11580249T T 52 0.024 15 0.0264 37 0.0232 T G 603 0.2783 VSR hCV11548152rs11580249 T T 34 0.0249 17 0.0309 17 0.0209 T G 345 0.2527 UCSFCCFhCV11738775 rs6754561 C C 279 0.1286 57 0.1002 222 0.1388 C T 10580.4878 VSR hCV11738775 rs6754561 C C 201 0.1477 65 0.1186 1360.1673 C T 623 0.4578 UCSFCCF hCV11758801 rs11841997 G G 4 0.0018 20.0035 2 0.0012 G C 123 0.0567 VSR hCV11758801 rs11841997 G G 20.0015 2 0.0036 0 0 G C 83 0.0608 UCSFCCF hCV11861255 rs529407 G G144 0.0664 27 0.0475 117 0.0731 G A 750 0.3456 VSR hCV11861255rs529407 G G 95 0.0706 30 0.0554 65 0.0809 G A 484 0.3599 UCSFCCFhCV12071939 rs1950943 T T 94 0.0433 15 0.0264 79 0.0494 T G 7410.3416 VSR hCV12071939 rs1950943 T T 61 0.0448 25 0.0455 36 0.0443T G 410 0.3008 UCSFCCF hCV1209800 rs35067690 T T 4 0.0018 0 0 40.0025 T G 199 0.0917 VSR hCV1209800 rs35067690 T T 4 0.0029 0 0 40.0049 T G 103 0.0754 UCSFCCF hCV1262973 rs229653 A A 29 0.0134 110.0193 18 0.0112 A G 324 0.1493 VSR hCV1262973 rs229653 A A 160.0118 5 0.0093 11 0.0135 A G 245 0.1812 UCSFCCF hCV1348610rs3739636 A A 474 0.2187 135 0.2377 339 0.212 A G 1065 0.4912 VSRhCV1348610 rs3739636 A A 301 0.2566 137 0.2566 164 0.2037 A G 6210.4638 UCSFCCF hCV1408483 rs17070848 T T 56 0.0246 14 0.0246 420.0262 T C 607 0.2799 VSR hCV1408483 rs17070848 T T 50 0.0401 220.0401 28 0.0344 T C 426 0.3128 UCSFCCF hCV1452085 rs12223005 A A28 0.0053 3 0.0053 25 0.0156 A C 412 0.1899 VSR hCV1452085rs12223005 A A 17 0.0127 7 0.0127 10 0.0123 A C 245 0.1794 UCSFCCFhCV15851766 rs2229995 A A 0 0 0 0 0 0 A G 87 0.0402 VSR hCV15851766rs2229995 A A 0 0 0 0 0 0 A G 59 0.044 UCSFCCF hCV15857769rs2924914 T T 212 0.0977 65 0.1142 147 0.0919 T C 890 0.4183 VSRhCV15857769 rs2924914 T T 106 0.0778 53 0.0965 53 0.0651 T C 5740.4098 UCSFCCF hCV15879601 rs2275769 T T 13 0.006 2 0.0035 110.0069 T C 307 0.116 VSR hCV15879601 rs2275769 T T 8 0.0059 0 0 80.0098 T C 155 0.1075 UCSFCCF hCV16134786 rs2857595 A A 72 0.033222 0.0387 50 0.0312 A G 630 0.3204 VSR hCV16134786 rs2857595 A A 530.0388 22 0.04 31 0.038 A G 404 0.3327 UCSFCCF hCV1619596 rs1048621A A 186 0.0858 54 0.0949 132 0.0826 A G 826 0.4025 VSR hCV1619596rs1048621 A A 83 0.0609 37 0.0673 46 0.0565 A G 509 0.4055 UCSFCCFhCV16336 rs362277 T T 31 0.0143 7 0.0123 24 0.015 T C 407 0.1634VSR hCV16336 rs362277 T T 15 0.011 2 0.0036 13 0.016 T C 264 0.1697UCSFCCF hCV1723718 rs12481805 A A 199 0.0918 61 0.1072 138 0.0863 AG 938 0.4482 VSR hCV1723718 rs12481805 A A 123 0.0902 53 0.0965 700.086 A G 533 0.4189 UCSFCCF hCV1958451 rs2985822 T T 135 0.623 300.0527 105 0.0657 T G 803 0.3445 VSR hCV1958451 rs2985822 T T 900.0662 27 0.0495 63 0.0775 T G 496 0.3553 UCSFCCF hCV2121658rs1187332 A A 23 0.0106 6 0.0106 17 0.0106 A G 488 0.1905 VSRhCV2121658 rs1187332 A A 18 0.0133 3 0.0056 15 0.0185 A G 2950.2096 UCSFCCF hCV2358247 rs415989 G G 14 0.0065 2 0.0035 12 0.0075G A 262 0.1208 VSR hCV2358247 rs415989 G G 5 0.0037 5 0.0091 0 0 GA 140 0.1025 UCSFCCF hCV2390937 rs739719 A A 12 0.0055 2 0.0035 100.0062 A C 294 0.1355 VSR hCV2390937 rs739719 A A 3 0.0022 1 0.00182 0.0025 A C 179 0.1311 UCSFCCF hCV25473186 rs2880415 C C 4880.2248 135 0.2373 353 0.2203 C T 1068 0.4919 VSR hCV25473186rs2880415 C C 246 0.1806 109 0.1993 137 0.1681 C T 689 0.5059UCSFCCF hCV25596936 rs6967117 T T 13 0.006 2 0.0035 11 0.0069 T C282 0.1299 VSR hCV25596936 rs6967117 T T 15 0.011 7 0.0127 8 0.0098T C 211 0.1548 UCSFCCF hCV25615822 NONE T T 1 0.0005 1 0.0018 0 0 TC 112 0.0516 VSR hCV25615822 NONE T T 2 0.0015 1 0.0018 1 0.0012 TC 109 0.0799 UCSFCCF hCV25983294 rs3739709 A A 75 0.0346 19 0.033556 0.035 A G 671 0.3092 VSR hCV25983294 rs3739709 A A 64 0.047 230.0419 41 0.0505 A G 413 0.3035 UCSFCCF hCV2637554 rs3205421 C C190 0.0877 64 0.1129 126 0.0788 C T 913 0.4215 VSR hCV2637554rs3205421 C C 139 0.1027 63 0.1158 76 0.0938 C T 564 0.4165 UCSFCCFhCV26478797 rs2015018 A A 122 0.0563 31 0.0545 91 0.0569 A G 8560.3948 VSR hCV26478797 rs2015018 A A 95 0.0699 28 0.0513 67 0.0824A G 531 0.3907 UCSFCCF hCV26881276 rs2344829 G G 250 0.1154 660.1162 184 0.1151 G A 929 0.4287 VSR hCV26881276 rs2344829 G G 1830.1341 86 0.1564 97 0.119 G A 597 0.4374 UCSFCCF hCV27077072rs8060368 T T 237 0.1092 60 0.1054 177 0.1106 T C 955 0.4401 VSRhCV27077072 rs8060368 T T 152 0.1114 54 0.0982 98 0.1204 T C 6070.445 UCSFCCF hCV27473671 rs3750465 C C 183 0.0843 54 0.0949 1290.0805 C T 904 0.4164 VSR hCV27473671 rs3750465 C C 103 0.0756 510.0927 52 0.064 C T 532 0.3906 UCSFCCF hCV27494483 rs3748742 T T 120.005 4 0.007 8 0.005 T C 202 0.0931 VSR hCV27494483 rs3748742 T T3 0.0022 2 0.0036 1 0.0012 T C 121 0.0888 UCSFCCF hCV27504565rs3219489 G G 138 0.0637 39 0.0685 99 0.0619 G C 859 0.3962 VSRhCV27504565 rs3219489 G G 67 0.049 13 0.0236 54 0.0663 G C 4600.3367 UCSFCCF hCV27511436 rs3750145 C C 55 0.0255 5 0.0088 500.0314 C T 577 0.2375 VSR hCV27511436 rs3750145 C C 47 0.0344 160.0291 31 0.038 C T 380 0.2784 UCSFCCF hCV2769503 rs4787956 G G 2530.1166 74 0.1301 179 0.1118 G A 989 0.4558 VSR hCV2769503 rs4787956G G 146 0.1087 65 0.1213 81 0.1004 G A 599 0.446 UCSFCCFhCV27892569 rs4903741 C C 113 0.0523 35 0.0616 78 0.0489 C T 7960.3682 VSR hCV27892569 rs4903741 C C 88 0.0647 34 0.0617 54 0.0667C T 450 0.3306 UCSFCCF hCV28036404 rs4812768 A A 99 0.0456 17 0.0382 0.0512 A T 677 0.3121 VSR hCV28036404 rs4812768 A A 39 0.0287 130.0238 26 0.0319 A T 433 0.3184 UCSFCCF hCV2851380 rs12445805 C C32 0.0147 4 0.007 28 0.0175 C G 386 0.1779 VSR hCV2851380rs12445805 C C 21 0.0154 7 0.0127 14 0.0172 C G 278 0.2038 UCSFCCFhCV29401764 rs7793552 T T 223 0.1029 62 0.109 161 0.1007 T C 9560.441 VSR hCV29401764 rs7793552 T T 159 0.1169 58 0.1062 101 0.1241T C 595 0.4375 UCSFCCF hCV29537898 rs6073804 T T 23 0.0106 100.0176 13 0.0081 T C 347 0.1601 VSR hCV29537898 rs6073804 T T 60.0044 5 0.0092 1 0.0012 T C 204 0.1504 UCSFCCF hCV29538757rs10110659 A A 192 0.0885 49 0.0863 143 0.0893 A C 927 0.4274 VSRhCV29538757 rs10110659 A A 136 0.0998 46 0.0838 90 0.1106 A C 5980.4387 UCSFCCF hCV302629 rs9284183 G G 185 0.0853 68 0.1197 1170.0731 G A 877 0.4045 VSR hCV302629 rs9284183 G G 111 0.0819 550.1011 56 0.0691 G A 541 0.3993 UCSFCCF hCV30308202 rs9482985 C C101 0.0466 17 0.0299 84 0.0525 C G 715 0.3298 VSR hCV30308202rs9482985 C C 66 0.0485 25 0.0457 41 0.0504 C G 417 0.3064 UCSFCCFhCV3054550 rs1559599 T T 50 0.023 17 0.0299 33 0.0206 T C 5410.2492 VSR hCV3054550 rs1559599 T T 36 0.0264 14 0.0254 22 0.027 TC 362 0.265 UCSFCCF hCV3082219 rs1884833 A A 27 0.0124 7 0.0123 200.0125 A G 451 0.2078 VSR hCV3082219 rs1884833 A A 21 0.0155 110.0203 10 0.0123 A G 302 0.223 UCSFCCF hCV31137507 rs7660668 C C162 0.0746 47 0.0826 115 0.0718 C G 841 0.3874 VSR hCV31137507rs7660668 C C 101 0.0742 46 0.0839 55 0.0676 C G 539 0.3957 UCSFCCFhCV31227848 rs11809423 T T 4 0.0018 1 0.0018 3 0.0019 T C 1640.0756 VSR hCV31227848 rs11809423 T T 2 0.0015 1 0.0018 1 0.0012 TC 116 0.085 UCSFCCF hCV31573621 rs11079818 C C 164 0.0755 36 0.0633128 0.0799 C T 895 0.4123 VSR hCV31573621 rs11079818 C C 100 0.074530 0.056 70 0.0867 C T 539 0.4013 UCSFCCF hCV31705214 rs12804599 TT 116 0.0534 41 0.0721 75 0.0468 T A 752 0.3464 VSR hCV31705214rs12804599 T T 71 0.052 31 0.0564 40 0.0491 T A 454 0.3326 UCSFCCFhCV32160712 rs11079160 T T 57 0.0263 17 0.0299 40 0.025 T A 6290.29 VSR hCV32160712 rs11079160 T T 37 0.0273 20 0.0367 17 0.021 TA 358 0.2644 UCSFCCF hCV435733 rs10276935 G G 226 0.1042 65 0.1142161 0.1006 G C 894 0.4122 VSR hCV435733 rs10276935 G G 132 0.096846 0.0838 86 0.1057 G C 555 0.4072 UCSFCCF hCV454333 rs10916581 T T42 0.0194 6 0.0106 36 0.0225 T C 506 0.2333 VSR hCV454333rs10916581 T T 25 0.0184 5 0.0091 20 0.0248 T C 274 0.2019 UCSFCCFhCV540056 rs346802 T T 2 0.0009 1 0.0018 1 0.0006 T C 159 0.0733VSR hCV540056 rs346802 T T 0 0 0 0 0 0 T C 90 0.0661 UCSFCCFhCV7917138 rs9822460 G G 94 0.0434 29 0.051 65 0.0407 G A 6720.3101 VSR hCV7917138 rs9822460 G G 53 0.039 29 0.0531 24 0.0296 GA 432 0.3181 UCSFCCF hCV8147903 rs680014 A A 118 0.0544 25 0.043993 0.0581 A G 735 0.3387 VSR hCV8147903 rs680014 A A 66 0.0486 210.0385 45 0.0554 A G 445 0.3277 UCSFCCF hCV8754449 rs781226 T T 1370.0632 37 0.065 100 0.0625 T C 852 0.3928 VSR hCV8754449 rs781226 TT 73 0.0536 15 0.0274 58 0.0713 T C 460 0.338 UCSFCCF hCV8820007rs938390 A A 143 0.0659 29 0.0511 114 0.0712 A T 769 0.3545 VSRhCV8820007 rs938390 A A 94 0.0693 28 0.0511 66 0.0816 A T 4630.3412 UCSFCCF hCV8942032 rs1264352 C C 46 0.0212 14 0.0246 32 0.02C G 518 0.2388 VSR hCV8942032 rs1264352 C C 34 0.0249 16 0.0292 180.0221 C G 298 0.2186 Case Case Control Control ALL ALL Case CaseControl Control Study Marker cnt frq cnt frq Genot cnt frq cnt frqcnt frq UCSFCCF hCV1053082 182 0.3199 506 0.3164 C C 1382 0.6375370 0.6503 1012 0.6329 VSR hCV1053082 145 0.2646 251 0.3084 C C 9140.6711 387 0.7062 527 0.6474 UCSFCCF hCV1116757 158 0.2777 5160.3225 T T 1410 0.6501 387 0.6801 1023 0.6394 VSR hCV1116757 1380.2546 234 0.2936 T T 926 0.6916 391 0.7214 535 0.6713 UCSFCCFhCV11425801 284 0.4991 786 0.4906 T T 602 0.2773 142 0.2496 4600.2871 VSR hCV11425801 274 0.5009 408 0.5025 T T 358 0.2634 1330.2431 225 0.2771 UCSFCCF hCV11425842 291 0,5123 785 0,4906 C C 6060,2795 166 0,2923 440 0,275 VSR Hcv11425842 277 0,5055 415 0,5098 CC 387 0,2841 167 0,30472 0,2703 ucsfccfcfcfcfcfcfcfcfcfcfcfcfs.

VSR hCV11548152 150 0.2727 195 0.2393 G G 986 0.7223 383 0.6964 6030.7399 UCSFCCF hCV11738775 280 0.4921 778 0.4862 T T 832 0.3836 2320.4077 600 0.375 VSR hCV11738775 257 0.469 366 0.4502 T T 5370.3946 226 0.4124 311 0.3825 UCSFCCF hCV11758801 40 0.0704 830.0518 C C 2042 0.9414 526 0.9261 1516 0.9469 VSR hCV11758801 400.0727 43 0.0528 C C 1280 0.9377 508 0.9236 772 0.9472 UCSFCCFhCV11861255 206 0.362 544 0.3398 A A 1276 0.588 336 0.5905 9400.5871 VSR hCV11861255 185 0.3413 299 0.3724 A A 766 0.5695 3270.6033 439 0.5467 UCSFCCF hCV12071939 191 0.3357 550 0.3438 G G1334 0.615 363 0.638 971 0.6069 VSR hCV12071939 143 0.26 267 0.3284G G 892 0.6544 382 0.6945 510 0.6273 UCSFCCF hCV1209800 38 0.0669161 0.1005 G G 1967 0.9065 530 0.9331 1437 0.897 VSR hCV1209800 340.0617 69 0.0847 G G 1259 0.9217 517 0.9383 742 0.9104 UCSFCCFhCV1262973 92 0.1617 232 0.1449 G G 1817 0.8373 466 0.819 13510.8438 VSR hCV1262973 117 0.2175 128 0.1572 G G 1091 0.807 4160.7732 675 0.8292 UCSFCCF hCV1348610 289 0.5088 776 0.4853 G G 6280.2898 144 0.2535 484 0.3027 VSR hCV1348610 238 0.4457 383 0.4758 GG 417 0.3114 159 0.2978 258 0.3205 UCSFCCF hCV1408483 181 0.3181426 0.2662 C C 1506 0.6943 374 0.6573 1132 0.7075 VSR hCV1408483188 0.3431 238 0.2924 C C 886 0.6505 338 0.6168 548 0.6732 UCSFCCFhCV1452085 105 0.1845 307 0.1918 C C 1730 0.7972 461 0.8102 12690.7926 VSR hCV1452085 84 0.1525 161 0.1975 C C 1104 0.8082 4600.8348 644 0.7902 UCSFCCF hCV15851766 14 0.0246 73 0.0457 G G 20790.9597 554 0.9754 1525 0.9543 VSR hCV15851766 15 0.0279 44 0.0549 GG 1281 0.956 523 0.9721 758 0.9451 UCSFCCF hCV15857769 238 0.4183652 0.4075 C C 1067 0.4919 266 0.4675 801 0.5006 VSR hCV15857769225 0.4098 349 0.4287 C C 683 0.5011 271 0.4936 412 0.5061 UCSFCCFhCV15879601 66 0.116 241 0.1504 C C 1851 0.8526 501 0.8805 13500.8427 VSR hCV15879601 59 0.1075 96 0.1181 C C 1199 0.8803 4900.8925 709 0.8721 UCSFCCF hCV16134786 182 0.3204 448 0.28 G G 14660.6762 364 0.6408 1102 0.6888 VSR hCV16134786 183 0.3327 221 0.2712G G 908 0.6652 345 0.6273 563 0.6908 UCSFCCF hCV1619596 229 0.4025597 0.3736 G G 1155 0.533 286 0.5026 869 0.5438 VSR hCV1619596 2230.4055 286 0.3514 G G 772 0.566 290 0.5273 482 0.5921 UCSFCCFhCV16336 93 0.1634 314 0.196 C C 1733 0.7982 469 0.8243 1264 0.789VSR hCV16336 93 0.1697 171 0.2101 C C 1083 0.7952 453 0.8266 6300.774 UCSFCCF hCV1723718 255 0.4482 683 0.4271 G G 1031 0.4756 2530.4446 778 0.4866 VSR hCV1723718 230 0.4189 303 0.3722 G G 7070.5187 266 0.4845 441 0.5418 UCSFCCF hCV1958451 196 0.3445 6070.3796 G G 1230 0.5673 343 0.6028 887 0.5547 VSR hCV1958451 1940.3553 302 0.3715 G G 773 0.5688 325 0.5952 448 0.551 UCSFCCFhCV2121658 108 0.1905 380 0.2375 G G 1656 0.7642 453 0.7989 12030.7519 VSR hCV2121658 113 0.2096 182 0.2244 G G 1037 0.7681 4230.7848 614 0.7571 UCSFCCF hCV2358247 84 0.1479 178 0.1112 A A 18920.8727 482 0.8486 1410 0.8812 VSR hCV2358247 67 0.1216 73 0.0896 AA 1221 0.8939 479 0.8693 742 0.9104 UCSFCCF hCV2390937 66 0.116 2280.1424 C C 1864 0.859 501 0.8805 1363 0.8513 VSR hCV2390937 580.1055 121 0.1485 C C 1183 0.8667 491 0.8927 692 0.8491 UCSFCCFhCV25473186 296 0.5202 772 0.4819 T T 615 0.2833 138 0.2425 4770.2978 VSR hCV25473186 291 0.532 398 0.4883 T T 427 0.3135 1470.2687 280 0.3436 UCSFCCF hCV25596936 88 0.1547 194 0.1211 C C 18760.8641 479 0.8418 1397 0.872 VSR hCV25596936 104 0.1891 107 0.1316C C 1137 0.8342 439 0.7982 698 0.8585 UCSFCCF hCV25615822 33 0.058179 0.0493 C C 2056 0.9479 534 0.9401 1522 0.9507 VSR hCV25615822 540.098 55 0.0676 C C 1254 0.9187 496 0.9002 758 0.9312 UCSFCCFhCV25983294 152 0.2676 519 0.324 G G 1424 0.6562 397 0.6989 10270.6411 VSR hCV25983294 151 0.275 262 0.3227 G G 884 0.6495 3750.6831 509 0.6268 UCSFCCF hCV2637554 240 0.4233 673 0.4209 T T 10630.4908 263 0.4638 800 0.5003 VSR hCV2637554 237 0.4357 327 0.4037 TT 651 0.4808 244 0.4485 407 0.5025 UCSFCCF hCV26478797 204 0.3585652 0.4078 G G 1190 0.5489 334 0.587 856 0.5353 VSR hCV26478797 2140.3919 317 0.3899 G G 733 0.5394 304 0.5568 429 0.5277 UCSFCCFhCV26881276 260 0.4577 669 0.4184 A A 988 0.4559 242 0.4261 7460.4665 VSR hCV26881276 246 0.4473 351 0.4307 A A 585 0.4286 2180.3964 367 0.4503 UCSFCCF hCV27077072 233 0.4095 722 0.451 C C 9780.4507 276 0.4851 702 0.4385 VSR hCV27077072 238 0.4327 369 0.4533C C 605 0.4435 258 0.4691 347 0.4263 UCSFCCF hCV27473671 249 0.4376655 0.4089 T T 1084 0.4993 266 0.4675 818 0.5106 VSR hCV27473671222 0.4036 310 0.3818 T T 727 0.5338 277 0.5036 450 0.5542 UCSFCCFhCV27494483 64 0.1125 138 0.0862 C C 1956 0.9014 501 0.8805 14550.9088 VSR hCV27494483 59 0.1073 62 0.0763 C C 1239 0.909 4890.8891 750 0.9225 UCSFCCF hCV27504565 199 0.3497 660 0.4128 C C1171 0.5401 331 0.5817 840 0.5253 VSR hCV27504565 187 0.3394 2730.335 C C 839 0.6142 351 0.637 4888 0.5988 UCSFCCF hCV27511436 1470.2602 430 0.2701 T T 1525 0.707 413 0.731 1112 0.6985 VSRhCV27511436 141 0.2564 239 0.2933 T T 938 0.6872 393 0.7145 5450.6687 UCSFCCF hCV2769503 278 0.4886 711 0.4441 A A 928 0.4276 2170.3814 711 0.4441 VSR hCV2769503 263 0.4907 336 0.4164 A A 5980.4453 208 0.3881 390 0.4833 UCSFCCF hCV27892569 219 0.3856 5770.362 T T 1253 0.5796 314 0.5528 939 0.5891 VSR hCV27892569 2000.363 250 0.3086 T T 823 0.6047 317 0.5753 506 0.6247 UCSFCCFhCV28036404 182 0.321 495 0.309 T T 1393 0.6422 368 0.649 10250.6398 VSR hCV28036404 156 0.2857 277 0.3403 T T 888 0.6529 3770.6905 511 0.6278 UCSFCCF hCV2851380 91 0.1602 295 0.1841 G G 17520.8074 473 0.8327 1279 0.7984 VSR hCV2851380 99 0.18 179 0.2199 G G1065 0.7808 444 0.8073 621 0.7629 UCSFCCF hCV29401764 223 0.3919733 0.4584 C C 989 0.4562 284 0.4991 705 0.4406 VSR hCV29401764 2210.4048 374 0.4595 C C 606 0.4456 267 0.489 339 0.4165 UCSFCCFhCV29537898 100 0.1761 247 0.1545 C C 1797 0.8293 458 0.8063 13390.8374 VSR hCV29537898 90 0.1657 114 0.1402 C C 1146 0.8451 4480.825 698 0.8585 UCSFCCF hCV29538757 214 0.3768 713 0.4453 C C 10500.4841 305 0.537 745 0.4653 VSR hCV29538757 226 0.4117 372 0.457 CC 629 0.4615 277 0.5046 352 0.5324 UCSFCCF hCV302629 223 0.3926 6540.4088 A A 1106 0.5101 277 0.4877 829 0.5181 VSR hCV302629 2090.3842 332 0.4094 A A 703 0.5188 280 0.5147 423 0.5216 UCSFCCFhCV30308202 185 0.3251 530 0.3315 G G 1352 0.6236 367 0.645 9850.616 VSR hCV30308202 150 0.2742 267 0.328 G G 878 0.6451 3720.6801 506 0.6216 UCSFCCF hCV3054550 155 0.2724 386 0.2409 C C 15800.7278 397 0.6977 1183 0.7385 VSR hCV3054550 161 0.2922 201 0.2466C C 968 0.7086 376 0.6824 592 0.7264 UCSFCCF hCV3082219 134 0.2355317 0.198 G G 1692 0.7797 428 0.7522 1264 0.7895 VSR hCV3082219 1370.2532 165 0.203 G G 1031 0.7614 393 0.7264 638 0.7847 UCSFCCFhCV31137507 234 0.4112 607 0.3789 G G 1168 0.538 288 0.5062 8800.5493 ​​VSR hCV31137507 225 0.4106 314 0.3857 G G 722 0.5301 2770.5055 445 0.5467 UCSFCCF hCV31227848 59 0.1037 105 0.0656 C C 20020.9226 509 0.8946 1493 0.9325 VSR hCV31227848 62 0.1129 54 0.0663 CC 1246 0.9135 486 0.8852 760 0.9325 UCSFCCF hCV31573621 223 0.3919672 0.4195 T T 1112 0.5122 310 0.5448 802 0.5006 VSR hCV31573621216 0.403 323 0.4002 T T 704 0.5242 290 0.541 414 0.513 UCSFCCFhCV31705214 201 0.3533 551 0.3439 A A 1303 0.6002 327 0.5747 9760.6092 VSR hCV31705214 204 0.3709 250 0.3067 A A 840 0.6154 3150.5727 525 0.6442 UCSFCCF hCV32160712 187 0.3286 442 0.2762 A A1483 0.6837 365 0.6415 1118 0.6988 VSR hCV32160712 151 0.2771 2070.2559 A A 959 0.7083 374 0.6862 585 0.7231 UCSFCCF hCV435733 2530.4446 641 0.4006 C C 1049 0.4836 251 0.4411 798 0.4988 VSRhCV435733 253 0.4608 302 0.371 C C 676 0.496 250 0.4554 426 0.5233UCSFCCF hCV454333 127 0.2236 379 0.2367 C C 1621 0.7473 435 0.76581186 0.7408 VSR hCV454333 100 0.1815 174 0.2159 C C 1058 0.7797 4460.8094 612 0.7593 UCSFCCF hCV540056 30 0.0527 129 0.0806 C C 20090.9258 538 0.9455 1471 0.9188 VSR hCV540056 26 0.0474 64 0.0787 C C1272 0.9339 523 0.9526 749 0.9213 UCSFCCF hCV7917138 197 0.3462 4750.2972 A A 1401 0.6465 343 0.6028 1058 0.6621 VSR hCV7917138 1730.3168 259 0.319 A A 873 0.6429 344 0.63 529 0.6515 UCSFCCFhCV8147903 175 0.3076 560 0.3498 G G 1317 0.6069 369 0.6485 9480.5921 VSR hCV8147903 172 0.3156 273 0.3358 G G 847 0.6237 3520.6459 495 0.6089 UCSFCCF hCV8754449 203 0.3568 649 0.4056 C C 11800.544 329 0.5782 851 0.5319 VSR hCV8754449 188 0.3431 272 0.3346 CC 828 0.6084 345 0.6296 483 0.5941 UCSFCCF hCV8820007 207 0.3644562 0.351 T T 1257 0.5795 332 0.5845 925 0.5778 VSR hCV8820007 1780.3248 285 0.3523 T T 800 0.5895 342 0.6241 458 0.5661 UCSFCCFhCV8942032 151 0.2654 367 0.2294 G G 1605 0.74 404 0.71 1201 0.7506VSR hCV8942032 133 0.2427 165 0,2025 G G 1031 0,7564 399 0,7281 6320,7755

