Genome-Wide Association Study of Circadian Rhythmicity in 71,500 UK Biobank Participants and Polygenic Association with Mood Instability

Amy Ferguson, Laura M Lyall, Joey Ward, Rona J Strawbridge, Breda Cullen, Nicholas Graham, Claire L Niedzwiedz, Keira J A Johnston, Daniel MacKay, Stephany M Biello, Jill P Pell, Jonathan Cavanagh, Andrew M McIntosh, Aiden Doherty, Mark E S Bailey, Donald M Lyall, Cathy A Wyse, Daniel J Smith, Amy Ferguson, Laura M Lyall, Joey Ward, Rona J Strawbridge, Breda Cullen, Nicholas Graham, Claire L Niedzwiedz, Keira J A Johnston, Daniel MacKay, Stephany M Biello, Jill P Pell, Jonathan Cavanagh, Andrew M McIntosh, Aiden Doherty, Mark E S Bailey, Donald M Lyall, Cathy A Wyse, Daniel J Smith

Abstract

Background: Circadian rhythms are fundamental to health and are particularly important for mental wellbeing. Disrupted rhythms of rest and activity are recognised as risk factors for major depressive disorder and bipolar disorder.

Methods: We conducted a genome-wide association study (GWAS) of low relative amplitude (RA), an objective measure of rest-activity cycles derived from the accelerometer data of 71,500 UK Biobank participants. Polygenic risk scores (PRS) for low RA were used to investigate potential associations with psychiatric phenotypes.

Outcomes: Two independent genetic loci were associated with low RA, within genomic regions for Neurofascin (NFASC) and Solute Carrier Family 25 Member 17 (SLC25A17). A secondary GWAS of RA as a continuous measure identified a locus within Meis Homeobox 1 (MEIS1). There were no significant genetic correlations between low RA and any of the psychiatric phenotypes assessed. However, PRS for low RA was significantly associated with mood instability across multiple PRS thresholds (at PRS threshold 0·05: OR = 1·02, 95% CI = 1·01-1·02, p = 9·6 × 10-5), and with major depressive disorder (at PRS threshold 0·1: OR = 1·03, 95% CI = 1·01-1·05, p = 0·025) and neuroticism (at PRS threshold 0·5: Beta = 0·02, 95% CI = 0·007-0·04, p = 0·021).

Interpretation: Overall, our findings contribute new knowledge on the complex genetic architecture of circadian rhythmicity and suggest a putative biological link between disrupted circadian function and mood disorder phenotypes, particularly mood instability, but also major depressive disorder and neuroticism.

Funding: Medical Research Council (MR/K501335/1).

Keywords: Circadian rhythmicity; Gwas; Mood instability; Polygenic risk score; Relative amplitude.

Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Figures

Fig. 1
Fig. 1
SNP Manhattan plot and QQ plot (inset) of low RA GWAS (N = 2700 cases verses N = 68,300 controls). Red line of Manhattan plot represents genome-wide significance (p −8).
Fig. 2
Fig. 2
SNP Manhattan plot and QQ plot (inset) of continuous RA GWAS (N = 77,440). Red line of Manhattan plot represents genome-wide significance (p −8).

