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Rank concordance of polygenic indices

Author

Listed:
  • Dilnoza Muslimova

    (Erasmus School of Economics, Erasmus University Rotterdam
    Tinbergen Institute)

  • Rita Dias Pereira

    (Erasmus School of Economics, Erasmus University Rotterdam
    Tinbergen Institute)

  • Stephanie Hinke

    (Tinbergen Institute
    School of Economics, University of Bristol)

  • Hans Kippersluis

    (Erasmus School of Economics, Erasmus University Rotterdam
    Tinbergen Institute)

  • Cornelius A. Rietveld

    (Erasmus School of Economics, Erasmus University Rotterdam
    Tinbergen Institute
    Erasmus University Rotterdam Institute for Behaviour and Biology, Erasmus University Rotterdam)

  • S. Fleur W. Meddens

    (Erasmus School of Economics, Erasmus University Rotterdam
    Statistics Netherlands)

Abstract

Polygenic indices (PGIs) are increasingly used to identify individuals at risk of developing disease and are advocated as screening tools for personalized medicine and education. Here we empirically assess rank concordance between PGIs created with different construction methods and discovery samples, focusing on cardiovascular disease and educational attainment. We find Spearman rank correlations between 0.17 and 0.93 for cardiovascular disease, and 0.40 and 0.83 for educational attainment, indicating highly unstable rankings across different PGIs for the same trait. Potential consequences for personalized medicine and gene–environment (G × E) interplay are illustrated using data from the UK Biobank. Simulations show how rank discordance mainly derives from a limited discovery sample size and reveal a tight link between the explained variance of a PGI and its ranking precision. We conclude that PGI-based ranking is highly dependent on PGI choice, such that current PGIs do not have the desired precision to be used routinely for personalized intervention.

Suggested Citation

  • Dilnoza Muslimova & Rita Dias Pereira & Stephanie Hinke & Hans Kippersluis & Cornelius A. Rietveld & S. Fleur W. Meddens, 2023. "Rank concordance of polygenic indices," Nature Human Behaviour, Nature, vol. 7(5), pages 802-811, May.
    • Handle: RePEc:nat:nathum:v:7:y:2023:i:5:d:10.1038_s41562-023-01544-6
    DOI: 10.1038/s41562-023-01544-6
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    Cited by:

    1. Bertoni, M.; & Marin-Lopez, B.A.; & Sanz-de-Galdeano, A.;, 2023. "Subjective Gender-Based Patterns in ADHD Diagnosis," Health, Econometrics and Data Group (HEDG) Working Papers 23/17, HEDG, c/o Department of Economics, University of York.

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