Abstract
Time to fall asleep (sleep latency) is a major determinant of sleep quality. Chronic, long sleep latency is a major characteristic of sleep-onset insomnia and/or delayed sleep phase syndrome. In this study we aimed to discover common polymorphisms that contribute to the genetics of sleep latency. We performed a meta-analysis of genome-wide association studies (GWAS) including 2 572 737 single nucleotide polymorphisms (SNPs) established in seven European cohorts including 4242 individuals. We found a cluster of three highly correlated variants (rs9900428, rs9907432 and rs7211029) in the RNA-binding protein fox-1 homolog 3 gene (RBFOX3) associated with sleep latency (P-values=5.77 × 10−08, 6.59 × 10−08 and 9.17 × 10−08). These SNPs were replicated in up to 12 independent populations including 30 377 individuals (P-values=1.5 × 10−02, 7.0 × 10−03 and 2.5 × 10−03; combined meta-analysis P-values=5.5 × 10−07, 5.4 × 10−07 and 1.0 × 10−07). A functional prediction of RBFOX3 based on co-expression with other genes shows that this gene is predominantly expressed in brain (P-value=1.4 × 10−316) and the central nervous system (P-value=7.5 × 10−321). The predicted function of RBFOX3 based on co-expression analysis with other genes shows that this gene is significantly involved in the release cycle of neurotransmitters including gamma-aminobutyric acid and various monoamines (P-values<2.9 × 10−11) that are crucial in triggering the onset of sleep. To conclude, in this first large-scale GWAS of sleep latency we report a novel association of variants in RBFOX3 gene. Further, a functional prediction of RBFOX3 supports the involvement of RBFOX3 with sleep latency.
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Acknowledgements
We thank all the participants and staff of all the studies for their co-operation and contribution. We are grateful to all participants and their relatives, general practitioners and neurologists for their contributions and to P Veraart for her help in genealogy, Jeannette Vergeer for the supervision of the laboratory work and P Snijders for his help in data collection for the ERF study. We thank Pascal Arp, Mila Jhamai, Marijn Verkerk, Lizbeth Herrera and Marjolein Peters for their help in creating the GWAS database, and Karol Estrada and Maksim V Struchalin for their support in creation and analysis of imputed data for the Rotterdam Study. We are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. We thank Dr Fernando Rivadeneira, Dr Tobias A Knoch, Anis Abuseiris, Luc V de Zeeuw and Rob de Graaf for their help in creating GRIMP, and BigGRID, MediGRID and Services@MediGRID/D-Grid. We acknowledge the invaluable contributions of the recruitment team from the Croatian Centre for Global Health, University of Split, the administrative teams in Croatia and Edinburgh and the people of Split. Our work was supported by the FP6 programme EUCLOCK, the Dutch Science Foundation (the NWO), the Hersenstichting Nederland, the Rosalind Franklin Fellowships of the University of Groningen, targeted Financing from the Estonian Government, the European Union through the European Regional Development Fund in the frame of Centre of Excellence in Genomics, FP7 Projects ECOGENE, BBMRI, ENGAGE and OPENGENE, the Geestkracht programme of the Dutch Scientific Organization (ZON-MW) and matching funds from participating universities and mental health care organizations, the Genetic Association Information Network (GAIN) of the Foundation for the US National Institutes of Health, the EUROSPAN (European Special Populations Research Network) through the European Commission FP6 STRP grant, the Chief Scientist Office of the Scottish Government, the Royal Society, the Medical Research Council, Erasmus University, Erasmus MC, the Centre for Medical Systems Biology (CMSB1 and CMSB2) and the Netherlands Genomics Initiative (NGI) and ALBAN. We acknowledge the High Performance Computing Center of University of Tartu, for space and facilities to conduct part of the EGCUT analysis. We also acknowledge the Netherlands Organization for Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), The Ministry of Education, Culture and Science, the Ministry of Health, Welfare and Sports of the Netherlands, the European Commission (DG XII) and the Municipality of Rotterdam. This study was supported by grants from the Netherlands Organization for Scientific Research (NWO-VENI grant 916.10.135 to LF) and a Horizon Breakthrough grant from the Netherlands Genomics Initiative (grant 92519031 to LF). The research leading to these results has received funding from the European Community’s Health Seventh Framework Programme (FP7/2007–2013) under grant agreement 259867. Study-specific acknowledgments and the ethical statement are provided in the Supplementary text.
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Dr Najaf Amin is supported by the Netherlands Brain Foundation (project number F2013(1)-28). Dr Gregory J Tranah was supported by NIA grant R01AG030474. Dr Henning Tiemeier was supported by the Vidi Grant of ZonMw (the Netherlands Organization for Health Research and Development, 2009-017.106.370). All other authors report no biomedical financial interests or potential conflicts of interest.
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Amin, N., Allebrandt, K., van der Spek, A. et al. Genetic variants in RBFOX3 are associated with sleep latency. Eur J Hum Genet 24, 1488–1495 (2016). https://doi.org/10.1038/ejhg.2016.31
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DOI: https://doi.org/10.1038/ejhg.2016.31
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