Communications BiologyGenetic & Genomic MedicinePeer-reviewed journal article
Genome-wide association analysis of composite sleep health scores in 413,904 individuals
Matthew O. GoodmaniD, Tariq O. FaquihiD, Valentina PaziD, Pavithra NagarajaniD, Jacqueline M. LaneiD, Brian Spitzer, Matthew MaheriD, Joon ChungiD, Brian E. CadeiD, Shaun PurcelliD, Xiaofeng ZhuiD, Raymond NoordamiD, Andrew J. K. PhillipsiD, Simon David KyleiD, Kai SpiegelhalderiD, Michael N. WeedoniD, Debbie A. LawloriD, Jerome I. RotteriD, Kent D. TayloriD, Carmen R. IsasiiD, Tamar SoferiD, Hassan S. DashtiiD, Martin K. RutteriD, Susan S RedlineiD, Richa SaxenaiD, Heming WangiD
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, and together may provide a more complete picture of sleep health, while also 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 to behavioral, psychological, and cardiometabolic traits.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 18
- FWCI
- 16.76
- Field percentile
- top 1%
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