Nature CommunicationsGenomicsPeer-reviewed journal article
Genome-wide association analysis of excessive daytime sleepiness identifies 42 loci that suggest phenotypic subgroups
Heming WangiD, Jacqueline M. LaneiD, Samuel E. JonesiD, Hassan S. DashtiiD, Hanna Maria OllilaiD, Andrew R. WoodiD, Vincent T. van HeesiD, Ben Michael BrumptoniD, Bendik Slagsvold WinsvoldiD, Katri KantojärviiD, Teemu PalviaineniD, Brian E. CadeiD, Tamar SoferiD, Yanwei SongiD, Krunal Patel, Simon George AndersoniD, David A. BechtoldiD, Jack BowdeniD, Richard EmsleyiD, Simon David KyleiD, Max A. LittleiD, Andrew S. I. LoudoniD, Frank A. J. L. ScheeriD, Shaun PurcelliD, Rebecca Claire RichmondiD, , Richa SaxenaiD
Abstract
Excessive daytime sleepiness (EDS) affects 10-20% of the population and is associated with substantial functional deficits. We identified 42 loci for self-reported EDS in GWAS of 452,071 individuals from the UK Biobank, with enrichment for genes expressed in brain tissues and in neuronal transmission pathways. We confirmed the aggregate effect of a genetic risk score of 42 SNPs on EDS in independent Scandinavian cohorts and on other sleep disorders (restless leg syndrome, insomnia) and sleep traits (duration, chronotype, accelerometer-derived sleep efficiency and daytime naps or inactivity). Strong genetic correlations were also seen with obesity, coronary heart disease, psychiatric diseases, cognitive traits and reproductive ageing. EDS variants clustered into two predominant composite phenotypes - sleep propensity and sleep fragmentation - with the former showing stronger evidence for enriched expression in central nervous system tissues, suggesting two unique mechanistic pathways. Mendelian randomization analysis indicated that higher BMI is causally associated with EDS risk, but EDS does not appear to causally influence BMI.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 238
- FWCI
- 3.40
- Field percentile
- top 6%
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