Specificity, length and luck drive gene rankings in association studies
Jeffrey P. Spence, Hakhamanesh Mostafavi, Mineto Ota, Nikhil Milind, Tamara Gjorgjieva, Courtney J. Smith, Yuval B. Simons, Guy Sella, Jonathan K. Pritchard
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.