Biological embedding of the pyscho-social environment; an Epigenetic Analysis of Adversity from Early-life to Adulthood

IntroductionResearch has shown that social and physical stressors of early-life adversity (ELA) can negatively affect long-term health trajectories. Despite differences in types of ELA exposure, previous studies have identified common health-related outcomes in adults who had experienced less favourable conditions during developmentally sensitive periods. This meta-analysis investigates the potential role of DNA methylation in mediating these adverse health trajectories by identifying common biological signatures across cohorts with distinct adversity exposures and environmental backgrounds. Materials and MethodsDNA methylation data from previously published studies was used to perform a meta-analysis on 227 individuals across three cohorts. These include the EpiPath cohort consisting of adults who were exposed early institutional care, ImmunoTwin cohort consisting of adversity discordant monozygotic twin pairs and lastly a cohort of young children exposed to early institutional care. ResultsDNA methylation analysis across the three cohorts revealed differential methylation at CpG loci associated with 15 genes common to all cohorts. These genes are involved in neuronal development, chromatin remodeling and metabolism. Pathway enrichment analysis of the combined dataset showed potential associations with oxytocin signalling, regulation of nervous system development, and calcium signalling in relation to the later-life phenotype of the adversity exposed individuals. In addition, a poly-epigenetic score was developed by identifying a subset of 200 differentially methylated CpG sites through PLS-DA analysis with the combined beta matrix of these cohorts. ConclusionThis study highlights the long-term impact of adversity by identifying common DNA methylation signatures of negative life experiences across three cohorts. The development of a poly-epigenetic score represents the first steps towards identifying group differences by combining weighted methylation values for CpG sites of interest. This method illustrates the potential to track changes in individuals across long-term studies that may benefit research in lifelong healthoutcomes.