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.
Abstract MP020: Long-term, Visit-to-visit Blood Pressure Variability and the Risk of Total Mortality, MI, and Stroke in the Cardiovascular Health Study
Introduction: Recent reports have linked visit-to-visit blood pressure (BP) variability to risk of mortality and stroke, independent of the effect of mean BP level. We sought to confirm these findings in the Cardiovascular Health Study (CHS), a cohort study of cardiovascular risk factors. Hypothesis: Variability in visit-to-visit SBP, defined as intraindividual SBP SD, is directly associated with risk of mortality, myocardial infarction (MI), and stroke, independent of intraindividual SBP mean and trend over time. Methods: Participants from CHS were eligible if they attended their first five annual clinic visits and did not have stroke, MI, or death by the 5th visit (N=3513). Follow-up started at the 5th visit and extended through June 2008. Analyses were further restricted to subjects who used no antihypertensive medications during the entire 5-year baseline period (non-users, n=1570) and subjects who used the same antihypertensive regimen during that time (users, n=978). Intraindividual SBP variables were defined using each subject’s 5-visit BPs. Cox proportional hazards models estimated adjusted hazard ratios (HR) per standard deviation (SD) increase in intraindividual SD (iSD) SBP or intraindividual mean (iMean) SBP. Results were stratified on medication use or non-use. Results: Participants’ mean age was 71 years, 42% were men, and 95% were white. Mean(SD) of iSD SBP was 9.8(4.6) mmHg for anti-hypertensive medications non-users and 12.0(6.0) mmHg for users. iMean SBP was significantly associated with all 3 outcomes among non-users and with stroke among users (table). iSD SBP was significantly associated with mortality in all participants and with MI among non-users; associations for stroke were not significant. Conclusion: Long-term visit-to-visit SBP variability may be an important determinant of MI and mortality risk in the elderly. Results for stroke are not consistent with other, previous reports. More research is needed to determine the clinical implications.
Abstract P212: Combined Analysis of Longitudinal Cohorts With Case-only Sample Sets for Detecting Genetic Effects on Venous Thromboembolism in Topmed
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.
Exome Chip Analysis Identifies Low-Frequency and Rare Variants in
MRPL38
for White Matter Hyperintensities on Brain Magnetic Resonance Imaging
Background and Purpose— White matter hyperintensities (WMH) on brain magnetic resonance imaging are typical signs of cerebral small vessel disease and may indicate various preclinical, age-related neurological disorders, such as stroke. Though WMH are highly heritable, known common variants explain a small proportion of the WMH variance. The contribution of low-frequency/rare coding variants to WMH burden has not been explored. Methods— In the discovery sample we recruited 20 719 stroke/dementia-free adults from 13 population-based cohort studies within the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, among which 17 790 were of European ancestry and 2929 of African ancestry. We genotyped these participants at ≈250 000 mostly exonic variants with Illumina HumanExome BeadChip arrays. We performed ethnicity-specific linear regression on rank-normalized WMH in each study separately, which were then combined in meta-analyses to test for association with single variants and genes aggregating the effects of putatively functional low-frequency/rare variants. We then sought replication of the top findings in 1192 adults (European ancestry) with whole exome/genome sequencing data from 2 independent studies. Results— At 17q25, we confirmed the association of multiple common variants in TRIM65 , FBF1 , and ACOX1 ( P <6×10 −7 ). We also identified a novel association with 2 low-frequency nonsynonymous variants in MRPL38 (lead, rs34136221; P EA =4.5×10 −8 ) partially independent of known common signal ( P EA(conditional) =1.4×10 −3 ). We further identified a locus at 2q33 containing common variants in NBEAL1 , CARF , and WDR12 (lead, rs2351524; P all =1.9×10 −10 ). Although our novel findings were not replicated because of limited power and possible differences in study design, meta-analysis of the discovery and replication samples yielded stronger association for the 2 low-frequency MRPL38 variants ( P rs34136221 =2.8×10 −8 ). Conclusions— Both common and low-frequency/rare functional variants influence WMH. Larger replication and experimental follow-up are essential to confirm our findings and uncover the biological causal mechanisms of age-related WMH.
Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases
A Genome‐Wide Association Study for Venous Thromboembolism: The Extended Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium
ABSTRACTVenous thromboembolism (VTE) is a common, heritable disease resulting in high rates of hospitalization and mortality. Yet few associations between VTE and genetic variants, all in the coagulation pathway, have been established. To identify additional genetic determinants of VTE, we conducted a two‐stage genome‐wide association study (GWAS) among individuals of European ancestry in the extended cohorts for heart and aging research in genomic epidemiology (CHARGE) VTE consortium. The discovery GWAS comprised 1,618 incident VTE cases out of 44,499 participants from six community‐based studies. Genotypes for genome‐wide single‐nucleotide polymorphisms (SNPs) were imputed to approximately 2.5 million SNPs in HapMap and association with VTE assessed using study‐design appropriate regression methods. Meta‐analysis of these results identified two known loci, in F5 and ABO. Top 1,047 tag SNPs (P ≤ 0.0016) from the discovery GWAS were tested for association in an additional 3,231 cases and 3,536 controls from three case‐control studies. In the combined data from these two stages, additional genome‐wide significant associations were observed on 4q35 at F11 (top SNP rs4253399, intronic to F11) and on 4q28 at FGG (rs6536024, 9.7 kb from FGG; P < 5.0 × 10−13 for both). The associations at the FGG locus were not completely explained by previously reported variants. Loci at or near SUSD1 and OTUD7A showed borderline yet novel associations (P < 5.0 × 10−6) and constitute new candidate genes. In conclusion, this large GWAS replicated key genetic associations in F5 and ABO, and confirmed the importance of F11 and FGG loci for VTE. Future studies are warranted to better characterize the associations with F11 and FGG and to replicate the new candidate associations.