<p>Standard genome-wide association studies (GWAS) and rare variant burden tests are essential tools for identifying trait-relevant genes<sup><CitationRef CitationID="CR1">1</CitationRef></sup>. Although these methods are conceptually similar, by analysing association studies of 209 quantitative traits in the UK Biobank<sup><CitationRef AdditionalCitationIDS="CR3" CitationID="CR2">2</CitationRef>–<CitationRef CitationID="CR4">4</CitationRef></sup>, 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.</p>

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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

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 Biobank24, 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.