UPLC-Q-TOF/MS Based Plasma Metabolomics for Identification of Paeonol’s Metabolic Target in Endometriosis

丹皮酚 子宫内膜异位症 代谢组学 药理学 化学 医学 内科学 病理 色谱法 替代医学
作者
Jing Liu,Di Yang,Chengyu Piao,Xu Wang,Xiaolan Sun,Yongyan Li,Shuxiang Zhang,Xiuhong Wu
出处
期刊:Molecules [MDPI AG]
卷期号:28 (2): 653-653 被引量:1
标识
DOI:10.3390/molecules28020653
摘要

Endometriosis is a common gynecological illness in women of reproductive age that significantly decreases life quality and fertility. Paeonol has been shown to play an important part in endometriosis treatments. Understanding the mechanism is critical for treating endometriosis. In this study, autologous transplantation combined with a 28 day ice water bath was used to create a rat model of endometriosis with cold clotting and blood stagnation. The levels of estradiol and progesterone in plasma were detected by ELISA, and the pathological changes of ectopic endometrial tissue were examined by H&E staining, which proved the efficacy of paeonol. For metabolomic analysis of plasma samples, UPLC-Q/TOF-MS was combined with multivariate statistical analysis to identify the influence of paeonol on small molecule metabolites relevant to endometriosis. Finally, the key targets were screened using a combination of network pharmacology and molecular docking approaches. The results showed that the pathological indexes of rats were improved and returned to normal levels after treatment with paeonol, which was the basis for confirming the efficacy of paeonol. Metabolomics results identified 13 potential biomarkers, and paeonol callbacks 7 of them, involving six metabolic pathways. Finally, four key genes were found for paeonol therapy of endometriosis, and the results of molecular docking revealed a significant interaction between paeonol and the four key genes. This study was successful in establishing a rat model of endometriosis with cold coagulation and blood stagnation. GCH1, RPL8, PKLR, and MAOA were the key targets of paeonol in the treatment of endometriosis. It is also demonstrated that metabolomic techniques give the potential and environment for comprehensively understanding drug onset processes.
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