Identification of Potential Biomarkers of Depression and Network Pharmacology Approach to Investigate the Mechanism of Key Genes and Therapeutic Traditional Chinese Medicine in the Treatment of Depression.
Identification of Potential Biomarkers of Depression and Network Pharmacology Approach to Investigate the Mechanism of Key Genes and Therapeutic Traditional Chinese Medicine in the Treatment of Depression.
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DOI：
10.1155/2021/2165632
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Deng L
中科院分区：
文献类型：
--
作者：
Shi Y;Chen D;Ma S;Xu H;Deng L
探讨抑郁症的潜在靶点及相关中药治疗抑郁症的作用机制。 在GEO数据库中分析抑郁症患者和对照组的差异基因表达。通过检索疾病数据库获得抑郁症的关键基因。利用COREMINE医学数据库检索与治疗抑郁症关键基因对应的中药，并对这些中药进行网络药理分析。然后，进行蛋白质-蛋白质相互作用分析。基因表型的预测基于基因本体论（GO）和京都基因和基因组百科全书（KEGG）途径富集评分。 GEO数据库中差异表达基因的总数为147个。结合GEO数据集和疾病数据库，共分析了3533个抑郁症相关基因。在COREMINE Medical进行筛选后发现，抑郁症用药频率最高的前4种中药分别是：芍药、番红花，柴胡，和Cannabis sativa L. GO和KEGG分析显示，最常用的中药通过这些靶点对抑郁症的多个方面进行调节，涉及代谢、神经内分泌功能、神经免疫等。蛋白质-蛋白质相互作用的预测和分析导致9个枢纽基因（ESR 1、HSP 90 AA 1、JUN、MAPK 1、MAPK 14、MAPK 8、RB 1、RELA和TP 53）的选择。此外，该中药中共有四种成分（矮牵牛素、异鼠李素、槲皮素和木犀草素）可以作用于这些枢纽基因。 本研究揭示了常用中药复杂的抗抑郁作用机制，为揭示中药复方复杂的成分和功能提供了合理的策略。
To explore the potential target of depression and the mechanism of related traditional Chinese medicine in the treatment of depression. Differential gene expression in depression patients and controls was analyzed in the GEO database. Key genes for depression were obtained by searching the disease databases. The COREMINE Medical database was used to search for Chinese medicines corresponding to the key genes in the treatment of depression, and the network pharmacological analysis was performed on these Chinese medicines. Then, protein-protein interaction analysis was conducted. Prediction of gene phenotypes was based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment scores. The total number of differentially expressed genes in the GEO database was 147. Combined with the GEO dataset and disease database, a total of 3533 depression-related genes were analyzed. After screening in COREMINE Medical, it was found that the top 4 traditional Chinese medicines with the highest frequency for depression were Paeonia lactiflora Pall., Crocus sativus L., Bupleurum chinense DC., and Cannabis sativa L. The compound target network consisted of 24 compounds and 138 corresponding targets, and the key targets involved PRKACA, NCOA2, PPARA, and so on. GO and KEGG analysis revealed that the most commonly used Chinese medicine could regulate multiple aspects of depression through these targets, related to metabolism, neuroendocrine function, and neuroimmunity. Prediction and analysis of protein-protein interactions resulted in the selection of nine hub genes (ESR1, HSP90AA1, JUN, MAPK1, MAPK14, MAPK8, RB1, RELA, and TP53). In addition, a total of four ingredients (petunidin, isorhamnetin, quercetin, and luteolin) from this Chinese medicine could act on these hub genes. Our research revealed the complicated antidepressant mechanism of the most commonly used Chinese medicines and also provided a rational strategy for revealing the complex composition and function of Chinese herbal formulas.
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DOI：
10.1186/2008-2231-22-16
发表时间：
2014-01-08
期刊：
Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences
影响因子：
--
作者：
Vahdati Hassani F;Naseri V;Razavi BM;Mehri S;Abnous K;Hosseinzadeh H
通讯作者：
Hosseinzadeh H
DOI：
10.5455/jice.20140903012921
发表时间：
2014-10
期刊：
Journal of intercultural ethnopharmacology
影响因子：
--
作者：
Jain D;Gangshettiwar A
通讯作者：
Gangshettiwar A
影响因子：
2.9
作者：
Gartlehner G;Wagner G;Matyas N;Titscher V;Greimel J;Lux L;Gaynes BN;Viswanathan M;Patel S;Lohr KN
通讯作者：
Lohr KN
影响因子：
14.9
作者：
Franceschini A;Szklarczyk D;Frankild S;Kuhn M;Simonovic M;Roth A;Lin J;Minguez P;Bork P;von Mering C;Jensen LJ
通讯作者：
Jensen LJ
槲皮素通过调节海马和 PFC 中与 BDNF 相关的 Copine 6 和 TREM1/2 失衡来减轻 LPS 诱导的大鼠抑郁样行为
影响因子：
5.6
作者：
Fang, Ke;Li, Hua-Rong;Ge, Jin-Fang
通讯作者：
Ge, Jin-Fang