Communications Biology (Jan 2025)

Genome-wide association analysis of composite sleep health scores in 413,904 individuals

  • Matthew O. Goodman,
  • Tariq Faquih,
  • Valentina Paz,
  • Pavithra Nagarajan,
  • Jacqueline M. Lane,
  • Brian Spitzer,
  • Matthew Maher,
  • Joon Chung,
  • Brian E. Cade,
  • Shaun M. Purcell,
  • Xiaofeng Zhu,
  • Raymond Noordam,
  • Andrew J. K. Phillips,
  • Simon D. Kyle,
  • Kai Spiegelhalder,
  • Michael N. Weedon,
  • Deborah A. Lawlor,
  • Jerome I. Rotter,
  • Kent D. Taylor,
  • Carmen R. Isasi,
  • Tamar Sofer,
  • Hassan S. Dashti,
  • Martin K. Rutter,
  • Susan Redline,
  • Richa Saxena,
  • Heming Wang

DOI
https://doi.org/10.1038/s42003-025-07514-0
Journal volume & issue
Vol. 8, no. 1
pp. 1 – 15

Abstract

Read online

Abstract Recent genome-wide association studies (GWASs) of several individual sleep traits have identified hundreds of genetic loci, suggesting diverse mechanisms. Moreover, sleep traits are moderately correlated, so together may provide a more complete picture of sleep health, while illuminating distinct domains. Here we construct novel sleep health scores (SHSs) incorporating five core self-report measures: sleep duration, insomnia symptoms, chronotype, snoring, and daytime sleepiness, using additive (SHS-ADD) and five principal components-based (SHS-PCs) approaches. GWASs of these six SHSs identify 28 significant novel loci adjusting for multiple testing on six traits (p < 8.3e-9), along with 341 previously reported loci (p < 5e-08). The heritability of the first three SHS-PCs equals or exceeds that of SHS-ADD (SNP-h2 = 0.094), while revealing sleep-domain-specific genetic discoveries. Significant loci enrich in multiple brain tissues and in metabolic and neuronal pathways. Post-GWAS analyses uncover novel genetic mechanisms underlying sleep health and reveal connections (including potential causal links) to behavioral, psychological, and cardiometabolic traits.