TABLE-US-00019 TABELLE 19C HW (Kontrolle) allelicAsc allelicAscallelicAsc DomGenotAsc DomGenotAsc RecGenotAsc RecGenotAscAddGenotAsc AddGenotAsc OR.Hom. Studie Marker RS ​​Pexact Chi2 Pasympexact Chi2 Pasym Chi2 Pasym Chi2 Pasym Or.HOM 95CI.L UCSFHCV1053082 RS544115 9.57E-02 1,8813 1,572 1,84e-012. CCF VSRHCV1053082 RS544115 3.79E-01 5.9535 1,47E-02 1,54E-02 5.12722.36E-02 2,0145 1,56E-01 5.7805 1,802 0,9971,91,901,901,901.91.331 uCSF101.9.91.3.331 uCSFSF-01. 99E-02 0.1832 6.69E-01 1.7897 1.81E-01 1.04 0.6394 CCF VSRhCV1116757 rs3794971 7.21E-01 4.3026 0.0381 0.0407 3.8015 0.05121.3504 0.2450 4.246 0.0393 0.6353 0.3249 UCSF hCV11425801 rs38059535.81E-01 3.7417 5.31E-02 5.74E-02 2.959 8.54E-02 2.008 1.56E-013.6971 5.45E-02 1.3012 0.993 CCF VSR hCV11425801 rs3805953 8.33E-013.1552 7.57E-02 7.83E-02 1.9414 1.64E-01 2.2927 1.30E-01 3.16957.50E-02 1.3231 0.9724 UCSF hCV11425842 rs10948059 5.15E-01 2.65671.03E-01 1.04E-01 0.6196 4.31E-01 3.6571 5.58E-02 2.6452 1.04E-010.7846 0.5948 CCF VSR hCV11425842 rs10948059 5.74E-01 2.74919.73E-02 9.99E-02 1.9136 1.67 E-01 1.8051 1.79E-01 2.8113 9.36E-020.7654 0.5589 UCSF hCV11548152 rs11580249 8.49E-01 5.1795 2.29E-022.49E-02 5.9849 1.44E-02 0.1844 6.68E-01 5.2806 2.16E-02 1.23360.6694 CCF VSR hCV11548152 rs11580249 7.72E-01 3.669 5.54E-025.68E-02 3.1002 7.83E-02 1.3657 2.43E-01 3.6121 5.74E-02 1.57440.7942 UCSF hCV11738775 rs6754561 2.44E-01 4.5652 3.26E-02 3.52E-021.902 1.68E- 01 5.5721 1.82E-02 4.7722 2.89E-02 0.664 0.4783 CCF VSRhCV11738775 rs6754561 1.22E-01 4.301 3.81E-02 3.97E-02 1.2232.69E-01 6.1599 1.31E-02 4.1958 4.05E-02 0.6577 0.4674 UCSFhCV11758801 rs11841997 3.28E -01 3.8274 5.04E-02 5.52E-02 3.3076.90E-02 1.1756 2.78E-01 3.7093 5.41E-02 2.8821 0.405 CCF VSRhCV11758801 rs11841997 1.00E+00 3.9487 4.69E-02 5.84E-02 3.1337.67E-02 2.968 8.49E-02 3.892 4.85E-02 UCSF hCV11861255 rs5294072.74E-03 0.9704 3.25E-01 3.32E-01 0.0198 8.87E-01 4.4502 3.49E-020.9239 3.36E-01 0.6456 0.4172 CCF VSR hCV11861255 rs529407 1.76E-015.8243 1.58 E-02 1,62E-02 4.2314 3.97E-02 3.2296 7.23E-02 5.59051.81E-02 0,6196 0,3928 UCSF HCV12071939 RS1950943 9.42113131313131313131313131313131313131313131313131. 3.7053 5.42E-020.5079 0.2887 CCF VSR hCV12071939 rs1950943 9.15E-01 4.558 3.28E-023.42E-02 6.5586 1.04E-02 0.0106 9.15E-01 4.3724 3.65E-02 0.92710.5472 UCSF hCV1209800 rs35067690 1.00E+00 6.8747 8.74E -03 9.31E-036.4426 1.11E-02 1.4208 2.33E-01 6.9406 8.43E-03 0 CCF VSRhCV1209800 rs35067690 9.86E-02 4.5292 3.33E-02 3.77E-02 3.53556.01E-02 2.7122 9.96E-02 4.3855 3.62E -02 0 UCSF HCV1262973 RS2296533.31E-02 2.8401 9.19E-02 9.99E-02 1,9058 1,67E-01 2,0833 1,49E-012.29.03.295-01 1,77717 0,8307 CCF VSR. 02 6.5217 1.07E-02 0,4932 4,82E-01 4,65563.10E-02 0,7375 0,2545 UCSF HCV1348610 RS3739636 3,922,9212,922,102,102,102,102. CCF VSR hCV1348610 rs3739636 3.18E-01 3.6947 5.46E-025.73E-02 0.7744 3.79E-01 5.1413 2.34E-02 3.4678 6.26E-02 1.35551.0033 UCSF hCV1408483 rs17070848 7.80E-01 3.5792 5.85E-02 6.33E-024.9851 2.56E-02 0.0452 8.31E-01 3.6225 5.70E-02 1.0089 0.5449 CCFVSR hCV1408483 rs17070848 7.23E-01 4.0633 4.38E-02 4.77E-02 4.58743.22E-02 0.306 5.80E-01 4.0784 4.34E-02 1.2739 0.7171 UCSFhCV1452085 RS12223005 2.06E-01 1,6991 1,92E-01 2,01E-01 0,80113.71E-01 3.5259 6,04E-02 1,6769 1,95E-01 0,3303 0.0993 CCF VSRHCV1452085 RS1222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222222. -02 0,005 9.36E-01 3.431 6.40E-02 0,98 0,3703 UCSF HCV15851766RS222995 1,00E+00 4,7105 3.00E. 3,80912,80912,80912,80912,83E-02 CCF. -022.19E-02 5.5693 1.83E-02 5.5693 1.83E-02 UCSF HCV15857769 RS29249144.0115,01 3.0613 8,022,95,95,5,842 1.74e-01 2,3797 1.2322,842 1,74e-01 2,3797 1.2312,842 1,74e-01 2,3797 1.2312,842 1,742 1.74e-01 2,3797 1.2312,842,42,42 1.74e-01 2.3797 1.2312. rs29249148.13E-02 1.5429 2.14E-01 2.27E-01 0.2055 6.50E-01 4.5155 3.36E-021.5844 2.08E-01 1.5203 ​​1.0085 UCSF hCV15879601 rs2275769 8.69E-015.0195 2.51E-02 2.73E-02 4.7726 2.89E-02 0,7923 3,73E-01 5.0122,52E-02 0,4899 0,1082 CCF VSR HCV15879601 RS2275769 4,68E-022.5557 1.10e-01,975,301,3012 2,54e-01 5.4341,41,97.2,52 2,54e-01 5.4341,41,41,4341 1,97e-02. 01 4.3847 3.63E-023.81E-02 4.3936 3.61E-02 0.7309 3.93E-01 4.3449 3.71E-02 1.33210.7957 CCF VSR hCV16134786 rs2857595 1.14E-01 4.6354 3.13E-023.54E-02 5.9503 1.47E-02 0.0339 8.53 E-01 4,5185 3.35E-02 1.15810.6598 UCSF HCV1619596 RS1048621 4,21E-02 2,9988 8,333E-02 8,94E-0119.9.809,809 3.68E-011212121212. 5.0407 2,48E-02 2.67E-02 5.62191.77E-02 0,6652 4.15E-01 5.0508 2.46e-02 1.3369 0.8468 UCSFHCV16336 RS36277 3.82e-01 3.2376 3.1329 7.1329 7,67,4777. 3.0502 8.07E-02 0.7861 0.3365 CCF VSR hCV16336rs362277 7.41E-01 7.1876 7.34E-03 8.10E-03 5.5815 1.82E-02 4.56463.26E-02 7.2354 7.15E-03 0.214 0.048 UCSF hCV1723718 rs124818055.13E-01 3.8839 4.88E -02 5.19E-02 2.9562 8.56E-02 2.1993 1.38E-013.9421 4.71E-02 1.3593 0.9742 CCF VSR hCV1723718 rs124818059.24E-02 3.6917 5.47E-02 5.72E-02 4.3047 3.80E-02 0.444 5.05E-013.5428 5.98 E-02 1.2553 0.8516 UCSF hCV1958451 rs2985822 9.48E-014.1971 4.05E-02 4.14E-02 3.9539 4.68E-02 1.2038 2.73E-01 4.1744.10E-02 0.7389 0.4833 CCF VSR hCV1958451 rs2985822 2.40E-01 4.56043.27E-02 3.35E-02 2.6009 1.07E-01 4.153 4.16E-02 4.4562 3.48E-020.5908 0.3682 UCSF hCV2121658 rs1187332 3.41E-02 4.3002 3.81E-024.02E-02 5.1465 2.33E-02 0.0001 9.61E-01 4.49 3.41E-02 0.93730.3672 CCF VSR hCV2121658 rs1187332 7.57E-01 2.4843 1.15E-011.20E-01 1.3947 2.38E-01 4.1148 4.25E-02 2.5241 1.12E-01 0.29030.0835 UCSF hCV2358247 rs415989 3.03E-02 2.7624 9.65E-02 9.75 E-024.0243 4.48E-02 1.0344 3.09E-01 2.6772 1.02E-01 0,4876 0.1087 CCFVSR HCV2358247 RS415989 4.00E-01 7,9749 4,74e-03 6.00 6.00.03 6.00,00-0. UCSF HCV2390937 RS7397198.61E-01 3.1417 7.63E-02 8.49E-02 2,9448 8.62E.02 0,5694 4.50e-013.1343 7.5,5,5,5,5,5.2,52,52.2.2. E-02 0.0605 8.05E-01 5.29772.14E-02 0,7047 0,0637 UCSF HCV25473186 RS2880415 2,28E-01 4.38413.63912,812,322,302 4.3063 1,202,202,202,202,202,202,202,202,202,202,202,202. RS2880415 8.85E-01 7.48636.22E-03 6.51E-03 8.5136 3.52E-03 2,1489 1.43E-01 7.7174 5.47E-031.5155 1,992 UCSF HCV255596936 RS696111111111111111111129.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.29.2. 0,7923 3,73E-01 2,2646 1,32E-01 0,53030.1171 CCF VSR HCV25596936 RS6967117 1,24E.01 8,1435 4,322e-0323232323233.28e. 6.23E-01 1.2345 2.67E-01 2.80E-010.9387 3.33E-01 2.82 9.31E-02 1.2457 2.64E-01 CCF VSR hCV25615822NONE 1.00E+00 4.1369 4.20E-02 4.98E-02 4.2329 3.96E-02 0.07727. 81E-01 4.1629 4.13E-02 1.5282 0.0954 UCSF hCV25983294 rs37397093.85E-01 4.819 2.81E-02 3.07E-02 6.2248 1.26E-02 0.0285 8.65E-014.8577 2.75E-02 0.8777 0.515 CCF VSR hCV25983294 rs3739709 3.44E-014.3198 3.77E-02 3.98E-02 4.5466 3.30E-02 0.5404 4.62E-01 4.12494.23E-02 0.7614 0.4492 UCSF hCV2637554 rs3205421 3.62E-01 4.9742.57E-02 2.85E-02 2.2274 1.36E-01 6.0734 1.37E- 02 5.0067 2.52E-021.5451 1.1091 CCF VSR hCV2637554 rs3205421 3.99E-01 4.3776 3.64E-023.80E-02 3.793 5.15E-02 1.707 1.91E-01 4.2587 3.90E-02 1.38270.9553 UCSF hCV26478797 rs2015018 2.31E-02 3.2424 7.18 E-02 7.43E-024.5232 3,34E-02 0,0466 8.29E-01 3.3871 6,57E-02 0,8731 0,5698 CCFVSR HCV26478797 RS2015018 4,32E21,92,98 8.1212.98 8.12e- 8.12e-02. 8.09E-02 0.5897 0.3705 UCSFhCV26881276 rs2344829 7.67E-02 1.6418 2.00E-01 2.12E-01 2.76949.61E-02 0.0052 9.35E-01 1.5938 2.07E-01 1.1057 0.8058 CCF VSRhCV26881276 rs2344829 3.46E-01 5.9931 1.44E-02 1.60E-02 3.90194.82E-02 3.9451 4.70E-02 5.7504 1.65E-02 1.4926 1.0675 UCSFhCV27077072 rs8060368 6.95E-01 2.5397 1.11E-01 1.14E-01 3.685.51E-02 0.1126 7.37E-01 2.5305 1.12E- 01 0.8622 0.6234 CCF VSRhCV27077072 rs8060368 1.00E+00 3.1185 7.74E-02 8.22E-02 2.43621.19E-01 1.6353 2.01E-01 3.0097 7.74E-02 0.7411 0.5123 UCSFhCV27473671 rs3750465 9.51E-01 3.3546 6.70E-02 6.87E- 02 3.12347.72E-02 1.1247 2,89E-01 3.3751 6.62E-02 1,2873 0,9103 CCF VSRHCV27473671 RS3750465 9.27e-01 5,215 2,24,22 3.22. 1.0529 UCSFhCV27494483 rs3748743 2.72E-02 3.9163 4.78E-02 5.21E-02 3.78635.17E-02 0.3155 5.74E-01 3.7048 5.43E-02 1.4521 0.4354 CCF VSRhCV27494483 rs3748743 1.00E+00 4.7395 2.95E-02 3.30E-02 4.43023 .53E-02 0.865 3.52E-01 4.7363 2.95E-02 3.0675 0.2774 UCSFhCV27504565 rs3219489 4.17E-02 2.6893 1.01E-01 1.07E-01 5.37322.04E-02 0.3093 5.78E-01 2.7588 9.67E-02 0.9997 0.6757 CCF VSRhCV27504565 RS3219489 6.37E-02 6.3249 1,19E-02 1,22E-02 2.02981.54E-01 12.829 3,41E-04 6.2596 1,24E-02 0.3347 0,1799 UCSFHCV27517517511436 RS375014-22.-011,7517511436 RS3750145-22. 01 8.5394 3.48E-03 4.7125 2.99E-02 0.2692 0.1066 CCF VSRhCV27511436 rs3750145 4.85E-01 3.434 6.39E-02 7.13E-02 3.20927.32E-02 0.7905 3.74E-01 3.3344 6.78E-02 0.7158 0.3861 UCSFhCV2769503 rs4787956 9.55E -01 6.0949 1.36E-02 1.50E-02 6.74839.38E-03 1.3572 2.44E-01 6.1512 1.31E-02 1.3545 0.9929 CCF VSRhCV2769503 rs4787956 5.09E-01 9.7933 1.75E-03 1.95E-03 11.8215.86E-04 1.4515 2.28E-01 9.8523 1.70E-03 1.5046 1.0422 UCSFhCV27892569 rs4903741 3.97E-01 2.7801 9.54E-02 9.57E-02 2.26051.33E-01 1.3606 2.43E-01 2.8366 9.21E-02 1.3419 0.8828 CCF VSRhCV27892569 rs4903741 4.12E-03 1.8263 1.77E-01 1.79E-01 3.34436.74E-02 0.1334 7.15E-01 1.7125 1.91E-01 1.005 0.6399 UCSFhCV28036404 rs4812768 3.21E-02 1.2024 2.73E-01 2.82E-01 0.15446.94E-01 4.3224 3.76E- 02 1.1665 2.80E-01 0.5774 0.3379 CCF VSRhCV28036404 rs4812768 1.28E-01 5.3749 2.04E-02 2.13E-02 5.67161.72E-02 0.7758 3.78E-01 5.6186 1.78E-02 0.6777 0.3437 UCSFhCV2851380 rs12445805 2.89E-02 4.529 3.33E -02 3.60E-02 3.1857.43E-02 3.1432 7.62E-02 4.3423 3.72E-02 0.3863 0.1348 CCF VSRhCV2851380 rs12445805 7.53E-01 3.7815 5.18E-02 5.25E-02 3.7765.20E-02 0.433 5.11E-01 3.7227 5.37E-02 0.6993 0.28 UCSFhCV29401764 rs7793552 1.57E-01 2.3924 1.22E-01 1.30E-01 5.73411.66E-02 0.3114 5.77E-01 2.411 1.20E-01 0.956 0.6916 CCF VSRhCV29401764 rs7793552 9.39E-01 5.9882 1.44E-02 1,46E-02 6.96278.32E-03 1,0087 3.15E-01 5.8764 1,53E-02 0,7291 0,5084 UCSF CCFHCV29537898 RS6073805 6.111,10,10.10.10.10.10.2.2 4.102 4.102,2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2. -02 2.2489 0.9794 VSRhCV29537898 rs6073804 1.14E-01 3.821 5.06E-02 5.96E-02 2.79199.47E-02 4.704 3.01E-02 3.9237 4.76E-02 7.7902 0.9071 UCSFhCV29539757 rs10110659 1.46E-01 5.5454 1.85E-02 1.97E- 02 8.61513.33E-03 0,0484 8.25E-01 5.6203 1,78E-02 0,837 0,5894 CCF VSRHCV29539757 RS10110659 6.39E.302 6.60E-03,3.3.33.3.3.3.3.3.3.03.03.03.03 6,86248.802. 0.4404 UCSFhCV302629 rs9284183 4.55E-01 6.072 1.37E-02 1.46E-02 1.55522.12E-01 11.66 6.39E-04 5.9952 1.43E-02 1.7394 1.2525 CCF VSRhCV302629 rs9284183 4.28E-01 1.2194 2.69E-01 2.76E-01 0.06168 .04e-01 4.4477 3.49e-02 1.2037 2,73E-01 1.4837 0,993 UCSFHCV30308202 RS9482985 2,71E215 3,3551 6.702,9222,5032,5010172.2012,2012.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2.2. RS9482985 4.66E-01 4.0472 4,42E-02 4,58E-02 4.88222.71E-02 0,1543 6,94E-01 3.8598 4,95E-02 0,8294 0,49555.01 4.111733333333333333333. 02 1.6062 2.05E-01 4.1327 4.21E-02 1.5351 0.8458 CCF VSRhCV3054550 rs1559599 3.36E-01 2.2114 1.37E-01 1.50E-01 3.08047.92E-02 0.0322 8.57E-01 2.193 1.39E-01 1.0019 0.5064 UCSFhCV3082219 rs1884833 1.00E +00 2.8129 9.35E-02 9,54E-02 3.40246.51E-02 0,0012 9,55E-01 2,8432 9.18E-02 1.0336 0,434 CCF VSRHCV308219 RS18888833 1,00 1,00 1,00 1,00 1,00 1,00 1,00 1,00 1,33. 2,41E-01 6.4841 1.09E-02 1,7858 0,7515 UCSFHCV31137507 RS766068 4,76E-01 3,1157 7,75E-02 7,98E-02 3.1477.61E.02 0,7113 3.99e-01 3.0745.

CCF VSR hCV31137507 rs7660668 1.00E+00 2.7419 9.77E-02 1.04E-012.2328 1.35E-01 1.279 2.58E-01 2.7397 9.79E-02 1.3436 0.8834 UCSFhCV31227848 rs11809423 4.36E-01 7.9108 4.91E-03 6.04E-03 8.48273. 59E-03 0.0031 9.45E-01 7.8545 5.07E-03 0.9777 0.1015 CCF VSRhCV31227848 rs11809423 1.00E+00 8.9352 2.80E-03 3.13E-03 9.27482.32E-03 0.0792 7.78E-01 9.0359 2.65E-03 1.5638 0.0976 UCSFhCV31573621 rs11079818 4,66E-01 3.8384 5.01E-02 5.05E-02 3.28187.01E-02 1,663 1,97E-01 3.9118 4,79E-02 0.7276 0,4915 CCF VSRHCV31573621 RS11079818 5.47123.4711111079818 5.47123. 01 4.4251 3.54E-02 2.8097 9.37E-02 0.6118 0.3888 UCSFhCV31705214 rs12804599 8.84E-01 4.2814 3.85E-02 3.94E-02 2.08821.48E-01 5.2885 2.15E-02 4.2313 3.97E-02 1.6316 1.0929 CCF VSRhCV31705214 rs12804599 1.58E -01 5.9636 1,46E-02 1,60E-02 7.08197.79E-03 0,3533 5.52E-01 5.8152 1,59E-02 1,2917 0,7918 UCSFHCV32160712 RS11079160 7.14.140 7.14.14.14.14.14. E-01 5.8369 1.57E-02 1.3018 0.7291 CCF VSRhCV32160712 rs11079160 8.90E-01 3.3547 6.70E-02 6.90E-02 2.14311.43E-01 3.0135 8.26E-02 3.3083 6.89E-02 1.8402 0.9516 UCSFhCV435733 rs10276935 5.73E-02 4.9763 2,57E-02 2.77E-02 5.58111.82E-02 0,833 3,61E-01 4.7987 2.85e-02 1,2836 0.9311 CCF VSRHCV435733 RS10276935 4.96E-03.3.658 1.988 1. 01 1.6077 2.05E-01 0.9114 0.6167 UCSFhCV454333 rs10916581 4.08E-01 2.4396 1.18E-01 1.31E-01 1.39422.38E-01 3.1385 7.65E-02 2.4218 1.20E-01 0.4544 0.1901 CCF VSRhCV454333 rs10916581 9.04E-02 6.7538 9.35E -03 9.52E-03 4.78792.87E-02 4.4834 3.42E-02 6.4961 1.08E-02 0.343 0.1278 UCSFhCV540056 rs346802 5.17E-01 3.8011 5.12E-02 5.63E-02 4.36273.67E-02 0.5851 4.44E-01 3.8532 4.97 E-02 2,7342 0,1707 CCF VSRHCV540056 RS346802 6.30E-01 5.0445 2,47E-02 2,84E-02 5.223 2,23E 2,23E-025.223 2,23E-02. 1.0708 3.01E-01 6.2249 1.26E-02 1.37620.8737 CCF VSR hCV7917138 rs9822460 3.02E-01 2.0808 1.49E-011.55E-01 0.6537 4.19E-01 4.8306 2.80E-02 2.0835 1.49E-01 1.85821.0639 UCSF hCV8147903 rs680014 4.01e-01 6.0117 1.42E-02 1.45E-025,5927 1,80E-02 1,6351 2.01E-01 5,8658 1,54E-02 0,6906 0,437 CCFVSR HCV8147903 RS680014 3.633,633,633.633.633. 1.996 1.58E-01 2.7684 9.61E-02 0.6562 0.3841 UCSFhCV8754449 rs781226 1.09E-01 2.0954 1.48E-01 1.56E-01 3.63235.67E-02 0.0453 8.31E-01 2.1424 1.43E-01 0.9571 0.6428 CCF VSRhCV8754449 rs781226 2.62E- 02 5.9675 1.46E-02 1.46E-02 1.72821.89E-01 12.467 4,14E-04 5.8303 1,58E-02 0.3621 0.2018 UCSFHCV8820007 RS938390 2,66E-02 0,8237 3.64011,76E-01 0,82 0,8237 3.64013.011,02 0,8237 3.6401901,02 0,82 02 0,8237 3.6401901,01 0,02 0,8237 3.640007. -02 0,7944 3,73E-01 0,7088 0,4627 CCF VSRHCV8820007 RS938390 2,72E-02 7,008 8,11E11E-03 8,99E-03 4,53493.32,9999.00.00e-02 6,5843 1,03.299999,00-02 6,5843 1.03E-029999. E-02 6.61E-02 3.59715.79E-02 0,4287 5.13E-01 3.5083 6.11e-02 1,3006 0,6871 CCF VSRHCV8942032 RS1264352 7.412 4,1819 4.09E-02 4,02 4.022,59E-022,02 4.02 4.02, 02 4,02, 02 4,02 4,02, 02, 02, 02, 02, 02, 02 4,02 4,02 4,02, 02, 02, 02, 02 4,02 4.49E-02,-02,5819E-022. 3,947 4,70E-02 1,408 0,7097 G OR.Hom.OR.Het. ODER.Het. G Statistik std.ln OR99CI. ODER99CI. ODER95CI. OR95CI.Study Marker 95CI.U OR.Het 95CI.L 95CI.U Statistic pAsym OR (OR) LU L U UCSF hCV1053082 0.9814 0.9838 0.7998 1.2101 4.5688 1.02E-010.8873 0.0872 0.7088 1.1108 0.7479 1.0527 CCF VSR hCV1053082 1.10650.7867 0.617 1.003 5.8263 5.43 E-02 0.7782 0.103 0.5969 1.0145 0.6360.9521 UCSF hCV1116757 1.6918 0.8094 0.654 1.0017 3.9968 1.36E-010.8876 0.0888 0.7061 1.1157 0.7458 1.0563 CCF VSR hCV1116757 1.24220.8069 0.63 1.0336 4.2673 1.18E-01 0.8016 0.1068 0.6088 1.05530.6502 0.9881 UCSF hCV11425801 1.7051 1.1705 0.9281 1.4761 3.76021.53E-01 1.1429 0.0691 0.9566 1.3654 0.9982 1.3085 CCF VSRhCV11425801 1.8004 1.1361 0.873 1.4785 3.1782 2.04E-01 1.14910.0783 0.9393 1.4059 0.9857 1.3397 UCSF hCV11425842 1.035 0.98260.7858 1.2287 3.7537 1.53E-01 0.8932 0.0693 0.7471 1.0678 0.77971.0232 CCF VSR hCV11425842 1.0482 0.8793 0.6833 1.1315 2.81212.45E-01 0.878 0.0785 0.7173 1.0747 0.7528 1.024 UCSF hCV115481522.273 1.2948 1.0496 1.5973 5.8774 5.29E-02 1.2289 0.0907 0.97291.5522 1.0288 1.4679 CCF VSR hCV11548152 3.1213 1.2111 0.94471.5526 3.5834 1.67E-01 1.2289 0.1077 0.9311 1.622 0.995 1.5179 UCSFhCV11738775 0.9219 0.9308 0.759 1.1414 6.296 4.29E-02 0.8572 0.07220.7118 1.0323 0.7442 0.9874 CCF VSR hCV11738775 0.9255 0.96630.7646 1.2211 6.3672 4.14E-02 0.8453 0.0811 0.686 1.0416 0.72110.9909 UCSF hCV11758801 20.513 1.389 0.9403 2.0517 3.3582 1.87E-011.4427 0.1883 0.8882 2.3432 0.9974 2.0867 CCF VSR hCV117588011.4137 0.906 2.2057 1.5378 0.2181 0.8769 2.6969 1.0029 2.3579 UCSFhCV11861255 0.9991 1.0594 0.8647 1.2979 5.0497 8.01E-02 0.92260.0817 0.7474 1.1389 0.786 1.083 CCF VSR hCV11861255 0.9773 0.83060.6583 1.0482 5.7533 5.63E -02 0.8012 0.0919 0.6322 1.0153 0.6690.9594 UCSF hCV12071939 0.8937 0.9289 0.7575 1.1392 6.4 4.08E-020.8483 0.0862 0.6794 1.0592 0.7164 1.0044 CCF VSR hCV120719391.5708 0.715 0.561 0.9113 7.4172 2.45E-02 0.8078 0.1001 0.62431.0453 0.664 0.9829 UCSF hCV1209800 0.6399 0.4432 0.9239 0.62150.183 0.388 0.9957 0.4342 0.8896 CCF VSR hCV1209800 0.7072 0.4621.0826 0.6421 0.2097 0.3741 1.012 0.4257 0.9685 UCSF hCV12629733.7788 1.1497 0.8834 1.4962 2.9516 2.29E-01 1.2188 0.1176 0.90041.6498 0.968 1.5346 CCF VSR hCV1262973 2.1377 1.4832 1.1222 1.96027.9944 1.84E -02 1.3186 0.1276 0.9493 1.8315 1.0269 1.6932 UCSFhCV1348610 1.7582 1.2518 0.9947 1.5753 5.2978 7.07E-02 1.162 0.06920.9724 1.3886 1.0147 1.3307 CCF VSR hCV1348610 1.8313 1.0083 0.78111.3017 5.0887 7.85E-02 1.1644 0.0792 0.9495 1.4278 0.997 1.3598UCSF hCV1408483 1.8681 1.286 1.0429 1.5858 5.472 6.48E-02 1.18660.0905 0.9398 1.4982 0.9937 1.417 CCF VSR hCV1408483 2.263 1.28071.0131 1.619 4.5423 1.03E-01 1.2184 0.0981 0.9464 1.5685 1.00531.4766 UCSF hCV1452085 1.0993 0.9415 0.7362 1.2039 4.3881 1.11E-010.8613 0.1146 0.6411 1.1571 0.688 1.0783 CCF VSR hCV1452085 2.59370.7304 0.5467 0.9759 4.5378 1.03E-01 0.7814 0.132 0.5562 1.09780.6033 1.0121 UCSF hCV15851766 0.5279 0.2956 0.9429 0.5338 0.29380.2504 1.1379 0.3001 0.9495 CCF VSR hCV15851766 0.4941 0.27210.8972 0.5012 0.3016 0.2305 1.0901 0.2775 0.9053 UCSF hCV158577691.8396 1.0992 0.8971 1.3468 3.1352 2.09E-01 1.1387 0.0743 0.94041.3788 0.9845 1.3172 CCF VSR hCV15857769 2.2918 0.9801 0.781 1.234.4526 1.08E-01 1.1125 0.0859 0.8918 1.388 0.9402 1.3165 UCSFhCV15879601 2.2181 0.7379 0.5516 0.9872 5.1115 7.76E-02 0.73290.1392 0.5121 1.0489 0.558 0.9628 CCF VSR hCV15879601 0.8893 0.63041.2545 0.7676 0.1658 0.5008 1.1767 0.5546 1.0624 UCSF hCV161347862.23 1.2299 0.9978 1.5159 4.4069 1.10E-01 1.2019 0.0879 0.95841.5073 1.0117 1.4278 CCF VSR hCV16134786 2.0327 1.3513 1.06581.7133 6.1591 4.60E-02 1.2376 0.0991 0.9587 1.5977 1.0191 1.5031UCSF hCV1619596 1.7527 1.1655 0.9517 1.4273 2.9745 2.26E-01 1.1410.0762 0.9377 1.3884 0.9827 1.3248 CCF VSR hCV1619596 2.1107 1.29591.032 1.6274 5.6095 6.05E-02 1.2231 0.0898 0.9706 1.5413 1.02581.4584 UCSF hCV16336 1.8365 0.7982 0.6189 1.0296 3.2722 1.95E-010.8148 0.1159 0.6045 1.0982 0.6492 1.0226 CCF VSR hCV16336 0.95280.7564 0.5717 1.0007 9.0123 1.10E-02 0.7053 0.1307 0.5037 0.98760.5459 0.9113 UCSF hCV1723718 1.8965 1.1481 0.9381 1.4051 3.92091.41E-01 1.1566 0.0739 0.9562 1.399 1.0007 1.3368 CCF VSRhCV1723718 1.8502 1.2585 1.0007 1.5826 4.2931 1.17E- 01 1.1795 0.0860.9452 1.4719 0.9966 1.396 UCSF hCV1958451 1.1295 0.835 0.68121.0236 4.2666 1.18E-01 0.8459 0.0818 0.6853 1.0442 0.7206 0.9929CCF VSR hCV1958451 0.948 0.8855 0.7035 1.1145 5.3527 6.88E-020.8225 0.0916 0.6496 1.0413 0.6873 0.9842 UCSF hCV2121658 2.39220.7548 0.594 0.959 5.3775 6.80E-02 0.7964 0.11 0.5999 1.0572 0.6420.9879 CCF VSR hCV2121658 1.009 0.9012 0.6911 1.1752 5.14337.64E-02 0.8253 0.122 0.6028 1.1299 0.6498 1.0481 UCSF hCV23582472.1862 1.3805 1.0441 1.8253 5.9832 5.02E-02 1.2462 0.1327 0.88551.754 0.9609 1.6163 CCF VSR hCV2358247 1.4217 1.0009 2.0194 1.60230.1682 1.0388 2.4713 1.1522 2.2281 UCSF hCV2390937 2.4919 0.78750.5878 1.0551 3.1758 2.04E-01 0.7807 0.14 0.5444 1.1196 0.59341.0272 CCF VSR hCV2390937 7.7934 0.6756 0.4839 0.9432 5.08427.87E-02 0.6946 0.1622 0.4575 1.0547 0.5055 0.9545 UCSF hCV254731861.7391 1.3253 1.0508 1.6714 6.4292 4.02E-02 1.1555 0.0691 0.96721.3806 1.0092 1.3231 CCF VSR hCV25473186 2.0894 1.3927 1.0842 1.7898.9051 1.16E-02 1.2404 0.0788 1.0126 1.5194 1.0629 1.4475 UCSFhCV25596936 2.401 1.3229 1.0074 1.7373 4.7012 9.53E-02 1.21670.1296 0.8714 1.6988 0.9438 1.5685 CCF VSR hCV25596936 3.86361.5454 1.1505 2.0759 8.4034 1.50E-02 1.4683 0.1352 1.0364 2.08021.1264 1.914 UCSF hCV25615822 1.1906 0.7838 1.8085 1.2567 0.20610.7391 2.1366 0.8391 1.882 CCF VSR hCV25615822 24.49 1.5004 1.01372.2209 3.6716 1.59E-01 1.4756 0.1923 0.8991 2.4217 1.0121 2.1512UCSF hCV25983294 1.4958 0.7576 0.6112 0.9391 6.5483 3.78E-02 0.8190.0911 0.6477 1.0355 0.6851 0.979 CCF VSR hCV25983294 1.2907 0.78230.615 0.9951 4.5596 1.02E-01 0.8136 0.0994 0.6298 1.0509 0.66960.9885 UCSF hCV2637554 2.1524 1.0848 0.8856 1.3286 6.3881 4.10E-021.1805 0.0745 0.9745 1.4301 1.0202 1.366 CCF VSR hCV2637554 2.00131.2089 0.96 1.5224 4.2815 1.18E-01 1.1927 0.0843 0.96 1.4817 1.01111.4068 UCSF hCV26478797 1.3378 0.8019 0.6554 0.9812 4.6697 9.68E-020.8647 0.0808 0.7022 1.0647 0.738 1.013 CCF VSR hCV26478797 0.93880. 9527 0.759 1.1958 5.2035 7.41E-02 0.8558 0.0894 0.6798 1.07730.7182 1.0196 UCSF hCV26881276 1.5173 1.198 0.9771 1.4689 3.02092.21E-01 1.098 0.073 0.9099 1.325 0.9517 1.2667 CCF VSR hCV268812762.087 1.1799 0.9339 1.4906 5.8097 5.48E-02 1.2202 0.0813 0.98961.5046 1.0404 1.4311 UCSF hCV27077072 1.1924 0.8208 0.67 1.00553.7499 1.53E-01 0.8885 0.0742 0.7339 1.0756 0.7682 1.0276 CCF VSRhCV27077072 1.072 0.8675 0.6898 1.0909 3.1285 2.09E-01 0.86340.0832 0.6968 1.0698 0.7334 1.0163 UCSF hCV27473671 1.8204 1.1690.9561 1.4294 3.4061 1.82E-01 1.147 0.0749 0.9457 1.3912 0.99041.3285 CCF VSR hCV27473671 2.4111 1.1634 0.926 1.4617 5.46616.50E-02 1.2203 0.0873 0.9746 1.5279 1.0284 1.448 UCSF hCV274944834.843 1.3469 0.9846 1.8425 3.554 1.69E-01 1.3368 0.1471 0.91511.9528 1.0019 1.7837 CCF VSR hCV27494483 33.922 1.4595 1.0039 2.1224.3507 1.14E-01 1.4827 0.1819 0.928 2.3692 1.038 2.118 UCSFhCV27504565 1.4792 0.7652 0.6244 0.9376 7.0162 3.00E-02 0.87740.0798 0.7144 1.0776 0.7504 1.0256 CCF VSR hCV27504565 0.62270.9523 0.7558 1.2 14.186 8.31E-04 0.7854 0.0962 0.6131 1.00620.6505 0.9483 UCSF hCV27511436 0,6798 0,9205 0,7397 1,1455 10,9554,18E-03 0,808 0,0983 0,6273 1,0408 0,6664 0,9797

CCF VSR hCV27511436 1.3267 0.8181 0.6402 1.0455 3.3771 1.85E-010.824 0.1046 0.6294 1.0787 0.6713 1.0114 UCSF hCV2769503 1.84791.2811 1.0429 1.5738 6.9114 3.16E-02 1.1938 0.0718 0.9922 1.43641.0371 1.3743 CCF VSR hCV2769503 2.1723 1.4676 1.1624 1.853 11.8642.65E-03 1.2971 0.0832 1.0469 1.607 1.1019 1.5268 UCSF hCV278925692.0397 1.135 0.9281 1.3881 2.8209 2.44E-01 1.1428 0.0801 0.92981.4046 0.9768 1.337 CCF VSR hCV27892569 1.5785 1.277 1.0116 1.6124.3397 1.14E-01 1.1328 0.0923 0.8931 1.4367 0.9453 1.3574 UCSFhCV28036404 0.9867 1.0241 0.8322 1.2603 4.7358 9.37E -02 0.90870.0873 0.7256 1.138 0.7657 1.0784 CCF VSR hCV28036404 1.3363 0.76340.6022 0.9676 5.7808 5.56E-02 0.7897 0.102 0.6072 1.0269 0.64660.9644 UCSF hCV2851380 1.1071 0.8341 0.6447 1.0792 5.5293 6.30E-020.776 0.1194 0.5705 1.0555 0.614 0.9807 CCF VSR hCV2851380 1.74680. 7736 0.5881 1.0174 3.8106 1.49E-01 0.7859 0.1241 0.5709 1.08190.6163 1.0023 UCSF hCV29401764 1.3214 0.7552 0.6161 0.9257 7.63432.20E-02 0.8911 0.0746 0.7354 1.0798 0.7699 1.0313 CCF VSRhCV29401764 1.0456 0.7503 0.5955 0.9452 6.9627 3.08E-02 0.81520.0835 0.6574 1.0109 0.6921 0.9603 UCSF CCF hCV29537898 5.16381.1836 0.9169 1.528 4.7982 9.08E-02 1.2655 0.1154 0.94 1.70361.0093 1.5867 VSR hCV29537898 66.901 1.23 0.9105 1.6616 6.31174.26E-02 1.3202 0.1425 0.9147 1.9055 0.9986 1.7455 UCSF hCV295397571.1886 0.7331 0.5986 0.8979 9.1106 1.05E-02 0.835 0.0766 0.68541.0172 0.7185 0.9703 CCF VSR hCV29539757 0.9579 0.772 0.6145 0.977.5953 2.24E-02 0.7947 0.0847 0.639 0.9884 0.6732 0.9381 UCSFhCV302629 2.4155 1.0205 0.8322 1.2514 10.938 4.22E-03 1.203 0.0750.9915 1.4595 1.0384 1.3936 CCF VSR hCV302629 2.2169 0.951 0.75591.1966 4.5406 1.03E-01 1.1006 0.0868 0.8801 1.3764 0.9284 1.3047UCSF hCV30308202 0.9273 0.9368 0.7625 1.151 5.6664 5.88E-02 0.85350.0865 0.683 1.0666 0.7204 1.0113 CCF VSR hCV30308202 1.3882 0.76420.6007 0.9721 4.9764 8.31E-02 0.8199 0.0988 0.6356 1.0575 0.67550.9951 UCSF hCV3054550 2.7861 1.1966 0.9619 1.4885 4.0552 1.32E-011.2126 0.0944 0.9507 1.5465 1.0076 1.4592 CCF VSR hCV3054550 1.98251.2611 0.9878 1.6101 3.4557 1.78E-01 1.1702 0.1058 0.8911 1.53680.9511 1.4399 UCSF hCV3082219 2.4615 1.2484 0.9921 1.5709 3.47411.76E-01 1.1914 0.1045 0.9102 1.5593 0.9707 1.4621 CCF VSRhCV3082219 4.2435 1.3479 1.0403 1.7465 6.3282 4.23E-02 1.34180.1161 0.995 1.8094 1.0688 1.6846 UCSF hCV31137507 1.798 1.17790.9633 1.4403 3.228 1.99E-01 1.1451 0.0768 0.9396 1.3957 0.98511.3312 CCF VSR hCV31137507 2.0436 1.1512 0.9168 1.4454 2.7242.56E- 01 1.1555 0.0873 0.9227 1.447 0.9737 1.3713 UCSF hCV312278489.4209 1.6482 1.1797 2.3027 7.5344 2.31E-02 1.5772 0.1633 1.03572.4017 1.1453 2.172 CCF VSR hCV31227848 25.061 1.7955 1.2252 2.63128.0196 1.81E-02 1.7397 0.1873 1.0738 2.8185 1.2051 2.5114 UCSFhCV31573621 1.0772 0.8585 0.7027 1.0489 3.9481 1.39E-01 0.85830.0781 0.7019 1.0494 0.7365 1.0001 CCF VSR hCV31573621 0.96270.9547 0.7597 1.1997 4.7176 9.45E-02 0.862 0.0889 0.6855 1.08390.7241 1.0261 UCSF hCV31705214 2.436 1.0888 0.8875 1.3357 5.62386.01E-02 1.1819 0.0808 0.9598 1.4553 1.0087 1.3847 CCF VSRhCV31705214 2.1071 1.36 1.0787 1.7147 7.0676 2.92E-02 1.2564 0.09360.9873 1.5989 1.0459 1.5094 UCSF hCV32160712 2.3242 1.2959 1.05271.5953 6.2375 4.42E-02 1.2364 0.0889 0.9833 1.5546 1.0387 1.4718CCF VSR hCV32160712 3.5585 1.141 0.8916 1.4602 4.0086 1.35E-011.2139 0.1059 0.924 1.5948 0.9863 1.4941 UCSF hCV435733 1.76951.2548 1.0241 1.5376 5.6002 6.08E-02 1.1784 0.0736 0.9748 1.42451.02 1.3613 CCF VSR hCV435733 1.347 1.4275 1.1357 1.7943 11.1193.85E-03 1.1155 0.0849 0.8964 1.388 0.9445 1.3173 UCSF hCV4543331.086 0.9136 0.7266 1.1488 4.1171 1.28E- 01 0.8504 0.1038 0.65091.1111 0.6938 1.0423 CCF VSR hCV454333 0.921 0.7886 0.5993 1.03787.7331 2.09E-02 0.7244 0.1244 0.5257 0.9981 0.5676 0.9245 UCSFhCV540056 43.792 0.6359 0.4223 0.9575 4.7627 9.24E-02 0.6783 0.20030.4049 1.1362 0.4581 1.0044 CCF VSR hCV540056 0.5818 0.3639 0.93020 .5919 0.2359 0.3224 1.0869 0.3728 0.9399 UCSF hCV7917138 2.16761.2793 1.0412 1.5718 6.4455 3.98E-02 1.2368 0.0842 0.9956 1.53641.0486 1.4587 CCF VSR hCV7917138 3.2454 1.0272 0.8116 1.3 4.7429.34E-02 1.1509 0.0975 0.8953 1.4796 0.9507 1.3933 UCSF hCV81479031.0914 0.8028 0.6521 0.9885 6.0203 4.93E-02 0.8113 0.0854 0.65121.0109 0.6863 0.9591 CCF VSR hCV8147903 1.1213 0.886 0.7007 1.12043.0613 2.16E-01 0.85 0.0968 0.6625 1.0905 0.7032 1.0275 UCSFhCV8754449 1.425 0.8091 0.6607 0.9907 4.2677 1.18E-01 0.8909 0.07980.7253 1.0943 0.7618 1.0418 CCF VSR hCV8754449 0.6495 0.9676 0.76761.2199 13.591 1.12E-03 0.7922 0.0955 0.6195 1.013 0.6571 0.9552UCSF hCV8820007 1.0857 1.0262 0.8379 1.2569 2.9617 2.27E-01 0.92890.0813 0.7535 1.1452 0.7922 1.0893 CCF VSR hCV8820007 0.9033 0.83640.662 1.0567 7.1036 2.87E-02 0.7818 0.0931 0.6152 0.9937 0.65150.9383 UCSF hCV8942032 2.4618 1.2231 0.9811 1.5249 3.5479 1.70E-011.1992 0.0965 0.9353 1.5375 0.9925 1.4488 CCF VSR hCV8942032 2.79311.2768 0.9839 1.6567 3.9974 1.36E-01 1.26 0.1132 0.9414 1.68651.0093 1.5729

