Adjusting for common variant polygenic scores improves yield in rare variant association analyses

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 alpha = 2.6 x 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.