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Leveraging DNA methylation to predict treatment response in major depressive disorder: A critical review

DNA甲基化 重性抑郁障碍 心理学 计算生物学 精神科 遗传学 生物 认知 基因 基因表达
作者
Jan Dahrendorff,Glenn W. Currier,Monica Uddin
出处
期刊:American Journal of Medical Genetics - Neuropsychiatric Genetics [Wiley]
卷期号:195 (7) 被引量:1
标识
DOI:10.1002/ajmg.b.32985
摘要

Major depressive disorder (MDD) is a debilitating and prevalent mental disorder with a high disease burden. Despite a wide array of different treatment options, many patients do not respond to initial treatment attempts. Selection of the most appropriate treatment remains a significant clinical challenge in psychiatry, highlighting the need for the development of biomarkers with predictive utility. Recently, the epigenetic modification DNA methylation (DNAm) has emerged to be of great interest as a potential predictor of MDD treatment outcomes. Here, we review efforts to date that seek to identify DNAm signatures associated with treatment response in individuals with MDD. Searches were conducted in the databases PubMed, Scopus, and Web of Science with the concepts and keywords MDD, DNAm, antidepressants, psychotherapy, cognitive behavior therapy, electroconvulsive therapy, transcranial magnetic stimulation, and brain stimulation therapies. We identified 32 studies implicating DNAm patterns associated with MDD treatment outcomes. The majority of studies (N = 25) are focused on selected target genes exploring treatment outcomes in pharmacological treatments (N = 22) with a few studies assessing treatment response to electroconvulsive therapy (N = 3). Additionally, there are few genome-scale efforts (N = 7) to characterize DNAm patterns associated with treatment outcomes. There is a relative dearth of studies investigating DNAm patterns in relation to psychotherapy, electroconvulsive therapy, or transcranial magnetic stimulation; importantly, most existing studies have limited sample sizes. Given the heterogeneity in both methods and results of studies to date, there is a need for additional studies before existing findings can inform clinical decisions.

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