Laurie, Cathy C.

Background: Risk for venous thromboembolism has a strong genetic component. Whole genome sequencing from the TOPMed program (Trans-Omics for Precision Medicine) allowed us to look for new associations, particularly rare variants missed by standard genome-wide association studies. Methods: The 3793 cases and 7834 controls (11.6% of cases were individuals of African, Hispanic/Latino, or Asian ancestry) were analyzed using a single variant approach and an aggregate gene-based approach using our primary filter (included only loss-of-function and missense variants predicted to be deleterious) and our secondary filter (included all missense variants). Results: Single variant analyses identified associations at 5 known loci. Aggregate gene-based analyses identified only PROC (odds ratio, 6.2 for carriers of rare variants; P =7.4×10 −14 ) when using our primary filter. Employing our secondary variant filter led to a smaller effect size at PROC (odds ratio, 3.8; P =1.6×10 −14 ), while excluding variants found only in rare isoforms led to a larger one (odds ratio, 7.5). Different filtering strategies improved the signal for 2 other known genes: PROS1 became significant (minimum P =1.8×10 −6 with the secondary filter), while SERPINC1 did not (minimum P =4.4×10 −5 with minor allele frequency <0.0005). Results were largely the same when restricting the analyses to include only unprovoked cases; however, one novel gene, MS4A1 , became significant ( P =4.4×10 −7 using all missense variants with minor allele frequency <0.0005). Conclusions: Here, we have demonstrated the importance of using multiple variant filtering strategies, as we detected additional genes when filtering variants based on their predicted deleteriousness, frequency, and presence on the most expressed isoforms. Our primary analyses did not identify new candidate loci; thus larger follow-up studies are needed to replicate the novel MS4A1 locus and to identify additional rare variation associated with venous thromboembolism.

BACKGROUND: Recent genome-wide association studies (GWAS) have identified a number of novel SNPs associated with blood pressure and hypertension-related traits although studies were very large (approaching 80K participants) and effect sizes were modest with per allele effect sizes as small variants as a single millimeter of mercury difference in blood pressure. However, because hypertension is the most potent modifiable risk factor for ischemic stroke, lowering blood pressure by a few mm Hg can translate into measurable decrease in stroke risk. METHODS: We investigated 22 hypertension (HTN) associated SNPs in a case-control analysis of ischemic stroke in multiple stroke studies including the Siblings With Ischemic Stroke Study (SWISS), the Ischemic Stroke Genetics Study (ISGS), the Bio-Repository of DNA in Stroke (BRAINS), the Vitamin Intervention for Stroke Prevention (VISP) trial, and the Women's Health Initiative (WHI). SWISS/ISGS/BRAINS were analyzed together and included subtype information. Genotyping was funded through the individual studies, the Genomics and Randomized Trials Network (GARNET) consortium, and the SHARe (SNP Health Association Resource). All studies had both raw and imputed GWAS data. Analyses included the following phenotypes: all ischemic stroke, stroke subtypes, and age-at-stroke-onset and were stratified by race. Analyses were minimally adjusted for age, sex and principal components 1 & 2. Alpha was set at 0.05. RESULTS: Eleven of the SNPs from the HTN GWAS were associated with ischemic stroke in European ancestry from one or more of the study populations. Two SNPs on chromosome 12 and one on chromosome 21 were associated in multiple European ancestry cohorts. No SNP was associated in all studies. A SNP previously associated with HTN in African ancestry populations was associated with stroke in African-Americans. Analysis of subtypes found associations with small vessel disease and cardioembolic stroke but not large artery disease. The case-only age-at-stroke-onset analysis also found associations for the two SNPs on chromosome 12. CONCLUSION: These data suggest that candidate SNPs from a HTN GWAS may be associated with ischemic stroke and warrant further investigation. Racial differences were observed. Replication in populations from the other SiGN (Stroke Genetics Network), GENEVA (Gene Environment Association Studies) consortium, and the ISGC (International Stroke Genetics Consortium) studies are underway.

