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Genome-wide association analysis of insomnia complaints identifies risk genes and genetic overlap with psychiatric and metabolic traits

Abstract

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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Figure 1: Manhattan plots showing SNP and gene associations with insomnia complaints.
Figure 2: Comparison of association results for insomnia complaints in males and females.
Figure 3: Protein–protein interaction subnetworks identified by the heat diffusion algorithm HotNet2.
Figure 4: Genetic and phenotypic overlap between insomnia complaints and other traits and disorders.

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Acknowledgements

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. (bergerk@uni-muenster.de). Acknowledgments for data contributed by other consortia that were used for secondary analyses are presented in the Supplementary Note.

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Contributions

D.P. and E.J.W.V.S. conceived the study. A.R.H. and D.P. performed the analyses. T.F.B., K.D., B.H.W.t.L, R.W. and E.J.W.V.S. recruited participants from the NSR and collected and analyzed data for phenotypic validation. C.A.d.L., S. Sniekers, K.W. and E.T. performed secondary analyses. S. Stringer prepared the UK Biobank data for analyses and wrote a pipeline to facilitate efficient data processing. G.T. and I.J. performed the deCODE analyses. K.O. performed the COR and DHS analyses. H.S., T.G., K.B., B.S., J. Wellmann, J. Winkelmann, K.S., K.O. and E.J.W.V.S. contributed data analyzed in this study. A.R.H., K.O., E.J.W.V.S. and D.P. wrote the paper. All authors discussed the results and commented on the paper.

Corresponding author

Correspondence to Danielle Posthuma.

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Competing interests

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 information

Supplementary Text and Figures

Supplementary Figures 1–18, Supplementary Tables 1–3, 5, 7, 8, 10–30, 33 and 34, and Supplementary Note (PDF 5221 kb)

Supplementary Table 4

Functional annotations of the SNPs and SNPs in LD that are associated with insomnia complaints. (XLSX 25 kb)

Supplementary Table 6

Genome-wide gene associations with insomnia complaints. (XLSX 1798 kb)

Supplementary Table 9

Tissue expression of the genes identified by the insomniacomplaints GWAS and GWGAS. (XLSX 30 kb)

Supplementary Table 31

Pathway analysis of canonical pathways and GO pathways. (XLSX 169 kb)

Supplementary Table 32

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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