Summary paragraphThe Trans-Omics for Precision Medicine (TOPMed) program seeks to elucidate the genetic architecture and disease biology of heart, lung, blood, and sleep disorders, with the ultimate goal of improving diagnosis, treatment, and prevention. The initial phases of the program focus on whole genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here, we describe TOPMed goals and design as well as resources and early insights from the sequence data. The resources include a variant browser, a genotype imputation panel, and sharing of genomic and phenotypic data via dbGaP. In 53,581 TOPMed samples, >400 million single-nucleotide and insertion/deletion variants were detected by alignment with the reference genome. Additional novel variants are detectable through assembly of unmapped reads and customized analysis in highly variable loci. Among the >400 million variants detected, 97% have frequency <1% and 46% are singletons. These rare variants provide insights into mutational processes and recent human evolutionary history. The nearly complete catalog of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and non-coding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and extends the reach of nearly all genome-wide association studies to include variants down to ~0.01% in frequency.

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

BACKGROUND Limited information is available regarding genetic contributions to valvular calcification, which is an important precursor of clinical valve disease. METHODS We determined genomewide associations with the presence of aorticvalve calcification (among 6942 participants) and mitral annular calcification (among 3795 participants), as detected by computed tomographic (CT) scanning; the study population for this analysis included persons of white European ancestry from three cohorts participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (discovery population). Findings were replicated in independent cohorts of persons with either CT-detected valvular calcification or clinical aortic stenosis. RESULTS One SNP in the lipoprotein(a) (LPA) locus (rs10455872) reached genomewide significance for the presence of aorticvalve calcification (odds ratio per allele, 2.05; P = 9.0×10−10), a finding that was replicated in additional white European, African-American, and Hispanic-American cohorts (P<0.05 for all comparisons). Genetically determined Lp(a) levels, as predicted by LPA genotype, were also associated with aorticvalve calcification, supporting a causal role for Lp(a). In prospective analyses, LPA genotype was associated with incident aortic stenosis (hazard ratio per allele, 1.68; 95% confidence interval [CI], 1.32 to 2.15) and aortic-valve replacement (hazard ratio, 1.54; 95% CI, 1.05 to 2.27) in a large Swedish cohort; the association with incident aortic stenosis was also replicated in an independent Danish cohort. Two SNPs (rs17659543 and rs13415097) near the proinflammatory gene IL1F9 achieved genomewide significance for mitral annular calcification (P = 1.5×10−8 and P = 1.8×10−8, respectively), but the findings were not replicated consistently. CONCLUSIONS Genetic variation in the LPA locus, mediated by Lp(a) levels, is associated with aorticvalve calcification across multiple ethnic groups and with incident clinical aortic stenosis. (Funded by the National Heart, Lung, and Blood Institute and others.)

Age is the dominant risk factor for most chronic human diseases; yet the mechanisms by which aging confers this risk are largely unknown. 1 Recently, the age-related acquisition of somatic mutations in regenerating hematopoietic stem cell populations leading to clonal expansion was associated with both hematologic cancer 2 – 4 and coronary heart disease 5 , a phenomenon termed ‘Clonal Hematopoiesis of Indeterminate Potential’ (CHIP). 6 Simultaneous germline and somatic whole genome sequence analysis now provides the opportunity to identify root causes of CHIP. Here, we analyze high-coverage whole genome sequences from 97,691 participants of diverse ancestries in the NHLBI TOPMed program and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid, and inflammatory traits specific to different CHIP genes. Association of a genome-wide set of germline genetic variants identified three genetic loci associated with CHIP status, including one locus at TET2 that was African ancestry specific. In silico -informed in vitro evaluation of the TET2 germline locus identified a causal variant that disrupts a TET2 distal enhancer resulting in increased hematopoietic stem cell self-renewal. Overall, we observe that germline genetic variation shapes hematopoietic stem cell function leading to CHIP through mechanisms that are both specific to clonal hematopoiesis and shared mechanisms leading to somatic mutations across tissues.

Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate–increasing and heart rate–decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets.

