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基于GC-MS分析的Corilagin暴露小鼠代谢变化的综合分析
Authors Xu B, Wang C, Zhu X, Zhu L , Han G, Cui C
Received 14 June 2024
Accepted for publication 14 January 2025
Published 21 January 2025 Volume 2025:19 Pages 389—404
DOI https://doi.org/10.2147/DDDT.S482510
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Prof. Dr. Georgios Panos
Biao Xu,1,* Changshui Wang,2,* Xiaodong Zhu,2 Li Zhu,3 Guangkui Han,2 Changmeng Cui2
1Clinical Medical School, Jining Medical University, Jining, 272067, People’s Republic of China; 2Department of Neurosurgery, Affiliated Hospital of Jining Medical University, Jining Medical University, Jining, 272000, People’s Republic of China; 3Translational Pharmaceutical Laboratory, Jining No. 1 People’s Hospital, Shandong First Medical University, Jining, 272000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Changmeng Cui; Guangkui Han, Department of Neurosurgery, Affiliated Hospital of Jining Medical University, 89 Guhuai Road, Jining, Shandong, 272000, People’s Republic of China, Tel +86 0537 2908518, Email cmcuidr1989@163.com; guangkui_han@163.com
Background: Corilagin is widely distributed in various medicinal plants. In recent years, numerous pharmacological activities of Corilagin have been reported, including anti-inflammatory, antiviral, hepatoprotective, anti-tumor, and anti-fibrosis effects. However, there is still a need for systematic metabolomics analysis to further elucidate its mechanisms of action. The aim of this study was to explore the pharmacological mechanism of Corilagin.
Methods: This study utilized gas chromatography-mass spectrometry (GC-MS) to analyze central target tissues, comprehensively exploring the pharmacological mechanism of Corilagin in mouse models. We identified the differential metabolites by multivariate analyses, which include principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Using MetaboAnalyst 5.0 and the KEGG database was used to depict the 12 key metabolic pathways.
Results: Compared with the control group, the Corilagin induced 20, 9, 11, 7, 16, 19, 14, 15, and 16 differential metabolites in the intestine, lung, kidney, stomach, heart, liver, hippocampus, cerebral cortex, and serum, respectively. And 12 key pathways involving glucose metabolism, lipid metabolism, and amino acid metabolism were identified following Corilagin treatment.
Conclusion: This research provides insight into the action mechanism of Corilagin’s anti-oxidative, anti-inflammatory, anti-atherosclerotic, hepatoprotective, anti-tumor, and neuroprotective properties.
Keywords: Corilagin, gas chromatography-mass spectrometry, metabolomics, amino acids, pharmacological mechanism