Multi-Omics for Health and Disease (Multi-Omics)
Contributing NIH Institutes:
National Human Genome Research Institute (NHGRI)
National Cancer Institute (NCI)
National Institute of Environmental Health Sciences (NIEHS)
The Multi-Omics for Health and Disease Consortium aims to advance the application of multi-omic technologies to study health and disease in ancestrally diverse populations.
While single ‘omic analyses have produced valuable insights, recent studies have shown that integrative (or multi-omic) analysis approaches can improve the classification of disease into clinically relevant subgroups and potentially identify biomarkers of health or disease. Multi-omic analyses can also help define relationships among ‘omic data types to unravel biological networks regulating transitions from health to disease. This initiative is expected to produce consensus approaches, best practices, and standards that can be generalized across diseases and populations. It will also generate a standardized and harmonized dataset for general research use available through controlled-access processes as well as a portal for visualization. Ultimately, this program will enhance the utility of ‘omic technologies in understanding the biology of health and disease.
The Multi-Omics for Health and Disease Consortium is a collaborative initiative that will advance the application of multi-omic technologies to study health and disease in ancestrally diverse populations. By leveraging disease contexts where multi-omic approaches are expected to be most impactful, the proposed consortium will
- Examine the use of multiple ‘omics data, combined with phenotypic and environmental exposure data, including social determinants of health (SDOH), to detect and assess molecular “profiles” associated with healthy and diseased states as well as transitions from health to disease or vice versa.
- Leverage this collaborative analysis to develop generalizable data harmonization, integration, and analysis methods, as well as best practices and standards for the optimal application of multi-omics technologies across clinical conditions.
- Create a standardized and harmonized multi-dimensional data set that is widely available to the broader research community, is interoperable with existing resources, and upholds data sharing and privacy principles. This rich data set will include 1) persons from ancestrally diverse populations; 2) persons with and without specific diseases; 3) harmonized and standardized phenotypic and environmental exposure data; 4) harmonized and standardized data for all or most ‘omes for each biosample; 5) data from multiple time points; and 6) associated meta-data to facilitate links across data types.
While this program may provide some insights into disease etiology, its primary goal is to validate and enhance generalizable multi-omic approaches to identify meaningful biological changes related to health or disease.
The consortium will include 3 components:
- up to 6 Disease Study Sites that will enroll participants and capture phenotypic and environmental exposure data to study clinical conditions for which integrative multi-omics would be particularly impactful in defining associations with healthy and disease states.
- one or two ‘Omics Production Centers that will utilize high-throughput molecular assays to produce: genomic, epigenomic, transcriptomic, proteomic, and metabolomic data.
- one Data Analysis and Coordination Center that will focus on coordinating protocol development, consortium logistics, and the production and release of a multi-dimensional data set that is available to the scientific community.
- Scientific Program Analyst
- Division of Genome Sciences
- Program Director
- Division of Cancer Control and Population Sciences
- Program Director
- Division of Cancer Control and Population Sciences, NCI
- Program Director
- Genes, Environment, and Health Branch, NIEHS
Last updated: June 23, 2023