Abstract

Polygenic risk scores (PRS) are poised to improve biomedical outcomes via precision medicine. However, the major ethical and scientific challenge surrounding clinical implementation of PRS is that those available today are several times more accurate in individuals of European ancestry than other ancestries. This disparity is an inescapable consequence of Eurocentric biases in genome-wide association studies, thus highlighting that—unlike clinical biomarkers and prescription drugs, which may individually work better in some populations but do not ubiquitously perform far better in European populations—clinical uses of PRS today would systematically afford greater improvement for European-descent populations. Early diversifying efforts show promise in leveling this vast imbalance, even when non-European sample sizes are considerably smaller than the largest studies to date. To realize the full and equitable potential of PRS, greater diversity must be prioritized in genetic studies, and summary statistics must be publically disseminated to ensure that health disparities are not increased for those individuals already most underserved.

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Acknowledgements

We thank A. Khera for helpful discussions. We also thank M. Kubo, Y. Murakami, M. Akiyama and K. Ishigaki for their support in the BBJ Project analysis. We are grateful to S. Gazal for help in calculating LD scores. This work was supported by funding from the National Institutes of Health (K99MH117229 to A.R.M.). UKBB analyses were conducted via application 31063. The BBJ Project was supported by the Tailor-Made Medical Treatment Program of the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) and the Japan Agency for Medical Research and Development (AMED). M.K. was supported by a Nakajima Foundation Fellowship and the Masason Foundation.

Author information

Affiliations

  1. Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA

    • Alicia R. Martin
    • , Masahiro Kanai
    • , Benjamin M. Neale
    •  & Mark J. Daly
  2. Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA

    • Alicia R. Martin
    • , Masahiro Kanai
    • , Benjamin M. Neale
    •  & Mark J. Daly
  3. Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA

    • Alicia R. Martin
    • , Masahiro Kanai
    • , Benjamin M. Neale
    •  & Mark J. Daly
  4. Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA

    • Masahiro Kanai
  5. Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

    • Masahiro Kanai
    • , Yoichiro Kamatani
    •  & Yukinori Okada
  6. Kyoto–McGill International Collaborative School in Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan

    • Yoichiro Kamatani
  7. Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan

    • Yukinori Okada
  8. Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan

    • Yukinori Okada
  9. Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland

    • Mark J. Daly

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Contributions

A.R.M. and M.J.D. conceived and designed the experiments. A.R.M. and M.K. performed statistical analysis. A.R.M. and M.K. analyzed the data. A.R.M., M.K., Y.K., Y.O., B.M.N. and M.J.D. contributed reagents/materials/analysis tools. A.R.M., M.K., B.M.N. and M.J.D. wrote the paper.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Alicia R. Martin.

Supplementary information

  1. Supplementary Information

    Supplementary Note, Supplementary Tables 1–9 and Supplementary Figures 1–13

  2. Reporting Summary

  3. Supplementary Data Sets 1–3

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https://doi.org/10.1038/s41588-019-0379-x

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