Investigating the Epigenetic Landscape of Major Depressive Disorder: A Genome-Wide Meta-Analysis of DNA Methylation Data, Including New Insights into Stochastic Epigenetic Mutations and Epivariations

探究重度抑郁症的表观遗传图谱:基于全基因组DNA甲基化数据的荟萃分析,包括对随机表观遗传突变和表观变异的新见解

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Abstract

Background/Objectives: Major depressive disorder (MDD) is a mental health condition that can severely impact patients' social lives, leading to withdrawal and difficulty in maintaining relationships. Environmental factors such as trauma and stress can worsen MDD by interacting with genetic predispositions. Epigenetics, which examines changes in gene expression influenced by the environment, may help identify patterns linked to depression. This study aimed to explore the epigenetic mechanisms behind MDD by analysing six public datasets (n = 1125 MDD cases, 398 controls in blood; n = 95 MDD cases, 96 controls in brain tissues) from the Gene Expression Omnibus. Methods: As an innovative approach, two meta-analyses of DNA methylation patterns were conducted alongside an investigation of stochastic epigenetic mutations (SEMs), epigenetic age acceleration, and rare epivariations. Results: While no significant global methylation differences were observed between MDD cases and controls, hypomethylation near the SHF gene (brain-specific probe cg25801113) was consistently found in MDD cases. SEMs revealed a gene-level burden in MDD, though epigenetic age acceleration was not central to the disorder. Additionally, 51 rare epivariations were identified in blood tissue and 1 in brain tissue linked to MDD. Conclusions: The study emphasises the potential role of rare epivariations in MDD's epigenetic regulation but calls for further research with larger, more diverse cohorts to confirm these findings.

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