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Analysis of polygenic risk score usage and performance in diverse human populations

Author

Listed:
  • L. Duncan

    (Stanford University)

  • H. Shen

    (Stanford University)

  • B. Gelaye

    (Harvard T.H. Chan School of Public Health)

  • J. Meijsen

    (Stanford University)

  • K. Ressler

    (McLean Hospital)

  • M. Feldman

    (Stanford University)

  • R. Peterson

    (Virginia Commonwealth University)

  • B. Domingue

    (Stanford University)

Abstract

A historical tendency to use European ancestry samples hinders medical genetics research, including the use of polygenic scores, which are individual-level metrics of genetic risk. We analyze the first decade of polygenic scoring studies (2008–2017, inclusive), and find that 67% of studies included exclusively European ancestry participants and another 19% included only East Asian ancestry participants. Only 3.8% of studies were among cohorts of African, Hispanic, or Indigenous peoples. We find that predictive performance of European ancestry-derived polygenic scores is lower in non-European ancestry samples (e.g. African ancestry samples: t = −5.97, df = 24, p = 3.7 × 10−6), and we demonstrate the effects of methodological choices in polygenic score distributions for worldwide populations. These findings highlight the need for improved treatment of linkage disequilibrium and variant frequencies when applying polygenic scoring to cohorts of non-European ancestry, and bolster the rationale for large-scale GWAS in diverse human populations.

Suggested Citation

  • L. Duncan & H. Shen & B. Gelaye & J. Meijsen & K. Ressler & M. Feldman & R. Peterson & B. Domingue, 2019. "Analysis of polygenic risk score usage and performance in diverse human populations," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11112-0
    DOI: 10.1038/s41467-019-11112-0
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    2. Qin Qin Huang & Neneh Sallah & Diana Dunca & Bhavi Trivedi & Karen A. Hunt & Sam Hodgson & Samuel A. Lambert & Elena Arciero & John Wright & Chris Griffiths & Richard C. Trembath & Harry Hemingway & M, 2022. "Transferability of genetic loci and polygenic scores for cardiometabolic traits in British Pakistani and Bangladeshi individuals," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
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    6. Rita Dias Pereira & Pietro Biroli & Titus Galama & Stephanie von Hinke & Hans van Kippersluis & Cornelius A. Rietveld & Kevin Thom, 2022. "Gene-Environment Interplay in the Social Sciences," Papers 2203.02198, arXiv.org, revised Aug 2022.
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    9. Ananyo Choudhury & Jean-Tristan Brandenburg & Tinashe Chikowore & Dhriti Sengupta & Palwende Romuald Boua & Nigel J. Crowther & Godfred Agongo & Gershim Asiki & F. Xavier Gómez-Olivé & Isaac Kisiangan, 2022. "Meta-analysis of sub-Saharan African studies provides insights into genetic architecture of lipid traits," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    10. Nuzulul Kurniansyah & Matthew O. Goodman & Tanika N. Kelly & Tali Elfassy & Kerri L. Wiggins & Joshua C. Bis & Xiuqing Guo & Walter Palmas & Kent D. Taylor & Henry J. Lin & Jeffrey Haessler & Yan Gao , 2022. "A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    11. Brieuc Lehmann & Maxine Mackintosh & Gil McVean & Chris Holmes, 2023. "Optimal strategies for learning multi-ancestry polygenic scores vary across traits," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    12. Trejo, Sam, 2020. "Exploring Genetic Influences on Birth Weight," SocArXiv 7j59q, Center for Open Science.
    13. Jiacheng Miao & Hanmin Guo & Gefei Song & Zijie Zhao & Lin Hou & Qiongshi Lu, 2023. "Quantifying portable genetic effects and improving cross-ancestry genetic prediction with GWAS summary statistics," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    14. Ricky Lali & Michael Chong & Arghavan Omidi & Pedrum Mohammadi-Shemirani & Ann Le & Edward Cui & Guillaume Paré, 2021. "Calibrated rare variant genetic risk scores for complex disease prediction using large exome sequence repositories," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    15. Alesha A. Hatton & Fei-Fei Cheng & Tian Lin & Ren-Juan Shen & Jie Chen & Zhili Zheng & Jia Qu & Fan Lyu & Sarah E. Harris & Simon R. Cox & Zi-Bing Jin & Nicholas G. Martin & Dongsheng Fan & Grant W. M, 2024. "Genetic control of DNA methylation is largely shared across European and East Asian populations," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    16. Carla Márquez-Luna & Steven Gazal & Po-Ru Loh & Samuel S. Kim & Nicholas Furlotte & Adam Auton & Alkes L. Price, 2021. "Incorporating functional priors improves polygenic prediction accuracy in UK Biobank and 23andMe data sets," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    17. H. Serhat Tetikol & Deniz Turgut & Kubra Narci & Gungor Budak & Ozem Kalay & Elif Arslan & Sinem Demirkaya-Budak & Alexey Dolgoborodov & Duygu Kabakci-Zorlu & Vladimir Semenyuk & Amit Jain & Brandi N., 2022. "Pan-African genome demonstrates how population-specific genome graphs improve high-throughput sequencing data analysis," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    18. Kaname Kojima & Shu Tadaka & Fumiki Katsuoka & Gen Tamiya & Masayuki Yamamoto & Kengo Kinoshita, 2020. "A genotype imputation method for de-identified haplotype reference information by using recurrent neural network," PLOS Computational Biology, Public Library of Science, vol. 16(10), pages 1-21, October.
    19. Jasmin Wertz & Terrie E. Moffitt & Louise Arseneault & J. C. Barnes & Michel Boivin & David L. Corcoran & Andrea Danese & Robert J. Hancox & HonaLee Harrington & Renate M. Houts & Stephanie Langevin &, 2023. "Genetic associations with parental investment from conception to wealth inheritance in six cohorts," Nature Human Behaviour, Nature, vol. 7(8), pages 1388-1401, August.

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