Specificity, length and luck drive gene rankings in association studies

Abstract

Abstract Standard genome-wide association studies (GWAS) and rare variant burden tests are essential tools for identifying trait-relevant genes 1 . Although these methods are conceptually similar, by analysing association studies of 209 quantitative traits in the UK Biobank 2–4 , we show that they systematically prioritize different genes. This raises the question of how genes should ideally be prioritized. We propose two prioritization criteria: (1) trait importance — how much a gene quantitatively affects a trait; and (2) trait specificity — the importance of a gene for the trait under study relative to its importance across all traits. We find that GWAS prioritize genes near trait-specific variants, whereas burden tests prioritize trait-specific genes. Because non-coding variants can be context specific, GWAS can prioritize highly pleiotropic genes, whereas burden tests generally cannot. Both study designs are also affected by distinct trait-irrelevant factors, complicating their interpretation. Our results illustrate that burden tests and GWAS reveal different aspects of trait biology and suggest ways to improve their interpretation and usage.