Specificity, length and luck drive gene rankings in association studies

作者信息Jeffrey P Spence, Hakhamanesh Mostafavi, Mineto Ota, Nikhil Milind, Tamara Gjorgjieva, Courtney J Smith, Yuval B Simons, Guy Sella, Jonathan K Pritchard
PMID41193809
期刊Nature
发布时间2026-01
DOI10.1038/s41586-025-09703-7
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摘要

Standard genome-wide association studies (GWAS) and rare variant burden tests are essential tools for identifying trait-relevant genes1. Although these methods are conceptually similar, by analysing association studies of 209 quantitative traits in the UK Biobank2-4, 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.

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