An integrated genetic-epigenetic analysis of schizophrenia

Evidence for co-localization of genetic associations and differential DNA methylation

Eilis Hannon, Emma Dempster, Joana Viana, Joe Burrage, Adam R. Smith, Ruby Macdonald, David St Clair, Colette Mustard, Gerome Breen, Sebastian Therman, Jaakko Kaprio, Timothea Toulopoulou, Hilleke E.Hulshoff Pol, Marc M. Bohlken, Rene S. Kahn, Igor Nenadic, Christina M. Hultman, Robin M. Murray, David A. Collier, Nick Bass & 4 others Hugh Gurling, Andrew McQuillin, Leonard Schalkwyk, Jonathan Mill*

*Corresponding author for this work

Research output: Contribution to journalArticle

87 Citations (Scopus)
4 Downloads (Pure)

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.

Original languageEnglish
Article number176
JournalGenome Biology
Volume17
DOIs
Publication statusPublished - 30 Aug 2016

Fingerprint

methylation
genetic analysis
DNA methylation
DNA Methylation
Epigenomics
epigenetics
Schizophrenia
DNA
genome
Quantitative Trait Loci
smoking
quantitative trait loci
genomics
schizophrenia
gene
Genome-Wide Association Study
cognition
Psychotic Disorders
Cognition
Uncertainty

Keywords

  • DNA methylation
  • Epigenetics
  • Epigenome-wide association study (EWAS)
  • Genetics
  • Genome-wide association study (GWAS)
  • Polygenic risk score (PRS)
  • Schizophrenia

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Cell Biology

Cite this

An integrated genetic-epigenetic analysis of schizophrenia : Evidence for co-localization of genetic associations and differential DNA methylation. / Hannon, Eilis; Dempster, Emma; Viana, Joana; Burrage, Joe; Smith, Adam R.; Macdonald, Ruby; St Clair, David; Mustard, Colette; Breen, Gerome; Therman, Sebastian; Kaprio, Jaakko; Toulopoulou, Timothea; Pol, Hilleke E.Hulshoff; Bohlken, Marc M.; Kahn, Rene S.; Nenadic, Igor; Hultman, Christina M.; Murray, Robin M.; Collier, David A.; Bass, Nick; Gurling, Hugh; McQuillin, Andrew; Schalkwyk, Leonard; Mill, Jonathan.

In: Genome Biology, Vol. 17, 176, 30.08.2016.

Research output: Contribution to journalArticle

Hannon, E, Dempster, E, Viana, J, Burrage, J, Smith, AR, Macdonald, R, St Clair, D, Mustard, C, Breen, G, Therman, S, Kaprio, J, Toulopoulou, T, Pol, HEH, Bohlken, MM, Kahn, RS, Nenadic, I, Hultman, CM, Murray, RM, Collier, DA, Bass, N, Gurling, H, McQuillin, A, Schalkwyk, L & Mill, J 2016, 'An integrated genetic-epigenetic analysis of schizophrenia: Evidence for co-localization of genetic associations and differential DNA methylation', Genome Biology, vol. 17, 176. https://doi.org/10.1186/s13059-016-1041-x
Hannon, Eilis ; Dempster, Emma ; Viana, Joana ; Burrage, Joe ; Smith, Adam R. ; Macdonald, Ruby ; St Clair, David ; Mustard, Colette ; Breen, Gerome ; Therman, Sebastian ; Kaprio, Jaakko ; Toulopoulou, Timothea ; Pol, Hilleke E.Hulshoff ; Bohlken, Marc M. ; Kahn, Rene S. ; Nenadic, Igor ; Hultman, Christina M. ; Murray, Robin M. ; Collier, David A. ; Bass, Nick ; Gurling, Hugh ; McQuillin, Andrew ; Schalkwyk, Leonard ; Mill, Jonathan. / An integrated genetic-epigenetic analysis of schizophrenia : Evidence for co-localization of genetic associations and differential DNA methylation. In: Genome Biology. 2016 ; Vol. 17.
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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.",
keywords = "DNA methylation, Epigenetics, Epigenome-wide association study (EWAS), Genetics, Genome-wide association study (GWAS), Polygenic risk score (PRS), Schizophrenia",
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T1 - An integrated genetic-epigenetic analysis of schizophrenia

T2 - Evidence for co-localization of genetic associations and differential DNA methylation

AU - Hannon, Eilis

AU - Dempster, Emma

AU - Viana, Joana

AU - Burrage, Joe

AU - Smith, Adam R.

AU - Macdonald, Ruby

AU - St Clair, David

AU - Mustard, Colette

AU - Breen, Gerome

AU - Therman, Sebastian

AU - Kaprio, Jaakko

AU - Toulopoulou, Timothea

AU - Pol, Hilleke E.Hulshoff

AU - Bohlken, Marc M.

AU - Kahn, Rene S.

AU - Nenadic, Igor

AU - Hultman, Christina M.

AU - Murray, Robin M.

AU - Collier, David A.

AU - Bass, Nick

AU - Gurling, Hugh

AU - McQuillin, Andrew

AU - Schalkwyk, Leonard

AU - Mill, Jonathan

N1 - We thank Dr Hannah Elliott (University of Bristol MRC Integrative Epidemiology Unit) for providing code to calculate DNA methylation smoking scores.

PY - 2016/8/30

Y1 - 2016/8/30

N2 - 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.

AB - 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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KW - Epigenome-wide association study (EWAS)

KW - Genetics

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KW - Schizophrenia

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JF - Genome Biology

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