Both short and long sleep duration have been associated with poor glycemic control and an increased risk of developing type 2 diabetes mellitus. Although sleep duration may differentially modify the effects of genetic risk factors for type 2 diabetes, this has not been systematically investigated. In the present study, we conducted genome-wide gene by sleep duration meta-analyses, separately assessing interactions of short and long sleep, for fasting glucose, fasting insulin, and hemoglobin A1c in up to 489,309 individuals without diabetes from seven different population groups. In total, 16 loci were identified to interact with sleep duration - six with short sleep and ten with long sleep. Of these, four loci were identified through cross-population meta-analysis. Mapped genes exhibit pathway connections to pericyte apoptosis, NMDA receptor activity, the GLUT1 receptor, neurological health, and sleep architecture. Eleven loci (VRK2, PCDH7, TFAP2A, CAP2, PAPPA, ZCCHC2, MYH9, SGIP1, JAKMIP3, RRAS2, MAPT) have not been reported in previous glycemic trait genome-wide association studies. Interaction loci identify divergent biological mechanisms for short and long sleep duration influencing glycemic control, suggesting specific pathways of intervention for precision medicine approaches to diabetes prevention and management.

Gene-environment interactions may enhance our understanding of blood pressure (BP) biology. We conducted a meta-analysis of multi-population genome-wide association studies (GWASs) of BP traits accounting for gene-depressive symptomatology (DEPR) interactions. Our study included 564,680 adults from 67 cohorts and four population backgrounds: African (5%), Asian (7%), European (85%), and Hispanic (3%). We discovered seven previously unreported BP loci showing gene-DEPR interaction. These loci mapped to genes implicated in neurogenesis (TGFA and CASP3), lipid metabolism (ACSL1), neuronal apoptosis (CASP3), and synaptic activity (CNTN6 and DBI). We also showed evidence for gene-DEPR interaction at nine known BP loci, further suggesting links between mood disturbance and BP regulation. Of the 16 identified loci, 11 were derived from non-European populations. Post-GWAS analyses prioritized 36 genes, including genes involved in synaptic functions (DOCK4 and MAGI2) and neuronal signaling (CCK, UGDH, and SLC01A2). Integrative druggability analyses identified 11 druggable candidate gene targets linked to pathways involved in mood disorders as well as known anti-hypertensive drugs. Our findings emphasize the importance of considering gene-DEPR interactions on BP, particularly in non-European populations. Our prioritized genes and druggable targets highlight biological pathways connecting mood disorders and hypertension and suggest opportunities for BP drug repurposing and risk factor prevention, especially in individuals with DEPR.

BACKGROUND AND AIMS:Deviations from the population mean in sleep duration have been associated with increased risk for developing dyslipidemia and atherosclerotic cardiovascular disease, but the mechanism of effect is poorly characterized. We performed large-scale genome-wide gene-sleep interaction analyses of lipid levels to identify genetic variants underpinning the biomolecular pathways of sleep-associated lipid disturbances and to suggest possible druggable targets. METHODS:We collected data from 55 cohorts with a combined sample size of 732,564 participants (87 % European ancestry) with data on lipid traits (high-density lipoprotein [HDL-c] and low-density lipoprotein [LDL-c] cholesterol and triglycerides [TG]). Short (STST) and long (LTST) total sleep time were defined by the extreme 20 % of the age- and sex-standardized values within each cohort. Based on cohort-level summary statistics data, we performed meta-analyses for one-degree of freedom tests of interaction and two-degree of freedom joint tests of the SNP-main and -interaction effect on lipid levels. RESULTS:The one-degree of freedom variant-sleep interaction test identified 10 novel loci (Pint<5.0e-9), and we additionally identify 7 loci within the two-degree of freedom analyses (Pjoint<5.0e-9 in combination with Pint<6.6e-6). Multiple loci, including those mapped to APSH (target for aspartic and succinic acid) and SLC8A1 showed biological plausibility and druggability potential based on literature. CONCLUSIONS:Collectively, the 17 (9 with short and 8 with long sleep) loci provided evidence into the biomolecular mechanisms underlying sleep-associated lipid changes, including potential involvement of the vitamin D receptor pathway. Collectively, these findings may contribute developing novel interventions for treating dyslipidemia in people with sleep disturbances.

