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An integrated genetic-epigenetic analysis of schizophrenia: evidence for co-localization of genetic associations and differential DNA methylation
Open accessAbstract
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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![Fig. 1 It is critical to control for smoking in an epigenome-wide association study (EWAS) of schizophrenia. Manhattan plots comparing association P-values (y-axis, −log10 scale) against genomic location (x-axis) for (a) an EWAS of schizophrenia case–control status without inclusion of a smoking covariate, (b) a published EWAS of tobacco smoking (never versus current) [22], and (c) an EWAS of schizophrenia case–control status including a DNA methylation-derived smoking score as a covariate. There is considerable overlap between the associated loci in panels a and b (e.g., on chromosomes 2, 5, 6, and 19), implying that the elevated rate and intensity of smoking in patients with schizophrenia [25–27] is a severe confounder in this analysis. In contrast, there is no overlap in the associated loci shown in panels b and c, suggesting that the derived smoking score effectively removes these false positives](/paper-figures/3dd11689a1dc4123ae5e238aeb3f5cac/an-integrated-genetic-epigenetic-analysis-of-schizophrenia-evidence-for-co-figure-1.jpg)
![Fig. 2 Replication of schizophrenia-associated DNA methylation differences identified in the phase 1 analysis in two independent cohorts. Shown are scatterplots demonstrating the concordance in effect size [schizophrenia-associated DNA methylation difference (%)] between the phase 1 (case–control) cohort (n = 675) (x-axis) and either the (a) phase 2 (case–control) cohort (n = 847) or (b) phase 3 (n = 96 monozygotic twin pairs) cohort for probes associated with schizophrenia at both the experiment-wide (P < 1 × 10−7; red circles) and discovery (P < 5 × 10−5; blue triangles) P-value thresholds. Many of these individual DNA methylation sites are significantly associated with schizophrenia in the replication cohorts (Table 1 and Additional file 2: Table S3). Meta-analyses across the three independent cohorts identified many additional sites significantly associated with schizophrenia at P < 1 × 10−7. (c) A forest plot of the top ranked probe from the meta-analysis (cg02488934), with the effect size and standard error (SE) from each individual cohort and the pooled effect from the meta-analysis. CI confidence interval](/paper-figures/edeb5a4d619a42fb802fffb311cac580/an-integrated-genetic-epigenetic-analysis-of-schizophrenia-evidence-for-co-figure-2.jpg)

![Fig. 4 Evidence for schizophrenia-associated differential DNA methylation within genome-wide association study (GWAS)-nominated genomic regions. A Manhattan plot of an example genomic region (chr10:104423800-105165583) identified in the recent GWAS of schizophrenia [2] illustrates the location (x-axis) of genetic variants and Illumina 450 K probes against their significance with schizophrenia (y-axis; −log10 P value). Gene locations (exons and introns) are depicted above the Manhattan plot. Red diamonds depict GWAS results, green circles depict results from our phase 1 schizophrenia EWAS, and blue triangles depict results from our schizophrenia polygenic risk score EWAS](/paper-figures/5bcbaff9cfcd4123820d9b5aa5ef1dd7/an-integrated-genetic-epigenetic-analysis-of-schizophrenia-evidence-for-co-figure-4.jpg)

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“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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“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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Self-citationAdditional file 3 of DNA methylation of the KLK8 gene in depression symptomatology
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Self-citationAdditional file 2 of DNA methylation of the KLK8 gene in depression symptomatology
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Metadata
- 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
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