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Background Epigenetic modifications, in particular DNA methylation, play an important role in many biological processes in human health and disease. Understanding the cause of inter-individual differences in DNA methylation levels may help to identify novel molecular mechanisms contributing to a number of human diseases, including psychiatric diseases. Methods The aim of this study was to determine whether environmental risk factors for major depression (child abuse, socioeconomic status), genotype, or their interaction (GxE) best explain variablity in DNA methylation. We analyzed genome-wide DNA methylation (Illumina 450k arrays) from whole blood and genotype data of four independent cohorts (total N=1,.253). The cohorts consisted of adult individuals with diverse ethnic backgrounds, ages, and psychiatric disease status. Results We first identified the 15% most variably methylated (vm) CpGs in each cohort and observed that these vmCpGs had a higher correlation with brain methylation levels than expected by chance. Additionally, they were enriched in regulatory regions (including enhancer regions and specific, transcription factor binding sites). 40% (n=25.042) of the vmCpgGs overlapped between all 4 cohorts. We next analyzed, which factors explained most of the variance in methylation of these CpGs. While genotype alone explained most of the variance of about 20% of the vmCpGs, the majority of the vmCpGs were best explained by GxE (74%). E alone was almost never the model explaining most variance. We then investigated, how consistent the GxE effects on DNA methylation were across the 4 cohorts. We found that 30% of the vmCpGs were best explained by GxE in all four cohorts and 74% in at least three cohorts. The CpGs with GxE effects in all 4 cohorts also showed even stronger enrichment for enhancer regions than vmCpGs overall. Discussion Our study highlights the importance of considering both genetic and environmental data in interpreting epigenetic variation and suggests that integrating genotypes with epigenetic information could contribute to identifying functional genetic variants that moderate the impact of risk environments on the development of psychiatric disorders.