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TOPMed

What is TOPMed?

Trans-Omics for Precision Medicine (TOPMed), is a program of the National Heart, Lung and Blood Institute (NHLBI), a part of the National Institutes of Health, which aims to improve scientific understanding of the fundamental biological processes that underlie heart, lung, blood, and sleep (HLBS) disorders and advance precision medicine in ways that lead to disease treatments tailored to individuals’ unique genes and environments.

TOPMed supports these scientific advances through the integration of whole-genome sequencing (WGS) and other omics data (e.g., metabolic profiles, epigenomics, protein and RNA expression patterns) with molecular, behavioral, imaging, environmental, and clinical data from pre-existing parent studies that have large samples of human subjects with rich phenotypic characterization and environmental exposure data. TOPMed also collects environmental and behavioral data, such as dietary habits, physical activity, and socioeconomic factors, to provide a more comprehensive understanding of the factors that contribute to these disorders.

Explore the Data

The TOPMed program provides data resources for researchers studying heart, lung, blood, and sleep disorders. These data resources include various types of genomic and other data, such as whole-genome sequencing, whole-exome sequencing, RNA sequencing, epigenetic data, metabolomic data, and proteomic data. Researchers who wish to access TOPMed data, including electronic health records, medical imaging data, and other patient health information, must get approval through the Database of Genotypes and Phenotypes (dbGaP). Once approval is granted, researchers can access the data from NHLBI BioData Catalyst® (BDC) or dbGaP.

BioData Catalyst (BDC)

Cloud-based computing ecosystem
Features secure workspaces, tools, applications, and workflows
Hosts data and supports collaboration

The TOPMed program uses BioData Catalyst (BDC) as a resource to facilitate research efforts. BDC is a cloud-based ecosystem where researchers can access NHLBI datasets, including TOPMed data, and leverage innovative data analysis tools, applications, and workflows to accelerate their research efforts. Additionally, BDC allows researchers to bring their own data, collaborate, and share their findings with other researchers in the community, ultimately driving discovery and scientific advancement in precision medicine.

Access BioData Catalyst

TOPMed Data Freeze 9

Variant discovery was initially made on approximately 206,000 samples.
781 million single nucleotide variants were identified.
62 million short insertion/deletion variants were identified and passed variant quality control (QC).

Note: These variant counts are slightly smaller than the corresponding numbers in data freeze 9 due to omitting sites that show no variation in TOPMed samples. More information about WGS methods can be found by selecting a freeze listed on the Methods page.

View TOPMed data freeze 9

OMICS Data Processing & Sources

TOPMed Omics data processing is being performed by several sequencing centers. The program requires that omics data be submitted to dbGaP with thorough documentation of bio-sampling, laboratory methods, and sample provenance. Visit the Methods webpage and scroll to the Standards, Pipelines and Flowcharts for Data Processing section to find available documented omics pipelines specific to omics type and phase. Below is a summary of the approved data sources for each study/cohort name categorized by data type.

TOPMed WGS and Omics Summary of Approved Projects

TOPMed WGS and Omics Summary of Approved Data
Short Name Sort descending	Study/Cohort Name	Populations	dbGaP ID	WGS	RNA-seq	Methylation	Metabolomics	Proteomics
MDS	Genomics of Myelodysplastic Syndromes	Adults aged 18 or older	phs002360	473	145
MESA	Multi-Ethnic Study of Atherosclerosis	Multi-ethnic populations	phs001416	7,107	8,903	13,286	12,800	14,200
MLOF	My Life, Our Future: Genotyping for Progress in Hemophilia	Adults and children with hemophilia A	phs001515	5,670	4,500
MWCCS	MACS/WIHS COMBINED COHORT STUDY
OMG_SCD	Outcome Modifying Genes in Sickle Cell Disease	Adults from North Carolina and Georgia	phs001608	653
PCGC_CHD	Pediatric Cardiac Genomics Consortium's Congenital Heart Disease Biobank	Children and adults	phs001735	3,888
PGX_Asthma	Pharmacogenomics of Bronchodilator Response in Minority Children with Asthma	African American, Puerto Rican, and Mexican ancestry	phs001682	423
PROMIS	Pakistan Risk of Myocardial Infarction Study	South Asian ancestry from Pakistan	phs001569	9,204
PharmHU	The Pharmacogenomics of Hydroxyurea in Sickle Cell Disease	Pediatric patients	phs001466	862	826
nuMoM2b-HHS	nuMoM2b-Heart Health Study	Hispanic (17%), non-Hispanic Black (14%), Asian (4%), other (5%), non-Hispanic White (60%)		4,341	600
				196,938	64,412	81,033	82,534	34,014

Notes:

“phs” is a dbGaP study accession number prefix indicating a phenotype study. A study accession number is a unique, stable, and versioned identifier.

AFGen dbGaP IDs: phs001435 , phs001543 , phs001624 , phs001732 , phs001600 , phs001189 , phs001546 , phs001606 , phs001547 , phs001725 , phs001545 , phs000993 , phs001598 , phs001062 , phs001434 , phs001544 , phs001024 , phs001601 , phs001933 , phs000997 , phs001032 , phs001040

ATGC dbGaP IDs: phs001728 , phs001729 , phs001730 , phs001602 , phs001603 , phs001604 , phs001605 , phs000920, phs001542 , phs001661 , phs001727 , phs000921 , phs001467

In the table, you may encounter phs links that redirect to a dbGaP error page. If so, this is because the TOPMed dbGaP study webpages are not available until the study accession is released.

TOPMed is generating a rich resource of multi-omics data that will include approximately 40,000 samples undergoing RNA-sequencing, 37,000 samples from metabolomics profiling, 57,000 samples from DNA methylation, and 4,000 samples from proteomics assaying. These projected totals include all stages of progress, from DNA/RNA that are currently being extracted to those that are undergoing sequencing/profiling or those that have completed the sequencing/profiling pipelines. Therefore, most omics data are in the process of being generated and will be released in the future.

Published Papers That Used TOPMed Data

Published papers utilize TOPMed data to address topics related to heart, lung, blood, and sleep disorders.

Title	Journal Name	Publication Date Sort ascending	PMID
Metagenomic Study of the MESA: Detection of Gemella Morbillorum and Association With Coronary Heart Disease	J Am Heart Assoc.	2024	39344648
Genetic variants associated with white blood cell count amongst individuals with sickle cell disease	British Journal of Hematology	2024	39279196
A genome-wide association study of alloimmunization in the TOPMed OMG-SCD cohort identifies a locus on chromosome 12	Transfusion	2024	38966903
Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium	Human Molecular Genetics	2024	38747556
Metabolite signatures associated with microRNA miR-143-3p serve as drivers of poor lung function trajectories in childhood asthma	eBioMedicine	2024	38458111

Resources for the Scientific Community

TOPMed data are being made available to the scientific community as a series of “data freezes”:

genotypes and phenotypes via dbGaP
read alignments via the Sequence Read Archive (SRA)
variant summary information via the Bravo variant server
single nucleotide polymorphisms (dbSNP)

TOPMed WGS data are contained in study-specific accessions with names containing “NHLBI TOPMed,” while most phenotypic data are in parent study accessions. The TOPMed accessions can be identified by searching the dbGaP website for “TOPMed.” More information about the available data and how to access it can be found on the Data Access page.

Trans-Omics for Precision Medicine | TOPMed