Cigarette smoking influences blood pressure (BP) levels. Studying and accounting for potential gene-smoking interactions can help discover novel loci and provide insights into biological pathways for smoking-associated BP regulation. We conducted a genome-wide association meta-analysis involving 1,188,241 individuals from 66 studies in five ancestry groups, analyzing systolic BP, diastolic BP, and pulse pressure while considering interactions between genetic variants and three smoking exposures: smoking status, cigarettes per day, and pack years. These analyses identified twelve novel loci for BP at genome-wide significance ( P < 5 × 10 - 9 ), and highlighted biological processes including tight junction integrity, mitochondrial health, vascular relaxation, and endothelial function. In smoking status-stratified analyses, smoking modifies the genetic effect of six variants on BP. To prioritize likely causal, we developed and applied SuSiEgxe, a fine-mapping method based on a two-degree-of-freedom joint test using gene-environment interaction summary statistics. Fine-mapped loci uncovered immune-related pathway for smoking-associated BP regulation.

Background:Gene-environment interactions may enhance our understanding of hypertension. Our previous study highlighted the importance of considering psychosocial factors in gene discovery for blood pressure (BP) but was limited in statistical power and population diversity. To address these challenges, we conducted a multi-population genome-wide association study (GWAS) of BP accounting for gene-depressive symptomatology (DEPR) interactions in a larger and more diverse sample. Results:Our study included 564,680 adults aged 18 years or older from 67 cohorts and 4 population backgrounds (African (5%), Asian (7%), European (85%), and Hispanic (3%)). We discovered seven novel gene-DEPR interaction loci for BP traits. These loci mapped to genes implicated in neurogenesis (TGFA, CASP3), lipid metabolism (ACSL1), neuronal apoptosis (CASP3), and synaptic activity (CNTN6, DBI). We also identified evidence for gene-DEPR interaction at nine known BP loci, further suggesting links between mood disturbance and BP regulation. Of the 16 identified loci, 11 loci were derived from African, Asian, or Hispanic populations. Post-GWAS analyses prioritized 36 genes, including genes involved in synaptic functions (DOCK4, MAGI2) and neuronal signaling (CCK, UGDH, SLC01A2). Integrative druggability analyses identified 11 druggable candidate gene targets, including genes implicated in pathways linked to mood disorders as well as gene products targeted by known antihypertensive drugs. Conclusions:Our findings emphasize the importance of considering gene-DEPR interactions on BP, particularly in non-European populations. Our prioritized genes and druggable targets highlight biological pathways connecting mood disorders and hypertension and suggest opportunities for BP drug repurposing and risk factor prevention, especially in individuals with DEPR.

We performed large-scale genome-wide gene-sleep interaction analyses of lipid levels to identify novel genetic variants underpinning the biomolecular pathways of sleep-associated lipid disturbances and to suggest possible druggable targets. We collected data from 55 cohorts with a combined sample size of 732,564 participants (87% European ancestry) with data on lipid traits (high-density lipoprotein [HDL-c] and low-density lipoprotein [LDL-c] cholesterol and triglycerides [TG]). Short (STST) and long (LTST) total sleep time were defined by the extreme 20% of the age- and sex-standardized values within each cohort. Based on cohort-level summary statistics data, we performed meta-analyses for the one-degree of freedom tests of interaction and two-degree of freedom joint tests of the main and interaction effect. In the cross-population meta-analyses, the one-degree of freedom variant-sleep interaction test identified 10 loci (Pint<5.0e-9) not previously observed for lipids. Of interest, the ASPH locus (TG, LTST) is a target for aspartic and succinic acid metabolism previously shown to improve sleep and cardiovascular risk. The two-degree of freedom analyses identified an additional 7 loci that showed evidence for variant-sleep interaction (Pjoint<5.0e-9 in combination with Pint<6.6e-6). Of these, the SLC8A1 locus (TG, STST) has been considered a potential treatment target for reduction of ischemic damage after acute myocardial infarction. Collectively, the 17 (9 with STST; 8 with LTST) loci identified in this large-scale initiative provides evidence into the biomolecular mechanisms underpinning sleep-duration-associated changes in lipid levels. The identified druggable targets may contribute to the development of novel therapies for dyslipidemia in people with sleep disturbances.

