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Data sharing in the PRIMED Consortium: Design, implementation, and recommendations for future policymaking.

Johanna L Smith1, Quenna Wong2, Whitney Hornsby3

  • 1Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55902, USA.

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|July 8, 2025
PubMed
Summary
This summary is machine-generated.

The Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium developed data-sharing policies for diverse genomic data. This enables improved polygenic risk scores for global health equity.

Keywords:
cloud platformsconsortiumdata access and usedata sharinggenomic summary resultspolygenic risk scores

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Area of Science:

  • Genomics
  • Biomedical Data Science
  • Health Equity

Background:

  • Sharing diverse genomic and biomedical data is crucial for scientific advancement and equitable health translation.
  • Challenges in data sharing include legacy datasets, evolving policies, multi-institutional collaborations, and international data governance.
  • The Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium aims to enhance polygenic risk estimates across diverse populations.

Purpose of the Study:

  • To design and implement data-sharing policies and procedures for the PRIMED Consortium.
  • To aggregate and analyze data from multiple, heterogeneous sources while respecting existing policies and participant consent.
  • To facilitate the improvement of polygenic risk score performance in genetically diverse populations.

Main Methods:

  • Developed coordinated database of Genotypes and Phenotypes (dbGaP) applications and a Consortium Data Sharing Agreement.
  • Utilized federated analyses as an alternative for data that cannot be shared directly.
  • Implemented data sharing on the NHGRI Analysis Visualization and Informatics Lab-space (AnVIL) cloud platform for derived data, summary results, and workflows.

Main Results:

  • Established robust data-sharing mechanisms accommodating diverse data sources and pre-existing policies.
  • Successfully shared derived individual-level data, genomic summary results, and methods workflows via the AnVIL platform.
  • Identified and proposed solutions for challenges related to the secondary use and release of data products.

Conclusions:

  • The PRIMED Consortium's data-sharing framework enables secondary data use and analysis for improved polygenic risk scores.
  • Recommendations are provided for future consortia and policymaking to enhance data sharing in genomic research.
  • The implemented policies and technical solutions support equitable translation of genomic discoveries into health benefits.