Identifying the mechanism underlying antidepressant-like effects of loganin by network pharmacology in combination with experimental validation. (5th December 2021)

• Record Type: Journal Article
• Authors: Xia, Cong-Yuan; Xu, Jie-Kun; Li, Li; Lian, Wen-Wen; Yan, Yu; Ma, Bing-Zhi; He, Jun; Zhang, Wei-Ku
• Is Part Of: Journal of ethnopharmacology. Volume 281(2021)
• Publication Date: 2021-12-05
• Subjects: Loganin -- Antidepressant -- Inflammation -- Depression -- Network pharmacology -- Microglia phenotype; CO Cornus officinalis Sieb. et Zucc -- WHO World Health Organization -- LPS Lipopolysaccharide -- BBB blood-brain barrier -- PPI Protein–protein interaction -- OMIM Online Mendelian Inheritance in Man -- KEGG Kyoto Encyclopedia of Genes and Genomes -- qRT-PCR Quantitative Real-Time PCR -- SD standard deviation -- CCK-8 Cell counting kit-8 -- ASPL Average shortest path length -- BC Betweenness centrality -- CC Closeness centrality -- HPLC high performance liquid chromatography; Ethnopharmacology -- Periodicals; Pharmacognosy -- Periodicals; Herbs -- Periodicals; Herbs -- Periodicals; Pharmacognosy -- Periodicals; Pharmacognosie -- Périodiques; Herbes -- Périodiques; 615.1
• DOI: 10.1016/j.jep.2021.114526
• Languages: English
• ISSNs: 0378-8741

Abstract

Abstract: Ethnopharmacological relevance: Loganin, an iridoid glycoside, is one of the quality control indexes of Cornus officinalis Sieb. et Zucc. Increasing evidence emphasize the important role of inflammation in the pathology of depression, which links depression with other chronic diseases. Loganin prevents inflammatory response in multiple diseases and reverses depressive-like behaviors. However, the mechanisms underlying antidepressant-like effects of loganin for the treatment of inflammation-associated depression are not utterly understood. Aim of the study: The present study was designed to predict the potential targets of loganin against inflammation-associated depression using a network pharmacology approach. Materials and methods: Pharmmapper and Uniport were used to predict loganin-related targets. Targets of inflammation were identified through GeneCards databases and Online Mendelian Inheritance in Man (OMIM). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to identify the potential mechanism. Finally, qRT-PCR and ELISA were used to confirm the role of loganin on these targets. Results: There were 15 nodes in the loganin-inflammation-depression intersection targets network. In the network, the degree value of CTNNB1 was above 3. Among top ten pathways identified by KEGG analysis, Th1/Th2 cell differentiation and IL-17 signaling pathways were related with both inflammation and depression. As indicated by qRT-PCR results, loganin increased CTNNB1 mRNA level. Moreover, loganin elevated M2 markers of microglia but decreased M1 markers of microglia against lipopolysaccharide (LPS), indicated by qRT-PCR results and ELISA results. Conclusion: CTNNB1 was the main target of loganin. Loganin alleviated LPS-induced inflammation through inhibiting M1 polarization of microglia. Our results provide a better understanding of loganin-induced antidepressant-like effects for the treatment of inflammation-associated depression. Graphical abstract: Image 1