Broad range metabolomics coupled with network analysis for explaining possible mechanisms of Er-Zhi-Wan in treating liver-kidney Yin deficiency syndrome of Traditional Chinese medicine

中医药 传统医学 医学 代谢组学 阴虚 生药学 西医 替代医学 生物信息学 生物 内科学 病理 生物化学 生物活性 体外
作者
Yuanyuan Zhai,Jia Xu,Li Feng,Qinan Liu,Weifeng Yao,Hui Li,Yudan Cao,Fang-Fang Cheng,Beihua Bao,Li Zhang
出处
期刊:Journal of Ethnopharmacology [Elsevier BV]
卷期号:234: 57-66 被引量:27
标识
DOI:10.1016/j.jep.2019.01.019
摘要

ETHNOPHARMACOLOGICAL RELEVANCE: Er-Zhi-Wan (EZW), a famous traditional Chinese formulation, is used to prevent, or to treat, various liver and kidney diseases for its actions of replenishing liver and kidney. However, the mechanisms of treating Liver-kidney Yin deficiency syndrome (LKYDS) of EZW have not been comprehensively investigated. AIM OF THE STUDY: In this study, a broad range metabolomics strategy coupled with network analysis was established to investigate possible mechanisms of EZW in treating LKYDS. MATERIALS AND METHOD: The rat models of LKYDS were established using the mixture of thyroxine and reserpine, and the changes of biochemical indices in serum and histopathology were detected to explore the effects of EZW. Next, a broad range metabolomics strategy based on RPLC-Q-TOF/MS and HILIC-Q-TOF/MS has been developed to find the possible significant metabolites in the serum and urine of LKYDS rats. Then, network analysis was applied to visualize the relationships between identified serum and urine metabolites and in detail to find hub metabolites, which might be responsible for the effect of EZW on rats of LKYDS. Furthermore, the shortest path of "disease gene-pathway protein-metabolite" was built to investigate the possible intervention path of EZW from the systematic perspective. RESULTS: Five hub metabolites, namely, arachidonic acid, L-arginine, testosterone, taurine and oxoglutaric acid, were screened out and could be adjusted to recover by EZW. After that, the shortest path starting from disease genes and ending in metabolites were identified and disclosed, and the genes of aging such as CAV1 and ACO1 were selected to explain the pathological mechanism of LKYDS. CONCLUSION: Broad range metabolomics coupled with network analysis could provide another perspective on systematically investigating the molecular mechanism of EZW in treating LKYDS at metabolomics level. In addition, EZW might prevent the pathological process of LKYDS through regulating the disturbed metabolic pathway and the aging genes such as CAV1 and ACO1, which may be potential targets for EZW in the treatment of LKYDS.
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