Nature Communications (Jun 2023)
Evaluating the use of blood pressure polygenic risk scores across race/ethnic background groups
- Nuzulul Kurniansyah,
- Matthew O. Goodman,
- Alyna T. Khan,
- Jiongming Wang,
- Elena Feofanova,
- Joshua C. Bis,
- Kerri L. Wiggins,
- Jennifer E. Huffman,
- Tanika Kelly,
- Tali Elfassy,
- Xiuqing Guo,
- Walter Palmas,
- Henry J. Lin,
- Shih-Jen Hwang,
- Yan Gao,
- Kendra Young,
- Gregory L. Kinney,
- Jennifer A. Smith,
- Bing Yu,
- Simin Liu,
- Sylvia Wassertheil-Smoller,
- JoAnn E. Manson,
- Xiaofeng Zhu,
- Yii-Der Ida Chen,
- I-Te Lee,
- C. Charles Gu,
- Donald M. Lloyd-Jones,
- Sebastian Zöllner,
- Myriam Fornage,
- Charles Kooperberg,
- Adolfo Correa,
- Bruce M. Psaty,
- Donna K. Arnett,
- Carmen R. Isasi,
- Stephen S. Rich,
- Robert C. Kaplan,
- Susan Redline,
- Braxton D. Mitchell,
- Nora Franceschini,
- Daniel Levy,
- Jerome I. Rotter,
- Alanna C. Morrison,
- Tamar Sofer
Affiliations
- Nuzulul Kurniansyah
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital
- Matthew O. Goodman
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital
- Alyna T. Khan
- Department of Biostatistics, University of Washington
- Jiongming Wang
- Department of Biostatistics, University of Michigan
- Elena Feofanova
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston
- Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington
- Kerri L. Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington
- Jennifer E. Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System
- Tanika Kelly
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine
- Tali Elfassy
- Department of Public Health Sciences, University of Miami Miller School of Medicine
- Xiuqing Guo
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
- Walter Palmas
- Department of Medicine, Columbia University Medical Center
- Henry J. Lin
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
- Shih-Jen Hwang
- The Population Sciences Branch of the National Heart, Lung and Blood Institute
- Yan Gao
- The Jackson Heart Study, University of Mississippi Medical Center
- Kendra Young
- Department of Epidemiology, Colorado School of Public Health
- Gregory L. Kinney
- Department of Epidemiology, Colorado School of Public Health
- Jennifer A. Smith
- Department of Epidemiology, University of Michigan School of Public Health
- Bing Yu
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston
- Simin Liu
- Center for Global Cardiometabolic Health, Department of Epidemiology, Brown University
- Sylvia Wassertheil-Smoller
- Department of Pediatrics, Albert Einstein College of Medicine
- JoAnn E. Manson
- Department of Medicine, Harvard Medical School, Brigham and Women’s Hospital
- Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University
- Yii-Der Ida Chen
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
- I-Te Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital
- C. Charles Gu
- Division of Biostatistics, Washington University School of Medicine
- Donald M. Lloyd-Jones
- Department of Preventive Medicine, Northwestern University
- Sebastian Zöllner
- Department of Biostatistics, University of Michigan
- Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston
- Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center
- Adolfo Correa
- Departments of Medicine and Pediatrics, University of Mississippi Medical Center
- Bruce M. Psaty
- Department of Medicine, University of Washington
- Donna K. Arnett
- Office of the Provost, University of South Carolina
- Carmen R. Isasi
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine
- Stephen S. Rich
- Center for Public Health Genomics, University of Virginia School of Medicine
- Robert C. Kaplan
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center
- Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital
- Braxton D. Mitchell
- Department of Medicine, University of Maryland School of Medicine
- Nora Franceschini
- Department of Epidemiology, University of North Carolina
- Daniel Levy
- The Population Sciences Branch of the National Heart, Lung and Blood Institute
- Jerome I. Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
- Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston
- Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital
- DOI
- https://doi.org/10.1038/s41467-023-38990-9
- Journal volume & issue
-
Vol. 14,
no. 1
pp. 1 – 14
Abstract
Abstract We assess performance and limitations of polygenic risk scores (PRSs) for multiple blood pressure (BP) phenotypes in diverse population groups. We compare “clumping-and-thresholding” (PRSice2) and LD-based (LDPred2) methods to construct PRSs from each of multiple GWAS, as well as multi-PRS approaches that sum PRSs with and without weights, including PRS-CSx. We use datasets from the MGB Biobank, TOPMed study, UK biobank, and from All of Us to train, assess, and validate PRSs in groups defined by self-reported race/ethnic background (Asian, Black, Hispanic/Latino, and White). For both SBP and DBP, the PRS-CSx based PRS, constructed as a weighted sum of PRSs developed from multiple independent GWAS, perform best across all race/ethnic backgrounds. Stratified analysis in All of Us shows that PRSs are better predictive of BP in females compared to males, individuals without obesity, and middle-aged (40-60 years) compared to older and younger individuals.
