TOPMed

TOPMed
Name	TOPMed
Established	2014
Funder	National Heart, Lung, and Blood Institute
Location	Bethesda, Maryland

TOPMed

The Trans-Omics for Precision Medicine program is a large-scale biomedical research initiative coordinating whole-genome sequencing and multi-omics across diverse population cohorts to study heart disease, lung disease, and blood disorders. It brings together investigators from institutions such as the Broad Institute, the University of Washington, the Harvard T.H. Chan School of Public Health, the University of Michigan, and the Vanderbilt University Medical Center to integrate genomic data with clinical and epidemiological resources like the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis.

Background

TOPMed was launched by the National Heart, Lung, and Blood Institute to advance precision medicine approaches related to cardiovascular disease, chronic obstructive pulmonary disease, and hematologic conditions. The program builds on legacy cohorts including the Atherosclerosis Risk in Communities study, the Cardiovascular Health Study, and the Women's Health Initiative, while collaborating with consortia such as the Genetic Epidemiology Network of Arteriopathy and networks funded under the All of Us Research Program. Leadership and coordination involve partnerships with infrastructure organizations like the National Center for Biotechnology Information, the Database of Genotypes and Phenotypes, and sequencing centers including the Broad Institute Genomics Platform and the Baylor College of Medicine Human Genome Sequencing Center.

Objectives and Scope

TOPMed's objectives include generating high-coverage whole-genome sequencing to enable discovery of genetic variants associated with myocardial infarction, stroke, asthma, sickle cell disease, and related traits; developing tools for imputation and variant annotation; and integrating multi-omics layers such as transcriptomics, proteomics, and metabolomics. The program aims to enhance representation of populations historically studied in cohorts like the Hispanic Community Health Study/Study of Latinos, the Singapore Chinese Health Study, and the Multi-Ethnic Study of Atherosclerosis to improve the utility of polygenic risk scores and clinical translation alongside efforts from initiatives like ClinGen and the Global Alliance for Genomics and Health.

Study Design and Cohorts

TOPMed integrates data from dozens of cohort studies and clinical trials, including the Framingham Heart Study, the Jackson Heart Study, the Multi-Ethnic Study of Atherosclerosis, the Cardiovascular Health Study, the Atherosclerosis Risk in Communities study, the Women's Health Initiative, the Hispanic Community Health Study/Study of Latinos, and disease-focused repositories such as the Sickle Cell Disease Implementation Consortium. Participating sites include Johns Hopkins University, Massachusetts General Hospital, Mayo Clinic, Cleveland Clinic, University of California, San Francisco, Duke University School of Medicine, Stanford University School of Medicine, and international collaborators like the University of Cambridge and the Karolinska Institutet. Study designs range from prospective cohort follow-up, case-control nested designs, to family-based studies derived from references such as the Old Order Amish population research and longitudinal registries like the Atherosclerosis Risk in Communities study.

Data Types and Technologies

TOPMed generates high-coverage whole-genome sequencing alongside RNA sequencing, DNA methylation arrays, proteomics using mass spectrometry, and metabolomics platforms. Sequencing is performed at centers such as the Broad Institute, Baylor College of Medicine, and the Washington University Genome Institute using platforms from Illumina, and analytical pipelines incorporate tools like GATK, PLINK, and SAMtools. Variant annotation and functional interpretation leverage resources including ENCODE, the GTEx project, dbSNP, and the 1000 Genomes Project, while imputation reference panels are augmented alongside projects such as the Haplotype Reference Consortium and methods referenced by Beagle (software).

Data Access and Governance

Data access and governance for TOPMed datasets are managed through controlled-access repositories including the Database of Genotypes and Phenotypes under policies aligned with the NIH Genomic Data Sharing Policy and governance frameworks similar to the Global Alliance for Genomics and Health. Data use committees incorporate representatives from participating cohorts like the Framingham Heart Study and community advisory boards reflecting stakeholders from the Jackson Heart Study and the Hispanic Community Health Study/Study of Latinos. Consent models engage approaches discussed in forums such as the Presidential Commission for the Study of Bioethical Issues and harmonize with standards from organizations like ClinicalTrials.gov and the Office for Human Research Protections.

Major Findings and Publications

TOPMed-enabled research has contributed to discovery of rare and low-frequency variants influencing lipid traits, blood pressure, arrhythmia susceptibility, and pulmonary function, with publications in journals such as Nature, Science, The New England Journal of Medicine, Cell, and Nature Genetics. Notable collaborative outputs have refined imputation panels, improved polygenic risk prediction across diverse ancestries, and identified novel loci linked to atrial fibrillation, heart failure, chronic obstructive pulmonary disease, and sickle cell disease-related phenotypes. Consortia analyses have intersected TOPMed data with resources like UK Biobank, the BioBank Japan Project, and the FinnGen study to replicate findings and to advance translational work referenced by initiatives such as ClinVar and PharmGKB.

Ethical, Legal, and Social Implications

TOPMed raises ethical, legal, and social questions concerning data privacy, return of results, ancestry representation, and equitable benefit sharing, engaging stakeholders across institutions including the National Academies of Sciences, Engineering, and Medicine and advisory bodies such as the Presidential Commission for the Study of Bioethical Issues. Debates involve frameworks like the Common Rule, discussions of secondary use governed by the NIH Genomic Data Sharing Policy, and community-engagement models drawing on lessons from the Havasupai Tribe case and community advisory boards in the Jackson Heart Study. Efforts address health disparities highlighted by analyses comparing outcomes in cohorts such as the Framingham Heart Study and the Jackson Heart Study and coordinate with policy forums in Congress of the United States and regulatory agencies like the Food and Drug Administration.

Category:Genomics research programs