Identifying individuals with high risk of Alzheimer’s disease using polygenic risk scores

Ganna Leonenko, Emily Baker, Joshua Stevenson-Hoare, Annerieke Sierksma, Mark Fiers, Julie Williams, Bart Strooper and Valentina Escott-Price ()
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Ganna Leonenko: Cardiff University
Emily Baker: Cardiff University
Joshua Stevenson-Hoare: Cardiff University
Annerieke Sierksma: VIB Center for Brain & Disease Research
Mark Fiers: VIB Center for Brain & Disease Research
Julie Williams: Cardiff University
Bart Strooper: VIB Center for Brain & Disease Research
Valentina Escott-Price: Cardiff University

Nature Communications, 2021, vol. 12, issue 1, 1-10

Abstract: Abstract Polygenic Risk Scores (PRS) for AD offer unique possibilities for reliable identification of individuals at high and low risk of AD. However, there is little agreement in the field as to what approach should be used for genetic risk score calculations, how to model the effect of APOE, what the optimal p-value threshold (pT) for SNP selection is and how to compare scores between studies and methods. We show that the best prediction accuracy is achieved with a model with two predictors (APOE and PRS excluding APOE region) with pT

Date: 2021
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DOI: 10.1038/s41467-021-24082-z

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