TABLE-US-00020 TABLE 20 GENO- hCV # rs # Gene OUTCOME ADJUST MODETYPE hCV1958451 rs2985822 MIER1 EO_STK AGE MALE GEN GT DIAB HTNhCV1958451 rs2985822 MIER1 EO_STK AGE MALE DOM GT or GG DIAB HTNhCV1958451 rs2985822 MIER1 EO_STK GEN GT hCV1958451 rs2985822 MIER1EO_STK AGE MALE GEN GG DIAB HTN hCV1958451 rs2985822 MIER1 LACUNAR_GEN GT STK hCV27494483 rs3748743 SLC22A15 CE_STK GEN TC hCV27494483rs3748743 SLC22A15 CE_STK DOM TC or TT hCV27494483 rs3748743SLC22A15 CE_STK ADD T hCV27494483 rs3748743 SLC22A15 ISCHEMIC_ DOMTC or TT STK hCV27494483 rs3748743 SLC22A15 ISCHEMIC_ ADD T STKhCV27494483 rs3748743 SLC22A15 ISCHEMIC_ GEN TC STK hCV27504565rs3219489 MUTYH ATHERO_ AGE MALE GEN CG STK DIAB HTN hCV27504565rs3219489 MUTYH ATHERO_ AGE MALE DOM CG or CC STK DIAB HTNhCV27504565 rs3219489 MUTYH ATHERO_ AGE MALE GEN CC STK DIAB HTNhCV27504565 rs3219489 MUTYH ATHERO_ GEN CG STK hCV27504565rs3219489 MUTYH ATHERO_ DOM CG or CC STK hCV27504565 rs3219489MUTYH ATHERO_ GEN CC STK hCV27504565 rs3219489 MUTYH ISCHEMIC_ GENCG STK hCV27504565 rs3219489 MUTYH NOHD_STK GEN CG hCV27504565rs3219489 MUTYH NOHD_STK AGE MALE GEN CG DIAB HTN hCV27504565rs3219489 MUTYH NONCE_ AGE MALE GEN CG STK DIAB HTN hCV27504565rs3219489 MUTYH NONCE_ GEN CG STK hCV27504565 rs3219489 MUTYHRECURRENT_ AGE MALE GEN CG STK DIAB HTN hCV27504565 rs3219489 MUTYHRECURRENT_ AGE MALE DOM CG or CC STK DIAB HTN hCV8754449 rs781226TESK2 ATHERO_ AGE MALE GEN CT STK DIAB HTN hCV8754449 rs781226TESK2 ATHERO_ AGE MALE DOM CT or CC STK DIAB HTN hCV8754449rs781226 TESK2 ATHERO_ GEN CT STK hCV8754449 rs781226 TESK2 ATHERO_DOM CT or CC STK hCV8754449 rs781226 TESK2 ATHERO_ GEN CC STKhCV8754449 rs781226 TESK2 ATHERO_ AGE MALE GEN CC STK DIAB HTNhCV8754449 rs781226 TESK2 RECURRENT_ AGE MALE GEN CT STK DIAB HTNhCV8754449 rs781226 TESK2 RECURRENT_ AGE MALE DOM CT or CC STK DIABHTN hCV2091644 rs1010 VAMP8 CE_STK REC CC hCV8820007 rs938390ATHERO GEN TA STK hCV8820007 rs938390 ISCHEMIC_ GEN TA STKhCV8820007 rs938390 ISCHEMIC_ AGE MALE GEN TA STK DIAB HTNhCV8820007 rs938390 NOHD_STK GEN TA hCV8820007 rs938390 NOHD_STKAGE MALE GEN TA DIAB HTN hCV8820007 rs938390 NOHD_STK AGE MALE DOMTA or TT DIAB HTN hCV8820007 rs938390 NOHD_STK DOM TA or TThCV11354788 rs12644625 LOC729065 ATHERO_ AGE MALE ADD T STK DIABHTN hCV11354788 rs12644625 LOC729065 ATHERO_ AGE MALE DOM TC or TTSTK DIAB HTN hCV11354788 rs12644625 LOC729065 ATHERO_ AGE MALE GENTC STK DIAB HTN hCV11354788 rs12644625 LOC729065 ATHERO_ DOM TC orTT STK hCV11354788 rs12644625 LOC729065 ATHERO_ GEN TC STKhCV11354788 rs12644625 LOC729065 ATHERO_ ADD T STK hCV11354788rs12644625 LOC729065 CE_STK ADD T hCV11354788 rs12644625 LOC729065CE_STK DOM TC or TT hCV11354788 rs12644625 LOC729065 CE_STK AGEMALE ADD T DIAB HTN hCV11354788 rs12644625 LOC729065 CE_STK AGEMALE DOM TC or TT DIAB HTN hCV11354788 rs12644625 LOC729065 CE_STKGEN TC hCV11354788 rs12644625 LOC729065 CE_STK AGE MALE GEN TC DIABHTN hCV11354788 rs12644625 LOC729065 CE_STK GEN TT hCV11354788rs12644625 LOC729065 CE_STK REC TT hCV11354788 rs12644625 LOC729065CE_STK AGE MALE GEN TT DIAB HTN hCV11354788 rs12644625 LOC729065EO_STK AGE MALE ADD T DIAB HTN hCV11354788 rs12644625 LOC729065EO_STK DOM TC or TT hCV11354788 rs12644625 LOC729065 EO_STK ADD ThCV11354788 rs12644625 LOC729065 EO_STK AGE MALE DOM TC or TT DIABHTN hCV11354788 rs12644625 LOC729065 EO_STK GEN TC hCV11354788rs12644625 LOC729065 EO_STK AGE MALE GEN TC DIAB HTN hCV11354788rs12644625 LOC729065 ISCHEMIC_ DOM TC or TT STK hCV11354788rs12644625 LOC729065 ISCHEMIC_ ADD T STK hCV11354788 rs12644625LOC729065 ISCHEMIC_ GEN TC STK hCV11354788 rs12644625 LOC729065ISCHEMIC_ AGE MALE ADD T STK DIAB HTN hCV11354788 rs12644625LOC729065 ISCHEMIC_ AGE MALE DOM TC or TT STK DIAB HTN hCV11354788rs12644625 LOC729065 ISCHEMIC_ AGE MALE GEN TC STK DIAB HTNhCV11354788 rs12644625 LOC729065 NOHD_STK ADD T hCV11354788rs12644625 LOC729065 NOHD_STK DOM TC or TT hCV11354788 rs12644625LOC729065 NOHD_STK GEN TC hCV11354788 rs12644625 LOC729065 NOHD_STKAGE MALE ADD T DIAB HTN hCV11354788 rs12644625 LOC729065 NOHD_STKAGE MALE DOM TC or TT DIAB HTN hCV11354788 rs12644625 LOC729065NOHD_STK AGE MALE GEN TC DIAB HTN hCV11354788 rs12644625 LOC729065NONCE_ GEN TC STK hCV11354788 rs12644625 LOC729065 NONCE_ DOM TC orTT STK hCV11354788 rs12644625 LOC729065 NONCE_ AGE MALE DOM TC orTT STK DIAB HTN hCV11354788 rs12644625 LOC729065 RECURRENT_ AGEMALE GEN TC STK DIAB HTN hCV11354788 rs12644625 LOC729065RECURRENT_ AGE MALE DOM TC or TT STK DIAB HTN hCV11354788rs12644625 LOC729065 RECURRENT_ AGE MALE ADD T STK DIAB HTNhCV11354788 rs12644625 LOC729065 RECURRENT_ DOM TC or TT STKhCV11354788 rs12644625 LOC729065 RECURRENT_ GEN TC STK hCV11354788rs12644625 LOC729065 RECURRENT_ ADD T STK hCV16158671 rs2200733ATHERO_ AGE MALE ADD T STK DIAB HTN hCV16158671 rs2200733 ATHERO_AGE MALE DOM TC or TT STK DIAB HTN hCV16158671 rs2200733 ATHERO_DOM TC or TT STK hCV16158671 rs2200733 ATHERO_ ADD T STKhCV16158671 rs2200733 ATHERO_ GEN TC STK hCV16158671 rs2200733ATHERO_ AGE MALE GEN TC STK DIAB HTN hCV16158671 rs2200733 CE_STKADD T hCV16158671 rs2200733 CE_STK DOM TC or TT hCV16158671rs2200733 CE_STK GEN TC hCV16158671 rs2200733 CE_STK AGE MALE ADD TDIAB HTN hCV16158671 rs2200733 CE_STK AGE MALE DOM TC or TT DIABHTN hCV16158671 rs2200733 CE_STK AGE MALE GEN TC DIAB HTNhCV16158671 rs2200733 CE_STK GEN TT hCV16158671 rs2200733 CE_STKREC TT hCV16158671 rs2200733 CE_STK AGE MALE GEN TT DIAB HTNhCV16158671 rs2200733 EO_STK DOM TC or TT hCV16158671 rs2200733EO_STK ADD T hCV16158671 rs2200733 EO_STK AGE MALE ADD T DIAB HTNhCV16158671 rs2200733 EO_STK GEN TC hCV16158671 rs2200733 EO_STKAGE MALE DOM TC or TT DIAB HTN hCV16158671 rs2200733 EO_STK AGEMALE GEN TC DIAB HTN hCV16158671 rs2200733 ISCHEMIC_ DOM TC or TTSTK hCV16158671 rs2200733 ISCHEMIC_ ADD T STK hCV16158671 rs2200733ISCHEMIC_ GEN TC STK hCV16158671 rs2200733 ISCHEMIC_ AGE MALE ADD TSTK DIAB HTN hCV16158671 rs2200733 ISCHEMIC_ AGE MALE DOM TC or TTSTK DIAB HTN hCV16158671 rs2200733 ISCHEMIC_ AGE MALE GEN TC STKDIAB HTN hCV16158671 rs2200733 NOHD_STK ADD T hCV16158671 rs2200733NOHD_STK DOM TC or TT hCV16158671 rs2200733 NOHD_STK GEN TChCV16158671 rs2200733 NOHD_STK AGE MALE ADD T DIAB HTN hCV16158671rs2200733 NOHD_STK AGE MALE DOM TC or TT DIAB HTN hCV16158671rs2200733 NOHD_STK AGE MALE GEN TC DIAB HTN hCV16158671 rs2200733NOHD_STK AGE MALE GEN TT DIAB HTN hCV16158671 rs2200733 NONCE_ DOMTC or TT STK hCV16158671 rs2200733 NONCE_ GEN TC STK hCV16158671rs2200733 NONCE_ ADD T STK hCV16158671 rs2200733 NONCE_ AGE MALEADD T STK DIAB HTN hCV16158671 rs2200733 NONCE_ AGE MALE DOM TC orTT STK DIAB HTN hCV16158671 rs2200733 RECURRENT_ AGE MALE GEN TCSTK DIAB HTN hCV16158671 rs2200733 RECURRENT_ AGE MALE DOM TC or TTSTK DIAB HTN hCV16158671 rs2200733 RECURRENT_ AGE MALE ADD T STKDIAB HTN hCV16158671 rs2200733 RECURRENT_ DOM TC or TT STKhCV16158671 rs2200733 RECURRENT_ GEN TC STK hCV16158671 rs2200733RECURRENT_ ADD T STK hCV16336 rs362277 HD ATHERO_ REC CC STKhCV16336 rs362277 HD ATHERO_ ADD C STK hCV16336 rs362277 HD ATHERO_AGE MALE REC CC STK DIAB HTN hCV16336 rs362277 HD CE_STK ADD ChCV16336 rs362277 HD CE_STK REC CC hCV16336 rs362277 HD CE_STK AGEMALE ADD C DIAB HTN hCV16336 rs362277 HD CE_STK AGE MALE REC CCDIAB HTN hCV16336 rs362277 HD CE_STK GEN CC hCV16336 rs362277 HDEO_STK AGE MALE REC CC DIAB HTN hCV16336 rs362277 HD EO_STK AGEMALE ADD C DIAB HTN hCV16336 rs362277 HD EO_STK REC CC hCV16336rs362277 HD EO_STK ADD C hCV16336 rs362277 HD ISCHEMIC_ ADD CSTK

hCV16336 rs362277 HD ISCHEMIC_ REC CC STK hCV16336 rs362277 HDISCHEMIC_ AGE MALE ADD C STK DIAB HTN hCV16336 rs362277 HDISCHEMIC_ AGE MALE REC CC STK DIAB HTN hCV16336 rs362277 HDNOHD_STK ADD C hCV16336 rs362277 HD NOHD_STK REC CC hCV16336rs362277 HD NONCE_ REC CC STK hCV16336 rs362277 HD NONCE_ ADD C STKhCV16336 rs362277 HD NONCE_ AGE MALE REC CC STK DIAB HTN hCV16336rs362277 HD NONCE_ AGE MALE ADD C STK DIAB HTN hCV26478797rs2015018 CHSY-2 CE_STK REC GG hCV11425801 rs3805953 PEX6 ATHERO_AGE MALE GEN CT STK DIAB HTN hCV11425801 rs3805953 PEX6 ATHERO_ AGEMALE DOM CT or CC STK DIAB HTN hCV11425801 rs3805953 PEX6 ATHERO_GEN CT STK hCV11425801 rs3805953 PEX6 ATHERO_ DOM CT or CC STKhCV11425801 rs3805953 PEX6 ATHERO_ ADD C STK hCV11425801 rs3805953PEX6 ATHERO_ GEN CC STK hCV11425801 rs3805953 PEX6 ATHERO_ AGE MALEADD C STK DIAB HTN hCV11425801 rs3805953 PEX6 EO_STK GEN CThCV11425801 rs3805953 PEX6 EO_STK AGE MALE GEN CT DIAB HTNhCV11425801 rs3805953 PEX6 EO_STK DOM CT or CC hCV11425801rs3805953 PEX6 EO_STK AGE MALE DOM CT or CC DIAB HTN hCV11425801rs3805953 PEX6 ISCHEMIC_ AGE MALE GEN CT STK DIAB HTN hCV11425801rs3805953 PEX6 ISCHEMIC_ AGE MALE DOM CT or CC STK DIAB HTNhCV11425801 rs3805953 PEX6 ISCHEMIC_ GEN CT STK hCV11425801rs3805953 PEX6 ISCHEMIC_ DOM CT or CC STK hCV11425801 rs3805953PEX6 ISCHEMIC_ ADD C STK hCV11425801 rs3805953 PEX6 LACUNAR_ AGEMALE GEN CT STK DIAB HTN hCV11425801 rs3805953 PEX6 LACUNAR_ AGEMALE DOM CT or CC STK DIAB HTN hCV11425801 rs3805953 PEX6 LACUNAR_GEN CT STK hCV11425801 rs3805953 PEX6 NOHD_STK AGE MALE GEN CT DIABHTN hCV11425801 rs3805953 PEX6 NOHD_STK AGE MALE DOM CT or CC DIABHTN hCV11425801 rs3805953 PEX6 NOHD_STK DOM CT or CC hCV11425801rs3805953 PEX6 NOHD_STK GEN CT hCV11425801 rs3805953 PEX6 NOHD_STKADD C hCV11425801 rs3805953 PEX6 NOHD_STK GEN CC hCV11425801rs3805953 PEX6 NONCE_ AGE MALE DOM CT or CC STK DIAB HTNhCV11425801 rs3805953 PEX6 NONCE_ GEN CT STK hCV11425801 rs3805953PEX6 NONCE_ DOM CT or CC STK hCV11425801 rs3805953 PEX6 NONCE_ ADDC STK hCV11425801 rs3805953 PEX6 NONCE_ GEN CC STK hCV11425801rs3805953 PEX6 RECURRENT_ AGE MALE GEN CT STK DIAB HTN hCV11425801rs3805953 PEX6 RECURRENT_ GEN CT STK hCV11425842 rs10948059 GNMTATHERO_ AGE MALE DOM CT or CC STK DIAB HTN hCV11425842 rs10948059GNMT ATHERO_ AGE MALE GEN CT STK DIAB HTN hCV11425842 rs10948059GNMT ATHERO_ DOM CT or CC STK hCV11425842 rs10948059 GNMT ATHERO_AGE MALE GEN CC STK DIAB HTN hCV11425842 rs10948059 GNMT ATHERO_GEN CT STK hCV11425842 rs10948059 GNMT EO_STK GEN CT hCV11425842rs10948059 GNMT EO_STK DOM CT or CC hCV11425842 rs10948059 GNMTEO_STK AGE MALE GEN CT DIAB HTN hCV11425842 rs10948059 GNMT EO_STKAGE MALE DOM CT or CC DIAB HTN hCV11425842 rs10948059 GNMT EO_STKGEN CC hCV11425842 rs10948059 GNMT ISCHEMIC_ AGE MALE GEN CT STKDIAB HTN hCV11425842 rs10948059 GNMT ISCHEMIC_ AGE MALE DOM CT orCC STK DIAB HTN hCV11425842 rs10948059 GNMT NONCE_ AGE MALE GEN CTSTK DIAB HTN hCV11425842 rs10948059 GNMT NONCE_ AGE MALE DOM CT orCC STK DIAB HTN hCV1209800 rs35067690 CLIC5 CE_STK REC GGhCV1209800 rs35067690 CLIC5 CE STK ADD G hCV16134786 rs2857595EO_STK ADD A hCV16134786 rs2857595 EO_STK GEN AA hCV16134786rs2857595 EO_STK REC AA hCV16134786 rs2857595 EO_STK DOM AG or AAhCV16134786 rs2857595 LACUNAR_ GEN AA STK hCV16134786 rs2857595LACUNAR_ REC AA STK hCV16134786 rs2857595 LACUNAR_ ADD A STKhCV16134786 rs2857595 NONCE_ ADD A STK hCV16134786 rs2857595 NONCE_GEN AA STK hCV25651109 rs35690712 SLC39A7 ISCHEMIC_ GEN GG STKhCV25651109 rs35690712 SLC39A7 ISCHEMIC_ DOM GC or GG STKhCV25651109 rs35690712 SLC39A7 ISCHEMIC_ GEN GC STK hCV25651109rs35690712 SLC39A7 NOHD_STK GEN GC hCV25651109 rs35690712 SLC39A7NOHD_STK DOM GC or GG hCV25651109 rs35690712 SLC39A7 NOHD_STK GENGG hCV30308202 rs9482985 LAMA2 RECURRENT_ ADD G STK hCV30308202rs9482985 LAMA2 RECURRENT_ AGE MALE GEN GG STK DIAB HTN hCV30308202rs9482985 LAMA2 RECURRENT_ AGE MALE DOM GC or GG STK DIAB HTNhCV30308202 rs9482985 LAMA2 RECURRENT_ REC GG STK hCV30308202rs9482985 LAMA2 RECURRENT_ AGE MALE GEN GC STK DIAB HTN hCV30308202rs9482985 LAMA2 RECURRENT_ GEN GG STK hCV3082219 rs1884833 RFXDC1EO_STK ADD A hCV3082219 rs1884833 RFXDC1 LACUNAR_ ADD A STKhCV3082219 rs1884833 RFXDC1 LACUNAR_ DOM AG or AA STK hCV3082219rs1884833 RFXDC1 LACUNAR_ GEN AG STK hCV3082219 rs1884833 RFXDC1NONCE_ ADD A STK hCV3082219 rs1884833 RFXDC1 NONCE_ DOM AG or AASTK hCV3082219 rs1884833 RFXDC1 NONCE_ GEN AG STK hCV8942032rs1264352 DDR1 EO_STK DOM CG or CC hCV8942032 rs1264352 DDR1 EO_STKGEN CG hCV8942032 rs1264352 DDR1 EO_STK ADD C hCV8942032 rs1264352DDR1 EO_STK AGE MALE GEN CG DIAB HTN hCV8942032 rs1264352 DDR1EO_STK AGE MALE DOM CG or CC DIAB HTN hCV8942032 rs1264352 DDR1EO_STK AGE MALE ADD C DIAB HTN hCV8942032 rs1264352 DDR1 ISCHEMIC_AGE MALE GEN CG STK DIAB HTN hCV8942032 rs1264352 DDR1 ISCHEMIC_AGE MALE DOM CG or CC STK DIAB HTN hCV8942032 rs1264352 DDR1ISCHEMIC_ AGE MALE ADD C STK DIAB HTN hCV8942032 rs1264352 DDR1ISCHEMIC_ GEN CG STK hCV8942032 rs1264352 DDR1 ISCHEMIC_ DOM CG orCC STK hCV8942032 rs1264352 DDR1 LACUNAR_ AGE MALE DOM CG or CC STKDIAB HTN hCV8942032 rs1264352 DDR1 LACUNAR_ AGE MALE ADD C STK DIABHTN hCV8942032 rs1264352 DDR1 LACUNAR_ AGE MALE GEN CG STK DIAB HTNhCV8942032 rs1264352 DDR1 LACUNAR_ DOM CG or CC STK hCV8942032rs1264352 DDR1 LACUNAR_ ADD C STK hCV8942032 rs1264352 DDR1LACUNAR_ GEN CG STK hCV8942032 rs1264352 DDR1 NOHD_STK AGE MALE GENCG DIAB HTN hCV8942032 rs1264352 DDR1 NOHD_STK AGE MALE DOM CG orCC DIAB HTN hCV8942032 rs1264352 DDR1 NOHD_STK GEN CG hCV8942032rs1264352 DDR1 NONCE_ AGE MALE GEN CG STK DIAB HTN hCV8942032rs1264352 DDR1 NONCE_ AGE MALE DOM CG or CC STK DIAB HTN hCV8942032rs1264352 DDR1 NONCE_ GEN CG STK hCV8942032 rs1264352 DDR1 NONCE_AGE MALE ADD C STK DIAB HTN hCV8942032 rs1264352 DDR1 NONCE_ DOM CGor CC STK hCV8942032 rs1264352 DDR1 RECURRENT_ AGE MALE DOM CG orCC STK DIAB HTN hCV8942032 rs1264352 DDR1 RECURRENT_ AGE MALE GENCG STK DIAB HTN hCV8942032 rs1264352 DDR1 RECURRENT_ AGE MALE ADD CSTK DIAB HTN hCV8942032 rs1264352 DDR1 RECURRENT_ GEN CG STKhCV8942032 rs1264352 DDR1 RECURRENT_ DOM CG or CC STK hCV8942032rs1264352 DDR1 RECURRENT_ ADD C STK hCV25596936 rs6967117 EPHA1ATHERO_ GEN TC STK hCV25596936 rs6967117 EPHA1 ATHERO_ DOM TC or TTSTK hCV25596936 rs6967117 EPHA1 ISCHEMIC_ GEN TC STK hCV25596936rs6967117 EPHA1 LACUNAR_ GEN TC STK hCV25596936 rs6967117 EPHA1NOHD_STK GEN TC hCV25596936 rs6967117 EPHA1 NONCE_ GEN TC STKhCV25596936 rs6967117 EPHA1 NONCE_ DOM TC or TT STK hCV25596936rs6967117 EPHA1 NONCE_ ADD T STK hCV27511436 rs3750145 FZD1 ATHERO_GEN TC STK hCV27511436 rs3750145 FZD1 ATHERO_ AGE MALE GEN TC STKDIAB HTN hCV27511436 rs3750145 FZD1 ATHERO_ DOM TC or TT STKhCV27511436 rs3750145 FZD1 ATHERO_ GEN TT STK hCV27511436 rs3750145FZD1 ATHERO_ AGE MALE DOM TC or TT STK DIAB HTN hCV27511436rs3750145 FZD1 ATHERO_ AGE MALE GEN TT STK DIAB HTN hCV27511436rs3750145 FZD1 CE STK GEN TC hCV27511436 rs3750145 FZD1 CE STK AGEMALE GEN TC DIAB HTN hCV27511436 rs3750145 FZD1 CE_STK AGE MALE DOMTC or TT DIAB HTN hCV27511436 rs3750145 FZD1 CE STK AGE MALE GEN TTDIAB HTN hCV27511436 rs3750145 FZD1 CE STK DOM TC or TT hCV27511436rs3750145 FZD1 EO_STK GEN TC hCV27511436 rs3750145 FZD1 EO_STK DOMTC or TT hCV27511436 rs3750145 FZD1 EO_STK ALTER MÄNNLICH GEN TC DIAB HTNhCV27511436 rs3750145 FZD1 EO_STK GEN TT hCV27511436 rs3750145 FZD1EO_STK ALTER MÄNNLICH DOM TC oder TT DIAB HTN hCV27511436 rs3750145 FZD1EO_STK ALTER MÄNNLICH GEN TT

DIAB HTN hCV27511436 rs3750145 FZD1 ISCHEMIC_ AGE MALE GEN TC STKDIAB HTN hCV27511436 rs3750145 FZD1 ISCHEMIC_ DOM TC or TT STKhCV27511436 rs3750145 FZD1 ISCHEMIC_ AGE MALE DOM TC or TT STK DIABHTN hCV27511436 rs3750145 FZD1 ISCHEMIC_ AGE MALE GEN TT STK DIABHTN hCV27511436 rs3750145 FZD1 ISCHEMIC_ GEN TT STK hCV27511436rs3750145 FZD1 LACUNAR_ AGE MALE GEN TC STK DIAB HTN hCV27511436rs3750145 FZD1 LACUNAR_ GEN TC STK hCV27511436 rs3750145 FZD1LACUNAR_ AGE MALE DOM TC or TT STK DIAB HTN hCV27511436 rs3750145FZD1 LACUNAR_ AGE MALE GEN TT STK DIAB HTN hCV27511436 rs3750145FZD1 LACUNAR_ DOM TC or TT STK hCV27511436 rs3750145 FZD1 LACUNAR_GEN TT STK hCV27511436 rs3750145 FZD1 NOHD_STK GEN TC hCV27511436rs3750145 FZD1 NOHD_STK AGE MALE GEN TC DIAB HTN hCV27511436rs3750145 FZD1 NOHD_STK DOM TC or TT hCV27511436 rs3750145 FZD1NOHD_STK AGE MALE DOM TC or TT DIAB HTN hCV27511436 rs3750145 FZD1NOHD_STK AGE MALE GEN TT DIAB HTN hCV27511436 rs3750145 FZD1NOHD_STK GEN TT hCV27511436 rs3750145 FZD1 NONCE_ AGE MALE GEN TCSTK DIAB HTN hCV27511436 rs3750145 FZD1 NONCE_ DOM TC or TT STKhCV27511436 rs3750145 FZD1 NONCE_ GEN TT STK hCV27511436 rs3750145FZD1 NONCE_ AGE MALE DOM TC or TT STK DIAB HTN hCV27511436rs3750145 FZD1 NONCE_ AGE MALE GEN TT STK DIAB HTN hCV29401764rs7793552 LOC646588 ATHERO_ AGE MALE GEN CT STK DIAB HTNhCV15857769 rs2924914 ATHERO_ ADD T STK hCV15857769 rs2924914ATHERO_ DOM TC or TT STK hCV15857769 rs2924914 ATHERO_ GEN TC STKhCV15857769 rs2924914 ATHERO_ AGE MALE GEN TT STK DIAB HTNhCV15857769 rs2924914 ATHERO_ GEN TT STK hCV15857769 rs2924914CE_STK GEN TC hCV15857769 rs2924914 CE_STK DOM TC or TT hCV15857769rs2924914 ISCHEMIC_ GEN TC STK hCV15857769 rs2924914 ISCHEMIC_ DOMTC or TT STK hCV15857769 rs2924914 ISCHEMIC_ ADD T STK hCV15857769rs2924914 NOHD_STK GEN TC hCV15857769 rs2924914 NOHD_STK DOM TC orTT hCV15857769 rs2924914 NONCE_ DOM TC or TT STK hCV15857769rs2924914 NONCE_ GEN TC STK hCV15857769 rs2924914 NONCE_ ADD T STKhCV15857769 rs2924914 RECURRENT_ GEN TC STK hCV15857769 rs2924914RECURRENT_ DOM TC or TT STK hCV15857769 rs2924914 RECURRENT_ AGEMALE GEN TC STK DIAB HTN hCV15857769 rs2924914 RECURRENT_ AGE MALEDOM TC or TT STK DIAB HTN hCV15857769 rs2924914 RECURRENT_ ADD TSTK hCV29539757 rs10110659 KCNQ3 NONCE_ GEN CA STK hCV1348610rs3739636 C9orf46 ISCHEMIC_ AGE MALE GEN AG STK DIAB HTN hCV1348610rs3739636 C9orf46 ISCHEMIC_ AGE MALE DOM AG or AA STK DIAB HTNhCV1348610 rs3739636 C9orf46 NOHD_STK AGE MALE GEN AG DIAB HTNhCV1348610 rs3739636 C9orf46 NONCE_ AGE MALE GEN AG STK DIAB HTNhCV26505812 rs10757274 C9P21 ATHERO_ AGE MALE REC GG STK DIAB HTNhCV26505812 rs10757274 C9P21 NONCE_ AGE MALE REC GG STK DIAB HTNhCV2169762 rs1804689 HPS1 CE_STK GEN TG hCV2169762 rs1804689 HPS1CE_STK DOM TG or TT hCV2169762 rs1804689 HPS1 CE_STK ADD ThCV2169762 rs1804689 HPS1 CE_STK AGE MALE DOM TG or TT DIAB HTNhCV2169762 rs1804689 HPS1 CE_STK AGE MALE GEN TG DIAB HTNhCV2169762 rs1804689 HPS1 CE_STK AGE MALE ADD T DIAB HTN hCV2169762rs1804689 HPS1 EO_STK AGE MALE REC TT DIAB HTN hCV2169762 rs1804689HPS1 ISCHEMIC_ AGE MALE ADD T STK DIAB HTN hCV2169762 rs1804689HPS1 ISCHEMIC_ DOM TG or TT STK hCV2169762 rs1804689 HPS1 ISCHEMIC_AGE MALE DOM TG or TT STK DIAB HTN hCV2169762 rs1804689 HPS1ISCHEMIC_ GEN TG STK hCV2169762 rs1804689 HPS1 ISCHEMIC_ AGE MALEGEN TT STK DIAB HTN hCV2169762 rs1804689 HPS1 ISCHEMIC_ ADD T STKhCV2169762 rs1804689 HPS1 ISCHEMIC_ AGE MALE GEN TG STK DIAB HTNhCV2169762 rs1804689 HPS1 ISCHEMIC_ AGE MALE REC TT STK DIAB HTNhCV2169762 rs1804689 HPS1 LACUNAR_ AGE MALE DOM TG or TT STK DIABHTN hCV2169762 rs1804689 HPS1 NOHD_STK DOM TG or TT hCV2169762rs1804689 HPS1 NOHD_STK GEN TG hCV2169762 rs1804689 HPS1 NOHD_STKADD T hCV2169762 rs1804689 HPS1 NOHD_STK AGE MALE ADD T DIAB HTNhCV2169762 rs1804689 HPS1 NOHD_STK AGE MALE DOM TG or TT DIAB HTNhCV2169762 rs1804689 HPS1 NOHD_STK AGE MALE GEN TG DIAB HTNhCV2169762 rs1804689 HPS1 NOHD_STK AGE MALE GEN TT DIAB HTNhCV2169762 rs1804689 HPS1 NOHD_STK GEN TT hCV2169762 rs1804689 HPS1NONCE_ AGE MALE GEN TT STK DIAB HTN hCV2169762 rs1804689 HPS1NONCE_ AGE MALE ADD T STK DIAB HTN hCV2169762 rs1804689 HPS1 NONCE_AGE MALE REC TT STK DIAB HTN hCV27830265 rs12762303 ALOX5 ATHERO_GEN GG STK hCV27830265 rs12762303 ALOX5 ATHERO_ REC GG STKhCV27830265 rs12762303 ALOX5 ATHERO_ AGE MALE ADD G STK DIAB HTNhCV27830265 rs12762303 ALOX5 ATHERO_ ADD G STK hCV27830265rs12762303 ALOX5 ATHERO_ AGE MALE GEN GG STK DIAB HTN hCV27830265rs12762303 ALOX5 ATHERO_ AGE MALE REC GG STK DIAB HTN hCV27830265rs12762303 ALOX5 ATHERO_ AGE MALE DOM GA or GG STK DIAB HTNhCV27830265 rs12762303 ALOX5 EO_STK AGE MALE ADD G DIAB HTNhCV27830265 rs12762303 ALOX5 EO_STK AGE MALE DOM GA or GG DIAB HTNhCV27830265 rs12762303 ALOX5 EO_STK AGE MALE GEN GA DIAB HTNhCV27830265 rs12762303 ALOX5 ISCHEMIC_ GEN GG STK hCV27830265rs12762303 ALOX5 ISCHEMIC_ REC GG STK hCV27830265 rs12762303 ALOX5ISCHEMIC_ AGE MALE ADD G STK DIAB HTN hCV27830265 rs12762303 ALOX5ISCHEMIC_ AGE MALE GEN GG STK DIAB HTN hCV27830265 rs12762303 ALOX5ISCHEMIC_ AGE MALE REC GG STK DIAB HTN hCV27830265 rs12762303 ALOX5ISCHEMIC_ ADD G STK hCV27830265 rs12762303 ALOX5 LACUNAR_ AGE MALEADD G STK DIAB HTN hCV27830265 rs12762303 ALOX5 LACUNAR_ AGE MALEDOM GA or GG STK DIAB HTN hCV27830265 rs12762303 ALOX5 NOHD_STK GENGG hCV27830265 rs12762303 ALOX5 NOHD_STK REC GG hCV27830265rs12762303 ALOX5 NOHD_STK AGE MALE ADD G DIAB HTN hCV27830265rs12762303 ALOX5 NONCE_ AGE MALE ADD G STK DIAB HTN hCV27830265rs12762303 ALOX5 NONCE_ GEN GG STK hCV27830265 rs12762303 ALOX5NONCE_ ADD G STK hCV27830265 rs12762303 ALOX5 NONCE_ REC GG STKhCV27830265 rs12762303 ALOX5 NONCE_ AGE MALE DOM GA or GG STK DIABHTN hCV27830265 rs12762303 ALOX5 NONCE_ AGE MALE GEN GA STK DIABHTN hCV27830265 rs12762303 ALOX5 NONCE_ DOM GA or GG STKhCV27830265 rs12762303 ALOX5 NONCE_ AGE MALE GEN GG STK DIAB HTNhCV27830265 rs12762303 ALOX5 RECURRENT_ REC GG STK hCV27830265rs12762303 ALOX5 RECURRENT_ GEN GG STK hCV27830265 rs12762303 ALOX5RECURRENT_ AGE MALE REC GG STK DIAB HTN hCV27830265 rs12762303ALOX5 RECURRENT_ AGE MALE GEN GG STK DIAB HTN hCV1053082 rs544115NEU3 ATHERO_ AGE MALE DOM CT or CC STK DIAB HTN hCV1053082 rs544115NEU3 ATHERO_ AGE MALE GEN CC STK DIAB HTN hCV1053082 rs544115 NEU3ATHERO_ AGE MALE GEN CT STK DIAB HTN hCV1053082 rs544115 NEU3CE_STK AGE MALE GEN CC DIAB HTN hCV1053082 rs544115 NEU3 CE_STK AGEMALE DOM CT or CC DIAB HTN hCV1053082 rs544115 NEU3 CE_STK ADD ChCV1053082 rs544115 NEU3 CE_STK AGE MALE GEN CT DIAB HTN hCV1053082rs544115 NEU3 CE_STK REC CC hCV1053082 rs544115 NEU3 EO_STK DOM CTor CC hCV1053082 rs544115 NEU3 EO_STK GEN CC hCV1053082 rs544115NEU3 EO_STK GEN CT hCV1053082 rs544115 NEU3 EO_STK AGE MALE ADD CDIAB HTN hCV1053082 rs544115 NEU3 EO_STK AGE MALE GEN CC DIAB HTNhCV1053082 rs544115 NEU3 EO_STK AGE MALE REC CC DIAB HTN hCV1053082rs544115 NEU3 ISCHEMIC_ AGE MALE DOM CT or CC STK DIAB HTNhCV1053082 rs544115 NEU3 ISCHEMIC_ AGE MALE GEN CC STK DIAB HTNhCV1053082 rs544115 NEU3 ISCHEMIC_ AGE MALE GEN CT STK DIAB HTNhCV1053082 rs544115 NEU3 ISCHEMIC_ GEN CC STK hCV1053082 rs544115NEU3 ISCHEMIC_ DOM CT or CC STK hCV1053082 rs544115 NEU3 ISCHEMIC_GEN CT STK hCV1053082 rs544115 NEU3 ISCHEMIC_ ADD C STK hCV1053082rs544115 NEU3 NOHD_STK AGE MALE DOM CT or CC DIAB HTN hCV1053082rs544115 NEU3 NOHD_STK AGE MALE GEN CT DIAB HTN hCV1053082 rs544115NEU3 NOHD_STK AGE MALE GEN CC DIAB HTN hCV1053082 rs544115 NEU3NOHD_STK GEN CC hCV1053082 rs544115 NEU3 NOHD_STK DOM CT or CChCV1053082 rs544115 NEU3 NOHD_STK GEN CT

