Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations

Tian Ge(Broad Institute), Marguerite R. Irvin(University of Alabama at Birmingham), Amit Patki(University of Alabama at Birmingham), Vinodh Srinivasasainagendra(University of Alabama at Birmingham), Kuang Lin(National Yang Ming Chiao Tung University), Hemant K. Tiwari(University of Alabama at Birmingham), Nicole D. Armstrong(University of Alabama at Birmingham), Barbara Benoit(Mass General Brigham), Chia‐Yen Chen(Biogen (United States)), Karmel W. Choi(Massachusetts General Hospital), James J. Cimino(University of Alabama at Birmingham), Brittney H. Davis(University of Alabama at Birmingham), Ozan Dikilitas(Mayo Clinic), Bethany Etheridge(University of Alabama at Birmingham), Yen‐Chen Anne Feng(National Taiwan University), Vivian S. Gainer(Mass General Brigham), Hailiang Huang(Broad Institute), Gail P. Jarvik(University of Washington Medical Center), Christopher Kachulis(Broad Institute), Eimear E. Kenny(Genomic Health (United States)), Atlas Khan(Columbia University), Krzysztof Kiryluk(Columbia University), Leah C. Kottyan(Cincinnati Children's Hospital Medical Center), Iftikhar J. Kullo(Mayo Clinic in Arizona), Christoph Lange(Harvard University), Niall J. Lennon(Broad Institute), Aaron Leong(Broad Institute), Edyta Małolepsza(Broad Institute), Ayme D. Miles(University of Alabama at Birmingham), Shawn N. Murphy(Massachusetts General Hospital), Bahram Namjou(Cincinnati Children's Hospital Medical Center), Renuka Narayan(University of Alabama at Birmingham), Mark J. O’Connor(UMass Memorial Health Care), Jennifer A. Pacheco(Northwestern University), Emma Perez(Brigham and Women's Hospital), Laura J. Rasmussen‐Torvik(Northwestern University), Elisabeth A. Rosenthal(University of Washington Medical Center), Daniel J. Schaid(Mayo Clinic in Florida), Maria Stamou(Massachusetts General Hospital), Miriam S. Udler(Broad Institute), Wei‐Qi Wei(Vanderbilt University Medical Center), Scott T. Weiss(Brigham and Women's Hospital), Maggie C. Y. Ng(Vanderbilt University Medical Center), Jordan W. Smoller(Broad Institute), Matthew S. Lebo(Broad Institute), James B. Meigs(Broad Institute), Nita A. Limdi(University of Alabama at Birmingham), Elizabeth W. Karlson(Brigham and Women's Hospital)
Genome Medicine
June 28, 2022
Cited by 168Open Access
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Abstract

BACKGROUND: Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations. METHODS: We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts. RESULTS: The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5-4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance. CONCLUSIONS: By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.


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