Importance: DNA methylation may play an important role in schizophrenia (SZ), either directly as a mechanism of pathogenesis or as a biomarker of risk.
Objective: 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.
Results: 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.