hCV1053082 rs544115 NEU3 NONCE_ AGE MALE DOM CT or CC STK DIAB HTNhCV1053082 rs544115 NEU3 NONCE_ AGE MALE GEN CT STK DIAB HTNhCV1053082 rs544115 NEU3 NONCE_ AGE MALE GEN CC STK DIAB HTNhCV1053082 rs544115 NEU3 NONCE_ DOM CT or CC STK hCV1053082rs544115 NEU3 NONCE_ GEN CC STK hCV1053082 rs544115 NEU3 NONCE_ GENCT STK hCV1452085 rs12223005 TRIM22 ISCHEMIC_ AGE MALE GEN CA STKDIAB HTN hCV1452085 rs12223005 TRIM22 LACUNAR_ AGE MALE GEN CA STKDIAB HTN hCV1452085 rs12223005 TRIM22 NOHD_STK AGE MALE GEN CA DIABHTN hCV1452085 rs12223005 TRIM22 NOHD_STK AGE MALE DOM CA or CCDIAB HTN hCV1452085 rs12223005 TRIM22 NOHD_STK AGE MALE GEN CC DIABHTN hCV1452085 rs12223005 TRIM22 NONCE_ AGE MALE GEN CA STK DIABHTN hCV1452085 rs12223005 TRIM22 RECURRENT_ AGE MALE GEN CA STKDIAB HTN hCV302629 rs9284183 UBAC2 EO_STK GEN GA hCV11474611rs3814843 CALM1 ATHERO_ GEN GT STK hCV11474611 rs3814843 CALM1CE_STK AGE MALE GEN GG DIAB HTN hCV11474611 rs3814843 CALM1 CE_STKAGE MALE REC GG DIAB HTN hCV1262973 rs229653 PLEKHG3 CE_STK GEN AGhCV27892569 rs4903741 NRXN3 CE_STK GEN CC hCV27892569 rs4903741NRXN3 CE_STK REC CC hCV27892569 rs4903741 NRXN3 CE_STK ADD ChCV27892569 rs4903741 NRXN3 NOHD_STK ADD C hCV27077072 rs8060368RECURRENT_ ADD C STK hCV27077072 rs8060368 RECURRENT_ REC CC STKhCV27077072 rs8060368 RECURRENT_ AGE MALE GEN CC STK DIAB HTNhCV32160712 rs11079160 CE_STK GEN TT hCV32160712 rs11079160 CE_STKREC TT hCV32160712 rs11079160 CE_STK ADD T hCV32160712 rs11079160EO_STK AGE MALE REC TT DIAB HTN hCV32160712 rs11079160 EO_STK AGEMALE GEN TT DIAB HTN hCV32160712 rs11079160 ISCHEMIC_ GEN TT STKhCV32160712 rs11079160 ISCHEMIC_ REC TT STK hCV1619596 rs1048621SDCBP2 CE_STK AGE MALE GEN AG DIAB HTN hCV1619596 rs1048621 SDCBP2CE_STK AGE MALE DOM AG or AA DIAB HTN hCV1619596 rs1048621 SDCBP2CE_STK ADD A hCV1619596 rs1048621 SDCBP2 EO_STK DOM AG or AAhCV1619596 rs1048621 SDCBP2 EO_STK GEN AG hCV1619596 rs1048621SDCBP2 EO_STK ADD A hCV1619596 rs1048621 SDCBP2 EO_STK AGE MALE DOMAG or AA DIAB HTN hCV1619596 rs1048621 SDCBP2 EO_STK AGE MALE GENAG DIAB HTN hCV1619596 rs1048621 SDCBP2 ISCHEMIC_ AGE MALE GEN AGSTK DIAB HTN hCV1619596 rs1048621 SDCBP2 ISCHEMIC_ AGE MALE DOM AGor AA STK DIAB HTN hCV1619596 rs1048621 SDCBP2 ISCHEMIC_ ADD A STKhCV2358247 rs415989 WFDC3 RECURRENT_ DOM GA or GG STK hCV2358247rs415989 WFDC3 RECURRENT_ GEN GA STK hCV2358247 rs415989 WFDC3RECURRENT_ ADD G STK hCV29537898 rs6073804 NOHD_STK GEN TChCV29537898 rs6073804 NOHD_STK DOM TC or TT hCV29537898 rs6073804RECURRENT_ DOM TC or TT STK hCV29537898 rs6073804 RECURRENT_ ADD TSTK hCV29537898 rs6073804 RECURRENT_ GEN TC STK hCV1723718rs12481805 UMODL1 EO_STK AGE MALE REC AA DIAB HTN hCV1723718rs12481805 UMODL1 LACUNAR_ REC AA STK hCV1723718 rs12481805 UMODL1LACUNAR_ GEN AA STK ProbChi 95 % 95 % Sq (2- Odds Lower Upper sidedp- PVALUE_ hCV # Ratio CL CL value) 2DF hCV1958451 1,753 0,99 3,1060,0543 0,15583 hCV1958451 1,676 0,974 2,884 0,0623 . hCV19584511.565 0.952 2.573 0.0775 0.15311 hCV1958451 1.628 0.935 2.8350.0852 0.15583 hCV1958451 1.932 0.987 3.781 0.0546 0.06739hCV27494483 1.575 1.084 2.287 0.0171 0.05794 hCV27494483 1.5641.081 2.263 0.0176 . hCV27494483 1,522 1,065 2,175 0,0211 .hCV27494483 1,307 0,967 1,765 0,0814 . hCV27494483 1,291 0,9661,725 ​​0,0847 . hCV27494483 1,306 0,963 1,771 0,0859 0,21896hCV27504565 2,619 1,242 5,524 0,0115 0,04076 hCV27504565 2,336 1,127 4,841 0,0225 0,04076hCV27504565 1,922 1,077 3,43 0,027 0,08635 hCV27504565 1.821 1.032 3.212 0.0385 0.08635hCV27504565 1.416 0.957 2.095 0.0819 0.13029 hCV27504565 1.5270.985 2.369 0.0585 0.11469 hCV27504565 1.706 0.952 3.055 0.07250.18169 hCV27504565 1.811 0.973 3.371 0.061 0.10231 hCV275045651.487 0.943 2.346 0.0877 0.12763 hCV27504565 2.79 0.968 8.0460.0575 0.15677 hCV27504565 2.47 0.893 6.833 0,0817 . hCV87544492,155 1,043 4,452 0,0381 0,11587 hCV8754449 2,021 1,004 4,0650,0486 . hCV8754449 1,768 1,002 3,119 0,049 0,1425 hCV8754449 1,7240,995 2,986 0,0521 . hCV8754449 1.698 0.974 2.96 0.0619 0.1425hCV8754449 1.949 0.96 3.955 0.0647 0.11587 hCV8754449 2.615 0.9097.524 0.0747 0.20413 hCV8754449 2.421 0.876 6.693 0.0883 .hCV2091644 1.275 0.956 1.699 0.0984 . hCV8820007 1.597 0.953 2.6780.0757 0.18574 hCV8820007 1.387 0.953 2.02 0.0876 0.11797hCV8820007 1.511 0.927 2.463 0.0975 0.21063 hCV8820007 1.624 1.0652.478 0.0243 0.01745 hCV8820007 1.751 1.027 2.984 0.0396 0.07825hCV8820007 1.543 0.929 2.564 0.094 . hCV8820007 1,404 0,937 2,1020,0998 . hCV11354788 1,379 1,016 1,871 0,0394 . hCV11354788 1,4191,012 1,99 0,0423 . hCV11354788 1,397 0,987 1,977 0,0592 0,11826hCV11354788 1,274 0,99 1,639 0,0597 . hCV11354788 1,275 0,984 1,6530,066 0,16972 hCV11354788 1,231 0,982 1,542 0,0711 . hCV113547881,501 1,205 1,869 0,0003 . hCV11354788 1,56 1,216 2,002 0,0005 .hCV11354788 1,633 1,215 2,196 0,0011 . hCV11354788 1.712 1.227 2.390.0016 . hCV11354788 1.51 1.166 1.956 0.0018 0.00137 hCV113547881.652 1.17 2.332 0.0043 0.00498 hCV11354788 2.198 1.061 4.5560.0341 0.00137 hCV11354788 1.996 0.966 4.125 0.0619 . hCV113547882,533 0,921 6,962 0,0716 0,00498 hCV11354788 1,432 1,068 1,9220,0165 . hCV11354788 1,413 1,06 1,883 0,0184 . hCV11354788 1,3651,053 1,768 0,0186 . HCV11354788 1,466 1,057 2,032 0,0217 .HCV11354788 1,396 1,038 1,876 0,0273 0,05898 HCV11354788 1,4231,09191991996 0,05696 0,056478 HCV113591993,096 0,056405640564056405640564056405640564056405640564056405640564. hCV11354788 1,346 1,099 1,650,0041 0,0099 hCV11354788 1,367 1,077 1,735 0,0102 . hCV113547881,404 1,077 1,831 0,0122 . hCV11354788 1,376 1,047 1,809 0,0220,03661 hCV11354788 1,31 1,083 1,585 0,0053 . hCV11354788 1,3451,086 1,666 0,0065 . hCV11354788 1,321 1,059 1,647 0,0135 0,02034hCV11354788 1,354 1,052 1,743 0,0188 . hCV11354788 1,375 1,0361,825 0,0275 . hCV11354788 1,332 0,995 1,784 0,0544 0,06231hCV11354788 1,248 0,99 1,573 0,0613 0,17362 hCV11354788 1,295 0,953 1,758 0,0982 . hCV113547882,096 1,252 3,509 0,0049 0,01709 hCV11354788 1,962 1,187 3,2430,0086 . hCV11354788 1,701 1,072 2,7 0,0241 . hCV11354788 1,3830,979 1,955 0,066 . hCV11354788 1,382 0,968 1,973 0,075 0,1844hCV11354788 1,321 0,972 1,796 0,0752 . hCV16158671 1,415 1,0451,915 0,0248 . hCV16158671 1,442 1,028 2,023 0,0339 . hCV161586711,304 1,013 1,679 0,039 . HCV16158671 1,257 1,005 1,573 0,0456 .HCV16158671 1,302 1,003 1,69 0,047 0,11865 HCV16158671 1,397 0,9861,98 0,06 0,07966666.0,03,03,03,096666666666666666. hCV16158671 1,543 1,1911,999 0,001 0,00106 hCV16158671 1,631 1,216 2,189 0,0011 .hCV16158671 1,733 1,241 2,42 0,0012 . hCV16158671 1,684 1,192 2,3810,0032 0,00458 hCV16158671 2,083 1,015 4,275 0,0454 0,00106hCV16158671 1,883 0,92 3,853 0,0832 . hCV16158671 2,319 0,869 6,1910,093 0,00458 hCV16158671 1,426 1,069 1,901 0,0156 . hCV161586711,364 1,055 1,763 0,0178 . hCV16158671 1,409 1,052 1,887 0,0215 .hCV16158671 1,415 1,051 1,905 0,022 0,05284 hCV16158671 1,448 1,0442.008 0,0267 . hCV16158671 1,409 1,006 1,975 0,0461 0,07117hCV16158671 1,376 1,13 1,677 0,0015 . hCV16158671 1,324 1,11 1,5790,0018 . hCV16158671 1,365 1,113 1,674 0,0028 0,00631 hCV161586711,375 1,085 1,742 0,0083 . hCV16158671 1,413 1,083 1,843 0,0109 .hCV16158671 1,378 1,047 1,813 0,0222 0,03074 hCV16158671 1,3271,099 1,603 0,0032 . hCV16158671 1,366 1,103 1,691 0,0042 .hCV16158671 1,337 1,072 1,668 0,0101 0,01299 hCV16158671 1,3661.063 1,754 0,0147 . hCV16158671 1.384 1.042 1.838 0.0247 .hCV16158671 1.33 0.992 1.783 0.0569 0.04871 hCV16158671 2.103 0.8914.961 0.0896 0.04871 hCV16158671 1.251 0.998 1.568 0.0518 .hCV16158671 1.259 0.998 1.588 0.0525 0.14733 hCV16158671 1.2060.985 1.475 0.0696 . hCV16158671 1,274 0,967 1,679 0,0852 .hCV16158671 1,297 0,954 1,761 0,0967 . hCV16158671 2,087 1,24 3,5120,0056 0,01904 hCV16158671 1,943 1,171 3,225 0,0102 . hCV161586711,671 1,053 2,652 0,0294 . hCV16158671 1,375 0,971 1,948 0,0728 .hCV16158671 1,38 0,964 1,975 0,0786 0,19939 hCV16158671 1,307 0,9611,776 0,0879 . hCV16336 1,377 1,032 1,837 0,0298 . hCV16336 1,3151,013 1,707 0,0399 . hCV16336 1,39 0,96 2,013 0,0812 . hCV163361,523 1,147 2,022 0,0036 . hCV16336 1,525 1,126 2,066 0,0065 .hCV16336 1,49 1,033 2,148 0,0328 . hCV16336 1,52 1,028 2,247 0,036. hCV16336 3,625 0,825 15,926 0,0881 0,01511 hCV16336 1,659 1,1562,381 0,0061 . hCV16336 1,559 1,11 2,188 0,0103 . hCV16336 1,3891,014 1,904 0,0407 . hCV16336 1,355 1,01 1,819 0,0427 . hCV163361,379 1,127 1,686 0,0018 . hCV16336 1,41 1,131 1,758 0,0023 .hCV16336 1,377 1,052 1,803 0,0198 . hCV16336 1,417 1,056 1,9010,0203 . hCV16336 1,227 0,99 1,521 0,0619 . hCV16336 1,248 0,9861,581 0,0658 . hCV16336 1,345 1,046 1,73 0,0211 . hCV16336 1.31.035 1.633 0.0244 . hCV16336 1,39 0,999 1,935 0,0508 . hCV163361,346 0,997 1,816 0,0521 . hCV26478797 1,205 0,965 1,505 0,099 .hCV11425801 1,99 1,402 2,824 0,0001 0,0005 hCV11425801 1,726 1,2512,38 0,0009 .

hCV11425801 1,539 1,183 2,002 0,0013 0,00531 hCV11425801 1,4811,159 1,892 0,0017 . hCV11425801 1,179 1,019 1,363 0,0271 .hCV11425801 1,385 1,028 1,865 0,0323 0,00531 hCV11425801 1,18 0,9741,429 0,0913 . HCV11425801 1,639 1,226 2,192 0,0009 0,00345hCV11425801 1,718 1,229 2,4 0,0015 0,00399 hCV11425801 1,483 1,092 2,015 0,0116 . hCV114258011,617 1,235 2,116 0,0005 0,00176 hCV11425801 1,453 1,135 1,86 0,003. hCV11425801 1,321 1,082 1,612 0,0062 0,02335 hCV11425801 1,2761,062 1,534 0,0094 . hCV11425801 1,104 0,985 1,236 0,0889 .hCV11425801 1,826 1,186 2,811 0,0063 0,01078 hCV11425801 1,51 1,0142,25 0,0427 . hCV11425801 1,368 0,973 1,923 0,0715 0,11508 hCV11425801 1,276 1,043 1,559 0,0176 . hCV114258011.295 1.041 1.61 0.0201 0.05622 hCV11425801 1.12 0.991 1.266 0.07 .hCV11425801 1.244 0.973 1.591 0.0821 0.05622 hCV11425801 1.6891.268 2.251 0.0003 . hCV11425801 1,48 1,176 1,862 0,0008 0,00363hCV11425801 1,393 1,125 1,725 ​​0,0023 . hCV11425801 1,126 0,9891,282 0,0732 . hCV11425801 1.249 0.96 1.625 0.0971 0.00363hCV11425801 1.636 0.988 2.71 0.0556 0.12066 hCV11425801 1.368 0.9511.967 0.091 0.22257 hCV11425842 1.483 1.042 2.111 0.0286 .hCV11425842 1.508 1.036 2.195 0.032 0.08825 hCV11425842 1.281 0.9791.676 0.0707 . hCV11425842 1.445 0.961 2.172 0.077 0.08825hCV11425842 1.292 0.972 1.717 0.0777 0.19224 hCV11425842 1.44 1.0561.965 0.0214 0.06697 hCV11425842 1.4 1.047 1.871 0.0232 .hCV11425842 1.497 1.048 2.138 0.0267 0.08575 hCV11425842 1.4181.016 1.978 0.0399 . hCV11425842 1,338 0,953 1,878 0,0927 0,06697hCV11425842 1,334 0,998 1,785 0,0518 0,1427 hCV11425842 1,435 1,028 2,005 0,0341 0,10566hCV11425842 1,379 1,008 1,886 0,0444 . hCV1209800 1,54 0,995 2,3840,0529 . hCV1209800 1,497 0,985 2,277 0,059 . hCV16134786 1,2871,044 1,587 0,018 . hCV16134786 1,967 1,08 3,581 0,0269 0,0477hCV16134786 1,845 1,02 3,336 0,0428 . hCV16134786 1,283 0,999 1,650,0513 . hCV16134786 2,149 1,196 3,86 0,0105 0,0372 hCV161347862,114 1,189 3,76 0,0108 . hCV16134786 1,243 0,98 1,578 0,073 .hCV16134786 1,158 0,984 1,363 0,0777 . hCV16134786 1,501 0,9532,365 0,0799 0,16516 hCV25651109 8,255 1,015 67,158 0,0484 0,13989hCV25651109 8,232 1,012 66,954 0,0487 . hCV25651109 7,978 0,96366,101 0,0542 0,13989 hCV25651109 6,169 0,743 51,25 0,0921 0,2415hCV25651109 5,892 0,724 47,938 0,0973 . HCV25651109 5.866 0,72147.736 0,0981 0,2415 HCV30308202 1,354 1,016 1,803 0,0384 .HCV30308202 3,706 1,016 13.521 0,0473 0,129032.12903 HCV308202 3.53702. hCV30308202 1.349 0.975 1.868 0.0712 .hCV30308202 3.204 0.854 12.028 0.0845 0.12903 hCV30308202 2.4190.856 6.839 0.0956 0.11116 hCV3082219 1.273 0.982 1.65 0.0681 .hCV3082219 1.399 1.049 1.867 0.0225 . hCV3082219 1,424 1,035 1,9590,03 . hCV3082219 1,391 1,003 1,93 0,0483 0,07365 hCV3082219 1,2130,991 1,485 0,0608 . hCV3082219 1,227 0,984 1,529 0,0688 .hCV3082219 1,214 0,969 1,52 0,0917 0,17242 hCV8942032 1,484 1,1271,954 0,0049 . hCV8942032 1,488 1,12 1,978 0,0062 0,01912hCV8942032 1,394 1,092 1,78 0,0077 . hCV8942032 1,513 1,09 2,1010,0134 0,04543 hCV8942032 1,486 1,083 2,038 0,0142 . hCV89420321,37 1,037 1,81 0,0265 . hCV8942032 1,383 1,056 1,811 0,0183 0,061hCV8942032 1,341 1,035 1,737 0,0262 . hCV8942032 1,241 0,991 1,5540,0604 . hCV8942032 1,208 0,988 1,476 0,0658 0,17422 hCV89420321,178 0,972 1,428 0,0949 . hCV8942032 1,803 1,207 2,694 0,004 .hCV8942032 1,64 1,165 2,307 0,0046 . hCV8942032 1,77 1,166 2,6890,0074 0,01502 hCV8942032 1,418 1,036 1,942 0,0294 . hCV89420321,328 1,023 1,725 ​​0,0333 . HCV8942032 1,405 1,01 1,954 0,04350,09148 HCV8942032 1,358 1,021 1,807 0,0355 0,09951 HCV8942032 1,218 0,98 1,513 0,07490,10394 HCV8942032 1,419 1,047 1,923 0,0242 0,07825 hCV8942032 1,244 0,992 1,559 0,05850,1603 hCV8942032 1,269 0,983 1,637 0,0672 . hCV8942032 1,211 0,9751,504 0,0833 . hCV8942032 1,953 1,219 3,129 0,0054 . hCV89420321,965 1,206 3,201 0,0067 0,02072 hCV8942032 1,728 1,15 2,594 0,0084. hCV8942032 1,415 1,001 2,001 0,0494 0,14433 hCV8942032 1,3840,992 1,931 0,0561 . hCV8942032 1,269 0,959 1,68 0,0956 .hCV25596936 1,432 1,071 1,913 0,0153 0,03518 hCV25596936 1,3451,017 1,779 0,038 . hCV25596936 1.263 0.997 1.601 0.0533 0.04107hCV25596936 1.433 0.981 2.092 0.0627 0.15123 hCV25596936 1.302 1.011.679 0.0419 0.06504 hCV25596936 1.438 1.108 1.865 0.0063 0.01473hCV25596936 1.352 1.052 1.736 0.0183 . hCV25596936 1,224 0,9811,526 0,0731 . hCV27511436 2,706 1,389 5,271 0,0034 0,00764hCV27511436 2,877 1,272 6,508 0,0111 0,03448 hCV27511436 2,105 1,11 3,993 0,0227 0,00764hCV27511436 2,397 1,108 5,184 0,0263 . hCV27511436 2.271 1.046 4.930.0381 0.03448 hCV27511436 2.392 1.294 4.422 0.0054 0.00015hCV27511436 3.084 1.383 6.875 0.0059 0.00609 hCV27511436 2.2571.055 4.828 0.0359 . hCV27511436 2,025 0,943 4,352 0,0705 0,00609hCV27511436 1,647 0,917 2,958 0,0946 . hCV27511436 5.062 2.21111.593 0.0001 0.00053 hCV27511436 4.226 1.901 9.394 0.0004 .hCV27511436 4.83 1.964 11.882 0.0006 0.00223 hCV27511436 3.9831.786 8.882 0.0007 0.00053 hCV27511436 3.916 1.653 9.279 0.0019 .hCV27511436 3.668 1.542 8.725 0.0033 0.00223 hCV27511436 3.4491.798 6.618 0.0002 0.00063 hCV27511436 2.217 1.397 3.521 0.0007 .hCV27511436 2,78 1,498 5,158 0,0012 . hCV27511436 2.59 1.392 4.820.0027 0.00063 hCV27511436 2.033 1.277 3.236 0.0028 0.00001hCV27511436 12.63 2.356 67.742 0.0031 0.00773 hCV27511436 8.0491.905 34.008 0.0046 0.00667 hCV27511436 9.88 1.896 51.473 0.0065 .hCV27511436 9.1 1.743 47.499 0.0088 0.00773 hCV27511436 6.318 1.52826.128 0.0109 . hCV27511436 5.858 1.413 24.288 0.0148 0.00667hCV27511436 2.83 1.661 4.824 0.0001 0.00002 hCV27511436 3.231 1.6126.479 0.001 0.00243 hCV27511436 2.088 1.258 3.467 0.0044 .hCV27511436 2.586 1.334 5.012 0.0049 . HCV27511436 2,4 1,235 4.6650.0098 0,00243 HCV27511436 1,891 1,135 3,149 0,0144 0,0000002HCV27511436 3,955 1,807 8,657 0,0006 0.00244 HCV2751141427142. hCV27511436 2,657 1,457 4,843 0,0014 0,00023hCV27511436 3,312 1,571 6,985 0,0017 . hCV27511436 3,137 1,4836,636 0,0028 0,00244 hCV29401764 1,633 0,952 2,798 0,0746 0,17293hCV15857769 1,187 1,011 1,394 0,0361 . hCV15857769 1,255 1,0111,557 0,0391 . hCV15857769 1.23 0.979 1.545 0.0756 0.1026hCV15857769 1.532 0.946 2.48 0.0827 0.21882 hCV15857769 1.36 0.9471.952 0.096 0.1026 hCV15857769 1.295 1.029 1.63 0.0275 0.0333hCV15857769 1.209 0.97 1.507 0.0919 . hCV15857769 1,252 1,05 1,4930,0124 0,04329 hCV15857769 1,219 1,031 1,441 0,0203 . hCV158577691,117 0,983 1,27 0,0904 . hCV15857769 1,263 1,043 1,53 0,01670,05587 hCV15857769 1,228 1,024 1,474 0,0271 . hCV15857769 1,2261,013 1,483 0,0365 . hCV15857769 1,224 1,001 1,497 0,0489 0,11225hCV15857769 1,149 0,996 1,327 0,057 . hCV15857769 1,788 1,299 2,4630,0004 0,00102 hCV15857769 1,641 1,203 2,238 0,0018 . hCV158577691,733 1,112 2,701 0,0151 0,04261 hCV15857769 1,596 1,042 2,4430,0315 . hCV15857769 1,259 1,003 1,58 0,0471 . hCV29539757 1,4010,977 2,009 0,0671 0,0978 hCV1348610 1,307 1,014 1,685 0,03890,11763 hCV1348610 1,262 0,993 1,602 0,0567 . hCV1348610 1,2850,981 1,683 0,0688 0,15881 hCV1348610 1,283 0,96 1,714 0,09230,22581 hCV26505812 1,363 0,956 1,943 0,0866 . hCV26505812 1.320.959 1.818 0.0886 . hCV2169762 1,479 1,172 1,866 0,001 0,00436hCV2169762 1,422 1,139 1,774 0,0018 . hCV2169762 1,216 1,033 1,4330,0189 . hCV2169762 1,401 1,046 1,876 0,0237 . hCV2169762 1.411.038 1.916 0.0281 0.07665 hCV2169762 1.25 1.003 1.559 0.0473 .hCV2169762 1.493 0.946 2.357 0.0852 . hCV2169762 1.246 1.052 1.4760.0108 . hCV2169762 1,233 1,043 1,456 0,014 . hCV2169762 1,31 1,0461,641 0,0187 . hCV2169762 1,236 1,035 1,476 0,0192 0,04864hCV2169762 1,536 1,045 2,259 0,0291 0,03859 hCV2169762 1,258 0,991 1,597 0,0589 0,03859hCV2169762 1,382 0,955 2 0,0861 . hCV2169762 1,362 0,949 1,9550,0934 . hCV2169762 1,35 1,125 1,619 0,0012 . hCV2169762 1,3541,116 1,642 0,0021 0,00545 hCV2169762 1,218 1,064 1,395 0,0042 .hCV2169762 1,281 1,069 1,534 0,0073 . hCV2169762 1,386 1,089 1,7630,0079 . hCV2169762 1.347 1.044 1.737 0.0221 0.02354 hCV21697621.553 1.031 2.34 0.035 0.02354 hCV2169762 1.335 0.985 1.809 0.0630.00545 hCV2169762 1.497 0.971 2.308 0.0677 0.17878 hCV21697621.188 0.981 1.438 0.0774 . hCV2169762 1,422 0,939 2,153 0,0966 .hCV27830265 2,437 1,292 4,596 0,0059 0,01855 hCV27830265 2,3541,254 4,421 0,0077 . hCV27830265 1,051 0,0204 1,38 1,812 .hCV27830265 1,256 1,027 1,535 0,0262 . hCV27830265 2,705 1,09 6,7110,0318 0,04449 hCV27830265 2,508 1,018 6,179 0,0456 . hCV278302651,356 0,997 1,845 0,0522 . hCV27830265 1,294 0,988 1,697 0,0616 .hCV27830265 1,322 0,979 1,786 0,0687 . hCV27830265 1,302 0,9561,772 0,0938 0,17365 hCV27830265 1,909 1,098 3,32 0,0219 0,06853hCV27830265 1,88 1,084 3,26 0,0246 . hCV27830265 1.231 0.99 1.530.0618 . hCV27830265 2,011 0,94 4,304 0,0719 0,12112 hCV278302651,923 0,902 4,099 0,0903 . hCV27830265 1,146 0,977 1,344 0,0941 .hCV27830265 1,391 0,982 1,972 0,0632 . hCV27830265 1,408 0,9582,069 0,082 . hCV27830265 1,889 1,048 3,404 0,0342 0,10105hCV27830265 1,859 1,035 3,339 0,0381 . hCV27830265 1,246 0,9881,571 0,0637 . hCV27830265 1,376 1,074 1,761 0,0114 . hCV278302652.132 1,172 3,878 0,0132 0,02459 hCV27830265 1,248 1,042 1,4930,0158 . hCV27830265 2,037 1,124 3,693 0,019 . hCV27830265 1,3861,051 1,83 0,021 . hCV27830265 1,335 1,004 1,775 0,0472 0,03807hCV27830265 1,221 0,996 1,497 0,0553 . HCV27830265 2,187 0,9395.093 0,0697 0,03807 HCV27830265 3,032 1,42 6,474 0,0042 .HCV27830265 2,907 1,354 6,243 0,0062 0,01156 HCV27830265 4.1281.238 13.01156 HCV27830265 4.1281.238 13.01156 HCV27830265 4.1281.238 13.01156 HCV27830265 4.1281.238 13.01156 HCV27830265 4.1281.238 13.01156 HCV27830265 4.1281.238 13.01156. hCV27830265 4,048 1,205 13,592 0,0237 0,06695hCV1053082 2,424 1,101 5,338 0,028 . HCV1053082 2.412 1.089 5.3420.03 0.08891 HCV1053082 2.452 1.079 5.571 0,0322 0.08891 HCV10530822,519 1.057 6.004 0,0372 0,1133333333333333333333333333333333333333. hCV1053082 1,228 1,001 1,508 0,0494 . hCV1053082 2,3390,958 5,715 0,0622 0,11133 hCV1053082 1,233 0,972 1,564 0,084 .hCV1053082 2,443 1,139 5,24 0,0218 . hCV1053082 2,453 1,139 5,2820,0219 0,07158 hCV1053082 2,419 1,101 5,313 0,0278 0,07158

hCV1053082 1,306 1,002 1,703 0,0483 . hCV1053082 2,182 0,894 5,3240,0865 0,11774 hCV1053082 1,297 0,959 1,752 0,0909 . hCV10530822,441 1,274 4,675 0,0071 . HCV1053082 2.438 1.267 4,689 0,00760.02673 HCV1053082 2.449 1,249 4,801 0,0091 0.02673 HCV10530821.695 1,052 2.732 0,0302 0,08373737373737373737373737373737373737373737. hCV1053082 1,577 0,965 2,576 0,0691 0,08337 hCV10530821,152 0,989 1,343 0,0698 . HCV1053082 2.225 1,109 4,465 0,0244 .HCV1053082 2,282 1,109 4,692 0,025 0,07672 HCV1053082 2,202 1,0924,438 0,0274 0,07672 HCV1053082 1,715 1,006 0,924 0.04755053082 1,715 1,006 0,006 0.09505053082 1,715 1,006 0,006 0.099505053082 1,715 1,006 0,0924 0,04755053082 1,715 1,006 0,86 0,675.0952.052. hCV1053082 1,651 0,955 2,8550,0727 0,13875 hCV1053082 2,388 1,164 4,897 0,0175 . hCV10530822,451 1,164 5,163 0,0183 0,05761 hCV1053082 2,36 1,145 4,866 0,020,05761 hCV1053082 1,684 0,963 2,945 0,0673 . hCV1053082 1.69 0.9632.966 0.0674 0.18668 hCV1053082 1.672 0.939 2.977 0.0808 0.18668hCV1452085 2.844 0.95 8.517 0.0617 0.07446 hCV1452085 8.604 0.86385.766 0.0666 0.00063 hCV1452085 4.953 1.405 17.456 0.0128 0.01831hCV1452085 3.875 1.132 13.267 0.031 . hCV1452085 3.687 1.075 12.650.038 0.01831 hCV1452085 2.892 0.881 9.491 0.0798 0.03384hCV1452085 12.05 0.995 145.92 0.0505 0.02942 hCV302629 1.268 0.9821.638 0.0684 0.16605 hCV11474611 1.408 0.962 2.061 0.0785 0.15447hCV11474611 7.206 0.691 75.167 0.0988 0.25264 hCV11474611 7.1760.688 74.834 0.0995 . hCV1262973 1,33 0,99 1,789 0,0586 0,03312hCV27892569 1,569 1,022 2,409 0,0394 0,11153 hCV27892569 1,5140,996 2,303 0,0525 . hCV27892569 1,184 0,993 1,412 0,06 .hCV27892569 1,139 0,982 1,32 0,0847 . hCV27077072 1,253 0,99 1,5870,0605 . hCV27077072 1,308 0,967 1,77 0,0816 . hCV27077072 1,9520,901 4,23 0,0899 0,22584 hCV32160712 1,93 1,061 3,512 0,03130,0843 hCV32160712 1,872 1,034 3,391 0,0385 . hCV32160712 1,2130,988 1,489 0,0648 . hCV32160712 2.382 1.026 5.532 0.0435 .hCV32160712 2.361 1.011 5.513 0.047 0.12823 hCV32160712 1.563 0.9532.565 0.0772 0.1756 hCV32160712 1.529 0.935 2.502 0.0907 .hCV1619596 1.412 1.038 1.92 0.0281 0.08963 hCV1619596 1.362 1.0171.823 0.0382 . hCV1619596 1,168 0,982 1,389 0,0794 . hCV16195961,314 1,03 1,677 0,0281 . hCV1619596 1,33 1,029 1,719 0,02920,08594 hCV1619596 1,205 0,993 1,461 0,0586 . hCV1619596 1,2950,979 1,713 0,0699 . hCV1619596 1,298 0,967 1,741 0,0822 0,1932hCV1619596 1,271 1,001 1,612 0,0486 0,14298 hCV1619596 1,239 0,9891,554 0,0629. hCV1619596 1,125 0,985 1,284 0,0826 . hCV23582471,521 0,989 2,34 0,0561 . hCV2358247 1,527 0,987 2,363 0,05740,16029 hCV2358247 1,468 0,978 2,204 0,0636 . hCV29537898 1.3031.011 1.679 0.0406 0.06312 hCV29537898 1.258 0.98 1.614 0.0712 .hCV29537898 1.866 1.288 2.703 0.001 . hCV29537898 1,749 1,25 2,4480,0011 . hCV29537898 1,848 1,264 2,701 0,0015 0,00417 hCV17237181,543 0,928 2,565 0,0944 . hCV1723718 1,773 1,119 2,809 0,0147 .hCV1723718 1,632 1,011 2,633 0,045 0,02572

