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Polygenic risk score for type 2 diabetes shows context-dependent effects across populations

Author

Listed:
  • Boya Guo

    (Fred Hutchinson Cancer Center)

  • Yanwei Cai

    (Fred Hutchinson Cancer Center)

  • Daeeun Kim

    (University of North Carolina at Chapel Hill
    University of North Carolina at Chapel Hill)

  • Roelof A. J. Smit

    (Icahn School of Medicine at Mount Sinai)

  • Zhe Wang

    (Icahn School of Medicine at Mount Sinai
    University of Alabama at Birmingham)

  • Kruthika R. Iyer

    (Gladstone Institutes
    Stanford University School of Medicine
    VA Palo Alto Health Care System)

  • Austin T. Hilliard

    (VA Palo Alto Health Care System)

  • Jeffrey Haessler

    (Fred Hutchinson Cancer Center)

  • Ran Tao

    (Vanderbilt University Medical Center
    Vanderbilt University of Medical Center)

  • K. Alaine Broadaway

    (University of North Carolina at Chapel Hill)

  • Yujie Wang

    (University of North Carolina at Chapel Hill)

  • Nikita Pozdeyev

    (University of Colorado Anschutz Medical Campus)

  • Frederik F. Stæger

    (University of Copenhagen)

  • Chaojie Yang

    (University of Virginia)

  • Brett Vanderwerff

    (University of Michigan)

  • Amit D. Patki

    (University of Alabama at Birmingham)

  • Lauren Stalbow

    (Icahn School of Medicine at Mount Sinai)

  • Meng Lin

    (University of Colorado Anschutz Medical Campus)

  • Nicholas Rafaels

    (University of Colorado Anschutz Medical Campus)

  • Jonathan Shortt

    (University of Colorado Anschutz Medical Campus)

  • Laura Wiley

    (University of Colorado Anschutz Medical Campus)

  • Maggie Stanislawski

    (University of Colorado Anschutz Medical Campus)

  • Jack Pattee

    (University of Colorado Anschutz Medical Campus)

  • Lea Davis

    (Icahn School of Medicine at Mount Sinai)

  • Peter S. Straub

    (Vanderbilt University of Medical Center
    Vanderbilt University of Medical Center)

  • Megan M. Shuey

    (Vanderbilt University of Medical Center
    Vanderbilt University of Medical Center)

  • Nancy J. Cox

    (Vanderbilt University of Medical Center
    Vanderbilt University of Medical Center)

  • Nanette R. Lee

    (University of San Carlos)

  • Marit E. Jørgensen

    (Steno Diabetes Center Greenland
    University of Southern Denmark)

  • Peter Bjerregaard

    (University of Southern Denmark)

  • Christina Larsen

    (University of Southern Denmark)

  • Torben Hansen

    (University of Copenhagen)

  • Ida Moltke

    (University of Copenhagen)

  • James B. Meigs

    (Harvard Medical School)

  • Daniel O. Stram

    (University of Southern California)

  • Xianyong Yin

    (Nanjing Medical University
    University of Michigan
    University of Michigan)

  • Xiang Zhou

    (University of Michigan
    University of Michigan)

  • Kyong-Mi Chang

    (Corporal Michael J. Crescenz VA Medical Center
    University of Pennsylvania Perelman School of Medicine)

  • Shoa L. Clarke

    (Stanford University School of Medicine
    VA Palo Alto Health Care System
    Stanford University School of Medicine)

  • Rodrigo Guarischi-Sousa

    (Stanford University School of Medicine
    VA Palo Alto Health Care System)

  • Joanna Lankester

    (Stanford University School of Medicine
    VA Palo Alto Health Care System)

  • Philip S. Tsao

    (Stanford University School of Medicine
    VA Palo Alto Health Care System)

  • Steven Buyske

    (Rutgers University)

  • Mariaelisa Graff

    (University of North Carolina at Chapel Hill)

  • Laura M. Raffield

    (University of North Carolina at Chapel Hill)

  • Quan Sun

    (University of North Carolina at Chapel Hill)

  • Lynne R. Wilkens

    (University of Hawaii Cancer Center)

  • Christopher S. Carlson

    (Fred Hutchinson Cancer Center)

  • Charles B. Easton

    (Brown University
    Brown University)

  • Simin Liu

    (Brown University)

  • JoAnn E. Manson

    (Harvard Medical School)

  • Loïc L. Marchand

    (University of Hawaii Cancer Center)

  • Christopher A. Haiman

    (University of Southern California)

  • Karen L. Mohlke

    (University of North Carolina at Chapel Hill)

  • Penny Gordon-Larsen

    (University of North Carolina at Chapel Hill)

  • Anders Albrechtsen

    (University of Copenhagen)

  • Michael Boehnke

    (University of Michigan)

  • Stephen S. Rich

    (University of Virginia)

  • Ani Manichaikul

    (University of Virginia)

  • Jerome I. Rotter

    (The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center)

  • Noha A. Yousri

    (Hamad Bin Khalifa University
    Alexandria University)

  • Ryan M. Irvin

    (University of Alabama at Birmingham)

  • Chris Gignoux

    (University of Colorado Anschutz Medical Campus)

  • Kari E. North

    (University of North Carolina at Chapel Hill)

  • Ruth J. F. Loos

    (Icahn School of Medicine at Mount Sinai)

  • Themistocles L. Assimes

    (Stanford University School of Medicine
    VA Palo Alto Health Care System)

  • Ulrike Peters

    (Fred Hutchinson Cancer Center
    University of Washington)

  • Charles Kooperberg

    (Fred Hutchinson Cancer Center)

  • Sridharan Raghavan

    (University of Colorado Anschutz Medical Campus
    University of Colorado School of Medicine)

  • Heather M. Highland

    (University of North Carolina at Chapel Hill)

  • Burcu F. Darst

    (Fred Hutchinson Cancer Center)

Abstract

Polygenic risk scores hold prognostic value for identifying individuals at higher risk of type 2 diabetes. However, further characterization is needed to understand the generalizability of type 2 diabetes polygenic risk scores in diverse populations across various contexts. We systematically characterize a multi-ancestry type 2 diabetes polygenic risk score among 244,637 cases and 637,891 controls across diverse populations from the Population Architecture Genomics and Epidemiology Study and 13 additional biobanks and cohorts. Polygenic risk score performance is context dependent, with better performance in those who are younger, male, without hypertension, and not obese or overweight. Additionally, the polygenic risk score is associated with various diabetes-related cardiometabolic traits and type 2 diabetes complications, suggesting its utility for stratifying risk of complications and identifying shared genetic architecture between type 2 diabetes and other diseases. These findings highlight the need to account for context when evaluating polygenic risk score as a tool for type 2 diabetes risk prognostication and the potentially generalizable associations of type 2 diabetes polygenic risk score with diabetes-related traits, despite differential performance in type 2 diabetes prediction across diverse populations. Our study provides a comprehensive resource to characterize a type 2 diabetes polygenic risk score.

Suggested Citation

  • Boya Guo & Yanwei Cai & Daeeun Kim & Roelof A. J. Smit & Zhe Wang & Kruthika R. Iyer & Austin T. Hilliard & Jeffrey Haessler & Ran Tao & K. Alaine Broadaway & Yujie Wang & Nikita Pozdeyev & Frederik F, 2025. "Polygenic risk score for type 2 diabetes shows context-dependent effects across populations," Nature Communications, Nature, vol. 16(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-63546-4
    DOI: 10.1038/s41467-025-63546-4
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