An integrated genetic-epigenetic analysis of schizophrenia: evidence for co-localization of genetic associations and differential DNA methylation

Eilís Hannon(University of Exeter), Emma Dempster(University of Exeter), Joana Viana(University of Exeter), Joe Burrage(University of Exeter), Adam R. Smith(University of Exeter), Ruby I. MacDonald(University of Exeter), David St Clair(University of Aberdeen), Colette Mustard(University of the Highlands and Islands), Gerome Breen(King's College London), Sebastian Therman(Finnish Institute for Health and Welfare), Jaakko Kaprio(University of Helsinki), Timothea Toulopoulou(University of Hong Kong), Hilleke E. Hulshoff Pol(University Medical Center Utrecht), Marc M. Bohlken(University Medical Center Utrecht), René S. Kahn(University Medical Center Utrecht), Igor Nenadić(Jena University Hospital), Christina M. Hultman(Karolinska Institutet), Robin Murray(King's College London), David Collier(King's College London), Nick Bass(University College London), Hugh Gurling(University College London), Andrew McQuillin(University College London), Leonard C. Schalkwyk(University of Essex), Jonathan Mill(King's College London)
Genome biology
August 23, 2016
Cited by 387Open Access
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Abstract

BACKGROUND: Schizophrenia is a highly heritable, neuropsychiatric disorder characterized by episodic psychosis and altered cognitive function. Despite success in identifying genetic variants associated with schizophrenia, there remains uncertainty about the causal genes involved in disease pathogenesis and how their function is regulated. RESULTS: We performed a multi-stage epigenome-wide association study, quantifying genome-wide patterns of DNA methylation in a total of 1714 individuals from three independent sample cohorts. We have identified multiple differentially methylated positions and regions consistently associated with schizophrenia across the three cohorts; these effects are independent of important confounders such as smoking. We also show that epigenetic variation at multiple loci across the genome contributes to the polygenic nature of schizophrenia. Finally, we show how DNA methylation quantitative trait loci in combination with Bayesian co-localization analyses can be used to annotate extended genomic regions nominated by studies of schizophrenia, and to identify potential regulatory variation causally involved in disease. CONCLUSIONS: This study represents the first systematic integrated analysis of genetic and epigenetic variation in schizophrenia, introducing a methodological approach that can be used to inform epigenome-wide association study analyses of other complex traits and diseases. We demonstrate the utility of using a polygenic risk score to identify molecular variation associated with etiological variation, and of using DNA methylation quantitative trait loci to refine the functional and regulatory variation associated with schizophrenia risk variants. Finally, we present strong evidence for the co-localization of genetic associations for schizophrenia and differential DNA methylation.


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