TABELLE-US-00021 TABELLE 21 ProbChi 95 % 95 % Sq (2- AD- GENO- Odds LowerUpper sided p- PVAL- hCV # rs # Gene ERGEBNIS JUST MODE TYPE RatioCL CL-Wert) UE_2DF hCV11548152 rs11580249 EO_STK AGE GEN TG 1.2310.899 1.686 0.1947 0.43131 MALE DIAB HTN hCV1958451 rs2985822 MIER1EO_STK DOM GT or 1.409 0.879 2.258 0.1545 -- GG hCV1958451rs2985822 MIER1 ISCHEMIC_STK GEN GT 1.279 0.909 1.8 0.1576 0.08689hCV1958451 rs2985822 MIER1 LACUNAR_STK DOM GT or 1.638 0.857 3.1310.1351 -- GG hCV1958451 rs2985822 MIER1 LACUNAR_STK AGE GEN GT1.734 0.753 3.995 0.196 0.39776 MALE DIAB HTN hCV1958451 rs2985822MIER1 NOHD_STK GEN GT 1.284 0.887 1.859 0.1849 0.03579 hCV1958451rs2985822 MIER1 NONCE_STK GEN GT 1.361 0.915 2.024 0.1281 0.13834hCV27494483 rs3748743 SLC22A15 CE_STK AGE GEN TC 1.433 0.867 2.3660.1602 0.27105 MALE DIAB HTN hCV27504565 rs3219489 MUTYHISCHEMIC_STK DOM CG or 1.305 0.896 1.901 0.1656 -- CC hCV27504565rs3219489 MUTYH NOHD_STK GEN CC 1.339 0.872 2.055 0.1821 0.11469hCV27504565 rs3219489 MUTYH NOHD_STK DOM CG or 1.407 0.922 2.1460.1129 -- CC hCV27504565 rs3219489 MUTYH NOHD_STK AGE GEN CC 1.5190.859 2.683 0.1503 0.18169 MALE DIAB HTN hCV27504565 rs3219489MUTYH NOHD_STK AGE DOM CG or 1.587 0.906 2.782 0.1066 -- MALE CCDIAB HTN hCV27504565 rs3219489 MUTYH NONCE_STK DOM CG or 1.3510.871 2.095 0.1786 -- CC hCV27504565 rs3219489 MUTYH NONCE_STK AGEDOM CG or 1.593 0.877 2.895 0.1265 -- MALE CC DIAB HTN hCV27504565rs3219489 MUTYH RECURRENT_STK AGE GEN CC 2.313 0.826 6.477 0.11060.15677 MALE DIAB HTN hCV31227848 rs11809423 HIVEP3 ATHERO_STK GENTC 1.404 0.927 2.128 0.1094 0.06604 hCV31227848 rs11809423 HIVEP3NOHD_STK GEN TC 1.284 0.889 1.853 0.1822 0.0563 hCV31227848rs11809423 HIVEP3 NONCE_STK GEN TC 1.327 0.908 1.939 0.1434 0.12332hCV454333 rs10916581 NVL RECURRENT_STK GEN CT 5.03 0.664 38.10.1179 0.09083 hCV454333 rs10916581 NVL RECURRENT_STK GEN CC 3.7780.504 28.32 0.1959 0.09083 hCV454333 rs10916581 NVL RECURRENT_STKDOM CT or 4.101 0.548 30.66 0.1692 -- CC hCV8754449 rs781226 TESK2NOHD_STK GEN CT 1.375 0.894 2.114 0.1474 0.25013 hCV8754449rs781226 TESK2 NOHD_STK AGE GEN CT 1.508 0.856 2.656 0.1552 0.34108MALE DIAB HTN hCV8754449 rs781226 TESK2 NONCE_STK AGE GEN CT 1.5360.841 2.803 0.1625 0.25117 MALE DIAB HTN hCV8754449 rs781226 TESK2RECURRENT_STK AGE GEN CC 2.321 0.83 6.495 0.1087 0.20413 MALE DIABHTN hCV2091644 rs1010 VAMP8 CE_STK GEN CC 1.287 0.933 1.776 0.12360.25285 hCV2091644 rs1010 VAMP8 CE_STK ADD C 1.114 0.952 1.3050.1788 -- hCV2091644 rs1010 VAMP8 EO_STK AGE GEN CT 1.238 0.9121.682 0.1714 0.34826 MALE DIAB HTN hCV2091644 rs1010 VAMP8ISCHEMIC_STK GEN CC 1.189 0.927 1.524 0.1731 0.28614 hCV2091644rs1010 VAMP8 ISCHEMIC_STK REC CC 1.198 0.957 1.499 0.115 --hCV2091644 rs1010 VAMP8 RECURRENT_STK AGE GEN CT 1.385 0.865 2.2160.1753 0.3581 MALE DIAB HTN hCV7425232 rs3900940 MYH15 EO_STK AGEDOM CT or 1.208 0.913 1.596 0.1853 -- MALE CC DIAB HTN hCV8820007rs938390 ATHERO_STK GEN TT 1.428 0.865 2.359 0.1639 0.18574hCV8820007 rs938390 ATHERO_STK DOM TA or 1.486 0.906 2.437 0.1171-- TT hCV8820007 rs938390 ATHERO_STK AGE GEN TA 1.603 0.846 3.0380.1475 0.28036 MALE DIAB HTN hCV8820007 rs938390 CE_STK GEN TA1.389 0.846 2.282 0.194 0.14033 hCV8820007 rs938390 EO_STK GEN TA1.523 0.889 2.609 0.1254 0.30388 hCV8820007 rs938390 EO_STK DOM TAor 1.432 0.862 2.379 0.1661 -- TT hCV8820007 rs938390 EO_STK AGEGEN TA 1.659 0.904 3.046 0.1025 0.25362 MALE DIAB HTN hCV8820007rs938390 EO_STK AGE GEN TT 1.463 0.818 2.616 0.1998 0.25362 MALEDIAB HTN hCV8820007 rs938390 EO_STK AGE DOM TA or 1.525 0.861 2.7040.1482 -- MALE TT DIAB HTN hCV8820007 rs938390 ISCHEMIC_STK AGE DOMTA or 1.382 0.871 2.194 0.1698 -- MALE TT DIAB HTN hCV8820007rs938390 NOHD_STK AGE GEN TT 1.434 0.856 2.403 0.1711 0.07825 MALEDIAB HTN hCV8820007 rs938390 NONCE_STK GEN TA 1.386 0.897 2.1420.1412 0.28065 hCV8820007 rs938390 NONCE_STK AGE GEN TA 1.555 0.8912.713 0.1203 0.27256 MALE DIAB HTN hCV8820007 rs938390 NONCE_STKAGE DOM TA or 1.431 0.845 2.423 0.1829 -- MALE TT DIAB HTNhCV8820007 rs938390 RECURRENT_STK GEN TA 1.702 0.812 3.567 0.15920.19862 hCV11354788 rs12644625 LOC729065 CE_STK AGE REC TT 2.2490.823 6.145 0.1141 -- MALE DIAB HTN hCV11354788 rs12644625LOC729065 EO_STK AGE GEN TT 2.129 0.727 6.236 0.1683 0.0564 MALEDIAB HTN hCV11354788 rs12644625 LOC729065 ISCHEMIC_STK AGE GEN TT1.8 0.759 4.269 0.1821 0.03661 MALE DIAB HTN hCV11354788 rs12644625LOC729065 NOHD_STK GEN TT 1.651 0.849 3.213 0.1397 0.02034hCV11354788 rs12644625 LOC729065 NOHD_STK REC TT 1.552 0.799 3.0150.1942 -- hCV11354788 rs12644625 LOC729065 NOHD_STK AGE GEN TT1.985 0.81 4.86 0.1337 0.06231 MALE DIAB HTN hCV11354788 rs12644625LOC729065 NOHD_STK AGE REC TT 1.86 0.761 4.543 0.1733 -- MALE DIABHTN hCV11354788 rs12644625 LOC729065 NONCE_STK ADD T 1.186 0.9671.454 0.1013 -- hCV11354788 rs12644625 LOC729065 NONCE_STK AGE GENTC 1.288 0.941 1.763 0.1139 0.25236 MALE DIAB HTN hCV11354788rs12644625 LOC729065 NONCE_STK AGE ADD T 1.261 0.955 1.666 0.102 --MALE DIAB HTN hCV15854171 rs2231137 ABCG2 CE_STK ADD C 1.357 0.8652.129 0.184 -- hCV16158671 rs2200733 ATHERO_STK AGE GEN TT 2.1330.724 6.287 0.1696 0.07966 MALE DIAB HTN hCV16158671 rs2200733CE_STK AGE REC TT 2.054 0.774 5.452 0.1483 -- MALE DIAB HTNhCV16158671 rs2200733 EO_STK AGE GEN TT 1.982 0.7 5.614 0.19760.07117 MALE DIAB HTN hCV16158671 rs2200733 ISCHEMIC_STK GEN TT1.506 0.815 2.783 0.1916 0.00631 hCV16158671 rs2200733 ISCHEMIC_STKAGE GEN TT 1.874 0.819 4.292 0.1372 0.03074 MALE DIAB HTNhCV16158671 rs2200733 ISCHEMIC_STK AGE REC TT 1.743 0.763 3.9820.1873 -- MALE DIAB HTN hCV16158671 rs2200733 NOHD_STK GEN TT 1.7050.898 3.238 0.1031 0.01299 hCV16158671 rs2200733 NOHD_STK REC TT1.599 0.844 3.032 0.1501 -- hCV16158671 rs2200733 NOHD_STK AGE RECTT 1.973 0.839 4.643 0.1195 -- MALE DIAB HTN hCV16158671 rs2200733NONCE_STK AGE GEN TC 1.275 0.93 1.747 0.1316 0.22725 MALE DIAB HTNhCV16336 rs362277 HD ATHERO_STK AGE ADD C 1.321 0.946 1.844 0.102-- MALE DIAB HTN hCV16336 rs362277 HD CE_STK DOM CT or 3.411 0.77714.97 0.104 -- CC hCV16336 rs362277 HD ISCHEMIC_STK GEN CC 1.8470.825 4.133 0.1354 0.00758 hCV16336 rs362277 HD ISCHEMIC_STK DOM CTor 1,751 0,783 3,914 0,1725 -- CC

hCV16336 rs362277 HD LACUNAR_STK AGE ADD C 1.368 0.892 2.097 0.1507-- MALE DIAB HTN hCV16336 rs362277 HD LACUNAR_STK AGE REC CC 1.3890.873 2.211 0.1656 -- MALE DIAB HTN hCV31137507 rs7660668 CLOCKLACUNAR_STK GEN CG 1.274 0.945 1.716 0.112 0.22027 hCV31137507rs7660668 CLOCK LACUNAR_STK DOM CG or 1.21 0.909 1.612 0.1921 -- CChCV26478797 rs2015018 CHSY-2 CE_STK ADD G 1.134 0.951 1.352 0.1602-- hCV26478797 rs2015018 CHSY-2 CE_STK AGE REC GG 1.233 0.921 1.6490.1593 -- MALE DIAB HTN hCV26478797 rs2015018 CHSY-2 NOHD_STK RECGG 1.132 0.944 1.358 0.1816 - - hCV26478797 rs2015018 CHSY-2RECURRENT_STK GEN GA 1.613 0.804 3.238 0.1787 0.30867 hCV26478797rs2015018 CHSY-2 RECURRENT_STK GEN GG 1.712 0.86 3.407 0.12550.30867 hCV26478797 rs2015018 CHSY-2 RECURRENT_STK DOM GA or 1.6680.85 3.272 0.137 -- GG hCV11425801 rs3805953 PEX6 ATHERO_STK AGEGEN CC 1.372 0.929 2.025 0.1116 0.0005 MALE DIAB HTN hCV11425801rs3805953 PEX6 CE_STK AGE GEN CT 1.287 0.913 1.812 0.1493 0.35182MALE DIAB HTN hCV11425801 rs3805953 PEX6 EO_STK GEN CC 1.254 0.9031.739 0.1764 0.00345 hCV11425801 rs3805953 PEX6 EO_STK ADD C 1.1330.961 1.335 0.1372 hCV11425801 rs3805953 PEX6 ISCHEMIC_STK GEN CC1 .202 0.958 1.508 0.1123 0.02335 hCV11425801 rs3805953 PEX6ISCHEMIC_STK AGE ADD C 1.116 0.959 1.3 0.1556 -- MALE DIAB HTNhCV11425801 rs3805953 PEX6 LACUNAR_STK DOM CT or 1.235 0.897 1.70.1959 -- CC hCV1142580 1 rs3805953 PEX6 NOHD_STK AGE GEN CC 1.2360.896 1.706 0.1968 0.00304 MALE DIAB HTN hCV11425801 rs3805953 PEX6NOHD_STK AGE ADD C 1.124 0.958 1.32 0.1525 -- MALE DIAB HTNhCV11425801 rs3805953 PEX6 NONCE_STK AGE GEN CC 1.276 0.898 1.8130.1732 0.00005 MALE DIAB HTN hCV11425801 rs3805953 PEX6 NONCE_STKAGE ADD C 1.147 0.963 1.365 0.1237 -- MALE DIAB HTN hCV11425801rs3805953 PEX6 RECURRENT_STK DOM CT or 1.28 0.912 1.798 0.1535 --CC hCV11425801 rs3805953 PEX6 RECURRENT_STK AGE DOM CT or 1.4030.885 2.225 0.1498 -- MALE CC DIAB HTN hCV11425842 rs10948059 GNMTATHERO_STK GEN CC 1.263 0.927 1.722 0.1392 0.19224 hCV11425842rs10948059 GNMT ATHERO_STK ADD C 1.109 0.953 1.29 0.1815 -- hCV11425842 rs10948059 GNMT ATHERO_STK AGE ADD C 1.178 0.964 1.4390.1101 -- MALE DIAB HTN hCV11425842 rs10948059 GNMT CE_STK AGE DOMCT or 1.272 0.898 1.8 0.1751 -- MALE CC DIAB HTN hCV11425842rs10948059 GNMT EO_STK ADD C 1.141 0.964 1.352 0.126 -- hCV11425842rs10948059 GNMT EO_STK AGE GEN CC 1.302 0.883 1.92 0.1827 0.08575MALE DIAB HTN hCV11425842 rs10948059 GNMT ISCHEMIC_STK AGE GEN CC1.27 0.925 1.743 0.1389 0.1427 MALE DIAB HTN hCV11425842 rs10948059GNMT ISCHEMIC_STK AGE ADD C 1.113 0.951 1.303 0.1836 -- MALE DIABHTN hCV11425842 rs10948059 GNMT NOHD_STK AGE GEN CT 1.279 0.9381.745 0.1197 0.26094 MALE DIAB HTN hCV11425842 rs10948059 GNMTNOHD_STK AGE GEN CC 1.266 0.905 1.772 0.1686 0.26094 MALE DIAB HTNhCV11425842 rs10948059 GNMT NOHD_STK AGE DOM CT or 1.274 0.9531.703 0.1015 -- MALE CC DIAB HTN hCV11425842 rs10948059 GNMTNONCE_STK GEN CT 1.195 0.932 1.531 0.1595 0.35697 hCV11425842rs10948059 GNMT NONCE_STK DOM CT or 1.184 0.938 1.495 0.1556 -- CChCV11425842 rs10948059 GNMT NONCE_STK AGE GEN CC 1.294 0.9 1.8610.1646 0.10566 MALE DIAB HTN hCV16134786 rs2857595 EO_STK GEN AG1.207 0.929 1.568 0.1593 0.0477 hCV16134786 rs2857595 EO_STK AGEADD A 1.185 0.934 1.504 0.1629 -- MALE DIAB HTN hCV16134786rs2857595 ISCHEMIC_STK GEN AA 1.406 0.933 2.119 0.103 0.26366hCV16134786 rs2857595 ISCHEMIC_STK REC AA 1.392 0.928 2.088 0.1098-- hCV16134786 rs2857595 ISCHEMIC_STK AGE ADD A 1.154 0.949 1.4020.1516 -- MALE DIAB HTN hCV16134786 rs2857595 LACUNAR_STK AGE GENAA 1.77 0.809 3.873 0.153 0.27205 MALE DIAB HTN hCV16134786rs2857595 LACUNAR_STK AGE ADD A 1.272 0.943 1.717 0.1157 -- MALEDIAB HTN hCV16134786 rs2857595 LACUNAR_STK AGE DOM AG or 1.2870.889 1.863 0.182 -- MALE AA DIAB HTN hCV16134786 rs2857595NONCE_STK DOM AG or 1.151 0.947 1.399 0.1584 -- AA hCV16134786rs2857595 NONCE_STK REC AA 1.448 0.924 2.268 0.1062 -- hCV25651109rs35690712 SLC39A7 EO_STK GEN GC 5.189 0.556 48.4 0.1484 0.34485hCV25651109 rs35690712 SLC39A7 EO_STK GEN GG 4.668 0.52 41.920.1689 0.34485 hCV25651109 rs35690712 SLC39A7 EO_STK DOM GC or4.709 0.525 42.28 0.1664 -- GG hCV25651109 rs35690712 SLC39A7ISCHEMIC_STK AGE GEN GC 4.69 0.505 43.57 0.1742 0.39506 MALE DIABHTN hCV25651109 rs35690712 SLC39A7 ISCHEMIC_STK AGE GEN GG 4.3720.486 39.35 0.1882 0.39506 MALE DIAB HTN hCV25651109 rs35690712SLC39A7 ISCHEMIC_STK AGE DOM GC or 4.398 0.489 39.56 0.1864 -- MALEGG DIAB HTN hCV25651109 rs35690712 SLC39A7 NONCE_STK GEN GC 4.5250.542 37.77 0.1632 0.26183 hCV25651109 rs35690712 SLC39A7 NONCE_STKGEN GG 5.073 0.623 41.3 0.129 0.26183 hCV25651109 rs35690712SLC39A7 NONCE_STK ADD G 1.239 0.895 1.713 0.1962 -- hCV25651109rs35690712 SLC39A7 NONCE_STK DOM GC or 5.026 0.618 40.91 0.1312 --GG hCV30308202 rs9482985 LAMA2 CE_STK ADD G 1.168 0.958 1.4230.1237 -- hCV30308202 rs9482985 LAMA2 CE_STK REC GG 1.179 0.9361.484 0.1621 -- hCV30308202 rs9482985 LAMA2 CE_STK AGE GEN GC 1.7240.779 3.815 0.1792 0.26508 MALE DIAB HTN hCV30308202 rs9482985LAMA2 CE_STK AGE GEN GG 1.878 0.867 4.07 0.1103 0.26508 MALE DIABHTN hCV30308202 rs9482985 LAMA2 CE_STK AGE ADD G 1.19 0.92 1.540.1851 -- MALE DIAB HTN hCV30308202 rs9482985 LAMA2 CE_STK AGE DOMGC or 1.825 0.848 3.929 0.124 -- MALE GG DIAB HTN hCV30308202rs9482985 LAMA2 RECURRENT_STK DOM GC or 2.236 0.795 6.289 0.1272 --GG hCV30308202 rs9482985 LAMA2 RECURRENT_STK AGE ADD G 1.379 0.942.022 0.1002 -- MALE DIAB HTN hCV3082219 rs1884833 RFXDC1 EO_STKGEN AG 1.217 0.909 1.628 0.1874 0.16147 hCV3082219 rs1884833 RFXDC1EO_STK GEN AA 2.194 0.766 6.286 0.1434 0.16147 hCV3082219 rs1884833RFXDC1 EO_STK DOM AG or 1.262 0.949 1.677 0.1091 -- AA hCV3082219rs1884833 RFXDC1 EO_STK REC AA 2.096 0.733 5.993 0.1672 --hCV3082219 rs1884833 RFXDC1 LACUNAR_STK GEN AA 2.024 0.703 5.8240.1911 0.07365 hCV3082219 rs1884833 RFXDC1 LACUNAR_STK AGE GEN AA2.876 0.735 11.26 0.1292 0.25425 MALE DIAB HTN hCV3082219 rs1884833RFXDC1 LACUNAR_STK AGE ADD A 1.288 0.89 1.865 0.18 -- MALE DIAB HTNhCV3082219 rs1884833 RFXDC1 LACUNAR_STK AGE REC AA 2.755 0.70610.75 0.1444 -- MALE DIAB HTN hCV3082219 rs1884833 RFXDC1 NOHD_STKGEN AA 1.762 0.835 3.717 0.137 0.20951 hCV3082219 rs1884833 RFXDC1NOHD_STK ADD A 1.171 0.965 1.421 0.11 -- hCV3082219 rs1884833RFXDC1 NOHD_STK DOM AG or 1.158 0.935 1.432 0.1783 --

AA hCV3082219 rs1884833 RFXDC1 NOHD_STK REC AA 1.715 0.814 3.6120.1557 -- hCV3082219 rs1884833 RFXDC1 NOHD_STK AGE GEN AA 1.980.711 5.513 0.1912 0.41847 MALE DIAB HTN hCV3082219 rs1884833RFXDC1 NOHD_STK AGE REC AA 1.961 0.706 5.45 0.1964 -- MALE DIAB HTNhCV8942032 rs1264352 DDR1 ATHERO_STK AGE GEN CG 1.315 0.937 1.8460.1128 0.23534 MALE DIAB HTN hCV8942032 rs1264352 DDR1 ATHERO_STKAGE DOM CG or 1.257 0.906 1.744 0.1707 -- MALE CC DIAB HTNhCV8942032 rs1264352 DDR1 CE_STK AGE GEN CG 1.299 0.916 1.8420.1424 0.29178 MALE DIAB HTN hCV8942032 rs1264352 DDR1 CE_STK AGEADD C 1.251 0.938 1.669 0.1269 -- MALE DIAB HTN hCV8942032rs1264352 DDR1 CE_STK AGE DOM CG or 1.307 0.935 1.826 0.1175 --MALE CC DIAB HTN hCV8942032 rs1264352 DDR1 ISCHEMIC_STK ADD C 1.1190.948 1.321 0.1832 -- hCV8942032 rs1264352 DDR1 LACUNAR_STK AGE GENCC 2.104 0.743 5.961 0.1614 0.01502 MALE DIAB HTN hCV8942032rs1264352 DDR1 NOHD_STK DOM CG or 1.16 0.942 1.43 0.163 -- CChCV8942032 rs1264352 DDR1 NOHD_STK AGE ADD C 1.211 0.951 1.5410.1206 -- MALE DIAB HTN hCV8942032 rs1264352 DDR1 NONCE_STK ADD C1.142 0.948 1.375 0.1628 -- hCV25596936 rs6967117 EPHA1 ATHERO_STKADD T 1.215 0.95 1.552 0.1207 -- hCV25596936 rs6967117 EPHA1ISCHEMIC_STK DOM TC or 1.181 0.941 1.482 0.1522 -- TT hCV25596936rs6967117 EPHA1 LACUNAR_STK DOM TC or 1.352 0.937 1.951 0.1065 --TT hCV25596936 rs6967117 EPHA1 NOHD_STK DOM TC or 1.226 0.961 1.5660.1014 -- TT hCV29401764 rs7793552 LOC646588 ATHERO_STK AGE DOM CTor 1.501 0.896 2.513 0.123 -- MALE CC DIAB HTN hCV15857769rs2924914 ATHERO_STK AGE ADD T 1.193 0.963 1.479 0.1061 -- MALEDIAB HTN hCV15857769 rs2924914 ATHERO_STK AGE REC TT 1.456 0.922.305 0.1089 -- MALE DIAB HTN hCV15857769 rs2924914 NOHD_STK ADD T1.12 0.975 1.287 0.1103 -- hCV15857769 rs2924914 RECURRENT_STK AGEADD T 1.255 0.909 1.731 0.167 -- MALE DIAB HTN hCV29539757rs10110659 KCNQ3 ATHERO_STK GEN CA 1.362 0.902 2.058 0.1417 0.31708hCV29539757 rs10110659 KCNQ3 ATHERO_STK DOM CA or 1.297 0.875 1.9250.1957 -- CC hCV29539757 rs10110659 KCNQ3 LACUNAR_STK GEN CA 1.4530. 843 2.504 0.1789 0.08401 hCV29539757 rs10110659 KCNQ3 NONCE_STKDOM CA or 1.283 0.909 1.81 0.1572 -- CC hCV1348610 rs3739636C9orf46 ATHERO_STK AGE GEN AG 1.304 0.945 1.799 0.1062 0.25491 MALEDIAB HTN hCV1348610 rs3739636 C9orf46 ATHERO_STK AGE DOM AG or1.242 0.918 1.682 0.1605 -- MALE AA DIAB HTN hCV1348610 rs3739636C9orf46 CE_STK AGE GEN AG 1.24 0.895 1.719 0.1962 0.39368 MALE DIABHTN hCV1348610 rs3739636 C9orf46 CE_STK AGE DOM AG or 1.238 0.9111.682 0.1722 -- MALE AA DIAB HTN hCV1348610 rs3739636 C9orf46NOHD_STK AGE DOM AG or 1.217 0.944 1.569 0.1306 -- MALE AA DIAB HTNhCV1348610 rs3739636 C9orf46 NONCE_STK AGE DOM AG or 1.226 0.9331.61 0.144 -- MALE AA DIAB HTN hCV1754669 rs2383206 C9P21ATHERO_STK AGE REC GG 1.277 0.913 1.784 0.1528 -- MALE DIAB HTNhCV1754669 rs2383206 C9P21 NONCE_STK AGE REC GG 1.227 0.906 1.6620.187 -- MALE DIAB HTN hCV26505812 rs10757274 C9P21 ISCHEMIC_STKAGE REC GG 1.207 0.912 1.599 0.1887 -- MALE DIAB HTN hCV26505812rs10757274 C9P21 NOHD_STK AGE REC GG 1.238 0.918 1.669 0.1611 --MALE DIAB HTN hCV26505812 rs10757274 C9P21 NONCE_STK AGE GEN GG1.297 0.893 1.884 0.1714 0.23096 MALE DIAB HTN hCV15752716rs2296436 HPS1 CE_STK ADD T 1.242 0.914 1.686 0.1656 -- hCV15752716rs2296436 HPS1 CE_STK REC TT 1.284 0.928 1.778 0.1311 -- hCV2169762rs1804689 HPS1 ATHERO_STK GEN TT 1.293 0.914 1.829 0.1461 0.33606hCV2169762 rs1804689 HPS1 ATHERO_STK REC TT 1.282 0.92 1.787 0.1422-- hCV2169762 rs1804689 HPS1 ATHERO_STK AGE GEN TT 1.446 0.9022.316 0.1255 0.27749 MALE DIAB HTN hCV2169762 rs1804689 HPS1ATHERO_STK AGE REC TT 1.447 0.92 2.276 0.1093 -- MALE DIAB HTNhCV2169762 rs1804689 HPS1 EO_STK AGE GEN TT 1.49 0.926 2.397 0.10030.2272 MALE DIAB HTN hCV2169762 rs1804689 HPS1 ISCHEMIC_STK GEN TT1.22 0.921 1.617 0.1658 0.04864 hCV2169762 rs1804689 HPS1LACUNAR_STK GEN TG 1.273 0.941 1.721 0.1172 0.29125 hCV2169762rs1804689 HPS1 LACUNAR_STK DOM TG or 1.235 0.927 1.644 0.1491 -- TThCV2169762 rs1804689 HPS1 LACUNAR_STK AGE GEN TG 1.345 0.919 1.970.1275 0.23974 MALE DIAB HTN hCV2169762 rs1804689 HPS1 LACUNAR_STKAGE ADD T 1.246 0.953 1.63 0.1085 -- MALE DIAB HTN hCV2169762rs1804689 HPS1 NOHD_STK AGE REC TT 1.351 0.914 1.999 0.1317 -- MALEDIAB HTN hCV2169762 rs1804689 HPS1 NONCE_STK GEN TT 1.229 0.8971.683 0.1999 0.37015 hCV2169762 rs1804689 HPS1 NONCE_STK ADD T1.106 0.961 1.272 0.1591 -- hCV2169762 rs1804689 HPS1 NONCE_STK AGEDOM TG or 1.193 0.923 1.541 0.1783 -- MALE TT DIAB HTN hCV27830265rs12762303 ALOX5 ATHERO_STK DOM GA or 1.204 0.956 1.515 0.1143 --GG hCV27830265 rs12762303 ALOX5 ATHERO_STK AGE GEN GA 1.275 0.9281.752 0.1331 0.04449 MALE DIAB HTN hCV27830265 rs12762303 ALOX5CE_STK GEN GG 1.591 0.788 3.212 0.1954 0.27948 hCV27830265rs12762303 ALOX5 CE_STK REC GG 1.637 0.813 3.293 0.1673 --hCV27830265 rs12762303 ALOX5 CE_STK AGE REC GG 1.967 0.73 5.3020.1811 -- MALE DIAB HTN hCV27830265 rs12762303 ALOX5 EO_STK GEN GG1.724 0.758 3.92 0.1937 0.27237 hCV27830265 rs12762303 ALOX5 EO_STKADD G 1.201 0.951 1.517 0.1236 -- hCV27830265 rs12762303 ALOX5EO_STK DOM GA or 1.194 0.919 1.551 0.1835 -- GG hCV27830265rs12762303 ALOX5 ISCHEMIC_STK AGE DOM GA or 1.211 0.948 1.5470.1246 -- MALE GG DIAB HTN hCV27830265 rs12762303 ALOX5 LACUNAR_STKGEN GA 1.242 0.911 1.692 0.1704 0.30411 hCV27830265 rs12762303ALOX5 LACUNAR_STK ADD G 1.237 0.944 1.621 0.1228 -- hCV27830265rs12762303 ALOX5 LACUNAR_STK DOM GA or 1.258 0.93 1.701 0.1365 --GG hCV27830265 rs12762303 ALOX5 LACUNAR_STK AGE GEN GA 1.371 0.9242.032 0.1169 0.17426 MALE DIAB HTN hCV27830265 rs12762303 ALOX5NOHD_STK ADD G 1.146 0.963 1.364 0.1236 -- hCV27830265 rs12762303ALOX5 NOHD_STK AGE GEN GA 1.204 0.92 1.575 0.1757 0.16102 MALE DIABHTN hCV27830265 rs12762303 ALOX5 NOHD_STK AGE GEN GG 1.82 0.8234.024 0.1389 0.16102 MALE DIAB HTN hCV27830265 rs12762303 ALOX5NOHD_STK AGE DOM GA or 1.244 0.958 1.615 0.1015 -- MALE GG DIAB HTNhCV27830265 rs12762303 ALOX5 NOHD_STK AGE REC GG 1.722 0.783 3.7870.1768 -- MALE

