Genome Medicine (Jun 2022)
Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations
- Tian Ge,
- Marguerite R. Irvin,
- Amit Patki,
- Vinodh Srinivasasainagendra,
- Yen-Feng Lin,
- Hemant K. Tiwari,
- Nicole D. Armstrong,
- Barbara Benoit,
- Chia-Yen Chen,
- Karmel W. Choi,
- James J. Cimino,
- Brittney H. Davis,
- Ozan Dikilitas,
- Bethany Etheridge,
- Yen-Chen Anne Feng,
- Vivian Gainer,
- Hailiang Huang,
- Gail P. Jarvik,
- Christopher Kachulis,
- Eimear E. Kenny,
- Atlas Khan,
- Krzysztof Kiryluk,
- Leah Kottyan,
- Iftikhar J. Kullo,
- Christoph Lange,
- Niall Lennon,
- Aaron Leong,
- Edyta Malolepsza,
- Ayme D. Miles,
- Shawn Murphy,
- Bahram Namjou,
- Renuka Narayan,
- Mark J. O’Connor,
- Jennifer A. Pacheco,
- Emma Perez,
- Laura J. Rasmussen-Torvik,
- Elisabeth A. Rosenthal,
- Daniel Schaid,
- Maria Stamou,
- Miriam S. Udler,
- Wei-Qi Wei,
- Scott T. Weiss,
- Maggie C. Y. Ng,
- Jordan W. Smoller,
- Matthew S. Lebo,
- James B. Meigs,
- Nita A. Limdi,
- Elizabeth W. Karlson
Affiliations
- Tian Ge
- Center for Genomic Medicine, Massachusetts General Hospital
- Marguerite R. Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham
- Amit Patki
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham
- Vinodh Srinivasasainagendra
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham
- Yen-Feng Lin
- Center for Neuropsychiatric Research, National Health Research Institutes
- Hemant K. Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham
- Nicole D. Armstrong
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham
- Barbara Benoit
- Mass General Brigham Research Information Science & Computing
- Chia-Yen Chen
- Translational Biology, Biogen Inc.
- Karmel W. Choi
- Center for Genomic Medicine, Massachusetts General Hospital
- James J. Cimino
- Informatics Institute, University of Alabama at Birmingham
- Brittney H. Davis
- Department of Neurology, School of Medicine, University of Alabama at Birmingham
- Ozan Dikilitas
- Department of Cardiovascular Medicine, Mayo Clinic
- Bethany Etheridge
- Department of Neurology, School of Medicine, University of Alabama at Birmingham
- Yen-Chen Anne Feng
- Center for Genomic Medicine, Massachusetts General Hospital
- Vivian Gainer
- Mass General Brigham Research Information Science & Computing
- Hailiang Huang
- Broad Institute of MIT and Harvard
- Gail P. Jarvik
- Division of Medical Genetics, Department of Medicine, University of Washington
- Christopher Kachulis
- Broad Institute of MIT and Harvard
- Eimear E. Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai
- Atlas Khan
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University
- Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University
- Leah Kottyan
- Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center
- Iftikhar J. Kullo
- Department of Cardiovascular Medicine, Mayo Clinic
- Christoph Lange
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
- Niall Lennon
- Broad Institute of MIT and Harvard
- Aaron Leong
- Broad Institute of MIT and Harvard
- Edyta Malolepsza
- Broad Institute of MIT and Harvard
- Ayme D. Miles
- Informatics Institute, University of Alabama at Birmingham
- Shawn Murphy
- Department of Neurology, Massachusetts General Hospital
- Bahram Namjou
- Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center
- Renuka Narayan
- Department of Neurology, School of Medicine, University of Alabama at Birmingham
- Mark J. O’Connor
- UMass Memorial Health Care
- Jennifer A. Pacheco
- Center for Genetic Medicine, Feinberg School of Medicine, Northwestern University
- Emma Perez
- Department of Medicine, Brigham and Women’s Hospital
- Laura J. Rasmussen-Torvik
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University
- Elisabeth A. Rosenthal
- Division of Medical Genetics, Department of Medicine, University of Washington
- Daniel Schaid
- Department of Quantitative Health Sciences, Mayo Clinic
- Maria Stamou
- Division of Endocrinology, Massachusetts General Hospital
- Miriam S. Udler
- Center for Genomic Medicine, Massachusetts General Hospital
- Wei-Qi Wei
- Department of Biomedical Informatics, Vanderbilt University Medical Center
- Scott T. Weiss
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital
- Maggie C. Y. Ng
- Vanderbilt Genetics Institute, Division of Genetic Medicine, Vanderbilt University Medical Center
- Jordan W. Smoller
- Center for Genomic Medicine, Massachusetts General Hospital
- Matthew S. Lebo
- Broad Institute of MIT and Harvard
- James B. Meigs
- Broad Institute of MIT and Harvard
- Nita A. Limdi
- Department of Neurology, School of Medicine, University of Alabama at Birmingham
- Elizabeth W. Karlson
- Department of Medicine, Brigham and Women’s Hospital
- DOI
- https://doi.org/10.1186/s13073-022-01074-2
- Journal volume & issue
-
Vol. 14,
no. 1
pp. 1 – 16
Abstract
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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