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Measuring the Effect of the Polygenic Risk Score on the Aging Rate

Author

Listed:
  • Effraimidis, Georgios

    (COHERE)

  • Levine, Morgan

    (Department of Human Genetics)

  • Crimmins, Eileen

    (USC Davis School of Gerontology)

Abstract

Population aging has emerged as a major demographic trend around the globe. Aging is a process that is determined by millions of genetic factors. The identification of the set of genetic factors that has a significant role in the aging process is a highly challenging task. This paper studies the association between genetic factors and the aging rate. We first calculate the so-called polygenic risk score (PRS) by following a well-designed algorithm for the selection of the significant single nucleotide polymorphisms (SNPs) and subsequently considering a weighted sum of those significant SNPs. Next, we construct a new mortality model, which allows the aging rate to depend on the PRS. Our statistical analysis is based on a rich dataset from the Health and Retirement Study.

Suggested Citation

  • Effraimidis, Georgios & Levine, Morgan & Crimmins, Eileen, 2016. "Measuring the Effect of the Polygenic Risk Score on the Aging Rate," DaCHE discussion papers 2016:7, University of Southern Denmark, Dache - Danish Centre for Health Economics.
    • Handle: RePEc:hhs:sduhec:2016_007
    as

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    File URL: http://www.sdu.dk/-/media/files/om_sdu/centre/cohere/working+papers/2016/wp-7_2016.pdf?la=en
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    References listed on IDEAS

    as
    1. Frank Dudbridge, 2013. "Power and Predictive Accuracy of Polygenic Risk Scores," PLOS Genetics, Public Library of Science, vol. 9(3), pages 1-17, March.
    2. James Vaupel & Kenneth Manton & Eric Stallard, 1979. "The impact of heterogeneity in individual frailty on the dynamics of mortality," Demography, Springer;Population Association of America (PAA), vol. 16(3), pages 439-454, August.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Aging rate; Genome-wide association study; Mortality rate; Polygenic risk score;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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