DIAB HTN hCV27830265 rs12762303 ALOX5 NONCE_STK GEN GA 1.16 0.941.432 0.166 0.02459 hCV27830265 rs12762303 ALOX5 NONCE_STK AGE RECGG 1.999 0.864 4.627 0.1056 -- MALE DIAB HTN hCV1053082 rs544115NEU3 ATHERO_STK GEN CC 1.629 0.864 3.07 0.1313 0.29853 hCV1053082rs544115 NEU3 ATHERO_STK ADD C 1.139 0.935 1.387 0.1971 -- hCV1053082 rs544115 NEU3 ATHERO_STK DOM CT or 1.597 0.851 2.9970.1454 -- CC hCV1053082 rs544115 NEU3 CE_STK GEN CC 1.702 0.8853.27 0.1107 0.13598 hCV1053082 rs544115 NEU3 CE_STK DOM CT or 1.6180.845 3.097 0.1466 -- CC hCV1053082 rs544115 NEU3 CE_STK AGE ADD C1. 237 0.945 1.619 0.1224 -- MALE DIAB HTN hCV1053082 rs544115 NEU3EO_STK ADD C 1.172 0.933 1.471 0.172 -- hCV1053082 rs544115 NEU3EO_STK AGE DOM CT or 2.054 0.846 4.982 0.1115 -- MALE CC DIAB HTNhCV1053082 rs544115 NEU3 ISCHEMIC_STK REC CC 1.125 0.942 1.3440.1924 -- hCV1053082 rs544115 NEU3 ISCHEMIC_STK AGE ADD C 1.1640.943 1.436 0.1567 -- MALE DIAB HTN hCV1053082 rs544115 NEU3LACUNAR_STK GEN CT 2.025 0.775 5.292 0.1499 0.33773 hCV1053082rs544115 NEU3 LACUNAR_STK DOM CT or 1.895 0.742 4.839 0.1815 -- CChCV1053082 rs544115 NEU3 LACUNAR_STK AGE GEN CT 2.148 0.723 6.380.1685 0.38668 MALE DIAB HTN hCV1053082 rs544115 NEU3 LACUNAR_STKAGE DOM CT or 2.036 0.708 5.851 0.1868 -- MALE CC DIAB HTNhCV1053082 rs544115 NEU3 NOHD_STK ADD C 1.128 0.954 1.333 0.1577 --hCV1452085 rs12223005 TRIM22 CE_STK GEN CA 3.193 0.705 14.47 0.13210.27397 hCV1452085 rs12223005 TRIM22 CE_STK GEN CC 2.843 0.63812.66 0.1703 0.27397 hCV1452085 rs12223005 TRIM22 CE_STK DOM CA or2.902 0.652 12.91 0.1619 -- CC hCV1452085 rs12223005 TRIM22 CE_STKAGE GEN CA 4.133 0.74 23.07 0.1058 0.25417 MALE DIAB HTN hCV1452085rs12223005 TRIM22 CE_STK AGE GEN CC 3.631 0.67 19.68 0.1347 0.25417MALE DIAB HTN hCV1452085 rs12223005 TRIM22 CE_STK AGE DOM CA or3.711 0.686 20.07 0.1279 -- MALE CC DIAB HTN hCV1452085 rs12223005TRIM22 EO_STK GEN CA 2.362 0.762 7.322 0.1364 0.26957 hCV1452085rs12223005 TRIM22 EO_STK DOM CA or 2.075 0.691 6.232 0.1935 -- CChCV1452085 rs12223005 TRIM22 ISCHEMIC_STK GEN CA 1.97 0.824 4.7140. 1275 0.08218 hCV1452085 rs12223005 TRIM22 ISCHEMIC_STK AGE GEN CC2.207 0.757 6.44 0.1472 0.07446 MALE DIAB HTN hCV1452085 rs12223005TRIM22 ISCHEMIC_STK AGE DOM CA or 2.31 0.793 6.727 0.1247 -- MALECC DIAB HTN hCV1452085 rs12223005 TRIM22 LACUNAR_STK GEN CA 4.4310.568 34.58 0.1556 0.00441 hCV1452085 rs12223005 TRIM22 LACUNAR_STKAGE DOM CA or 4.519 0.471 43.37 0.1911 -- MALE CC DIAB HTNhCV1452085 rs12223005 TRIM22 NOHD_STK GEN CA 2.418 0.843 6.9320.1004 0.16487 hCV1452085 rs12223005 TRIM22 NOHD_STK GEN CC 2.0820.739 5.866 0.1655 0.16487 hCV1452085 rs12223005 TRIM22 NOHD_STKDOM CA or 2.138 0.759 6.02 0.1502 -- CC hCV1452085 rs12223005TRIM22 RECURRENT_STK AGE GEN CC 6.513 0.564 75.15 0.1332 0.02942MALE DIAB HTN hCV1452085 rs12223005 TRIM22 RECURRENT_STK AGE DOM CAor 7.075 0.618 80.97 0.1157 -- MALE CC DIAB HTN hCV302629 rs9284183UBAC2 EO_STK DOM GA or 1.217 0.954 1.553 0.1137 -- GG hCV302629rs9284183 UBAC2 EO_STK AGE GEN GA 1.219 0.91 1.633 0.1853 0.37831MALE DIAB HTN hCV302629 rs9284183 UBAC2 EO_STK AGE ADD G 1.1560.927 1.442 0.1987 -- MALE DIAB HTN hCV302629 rs9284183 UBAC2EO_STK AGE DOM GA or 1.219 0.923 1.611 0.1632 -- MALE GG DIAB HTNhCV11474611 rs3814843 CALM1 ATHERO_STK DOM GT or 1.345 0.925 1.9560 .1207 -- GG hCV11474611 rs3814843 CALM1 ISCHEMIC_STK GEN GT 1.2820.939 1.748 0.1173 0.13174 hCV11474611 rs3814843 CALM1 ISCHEMIC_STKDOM GT or 1.222 0.902 1.656 0.1959 -- GG hCV11474611 rs3814843CALM1 NOHD_STK GEN GT 1.32 0.946 1.842 0.1021 0.1136 hCV11474611rs3814843 CALM1 NOHD_STK DOM GT or 1.251 0.902 1.735 0.1789 -- GGhCV11474611 rs3814843 CALM1 NONCE_STK GEN GT 1.328 0.939 1.8770.1082 0.1417 hCV11474611 rs3814843 CALM1 NONCE_STK DOM GT or 1.2610.898 1.772 0.1806 -- GG hCV11474611 rs3814843 CALM1 RECURRENT_STKGEN GT 1.526 0.916 2.544 0.1047 0.2681 hCV11474611 rs3814843 CALM1RECURRENT_STK DOM GT or 1.429 0.86 2.374 0.168 - - GG hCV1262973rs229653 PLEKHG3 ISCHEMIC_STK GEN AG 1.186 0.939 1.499 0.15230.00405 hCV1262973 rs229653 PLEKHG3 RECURRENT_STK GEN AG 1.33 0.8931.982 0.1605 0.3735 hCV27892569 rs4903741 NRXN3 CE_STK DOM CT or1.171 0.936 1.466 0.1674 -- CC hCV27892569 rs4903741 NRXN3LACUNAR_STK GEN CT 1.273 0.943 1.719 0.1153 0.28645 hCV27892569rs4903741 NRXN3 LACUNAR_STK DOM CT or 1.241 0.93 1.656 0.143 -- CChCV27892569 rs4903741 NRXN3 NOHD_STK GEN CC 1.333 0.917 1.9390.1323 0.22016 hCV27892569 rs4903741 NRXN3 NOHD_STK DOM CT or 1.1530.958 1.388 0.1327 -- CC hCV27892569 rs4903741 NRXN3 NOHD_STK RECCC 1.278 0.885 1.845 0.191 -- hCV27077072 rs8060368 RECURRENT_STKGEN CC 1.564 0.889 2.75 0.1205 0.17139 hCV27077072 rs8060368RECURRENT_STK AGE ADD C 1.308 0.947 1.806 0.1032 -- MALE DIAB HTNhCV27077072 rs8060368 RECURRENT_STK AGE DOM CT or 1.798 0.854 3.7860.1226 -- MALE CC DIAB HTN hCV2769503 rs4787956 CE_STK GEN GA 1.1710.924 1.484 0.1909 0.3088 hCV2769503 rs4787956 CE_STK ADD G 1.1310.961 1.331 0.1373 -- hCV2769503 rs4787956 CE_STK DOM GA or 1.1870.948 1.485 0.1354 -- GG hCV2769503 rs4787956 RECURRENT_STK GEN GA1.27 0.919 1.753 0.1471 0.27579 hCV31573621 rs11079818 SKAP1ATHERO_STK REC TT 1.165 0.939 1.445 0.1653 -- hCV31573621rs11079818 SKAP1 LACUNAR_STK AGE GEN TC 1.614 0.78 3.341 0.19730.13048 MALE DIAB HTN hCV32160712 rs11079160 CE_STK DOM TA or 1.1810.928 1.501 0.1761 -- TT hCV32160712 rs11079160 CE_STK AGE GEN TT1.93 0.872 4.27 0.1047 0.26509 MALE DIAB HTN hCV32160712 rs11079160CE_STK AGE REC TT 1.896 0.862 4.17 0.1116 -- MALE DIAB HTNhCV32160712 rs11079160 EO_STK GEN TT 1.734 0.829 3.629 0.1440.19059 hCV32160712 rs11079160 EO_STK REC TT 1.8 0.864 3.751 0.1167-- hCV32160712 rs11079160 ISCHEMIC_STK ADD T 1.137 0.972 1.330.1085 -- hCV32160712 rs11079160 ISCHEMIC_STK AGE GEN TT 1.6750.848 3.308 0.1373 0.31696 MALE DIAB HTN hCV32160712 rs11079160ISCHEMIC_STK AGE REC TT 1.646 0.837 3.237 0.1488 -- MALE DIAB HTNhCV32160712 rs11079160 NOHD_STK GEN TT 1.509 0.886 2.57 0.13030.30893 hCV32160712 rs11079160 NOHD_STK REC TT 1.49 0.878 2.5310.1396 -- hCV32160712 rs11079160 RECURRENT_STK GEN TT 1.887 0.8654.117 0.1107 0.28017 hCV32160712 rs11079160 RECURRENT_STK REC TT1.87 0.863 4.056 0.1128 -- hCV32160712 rs11079160 RECURRENT_STK AGEGEN TT 2.044 0.706 5.92 0.1878 0.41924 MALE DIAB HTN hCV32160712rs11079160 RECURRENT_STK AGE REC TT 2.029 0.706 5.827 0.1887 --MALE DIAB HTN hCV1408483 rs17070848 BCL2 ATHERO_STK GEN TT 1.5140.894 2.564 0.1231 0.29337 hCV1408483 rs17070848 BCL2 ATHERO_STKREC TT 1.487 0.882 2.505 0.1364 -- hCV1619596 rs1048621 SDCBP2CE_STK GEN AG 1.176 0.932 1.483 0.1731 0.21433 hCV1619596 rs1048621SDCBP2 CE_STK GEN AA 1.35 0.888 2.055 0.1607 0.21433 hCV1619596rs1048621 SDCBP2 CE_STK DOM AG or 1.203 0.964 1.501 0.1025 -- AAhCV1619596 rs1048621 SDCBP2 CE_STK AGE ADD A 1.204 0.959 1.51 0.109-- MÄNNLICHER DIAB HTN hCV1619596 rs1048621 SDCBP2 EO_STK AGE ADD A 1.2020.965 1.497 0.101 -- MÄNNLICHER DIAB HTN

hCV1619596 rs1048621 SDCBP2 ISCHEMIC_STK GEN AG 1.127 0.945 1.3440.1838 0.22154 hCV1619596 rs1048621 SDCBP2 ISCHEMIC_STK GEN AA1.261 0.909 1.748 0.1644 0.22154 hCV1619596 rs1048621 SDCBP2ISCHEMIC_STK DOM AG or 1.148 0.97 1.357 0.1079 -- AA hCV1619596rs1048621 SDCBP2 ISCHEMIC_STK AGE ADD A 1.139 0.954 1.36 0.1508 --MALE DIAB HTN hCV1619596 rs1048621 SDCBP2 NOHD_STK GEN AA 1.2670.89 1.804 0.1884 0.27789 hCV1619596 rs1048621 SDCBP2 NOHD_STK ADDA 1.125 0.974 1.299 0.1095 -- hCV1619596 rs1048621 SDCBP2 NOHD_STKDOM AG or 1.146 0.955 1.375 0.1442 -- AA hCV1619596 rs1048621SDCBP2 NOHD_STK AGE GEN AG 1.217 0.944 1.569 0.1302 0.29766 MALEDIAB HTN hCV1619596 rs1048621 SDCBP2 NOHD_STK AGE ADD A 1.14 0.9441.376 0.1722 -- MALE DIAB HTN hCV1619596 rs1048621 SDCBP2 NOHD_STKAGE DOM AG or 1.21 0.951 1.541 0.1208 -- MALE AA DIAB HTNhCV1619596 rs1048621 SDCBP2 RECURRENT_STK GEN AG 1.23 0.896 1.6890.1998 0.42372 hCV1619596 rs1048621 SDCBP2 RECURRENT_STK DOM AG or1.224 0.904 1.658 0.1917 -- AA hCV1619596 rs1048621 SDCBP2RECURRENT_STK AGE GEN AG 1.334 0.86 2.07 0.1987 0.41241 MALE DIABHTN hCV29537898 rs6073804 NOHD_STK ADD T 1.194 0.943 1.511 0.1415-- hCV29537898 rs6073804 RECURRENT_STK AGE GEN TT 5.809 0.6 56.260.1288 0.23964 MALE DIAB HTN hCV29537898 rs6073804 RECURRENT_STKAGE REC TT 5.608 0.578 54.4 0.1369 -- MALE DIAB HTN hCV1723718rs12481805 UMODL1 EO_STK REC AA 1.45 0.917 2.293 0.1118 --hCV1723718 rs12481805 UMODL1 ISCHEMIC_STK REC AA 1.254 0.922 1.7060.1498 -- hCV1723718 rs12481805 UMODL1 LACUNAR_STK AGE REC AA 1.5450.838 2.848 0.1633 -- MALE DIAB HTN hCV1723718 rs12481805 UMODL1NOHD_STK REC AA 1.316 0.947 1.829 0.1019 -- hCV1723718 rs12481805UMODL1 NONCE_STK REC AA 1.33 0.945 1.872 0.1017 -- hCV1723718rs12481805 UMODL1 RECURRENT_STK AGE GEN AG 1.349 0.867 2.098 0.1850.37072 MALE DIAB HTN hCV1723718 rs12481805 UMODL1 RECURRENT_STKAGE ADD A 1.239 0.897 1,711 0,1934 – MÄNNLICH DIAB HTN hCV1723718rs12481805 UMODL1 RECURRENT_STK ALTER DOM AG oder 1,352 0,889 2,0560,159 – MÄNNLICH AA DIAB HTN

TABLE-US-00022 TABLE 22 Gene GENO Risk hCV # rs # Symbol ENDPT MODESTRATA ADJUST TYPE Genotype hCV16336 r5362277 HD ENDPT4F1 GEN ALLSTATIN TC CC hCV16336 r5362277 HD ENDPT4F1 DOM ALL STATIN TC + TTCC hCV16336 r5362277 HD ENDPT4F1 ADD ALL STATIN T CC hCV32160712rs11079160 ENDPT4F1 GEN ALL STATIN TT TT hCV32160712 rs11079160ENDPT4F1 REC ALL STATIN TT TT hCV32160712 rs11079160 ENDPT4F1 ADDALL STATIN T TT hCV16134786 r52857595 ENDPT4F1 REC ALL AA AAhCV1619596 rs1048621 SDCBP2 ENDPT4F1 GEN ALL AA AG or AA hCV1619596rs1048621 SDCBP2 ENDPT4F1 REC ALL AA AG or AA hCV32160712rs11079160 ENDPT4F1 GEN ALL TT TT hCV32160712 RS11079160 ENDPT4F1DOM ALL TA + TT TT TT HCV32160712 RS11079160 ENDPT4F1 REC All TTHCV32160712 RS11079160 ENDPT4F1 ADFET TT TT 95% 95% HCV. 0.444 1.115 0.1341 0.3256 hCV16336r5362277 23 526 0.72 0.462 1.12 0.1447 -- hCV16336 r5362277 -- --0.76 0.507 1.14 0.1848 -- hCV32160712 rs11079160 8 83 1.88 0.9143.853 0.0866 0.221 hCV32160712 rs11079160 8 83 1.82 0.895 3.7140.0981 -- hCV32160712 rs11079160 -- -- 1.21 0.918 1.604 0.1746 --hCV16134786 r52857595 5 45 1.92 0.778 4.735 0.1569 -- hCV1619596rs1048621 12 115 1.69 0.894 3.195 0.1065 0.1552 hCV1619596rs1048621 12 115 1.78 0.97 3.274 0.0627 -- hCV32160712 rs11079160 637 3.09 1.33 7.19 0.0088 0.0281 hCV32160712 rs11079160 34 428 1.410.917 2,164 0,1172 -- hCV32160712 rs11079160 6 37 2,87 1,253 6,5850.0126 -- hCV32160712 rs11079160 -- -- 1,48 1,037 2,12 0,0308--

TABELLE-US-00023 TABELLE 23 95 % 95 % Unteres Oberes Gen GENO- Risiko Risiko CL für CL für P- hCV # rs # Symbol ENDPT TIMEVAR MODE TYP AlleleGenotyp STATIN EREIGNISSE GESAMT HR HR HR WERT PVAL_INTX hCV27830265rs12762303 ALOX5 ENDPT4F1 TIMETO_EP4F1 GEN GG G GA or GGPravastatin 0 23 0 0 -- 0.9967 0.15026 hCV27830265 rs12762303 ALOX5ENDPT4F1 TIMETO_EP4F1 GEN GG G GA or GG Placebo 2 42 ref -- -- --0.15026 hCV27830265 rs12762303 ALOX5 ENDPT4F1 TIMETO_EP4F1 GEN GA GGA or GG Pravastatin 13 376 0.47 0.239 0.906 0.0243 0.15026hCV27830265 rs12762303 ALOX5 ENDPT4F1 TIMETO_EP4F1 GEN GA G GA orGG Placebo 26 351 ref -- -- -- 0.15026 hCV27830265 rs12762303 ALOX5ENDPT4F1 TIMETO_EP4F1 GEN AA G GA or GG Pravastatin 54 1005 0.840.584 1.212 0.3548 0.15026 hCV27830265 rs12762303 ALOX5 ENDPT4F1TIMETO_EP4F1 GEN AA G GA or GG Placebo 62 980 Ref - - -0,15026HCV27830265 RS12762303 ALOX5 ENDPT4F1 TIMETO_EP4F1 DOM GA + GG G GAOR GG PRAVASTATIN 13 399 0,46 0,236 0,88 0,0192 0,10233 HCV27830265RS127623033. 0.10233 hCV27830265 rs12762303 ALOX5ENDPT4F1 TIMETO_EP4F1 REC GA + AA G GA or GG Pravastatin 67 13810.73 0.531 1.002 0.0514 0.24445 hCV27830265 rs12762303 ALOX5ENDPT4F1 TIMETO_EP4F1 REC GA + AA G GA or GG Placebo 88 1331 ref ---- -- 0.24445 hCV27830265 rs12762303 ALOX5 ENDPT4F1 TIMETO_EP4F1GEN GG G GA oder GG Pravastatin 0 23 0 0 - 0,9967 0,15067HCV27830265 RS12762303 ALOX5 ENDPT4F1 TIMETO_EP4F1 GG G G GA orgg Placebo 2 42 Ref - - - 0,15067 Hcv27830265 RS12762762762303 Alox5endPt4f1111120265 RS12762762762303 Alox5endPt4F11111120ng. 0.0254 0.15067 hCV27830265 rs12762303 ALOX5 ENDPT4F1TIMETO_EP4F1 GEN GA G GA or GG Placebo 26 352 ref -- -- -- 0.15067hCV27830265 rs12762303 ALOX5 ENDPT4F1 TIMETO_EP4F1 GEN AA G GA orGG Pravastatin 54 1002 0.85 0.587 1.218 0.3671 0.15067 hCV27830265rs12762303 ALOX5 ENDPT4F1 TIMETO EP4F1 GEN AA G GA oder GG Placebo 62981 Ref - - - 0,15067 HCV27830265 RS12762303 ALOX5 ENDPT4F1TIMETO_EP4F1 DOM GA + GG G GA oder GG PRAVASTATIN 13 398 0,46 0,2370.884 0.02 0,10281 HCV278303232323232323281 HCV2783026532323232323281 HCV27830265323232323230281 HCV2783026532323232323281 HCV2783. - ---0.10281 HCV27830265 RS12762303 ALOX5 ENDPT4F1 TIMETO_EP4F1 REC GA + AA G GA oder GG PRAVASTATIN 67 1377 0,73 0,533 1,007 0,0549 0,24354HCV27830265 RS1276233.127830265 RS127623. hCV8942032 rs1264352DDR1 ENDPT4F1 TIMETO_EP4F1 GEN CC C CG or CC Pravastatin 1 36 0.860.054 13.71 0.9134 0.18029 hCV8942032 rs1264352 DDR1 ENDPT4F1TIMETO_EP4F1 GEN CC C CG or CC Placebo 1 31 ref -- -- -- 0.18029hCV8942032 rs1264352 DDR1 ENDPT4F1 TIMETO_EP4F1 GEN CG C CG or CCPravastatin 9 356 0.39 0.179 0.844 0.0169 0.18029 hCV8942032rs1264352 DDR1 ENDPT4F1 TIMETO_EP4F1 GEN CG C CG or CC Placebo 22347 ref -- -- -- 0.18029 hCV8942032 rs1264352 DDR1 ENDPT4F1TIMETO_EP4F1 GEN GG C CG or CC Pravastatin 57 1011 0.84 0.592 1.2010.3442 0.18029 hCV8942032 rs1264352 DDR1 ENDPT4F1 TIMETO_EP4F1 GENGG C CG or CC Placebo 67 997 ref -- -- -- 0.18029 hCV8942032rs1264352 DDR1 ENDPT4F1 TIMETO_EP4F1 DOM CG + CC C CG or CCPravastatin 10 392 0.41 0.195 0.859 0.0182 0.07391 hCV8942032rs1264352 DDR1 ENDPT4F1 TIMETO_EP4F1 DOM CG + CC C CG or CC Placebo23 378 Ref - - -0,07391 HCV8942032 RS1264352 DDR1 ENDPT4F1TIMETO_EP4F1 REC CG + GG C CG ODER CC PRAVASTATIN 66 1367 0,73 0,5270.997 0,0479 0,925551 HCV8944203226352 DRAKTOG494420320252 DRAVETOG12551 DRAVETOTOG494420322252 DRAVATOTO DAWTOG494420322252 DRAVATOTO DAWTOG494420322252 DRAVATOTO DAWTOG4251 DRAVASTATIN DACHTOG4944203229252 DRAVASTATIN) --0.92551 hCV16134786 rs2857595 ENDPT4F1 TIMETO_EP4F1 GEN ALL AA AAPravastatin 2 71 0.23 0.044 1.189 0.0794 0.27061 hCV16134786rs2857595 ENDPT4F1 TIMETO_EP4F1 GEN ALL AA AA Placebo 5 45 ref ---- -- 0.27061 hCV16134786 rs2857595 ENDPT4F1 TIMETO_EP4F1 GEN ALLAG AA Pravastatin 14 403 0.67 0.342 1.293 0.2295 0.27061hCV16134786 rs2857595 ENDPT4F1 TIMETO_EP4F1 GEN ALL AG AA Placebo23 442 ref -- -- -- 0.27061 hCV16134786 rs2857595 ENDPT4F1TIMETO_EP4F1 GEN ALL GG AA Pravastatin 51 928 0.8 0.553 1.1640.2463 0.27061 hCV16134786 rs2857595 ENDPT4F1 TIMETO_EP4F1 GEN ALLGG AA Placebo 61 887 ref -- -- -- 0.27061 hCV16134786 rs2857595ENDPT4F1 TIMETO_EP4F1 DOM ALL AG + AA AA Pravastatin 16 474 0.580.313 1.068 0.0803 0.35911 hCV16134786 rs2857595 ENDPT4F1TIMETO_EP4F1 DOM ALL AG + AA AA Placebo 28 487 ref -- -- -- 0.35911hCV16134786 rs2857595 ENDPT4F1 TIMETO_EP4F1 REC ALL AG + GG AAPravastatin 65 1331 0.77 0.559 1.068 0.1182 0.12065 hCV16134786rs2857595 ENDPT4F1 TIMETO_EP4F1 REC ALL AG + GG AA Placebo 84 1329ref -- -- -- 0.12065 hCV1619596 rs1048621 SDCBP2 ENDPT4F1TIMETO_EP4F1 GEN ALL AA AG or AA Pravastatin 2 108 0.16 0.037 0.7340.018 0.05456 hCV1619596 rs1048621 SDCBP2 ENDPT4F1 TIMETO_EP4F1 GENALL AA AG or AA Placebo 12 115 ref -- -- -- 0.05456 hCV1619596rs1048621 SDCBP2 ENDPT4F1 TIMETO_EP4F1 GEN ALL AG AG or AAPravastatin 29 572 0.89 0.538 1.471 0.6494 0.05456 hCV1619596rs1048621 SDCBP2 ENDPT4F1 TIMETO_EP4F1 GEN ALL AG AG or AA Placebo32 559 ref -- - - -- 0.05456 hCV1619596 rs1048621 SDCBP2 ENDPT4F1TIMETO_EP4F1 GEN ALL GG AG or AA Pravastatin 36 719 0.77 0.4981.197 0.2473 0.05456 hCV1619596 rs1048621 SDCBP2 ENDPT4F1TIMETO_EP4F1 GEN ALL GG AG or AA Placebo 45 696 ref -- -- --0.05456 hCV1619596 rs1048621 SDCBP2 ENDPT4F1 TIMETO_EP4F1 DOM ALLAG + AA AG or AA Pravastatin 31 680 0.69 0.438 1.098 0.1188 0.74301hCV1619596 rs1048621 SDCBP2 ENDPT4F1 TIMETO_EP4F1 DOM ALL AG + AAAG or AA Placebo 44 674 ref -- -- -- 0.74301 hCV1619596 rs1048621SDCBP2 ENDPT4F1 TIMETO_EP4F1 REC ALL AG + GG AG or AA Pravastatin65 1291 0.82 0.59 1.142 0.2405 0.01754 hCV1619596 rs1048621 SDCBP2ENDPT4F1 TIMETO_EP4F1 REC ALL AG + GG AG or AA Placebo 77 1255 ref-- -- -- 0.01754 hCV32160712 rs11079160 ENDPT4F1 TIMETO_EP4F1 GENALL TT TT Pravastatin 2 46 0.24 0.048 1.193 0.0812 0.22268hCV32160712 rs11079160 ENDPT4F1 TIMETO_EP4F1 GEN ALL TT TT Placebo6 37 ref -- -- -- 0.22268 hCV32160712 rs11079160 ENDPT4F1TIMETO_EP4F1 GEN ALL TA TT Pravastatin 17 382 0.62 0.339 1.1320.1194 0.22268 hCV32160712 rs11079160 ENDPT4F1 TIMETO_EP4F1 GEN ALLTA TT Placebo 28 391 ref -- -- -- 0.22268 hCV32160712 rs11079160ENDPT4F1 TIMETO_EP4F1 GEN ALL AA TT Pravastatin 48 972 0.86 0.5821.267 0.4421 0.22268 hCV32160712 rs11079160 ENDPT4F1 TIMETO_EP4F1GEN ALL AA TT Placebo 54 942 ref -- -- -- 0.22268 hCV32160712rs11079160 ENDPT4F1 TIMETO_EP4F1 DOM ALL TA + TT TT Pravastatin 19428 0.55 0.315 0.967 0.0379 0.20087 hCV32160712 rs11079160 ENDPT4F1TIMETO_EP4F1 DOM ALL TA + TT TT Placebo 34 428 ref -- -- -- 0.20087hCV32160712 rs11079160 ENDPT4F1 TIMETO_EP4F1 REC ALL TA + AA TTPravastatin 65 1354 0.78 0.562 1.077 0.1301 0.13978 hCV32160712rs11079160 ENDPT4F1 TIMETO_EP4F1 REC ALL TA + AA TT Placebo 82 1333ref -- -- - - 0,13978

TABLE-US-00024 TABLE 24 Gene/ GENO- hCV # rs # Chrom ENDPT MODEADJUST TYPE EVENTS hCV1305848 rs6016200 ENDPT4F1 GEN STATIN AA 0hCV1305848 rs6016200 ENDPT4F1 GEN STATIN AG 41 hCV1305848 rs6016200ENDPT4F1 GEN STATIN GG 115 hCV1305848 rs6016200 ENDPT4F1 DOM STATINAG + AA 41 hCV1305848 rs6016200 ENDPT4F1 DOM STATIN GG 115hCV1305848 rs6016200 ENDPT4F1 REC STATIN AA 0 hCV1305848 rs6016200ENDPT4F1 REC STATIN AG + GG 156 hCV1305848 rs6016200 ENDPT4F1 ADDSTATIN A -- hCV1746715 rs4750628 C10orf38 ENDPT4F1 GEN STATIN AA 39hCV1746715 rs4750628 C10orf38 ENDPT4F1 GEN STATIN AG 89 hCV1746715rs4750628 C10orf38 ENDPT4F1 GEN STATIN GG 28 hCV1746715 rs4750628C10orf38 ENDPT4F1 DOM STATIN AG + AA 128 hCV1746715 rs4750628C10orf38 ENDPT4F1 DOM STATIN GG 28 hCV1746715 rs4750628 C10orf38ENDPT4F1 REC STATIN AA 39 hCV1746715 rs4750628 C10orf38 ENDPT4F1REC STATIN AG + GG 117 hCV1746715 rs4750628 C10orf38 ENDPT4F1 ADDSTATIN A -- hCV29881864 rs10514542 ENDPT4F1 GEN STATIN CC 20hCV29881864 rs10514542 ENDPT4F1 GEN STATIN CG 61 hCV29881864rs10514542 ENDPT4F1 GEN STATIN GG 75 hCV29881864 rs10514542ENDPT4F1 DOM STATIN CG + CC 81 hCV29881864 rs10514542 ENDPT4F1 DOMSTATIN GG 75 hCV29881864 rs10514542 ENDPT4F1 REC STATIN CC 20hCV29881864 rs10514542 ENDPT4F1 REC STATIN CG + GG 136 hCV29881864rs10514542 ENDPT4F1 ADD STATIN C -- hDV70959216 rs17482753 ENDPT4F1GEN STATIN TT 0 hDV70959216 rs17482753 ENDPT4F1 GEN STATIN TG 20hDV70959216 rs17482753 ENDPT4F1 GEN STATIN GG 136 hDV70959216rs17482753 ENDPT4F1 DOM STATIN TG + TT 20 hDV70959216 rs17482753ENDPT4F1 DOM STATIN GG 136 hDV70959216 rs17482753 ENDPT4F1 RECSTATIN TT 0 hDV70959216 rs17482753 ENDPT4F1 REC STATIN TG + GG 156hDV70959216 rs17482753 ENDPT4F1 ADD STATIN T -- hCV1305848rs6016200 ENDPT4F1 GEN AA 0 hCV1305848 rs6016200 ENDPT4F1 GEN AG 22hCV1305848 rs6016200 ENDPT4F1 GEN GG 67 hCV1305848 rs6016200ENDPT4F1 DOM AG + AA 22 hCV1305848 rs6016200 ENDPT4F1 DOM GG 67hCV1305848 rs6016200 ENDPT4F1 REC AA 0 hCV1305848 rs6016200ENDPT4F1 REC AG + GG 89 hCV1305848 rs6016200 ENDPT4F1 ADD A --hCV1746715 rs4750628 C10orf38 ENDPT4F1 GEN AA 21 hCV1746715rs4750628 C10orf38 ENDPT4F1 GEN AG 52 hCV1746715 rs4750628 C10orf38ENDPT4F1 GEN GG 16 hCV1746715 rs4750628 C10orf38 ENDPT4F1 DOM AG +AA 73 hCV1746715 rs4750628 C10orf38 ENDPT4F1 DOM GG 16 hCV1746715rs4750628 C10orf38 ENDPT4F1 REC AA 21 hCV1746715 rs4750628 C10orf38ENDPT4F1 REC AG + GG 68 hCV1746715 rs4750628 C10orf38 ENDPT4F1 ADDA - - hCV29881864 rs10514542 ENDPT4F1 GEN CC 14 hCV29881864rs10514542 ENDPT4F1 GEN CG 35 hCV29881864 rs10514542 ENDPT4F1 GENGG 40 hCV29881864 rs10514542 ENDPT4F1 DOM CG + CC 49 hCV29881864rs10514542 ENDPT4F1 DOM GG 40 hCV29881864 rs10514542 ENDPT4F1 RECCC 14 hCV29881864 rs10514542 ENDPT4F1 REC CG + GG 75 hCV29881864rs10514542 ENDPT4F1 ADD C -- 95 % 95% Lower Upper CL for CL for P-2DF P- hCV # rs # TOTAL HR HR HR VALUE VALUE hCV1305848 rs601620086 0 0 1.63E+248 0.9648 0.2079 hCV1305848 rs6016200 875 0.72 0.5071.035 0.0764 0.2079 hCV1305848 rs6016200 1806 ref -- - . - 0.63 0.451 0.876 0.0061 -- hCV1746715rs4750628 701 1.47 0.906 2.392 0.1187 0.0324 hCV1746715 rs47506281340 1.76 1.151 2.691 0.0091 0.0324 hCV1746715 rs4750628 726 ref ---- -- 0.0324 hCV1746715 rs4750628 2041 1.66 1.103 2.5 0.015 --hCV1746715 rs4750628 726 ref -- -- - - -- hCV1746715 rs4750628 7010.99 0.688 1.42 0.9495 -- hCV1746715 rs4750628 2066 ref -- -- -- --hCV1746715 rs4750628 -- 1.18 0.947 1.465 0.1424 -- hCV29881864rs10514542 224 1.76 1.072 2.875 0.0253 0.0767 hCV29881864rs10514542 1102 1.06 0.756 1.486 0.7354 0.0767 hCV29881864rs10514542 1450 ref -- -- -- 0.0767 hCV29881864 rs10514542 13261.18 0.858 1.609 0.3138 -- hCV29881864 rs10514542 1450 ref -- -- ---- hCV29881864 rs10514542 224 1.71 1.07 2.736 0.0249 -- hCV29881864rs10514542 2552 ref -- -- -- -- hCV29881864 rs10514542 - - 1.240.975 1.564 0.08 -- hDV70959216 rs17482753 21 0 0 -- 0.974 0.2331hDV70959216 rs17482753 495 0.66 0.416 1.063 0.088 0.2331hDV70959216 rs17482753 2252 ref -- -- -- 0.2331 hDV70959216rs17482753 516 0.64 0.399 1.019 0.0599 -- hDV70959216 rs174827532252 ref -- - . 0.98230.3016 hCV1305848 rs6016200 426 0.68 0.422 1.107 0.1216 0.3016hCV1305848 rs6016200 898 ref -- -- -- 0.3016 hCV1305848 rs6016200470 0.62 0.381 0.997 0.0487 -- hCV1305848 rs6016200 898 ref -- ---- -- hCV1305848 rs6016200 44 0 0 -- 0.9823 -- hCV1305848 rs60162001324 ref -- -- -- -- hCV1305848 rs6016200 -- 0.59 0.379 0.9290.0226 -- hCV1746715 rs4750628 349 1.34 0.699 2.568 0.3775 0.1054hCV1746715 rs4750628 665 1.79 1.021 3.132 0.0421 0.1054 hCV1746715rs4750628 355 ref -- -- -- 0.1054 hCV1746715 rs4750628 1014 1.630.95 2.802 0.0763 -- hCV1746715 rs4750628 355 ref -- -- -- --hCV1746715 rs4750628 349 0.89 0.545 1.449 0.6359 -- hCV1746715rs4750628 1020 ref -- -- -- -- hCV1746715 rs4750628 -- 1.13 0.8441.501 0.4216 -- hCV29881864 rs10514542 115 2.28 1.238 4.187 0.00810.0236 hCV29881864 rs10514542 565 1.06 0.675 1.673 0.7927 0.0236hCV29881864 rs10514542 694 ref -- -- -- 0.0236 hCV29881864rs10514542 680 1.25 0.826 1.903 0.2888 -- hCV29881864 rs10514542694 ref -- -- -- -- hCV29881864 rs10514542 115 2,21 1,25 3.9210.0064 -- hCV29881864 rs10514542 1259 ref -- -- -- -- hCV29881864rs10514542 -- 1,38 1,009 1,0438 --

