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The pharmacological mechanism of chaihu-jia-longgu-muli-tang for treating depression: integrated meta-analysis and network pharmacology analysis

Aim: Chaihu-jia-Longgu-Muli-tang (CLM) is derived from “Shang Han Lun” and is traditionally prescribed for treating depression. However, there is still a lack of evidence for its antidepressant effects, and the underlying mechanism is also unclear. This study aimed to assess clinical evidence on the...

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Autores principales: Zhao, Yang, Xu, Dan, Wang, Jing, Zhou, Dandan, Liu, Anlan, Sun, Yingying, Yuan, Yuan, Li, Jianxiang, Guo, Weifeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10551636/
https://www.ncbi.nlm.nih.gov/pubmed/37808199
http://dx.doi.org/10.3389/fphar.2023.1257617
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author Zhao, Yang
Xu, Dan
Wang, Jing
Zhou, Dandan
Liu, Anlan
Sun, Yingying
Yuan, Yuan
Li, Jianxiang
Guo, Weifeng
author_facet Zhao, Yang
Xu, Dan
Wang, Jing
Zhou, Dandan
Liu, Anlan
Sun, Yingying
Yuan, Yuan
Li, Jianxiang
Guo, Weifeng
author_sort Zhao, Yang
collection PubMed
description Aim: Chaihu-jia-Longgu-Muli-tang (CLM) is derived from “Shang Han Lun” and is traditionally prescribed for treating depression. However, there is still a lack of evidence for its antidepressant effects, and the underlying mechanism is also unclear. This study aimed to assess clinical evidence on the efficacy of CLM in patients with depression using a meta-analysis and to explore its underlying antidepressant molecular mechanisms via network pharmacology. Methods: Eight open databases were searched for randomized controlled trials (RCTs) comparing the effects of CLM alone or combined with serotonin-norepinephrine reuptake inhibitors (SNRIs) and selective serotonin reuptake inhibitors (SSRIs) in patients with depression, evaluating the total effective rate of the treatment group (CLM alone or combined with SSRIs/SNRIs) and the control group (SNRIs or SSRIs), and comparing changes in depression scale, anxiety scale, sleep scale, inflammation indicators and adverse effects. Subsequently, the active ingredients and target genes of CLM were screened through six databases. Then Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and protein-protein interaction (PPI) network and topology analysis were performed. Finally, Molecular docking was applied to evaluate the binding affinity between components and predicted targets. Results: Twenty-four RCTs with a total of 2,382 patients were included. For the efficacy of antidepression and adverse effects, whether CLM alone or in combination with SSRIs/SNRIs, the treatment group has no inferior to that of the control group. Additionally, the intervention of CLM + SSRI significantly improved the symptoms of anxiety and insomnia, and reduced serum IL-6 and TNF-α levels. For network pharmacology, a total of 129 compounds and 416 intersection targets in CLM were retrieved. The interaction pathway between CLM and depression is mainly enriched in PI3K-Akt, JAK-STAT, and NF-κB signaling pathway, PIK3R1, MAPK3, and AKT1 may be the potential targets of Stigmasterol, β-stiosterol, coumestrol. Conclusion: Compared to SSRIs/SNRIs alone, CLM is more effective and safe in treating depression. It not only significantly alleviates depressive mood, but improves symptoms such as anxiety and insomnia, with fewer side effects, especially in combination with SSRI. Its antidepressant mechanism may be correlated with the regulation of the PI3K/Akt signaling pathway and inhibiting inflammatory response.
