a Mental Illness Research, Education and Clinical Center , Crescenz VAMC , Philadelphia , PA , USA.
b Center for Studies of Addiction, Department of Psychiatry , University of Pennsylvania Perelman School of Medicine , Philadelphia , PA , USA.
Expert Opin Drug Metab Toxicol. 2019 Jul;15(7):553-564. doi: 10.1080/17425255.2019.1628218. Epub 2019 Jun 11.
: Alcohol use disorder (AUD) is highly prevalent; costly economically, socially, and interpersonally; and grossly undertreated. The low rate of utilization of medications with demonstrated (albeit modest) efficacy is particularly noteworthy. One approach to increasing the utility and safety of available medications is to use a precision medicine approach, which seeks to identify patients for whom specific medications are likely to be most efficacious and have the fewest adverse effects. : We review the literature on the pharmacogenetics of AUD treatment using both approved and off-label medications. We cover both laboratory studies and clinical trials, highlighting valuable mechanistic insights and underscoring the potential value of precision-based care for AUD. : Pharmacotherapy can be a useful component of AUD treatment. Currently, the evidence regarding genetic predictors of medication efficacy is very limited. Thus, a precision medicine approach is not yet ready for widespread clinical implementation. Further research is needed to identify candidate genetic variants that moderate the response to both established and novel medications. The growing availability of large-scale, longitudinal datasets that enable the synthesis of genetic and electronic health record data provides important opportunities to develop this area of research.
酒精使用障碍(AUD)的患病率很高;在经济、社会和人际关系方面造成了巨大的损失,但治疗率却很低。特别值得注意的是,具有已证实(尽管适度)疗效的药物的利用率很低。增加现有药物的实用性和安全性的一种方法是采用精准医学方法,这种方法旨在确定特定药物最有可能对哪些患者有效,且副作用最少。
我们使用已批准和非标签药物综述了 AUD 治疗的药物遗传学文献。我们涵盖了实验室研究和临床试验,突出了有价值的机制见解,并强调了基于精准的 AUD 护理的潜在价值。
药物治疗可以成为 AUD 治疗的有用组成部分。目前,关于药物疗效遗传预测因子的证据非常有限。因此,精准医学方法尚未准备好广泛应用于临床。需要进一步研究以确定候选基因变异,这些基因变异可以调节对既定和新型药物的反应。越来越多的大规模、纵向数据集的出现,使基因和电子健康记录数据的综合成为可能,为这一研究领域提供了重要机会。