TABLE-US-00025 TABLE 25 Gene GENO- Risk hCV # rs # Symbol ENDPTTIMEVAR MODE TYPE Allele STATIN hDV77718013 ENDPT4F1 TIMETO_EP4F1REC TC + CC Pravastatin hCV3216551 rs562338 ENDPT4F1 TIMETO_EP4F1GEN GG Pravastatin hCV2862873 rs780094 GCKR ENDPT4F1 TIMETO_EP4F1DOM TC + TT Pravastatin hCV9296529 rs4358307 ENDPT4F1 TIMETO_EP4F1GEN GA Pravastatin hCV29480044 rs10516433 TSPAN5 ENDPT4F1TIMETO_EP4F1 GEN TC Pravastatin hCV29480044 rs10516433 TSPAN5ENDPT4F1 TIMETO_EP4F1 REC TC + CC Pravastatin hCV30454150rs10516434 TSPAN5 ENDPT4F1 TIMETO_EP4F1 GEN TC PravastatinhCV30454150 rs10516434 TSPAN5 ENDPT4F1 TIMETO_EP4F1 REC TC + CCPravastatin hCV8942032 rs1264352 DDR1 ENDPT4F1 TIMETO_EP4F1 DOM CG+ CC C Pravastatin hCV9473891 rs1555173 ENDPT4F1 TIMETO_EP4F1 RECCT + TT Pravastatin hCV2442143 rs12544854 ASAH1 ENDPT4F1TIMETO_EP4F1 GEN TC Pravastatin hCV2442143 rs12544854 ASAH1ENDPT4F1 TIMETO_EP4F1 DOM TC + TT Pravastatin hCV2442143 rs12544854ASAH1 ENDPT4F1 TIMETO_EP4F1 GEN TC Pravastatin hCV2442143rs12544854 ASAH1 ENDPT4F1 TIMETO_EP4F1 DOM TC + TT PravastatinhCV1463226 rs10890 FXN ENDPT4F1 TIMETO_EP4F1 GEN TT PravastatinhCV1463226 rs10890 FXN ENDPT4F1 TIMETO_EP4F1 GEN CC PravastatinhCV2741051 rs2230806 ABCA1 ENDPT4F1 TIMETO_EP4F1 GEN TC PravastatinhCV2741051 rs2230806 ABCA1 ENDPT4F1 TIMETO_EP4F1 DOM TC + TTPravastatin hCV2741051 rs2230806 ABCA1 ENDPT4F1 TIMETO_EP4F1 GEN TCPravastatin hCV2741051 rs2230806 ABCA1 ENDPT4F1 TIMETO_EP4F1 DOM TC+ TT Pravastatin hCV2959482 rs3890182 ABCA1 ENDPT4F1 TIMETO_EP4F1GEN AG Pravastatin hCV2959482 rs3890182 ABCA1 ENDPT4F1 TIMETO_EP4F1DOM AG + AA Pravastatin hCV22275299 rs28927680 BUD13 ENDPT4F1TIMETO_EP4F1 GEN GC Pravastatin hCV29566897 rs10507755 ENDPT4F1TIMETO_EP4F1 REC CT + TT Pravastatin hCV8757333 rs1800588 LIPCENDPT4F1 TIMETO_EP4F1 DOM TC + TT Pravastatin hCV16164743 rs2928932ENDPT4F1 TIMETO_EP4F1 GEN CC Pravastatin hCV16164743 rs2928932ENDPT4F1 TIMETO_EP4F1 GEN AA Pravastatin hCV9324316 rs9305020ENDPT4F1 TIMETO_EP4F1 GEN TT Pravastatin hCV9324316 rs9305020ENDPT4F1 TIMETO_EP4F1 REC CT + TT Pravastatin hCV1846459 rs4803759ENDPT4F1 TIMETO_EP4F1 GEN TC Pravastatin hCV1846459 rs4803759ENDPT4F1 TIMETO_EP4F1 GEN CC Pravastatin hCV1846459 rs4803759ENDPT4F1 TIMETO_EP4F1 REC TC + CC Pravastatin hCV26682080 rs4420638ENDPT4F1 TIMETO_EP4F1 GEN GG Pravastatin hCV26682080 rs4420638ENDPT4F1 TIMETO_EP4F1 GEN GA Pravastatin hCV26682080 rs4420638ENDPT4F1 TIMETO_EP4F1 DOM GA + GG Pravastatin 95% 95% Lower UpperCL for CL for P- hCV # rs # EVENTS TOTAL HR HR HR VALUE PVAL_INTXhDV77718013 66 1359 0.74 0.539 1.022 0.0673 0.0556 hCV3216551rs562338 40 932 0.59 0.401 0.877 0.0089 0.04137 hCV2862873 rs78009441 887 0.6 0.403 0.881 0.0095 0.09031 hCV9296529 rs4358307 25 6240.5 0.307 0.807 0.0047 0.08098 hCV29480044 rs10516433 16 454 0.460.255 0.832 0.0101 0.03925 hCV29480044 rs10516433 61 1309 0.670. 487 0.934 0.0178 0.04698 hCV30454150 rs10516434 16 451 0.46 0.2550.832 0.0102 0.04149 hCV30454150 rs10516434 61 1310 0.67 0.4860.931 0.017 0.04884 hCV8942032 rs1264352 10 392 0.41 0.195 0.8590.0182 0.07391 hCV9473891 rs1555173 67 1363 0.75 0.547 1.035 0.08010.07415 hCV2442143 rs12544854 29 713 0.55 0.35 0.877 0.0118 0.02918hCV2442143 rs12544854 43 1070 0.57 0.391 0.836 0.004 0.00824hCV2442143 rs12544854 29 704 0.57 0.36 0.905 0.0172 0.04882hCV2442143 rs12544854 42 1059 0.56 0.384 0.825 0.0033 0.01402hCV1463226 rs10890 9 303 0.41 0.188 0.885 0.0233 0.02602 hCV1463226rs10890 16 416 0.48 0.266 0.874 0.0162 0.02602 hCV2741051 rs223080616 597 0.47 0.258 0.856 0.0136 0.09085 hCV2741051 rs2230806 20 7090.47 0.272 0.801 0.0056 0.03067 hCV2741051 rs2230806 17 603 0.50.275 0.892 0.0192 0.06908 hCV2741051 rs2230806 20 711 0.47 0.2730.802 0.0057 0.02439 hCV2959482 rs3890182 8 302 0.34 0.152 0.7670.0093 0.06769 hCV2959482 rs3890182 8 320 0.34 0.151 0.753 0.00810.02862 hCV22275299 rs28927680 2 175 0.2 0.042 0.908 0.0372 0.0983hCV29566897 rs10507755 67 1350 0.76 0.552 1.049 0.0957 0.02347hCV8757333 rs1800588 21 567 0.49 0.286 0.824 0.0074 0.05012hCV16164743 rs2928932 6 190 0.31 0.124 0.797 0.0148 0.03514hCV16164743 rs2928932 23 555 0.6 0.355 1.004 0.052 0.03514hCV9324316 rs9305020 48 963 0.7 0.482 1.016 0.0604 0.05765hCV9324316 rs9305020 67 1352 0.76 0.554 1.05 0.0968 0.02527hCV1846459 rs4803759 25 565 0.62 0.378 1.023 0.0613 0.05544hCV1846459 rs4803759 31 707 0.66 0.415 1.036 0.0707 0.05544hCV1846459 rs4803759 56 1272 0.64 0.457 0.895 0.0092 0.01624hCV26682080 rs4420638 2 58 0.25 0.05 1.217 0,0855 0,07632hCV26682080 rs4420638 15 383 0,5 0,268 0,919 0,0259 0,07632hCV26682080 rs4420638 17 441 0,45 0,255 0,804 0,0065 0,0418 0,0418

TABLE-US-00026 TABLE 26 95% 95% Lower Upper GENO- CL for CL for P-hCV # rs # Gen MODE LAYERS ADJUST TYPE EVENTS TOTAL HR HR HR VALUEThCV11474611 rs3814843 CALM1 GEN ALL STATIN GG 1 3 7.54 1.055 53 ,8860,0441 hCV11,47 rs3814843 CALM1 GEN ALL STATIN GT 14 224 1.170.676 2.038 0.5698 hCV11474611 rs3814843 CALM1 GEN ALL STATIN TT128 2392 ref -- -- -- hCV11474611 rs3814843 CALM1 REC ALL STATIN GG1 3 7.43 1.041 53.062 0.0455 hCV11474611 rs3814843 CALM1 REC ALLSTATIN GT + TT 142 2616 ref -- -- -- hCV11474611 rs3814843 CALM1GEN ALL GG 1 3 6.64 0.919 47.944 0.0606 hCV11474611 rs3814843 CALM1GEN ALL GT 6 104 0.95 0.413 2.188 0.9051 hCV11474611 rs3814843CALM1 GEN ALL TT 70 1183 ref -- -- -- hCV11474611 rs3814843 CALM1REC ALL GG 1 3 6.67 0.924 48.09 0.0599 hCV11474611 rs3814843 CALM1REC ALL GT + TT 76 1287 ref -- -- -- hCV2930693 rs13183672 FSTL4REC ALL STATIN AA 96 1498 1.51 1.07 2.14 0.0191 hCV2930693rs13183672 FSTL4 REC ALL STATIN AC + CC 48 1122 ref -- -- --hCV2930693 RS13183672 FSTL4 Add All Statin A-- 1.29 0.965 1.7190.0859 HCV2930693 RS13183672 FSTL4 REC ALL AA 52 52 729 1.61 0.9982.59 0.0510 HCV2930 RS A -- -- 1.48 0.9822.24 0.0609

TABELLE-US-00027 TABELLE 27 95 % 95 % Untere Obere GENO- CL für CL für P-hCV # rs Gen MODE TYP STATIN EREIGNISSE GESAMT HR HR HR VALUEPVAL_INTX hCV1022614 rs220479 ITGAE GEN CC Pravastatin 52 973 0,890,609 1,295 0,5366 2274 26V259 26V259 ITGAE GEN CC Placebo56 927 ref -- -- -- 0.22592 hCV1022614 rs220479 ITGAE GEN CTPravastatin 15 408 0.48 0.257 0.887 0.0192 0.22592 hCV1022614rs220479 ITGAE GEN CT Placebo 30 400 ref -- -- -- 0.22592hCV1022614 rs220479 ITGAE GEN TT Pravastatin 3 46 0.91 0.203 4.0470.8969 0.22592 hCV1022614 rs220479 ITGAE GEN TT Placebo 4 56 ref ---- -- 0.22592 hCV1022614 rs220479 ITGAE DOM CT + CC Pravastatin 671381 0.74 0.541 1.024 0.0696 0.79081 hCV1022614 rs220479 ITGAE DOMCT + CC Placebo 86 1327 ref -- -- -- 0.79081 hCV1022614 rs220479ITGAE REC CT + TT Pravastatin 18 454 0.52 0.294 0.921 0.02480.11998 hCV1022614 rs220479 ITGAE REC CT + TT Placebo 34 456 ref ---- -- 0.11998 hCV11450563 rs2038366 GEN GG Pravastatin 29 539 1.150.669 1.975 0.6132 0.17234 hCV11450563 rs2038366 GEN GG Placebo 24522 ref -- -- -- 0.17234 hCV11450563 rs2038366 GEN GT Pravastatin28 638 0.61 0.381 0.986 0.0436 0.17234 hCV11450563 rs2038366 GEN GTPlacebo 43 602 ref -- -- -- 0.17234 hCV11450563 rs2038366 GEN TTPravastatin 10 151 1.13 0.472 2.724 0.7789 0.17234 hCV11450563rs2038366 GEN TT Placebo 10 167 Ref---0,17234 HCV11450563RS2038366 DOM GT + GG PRAVASTATIN 57 1177 0,81 0,567 1,148 0,23340,47195 HCV11450563 RS2038366 DOM GT + GG SAPLEBOBE 67 1124--, 0.836666635 3595 3595 3595 3595 GT + GG 37 1124,-0,83666635 GT. 789 0.70.463 1.064 0.0954 0.15155 hCV11450563 rs2038366 REC GT + TTPlacebo 53 769 ref -- -- -- 0.15155 hCV2091644 rs1010 VAMP8 GEN CCPravastatin 12 271 1.18 0.51 2.73 0.6997 0.48071 hCV2091644 rs1010VAMP8 GEN CC Placebo 10 258 ref -- -- -- 0.48071 hCV2091644 rs1010VAMP8 GEN CT Pravastatin 31 686 0.66 0.418 1.045 0.0763 0.48071hCV2091644 rs1010 VAMP8 GEN CT Placebo 45 666 ref -- -- -- 0.48071hCV2091644 rs1010 VAMP8 GEN TT Pravastatin 26 455 0.71 0.43 1.1860.1928 0.48071 hCV2091644 rs1010 VAMP8 GEN TT Placebo 35 448 Ref -----0,48071 HCV2091644 RS1010 VAMP8 DOM CT + CC Pravastatin 43957 0,76 0,507 1,126 0,1678 0,87535 HCV2091644 RS1010 VAMP8 DOM CT + CCCOBO 55 924 Ref---------0,87535,--0,87535,--0.87535,--0.87535. 0.961 0.0284 0.23503hCV2091644 rs1010 VAMP8 REC CT + TT Placebo 80 1114 ref -- -- --0.23503 hCV2169762 rs1804689 HPS1 GEN TT Pravastatin 4 107 0.990.266 3.694 0.9903 0.34901 hCV2169762 rs1804689 HPS1 GEN TT Placebo5 131 ref -- -- -- 0.34901 hCV2169762 rs1804689 HPS1 GEN TGPravastatin 36 652 0.92 0.583 1.468 0.7398 0.34901 hCV2169762rs1804689 HPS1 GEN TG Placebo 36 600 ref -- -- -- 0.34901hCV2169762 rs1804689 HPS1 GEN GG Pravastatin 30 668 0.59 0.3720.924 0.0214 0.34901 hCV2169762 rs1804689 HPS1 GEN GG Placebo 49651 ref - - -- -- 0.34901 hCV2169762 rs1804689 HPS1 DOM TG + TTPravastatin 40 759 0.95 0.612 1.461 0.8004 0.13433 hCV2169762rs1804689 HPS1 DOM TG + TT Placebo 41 731 ref -- -- -- 0.13433hCV2169762 rs1804689 HPS1 REC TG + GG Pravastatin 66 1320 0.730.529 1.006 0.0547 0.65359 hCV2169762 rs1804689 HPS1 REC TG + GGPlacebo 85 1251 ref -- -- -- 0.65359 hCV2192261 rs3213646 EXOD1 GENCC Pravastatin 27 417 1.05 0.613 1.799 0.8592 0.20384 hCV2192261rs3213646 EXOD1 GEN CC Placebo 26 416 ref -- -- -- 0.20384hCV2192261 rs3213646 EXOD1 GEN CT Pravastatin 24 691 0.54 0.3280.898 0.0175 0.20384 hCV2192261 rs3213646 EXOD1 GEN CT Placebo 41646 ref -- -- -- 0.20384 hCV2192261 rs3213646 EXOD1 GEN TTPravastatin 13 245 0.64 0.316 1.278 0.2036 0.20384 hCV2192261rs3213646 EXOD1 GEN TT Placebo 20 243 ref -- -- -- 0.20384hCV2192261 rs3213646 EXOD1 DOM CT + CC Pravastatin 51 1108 0.730.506 1.048 0.0882 0.72432 hCV2192261 rs3213646 EXOD1 DOM CT + CCPlacebo 67 1062 ref -- -- -- 0.72432 hCV2192261 rs3213646 EXOD1 RECCT + TT Pravastatin 37 936 0.57 0.379 0.857 0.007 0.07855 hCV2192261 rs3213646 EXOD1 REC CT + TT Placebo 61 889 ref -- -- --0.07855 hCV7425232 rs3900940 MYH15 GEN CC Pravastatin 13 160 1.030.461 2.296 0.9448 0.57268 hCV7425232 rs3900940 MYH15 GEN CCPlacebo 11 142 ref -- -- -- 0.57268 hCV7425232 rs3900940 MYH15 GENCT Pravastatin 23 561 0.61 0.365 1.022 0.0604 0.57268 hCV7425232rs3900940 MYH15 GEN CT Placebo 39 583 ref -- -- -- 0.57268hCV7425232 rs3900940 MYH15 GEN TT Pravastatin 30 620 0.71 0.4421.146 0.1618 0.57268 hCV7425232 rs3900940 MYH15 GEN TT Placebo 39573 ref -- -- -- 0.57268 hCV7425232 rs3900940 MYH15 DOM CT + CCPravastatin 36 721 0.72 0.468 1.102 0.1293 0.97544 hCV7425232rs3900940 MYH15 DOM CT + CC Placebo 50 725 ref -- -- -- 0.97544hCV7425232 rs3900940 MYH15 REC CT + TT Pravastatin 53 1181 0.660.467 0.939 0.0207 0.33623 hCV7425232 rs3900940 MYH15 REC CT + TTPlacebo 78 1156 ref -- -- -- 0.33623 hCV945276 rs89962 KRT4 GEN TTPravastatin 9 238 0.96 0.392 2.375 0.9381 0.71864 hCV945276 rs89962KRT4 GEN TT Placebo 10 255 ref -- -- -- 0.71864 hCV945276 rs89962KRT4 GEN TG Pravastatin 37 674 0.64 0.423 0.979 0.0397 0.71864hCV945276 rs89962 KRT4 GEN TG Placebo 53 628 ref -- -- -- 0.71864hCV945276 rs89962 KRT4 GEN GG Pravastatin 17 443 0.65 0.349 1.1960.1641 0.71864 hCV945276 rs89962 KRT4 GEN GG Placebo 25 426 ref ---- - - 0.71864 hCV945276 rs89962 KRT4 DOM TG + TT Pravastatin 46 9120.7 0.48 1.027 0.0683 0.83505 hCV945276 rs89962 KRT4 DOM TG + TTPlacebo 63 883 ref -- -- -- 0.83505 hCV945276 rs89962 KRT4 REC TG +GG Pravastatin 54 1117 0.65 0.458 0.916 0.0141 0.42005 hCV945276rs89962 KRT4 REC TG + GG Placebo 78 1054 Ref -- -- -- 0,42005

TABLE-US-00028 TABLE 28 Association of MYH15 (rs3900940/hCV7425232) with Stroke Endpoint in CARE Study Population: CARE Study (n=2913) Endpoint: Stroke or TIA (official CARE endpoint) (“endpt4f1”) Statistical Method: Cox model association of MYH15 SNP(rs3900940/hCV7425232) with stroke endpoint in combined treatment CARE arms Adjusted1 Adjusted2 Adjusted3 Genotype HR 95% CI2-sided p-value HR 95% CI 2-sided p-value HR 95% CI 2-sided p-value Hom_CC 1.403 . -2.45 0.039 Maj + het 1 1 1 "Adjusted1" = Adjusted for statin use "Adjusted2" = Adjusted for traditional risk factors (TRF), body mass index (BMI) and statin use "Adjusted3" = Adjusted for TRF, BMI, Statin Conclusions: 1) The MYH15 SNP (rs3900940/hCV7425232) was associated with stroke in CARE. 2) The MYH15 SNP (rs3900940/hCV7425232) was associated with stroke in CARE even after adjustment for CHD. (CHD defined according to CARE original endpoint - fatal CHD/definitely non-fatal MI, "endpt1")

Tabelle-us-00029 Tabelle 29 Gen-Risiko Geno_ Events_ Total_ HCV # RS #Symbol Allelmodus Strata Placebo Placebo Placebo HCV2091644 RS1010VAMP8 C GEN ALL CC 49 521 HCV2091644 RS1010 VAMP8 CC Gen Hist CC 28235 HCV2091644211010101010101010101010101010101010101010101010101010101010129 CC 2 2825 T GEN no hist CT 48 808 hCV8942032 rs1264352 DDR1C GEN ALL CC 8 110 hCV2169762 rs1804689 HP51 T GEN no hist GT 38670 hCV16158671 rs2200733 C4 T GEN ALL CT 37 489 hCV16158671rs2200733 C4 T GEN no hist CT 19 285 hCV16158671 rs2200733 C4 T GENhist TT 3 10 hCV27504565 rs3219489 MUTYH C GEN hist CG 35 465hCV27511436 rs3750145 FZD1 T GEN ALL CC 4 77 hCV27511436 rs3750145FZD1 T GEN hist CC 1 31 hCV7425232 rs3900940 MYH15 C GEN hist CT 55528 HR_ LOWER_ UPPER_ P_ EVENTS_ no hCV # PLACEBO PLACEBO PLACEBOPLACEBO ALL event HR_ALL P_ALL hCV2091644 1.50982 1.030611 2.2118440.0344528 88 951 1.340598 0.051104903 hCV2091644 1.503 0.8979082.515874 0.1210805 54 428 1.633661 0.014183695 hCV2091644 1.139380.733208 1.770572 0.5617921 118 1136 1.344979 0.076364852hCV2442143 1.31132 0.778332 2.209298 0.3085018 101 1535 1.3260840.166536479 hCV8942032 1.01239 0.495766 2.067369 0.9730365 22 2141.368996 0.190221586 hCV2169762 0.99636 0.64971 1.527967 0.986667885 1236 1.35397 0.062193717 hCV16158671 1.07497 0.753308 1.5339750.6902781 80 900 1.197273 0.172251195 hCV16158671 1.2283 0.7424712.032018 0.4233603 38 517 1.282126 0.189409128 hCV16158671 3.711451.175206 11.72124 0.0254095 4 18 2.311594 0.124212946 hCV275045650.70803 0.473602 1.0585 0.092402 69 853 0.726379 0.040276813hCV27511436 0.65977 0.244625 1.779435 0.4113489 6 149 0,5031560.113669409 HCV27511436 0,32028 0.044599 2,300102 0,2576826 2 640.307292 0.120384642 HCV74232 1,2112222 0,833465 1.76095 0,3149450756 0,865 1,760195 0,3149450756 0,865 1,760195 0,3149450756 0,865 1,760195 0,3149450756.

TABLE-US-00030 TABLE 30 Gene/Chrom Risk GENO_ EVENTS_ TOTAL_ hCV #rs # symbol Allel MODE STRATA PLACEBO PLACEBO PLACEBO hCV2091644rs1010 VAMP8 C GEN ALL CC 49 521 hCV2091644 rs1010 VAMP8 C DOM ALLCC + CT 153 1968 hCV2 CT 153 1968 hCV2 0 VAMPrs1 C4 GEN18 hist.1 CC 21 286hCV2091644 rs1010 VAMP8 C GEN hist CC 28 235 hCV26505812 rs10757274C9p21 G GEN ALL AG 121 1455 hCV26505812 rs10757274 C9p21 G DOM ALLGG + AG 169 2156 hCV26505812 rs10757274 C9p21 G GEN no hist GG 23364 hCV26505812 rs10757274 C9p21 G GEN no hist AG 52 826hCV26505812 rs10757274 C9p21 G DOM no hist GG + AG 75 1190hCV26505812 rs10757274 C9p21 G GEN hist AG 69 629 hCV2442143rs12544854 ASAH1 T GEN no hist TT 26 393 hCV8942032 rs1264352 DDR1C GEN no hist CG 37 550 hCV8942032 rs1264352 DDR1 C DOM no hist CC+ CG 41 616 hCV16158671 rs2200733 C4 T GEN hist TT 3 10 hCV27504565rs3219489 MUTYH C GEN hist CG 35 465 hCV27504565 rs3219489 MUTYH CDOM hist GG + CG 41 523 hCV27511436 rs3750145 FZD1 T DOM ALL CC +CT 50 804 hCV27511436 rs3750145 FZD1 T GEN no hist CT 16 414hCV27511436 rs3750145 FZD1 T DOM no hist CC + CT 19 460 HR_ LOWER_UPPER_ P_ EVENTS_ no hCV # PLACEBO PLACEBO PLACEBO PLACEBO ALLevent HR_ALL P_ALL hCV2091644 1.509818 1.030611 2.211844 0.034452888 951 1.340598 0.0511049 hCV2091644 1.242162 0.916407 1.6837130.1622853 hCV2091644 1.452091 0.820968 2.568392 0.1998539 34 5231.033962 0.91230651 hCV2091644 1.503005 0.897908 2.515874 0.121080554 428 1.633661 0.0141837 hCV26505812 1.464442 1.027673 2.0868420.0347703 215 2683 1.118574 0.41790129 hCV26505812 1.3811460.981881 1.942766 0.0636069 hCV26505812 1.507129 0.820845 2.7671930.1857813 47 674 1.215134 0.39336777 hCV26505812 1.482778 0.8767942.50758 0.1417039 87 1528 0.992161 1 hCV26505812 1.489002 0.9001172.463154 0.1210931 hCV26505812 1.372228 0.849193 2.217411 0.196237128 1155 1.185801 0.35086569 hCV2442143 1.479057 0.825673 2.6494870.1881955 41 704 1.173733 0.49295851 hCV8942032 1.324522 0.8703672.015654 0.1895578 ​​61 972 1.10852 0.55960326 hCV8942032 1.3056870.868558 1.962816 0.1996948 hCV16158671 3.711451 1.175206 11.721240.0254095 4 18 2.311594 0.12421295 hCV27504565 0.708031 0.4736021.0585 0.092402 69 853 0.726379 0.04027681 hCV27504565 0.7416410.506363 1.08624 0,1247589 HCV27511436 0,80098 0,583058 1.1003530.1707752 HCV27511436 0,603398 0,351722 1,035162 0,066584 425050.824734 0,338472972,3934 0,33472972,3934 0,3384729727273834 0,3384729727273634 0,3384729727273834 0,3384729727273834 0,333847297227273634.

TABLE-US-00031 TABLE 31 Gene/ Chrom Risk GENO_ EVENTS_ hCV # rs #symbol Allel MODE STRATA RESP STATIN RESP hCV2091644 rs1010 VAMP8C DOM no hist CC + CT Pravastatin 50 hCV2091644 rs1010 VAMP8 C DOMno hist CC + CT 50 hCV2091644 rs1010 VAMP8 C DOMno hist CC + CT 510 K310CN Placebo 67 hCV295397 hCV295397 REC histCC + AC pravastatin 106 hCV29539757 rs10110659 KCNQ3 C REC hist CC+ AC placebo 100 hCV26505812 rs10757274 C9p21 G GEN ALL GGpravastatin 51 hCV26505812 rs10757274 C9p21 G GEN ALL GG placebo 48hCV26505812 rs10757274 C9p21 G GEN ALL AG pravastatin 94hCV26505812 rs10757274 C9p21 G GEN ALL AG placebo 121 hCV26505812rs10757274 C9p21 G GEN ALL AA pravastatin 56 hCV26505812 rs10757274C9p21 G GEN ALL AA placebo 41 hCV26505812 rs10757274 C9p21 G DOMALL GG + AG pravastatin 145 hCV26505812 rs10757274 C9p21 G DOM ALLGG + AG placebo 169 hCV26505812 rs10757274 C9p21 G GEN no hist GGpravastatin 24 hCV26505812 rs10757274 C9p21 G GEN no hist GGplacebo 23 hCV26505812 rs10757274 C9p21 G GEN no hist AGpravastatin 35 hCV26505812 rs10757274 C9p21 G GEN no hist AGplacebo 52 hCV26505812 rs10757274 C9p21 G GEN no hist AApravastatin 28 hCV26505812 rs10757274 C9p21 G GEN no hist AAplacebo 19 hCV26505812 rs10757274 C9p21 G DOM no hist GG + AGpravastatin 59 hCV26505812 rs10757274 C9p21 G DOM no hist GG + AGplacebo 75 hCV2169762 rs1804689 HPS1 T DOM no hist TT + GTpravastatin 57 hCV2169762 rs1804689 HPS1 T DOM no hist TT + GTplacebo 47 hCV2169762 rs1804689 HPS1 T REC hist GG + GT pravastatin109 hCV2169762 rs1804689 HPS1 T REC hist GG + GT placebo 102 noTOTAL_ LOWER_ UPPER_ P_INT_ hCV # event RESP HR_RESP RESP RESPP_RESP RESP hCV2091644 994 1044 0.7860368 0.54496 1.13377 0.197680.0837336 hCV2091644 1033 1100 0.0837336 hCV29539757 1087 11931.0088023 0.76761 1.32578 0.94987 0.0530448 hCV29539757 1040 11400.0530448 hCV26505812 638 689 1.0816406 0.7293 1.60421 0.696350.0696553 hCV26505812 653 701 0.0696553 hCV26505812 1349 14430.7768621 0.59335 1.01713 0.06629 0.0696553 hCV26505812 1334 14550.0696553 hCV26505812 674 730 1.3304985 0.88923 1.99075 0.164860.0696553 hCV26505812 680 721 0.0696553 hCV26505812 1987 21320.8638087 0.69193 1.07838 0.1959 0.0630809 hCV26505812 1987 21560.0630809 hCV26505812 333 357 1.0681052 0.6028 1.89259 0.821410.0828923 hCV26505812 341 364 0.0828923 hCV26505812 754 7890.6977172 0.45454 1.071 0.09971 0.0828923 hCV26505812 774 8260.0828923 hCV26505812 395 423 1.5704654 0.87695 2.81243 0.128940.0828923 hCV26505812 424 443 0.0828923 hCV26505812 1087 11460.8131888 0.57817 1.14374 0.23474 0.0573322 hCV26505812 1115 11900.0573322 hCV2169762 731 788 1.2655756 0.86016 1.86208 0.231930.033 hCV2169762 777 824 0.033 hCV2169762 1063 1172 1.02768010.7845 1,34624 0,84289 0,0507564 hCV2169762 1035 1137 0,0507564

TABLE-US-00032 TABLE 32 Gene/ Chrom Risk GENO_ EVENTS_ hCV # rs #symbol Allel MODE STRATA RESP STATIN RESP hCV2091644 rs1010 VAMP8C GEN no hist CC pravastatin 13 hCV2091644 rs1010 VAMP8 C GEN nohist CC placebo 21 hCV20916044 rs1010 VAMP8 C GEN nohist CC placebo 21 hCV20916044 rs101 VAMP8C GEN nohist CC placebo 21 hCV2091604 rs101 37 HCV2091644 RS1010 VAMP8 C GEN NO HIST CT LACEBO 46HCV2091644 RS1010 VAMP8 C GEN NO HIST TT PRAVASTATIN 36 HCV20916444RS1010 VAMP8 C GEN NO HILT TT SPLACBE 27 HCV2091644 RS1010 Vamp8 67 hCV29539757 rs10110659 KCNQ3 C GEN hist AApravastatin 7 hCV29539757 rs10110659 KCNQ3 C GEN hist AA placebo 16hCV29539757 rs10110659 KCNQ3 C GEN hist AC pravastatin 44hCV29539757 rs10110659 KCNQ3 C GEN hist AC placebo 44 hCV29539757rs10110659 KCNQ3 C GEN hist CC pravastatin 62 hCV29539757rs10110659 KCNQ3 C GEN hist CC placebo 56 hCV29539757 rs10110659KCNQ3 C REC hist CC + AC pravastatin 106 hCV29539757 rs10110659KCNQ3 C REC hist CC + AC placebo 100 hCV26505812 rs10757274 C9p21 GGEN ALL GG pravastatin 51 hCV26505812 rs10757274 C9p21 G GEN ALL GGplacebo 48 hCV26505812 rs10757274 C9p21 G GEN ALL AG pravastatin 94hCV26505812 rs10757274 C9p21 G GEN ALL AG placebo 121 hCV26505812rs10757274 C9p21 G GEN ALL AA pravastatin 56 hCV26505812 rs10757274C9p21 G GEN ALL AA placebo 41 hCV26505812 rs10757274 C9p21 G DOMALL GG + AG pravastatin 145 hCV26505812 rs10757274 C9p21 G DOM ALLGG + AG placebo 169 hCV26505812 rs10757274 C9p21 G GEN no hist GGpravastatin 24 hCV26505812 rs10757274 C9p21 G GEN no hist GGplacebo 23 hCV26505812 rs10757274 C9p21 G GEN no hist AGpravastatin 35 hCV26505812 rs10757274 C9p21 G GEN no hist AGplacebo 52 hCV26505812 rs10757274 C9p21 G GEN no hist AApravastatin 28 hCV26505812 rs10757274 C9p21 G GEN no hist AAplacebo 19 hCV26505812 rs10757274 C9p21 G DOM no hist GG + AGpravastatin 59 hCV26505812 rs10757274 C9p21 G DOM no hist GG + AGplacebo 75 hCV2442143 rs12544854 ASAH1 T REC no hist CC + CTpravastatin 72 hCV2442143 rs12544854 ASAH1 T REC no hist CC + CTplacebo 68 hCV2442143 rs12544854 ASAH1 T DOM hist TT + CTpravastatin 88 hCV2442143 rs12544854 ASAH1 T DOM hist TT + CTplacebo 82 hCV27830265 rs12762303 ALOX5 G DOM no hist GG + AGpravastatin 25 hCV27830265 rs12762303 ALOX5 G DOM no hist GG + AGplacebo 16 hCV2169762 rs1804689 HPS1 T GEN no hist TT pravastatin10 hCV2169762 rs1804689 HPS1 T GEN no hist TT placebo 9 hCV2169762rs1804689 HPS1 T GEN no hist GT pravastatin 47 hCV2169762 rs1804689HPS1 T GEN no hist GT placebo 38 hCV2169762 rs1804689 HPS1 T GEN nohist GG pravastatin 30 hCV2169762 rs1804689 HPS1 T GEN no hist GGplacebo 47 hCV2169762 rs1804689 HPS1 T DOM no hist TT + GTpravastatin 57 hCV2169762 rs1804689 HPS1 T DOM no hist TT + GTplacebo 47 hCV2169762 rs1804689 HPS1 T GEN hist TT pravastatin 5hCV2169762 rs1804689 HPS1 T GEN hist TT placebo 12 hCV2169762rs1804689 HPS1 T GEN hist GT pravastatin 47 hCV2169762 rs1804689HPS1 T GEN hist GT placebo 46 hCV2169762 rs1804689 HPS1 T GEN histGG pravastatin 62 hCV2169762 rs1804689 HPS1 T GEN hist GG placebo56 hCV2169762 rs1804689 HPS1 T REC hist GG + GT pravastatin 109hCV2169762 rs1804689 HPS1 T REC hist GG + GT placebo 102 hCV1348610rs3739636 C9orf46 A GEN hist AA pravastatin 24 hCV1348610 rs3739636C9orf46 A GEN hist AA placebo 19 hCV1348610 rs3739636 C9orf46 A GENhist AG pravastatin 47 hCV1348610 rs3739636 C9orf46 A GEN hist AGplacebo 61 hCV1348610 rs3739636 C9orf46 A GEN hist GG pravastatin43 hCV1348610 rs3739636 C9orf46 A GEN hist GG placebo 35 hCV1348610rs3739636 C9orf46 A DOM hist AA + AG pravastatin 71 hCV1348610rs3739636 C9orf46 A DOM hist AA + AG placebo 80 hCV27511436rs3750145 FZD1 T GEN no hist CC pravastatin 1 hCV27511436 rs3750145FZD1 T GEN no hist CC placebo 3 hCV27511436 rs3750145 FZD1 T GEN nohist CT pravastatin 26 hCV27511436 rs3750145 FZD1 T GEN no hist CTplacebo 16 hCV27511436 rs3750145 FZD1 T GEN no hist TT pravastatin60 hCV27511436 rs3750145 FZD1 T GEN no hist TT placebo 75hCV27511436 rs3750145 FZD1 T DOM no hist CC + CT pravastatin 27hCV27511436 rs3750145 FZD1 T DOM no hist CC + CT placebo 19 noTOTAL_ LOWER_ UPPER_ P_INT_ hCV # event RESP HR_RESP RESP RESPP_RESP RESP hCV2091644 258 271 0.635895 0.31841 1.26996 0.1995630.1798335 hCV2091644 265 286 0.1798335 hCV2091644 736 773 0.8503560.5516 1.31092 0.462931 0.1798335 hCV2091644 768 814 0.1798335hCV2091644 492 528 1.358113 0.82457 2.2369 0.22925 0.1798335hCV2091644 510 537 0.1798335 hCV2091644 994 1044 0.786037 0.544961.13377 0.197677 0.0837336 hCV2091644 1033 1100 0.0837336hCV29539757 96 103 0.411487 0.16926 1.00034 0.050088 0.1548877hCV29539757 92 108 0.1548877 hCV29539757 493 537 0.994615 0.65491.51055 0.979793 0.1548877 hCV29539757 481 525 0.1548877hCV29539757 594 656 1.015618 0.70762 1.45767 0.93301 0.1548877hCV29539757 559 615 0.1548877 hCV29539757 1087 1193 1.0088020.76761 1.32578 0.949874 0.0530448 hCV29539757 1040 1140 0.0530448hCV26505812 638 689 1.081641 0.7293 1.60421 0.696354 0.0696553hCV26505812 653 701 0.0696553 hCV26505812 1349 1443 0.7768620.59335 1.01713 0.066291 0.0696553 hCV26505812 1334 1455 0.0696553hCV26505812 674 730 1.330498 0.88923 1.99075 0.164856 0.0696553hCV26505812 680 721 0.0696553 hCV26505812 1987 2132 0.8638090.69193 1.07838 0.195899 0.0630809 hCV26505812 1987 2156 0.0630809hCV26505812 333 357 1.068105 0.6028 1.89259 0.821407 0.0828923hCV26505812 341 364 0.0828923 hCV26505812 754 789 0.697717 0.454541.071 0.099711 0.0828923 hCV26505812 774 826 0.0828923 hCV26505812395 423 1.570465 0.87695 2.81243 0.128942 0.0828923 hCV26505812 424443 0.0828923 hCV26505812 1087 1146 0.813189 0.57817 1.143740.234739 0.0573322 hCV26505812 1115 1190 0.0573322 hCV2442143 11461218 1.087339 0.78059 1.51463 0.620489 0.1385034 hCV2442143 11751243 0.1385034 hCV2442143 865 953 1.043307 0.77225 1.4095 0.782390 .1787787 hCV2442143 850 932 0.1787787 hCV27830265 474 499 1.4792940.78982 2.77065 0.22133 0.1332561 hCV27830265 445 461 0.1332561hCV2169762 127 137 1.27501 0.51771 3.14008 0.597269 0.102835hCV2169762 145 154 0.102835 hCV2169762 604 651 1.268286 0.827011.94501 0.27599 0.102835 hCV2169762 632 670 0.102835 hCV2169762 753783 0.65902 0.41685 1.04187 0.074354 0.102835 hCV2169762 763 8100.102835 hCV2169762 731 788 1.265576 0.86016 1.86208 0.231932 0.033hCV2169762 777 824 0.033 hCV2169762 119 124 0.336546 0.118470.95606 0.040922 0.1254774 hCV2169762 99 111 0.1254774 hCV2169762511 558 0.94255 0.62771 1.4153 0.775439 0.1254774 hCV2169762 480526 0.1254774 hCV2169762 552 614 1.104484 0.76954 1.58521 0.5898550.1254774 hCV2169762 555 611 0.1254774 hCV2169762 1063 1172 1.027680.7845 1.34624 0.842894 0.0507564 hCV2169762 1035 1137 0.0507564hCV1348610 226 250 0.986092 0.54 1.80071 0.963642 0.1842815hCV1348610 186 205 0.1842815 hCV1348610 566 613 0.740596 0.506241.08345 0.121846 0.1842815 hCV1348610 545 606 0.1842815 hCV1348610378 421 1.276897 0.81723 1.99511 0.283036 0.1842815 hCV1348610 392427 0.1842815 hCV1348610 792 863 0.806434 0.58581 1.11014 0.1870960.1002517 hCV1348610 731 811 0.1002517 hCV27511436 42 43 0.3492070.03631 3.35808 0.362284 0.1652143 hCV27511436 43 46 0.1652143hCV27511436 407 433 1.575251 0.84504 2.93645 0.152693 0.1652143hCV27511436 398 414 0.1652143 hCV27511436 1035 1095 0.85237 0.607011.19691 0.356417 0.1652143 hCV27511436 1099 1174 0,1652143hCV27511436 449 476 1,387947 0,77175 2,49613 0,273626 0,1600111hCV27511436 441 460 0,1600111