IMPORTANCE Plasma low-density lipoprotein cholesterol (LDL-C) has been associated with aortic stenosis in observational studies; however, randomized trials with cholesterol-lowering therapies in individuals with established valve disease have failed to demonstrate reduced disease progression. OBJECTIVE To evaluate whether genetic data are consistent with an association between LDL-C, high-density lipoprotein cholesterol (HDL-C), or triglycerides (TG) and aortic valve disease. DESIGN, SETTING, AND PARTICIPANTS Using a Mendelian randomization study design, we evaluated whether weighted genetic risk scores (GRSs), a measure of the genetic predisposition to elevations in plasma lipids, constructed using single-nucleotide polymorphisms identified in genome-wide association studies for plasma lipids, were associated with aortic valve disease. We included community-based cohorts participating in the CHARGE consortium (n = 6942), including the Framingham Heart Study (cohort inception to last follow-up: 1971-2013; n = 1295), Multi-Ethnic Study of Atherosclerosis (2000-2012; n = 2527), Age Gene/Environment Study-Reykjavik (2000-2012; n = 3120), and the Malmö Diet and Cancer Study (MDCS, 1991-2010; n = 28 461). MAIN OUTCOMES AND MEASURES Aortic valve calcium quantified by computed tomography in CHARGE and incident aortic stenosis in the MDCS. RESULTS The prevalence of aortic valve calcium across the 3 CHARGE cohorts was 32% (n = 2245). In the MDCS, over a median follow-up time of 16.1 years, aortic stenosis developed in 17 per 1000 participants (n = 473) and aortic valve replacement for aortic stenosis occurred in 7 per 1000 (n = 205). Plasma LDL-C, but not HDL-C or TG, was significantly associated with incident aortic stenosis (hazard ratio [HR] per mmol/L, 1.28; 95% CI, 1.04-1.57; P = .02; aortic stenosis incidence: 1.3% and 2.4% in lowest and highest LDL-C quartiles, respectively). The LDL-C GRS, but not HDL-C or TG GRS, was significantly associated with presence of aortic valve calcium in CHARGE (odds ratio [OR] per GRS increment, 1.38; 95% CI, 1.09-1.74; P = .007) and with incident aortic stenosis in MDCS (HR per GRS increment, 2.78; 95% CI, 1.22-6.37; P = .02; aortic stenosis incidence: 1.9% and 2.6% in lowest and highest GRS quartiles, respectively). In sensitivity analyses excluding variants weakly associated with HDL-C or TG, the LDL-C GRS remained associated with aortic valve calcium (P = .03) and aortic stenosis (P = .009). In instrumental variable analysis, LDL-C was associated with an increase in the risk of incident aortic stenosis (HR per mmol/L, 1.51; 95% CI, 1.07-2.14; P = .02). CONCLUSIONS AND RELEVANCE Genetic predisposition to elevated LDL-C was associated with presence of aortic valve calcium and incidence of aortic stenosis, providing evidence supportive of a causal association between LDL-C and aortic valve disease. Whether earlier intervention to reduce LDL-C could prevent aortic valve disease merits further investigation.

Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans.

Summary Introduction The discovery of disease-associated loci through genome-wide association studies (GWAS) is the leading approach to the identification of novel biological pathways for human disease. To date, GWAS have had been limited by relatively small sample sizes and yielded relatively few loci associated with ischemic stroke The National Institute of Neurological Disorders Stroke Genetics Network (NINDS-SiGN) is an international consortium that has taken a systematic approach to phenotyping and produced the largest ischemic stroke GWAS to date. Methods In order to identify genetic loci associated with ischemic stroke, we performed a two-stage genome-wide association study. The first stage consisted of 16,851 cases with state-of-the-art phenotyping and 32,473 stroke-free controls. Cases were aged 16 to 104 years, recruited between 1989 and 2012, and subtyped by centrally trained and certified investigators using the web-based protocol, Causative Classification of Stroke (CCS). We constructed case-control strata by identify samples genotyped on (nearly) identical arrays and of similar genetic ancestral background. Data was cleaned and imputed using dense imputation reference panels generated from whole-genome sequence data. Genome-wide testing was performed within each stratum for each available phenotype, and summary level results were combined using inverse variance-weighted fixed effects meta-analysis. The second stage consisted of in silico look-ups of 1,372 SNPs in 20,941 cases and 364,736 stroke-free controls, with cases previously subtyped using the TOAST classification system according to local standards. The two stages were then jointly analyzed in a final meta-analysis. Findings We identified a novel locus at 1p13.2 near TSPAN2 associated with large artery atherosclerosis (LAA)-related stroke (stage I OR for the G allele at rs12122341 = 1·21, p = 4.50 × 10−8; stage II OR = 1·19, p = 1·30 × 10−9). We also confirmed four loci robustly associated with ischemic stroke and reported in prior studies, including PITX2 and ZFHX3 for cardioembolic stroke, and HDAC9 for LAA stroke. The 12q24 locus near ALDH2, originally associated with all ischemic stroke but not with any specific subtype, exceeded genome-wide significance in the meta-analysis of small artery stroke. Other loci, including NINJ2, were not confirmed. Interpretation Our results identify a novel LAA-stroke susceptibility gene and now indicate that all loci implicated by GWAS to date are subtype specific. Follow-up studies will be necessary to determine whether the locus near TSPAN2 yields a novel therapeutic approach to stroke prevention. Given the subtype-specificity of these associations, the rich phenotyping available in SiGN is likely to prove vital for further genetic discovery in ischemic stroke. Funding National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH).