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Trans-Omics for Precision Medicine | 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.

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.

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
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

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
Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium Human Molecular Genetics 38747556
Metabolite signatures associated with microRNA miR-143-3p serve as drivers of poor lung function trajectories in childhood asthma eBioMedicine 38458111
Transcriptome-wide association study of the plasma proteome reveals cis and trans regulatory mechanisms underlying complex traits AJHG 38320554
A genetic association study of circulating coagulation Factor VIII and von Willebrand Factor levels Blood 38320121
Interaction molecular QTL mapping discovers cellular and environmental modifiers of genetic regulatory effects American Journal of Human Genetics 38181730

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.

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