Last updated:
Author(s):
Sean J. Jurgens, James P. Pirruccello, Seung Hoan Choi, Valerie N. Morrill, Mark Chaffin, Steven A. Lubitz, Kathryn L. Lunetta, Patrick T. Ellinor
Publish date:
23 March 2023
Journal:
Nature Genetics
PubMed ID:
36959364

Abstract

With the emergence of large-scale sequencing data, methods for improving power in rare variant association tests are needed. Here we show that adjusting for common variant polygenic scores improves yield in gene-based rare variant association tests across 65 quantitative traits in the UK Biobank (up to 20% increase at α = 2.6 × 10−6), without marked increases in false-positive rates or genomic inflation. Benefits were seen for various models, with the largest improvements seen for efficient sparse mixed-effects models. Our results illustrate how polygenic score adjustment can efficiently improve power in rare variant association discovery.

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