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Open AccessArticle

Evaluating the Potential of Younger Cases and Older Controls Cohorts to Improve Discovery Power in Genome-Wide Association Studies of Late-Onset Diseases

1
Centre for Computational Evolution, University of Auckland, Auckland 1010, New Zealand
2
Department of Computer Science, University of Auckland, Auckland 1010, New Zealand
J. Pers. Med. 2019, 9(3), 38; https://doi.org/10.3390/jpm9030038
Received: 14 June 2019 / Revised: 15 July 2019 / Accepted: 16 July 2019 / Published: 22 July 2019
For more than a decade, genome-wide association studies have been making steady progress in discovering the causal gene variants that contribute to late-onset human diseases. Polygenic late-onset diseases in an aging population display a risk allele frequency decrease at older ages, caused by individuals with higher polygenic risk scores becoming ill proportionately earlier and bringing about a change in the distribution of risk alleles between new cases and the as-yet-unaffected population. This phenomenon is most prominent for diseases characterized by high cumulative incidence and high heritability, examples of which include Alzheimer’s disease, coronary artery disease, cerebral stroke, and type 2 diabetes, while for late-onset diseases with relatively lower prevalence and heritability, exemplified by cancers, the effect is significantly lower. In this research, computer simulations have demonstrated that genome-wide association studies of late-onset polygenic diseases showing high cumulative incidence together with high initial heritability will benefit from using the youngest possible age-matched cohorts. Moreover, rather than using age-matched cohorts, study cohorts combining the youngest possible cases with the oldest possible controls may significantly improve the discovery power of genome-wide association studies. View Full-Text
Keywords: GWAS; genome-wide association studies; genetics; polygenic risk score; heritability; late-onset disease; simulation; gene variant; SNP GWAS; genome-wide association studies; genetics; polygenic risk score; heritability; late-onset disease; simulation; gene variant; SNP
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Oliynyk, R.T. Evaluating the Potential of Younger Cases and Older Controls Cohorts to Improve Discovery Power in Genome-Wide Association Studies of Late-Onset Diseases. J. Pers. Med. 2019, 9, 38.

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