Eating disorders are psychiatric disorders characterized by disturbed eating behaviors. They have a complex etiology in which genetic and environmental factors interact. Analyzing gene-environment interactions could help us to identify the mechanisms involved in the etiology of such conditions. For example, comethylation module analysis could detect the small effects of epigenetic interactions, reflecting the influence of environmental factors. We used MethylationEPIC and Psycharray microarrays to determine DNA methylation levels and genotype from 63 teenagers with eating disorders. We identified 11 comethylation modules in WGCNA (Weighted Gene Correlation Network Analysis) and correlated them with single nucleotide polymorphisms (SNP) and clinical features in our subjects. Two comethylation modules correlated with clinical features (BMI and height) in our sample and with SNPs associated with these phenotypes. One of these comethylation modules (yellow) correlated with BMI and rs10494217 polymorphism (associated with waist-hip ratio). Another module (black) was correlated with height, rs9349206, rs11761528, and rs17726787 SNPs; these polymorphisms were associated with height in previous GWAS. Our data suggest that genetic variations could alter epigenetics, and that these perturbations could be reflected as variations in clinical features.
Keywords: WGCNA; comethylation modules; eating disorders; genetic polymorphisms.