Identification of schizophrenia-associated loci by combining DNA methylation and gene expression data from whole blood.

Abstract

Emerging evidence suggests that schizophrenia (SZ) susceptibility involves variation at genetic, epigenetic and transcriptome levels. We describe an integrated approach that leverages DNA methylation and gene expression data to prioritize genetic variation involved in disease. DNA methylation levels were obtained from whole blood of 260 SZ patients and 250 unaffected controls of which a subset with gene expression data was available. By assessing DNA methylation and gene expression in cases and controls, we identified 432 CpG sites with differential methylation levels that are associated with differential gene expression. We hypothesized that genetic factors involved in these methylation levels may be associated with the genetic risk of SZ susceptibility. To test this hypothesis, we used results from the Psychiatric Genomics Consortium SZ genome-wide association study (GWAS). We observe an enrichment of SZ-associated SNPs in the mQTLs of which the associated CpG site is also correlated with differential gene expression in SZ. While this enrichment was already apparent when using nominal significant thresholds, enrichment was even more pronounced when applying more stringent significance levels. One locus, previously identified as susceptibility locus in a SZ GWAS, involves SNP rs11191514:C>T, which regulates DNA methylation of calcium homeostasis modulator 1 that is also associated with differential gene expression in patients. Overall, our results suggest that epigenetic variation plays an important role in SZ susceptibility and that the integration of analyses of genetic, epigenetic and gene expression profiles may be a biologically meaningful approach for identifying disease susceptibility loci, even when using whole blood data in studies of brain-related disorders.