References

    1. McClung C.A. Circadian genes, rhythms and the biology of mood disorders. Pharmacol Ther. 2007;114:222–232.
    1. Reppert S.M., Weaver D.R. Molecular analysis of mammalian circadian rhythms. Annu Rev Physiol. 2001;63:647–676.
    1. Merikanto I. Circadian preference towards morningness is associated with lower slow sleep spindle amplitude and intensity in adolescents. Sci Rep. 2017;7:1–12.
    1. Reutrakul S., Knutson K.L. Consequences of circadian disruption on cardiometabolic health. Sleep Med Clin. 2015;10:455–468.
    1. Wulff K., Gatti S., Wettstein J.G., Foster R.G. Sleep and circadian rhythm disruption in psychiatric and neurodegenerative disease. Nat Rev Neurosci. 2010;11:589–599.
    1. Sigurdardottir L., Circadian Disription E.A. Sleep loss and prostate cancer risk: a systematic review of epidemiological studies. Cancer Epidemiol Biomarkers Prev. 2012;21:1002–1011.
    1. Burton C. Activity monitoring in patients with depression: a systematic review. J Affect Disord. 2013;145:21–28.
    1. Bullock B., Murray G. Reduced amplitude of the 24 hour activity rhythm: a biomarker of vulnerability to bipolar disorder? Clin Psychol Sci. 2014;2:86–96.
    1. Ng T.H. Sleep-wake disturbance in interepisode bipolar disorder and high-risk individuals: a systematic review and meta-analysis. Sleep Med Rev. 2015;20:46–58.
    1. Charrier A., Olliac B., Roubertoux P., Tordjman S. Clock genes and altered sleep – wake rhythms : their role in the development of psychiatric disorders. Int J Mol Sci. 2017;18:1–22.
    1. Koike N. Transcriptional architecture and chromatin landscape of the core circadian clock in mammals nobuya. Science. 2012;80(338):349–354.
    1. Zhang E.E. A genome-wide RNAi screen for modifiers of the circadian clock in human cells. Cell. 2009;139:199–210.
    1. Alloy L.B., Ng T.H., Titone M.K., Boland E.M. Circadian rhythm dysregulation in bipolar Spectrum disorders. Curr Psychiatry Rep. 2017
    1. Corruble E. Morningness-eveningness and treatment response in major depressive disorder. Chronobiol Int. 2014;31:283–289.
    1. Dmitrzak-Węglarz M. Chronotype and sleep quality as a subphenotype in association studies of clock genes in mood disorders. Acta Neurobiol Exp (Wars) 2016;76(32–42)
    1. Goel N., Basner M., Rao H., Dinges D.F. Circadian rhythms, sleep deprivation, and human performance. Prog Mol Biol Transl Sci. 2014;119:155–190.
    1. Hu Y. GWAS of 89,283 individuals identifies genetic variants associated with self-reporting of being a morning person. Nat Commun. 2016;7:1–9.
    1. Jones S.E. Genome-Wide association analyses in 128, 266 individuals identifies new morningness and sleep duration loci. PLoS Genet. 2016;12:1–19.
    1. Lane J.M. Genome-wide association analysis identifies novel loci for chronotype in 100,420 individuals from the UK biobank. Nat Commun. 2016;7:1–10.
    1. Jones S.E. Genetic studies of accelerometer-based sleep measures in 85,670 individuals yield new insights into human sleep behaviour. bioRxiv. 2018:303925.
    1. Dashti H. GWAS in 446,118 European adults identifies 78 genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates. bioRxiv. 2018;274977
    1. Jones S.E. Genome-wide association analyses of chronotype in 697,828 individuals provides new insights into circadian rhythms in humans and links to disease. bioRxiv. 2018;303941
    1. Taillard J., Philip P., Coste O., Sagaspe P., Bioulac B. The circadian and homeostatic modulation of sleep pressure during wakefulness differs between morning and evening chronotypes. J Sleep Res. 2003;12:275–282.
    1. Lyall L.M. Association of disrupted circadian rhythmicity with mood disorders, subjective wellbeing, and cognitive function: a cross-sectional study of 91 105 participants from the UK biobank. Lancet Psychiatr. 2018;0
    1. Sudlow C. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12
