Phenotype Refinement Influences GWAS-Implicated Variant Effect Sizes for Insomnia.

Abstract

How phenotypes are measured, especially when relying on subjective reports, is an impediment to the utility of genome-wide association studies (GWAS). This is a common problem in GWAS for sleep traits, as many sleep disturbances appear subjectively similar despite having distinct underlying pathophysiology. Phenotype refinement is, therefore, necessary to improve our understanding of complex trait biology. Here, we utilise expanded questionnaire data collected from ~180,000 participants in the UK Biobank to help further distinguish insomnia from restless legs syndrome (RLS) from subjective reports. We demonstrate prior GWAS efforts for insomnia likely mischaracterised participants using a single-question approach. Through statistical models, we examine two of the most significant GWAS signals for insomnia, namely at the MEIS1 and BTBD9 loci, finding their effects are largely or completely, driven by their effects on RLS. Collectively, our results underscore the necessity of improving phenotype classification and highlight the utility of newly released UK Biobank data for sleep research.