Polygenic RIsk MEthods in Diverse populations (PRIMED) Consortium
Members of the Polygenic RIsk MEthods in Diverse populations (PRIMED) Consortium will work together to develop and implement approaches to integrating extant genotype and phenotype data for the purpose of conducting and disseminating Consortium-wide PRS analyses.
The Polygenic RIsk MEthods in Diverse populations (PRIMED) Consortium is working to improve the methods and application of PRS in diverse populations. The consortium has two overarching goals:
- improve the applicability of PRS in diverse populations
- optimize the integration of large-scale, harmonized genomic and phenotype data.
Starting June 2021, the seven awarded study sites and one awarded coordinating center will work together over the next five years to accomplish these goals and disseminate data to the scientific community. Data integration and analysis will occur largely on NHGRI's Genomic Data Science Analysis, Visualization, and Informatics Lab-Space (AnVIL platform). The group will collectively integrate data on a broad range of phenotypes from more than 120 datasets across 45 countries.
|University of Maryland, Baltimore||Sally Adebamowo*, Michele Ramsay, Bamidele Tayo||Polygenic risk score (PRS) methods and analysis for populations of diverse ancestry — study sites|
|University of Southern California**||David Conti*, John Witte||Leveraging diversity in cancer epidemiology cohorts and novel methods to improve polygenic risk scores|
|Massachusetts General Hospital||Amit Khera||Enabling improved applicability and transferability of polygenic scores across diverse populations — a focus on South Asians|
|Mayo Clinic, Rochester, Minnesota||Iftikhar Kullo*, Daniel Schaid||Polygenic risk of disease in populations of diverse ancestry|
|UNC-Chapel Hill||Yun Li*, Alexander Reiner, Nancy Cox||Polygenic risk scores and health disparities: The role of blood cells immune response and evolutionary adaptation|
|Broad Institute, Cambridge||Josep Mercader*, Maggie Ng, Alisa Manning||Development of polygenic risk scores for diabetes and complications across the life span in populations of diverse ancestry|
|University of California, Los Angeles||Bogdan Pasanuic*, Eimear Kenny, Leslie Lange||PRS Center for Admixed Populations and Health Equity (CAPE)|
**Co-funded by NCI
Working Groups Convened in 2021
Co-chairs: Yun Li and Josep Mercader
Mission: The Genotype Harmonization Working Group (WG) will ensure the availability of high-quality genotype datasets harmonized across all PRIMED Consortium studies. This WG will address the harmonization of both individual-level genotype data and genomic summary results. An initial priority for this WG will be to inventory existing data and formulate a quality control (QC) and harmonization plan. This plan will cover study-specific variant and sample QC; cross-study genotype harmonization — including imputation to a common reference panel and transformation to a common genome build, allele representation, and data format; and cross-study QC to evaluate harmonization. The WG will implement genotype QC and harmonization workflows on the AnVIL or other platforms.
Co-chairs: Laura Raffield and Leslie Lange
Mission: The Phenotype Harmonization WG will be responsible for defining the data format and documentation requirements for Study Site and Affiliate Member-provided phenotype data. These definitions will be chosen to generate a Consortium-wide phenotype variable inventory and subsequent harmonization. The WG will also define data standards for Consortium-generated data (e.g., ontologies for Consortium-harmonized variables). The Phenotype Harmonization WG will inventory existing data, coordinate and prioritize harmonization efforts, establish and document best practices, and define consortium phenotype data standards. As phenotype-specific WGs are established, this WG may also be called upon to refine or update PRIMED standards in collaboration with the phenotype-specific WGs.
Co-chairs: Bamidele Tayo and Quenna Wong
Mission: The Data Sharing WG will collaborate on developing policies and processes to share data within the PRIMED Consortium. The data to be shared include individual-level genotype and phenotype data (source and harmonized) and summary statistics from the studies and consortia proposed by the Study Sites for either PRS development or validation. An initial priority for this WG will be to understand the opportunities and constraints for intra-Consortium sharing of the studies and consortia proposed by Study Sites, especially those governed by groups not affiliated with the PRIMED Consortium. The policies and processes developed by this WG will need to facilitate sharing within Consortium workspaces on the AnVIL platform and anticipate subsequent data release to the scientific community, also on AnVIL. Initially, the WG scope will include both technical aspects of data sharing (e.g., the establishment of AnVIL workspaces) and policy aspects (e.g., data use limitations).
Co-chairs: Bogdan Pasanuic and John Witte
Mission: The Methods Review WG will review and summarize currently available methods and software for developing and validating PRS, focusing on their use in diverse ancestry populations. This review will identify key topics for new methods and software development by PRIMED investigators. In addition, WG members and AnVIL developers will assess the availability of state-of-the-art PRS software on AnVIL and describe how methods developers can ensure approaches are feasible at scale using AnVIL. Based on the critical topics identified, this WG will propose subsequent analysis- and methods-focused WGs to operate within PRIMED (see initial topic list suggestions in the section below). Early measures of the success of the WG will be the deployment of PRS software on AnVIL and the production of a review paper on the current state of PRS methods and their applicability — or otherwise — to diverse ancestry populations. The PRIMED Methods Review WG may be wound up after the subsequent analysis- and methods-focused WGs are sufficiently scoped and established.
- Program Director
- National Cancer Institute
- Science Program Analyst
- Division of Genomic Medicine
Last updated: October 27, 2021