Integration of rare large-effect expression variants improves polygenic risk prediction

Craig Smail, Ferraro Nm, Durrant Mg, Rao As,Matthew Aguirre,Li X, Gloudemans Mj,Themistocles L. Assimes,Charles Kooperberg,Reiner Ap, Hui Qian,Jie Huang,O’Donnell Cj, Sun Yv, Rivas Ma, Montgomery Sb

medRxiv (Cold Spring Harbor Laboratory)(2020)

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Abstract
Summary Polygenic risk scores (PRS) aim to quantify the contribution of multiple genetic loci to an individual’s likelihood of a complex trait or disease. However, existing PRS estimate genetic liability using common genetic variants, excluding the impact of rare variants. We identified rare, large-effect variants in individuals with outlier gene expression from the GTEx project and then assessed their impact on PRS predictions in the UK Biobank (UKB). We observed large deviations from the PRS-predicted phenotypes for carriers of multiple outlier rare variants; for example, individuals classified as “low-risk” but in the top 1% of outlier rare variant burden had a 6-fold higher rate of severe obesity. We replicated these findings using data from the NHLBI Trans-Omics for Precision Medicine (TOPMed) biobank and the Million Veteran Program, and demonstrated that PRS across multiple traits will significantly benefit from the inclusion of rare genetic variants.
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Key words
risk,prediction,large-effect
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