Literature DB >> 32072764

Untargeted metabolomic study on the insomnia effect of Suan-Zao-Ren decoction in the rat serum and brain using ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry combined with data processing analysis.

Yiyang Du1, Bo Wu1, Feng Xiao1, Tingxu Yan1, Qing Li2, Ying Jia1, Kaishun Bi2, Bosai He1.   

Abstract

Insomnia is a common clinical disease that can seriously damage the normal lives of sufferers. Suan-Zao-Ren decoction has been used to treat insomnia for a long time. However, the underlying molecular mechanism of Suan-Zao-Ren decoction is still not clear. In this study, the nontargeted metabolomics based on high-resolution mass spectrometry and multiple statistical approaches were initially used to investigate the changes of potential serum and brain biomarkers and metabolic pathways in the insomnia model rat. Principal component analysis-discriminate analysis indicated that the Suan-Zao-Ren decoction treatment improved the metabolic phenotype insomnia. Moreover, the heatmap analysis identified the most important biomarkers involved in insomnia. According to the pathway analysis, phenylalanine metabolism, tryptophan metabolism, and so on were recognized as the most affected metabolic pathways associated with insomnia disease. These findings provided a comprehensive understanding of the regulative effects of Suan-Zao-Ren decoction on the host metabolic phenotype of the insomnia rats. Our work demonstrated that the metabolomics approach is a promising tool that could help us to conduct the exploration of the therapeutic effects and mechanism of traditional Chinese medicines.
© 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  biomarkers; metabolic pathways; metabolomics; traditional Chinese medicine

Mesh:

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Year:  2020        PMID: 32072764     DOI: 10.1002/jssc.201901002

Source DB:  PubMed          Journal:  J Sep Sci        ISSN: 1615-9306            Impact factor:   3.645


  5 in total

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5.  Suan-Zao-Ren decoction for insomnia: A protocol for a systematic review and meta-analysis.

Authors:  Zhijian Song; Ping Fan; Qi Zhang; Yang Yang; Qinan Zhan; Xueyu Liu; Yurong Xiong
Journal:  Medicine (Baltimore)       Date:  2020-08-21       Impact factor: 1.817

  5 in total

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