Spurred by the 2016 release of the National Heart, Lung, and Blood Institute's Strategic Vision, the Division of Cardiovascular Sciences developed its Strategic Vision Implementation Plan-a blueprint for reigniting the decline in cardiovascular disease (CVD) mortality rates, improving health equity, and accelerating translation of scientific discoveries into better cardiovascular health (CVH). The 6 scientific focus areas of the Strategic Vision Implementation Plan reflect the multifactorial nature of CVD and include (1) addressing social determinants of CVH and health inequities, (2) enhancing resilience, (3) promoting CVH and preventing CVD across the lifespan, (4) eliminating hypertension-related CVD, (5) reducing the burden of heart failure, and (6) preventing vascular dementia. This article presents an update of strategic vision implementation activities within Division of Cardiovascular Sciences. Overarching and cross-cutting themes include training the scientific workforce and engaging the extramural scientific community to stimulate transformative research in cardiovascular sciences. In partnership with other NIH Institutes, Federal agencies, industry, and the extramural research community, Division of Cardiovascular Sciences strategic vision implementation has stimulated development of numerous workshops and research funding opportunities. Strategic Vision Implementation Plan activities highlight innovative intervention modalities, interdisciplinary systems approaches to CVD reduction, a life course framework for CVH promotion and CVD prevention, and multi-pronged research strategies for combatting COVID-19. As new knowledge, technologies, and areas of scientific research emerge, Division of Cardiovascular Sciences will continue its thoughtful approach to strategic vision implementation, remaining poised to seize emerging opportunities and catalyze breakthroughs in cardiovascular sciences.

Exposure of biological systems to acute or chronic insults triggers a host of molecular and physiological responses to either tolerate, adapt, or fully restore homeostasis; these responses constitute the hallmarks of resilience. Given the many facets, dimensions, and discipline-specific focus, gaining a shared understanding of "resilience" has been identified as a priority for supporting advances in cardiovascular health. This report is based on the working definition: "Resilience is the ability of living systems to successfully maintain or return to homeostasis in response to physical, molecular, individual, social, societal, or environmental stressors or challenges," developed after considering many factors contributing to cardiovascular resilience through deliberations of multidisciplinary experts convened by the National Heart, Lung, and Blood Institute during a workshop entitled: "Enhancing Resilience for Cardiovascular Health and Wellness." Some of the main emerging themes that support the possibility of enhancing resilience for cardiovascular health include optimal energy management and substrate diversity, a robust immune system that safeguards tissue homeostasis, and social and community support. The report also highlights existing research challenges, along with immediate and long-term opportunities for resilience research. Certain immediate opportunities identified are based on leveraging existing high-dimensional data from longitudinal clinical studies to identify vascular resilience measures, create a 'resilience index,' and adopt a life-course approach. Long-term opportunities include developing quantitative cell/organ/system/community models to identify resilience factors and mechanisms at these various levels, designing experimental and clinical interventions that specifically assess resilience, adopting global sharing of resilience-related data, and cross-domain training of next-generation researchers in this field.

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data sharing mechanisms. This system was developed for the National Heart, Lung and Blood Institute’s Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other omics data for >80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants from up to 17 TOPMed studies per phenotype. We discuss the challenges faced in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled-access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include (1) the code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify or extend these harmonizations to additional studies; and (2) results of labeling thousands of phenotype variables with controlled vocabulary terms.

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%.