    1. Doherty A. Large scale population assessment of physical activity using wrist worn accelerometers: the UK biobank study. PLoS One. 2017;12:1–14.
    1. Sadeh A. The role and validity of actigraphy in sleep medicine: an update. Sleep Med Rev. 2011;15:259–267.
    1. Van Someren E.J.W. Circadian rest-activity rhythm disturbances in Alzheimer's disease. Biol Psychiatry. 1996;40:259–270.
    1. Gonçalves B.S.B., Cavalcanti P.R.A., Tavares G.R., Campos T.F., Araujo J.F. Nonparametric methods in actigraphy: An update. Sleep Sci (Sao Paulo, Brazil) 2014;7:158–164.
    1. Zielinski T., Moore A.M., Troup E., Halliday K.J., Millar A.J. Strengths and limitations of period estimation methods for circadian data. PLoS One. 2014;9
    1. Bycroft C. 2017. Genome-wide genetic data on ~ 500, 000 UK Biobank participants.
    1. Purcell S. Vol. 81. 2007. REPORT PLINK: A tool set for whole-genome association and population-based linkage analyses; pp. 559–575.
    1. Loh P.-R. Efficient Bayesian mixed-model analysis increases association power in large cohorts. Nat Genet. 2015;47:284–290.
    1. GTEx Consortium, T. Gte. The genotype-tissue expression (GTEx) project. Nat Genet. 2013;45:580–585.
    1. Watanabe K., Taskesen E., van Bochoven A., Posthuma D. Functional mapping and annotation of genetic associations with FUMA. Nat Commun. 2017;8:1826.
    1. de Leeuw C.A., Mooij J.M., Heskes T., Posthuma D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput Biol. 2015;11
    1. Bulik-Sullivan B. An atlas of genetic correlations across human diseases and traits. Nat Publ Gr. 2015;47:1236–1241.
    1. Zheng J. LD hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics. 2017;33:272–279.
    1. Davis K.A.S. Mental health in UK Biobank: development, implementation and results from an online questionnaire completed by 157 366 participants *. BJ Psych Open. 2018;4:83–90.
    1. Eysenck S.B.G., Eysenck H.J., Barrett P. A revised version of the psychoticism scale. Personal Individ Differ. 1985;6:21–29.
    1. Smith D.J. 2015. Genome-wide association study of neuroticism in UK biobank.
    1. Ward J. Genome-wide analysis in UK biobank identifies four loci associated with mood instability and genetic correlation with major depressive disorder, anxiety disorder and schizophrenia. Transl Psychiatry. 2017;7:1264.
    1. Townsend P. Deprivation J Soc Policy. 1987;16:125–146.
    1. Pike N. 2011. Using false discovery rates for multiple comparisons in ecology and evolution; pp. 278–282.
    1. Benjamini Y., Hochberg Y., Benjamini Y., Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B. 1995;57:289–300.
    1. rs147964682 (SNP) - Linkage disequilibrium - Homo sapiens - ensembl genome browser 92. Available at.
    1. rs113851554 (SNP) - Linkage disequilibrium - Homo sapiens - ensembl genome browser 92.
    1. Taylor A.M., Saifetiarova J., Bhat M.A. Postnatal loss of neuronal and glial Neurofascins differentially affects node of Ranvier maintenance and myelinated axon function. Front Cell Neurosci. 2017;11
    1. Thaxton C. In vivo deletion of immunoglobulin domains 5 and 6 in Neurofascin (Nfasc) reveals domain-specific requirements in myelinated axons. J Neurosci. 2010;30:4868–4876.
    1. Ferreira M.A.R. Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder. Nat Genet. 2008;40:1056–1058.
    1. Agrimi G., Russo A., Scarcia P., Palmieri F. The human gene SLC25A17 encodes a peroxisomal transporter of coenzyme A, FAD and NAD + Biochem J. 2012;443:241–247.
    1. The Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium. Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophreniaMol Autism. 2017;8(21)
    1. Van Veldhoven P.P. Biochemistry and genetics of inherited disorders of peroxisomal fatty acid metabolism. J Lipid Res. 2010;51:2863–2895.
    1. Moser A.B. Plasma very long chain fatty acids in 3,000 peroxisome disease patients and 29,000 controls. Ann Neurol. 1999;45:100–110.
