DNA methylation may play an important role in schizophrenia (SZ), either directly as a mechanism of pathogenesis or as a biomarker of risk.
To scan genome-wide DNA methylation data to identify differentially methylated CpGs between SZ cases and controls.
Design, Setting, and Participants
Epigenome-wide association study begun in 2008 using DNA methylation levels of 456 513 CpG loci measured on the Infinium HumanMethylation450 array (Illumina) in a consortium of case-control studies for initial discovery and in an independent replication set. Primary analyses used general linear regression, adjusting for age, sex, race/ethnicity, smoking, batch, and cell type heterogeneity. The discovery set contained 689 SZ cases and 645 controls (n = 1334), from 3 multisite consortia: the Consortium on the Genetics of Endophenotypes in Schizophrenia, the Project among African-Americans To Explore Risks for Schizophrenia, and the Multiplex Multigenerational Family Study of Schizophrenia. The replication set contained 247 SZ cases and 250 controls (n = 497) from the Genomic Psychiatry Cohort.
Main Outcomes and Measures
Identification of differentially methylated positions across the genome in SZ cases compared with controls.
Of the 689 case participants in the discovery set, 477 (69%) were men and 258 (37%) were non–African American; of the 645 controls, 273 (42%) were men and 419 (65%) were non–African American. In our replication set, cases/controls were 76% male and 100% non–African American. We identified SZ-associated methylation differences at 923 CpGs in the discovery set (false discovery rate, <0.2). Of these, 625 showed changes in the same direction including 172 with P < .05 in the replication set. Some replicated differentially methylated positions are located in a top-ranked SZ region from genome-wide association study analyses.
Conclusions and Relevance
This analysis identified 172 replicated new associations with SZ after careful correction for cell type heterogeneity and other potential confounders. The overlap with previous genome-wide association study data can provide potential insights into the functional relevance of genetic signals for SZ.