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CYP2C19药物遗传学检测对预测西酞普兰和艾司西酞普兰耐受性及疗效的影响:一项回顾性纵向队列研究

Effect of CYP2C19 Pharmacogenetic Testing on Predicting Citalopram and Escitalopram Tolerability and Efficacy: A Retrospective, Longitudinal Cohort Study.

作者信息

Mahajna Mahmood, Abu Fanne Rami, Berkovitch Matitiahu, Tannous Elias, Vinker Shlomo, Green Ilan, Matok Ilan

机构信息

Department of Clinical Pharmacy, The Hebrew University, Jerusalem 9112002, Israel.

Hillel Yaffe Medical Center, Hadera 3810000, Israel.

出版信息

Biomedicines. 2023 Dec 7;11(12):3245. doi: 10.3390/biomedicines11123245.

Abstract

Background-Various antidepressant agents are metabolized by the CYP2C19 enzyme, including Citalopram and Escitalopram. Variation in CYP2C19 expression might give rise to different plasma concentrations of the active metabolites, potentially affecting both drugs' efficacy and tolerability. Aim-The aim of this study was to evaluate differences in the Escitalopram and Citalopram efficacy and tolerability between different CYP2C19 genotype-based metabolizing categories in outpatients suffering from major depressive disorder (MDD). Methods-In a retrospective, longitudinal cohort study of electronic medical-record data, 283 patients with MDD who were prescribed Escitalopram or Citalopram with the available CYP2C19-genotyping test were enrolled. The primary efficacy end point was adverse drug reactions recorded in the medical files. A proportional-odds, multilevel-regression model for longitudinal ordinal data was used to estimate the relation between the CYP2C19 genotype and adverse drug reactions, adjusting for potential confounding variables and other explanatory variables. Latent-class analysis (LCA) was utilized to detect the presence of clinically significant subgroups and their relation to an individual's metabolizing status for CYP2D6/CYP2C19. Results-With poor CYP2C19 metabolizers as a reference, for each unit difference in the activity score of the CYP2C19 phenotype, the odds ratio for drug intolerability was lowered by 0.73 (95% credible intervals: 0.56-0.89), adjusting for significant covariates. In addition, applying LCA, we identified two qualitatively different subgroups: the first group (61.85%) exhibited multiple side effects, low compliance, and frequent treatment changes, whereas the second group (38.15%) demonstrated fewer side effects, good adherence, and fewer treatment changes. The CYP2C19 phenotype was substantially associated with the group membership. Conclusions-We found a positive association between the CYP2C19 activity scores, as inferred from the genotype, and both the efficacy of and tolerability to both Es/Citalopram. LCA enabled valuable insights into the underlying structure of the population; the CYP2C19 phenotype has a predictive value that discriminates between low-adherence, low-drug-tolerance, and low-response patients and high-adherence, high-drug-tolerance, and high-response patients. Personalized medicine based on CYP2C19 genotyping could evolve as a promising new avenue towards mitigating Escitalopram and Citalopram therapy and the associated side effects and enhancing treatment success.

摘要

背景——多种抗抑郁药由CYP2C19酶代谢,包括西酞普兰和艾司西酞普兰。CYP2C19表达的差异可能导致活性代谢物的血浆浓度不同,从而可能影响两种药物的疗效和耐受性。目的——本研究的目的是评估重度抑郁症(MDD)门诊患者中,基于不同CYP2C19基因型代谢类别,艾司西酞普兰和西酞普兰在疗效和耐受性方面的差异。方法——在一项对电子病历数据的回顾性纵向队列研究中,纳入了283例接受艾司西酞普兰或西酞普兰治疗且进行了CYP2C19基因分型检测的MDD患者。主要疗效终点是病历中记录的药物不良反应。使用纵向有序数据的比例优势多级回归模型来估计CYP2C19基因型与药物不良反应之间的关系,并对潜在的混杂变量和其他解释变量进行调整。利用潜在类别分析(LCA)来检测临床显著亚组的存在及其与个体CYP2D6/CYP2C19代谢状态的关系。结果——以CYP2C19代谢不良者为参照,在对显著协变量进行调整后,CYP2C19表型活性评分每相差一个单位,药物不耐受的优势比降低0.73(95%可信区间:0.56 - 0.89)。此外,应用LCA,我们识别出两个质的不同的亚组:第一组(61.85%)表现出多种副作用、依从性低且频繁改变治疗,而第二组(38.15%)表现出较少的副作用、良好的依从性且较少改变治疗。CYP2C19表型与亚组成员身份密切相关。结论——我们发现,从基因型推断出的CYP2C19活性评分与艾司西酞普兰/西酞普兰的疗效和耐受性均呈正相关。LCA使我们能够深入了解人群的潜在结构;CYP2C19表型具有预测价值,可区分低依从性、低药物耐受性和低反应性患者与高依从性、高药物耐受性和高反应性患者。基于CYP2C19基因分型的个性化医疗可能会成为减轻艾司西酞普兰和西酞普兰治疗及其相关副作用、提高治疗成功率的一条有前景的新途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7ec/10740827/5abcf85c0cc8/biomedicines-11-03245-g001.jpg

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