Metabolomics research on time-selected combination of Liuwei Dihuang and Jinkui Shenqi pills in treating kidney deficiency and aging by chemometric methods
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文摘
Jinkui Shenqi pill (JKSQ) and Liuwei Dihuang (LWDH) pills are ancient traditional Chinese medicines (TCMs), which are usually used for the treatment of kidney deficiency for thousands of years in China. Time-selected combination of LWDH and JKSQ pills in treating kidney deficiency and aging is one of the features of traditional Chinese medicines (TCMs). However, the molecular mechanisms of time-selected combination remain unclear. In this work, UHPLC-QTOF/MS based metabolomics research was conducted to evaluate the therapeutic effect of LWDH, JKSQ pills and their combinations on kidney deficiency in Sprague-Dawley rats induced by d-galactose and Dexamethasone. Based on peak areas of serum extracts, analysis of variance (ANOVA) and graphical index of separation (GIOS) were employed to select the significant variables for kidney deficiency and aging and principal component projection (PCP) was subsequently applied to evaluate the influence of drugs on endogenous metabolites. 10 endogenous metabolites from 22 important ions were identified via database search. The score plot of PCA shows that nourishing Yang-nourishing Yin group shows the strongest rehabilitation for metabolic disorder induced by kidney deficiency and aging, which is consistent with the classic theories of traditional Chinese medicine. Moreover, metabolic pathway function analysis indicates that kidney deficiency and aging might possess closed relationships with lipid metabolism and energy metabolism. In this work, the change trends of potential biomarkers after administration provide molecular evidence for combined administration of Jinkui Shenqi pill in the morning and Liuwei Dihuang pill at night for the patients with kidney deficiency. The method proposed in this study may provide inspiration for evaluation of the therapeutic effect of Chinese medicines by comparing the rehabilitation of potential biomarkers.
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