Persistent insomnia is among the most frequent complaints in general practice. To identify genetic factors for insomnia complaints, we performed a genome-wide association study (GWAS) and a genome-wide gene-based association study (GWGAS) in 113,006 individuals. We identify three loci and seven genes associated with insomnia complaints, with the associations for one locus and five genes supported by joint analysis with an independent sample (n = 7,565). Our top association (MEIS1, P < 5 × 10−8) has previously been implicated in restless legs syndrome (RLS). Additional analyses favor the hypothesis that MEIS1 exhibits pleiotropy for insomnia and RLS and show that the observed association with insomnia complaints cannot be explained only by the presence of an RLS subgroup within the cases. Sex-specific analyses suggest that there are different genetic architectures between the sexes in addition to shared genetic factors. We show substantial positive genetic correlation of insomnia complaints with internalizing personality traits and metabolic traits and negative correlation with subjective well-being and educational attainment. These findings provide new insight into the genetic architecture of insomnia.
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Wittchen, H.U. et al. The size and burden of mental disorders and other disorders of the brain in Europe 2010. Eur. Neuropsychopharmacol. 21, 655–679 (2011).
Zhang, B. & Wing, Y.-K. Sex differences in insomnia: a meta-analysis. Sleep 29, 85–93 (2006).
Morin, C.M. et al. Insomnia disorder. Nat. Rev. Dis. Primers 1, 15026 (2015).
Baglioni, C. et al. Insomnia as a predictor of depression: a meta-analytic evaluation of longitudinal epidemiological studies. J. Affect. Disord. 135, 10–19 (2011).
Palagini, L. et al. Sleep loss and hypertension: a systematic review. Curr. Pharm. Des. 19, 2409–2419 (2013).
Mallon, L., Broman, J.E. & Hetta, J. Sleep complaints predict coronary artery disease mortality in males: a 12-year follow-up study of a middle-aged Swedish population. J. Intern. Med. 251, 207–216 (2002).
Nilsson, P.M., Nilsson, J.Å., Hedblad, B. & Berglund, G. Sleep disturbance in association with elevated pulse rate for prediction of mortality—consequences of mental strain? J. Intern. Med. 250, 521–529 (2001).
Schwartz, S.W. et al. Are sleep complaints an independent risk factor for myocardial infarction? Ann. Epidemiol. 8, 384–392 (1998).
Clark, A., Lange, T., Hallqvist, J., Jennum, P. & Rod, N.H. Sleep impairment and prognosis of acute myocardial infarction: a prospective cohort study. Sleep 37, 851–858 (2014).
Cappuccio, F.P., D'Elia, L., Strazzullo, P. & Miller, M.A. Quantity and quality of sleep and incidence of type 2 diabetes: a systematic review and meta-analysis. Diabetes Care 33, 414–420 (2010).
Hargens, T.A., Kaleth, A.S., Edwards, E.S. & Butner, K.L. Association between sleep disorders, obesity, and exercise: a review. Nat. Sci. Sleep 5, 27–35 (2013).
Lind, M.J., Aggen, S.H., Kirkpatrick, R.M., Kendler, K.S. & Amstadter, A.B. A longitudinal twin study of insomnia symptoms in adults. Sleep 38, 1423–1430 (2015).
Bootzin, R.R. & Epstein, D.R. Understanding and treating insomnia. Annu. Rev. Clin. Psychol. 7, 435–458 (2011).
Bettolo, A. L'insonnia e sua importanza clinica: le sue cause predisponenti e determinanti, i suoi caratteri nelle diverse malattie, Ia sua importanza prognostica ed il suo trattamento generale e speciale. Studium 21, 54–65 (1931).
Morin, C.M. et al. Cognitive behavioral therapy, singly and combined with medication, for persistent insomnia: a randomized controlled trial. J. Am. Med. Assoc. 301, 2005–2015 (2009).
Harvey, A.G. & Tang, N.K.Y. Cognitive behaviour therapy for primary insomnia: can we rest yet? Sleep Med. Rev. 7, 237–262 (2003).
Morin, C.M. et al. The natural history of insomnia: a population-based 3-year longitudinal study. Arch. Intern. Med. 169, 447–453 (2009).
Bastien, C.H. & Morin, C.M. Familial incidence of insomnia. J. Sleep Res. 9, 49–54 (2000).
Dauvilliers, Y. et al. Family studies in insomnia. J. Psychosom. Res. 58, 271–278 (2005).
Beaulieu-Bonneau, S., LeBlanc, M., Mérette, C., Dauvilliers, Y. & Morin, C.M. Family history of insomnia in a population-based sample. Sleep 30, 1739–1745 (2007).
Wing, Y.K. et al. Familial aggregation and heritability of insomnia in a community-based study. Sleep Med. 13, 985–990 (2012).
Byrne, E.M. et al. A genome-wide association study of sleep habits and insomnia. Am. J. Med. Genet. B. Neuropsychiatr. Genet. 162B, 439–451 (2013).