Human induced pluripotent stem cell (hiPSC) lines have previously been generated through the NHLBI sponsored NextGen program at nine individual study sites. Here, we examined the structural integrity of 506 hiPSC lines as determined by copy number variations (CNVs). We observed that 149 hiPSC lines acquired 258 CNVs relative to donor DNA. We identified six recurrent regions of CNVs on chromosomes 1, 2, 3, 16 and 20 that overlapped with cancer associated genes. Furthermore, the genes mapping to regions of acquired CNVs show an enrichment in cancer related biological processes (IL6 production) and signaling cascades (JNK cascade & NFκB cascade). The genomic region of instability on chr20 (chr20q11.2) includes transcriptomic signatures for cancer associated genes such as ID1, BCL2L1, TPX2, PDRG1 and HCK. Of these HCK shows statistically significant differential expression between carrier and non-carrier hiPSC lines. Overall, while a low level of genomic instability was observed in the NextGen generated hiPSC lines, the observation of structural instability in regions with known cancer associated genes substantiates the importance of systematic evaluation of genetic variations in hiPSCs before using them as disease/research models.

Cardiovascular diseases remain the leading cause of mortality and a major contributor to preventable deaths worldwide. The dominant modifiable risk factors and the social and environmental determinants that increase cardiovascular risk are known, and collectively, are as important in racial and ethnic minority populations as they are in majority populations. Their prevention and treatment remain the foundation for cardiovascular health promotion and disease prevention. Genetic and epigenetic factors are increasingly recognized as important contributors to cardiovascular risk and provide an opportunity for advancing precision cardiovascular medicine. In this review, we explore emerging concepts at the interface of precision medicine and cardiovascular disease in racial and ethnic minority populations. Important among these are the lack of racial and ethnic diversity in genomics studies and biorepositories; the resulting misclassification of benign variants as pathogenic in minorities; and the importance of ensuring ancestry-matched controls in variant interpretation. We address the relevance of epigenetics, pharmacogenomics, genetic testing and counseling, and their social and cultural implications. We also examine the potential impact of precision medicine on racial and ethnic disparities. The National Institutes of Health's All of Us Research Program and the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine Initiative are presented as examples of research programs at the forefront of precision medicine and diversity to explore research implications in minorities. We conclude with an overview of implementation research challenges in precision medicine and the ethical implications in minority populations. Successful implementation of precision medicine in cardiovascular disease in minority populations will benefit from strategies that directly address diversity and inclusion in genomics research and go beyond race and ethnicity to explore ancestry-matched controls, as well as geographic, cultural, social, and environmental determinants of health.

We present summaries of the scientific discussions at the workshop that was convened on June 6-7, 2018, by the NHLBI.120National Heart, Lung, and Blood Institute. Promoting Cardiovascular Health in Early Childhood (0-5 years) and Transitions in Childhood through Adolescence—Executive Summary. 2018. https://www.nhlbi.nih.gov/events/2018/promoting-cardiovascular-health-early-childhood-0-5-years-and-transitions-childhood. Accessed October 2, 2018.Google Scholar The workshop addresses the state of the science and research needs for promoting CVH using an integrated and synergistic approach and focusing on basic and population science research and clinical trials. Training to develop the next generation of researchers is also an integral component.

Adult class II/III obesity (BMI ≥ 35 kg/m2) has significant adverse health outcomes. Early prevention and treatment are critical, but prospective childhood risk estimates are lacking. This study aimed to define the prospective risk of adult class II/III obesity, using childhood BMI. Children ages 3–19 years enrolled in cohorts of the International Childhood Cardiovascular Cohort (i3C) consortium with measured BMI assessments in childhood and adulthood were included. Prospective risk of adult class II/III obesity was modeled based on childhood age, sex, race, and BMI. A total of 12,142 individuals (44% male, 85% white) were assessed at median age 14 [Interquartile range, IQR: 11, 16] and 33 [28, 39] years. Class II/III adult obesity developed in 6% of children with normal weight; 29% of children with overweight; 56% of children with obesity; and 80% of children with severe obesity. However, 38% of the 1440 adults with class II/III obesity (553/1440) were normal weight as children. Prospective risk of adult class II/III obesity varied by age, sex, and race within childhood weight status classifications, and is notably higher for girls, black participants, and those in the United States. The risk of class II/III obesity increased with older adult age. Children with obesity or severe obesity have a substantial risk of adult class II/III obesity, and observed prospective risk estimates are now presented by age, sex, race, and childhood BMI. Clinical monitoring of children’s BMI for adult class II/III obesity risk may be especially important for females and black Americans.

