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利用整合肠道微生物组、代谢组学和网络药理学探究雷公藤多苷抗阿尔茨海默病机制
Authors Zhang Y, Silang Q, Wang Y, Wang N, Gesang L, Tang L, Liu L
Received 6 June 2025
Accepted for publication 26 August 2025
Published 3 September 2025 Volume 2025:21 Pages 1911—1933
DOI https://doi.org/10.2147/NDT.S537129
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Professor Taro Kishi
Yongcang Zhang,1 Quxi Silang,2 Yan Wang,3 Niannian Wang,4 Luobu Gesang,5 Liang Tang,3 Lan Liu1
1Medical College, Tibet University, Lhasa, Tibet, People’s Republic of China; 2Clinical Laboratory, Maternal and Child Health Hospital of Tibet, Lhasa, Tibet, People’s Republic of China; 3Hunan Provincial University Key Laboratory of the Fundamental and Clinical Research on Neurodegenerative Diseases, Changsha Medical University, Changsha, People’s Republic of China; 4Plateau Brain Science Research Center, Tibet University, Lhasa, Tibet, People’s Republic of China; 5Department of research and development, Tibet Ganlu Tibetan Medicine Co, LTD, Lhasa, Tibet, People’s Republic of China
Correspondence: Lan Liu, Medical College, Tibet University, No. 36, Jiangsu road, Chengguan district, Lhasa, Tibet, 850000, People’s Republic of China, Email liulanyxy@utibet.edu.cn
Background: Tripterygium glycoside (TG) has been reported to have the effect of ameliorating Alzheimer’s disease (AD)-like symptoms in mice model. However, the underlying mechanism is largely unknown. This study aimed to investigate the potential mechanism of TG against AD by integrating metabolomics, 16s rRNA sequencing, network pharmacology, molecular docking, and molecular dynamics simulation.
Methods: Memory and cognitive functions were assessed in mice via the Morris water maze. The pathological changes were assessed using hematoxylin and Nissl’s straining. Pathological changes in p-Tau and Aβ1-42 were assessed using immunohistochemistry, immunofluorescence, ELISA, and Western blotting. 16S rRNA sequencing and metabolomics were performed to analyze alterations in the structure of gut microbiota and hippocampus metabolites. Network pharmacology, molecular docking, and molecular dynamics simulation were performed to determine the putative molecular regulatory mechanism of TG in treating AD.
Results: TG significantly could inhibit neuron loss, improved cognitive and memory functions, and significantly reduce the expression of p-Tau and Aβ1-42. In addition, 16s rRNA analysis revealed that TG could reverse AD-induced gut microbiota dysbiosis in AD model mice by reducing the abundance of Alistipes. Furthermore, metabolomic analysis revealed that TG may reverse AD-induced metabolic disorders by regulating glycerophospholipid metabolism. And spearman analysis revealed that glycerophospholipids metabolism might closely related to Alistipes. Moreover, network pharmacology, molecular docking, and molecular dynamics simulation analyses indicated that TG might regulate lipid metabolism-related pathways via SRC for the treatment of AD.
Conclusion: TG may serve as a potential therapeutic drug for preventing AD via the microbiota-gut-brain axis.
Keywords: tripterygium glycoside, Alzheimer’s disease, gut microbiota, metabolomic, glycerophospholipids metabolism