Background: The Trans-Omics for Precision Medicine (TOPMed) program is performing whole-genome sequencing across multiple studies, including longitudinal cohorts, case-control, and case-only sample sets. Detecting the effects of low frequency variants requires large sample sizes, which can only be achieved by combining data across diverse study designs, including matching of case-only sample sets with controls from other studies. Here we present a strategy for combined analysis of venous thromboembolism (VTE) case status in 3 longitudinal cohorts and 3 case-only sample sets, in the context of whole-genome association studies. Methods: For each cohort study, we sampled ‘pure’ controls (without replacement) from the risk set of each incident case, within strata defined by sex, ancestry and birth-cohort. Pure controls had no event throughout their period of observation. A case’s risk set was defined as controls with no prior VTE history and under observation through an age at least as old as the case. For case-only sample sets, controls for each case were sampled from a cohort study, using the same risk set definition. Because of limited overlap in birth years between the cohort studies and the case-only sample sets, this matching was done within strata defined only by sex and ancestry group. Mixed model logistic regression will be used to account for relatedness as a random effect. Although conditional logistic regression is not practical for whole-genome association studies, case-control matching is implicitly recognized by a fixed effect for age-at-event for each matched set (1 case and >=1 matched controls). Additional fixed effects will include sample set and sex. We will also adjust for variations in case-control ratio among the matched sets. Results: In two cohort studies, we matched 1,231 cases to 4,820 controls (overall ratio = 1:3.9); only 500 controls and 5 cases could not be matched. For the case-only sample sets we matched 2,141 cases to 2,780 controls from one cohort study (overall ratio = 1:1.3); zero controls and only 14 cases could not be matched. Conclusions: We were successfully able to match nearly all cases to controls, and more than 90% of controls were also matched. By matching controls to cases based on age at event, we can account for the different risk of VTE by age clusters. Although this strategy does not provide an asymptotically unbiased estimated of the hazard ratio, compared to classical risk set sampling, it uses a large portion of the available data, it provides odds ratio estimates yielding the correct sign of association, and it reduces the potential influence of resampling subjects with rare variants. This strategy also enables combined analysis of multiple studies with different designs.

Abstract Abstract 873 Introduction: Clonal chromosomal anomalies have been well-characterized in the blood cells of patients with Chronic Lymphocytic Leukemia (CLL) and other hematological malignancies. However, the frequencies and types of chromosomal anomalies found in “normal” people (i.e. no history of hematological cancer) are much less well known. Here we compare chromosomal anomalies in untreated CLL patients with those found in a large sample of people (n>50,000) recruited for genome-wide association studies in the Gene Environment Association Studies (GENEVA) consortium. This comparison provides information about the extent to which people without a prior history of hematological cancer have chromosomal anomalies that are characteristic of CLL. Methods and Results: The anomaly detection method focused on acquired, rather than inherited, chromosomal anomalies identified in whole blood samples. The method and results for the GENEVA subjects were published recently (Laurie et al. 2012, Nat. Gen. 44:642–650). The same method was applied to pre-treatment samples from 220 CLL patients from US Intergroup Trial E2997 of the Eastern Cooperative Oncology Group (ECOG). Acquired anomalies were detected as mosaic mixtures of normal disomic cells along with cells containing autosomal anomalies consisting of large (generally > 1 Mb) deletions, duplications and/or acquired uniparental disomy (UPD). Detection requires a large fraction of cells with the same abnormal karyotype (>5–10%), which is presumably of clonal origin. The subjects (of all ages) came from 12 different GENEVA studies, which addressed a variety of health conditions not directly related to hematological cancer (e.g. addiction and glaucoma). DNA was extracted mainly from blood samples (or, in 8% of subjects, from buccal/saliva samples) and genotyped on Illumina SNP mircroarrays. Clonal mosaic anomalies were detected from change points in intensity and genotype data (B Allele Frequency and Log R Ratio). We found 514 anomalies in 404 GENEVA subjects out of 50,222 examined (0.8% of subjects), although the prevalence increased with age. Clinical data from about 75% of subjects with a clonal chromosomal abnormality revealed that only a small fraction (2.8%, 95% CI=1.0 – 4.7%) had a record of prior hematological cancer. In the ECOG study, blood samples from 220 CLL patients enrolled in protocol E2997 were genotyped on the Illumina HumanOmni1-Quad_v1 array and clonal mosaic chromosome anomalies were detected using the GENEVA method. Chromosomal anomalies typical of CLL also were identified using interphase FISH (i.e. 6q23.3-, 11q22-, 12q15+, 13q14-, 17p13-) as previously reported (Grever, JCO 25:799-804). We found 489 anomalies in 148 patients of the 220 examined (67% of patients). The anomalies detected by FISH and SNP microarray were highly concordant (>98%). Although, the most common recurrent anomalies occurred on chromosomes 6, 11, 12, 13 and 17 in regions that span the FISH probes (except for chromosome 6), a majority of the anomalies detected by SNP data (74% of 489) were not detected by the CLL FISH panel. The frequency of large chromosomal anomalies was much higher in CLL patients than in GENEVA (67% versus 0.8% of subjects) and the overall composition of anomaly types found was also different. The fraction of anomalies consisting of acquired UPD was substantially higher in GENEVA subjects than in ECOG (34.0% versus 10.6%), while deletions were less common in GENEVA (50.1% versus 72.4%) and duplications were similar (15.6% versus 17.0%) (Chi-squared test p-value=3 × 10−18). We compared the most commonly deleted regions (CDR) on each chromosome across studies. In the ECOG CLL patients, four chromosomes each had 10 or more overlapping deletions in their top CDR (6, 11, 13 and 17), which span the FISH probes (except for chromosome 6). The GENEVA subjects also had CDR on chromosomes 11, 13 and 17, which overlap those in ECOG. In addition, GENEVA had CDR spanning genes or regions implicated in myeloid malignancies, including DNMT3a on 2p, TET2 on 4q, PRAME on 22q, and a region on 20q13. Conclusions: These genotyping results of >50,000 subjects suggest clonal chromosomal anomalies may represent precursor states, or perhaps undiagnosed or unrecorded cases, of a variety of hematological malignancies. Further studies to validate these findings and explore the natural history of these genetic defects in individuals without hematologic malignancy are warranted. Disclosures: Shanafelt: Genentech: Research Funding; Glaxo-Smith-Kline: Research Funding; Cephalon: Research Funding; Hospira: Research Funding; Celgene: Research Funding; Polyphenon E International: Research Funding.

