Epigenome-wide association study of self-reported antidepressant use in Generation Scotland implicates the innate immune system

BackgroundAntidepressants are an effective treatment for major depressive disorder (MDD), although individual response is unpredictable and highly variable. Whilst the mode of action of antidepressants is incompletely understood, many medications are associated with changes in DNA methylation that are plausibly linked to their mechanisms. Studies of DNA methylation may therefore reveal the biological processes underpinning the efficacy and side effects of antidepressants. MethodsWe performed an epigenome-wide association study (EWAS) of self-reported antidepressant use accounting for lifestyle factors and MDD in the Generation Scotland cohort (N=6,428). ResultsWe found 10 CpG sites significantly associated with self-reported antidepressant use, with the top CpG located within a gene previously associated with mental health disorders, ATP6V1B2 ({beta}=-0.055, pcorrected=0.005). Other top loci, annotated to genes including CASP10, TMBIM1, MAPKAPK3, and HEBP2, have previously been implicated in the innate immune response. We also identified a number of disease-associated single nucleotide polymorphisms as trans and cis methylation quantitative trait loci (mQTLs) for CpG sites identified here. Next, using penalised regression, we trained a methylation-based score (MS) of self-reported antidepressant use in 3,799 individuals that predicted antidepressant use in a second subset of Generation Scotland (N=3,360,{beta}=0.377, p=3.12x10-11,R2=2.12%). Lastly, in an EWAS analysis of SSRI antidepressant prescribing data from electronic health records, we showed convergent findings with those based on self-report. ConclusionsAntidepressants may exert their effects through epigenetic alterations in regions previously associated with mental health disorders and those involved in the innate immune system. These changes predicted self-reported antidepressant use in a subset of Generation Scotland and identify processes that may be relevant to our mechanistic understanding of clinically relevant antidepressant drug actions and side effects.