Principles and methods for transferring polygenic risk scores across global populations

Linda Kachuri; Nilanjan Chatterjee; Jibril Hirbo; Daniel J Schaid; Iman Martin; Iftikhar J Kullo; Eimear E Kenny; Bogdan Pasaniuc; Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium Methods Working Group; John S Witte; Tian Ge

doi:10.1038/s41576-023-00637-2

Principles and methods for transferring polygenic risk scores across global populations

Nat Rev Genet. 2024 Jan;25(1):8-25. doi: 10.1038/s41576-023-00637-2. Epub 2023 Aug 24.

Authors

Linda Kachuri^{1

2}, Nilanjan Chatterjee³, Jibril Hirbo^{4

5}, Daniel J Schaid⁶, Iman Martin⁷, Iftikhar J Kullo⁸, Eimear E Kenny^{9

10

11}, Bogdan Pasaniuc^{12

13

14}; Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium Methods Working Group; John S Witte^{15

16

17

18}, Tian Ge^{19

20

21}

Collaborators

Polygenic Risk Methods in Diverse Populations (PRIMED) Consortium Methods Working Group:
Paul L Auer, Matthew P Conomos, David V Conti, Yi Ding, Ying Wang, Haoyu Zhang, Yuji Zhang

Affiliations

¹ Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA.
² Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
³ Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
⁴ Department of Medicine Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
⁵ Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.
⁶ Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
⁷ Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, MD, USA.
⁸ Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
⁹ Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹⁰ Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹¹ Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
¹² Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
¹³ Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
¹⁴ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
¹⁵ Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA. jswitte@stanford.edu.
¹⁶ Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA. jswitte@stanford.edu.
¹⁷ Department of Biomedical Data Science, Stanford University, Stanford, CA, USA. jswitte@stanford.edu.
¹⁸ Department of Genetics, Stanford University, Stanford, CA, USA. jswitte@stanford.edu.
¹⁹ Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA. tge1@mgh.harvard.edu.
²⁰ Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. tge1@mgh.harvard.edu.
²¹ Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA. tge1@mgh.harvard.edu.

Abstract

Polygenic risk scores (PRSs) summarize the genetic predisposition of a complex human trait or disease and may become a valuable tool for advancing precision medicine. However, PRSs that are developed in populations of predominantly European genetic ancestries can increase health disparities due to poor predictive performance in individuals of diverse and complex genetic ancestries. We describe genetic and modifiable risk factors that limit the transferability of PRSs across populations and review the strengths and weaknesses of existing PRS construction methods for diverse ancestries. Developing PRSs that benefit global populations in research and clinical settings provides an opportunity for innovation and is essential for health equity.

Publication types

Review

MeSH terms

Genetic Predisposition to Disease*
Genome-Wide Association Study
Humans
Multifactorial Inheritance
Precision Medicine
Risk Factors

Abstract

Publication types

MeSH terms

Grants and funding