Amin, N. et al. Genetic variants in RBFOX3 are associated with sleep latency. Eur. J. Hum. Genet. 24, 1488–1495 (2016).
Lane, J.M. 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).
Lane, J.M. et al. Genome-wide association analysis identifies novel loci for chronotype in 100,420 individuals from the UK Biobank. Nat. Commun. 7, 10889 (2016).
Jones, S.E. et al. Genome-wide association analyses in 128,266 individuals identifies new morningness and sleep duration loci. PLoS Genet. 12, e1006125 (2016).
Vgontzas, A.N. et al. Persistent insomnia: the role of objective short sleep duration and mental health. Sleep 35, 61–68 (2012).
Sudlow, C. et al. UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015).
Benjamins, J.S. et al. Insomnia heterogeneity: characteristics to consider for data-driven multivariate subtyping. Sleep Med. Rev. http://dx.doi.org/10.1016/j.smrv.2016.10.005 (2016).
Morphy, H., Dunn, K.M., Lewis, M., Boardman, H.F. & Croft, P.R. Epidemiology of insomnia: a longitudinal study in a UK population. Sleep 30, 274–280 (2007).
Paparrigopoulos, T. et al. Insomnia and its correlates in a representative sample of the Greek population. BMC Public Health 10, 531 (2010).
Cho, Y.W. et al. Epidemiology of insomnia in Korean adults: prevalence and associated factors. J. Clin. Neurol. 5, 20–23 (2009).
Bulik-Sullivan, B.K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).
Loh, P.-R. et al. Contrasting genetic architectures of schizophrenia and other complex diseases using fast variance-components analysis. Nat. Genet. 47, 1385–1392 (2015).
de Leeuw, C.A., Mooij, J.M., Heskes, T. & Posthuma, D. MAGMA: generalized gene-set analysis of GWAS data. PLOS Comput. Biol. 11, e1004219 (2015).
Cai, M. et al. Dual actions of Meis1 inhibit erythroid progenitor development and sustain general hematopoietic cell proliferation. Blood 120, 335–346 (2012).
GTEx Consortium. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348, 648–660 (2015).
Skol, A.D., Scott, L.J., Abecasis, G.R. & Boehnke, M. Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies. Nat. Genet. 38, 209–213 (2006).
Winkelmann, J. et al. Genome-wide association study of restless legs syndrome identifies common variants in three genomic regions. Nat. Genet. 39, 1000–1006 (2007).
Winkelmann, J. et al. Genome-wide association study identifies novel restless legs syndrome susceptibility loci on 2p14 and 16q12.1. PLoS Genet. 7, e1002171 (2011).
Schulte, E.C. et al. Targeted resequencing and systematic in vivo functional testing identifies rare variants in MEIS1 as significant contributors to restless legs syndrome. Am. J. Hum. Genet. 95, 85–95 (2014).
Xiong, L. et al. MEIS1 intronic risk haplotype associated with restless legs syndrome affects its mRNA and protein expression levels. Hum. Mol. Genet. 18, 1065–1074 (2009).
Allen, R.P., Barker, P.B., Horská, A. & Earley, C.J. Thalamic glutamate/glutamine in restless legs syndrome: increased and related to disturbed sleep. Neurology 80, 2028–2034 (2013).
Spiegelhalder, K. et al. Magnetic resonance spectroscopy in patients with insomnia: a repeated measurement study. PLoS One 11, e0156771 (2016).
Han, B. et al. A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases. Nat. Genet. 48, 803–810 (2016).
Ohayon, M.M., O'Hara, R. & Vitiello, M.V. Epidemiology of restless legs syndrome: a synthesis of the literature. Sleep Med. Rev. 16, 283–295 (2012).
Yang, J. et al. Genome-wide genetic homogeneity between sexes and populations for human height and body mass index. Hum. Mol. Genet. 24, 7445–7449 (2015).
Tucci, V. Genomic imprinting: a new epigenetic perspective of sleep regulation. PLoS Genet. 12, e1006004 (2016).
Lassi, G. et al. Loss of Gnas imprinting differentially affects REM/NREM sleep and cognition in mice. PLoS Genet. 8, e1002706 (2012).
Dijk, D.-J. Sleep of aging women and men: back to basics. Sleep 29, 12–13 (2006).
Ursin, R., Bjorvatn, B. & Holsten, F. Sleep duration, subjective sleep need, and sleep habits of 40- to 45-year-olds in the Hordaland Health Study. Sleep 28, 1260–1269 (2005).
Redline, S. et al. The effects of age, sex, ethnicity, and sleep-disordered breathing on sleep architecture. Arch. Intern. Med. 164, 406–418 (2004).
Buysse, D.J. et al. EEG spectral analysis in primary insomnia: NREM period effects and sex differences. Sleep 31, 1673–1682 (2008).
Leiserson, M.D.M. et al. Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes. Nat. Genet. 47, 106–114 (2015).
Bonnet, M.H. & Arand, D.L. 24-hour metabolic rate in insomniacs and matched normal sleepers. Sleep 18, 581–588 (1995).