As we commemorate the 70th anniversary of the National Heart, Lung, and Blood Institute and celebrate important milestones that have been achieved by the division of cardiovascular sciences, it is imperative that division of cardiovascular sciences and the Extramural Research community at-large continue to address critical public health challenges that persist within the area of cardiovascular diseases. The National Heart, Lung, and Blood Institute Strategic Vision, developed with extensive input from the extramural research community and published in 2016, included overarching goals and strategic objectives that serve to provide a general blueprint for sustaining the legacy of the institute by leveraging opportunities in emerging scientific areas (eg, regenerative medicine, omics technology, data science, precision medicine, and mobile health), finding new ways to address enduring challenges (eg, social determinants of health, health inequities, prevention, and health promotion), and training the next generation of heart, lung, blood, and sleep researchers. Division of cardiovascular sciences has developed a strategic vision implementation plan to provide a cardiovascular framing for the pursuit of the institutes overarching goals and strategic objectives garnered from the input of the broader National Heart, Lung, and Blood Institute community. This plan highlights 6 scientific focus areas that demonstrate a cross-cutting and multifaceted approach to addressing cardiovascular sciences, including (1) addressing social determinants of cardiovascular health and health inequities, (2) enhancing resilience, (3) promoting cardiovascular health and preventing cardiovascular diseases across the lifespan, (4) eliminating hypertension-related cardiovascular diseases, (5) reducing the burden of heart failure, and (6) preventing vascular dementia. These priorities will guide our efforts in institute-driven activities in the coming years but will not exclude development of other novel ideas or the support of investigator-initiated grant awards. The Division of Cardiovascular Sciences strategic vision implementation plan is a living document that will evolve with iterative dialogue with the National Heart, Lung, and Blood Institute community and adapt as the dynamic scientific landscape changes to seize emerging opportunities.

BACKGROUND:Elevated levels of low-density lipoprotein cholesterol (LDL-C) are a major risk factor for cardiovascular disease via its contribution to the development and progression of atherosclerotic lesions. Although the genetic basis of LDL-C has been studied extensively, currently known genetic variants account for only ≈20% of the variation in LDL-C levels.METHODS:Through an array-based association analysis in 1102 Amish subjects, we identified a variant strongly associated with LDL-C levels. Using a combination of genetic analyses, zebrafish models, and in vitro experiments, we sought to identify the causal gene driving this association.RESULTS:We identified a founder haplotype associated with a 15 mg/dL increase in LDL-C on chromosome 5. After recombination mapping, the associated region contained 8 candidate genes. Using a zebrafish model to evaluate the relevance of these genes to cholesterol metabolism, we found that expression of the transcribed pseudogene, APOOP1, increased LDL-C and vascular plaque formation.CONCLUSIONS:Based on these data, we propose that APOOP1 regulates levels of LDL-C in humans, thus identifying a novel mechanism of lipid homeostasis.

Although it is widely thought that childhood levels of cardiovascular (CV) risk factors are related to adult CV disease, longitudinal data directly linking the two are lacking. This paper describes the design and organization of the International Childhood Cardiovascular Cohort Consortium Outcomes Study (i3C Outcomes), the first longitudinal cohort study designed to locate adults with detailed, repeated, childhood biological, physical, and socioeconomic measurements and a harmonized database. I3C Outcomes uses a Heart Health Survey (HHS) to obtain information on adult CV endpoints, using mail, email, telephone, and clinic visits in the United States (U.S.) and Australia and a national health database in Finland. Microsoft Access, REsearch Data Capture (REDCap) (U.S.), LimeSurvey (Australia), and Medidata™ Rave data systems are used to collect, transfer and organize data. Self-reported CV events are adjudicated via hospital and doctor-released medical records. After the first two study years, participants (N = 10,968) were more likely to be female (56% vs. 48%), non-Hispanic white (90% vs. 80%), and older (10.4 ± 3.8 years vs. 9.4 ± 3.3 years) at their initial childhood study visit than the currently non-recruited cohort members. Over 48% of cohort members seen during both adulthood and childhood have been found and recruited, to date, vs. 5% of those not seen since childhood. Self-reported prevalences were 0.7% Type 1 Diabetes, 7.5% Type 2 Diabetes, 33% hypertension, and 12.8% CV event. 32% of CV events were judged to be true. I3C Outcomes is uniquely able to establish evidence-based guidelines for child health care and to clarify relations to adult CV disease.

