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.

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.

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%.

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Substantial evidence suggests that there is genetic susceptibility to chronic obstructive pulmonary disease (COPD). To identify common genetic risk variants, we performed a genome-wide association study in 2940 cases and 1380 smoking controls with normal lung function. We demonstrate a novel susceptibility locus at 4q22.1 in FAM13A (rs7671167, OR=0.76, P=8.6×10−8) and provide evidence of replication in one case-control and two family-based cohorts (for all studies, combined P=1.2×10−11).

Background The genetic risk factors for susceptibility to chronic obstructive pulmonary disease (COPD) are still largely unknown. Additional genetic variants are likely to be identified by genome-wide association studies in larger cohorts or specific subgroups. Methods Genome-wide association analysis in COPDGene (non-Hispanic whites and African-Americans) was combined with existing data from the ECLIPSE, NETT/NAS, and GenKOLS (Norway) studies. Analyses were performed both using all moderate-to-severe cases and the subset of severe cases. Top loci not previously described as genome-wide significant were genotyped in the ICGN study, and results combined in a joint meta-analysis. Findings Analysis of a total of 6,633 moderate-to-severe cases and 5,704 controls confirmed association at three known loci: CHRNA3/CHRNA5/IREB2, FAM13A, and HHIP (10−12 < P < 10−14), and also showed significant evidence of association at a novel locus near RIN3 (overall P, including ICGN = 5•4×10−9). In the severe COPD analysis (n=3,497), the effects at two of three previously described loci were significantly stronger; we also identified two additional loci previously reported to affect gene expression of MMP12 and TGFB2 (overall P = 2•6x10−9 and 8•3×10−9). RIN3 and TGFB2 expression levels were reduced in a set of Lung Tissue Research Consortium COPD lung tissue samples compared with controls. Interpretation In a genome-wide study of COPD, we confirmed associations at three known loci and found additional genome-wide significant associations with moderate-to-severe COPD near RIN3 and with severe COPD near MMP12 and TGFB2. Genetic variants, apart from alpha-1 antitrypsin deficiency, increase the risk of COPD. Our analysis of severe COPD suggests additional genetic variants may be identified by focusing on this subgroup. Funding National Heart, Lung, and Blood Institute; the COPD Foundation through contributions from AstraZeneca, Boehringer Ingelheim, Novartis, and Sepracor; GlaxoSmithKline; Centers for Medicare and Medicaid Services; Agency for Healthcare Research and Quality; US Department of Veterans Affairs.

Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide(1). We performed a genetic association study in 15,256 cases and 47,936 controls, with replication of select top results (P < 5 x 10(-6)) in 9,498 cases and 9,748 controls. In the combined meta-analysis, we identified 22 loci associated at genome-wide significance, including 13 new associations with COPD. Nine of these 13 loci have been associated with lung function in general population samples(2-7), while 4 (EEFSEC, DSP, MTCL1, and SFTPD) are new. We noted two loci shared with pulmonary fibrosis(8,9) (FAM13A and DSP) but that had opposite risk alleles for COPD. None of our loci overlapped with genome-wide associations for asthma, although one locus has been implicated in joint susceptibility to asthma and obesity(10). We also identified genetic correlation between COPD and asthma. Our findings highlight new loci associated with COPD, demonstrate the importance of specific loci associated with lung function to COPD, and identify potential regions of genetic overlap between COPD and other respiratory diseases

Chronic obstructive pulmonary disease (COPD) is the leading cause of respiratory mortality worldwide. Genetic risk loci provide novel insights into disease pathogenesis. We performed a genome-wide association study in 35,735 cases and 222,076 controls from the UK Biobank and additional studies from the International COPD Genetics Consortium. We identified 82 loci with P -value < 5 × 10 −8 ; 47 were previously described in association with either COPD or population-based lung function. Of the remaining 35 novel loci, 13 were associated with lung function in 79,055 individuals from the SpiroMeta consortium. Using gene expression and regulation data, we identified enrichment for loci in lung tissue, smooth muscle and several lung cell types. We found 14 COPD loci shared with either asthma or pulmonary fibrosis. COPD genetic risk loci clustered into groups of quantitative imaging features and comorbidity associations. Our analyses provide further support to the genetic susceptibility and heterogeneity of COPD.