Effects of Xiaoyao San on exercise capacity and liver mitochondrial metabolomics in rat depression model

IF 4.7 4区医学 Q1 CHEMISTRY, MEDICINAL

Chinese Herbal Medicines Pub Date : 2024-01-01 DOI:10.1016/j.chmed.2023.09.004

Weidi Zhao , Cui Ji , Jie Zheng , Shi Zhou , Junsheng Tian , Yumei Han , Xuemei Qin

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引用次数: 0

Abstract

Objective

This study aimed to investigate the therapeutic effects of Xiaoyao San (XYS), a herbal medicine formula, on exercise capacity and liver mitochondrial metabolomics in a rat model of depression induced by chronic unpredictable mild stress (CUMS).

Methods

A total of 24 male SD rats were randomly divided into four groups: control group (C), CUMS control group (M), Venlafaxine positive treatment group (V), and XYS treatment group (X). Depressive behaviour and exercise capacity of rats were assessed by body weight, sugar-water preference test, open field test, pole test, and rotarod test. The liver mitochondria metabolomics were analyzed by using liquid chromatography-mass spectrometry (LC-MS) method. TCMSP database and GeneCards database were used to screen XYS for potential targets for depression, and GO and KEGG enrichment analyses were performed.

Results

Compared with C group, rats in M group showed significantly lower body weight, sugar water preference rate, number of crossing and rearing in the open field test, climbing down time in the pole test, and retention time on the rotarod test (P < 0.01). The above behaviors and exercise capacity indices were significantly modulated in rats in V and X groups compared with M group (P < 0.05, 0.01). Compared with C group, a total of 18 different metabolites were changed in the liver mitochondria of rats in M group. Nine different metabolites and six metabolic pathways were regulated in the liver mitochondria of rats in X group compared with M group. The results of network pharmacology showed that 88 intersecting targets for depression and XYS were obtained, among which 15 key targets such as IL-1β, IL-6, and TNF were predicted to be the main differential targets for the treatment of depression. Additionally, a total of 1 553 GO signaling pathways and 181 KEGG signaling pathways were identified, and the main biological pathways were AGE-RAGE signaling pathway, HIF-1 signaling pathway, and calcium signaling pathway.

Conclusion

XYS treatment could improve depressive symptoms, enhance exercise capacity, positively regulate the changes of mitochondrial metabolites and improve energy metabolism in the liver of depressed rats. These findings suggest that XYS exerts antidepressant effects through multi-target and multi-pathway.

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小枣散对抑郁模型大鼠运动能力和肝线粒体代谢组学的影响

方法将24只雄性SD大鼠随机分为4组：对照组（C）、CUMS对照组（M）、文拉法辛阳性治疗组（V）和XYS治疗组（X）。大鼠的抑郁行为和运动能力通过体重、糖水偏好试验、开阔地试验、撑竿试验和转体试验进行评估。采用液相色谱-质谱（LC-MS）方法对肝脏线粒体代谢组学进行分析。结果与C组相比，M组大鼠的体重、糖水偏好率、空地试验中的穿越次数和饲养次数、杆式试验中的爬下时间和转体试验中的停留时间均显著降低（P <0.01）。与 M 组相比，V 组和 X 组大鼠的上述行为和运动能力指数都有明显的改变（P < 0.05, 0.01）。与 C 组相比，M 组大鼠肝脏线粒体中总共有 18 种不同的代谢物发生了变化。与 M 组相比，X 组大鼠肝脏线粒体中有 9 种不同的代谢物和 6 条代谢途径受到调控。网络药理学结果显示，抑郁症与XYS有88个交叉靶点，其中IL-1β、IL-6和TNF等15个关键靶点被预测为治疗抑郁症的主要差异靶点。结论 XYS治疗可改善抑郁症状，提高运动能力，正向调节线粒体代谢产物的变化，改善抑郁大鼠肝脏的能量代谢。这些研究结果表明，XYS通过多靶点、多途径发挥抗抑郁作用。

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来源期刊

Chinese Herbal Medicines CHEMISTRY, MEDICINAL-

CiteScore

4.40

自引率

5.30%

发文量

629

审稿时长

10 weeks

期刊介绍： Chinese Herbal Medicines is intended to disseminate the latest developments and research progress in traditional and herbal medical sciences to researchers, practitioners, academics and administrators worldwide in the field of traditional and herbal medicines. The journal's international coverage ensures that research and progress from all regions of the world are widely included. CHM is a core journal of Chinese science and technology. The journal entered into the ESCI database in 2017, and then was included in PMC, Scopus and other important international search systems. In 2019, CHM was successfully selected for the “China Science and Technology Journal Excellence Action Plan” project, which has markedly improved its international influence and industry popularity. CHM obtained the first impact factor of 3.8 in Journal Citation Reports (JCR) in 2023.