Importance Atrial fibrillation (AF) is the most common arrhythmia affecting 1% of the population. Young individuals with AF have a strong genetic association with the disease, but the mechanisms remain incompletely understood. Objective To perform large-scale whole-genome sequencing to identify genetic variants related to AF. Design, Setting, and Participants The National Heart, Lung, and Blood Institute’s Trans-Omics for Precision Medicine Program includes longitudinal and cohort studies that underwent high-depth whole-genome sequencing between 2014 and 2017 in 18 526 individuals from the United States, Mexico, Puerto Rico, Costa Rica, Barbados, and Samoa. This case-control study included 2781 patients with early-onset AF from 9 studies and identified 4959 controls of European ancestry from the remaining participants. Results were replicated in the UK Biobank (346 546 participants) and the MyCode Study (42 782 participants). Exposures Loss-of-function (LOF) variants in genes at AF loci and common genetic variation across the whole genome. Main Outcomes and Measures Early-onset AF (defined as AF onset in persons <66 years of age). Due to multiple testing, the significance threshold for the rare variant analysis was P = 4.55 × 10−3. Results Among 2781 participants with early-onset AF (the case group), 72.1% were men, and the mean (SD) age of AF onset was 48.7 (10.2) years. Participants underwent whole-genome sequencing at a mean depth of 37.8 fold and mean genome coverage of 99.1%. At least 1 LOF variant in TTN, the gene encoding the sarcomeric protein titin, was present in 2.1% of case participants compared with 1.1% in control participants (odds ratio [OR], 1.76 [95% CI, 1.04-2.97]). The proportion of individuals with early-onset AF who carried a LOF variant in TTN increased with an earlier age of AF onset (P value for trend, 4.92 × 10−4), and 6.5% of individuals with AF onset prior to age 30 carried a TTN LOF variant (OR, 5.94 [95% CI, 2.64-13.35]; P = 1.65 × 10−5). The association between TTN LOF variants and AF was replicated in an independent study of 1582 patients with early-onset AF (cases) and 41 200 control participants (OR, 2.16 [95% CI, 1.19-3.92]; P = .01). Conclusions and Relevance In a case-control study, there was a statistically significant association between an LOF variant in the TTN gene and early-onset AF, with the variant present in a small percentage of participants with early-onset AF (the case group). Further research is necessary to understand whether this is a causal relationship.

The National Heart, Lung, and Blood Institute's Next Generation Genetic Association Studies Consortiumhas used induced pluripotent stem cell technology to study the effects of common genetic variants in vitro. This issue of Cell Stem Cell and affiliated journals include several manuscripts describing the results of the consortium's efforts.

The increasing volume of whole-genome sequence (WGS) and multi-omics data requires new approaches for analysis. As one solution, we have created the cloud-based Analysis Commons, which brings together genotype and phenotype data from multiple studies in a setting that is accessible by multiple investigators. This framework addresses many of the challenges of multicenter WGS analyses, including data-sharing mechanisms, phenotype harmonization, integrated multi-omics analyses, annotation and computational flexibility. In this setting, the computational pipeline facilitates a sequence-to-discovery analysis workflow illustrated here by an analysis of plasma fibrinogen levels in 3,996 individuals from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) WGS program. The Analysis Commons represents a novel model for translating WGS resources from a massive quantity of phenotypic and genomic data into knowledge of the determinants of health and disease risk in diverse human populations.