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spelling pubmed-105516362023-10-06 The pharmacological mechanism of chaihu-jia-longgu-muli-tang for treating depression: integrated meta-analysis and network pharmacology analysis Zhao, Yang Xu, Dan Wang, Jing Zhou, Dandan Liu, Anlan Sun, Yingying Yuan, Yuan Li, Jianxiang Guo, Weifeng Front Pharmacol Pharmacology Aim: Chaihu-jia-Longgu-Muli-tang (CLM) is derived from “Shang Han Lun” and is traditionally prescribed for treating depression. However, there is still a lack of evidence for its antidepressant effects, and the underlying mechanism is also unclear. This study aimed to assess clinical evidence on the efficacy of CLM in patients with depression using a meta-analysis and to explore its underlying antidepressant molecular mechanisms via network pharmacology. Methods: Eight open databases were searched for randomized controlled trials (RCTs) comparing the effects of CLM alone or combined with serotonin-norepinephrine reuptake inhibitors (SNRIs) and selective serotonin reuptake inhibitors (SSRIs) in patients with depression, evaluating the total effective rate of the treatment group (CLM alone or combined with SSRIs/SNRIs) and the control group (SNRIs or SSRIs), and comparing changes in depression scale, anxiety scale, sleep scale, inflammation indicators and adverse effects. Subsequently, the active ingredients and target genes of CLM were screened through six databases. Then Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and protein-protein interaction (PPI) network and topology analysis were performed. Finally, Molecular docking was applied to evaluate the binding affinity between components and predicted targets. Results: Twenty-four RCTs with a total of 2,382 patients were included. For the efficacy of antidepression and adverse effects, whether CLM alone or in combination with SSRIs/SNRIs, the treatment group has no inferior to that of the control group. Additionally, the intervention of CLM + SSRI significantly improved the symptoms of anxiety and insomnia, and reduced serum IL-6 and TNF-α levels. For network pharmacology, a total of 129 compounds and 416 intersection targets in CLM were retrieved. The interaction pathway between CLM and depression is mainly enriched in PI3K-Akt, JAK-STAT, and NF-κB signaling pathway, PIK3R1, MAPK3, and AKT1 may be the potential targets of Stigmasterol, β-stiosterol, coumestrol. Conclusion: Compared to SSRIs/SNRIs alone, CLM is more effective and safe in treating depression. It not only significantly alleviates depressive mood, but improves symptoms such as anxiety and insomnia, with fewer side effects, especially in combination with SSRI. Its antidepressant mechanism may be correlated with the regulation of the PI3K/Akt signaling pathway and inhibiting inflammatory response. Frontiers Media S.A. 2023-09-21 /pmc/articles/PMC10551636/ /pubmed/37808199 http://dx.doi.org/10.3389/fphar.2023.1257617 Text en Copyright © 2023 Zhao, Xu, Wang, Zhou, Liu, Sun, Yuan, Li and Guo. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Zhao, Yang
Xu, Dan
Wang, Jing
Zhou, Dandan
Liu, Anlan
Sun, Yingying
Yuan, Yuan
Li, Jianxiang
Guo, Weifeng
The pharmacological mechanism of chaihu-jia-longgu-muli-tang for treating depression: integrated meta-analysis and network pharmacology analysis
title The pharmacological mechanism of chaihu-jia-longgu-muli-tang for treating depression: integrated meta-analysis and network pharmacology analysis
title_full The pharmacological mechanism of chaihu-jia-longgu-muli-tang for treating depression: integrated meta-analysis and network pharmacology analysis
title_fullStr The pharmacological mechanism of chaihu-jia-longgu-muli-tang for treating depression: integrated meta-analysis and network pharmacology analysis
title_full_unstemmed The pharmacological mechanism of chaihu-jia-longgu-muli-tang for treating depression: integrated meta-analysis and network pharmacology analysis
title_short The pharmacological mechanism of chaihu-jia-longgu-muli-tang for treating depression: integrated meta-analysis and network pharmacology analysis
title_sort pharmacological mechanism of chaihu-jia-longgu-muli-tang for treating depression: integrated meta-analysis and network pharmacology analysis
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10551636/
https://www.ncbi.nlm.nih.gov/pubmed/37808199
http://dx.doi.org/10.3389/fphar.2023.1257617
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