Feige, B. et al. The microstructure of sleep in primary insomnia: an overview and extension. Int. J. Psychophysiol. 89, 171–180 (2013).
Allen, N.E., Sudlow, C., Peakman, T. & Collins, R. UK Biobank data: come and get it. Sci. Transl. Med. 6, 224ed4 (2014).
Visscher, P.M. Sizing up human height variation. Nat. Genet. 40, 489–490 (2008).
Marchini, J., Howie, B., Myers, S., McVean, G. & Donnelly, P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat. Genet. 39, 906–913 (2007).
Gudbjartsson, D.F. et al. Large-scale whole-genome sequencing of the Icelandic population. Nat. Genet. 47, 435–444 (2015).
Kong, A. et al. Detection of sharing by descent, long-range phasing and haplotype imputation. Nat. Genet. 40, 1068–1075 (2008).
Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).
Kichaev, G. et al. Integrating functional data to prioritize causal variants in statistical fine-mapping studies. PLoS Genet. 10, e1004722 (2014).
Willer, C.J., Li, Y. & Abecasis, G.R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).
Razick, S., Magklaras, G. & Donaldson, I.M. iRefIndex: a consolidated protein interaction database with provenance. BMC Bioinformatics 9, 405 (2008).
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102, 15545–15550 (2005).
This work was funded by the Netherlands Organization for Scientific Research (NWO Brain & Cognition 433-09-228, NWO VICI 453-14-005 and 453-07-001, 645-000-003) and by the European Research Council (ERC-ADG-2014-671084 INSOMNIA). The analyses were carried out on the Genetic Cluster Computer, which is financed by the Netherlands Scientific Organization (NWO; 480-05-003), by VU University (Amsterdam, the Netherlands) and by the Dutch Brain Foundation and is hosted by the Dutch National Computing and Networking Services (SurfSARA). This research has been conducted using the UK Biobank Resource under application number 16406. We thank the participants and researchers who contributed and collected the data. We thank the participants of the Netherlands Sleep Registry for providing extensive phenotypic data. We thank the participants who provided samples and data for the Icelandic study and our valued colleagues who contributed to data collection and the phenotypic characterization of clinical samples, genotyping and analysis of genome sequence data. We also thank the EU-RLS consortium and the Cooperative Research in the Region of Augsburg (KORA) study for providing the RLS summary statistics. KORA was initiated and is financed by the Helmholtz Zentrum München, which is funded by the German Federal Ministry of Education and Research and by the state of Bavaria. The collection of sociodemographic and clinical data in the DHS was supported by the German Migraine & Headache Society (DMKG) and by unrestricted grants of equal share from Almirall, AstraZeneca, Berlin Chemie, Boehringer, Boots Health Care, GlaxoSmithKline, Janssen Cilag, McNeil Pharma, MSD Sharp & Dohme, and Pfizer to the University of Münster. Blood collection in the DHS was done through funds from the Institute of Epidemiology and Social Medicine at the University of Münster. Genotyping for the Human Omni chip was supported by the German Ministry of Education and Research (BMBF; grant 01ER0816). Researchers interested in using DHS data are required to sign and follow the terms of a cooperation agreement that includes a number of clauses designed to ensure protection of privacy and compliance with relevant laws. The COR study was supported by unrestricted grants to the University of Münster from the German Restless Legs Patient Organisation (RLS Deutsche Restless Legs Vereinigung), the Swiss RLS Patient Association (Schweizerische Restless Legs Selbsthilfegruppe) and a consortium formed by Boeringer Ingelheim Pharma, Mundipharma Research, Neurobiotec, Roche Pharma, UCB (Germany + Switzerland) and Vifor Pharma. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Researchers interested in using COR data are required to sign and follow the terms of a cooperation agreement that includes a number of clauses designed to ensure protection of privacy and compliance with relevant laws. For further information on DHS and COR, contact K.B. (email@example.com). Acknowledgments for data contributed by other consortia that were used for secondary analyses are presented in the Supplementary Note.
I.J., G.T., H.S. and K.S. are affiliated with deCODE Genetics/Amgen, Inc., and declare competing financial interests as employees. The other authors declare no competing financial interests.
Supplementary Figures 1–18, Supplementary Tables 1–3, 5, 7, 8, 10–30, 33 and 34, and Supplementary Note (PDF 5221 kb)
Functional annotations of the SNPs and SNPs in LD that are associated with insomnia complaints. (XLSX 25 kb)
Genome-wide gene associations with insomnia complaints. (XLSX 1798 kb)
Tissue expression of the genes identified by the insomniacomplaints GWAS and GWGAS. (XLSX 30 kb)
Pathway analysis of canonical pathways and GO pathways. (XLSX 169 kb)
Enrichment analysis of HotNet2 subnetworks. (XLSX 30 kb)
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Hammerschlag, A., Stringer, S., de Leeuw, C. et al. Genome-wide association analysis of insomnia complaints identifies risk genes and genetic overlap with psychiatric and metabolic traits. Nat Genet 49, 1584–1592 (2017). https://doi.org/10.1038/ng.3888
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