Comprehensive Characterization of Antidepressant Pharmacogenetics: A Systematic Review of Studies in Major Depressive Disorder

IF 2.8 3区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL
Caroline W. Grant, Karina Delaney, Linsey E. Jackson, Justin Bobo, Leslie C. Hassett, Liewei Wang, Richard M. Weinshilboum, Paul E. Croarkin, Melanie T. Gentry, Ann M. Moyer, Arjun P. Athreya
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Abstract

Pharmacogenetics is a promising strategy to facilitate individualized care for patients with Major Depressive Disorder (MDD). Research is ongoing to identify the optimal genetic markers for predicting outcomes to antidepressant therapies. The primary aim of this systematic review was to summarize antidepressant pharmacogenetic studies to enhance understanding of the genes, variants, datatypes/methodologies, and outcomes investigated in the context of MDD. The secondary aim was to identify clinical genetic panels indicated for antidepressant prescribing and summarize their genes and variants. Screening of N = 5793 articles yielded N = 390 for inclusion, largely comprising adult (≥ 18 years) populations. Top-studied variants identified in the search were discussed and compared with those represented on the N = 34 clinical genetic panels that were identified. Summarization of articles revealed sources of heterogeneity across studies and low rates of replicability of pharmacogenetic associations. Heterogeneity was present in outcome definitions, treatment regimens, and differential inclusion of mediating variables in analyses. Efficacy outcomes (i.e., response, remission) were studied at greater frequency than adverse-event outcomes. Studies that used advanced analytical approaches, such as machine learning, to integrate variants with complimentary biological datatypes were fewer in number but achieved higher rates of significant associations with treatment outcomes than candidate variant approaches. As large biological datasets become more prevalent, machine learning will be an increasingly valuable tool for parsing the complexity of antidepressant response. This review provides valuable context and considerations surrounding pharmacogenetic associations in MDD which will help inform future research and translation efforts for guiding antidepressant care.

Abstract Image

抗抑郁药物遗传学的综合表征:对重度抑郁症研究的系统回顾
药物遗传学是一个很有前途的策略,以促进个性化护理的患者重度抑郁症(MDD)。研究正在进行中,以确定预测抗抑郁治疗结果的最佳遗传标记。本系统综述的主要目的是总结抗抑郁药物遗传研究,以加强对重度抑郁症的基因、变异、数据类型/方法和研究结果的理解。次要目的是确定抗抑郁药处方的临床遗传面板,并总结其基因和变异。筛选N = 5793篇文章,获得N = 390篇纳入,主要包括成人(≥18岁)人群。在搜索中发现的研究最多的变异进行了讨论,并与已确定的N = 34临床遗传面板上的变异进行了比较。文章的总结揭示了研究的异质性来源和药物遗传关联的低可重复性。异质性存在于结果定义、治疗方案和分析中中介变量的差异纳入。疗效结果(即反应、缓解)的研究频率高于不良事件结果。使用先进的分析方法(如机器学习)将变异与互补的生物学数据类型整合在一起的研究数量较少,但与候选变异方法相比,它们与治疗结果的显著相关性更高。随着大型生物数据集变得越来越普遍,机器学习将成为分析抗抑郁反应复杂性的越来越有价值的工具。这篇综述提供了有价值的背景和关于MDD药物遗传关联的考虑,这将有助于指导未来的研究和抗抑郁治疗的翻译工作。
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来源期刊
Cts-Clinical and Translational Science
Cts-Clinical and Translational Science 医学-医学:研究与实验
CiteScore
6.70
自引率
2.60%
发文量
234
审稿时长
6-12 weeks
期刊介绍: Clinical and Translational Science (CTS), an official journal of the American Society for Clinical Pharmacology and Therapeutics, highlights original translational medicine research that helps bridge laboratory discoveries with the diagnosis and treatment of human disease. Translational medicine is a multi-faceted discipline with a focus on translational therapeutics. In a broad sense, translational medicine bridges across the discovery, development, regulation, and utilization spectrum. Research may appear as Full Articles, Brief Reports, Commentaries, Phase Forwards (clinical trials), Reviews, or Tutorials. CTS also includes invited didactic content that covers the connections between clinical pharmacology and translational medicine. Best-in-class methodologies and best practices are also welcomed as Tutorials. These additional features provide context for research articles and facilitate understanding for a wide array of individuals interested in clinical and translational science. CTS welcomes high quality, scientifically sound, original manuscripts focused on clinical pharmacology and translational science, including animal, in vitro, in silico, and clinical studies supporting the breadth of drug discovery, development, regulation and clinical use of both traditional drugs and innovative modalities.
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