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Genome-wide association analyses of sleep disturbance traits identify new loci and highlight shared genetics with neuropsychiatric and metabolic traits

Abstract

Chronic sleep disturbances, associated with cardiometabolic diseases, psychiatric disorders and all-cause mortality1,2, affect 25–30% of adults worldwide3. Although environmental factors contribute substantially to self-reported habitual sleep duration and disruption, these traits are heritable4,5,6,7,8,9 and identification of the genes involved should improve understanding of sleep, mechanisms linking sleep to disease and development of new therapies. We report single- and multiple-trait genome-wide association analyses of self-reported sleep duration, insomnia symptoms and excessive daytime sleepiness in the UK Biobank (n = 112,586). We discover loci associated with insomnia symptoms (near MEIS1, TMEM132E, CYCL1 and TGFBI in females and WDR27 in males), excessive daytime sleepiness (near AROPHN1) and a composite sleep trait (near PATJ (INADL) and HCRTR2) and replicate a locus associated with sleep duration (at PAX8). We also observe genetic correlation between longer sleep duration and schizophrenia risk (rg = 0.29, P = 1.90 × 10−13) and between increased levels of excessive daytime sleepiness and increased measures for adiposity traits (body mass index (BMI): rg = 0.20, P = 3.12 × 10−9; waist circumference: rg = 0.20, P = 2.12 × 10−7).

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Figure 1: Sleep traits are phenotypically and genetically correlated.
Figure 2: Regional association plots for genome-wide significant loci.
Figure 3: Partitioning of the genetic architecture of sleep duration, insomnia symptoms and excessive daytime sleepiness across functional annotation categories.
Figure 4: Genetic architectures shared between sleep duration, insomnia symptoms or excessive daytime sleepiness and 20 behavioral and disease traits.

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Acknowledgements

This research has been conducted using the UK Biobank Resource under application number 6818. We would like to thank the participants and researchers from the UK Biobank who contributed or collected data. This work was supported by US NIH grants R01DK107859 (R.S.), R21HL121728 (R.S.), F32DK102323 (J.M.L.), R01HL113338 (J.M.L., S.R. and R.S.), R01DK102696 (R.S. and F.A.J.L.S.), R01DK105072 (R.S. and F.A.J.L.S.), T32HL007567 (J.L.) and HG003054 (X.Z.), the University of Manchester (Research Infrastructure Fund), the Wellcome Trust (salary support for D.W.R. and A.L.) and UK Medical Research Council MC_UU_12013/5 (D.A.L.). Data on glycemic traits have been contributed by MAGIC investigators and were downloaded from http://www.magicinvestigators.org/. Data on coronary artery disease and myocardial infarction have been contributed by CARDIoGRAMplusC4D investigators and were downloaded from http://www.cardiogramplusc4d.org/. We thank the International Genomics of Alzheimer's Project (IGAP) for providing summary results data for these analyses.

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J.M.L., M.K.R. and R.S. designed the study. J.M.L., J.L., I.V. and R.S. performed genetic analyses. J.M.L. and R.S. wrote the manuscript, and all co-authors helped interpret data and reviewed and edited the manuscript, before approving its submission. R.S. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

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Correspondence to Richa Saxena.

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Lane, J., Liang, J., Vlasac, I. et al. Genome-wide association analyses of sleep disturbance traits identify new loci and highlight shared genetics with neuropsychiatric and metabolic traits. Nat Genet 49, 274–281 (2017). https://doi.org/10.1038/ng.3749

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