AUTHOR=Li Qiao-feng , Lu Wen-tian , Zhang Qing , Zhao Yan-dong , Wu Cheng-yu , Zhou Hui-fang
TITLE=Proprietary Medicines Containing Bupleurum chinense DC. (Chaihu) for Depression: Network Meta-Analysis and Network Pharmacology Prediction
JOURNAL=Frontiers in Pharmacology
VOLUME=Volume 13 - 2022
YEAR=2022
URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2022.773537
DOI=10.3389/fphar.2022.773537
ISSN=1663-9812
ABSTRACT=Background and Aims: The rapid development of society has resulted in great competitive pressures, leading to the increase in suicide rates as well as incidence and recurrence of depression in recent years. Proprietary Chinese medicines containing Bupleurum chinense DC. (Chaihu) are widely used in clinical practice. This study aimed at evaluating the efficacy and safety of oral proprietary Chinese medicines containing Chaihu for treating depression by network meta-analysis (NMA) and exploring the potential pharmacological mechanisms of the optimal drugs obtained based on NMA.
Methods: This study searched for clinical randomized controlled trial studies (RCTs) about Chaihu-containing products alone or in combination with selective serotonin reuptake inhibitors (SSRI), serotonin-norepinephrine reuptake inhibitors (SNRI), and cyclic antidepressants (CAS) for depression in eight databases. The search deadline is from data inception to April 2021. For efficacy assessment, the clinical response rate, the Hamilton Depression Scale-17 (HAMD-17), and adverse reactions were calculated. The methodological quality of the included studies was assessed for risk of bias following the Cochrane Handbook for Systematic Reviews of Interventions, and the data were subjected to NMA via the Stata version 16.0 software. Subsequently, the optimal drug obtained from the NMA results, Danzhi Xiaoyao pill (DZXY), was used to conduct network pharmacology analysis. We searched databases to acquire bioactive and potential targets of DZXY and depression-related targets. The protein-protein interaction (PPI) network, component-target network, the Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by the STRING database, Cytoscape 3.9.0 software, and R version 4.1.2, respectively.
Results: Thirty-seven RCTs, with a total of 3,263 patients, involving seven oral proprietary Chinese medicines containing Chaihu, were finally included. The results of the NMA demonstrated that the top four interventions with the best efficiency were Jiawei Xiaoyao + SSRI, DZXY + SNRI, Xiaoyao pill + SSRI, and Jieyu pill + SNRI; the top four interventions reducing HAMD score were DZXY + SNRI, Jiawei Xiaoyao, Jieyu pill, and Puyu pill + SNRI; the top four interventions with the least adverse effects were Jieyu pill, Anle pill + SSRI, DZXY + SNRI, and Puyu pill + SNRI. In the aspects above, DZXY + SNRI performed better than other treatments. After network meta-analysis, we conducted a network pharmacology-based strategy on the optimal drugs, DZXY, to provide the pharmacological basis for a conclusion. A total of 147 active compounds and 248 targets in DZXY were identified, of which 175 overlapping targets related to depression. Bioinformatics analysis revealed that MAPK3, JUN, MAPK14, MYC, MAPK1, etc. could become potential therapeutic targets. The MAPK signaling pathway might play an essential role in DZXY against depression.
Conclusion: This is the very first systematic review and network meta-analysis evaluating different oral proprietary Chinese medicines containing Chaihu in depressive disorder. This study suggested that the combination of proprietary Chinese medicines containing Chaihu with antidepressants was generally better than antidepressant treatment. The incidence of adverse reactions with antidepressants alone was higher than that with proprietary Chinese medicines containing Chaihu alone or in combination with antidepressants. DZXY + SNRI showed significantly better results in efficacy, HAMD scores, and safety. The antidepressant effect of DZXY may be related to its regulation of neuroinflammation and apoptosis.