    1. Bischoff F.R., Krebber H., Kempf T., Hermes I., Ponstingl H. Human RanGTPase-activating protein RanGAP1 is a homologue of yeast Rna1p involved in mRNA processing and transport. Proc Natl Acad Sci U S A. 1995;92:1749–1753.
    1. Wang Q. Regulation of MEIS1 by distal enhancer elements in acute leukemia. Leukemia. 2014;28:138–146.
    1. Xiong L. MEIS1 intronic risk haplotype associated with restless legs syndrome affects its mRNA and protein expression levels. Hum Mol Genet. 2009;18:1065–1074.
    1. Jacquet B.V. Specification of a Foxj1-dependent lineage in the forebrain is required for embryonic-to-postnatal transition of neurogenesis in the olfactory bulb. J Neurosci. 2011;31:9368–9382.
    1. Nagano M. ZF21 protein, a regulator of the disassembly of focal adhesions and cancer metastasis, contains a novel noncanonical pleckstrin homology domain. J Biol Chem. 2011;286:31598–31609.
    1. Tomsig J.L., Creutz C.E. Copines: a ubiquitous family of Ca(2+)-dependent phospholipid-binding proteins. Cell Mol Life Sci. 2002;59:1467–1477.
    1. Szigeti K. Genome-wide scan for copy number variation association with age at onset of Alzheimer's disease. J Alzheimers Dis. 2013;33:517–523.
    1. Gene: C3orf62 (ENSG00000188315) - Summary - Homo sapiens - ensembl genome browser 92. Available at.
    1. Xu J. Renalase is a novel, soluble monoamine oxidase that regulates cardiac function and blood pressure. J Clin Invest. 2005;115:1275–1280.
    1. Lv Y.-B. Association of renalase SNPs rs2296545 and rs2576178 with the risk of hypertension: a meta-analysis. PLoS One. 2016;11
    1. Frohnert B.I. Prediction of type 1 diabetes using a genetic risk model in the diabetes autoimmunity study in the young. Pediatr Diabetes. 2018;19:277–283.
    1. Desir G.V. Renalase deficiency in chronic kidney disease, and its contribution to hypertension and cardiovascular disease. Curr Opin Nephrol Hypertens. 2008;17:181–185.
    1. Merikanto I. Evening types are prone to depression. Chronobiol Int. 2013;30:719–725.
    1. Merikanto I., Suvisaari J., Lahti T., Partonen T. Eveningness relates to burnout and seasonal sleep and mood problems among young adults. Nord J Psychiatry. 2016;70:72–80.
    1. Fabbri C., Serretti A. Genetics of long-term treatment outcome in bipolar disorder. Prog Neuro-Psychopharmacol Biol Psychiatr. 2016;65:17–24.
    1. Partonen T. Clock gene variants in mood and anxiety disorders. J Neural Transm. 2012;119:1133–1145.
    1. Etain B., Milhiet V., Bellivier F., Leboyer M. Genetics of circadian rhythms and mood spectrum disorders. Eur Neuropsychopharmacol. 2011;21:S676–S682.
    1. Liberman A.R., Halitjaha L., Ay A., Ingram K.K. Modeling strengthens molecular link between circadian polymorphisms and major mood disorders. J Biol Rhythms. 2018;33:318–336.
    1. Geoffroy P.A. Sleep in remitted bipolar disorder: a naturalistic case-control study using actigraphy. J Affect Disord. 2014;158:1–7.
    1. McCarthy M.J. Genetic and clinical factors predict lithium's effects on PER2 gene expression rhythms in cells from bipolar disorder patients. Transl Psychiatry. 2013;3 e318–8.
    1. Bellivier F., Geoffroy P.-A., Etain B., Scott J. Sleep- and circadian rhythm–associated pathways as therapeutic targets in bipolar disorder. Expert Opin Ther Targets. 2015;19:747–763.
    1. Broome M.R., Saunders K.E.A., Harrison P.J., Marwaha S. Mood instability: significance, definition and measurement. Br J Psychiatry. 2015;207:283–285.
    1. Fry A. Comparison of sociodemographic and health-related characteristics of UK biobank participants with those of the general population. Am J Epidemiol. 2017;186:1026–1034.
    1. Pagani L. Genetic contributions to circadian activity rhythm and sleep pattern phenotypes in pedigrees segregating for severe bipolar disorder. Proc Natl Acad Sci U S A. 2016;113:E754–E761.
    1. Davey Smith G., Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum Mol Genet. 2014;23:R89–R98.

Source: PubMed

3
Abonneren