Adjusting for common variant polygenic scores improves yield in rare variant association analyses - Jurgens, Sean J.; Pirruccello, James P.; Choi, Seung Hoan; Morrill, Valerie N.; Chaffin, Mark; Lubitz, Steven A.; Lunetta, Kathryn L.; Ellinor, Patrick T. (Nature genetics, 2023)
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. Adjusting for common variant polygenic scores improves yield in gene-based rare variant association tests for quantitative traits, particularly when using sparse mixed models or simple linear models as an alternative to dense mixed-model approaches.