An integrated genetic-epigenetic analysis of schizophrenia: evidence for co-localization of genetic associations and differential DNA methylation
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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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An EWAS by Montano et al. found differences in DNAm in genes involved in T-cell development in the blood of SCZ patients (ZC3H12D, TCF3, and IKZF4); other EWAS have also reported an enrichment in the immune system pathway by differently methylated genes.
“An EWAS by Montano et al. (Montano et al. 2016) found differences in DNAm in genes involved in T-cell development in the blood of SCZ patients (ZC3H12D, TCF3, and IKZF4); other EWAS have also reported an enrichment in the immune system pathway by differently methylated genes”
From Can epigenetics shine a light on the biological pathways underlying major mental disorders? (2022) · cites this paper as Hannon et al., 2016
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Experimental — accuracy not yet measuredThe confounding effect of smoking is clearly evidenced in an EWAS study on peripheral blood of schizophrenia patients.
“The confounding effect of smoking is clearly evidenced in an EWAS study on peripheral blood of SCZ patients (Hannon et al., 2016).”
From Can epigenetics shine a light on the biological pathways underlying major mental disorders? (2022) · cites this paper as Hannon et al., 2016
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- Authors
- Hannon, E., Dempster, E., Viana, J., Burrage, J., Smith, A. R., Macdonald, R., St Clair, D., Mustard, C., Breen, G., Therman, S., Kaprio, J., Toulopoulou, T., Pol, H. E. H., Bohlken, M. M., Kahn, R. S., Nenadic, I., Hultman, C. M., Murray, R. M., Collier, D. A., Bass, N., Gurling, H., McQuillin, A., Schalkwyk, L., & Mill, J.
- Affiliations
- University of Exeter (GB)
- University of the Highlands and Islands (GB)
- King's College London (GB)
- Finnish Institute for Health and Welfare (FI)
- University of Helsinki (FI)
- University of Hong Kong (HK)
- University Medical Center Utrecht (NL)
- Karolinska Institutet (SE)
- University College London (GB)
- University of Essex (GB)
- Corresponding author
- Mill, Jonathan
- ORCID
- Venue
- Genome Biology
- Published
- 2016-08-30
- Volume
- 17
- Issue
- 1
- Pages
- 176-176
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC5004279
- OpenAlex
- W2510420694
- Cited by
- 349
- References
- 66
- Citations by year
- 2026: 8 · 2025: 29 · 2024: 39 · 2023: 32 · 2022: 40 · 2021: 54 · 2020: 39 · 2019: 37 · 2018: 45 · 2017: 21 · 2016: 3
- FWCI
- 18.54
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Open Access at Essex (University of Essex) (acceptedVersion)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- Research Portal (King's College London) (submittedVersion, cc-by)
- Aberdeen University Research Archive (Aberdeen University) (submittedVersion)
- Työväentutkimus Vuosikirja (submittedVersion, other-oa)
- Open Research Exeter (University of Exeter) (submittedVersion, cc-by)
- Royal Devon and Exeter Research Repository (Royal Devon and Exeter) (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- Funders
- Medical Research Council (MR/K013807/1)
- National Institutes of Health (R01 AG036039, R01 MH52857)
- Suomen Akatemia (213506, 129680, 265240, 263278)
- Karolinska Institutet (ALF 20090183, ALF 20100305)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- schizophrenia, DNA methylation, epigenome-wide association study, differentially methylated regions, DNA methylation quantitative trait loci, polygenic risk score, genetic risk variants, gene expression regulation
- MeSH terms
- Bayes Theorem, Humans, Phenotype, Schizophrenia, Twins, Monozygotic, CpG Islands, DNA Methylation, Multifactorial Inheritance, Quantitative Trait Loci, Genome-Wide Association Study, Epigenomics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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