Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewed

Genome-wide association analysis of self-reported daytime sleepiness identifies 42 loci that suggest biological subtypes

Heming Wang, Jacqueline M. Lane, Samuel E. Jones, Hassan S. Dashti, Hanna M. Ollila, Andrew R. Wood, Vincent T. van Hees, Ben Brumpton, Bendik S. Winsvold, Katri Kantojärvi, Teemu Palviainen, Brian E. Cade, Tamar Sofer, Yanwei Song, Krunal Patel, Simon Anderson, David A. Bechtold, Jack Bowden, Richard Emsley, Simon D. Kyle, Max A. Little, Andrew Loudon, Frank A. J. L. Scheer, Shaun Purcell, Rebecca C. Richmond, Kai Spiegelhalder, Jessica Tyrrell, Xiaofeng Zhu, Christer Hublin, Jaakko Kaprio, Kati Kristiansson, Sonja Sulkava, Tiina Paunio, Kristian Hveem, Jonas B. Nielsen, Cristen J. Willer, John‐Anker Zwart, Linn Beate Strand, Timothy M. Frayling, David Ray, Debbie A. Lawlor, Martin K. Rutter, Michael N. Weedon, Susan Redline, Richa Saxena

Nature Communications · 2019

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Summary

This genome-wide association study of over 452,000 UK Biobank participants identified 42 genetic loci influencing self-reported daytime sleepiness, with enrichment in brain-expressed genes and neuronal transmission pathways. The study demonstrates that daytime sleepiness variants cluster into two predominant biological subtypes — sleep propensity and sleep fragmentation — and share genetic links with obesity, cardiovascular disease, psychiatric conditions, and cognitive traits. These findings suggest distinct biological mechanisms underlying excessive daytime sleepiness and implicate shared genetic architecture with multiple chronic health conditions.

UK applicability

The findings are directly applicable to UK populations, as the primary analysis used the UK Biobank cohort of 452,071 participants. The identified genetic variants and their associations with sleepiness, obesity, coronary heart disease, and psychiatric conditions may inform UK clinical and public health strategies for identifying high-risk individuals and understanding the biological heterogeneity of sleep disorders.

Key measures

Self-reported daytime sleepiness, genetic risk score (42 SNPs), sleep duration, sleep chronotype, accelerometer-derived sleep efficiency, daytime naps/inactivity, restless legs syndrome, insomnia, obesity, coronary heart disease, psychiatric disease, cognitive traits, reproductive ageing

Outcomes reported

The study identified 42 genetic loci associated with self-reported daytime sleepiness through genome-wide association analysis in 452,071 UK Biobank participants. The findings were validated in independent Scandinavian cohorts and examined for associations with objective sleep measures, other sleep disorders, and cardiometabolic and psychiatric traits.

Theme
Nutrition & health
Subject
Other / interdisciplinary
Study type
Research
Study design
Observational cohort
Source type
Peer-reviewed study
Status
Published
Geography
International
System type
Human clinical
DOI
10.1038/s41467-019-11456-7
Catalogue ID
SNmohdwfqs-dbhagk

Topic tags

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