TABLE-US-00033 TABLE 33 gene/ chrom GENO hCV # rs # symbol ENDPTMODE STRATA ADJUST TYPE hCV1348610 rs3739636 C9orf46 ATHERO GENWHITE AGEBL GEND01 AG hCV15857769 rs2924914 ATHERO GEN WHITE AGEBLGEND01 TT hCV15857769 rs2924914 ATHERO REC WHITE AGEBL GEND01 TThCV15857769 rs2924914 ATHERO ADD WHITE AGEBL GEND01 T hCV15857769rs2924914 ATHERO GEN WHITE AGEBL GEND01 TT BMI PRESSM DIABADA HTNLDLADJBL HDL44BL hCV15857769 rs2924914 ATHERO REC WHITE AGEBLGEND01 TT BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV15857769rs2924914 ISCHEM GEN WHITE AGEBL GEND01 TT hCV15857769 rs2924914ISCHEM REC WHITE AGEBL GEND01 TT hCV15857769 rs2924914 ISCHEM ADDWHITE AGEBL GEND01 T hCV15857769 rs2924914 ISCHEM GEN WHITE AGEBLGEND01 TT BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV15857769rs2924914 ISCHEM ADD WHITE AGEBL GEND01 T BMI PRESSM DIABADA HTNLDLADJBL HDL44BL hCV15857769 rs2924914 STROKE GEN WHITE AGEBLGEND01 TT hCV16336 rs362277 HD STROKE ADD WHITE AGEBL GEND01 ChCV30308202 rs9482985 LAMA2 ISCHEM REC WHITE AGEBL GEND01 GGhCV30308202 rs9482985 LAMA2 ISCHEM REC WHITE AGEBL GEND01 GG BMIPRESSM DIABADA HTN LDLADJBL HDL44BL 95% 95% P- Lower Upper VALUE CLfor CL for 2- 2DF P- hCV # EVENTS TOTAL HR HR HR sided) VALUEhCV1348610 147 1809 1.28 0.97 1.70 0.087 0.232 hCV15857769 31 3101.52 1.03 2.26 0.036 0.111 hCV15857769 31 310 1,47 1,01 2,13 0,046. hCV15857769 . . 1,19 0,99 1,43 0,066 . hCV15857769 30 300 1.460.98 2.17 0.067 0.186 hCV15857769 30 300 1.4 0.96 2.06 0.083 .hCV15857769 41 310 1.42 1.01 1.99 0.044 0.127 hCV15857769 41 3101.36 0.98 1.88 0.064 . hCV15857769 . . 1,16 0,99 1,35 0,060 .hCV15857769 40 300 1,36 0,97 1,93 0,078 0,202 hCV15857769 . . 1.140.98 1.34 0.093 . hCV15857769 48 310 1,32 0,96 1,80 0,084 0,220hCV16336 . . 1,2 0,97 1,49 0,093 . hCV30308202 280 2509 1,21 0,981,50 0,080 . hCV30308202 275 2458 1,21 0,98 1,51 0,080 .

TABLE-US-00034 TABLE 34 gene/ chrom GENO hCV # rs # symbol ENDPTMODE STRATA ADJUST TYPE hCV1348610 rs3739636 C9orf46 ATHERO GENBLACK AGEBL GEND01 AA BMI PRESSM DIABADA HTN LDLADJBL HDL44BLhCV1348610 rs3739636 C9orf46 ATHERO ADD BLACK AGEBL GEND01 A BMIPRESSM DIABADA HTN LDLADJBL HDL44BL hCV1348610 rs3739636 C9orf46ISCHEM GEN BLACK AGEBL GEND01 AA BMI PRESSM DIABADA HTN LDLADJBLHDL44BL hCV1348610 rs3739636 C9orf46 ISCHEM ADD BLACK AGEBL GEND01A BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV1348610 rs3739636C9orf46 STROKE GEN BLACK AGEBL GEND01 AA BMI PRESSM DIABADA HTNLDLADJBL HDL44BL hCV1348610 rs3739636 C9orf46 STROKE REC BLACKAGEBL GEND01 AA BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV1348610rs3739636 C9orf46 STROKE ADD BLACK AGEBL GEND01 A BMI PRESSMDIABADA HTN LDLADJBL HDL44BL hCV1619596 rs1048621 SDCBP2 ISCHEM GENBLACK AGEBL GEND01 AA hCV1619596 rs1048621 SDCBP2 ISCHEM REC BLACKAGEBL GEND01 AA hCV1619596 rs1048621 SDCBP2 ISCHEM GEN BLACK AGEBLGEND01 AA BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV1619596rs1048621 SDCBP2 ISCHEM REC BLACK AGEBL GEND01 AA BMI PRESSMDIABADA HTN LDLADJBL HDL44BL hCV1619596 rs1048621 SDCBP2 STROKE GENBLACK AGEBL GEND01 AA hCV1619596 rs1048621 SDCBP2 STROKE REC BLACKAGEBL GEND01 AA hCV1619596 rs1048621 SDCBP2 STROKE GEN BLACK AGEBLGEND01 AA BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV1619596rs1048621 SDCBP2 STROKE REC BLACK AGEBL GEND01 AA BMI PRESSMDIABADA HTN LDLADJBL HDL44BL hCV16336 rs362277 HD ISCHEM GEN BLACKAGEBL GEND01 CT hCV16336 rs362277 HD ISCHEM GEN BLACK AGEBL GEND01CT BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV1723718 rs12481805UMODL1 ATHERO GEN BLACK AGEBL GEND01 AA hCV1723718 rs12481805UMODL1 ATHERO REC BLACK AGEBL GEND01 AA hCV1723718 rs12481805UMODL1 ATHERO GEN BLACK AGEBL GEND01 AA BMI PRESSM DIABADA HTNLDLADJBL HDL44BL hCV1723718 rs12481805 UMODL1 ATHERO REC BLACKAGEBL GEND01 AA BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV1723718rs12481805 UMODL1 ISCHEM GEN BLACK AGEBL GEND01 AA hCV1723718rs12481805 UMODL1 ISCHEM REC BLACK AGEBL GEND01 AA hCV1723718rs12481805 UMODL1 ISCHEM GEN BLACK AGEBL GEND01 AA BMI PRESSMDIABADA HTN LDLADJBL HDL44BL hCV1723718 rs12481805 UMODL1 ISCHEMREC BLACK AGEBL GEND01 AA BMI PRESSM DIABADA HTN LDLADJBL HDL44BLhCV25596936 rs6967117 EPHA1 STROKE GEN BLACK AGEBL GEND01 TT BMIPRESSM DIABADA HTN LDLADJBL HDL44BL hCV25596936 rs6967117 EPHA1STROKE REC BLACK AGEBL GEND01 TT BMI PRESSM DIABADA HTN LDLADJBLHDL44BL hCV27077072 rs8060368 ATHERO REC BLACK AGEBL GEND01 CChCV27077072 rs8060368 ATHERO ADD BLACK AGEBL GEND01 C hCV27077072rs8060368 ATHERO ADD BLACK AGEBL GEND01 C BMI PRESSM DIABADA HTNLDLADJBL HDL44BL hCV27077072 rs8060368 ISCHEM ADD BLACK AGEBLGEND01 C hCV8754449 rs781226 TESK2 ATHERO GEN BLACK AGEBL GEND01 CTBMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV8754449 rs781226 TESK2ISCHEM GEN BLACK AGEBL GEND01 CT BMI PRESSM DIABADA HTN LDLADJBLHDL44BL 95% 95% P - Unterer oberer WERT CL für CL für (2- 2DF P- hCV #EVENTS TOTAL HR HR HR seitig) WERT hCV1348610 17 151 2,03 0,93 4.400.074 0,203 hCV1348610 . . 1,41 0,97 2,06 0,073 . hCV1348610 20 1511,83 0,91 3,67 0,089 0,214 hCV1348610 . . .hCV1348610 25 151 1,75 0,94 3,23 0,076 0,173 hCV1348610 25 151 1,560,96 2,54 0,075 . hCV1348610 . . 1,33 0,98 1,82 0,072 . hCV16195966 22 2,36 1,00 5,60 0,051 0,150 hCV1619596 6 22 2,28 0,98 5.320.055 . hCV1619596 5 20 2,66 1,02 6,90 0,045 0,133 hCV1619596 5 202,54 1,00 6,46 0,050 . hCV1619596 7 22 2,15 0,97 4,75 0,059 0,165hCV1619596 7 22 2,12 0,97 4,61 0,059 . hCV1619596 6 20 2,24 0,955,31 0,067 0,185 hCV1619596 6 20 2,2 0,95 5,14 0,068 . HCV16336 43326 1,68 0,92 3,07 0,094 0,083 HCV16336 41 309 1,95 1,02 3,71 0,0430,033 HCV1723718 3 8 3,95 1,21 12.91 0,023 0,046 HCV1723718 3 84.15 1.023 0,046 HCV1723718 3 84,15 1.023 0,046 0,046 HCV1723718 3 84.15 1.023 0,046 0,046 0,046 0,046 0,046 0,046. hCV1723718 3 8 3,4 1,00 11,56 0,051 0,085hCV1723718 3 8 3,61 1,07 12,22 0,039 . hCV1723718 3 8 3,26 1,0110,59 0,049 0,073 hCV1723718 3 8 3,46 1,07 11,17 0,038 . hCV17237183 8 3,08 0,92 10,32 0,068 0,096 hCV1723718 3 8 3,29 0,99 10.950.052 . hCV25596936 1 4 7 0,80 61,25 0,079 0,170 hCV25596936 1 46,66 0,77 58,06 0,086 . hCV27077072 48 444 1,78 0,96 3,29 0,066 .hCV27077072 . . 1,82 1,03 3,24 0,041 . hCV27077072 . . 1,64 0,912,95 0,097 . hCV27077072 . . 1,56 0,94 2,59 0,087 . hCV8754449 35297 1,86 0,99 3,46 0,052 0,081 hCV8754449 39 297 1,8 1,01 3.240.048 0,085

TABLE-US-00035 TABLE 35 gene/ chrom GENO- hCV # rs # symbol ENDPTMODE STRATA ADJUST TYPE hCV11425801 rs3805953 PEX6 ISCHEM GEN WHITEAGEBL GEND01 CT BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV11425801rs3805953 PEX6 STROKE GEN WHITE AGEBL GEND01 CT BMI PRESSM DIABADAHTN LDLADJBL HDL44BL hCV1348610 rs3739636 C9orf46 ATHERO DOM WHITEAGEBL GEND01 AG + AA hCV1348610 rs3739636 C9orf46 ATHERO GEN WHITEAGEBL GEND01 AG BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV1348610rs3739636 C9orf46 ATHERO DOM WHITE AGEBL GEND01 AG + AA BMI PRESSMDIABADA HTN LDLADJBL HDL44BL hCV15857769 rs2924914 ATHERO ADD WHITEAGEBL GEND01 T BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV15857769rs2924914 ISCHEM DOM WHITE AGEBL GEND01 TC + TT hCV15857769rs2924914 ISCHEM REC WHITE AGEBL GEND01 TT BMI PRESSM DIABADA HTNLDLADJBL HDL44BL hCV15857769 rs2924914 STROKE REC WHITE AGEBLGEND01 TT hCV15857769 rs2924914 STROKE ADD WHITE AGEBL GEND01 ThCV15857769 rs2924914 STROKE GEN WHITE AGEBL GEND01 TT BMI PRESSMDIABADA HTN LDLADJBL HDL44BL hCV15857769 rs2924914 STROKE REC WHITEAGEBL GEND01 TT BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV15857769rs2924914 STROKE ADD WHITE AGEBL GEND01 T BMI PRESSM DIABADA HTNLDLADJBL HDL44BL hCV16158671 rs2200733 STROKE GEN WHITE AGEBLGEND01 TT hCV16158671 rs2200733 STROKE REC WHITE AGEBL GEND01 TThCV16158671 rs2200733 STROKE GEN WHITE AGEBL GEND01 TT BMI PRESSMDIABADA HTN LDLADJBL HDL44BL hCV16158671 rs2200733 STROKE REC WHITEAGEBL GEND01 TT BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV16336rs362277 HD STROKE GEN WHITE AGEBL GEND01 CC hCV16336 rs362277 HDSTROKE DOM WHITE AGEBL GEND01 CT + CC hCV16336 rs362277 HD STROKEREC WHITE AGEBL GEND01 CC hCV16336 rs362277 HD STROKE ADD WHITEAGEBL GEND01 C BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV29401764rs7793552 LOC646588 ISCHEM REC WHITE AGEBL GEND01 CC hCV30308202rs9482985 LAMA2 ISCHEM ADD WHITE AGEBL GEND01 G hCV30308202rs9482985 LAMA2 ISCHEM ADD WHITE AGEBL GEND01 G BMI PRESSM DIABADAHTN LDLADJBL HDL44BL hCV30308202 rs9482985 LAMA2 STROKE REC WHITEAGEBL GEND01 GG hCV32160712 rs11079160 ATHERO GEN WHITE AGEBLGEND01 TT hCV32160712 rs11079160 ATHERO Rec White AgeBl Gend01 TTHCV32160712 RS11079160 AThero Gen White AgeBl Gend01 TT BMI PressMdiabada HTN LDLADJBL HDL4BL HDL4BL HCV32160712 RS11079160 HDL4BL HDL LOBL LOBL LOBL FRECHIT AGEHIT GEND GENT01 TTDL. # EVENTSTOTAL HR HR HR sided) VALUE hCV11425801 206 1814 1.17 0.928 1.480.1834 0.1314 hCV11425801 254 1814 1.15 0.933 1.418 0.1894 0.1374hCV1348610 205 2556 1.25 0.953 1.631 0.108 . hCV1348610 143 17631,25 0,938 1,658 0,1286 0,3147 hCV1348610 201 2499 1,22 0,933 1,6050,1444 . hCV15857769 . . 1,17 0,969 1,403 0,1033 . hCV15857769 1871704 1,16 0,942 1,422 0,165 . hCV15857769 40 300 1,31 0,942 1,8210,1092 . hCV15857769 48 310 1,28 0,947 1,723 0,1093 . hCV15857769 .. 1,12 0,974 1,288 0,1112 . hCV15857769 47 300 1,29 0,939 1,7660.1172 0,2918 hCV15857769 47 300 1,26 0,928 1,702 0,1394 .hCV15857769 . . 1,11 0,96 1,274 0,1632 . hCV16158671 16 90 1.410.853 2.323 0.1811 0.4076 hCV16158671 16 90 1.4 0.85 2.306 0.1856 .hCV16158671 16 88 1.48 0.895 2.443 0.1272 0.3047 hCV16336 408 30302.2 0.707 6.862 0.1734 0.2057 hCV16336 495 3764 2.14 0.689 6.6770.188 . hCV16336 408 3030 1,19 0,944 1,49 0,1428 . hCV16336 . .1,16 0,937 1,44 0,1709 . hCV29401764 199 1792 1,15 0,941 1,3950,1757 . hCV30308202 . . 1,14 0,946 1,368 0,1694 . hCV30308202 . .1,14 0,949 1,374 0,1586 . hCV30308202 342 2509 1,14 0,942 1,3760,1802 . hCV32160712 13 119 1,47 0,835 2,572 0,183 0,3099hCV32160712 13 119 1,5 0,858 2,617 0,1551 . hCV32160712 13 117 1.490.851 2.626 0.1621 0.2277 hCV32160712 13 117 1.54 0.883 2.6980.1277 .

TABLE-US-00036 TABLE 36 gene/ chrom GENO hCV # rs # symbol ENDPTMODE STRATA ADJUST TYPE hCV11425801 rs3805953 PEX6 ISCHEM GEN BLACKAGEBL GEND01 CT hCV11425801 rs3805953 PEX6 ISCHEM GEN BLACK AGEBLGEND01 CT BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV11425801rs3805953 PEX6 STROKE GEN BLACK AGEBL GEND01 CT hCV11425801rs3805953 PEX6 STROKE GEN BLACK AGEBL GEND01 CT BMI PRESSM DIABADAHTN LDLADJBL HDL44BL hCV11425842 rs10948059 GNMT ATHERO GEN BLACKAGEBL GEND01 CC BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV11425842rs10948059 GNMT ATHERO REC BLACK AGEBL GEND01 CC BMI PRESSM DIABADAHTN LDLADJBL HDL44BL hCV11425842 rs10948059 GNMT ATHERO ADD BLACKAGEBL GEND01 C BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV11425842rs10948059 GNMT STROKE GEN BLACK AGEBL GEND01 CC BMI PRESSM DIABADAHTN LDLADJBL HDL44BL hCV11425842 rs10948059 GNMT STROKE ADD BLACKAGEBL GEND01 C BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV1348610rs3739636 C9orf46 ATHERO GEN BLACK AGEBL GEND01 AA hCV1348610rs3739636 C9orf46 ATHERO DOM BLACK AGEBL GEND01 AG + AA BMI PRESSMDIABADA HTN LDLADJBL HDL44BL hCV1348610 rs3739636 C9orf46 ATHEROREC BLACK AGEBL GEND01 AA BMI PRESSM DIABADA HTN LDLADJBL HDL44BLhCV1348610 rs3739636 C9orf46 ISCHEM REC BLACK AGEBL GEND01 AA BMIPRESSM DIABADA HTN LDLADJBL HDL44BL hCV1619596 rs1048621 SDCBP2ISCHEM ADD BLACK AGEBL GEND01 A hCV1619596 rs1048621 SDCBP2 ISCHEMADD BLACK AGEBL GEND01 A BMI PRESSM DIABADA HTN LDLADJBL HDL44BLhCV16336 rs362277 HD ATHERO GEN BLACK AGEBL GEND01 CT BMI PRESSMDIABADA HTN LDLADJBL HDL44BL hCV16336 rs362277 HD ISCHEM DOM BLACKAGEBL GEND01 CT + CC BMI PRESSM DIABADA HTN LDLADJBL HDL44BLhCV16336 rs362277 HD STROKE GEN BLACK AGEBL GEND01 CT BMI PRESSMDIABADA HTN LDLADJBL HDL44BL hCV1723718 rs12481805 UMODL1 STROKEGEN BLACK AGEBL GEND01 AA hCV1723718 rs12481805 UMODL1 STROKE RECBLACK AGEBL GEND01 AA hCV1723718 rs12481805 UMODL1 STROKE GEN BLACKAGEBL GEND01 AA BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV1723718rs12481805 UMODL1 STROKE REC BLACK AGEBL GEND01 AA BMI PRESSMDIABADA HTN LDLADJBL HDL44BL hCV25596936 rs6967117 EPHA1 STROKE GENBLACK AGEBL GEND01 TT hCV25596936 rs6967117 EPHA1 STROKE REC BLACKAGEBL GEND01 TT hCV27077072 rs8060368 ATHERO REC BLACK AGEBL GEND01CC BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV27077072 rs8060368ISCHEM REC BLACK AGEBL GEND01 CC hCV27077072 rs8060368 ISCHEM ADDBLACK AGEBL GEND01 C BMI PRESSM DIABADA HTN LDLADJBL HDL44BLhCV29401764 rs7793552 LOC646588 STROKE GEN BLACK AGEBL GEND01 CChCV29401764 rs7793552 LOC646588 STROKE REC BLACK AGEBL GEND01 CChCV29401764 rs7793552 LOC646588 STROKE GEN BLACK AGEBL GEND01 CCBMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV29401764 rs7793552LOC646588 STROKE REC BLACK AGEBL GEND01 CC BMI PRESSM DIABADA HTNLDLADJBL HDL44BL hCV8754449 rs781226 TESK2 ATHERO GEN BLACK AGEBLGEND01 CT hCV8754449 rs781226 TESK2 ATHERO DOM BLACK AGEBL GEND01CT + CC BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV8754449 rs781226TESK2 ISCHEM DOM BLACK AGEBL GEND01 CT + CC BMI PRESSM DIABADA HTNLDLADJBL HDL44BL hCV8754449 rs781226 TESK2 STROKE GEN BLACK AGEBLGEND01 CT BMI PRESSM DIABADA HTN LDLADJBL HDL44BL hCV8942032rs1264352 DDR1 STROKE GEN BLACK AGEBL GEND01 CG hCV8942032rs1264352 DDR1 STROKE GEN BLACK AGEBL GEND01 CG BMI PRESSM Diabadahtn Ldladjbl HDL44BL 95% 95% P-unterer oberer Wert CL für CL für (2-2DF P-HCV # Ereignisse Gesamt HR HR HR HR SITIDD SITIDT) 184 1,35 0,865 2,119 0,1854 0,1546HCV11425801 29 177 1,39 0,88 2,209 0,1574 0,145 HCV11425842 19 1581,63 0,789 3.384 0,1864 0,3447 HCV11425842 19 1584 0,6287 HCV114258282 19 hCV11425842 . . 1,29 0,894 1,872 0,1716 . hCV11425842 25158 1,51 0,822 2,78 0,1837 0,4087 hCV11425842 . . 1,23 0,908 1,6640,181 . hCV1348610 17 157 1,64 0,769 3,515 0,1995 0,4376 hCV134861039 427 1,72 0,865 3,421 0,1223 . hCV1348610 17 151 1,54 0,855 2,7860,1497 . hCV1348610 20 151 1,57 0,91 2,713 0,1048 . hCV1619596 . .1,33 0,902 1,954 0,1502 . hCV1619596 . . 1,37 0,904 2,084 0,1373 .hCV16336 34 309 1,61 0,832 3,118 0,1574 0,1458 hCV16336 53 469 1,60,853 3 0,1434 . hCV16336 48 309 1,44 0,846 2,456 0,1788 0,1231hCV1723718 3 8 2,45 0,763 7,88 0,1323 0,1146 hCV1723718 3 8 2,28 0,692 7,493 0,1755 0,1501hCV1723718 3 8 2,44 0,746 8,015 0,1401 . HCV25596936 1 4 4,13 0,55131,03 0,1676 0,3443 HCV25596936 1 4 4,04 0,539 30,26 0,1741 hCV27077072 53 444 1.480.859 2.566 0.1567 . hCV27077072 . . 1,51 0,891 2,567 0,125 .hCV29401764 13 61 1,62 0,855 3,084 0,1382 0,3119 hCV29401764 13 611,58 0,873 2,848 0,1313 . hCV29401764 12 57 1,62 0,836 3,15 0,15290,3156 hCV29401764 12 57 1,61 0,87 2,981 0,1291 . hCV8754449 36 3101,49 0,836 2,657 0,1758 0,1929 hCV8754449 43 414 1,61 0,879 2,9660,1228 . hCV8754449 49 414 1,59 0,899 2,806 0,1107 . hCV8754449 46297 1,39 0,847 2,289 0,192 0,1777 hCV8942032 38 244 1,34 0,8672,058 0,1894 0,1396

TABLE-US-00037 TABLE 37 hCV # (C9p21 rs # (C9p21 GENO- SNP) SNP)ADJUST MODE TYPE STATIN EVENTS hCV26505812 rs10757274 unadjustedGEN AA Pravastatin 17 hCV26505812 rs10757274 unadjusted GEN AAPlacebo 17 hCV26505812 rs10757274 unadjusted GEN AG Pravastatin 27hCV26505812 rs10757274 unadjusted GEN AG Placebo 48 hCV26505812rs10757274 unadjusted GEN GG Pravastatin 23 hCV26505812 rs10757274unadjusted GEN GG Placebo 25 hCV26505812 rs10757274 unadjusted DOMAG + AA Pravastatin 44 hCV26505812 rs10757274 unadjusted DOM AG +AA Placebo 65 hCV26505812 rs10757274 unadjusted REC AG + GGPravastatin 50 hCV26505812 rs10757274 unadjusted REC AG + GGPlacebo 73 hCV26505812 rs10757274 AGE MALE CURRSMK GEN AAPravastatin 18 HYPERTEN_1 DIABETES_1 BMI BASE_LDL BASE_HD1hCV26505812 rs10757274 AGE_MALE CURRSMK GEN AA Placebo 17HYPERTEN_1 DIABETES_1 BMI BASE_EDL BASE_HD1 hCV26505812 rs10757274AGE_MALE CURRSMK GEN GA Pravastatin 29 HYPERTEN_1 DIABETES_1 BMIBASE_EDL BASE_HD1 hCV26505812 rs10757274 AGE_MALE CURRSMK GEN GAPlacebo 50 HYPERTEN_1 DIABETES_1 BMI BASE_EDL BASE_HD1 hCV26505812rs10757274 AGE_MALE CURRSMK GEN GG Pravastatin 25 HYPERTEN_1DIABETES_1 BMI BASE_EDL BASE_HD1 hCV26505812 rs10757274 AGE MALECURRSMK GEN GG Placebo 26 HYPERTEN_1 DIABETES_1 BMI BASE_EDLBASE_HD1 hCV26505812 rs10757274 AGE MALE CURRSMK REC GA + AAPravastatin 47 HYPERTEN_1 DIABETES_1 BMI BASE_EDL BASE_HD1hCV26505812 rs10757274 AGE MALE CURRSMK REC GA + AA Placebo 67HYPERTEN_1 DIABETES_1 BMI BASE_EDL BASE_HD1 hCV26505812 rs10757274AGE MALE CURRSMK DOM GA + GG Pravastatin 54 HYPERTEN_1 DIABETES_1BMI BASE_EDL BASE_HD1 hCV26505812 rs10757274 ALTER MÄNNLICH CURRSMK DOMGA + GG Placebo 76 HYPERTEN_1 DIABETES_1 BMI BASE_EDL BASE_HD1 95 % 95 % Verhältnis WERT TXhCV26505812 315 0,85 0,433 1,667 0,6359 0,44429 hCV26505812 262 ref. . . 0,44429 hCV26505812 666 0,58 0,361 0,927 0,0229 0,44429hCV26505812 689 ref . . . 0,44429 hCV26505812 414 0,91 0,515 1,5990,7377 0,44429 hCV26505812 412 ref . . . 0,44429 hCV26505812 9810,65 0,446 0,96 0,03 0,34883 hCV26505812 951 ref . . . 0,34883hCV26505812 1080 0,69 0,484 0,994 0,0463 0,65126 hCV26505812 1101ref . . . 0,65126 hCV26505812 328 0,92 0,469 1,802 0,8064 0,43653hCV26505812 272 ref . . . 0,43653 hCV26505812 690 0,61 0,384 0,9630,0339 0,43653 hCV26505812 727 ref . . . 0,43653 hCV26505812 441 10,574 1,732 0,9924 0,43653 hCV26505812 425 ref . . . 0,43653hCV26505812 1018 0,69 0,476 1,005 0,0533 0,3725 hCV26505812 999 ref. . . 0,3725 hCV26505812 1131 0,73 0,512 1,03 0,0728 0,60059hCV26505812 1152 ref . . . 0,60059

TABLE-US-00038 TABLE 38 for chromosome 9p21 SNP(rs10757274/hCV26505812): HR_ LOWER_ UPPER_ P_ Risk GENO_ EVENTS_no TOTAL_ RESP_ RESP_ RESP_ RESP_ ENDPT allele MODE STRATA RESPSTATIN RESP event RESP unadj unadj unadj unadjrava stroke G GEN ALL 5.2.8 p 8 prava3.1 8 ggstatin . 41 680 721 Stroke G Dom All GG + Agpravastatin 145 1932 0.692 1.078 0.196 Stroke G Dom Allgg + AG Placebo 169 1987 Stroke G REC All AA + AG Pravastatin150 2173 0.919 0.73 0.455 Stroke G REC All aa + Agplacebo 2176 Stroke G GEN no Hist GG Pravastatin 24 333357 1.068 0.603 1.893 0.821 Stroke G GEN no Hist GG Placebo 23 341364 Stroke G GEN no Hist AG Pravastatin 35 754 789 0.698 0.4551,071 0.100 Stroke AG 7 Gbo Gen no Hist AA Pravastatin 28 395 423 1.570 0.812 0.129 Strece GGEN No Hist aa placebo 19 424 443 Strece G Dom No Hist GG + Agpravavavavavel 59 10813 0.578 1,144 0 Hist AA + AGPRAPASTATIN 1212 0.660 + AG placebo 71 1198 1269 stroke G GEN hist GG pravastatin27 305 332 1098 0637 1892 0736 stroke G GEN hist GG placebo 25312 337 stroke G GEN hist AG pravastatin 59 595 654 0.816 0.5761.155 Place 629 Stroke G Genhist aa pravastatin 28 279 307 1.093 0.625 1.911 0.755 Stroke G Genhist AA Placebo 22 256 278 Streok Hist GG GG + AG + AG PAVAVAVEL 886 0.892 0.66 0.66 0.66 0.66. G DOM Hist GG + AG Placebo94 872 966 Stroke G REC Hist AA + AG Pravastatin 87 874 961 0.8850,660 1.187 0.415 Stroke G REC Hist AA + AG Placebo 91 816 907 PLA- PLA- PLA- PLA- PLA- PLA- Endt allelemode unadj adj adj cebo cebo cebo cebo cebo stroke G Gen070 0.602 001 1.20631 0.79513 1.83079 Stroke GGEN 0.070 Stroke G Gen 070 0.055 1.4644444441.0868 0 0.050 route Gen 0.0700.158 0.050 AA 41 721 REF 0 0 0.070 0.050 Stroke Gom 0.063 0.0555 GG + AG 169 2156 1.38105 GG + AG 169 2156 1.9818888888888. stroke G REC 0.472 0.432 0.398 AA+ AG stroke G REC 0.472 0.398 stroke G GEN 0.083 0.824 0.065 GG 23364 1.50713 0.82085 2.7672 0.18578 stroke G GEN 0.083 0.065 strokeG GEN 0.083 0.077 0.065 AG 52 826 1.48278 0.87679 2.5076 0.1417stroke G GEN 0.083 0.065 stroke G GEN 0.083 0.108 0.065 AA 19 443ref 0 0 stroke G Gen 0.083 0.065 stretch DOM 0.191 0.049GG + AG 75 1190 1.489 0.90012 0.12109 Stroke G DOM 0.0570.049 0.636 0.63 0.63 0.63 0.63 0.630 AAL +AGRECKREC. stroke G GEN 0.535 0.650 0.576 GG 25 337 0.91337 0.514991.6199 0.75659 stroke G GEN 0.535 0.576 stroke G GEN 0.535 0.3230.576 AG 69 629 1.37223 0.84919 2.2174 0.19624 stroke G GEN 0.5350.576 stroke G GEN 0.535 0.978 0.576 AA 22 278 ref 0 0 0 stroke GGEN 0.535 0.576 stroke G DOM 0.508 0.552 0.576 GG + AG 94 9661.21007 0.76069 1.9249 0.42078 stroke G DOM 0.508 0.576 stroke GREC 0.500 0.420 0.450 AA0 + AG G REC 0.5

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references

• seqdata.uspto.gov/?pageRequest=docDetail&DocID=US20200377950A1