Background and Purpose— Meta-analyses of extant genome-wide data illustrate the need to focus on subtypes of ischemic stroke for gene discovery. The National Institute of Neurological Disorders and Stroke SiGN (Stroke Genetics Network) contributes substantially to meta-analyses that focus on specific subtypes of stroke. Methods— The National Institute of Neurological Disorders and Stroke SiGN includes ischemic stroke cases from 24 genetic research centers: 13 from the United States and 11 from Europe. Investigators harmonize ischemic stroke phenotyping using the Web-based causative classification of stroke system, with data entered by trained and certified adjudicators at participating genetic research centers. Through the Center for Inherited Diseases Research, the Network plans to genotype 10 296 carefully phenotyped stroke cases using genome-wide single nucleotide polymorphism arrays and adds to these another 4253 previously genotyped cases, for a total of 14 549 cases. To maximize power for subtype analyses, the study allocates genotyping resources almost exclusively to cases. Publicly available studies provide most of the control genotypes. Center for Inherited Diseases Research–generated genotypes and corresponding phenotypes will be shared with the scientific community through the US National Center for Biotechnology Information database of Genotypes and Phenotypes, and brain MRI studies will be centrally archived. Conclusions— The Stroke Genetics Network, with its emphasis on careful and standardized phenotyping of ischemic stroke and stroke subtypes, provides an unprecedented opportunity to uncover genetic determinants of ischemic stroke.

Abstract Ischemic stroke (IS) is among the leading causes of death in Western countries. There is a significant genetic component to IS susceptibility, especially among young adults. To date, research to identify genetic loci predisposing to stroke has met only with limited success. We performed a genome-wide association (GWA) analysis of early-onset IS to identify potential stroke susceptibility loci. The GWA analysis was conducted by genotyping 1 million SNPs in a biracial population of 889 IS cases and 927 controls, ages 15–49 years. Genotypes were imputed using the HapMap3 reference panel to provide 1.4 million SNPs for analysis. Logistic regression models adjusting for age, recruitment stages, and population structure were used to determine the association of IS with individual SNPs. Although no single SNP reached genome-wide significance (P &lt; 5 × 10−8), we identified two SNPs in chromosome 2q23.3, rs2304556 (in FMNL2; P = 1.2 × 10−7) and rs1986743 (in ARL6IP6; P = 2.7 × 10−7), strongly associated with early-onset stroke. These data suggest that a novel locus on human chromosome 2q23.3 may be associated with IS susceptibility among young adults.