Chinese Journal of Integrative Medicine 2011-05-01

Evaluation study on urine metabolomics in yinhuang rat model induced by triplet factors of rhubarb, ethanol, and α-nephthylisothiolyanate.

Xin Tong, Hui Sun, Guang-li Yan, Wei Dong, Wen-jun Sun, Yang Yu, Ping Wang, Ying Han, Xi-jun Wang

Index: Chin. J. Integr. Med. 17(5) , 369-75, (2011)

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Abstract

To ascertain the biomarkers capable to characterize the animal composite model of Chinese medicine (CM) yinhuang syndrome induced by triplet factors of rhubarb, ethanol, and α-nephthylisothiolyanate (abbreviated as R, E, and A below) through metabolomic study and to evaluate the established model by means of studying the sources of markers based on the changes of metabolites produced from various combinations of the three modeling drugs.Eighty Wistar rats allocated equally in eight groups (A-H) were treated with saline, R+E+A, R, E, A, R+E, R+A, and E+A, respectively. Rats' 12 h urine in the 14 successive experimental days were collected separately using metabolic cages and analyzed by ultra performance liquid chromatograph/time of flight mass spectrometer (UPLC/TOF-MS) to create the metabolic contour graph of urine in different groups for identifying the differences between them. The similarities and differences of metabolic network among various groups were represented from microcosmic viewpoint by pattern recognition method (principal component analysis).Controlled by group A, the landing points in principal component map of various groups were apparently assorted, especially obvious on the 14th day; 19 biomarkers, which capable to represent the genesis and development process of the yinhuang syndrome in the triplet factors-induced rat model, were identified.Metabolomic method is successfully used in evaluating the animal model of CM syndrome. Furthermore, according to the holistic view and substance changes in vivo, the influences of disease on organism were comprehensively analyzed, and the pathogenic mechanism of CM yinhuang syndrome was explored at the level of metabolomics in vivo as well.


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