Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK.
Faculty of Behavioural and Movement Sciences, Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
Mol Psychiatry. 2022 Mar;27(3):1647-1657. doi: 10.1038/s41380-021-01412-7. Epub 2021 Dec 8.
Antidepressants 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 in genes 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. We performed a methylome-wide association study (MWAS) of self-reported antidepressant use accounting for lifestyle factors and MDD in Generation Scotland (GS:SFHS, N = 6428, EPIC array) and the Netherlands Twin Register (NTR, N = 2449, 450 K array) and ran a meta-analysis of antidepressant use across these two cohorts. We found ten CpG sites significantly associated with self-reported antidepressant use in GS:SFHS, with the top CpG located within a gene previously associated with mental health disorders, ATP6V1B2 (β = -0.055, p = 0.005). Other top loci were annotated to genes including CASP10, TMBIM1, MAPKAPK3, and HEBP2, which have previously been implicated in the innate immune response. Next, using penalised regression, we trained a methylation-based score of self-reported antidepressant use in a subset of 3799 GS:SFHS individuals that predicted antidepressant use in a second subset of GS:SFHS (N = 3360, β = 0.377, p = 3.12 × 10, R = 2.12%). In an MWAS analysis of prescribed selective serotonin reuptake inhibitors, we showed convergent findings with those based on self-report. In NTR, we did not find any CpGs significantly associated with antidepressant use. The meta-analysis identified the two CpGs of the ten above that were common to the two arrays used as being significantly associated with antidepressant use, although the effect was in the opposite direction for one of them. Antidepressants were associated with epigenetic alterations in loci previously associated with mental health disorders and the innate immune system. These changes predicted self-reported antidepressant use in a subset of GS:SFHS and identified processes that may be relevant to our mechanistic understanding of clinically relevant antidepressant drug actions and side effects.
抗抑郁药是治疗重度抑郁症（MDD）的有效方法，尽管个体反应不可预测且高度可变。虽然抗抑郁药的作用模式尚未完全了解，但许多药物与可能与其机制相关的基因中的 DNA 甲基化变化有关。因此，对 DNA 甲基化的研究可能会揭示抗抑郁药疗效和副作用的生物学过程。我们对苏格兰一代研究（GS：SFHS，N=6428，EPIC 阵列）和荷兰双胞胎登记处（NTR，N=2449，450K 阵列）中自我报告的抗抑郁药使用情况进行了全基因组甲基化关联研究（MWAS），并对这两个队列中的抗抑郁药使用情况进行了荟萃分析。我们发现 GS：SFHS 中与自我报告的抗抑郁药使用相关的十个 CpG 位点，位于先前与精神健康障碍相关的基因内的顶级 CpG 位点 ATP6V1B2（β=-0.055，p=0.005）。其他顶级基因座注释到 CASP10、TMBIM1、MAPKAPK3 和 HEBP2 等基因，这些基因先前与先天免疫反应有关。接下来，我们使用惩罚回归，在 GS：SFHS 的一个亚组中为自我报告的抗抑郁药使用训练了一个基于甲基化的评分，该亚组中的 3799 名个体可预测 GS：SFHS 的另一个亚组中的抗抑郁药使用（N=3360，β=0.377，p=3.12×10，R=2.12%）。在对处方选择性 5-羟色胺再摄取抑制剂的 MWAS 分析中，我们发现与基于自我报告的分析结果具有一致性。在 NTR 中，我们没有发现任何与抗抑郁药使用显著相关的 CpG。荟萃分析确定了上述十个 CpG 中的两个在两个使用的阵列中与抗抑郁药使用相关，尽管其中一个的效果方向相反。抗抑郁药与先前与精神健康障碍和先天免疫系统相关的基因座中的表观遗传改变有关。这些变化可预测 GS：SFHS 亚组中自我报告的抗抑郁药使用，并确定了可能与我们对抗抑郁药临床相关药物作用和副作用的机制理解相关的过程。
