Schizophrenia (SZ) is an often-devastating neuropsychiatric illness. Genetic factors have been strongly implicated. The genetic contribution to SZ is likely to be complex and to extend beyond sequence variation. DNA methylation studies represent a promising complement to analyses of DNA sequence. As methylation is related to gene expression, knowledge of methylation levels of, e.g., regulatory elements may contribute functional information. Furthermore, as DNA methylation changes over time, methylation studies can provide insight into phenomena such as age of onset and the episodic nature of SZ. In addition, the dynamic nature of methylation and its response to environmental exposures suggests that methylation may explain gene- environment interactions. In a recent study, including 1,500 SZ case-control samples, all CpGs in the methylome was investigated using the enrichment based MBD-seq approach. This approach employs a methyl-CpG binding domain protein with high affinity for methylated CpGs in combination with next-generation sequencing to investigate the methylation profile across all CpGs in the genome. The data was used to conduct a methylome-wide association study (MWAS) covering ~27 million CpGs in the autosomal human reference genome. Analysis of SZ case-control status resulted in significant CpGs of promising biological relevance such as hypoxia and immune response. The results where successfully replicated in an independent study-sample using highly quantitative bisulfite pyrosequencing. The current proposal aims to conduct new analysis of the methylome data. Phenotype information about birth complications (e.g., hypoxia and infection), and use of prescribed drugs, such as antipsychotics, as well as genotype information from GWAS SNP genotyping, exome-sequencing and exome-chips are available from the study sample, which will be used in the new analysis. The human genome consists of a large number of CpGs that are created/destroyed by SNPs. Using the MBD-seq approach the methylation status for these CpGs are already available. However, the analyses for these sites require a different approach than CpGs in general. By integrating methylation and SNP information the methylation signal in these sites can be investigated conditional on the sequence and the potential effect on methylation caused by SZ can be determined. Furthermore, even if a SNP itself does not change the CpG the SNP may be correlated with the methylation signal, a methylation quantitative trait locus (meQTL). Whether, the location and distribution of these meQTLs are associated with SZ status remains to be investigated. Another type of data integration involves datasets obtained from different study samples. If multiple data types, such as results from GWAS, MWAS and mRNA expression analysis point towards susceptibility in specific loci, these loci are more likely to be true findings than if they were detected by a single data type.

Public Health Relevance

The proposed analysis will greatly help to advance our understanding of the role played by DNA methylation in schizophrenia (SZ) pathogenesis. The dynamic nature of methylation suggests that SZ susceptible methylation sites may potentially play a profound role as targets for future SZ treatments. Therefore, the proposed research may provide findings that, in turn, may lead to improved daily life for SZ patients and their families, which indirectly will lead to tremendous savings for the society.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Small Research Grants (R03)
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Behavioral Genetics and Epidemiology Study Section (BGES)
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Senthil, Geetha
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Virginia Commonwealth University
Schools of Pharmacy
United States
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Shabalin, Andrey A; Hattab, Mohammad W; Clark, Shaunna L et al. (2018) RaMWAS: fast methylome-wide association study pipeline for enrichment platforms. Bioinformatics 34:2283-2285
Hattab, Mohammad W; Shabalin, Andrey A; Clark, Shaunna L et al. (2017) Correcting for cell-type effects in DNA methylation studies: reference-based method outperforms latent variable approaches in empirical studies. Genome Biol 18:24
Chan, Robin F; Shabalin, Andrey A; Xie, Lin Y et al. (2017) Enrichment methods provide a feasible approach to comprehensive and adequately powered investigations of the brain methylome. Nucleic Acids Res 45:e97
van den Oord, Edwin J C G; Clark, Shaunna L; Xie, Lin Ying et al. (2016) A Whole Methylome CpG-SNP Association Study of Psychosis in Blood and Brain Tissue. Schizophr Bull 42:1018-26
McClay, Joseph L; Shabalin, Andrey A; Dozmorov, Mikhail G et al. (2015) High density methylation QTL analysis in human blood via next-generation sequencing of the methylated genomic DNA fraction. Genome Biol 16:291
Shabalin, Andrey A; Aberg, Karolina A; van den Oord, Edwin J C G (2015) Candidate gene methylation studies are at high risk of erroneous conclusions. Epigenomics 7:13-5