Genetic studies of accelerometer-based sleep measures yield new insights into human sleep behaviour

Samuel E. Jones, Vincent T. van Hees, Diego R. Mazzotti, Pedro Marques-Vidal, S. verine Sabia, Ashley van der Spek, Hassan S. Dashti, Jorgen Engmann, Desana Kocevska, Jessica Tyrrell, Robin N. Beaumont, Melvyn Hillsdon, Katherine S. Ruth, Marcus A. Tuke, Hanieh Yaghootkar, Seth A. Sharp, Yingjie Ji, Jamie W. Harrison, Rachel M. Freathy, Anna MurrayAnnemarie I. Luik, Najaf Amin, Jacqueline M. Lane, Richa Saxena, Martin K. Rutter, Henning Tiemeier, Zoltán Kutalik, Meena Kumari, Timothy M. Frayling, Michael N. Weedon, Philip R. Gehrman, Andrew R. Wood

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Sleep is an essential human function but its regulation is poorly understood. Using accelerometer data from 85,670 UK Biobank participants, we perform a genome-wide association study of 8 derived sleep traits representing sleep quality, quantity and timing, and validate our findings in 5,819 individuals. We identify 47 genetic associations at P < 5 × 10 −8 , of which 20 reach a stricter threshold of P < 8 × 10 −10 . These include 26 novel associations with measures of sleep quality and 10 with nocturnal sleep duration. The majority of identified variants associate with a single sleep trait, except for variants previously associated with restless legs syndrome. For sleep duration we identify a missense variant (p.Tyr727Cys) in PDE11A as the likely causal variant. As a group, sleep quality loci are enriched for serotonin processing genes. Although accelerometer-derived measures of sleep are imperfect and may be affected by restless legs syndrome, these findings provide new biological insights into sleep compared to previous efforts based on self-report sleep measures.
Original languageEnglish
Article number1585
JournalNature Communications
Volume10
Issue number1
DOIs
Publication statusPublished - 1 Dec 2019

Cite this