Identification of the Perturbed Metabolic Pathways Associating With Renal Fibrosis and Evaluating Metabolome Changes of Pretreatment With Astragalus polysaccharide Through Liquid Chromatography Quadrupole Time-Of-Flight Mass Spectrometry

Renal fibrosis is glomerulosclerosis and renal tubulointerstitial fibrosis caused by the increase of interstitial cells and intercellular substances and the accumulation of extracellular matrix, and is a common pathological manifestation of renal disease progressing to end-stage renal failure. It has proved that Astragalus polysaccharide (AP) has curative effect on renal disease; however, its therapeutic mechanism on renal fibrosis is still unclear. Metabolomics approach provides an opportunity to identify novel molecular biomarkers. The purpose of this study is to study the changes of serum metabolic profile of rats with unilateral tubal ligation and replication of renal fibrosis model and the therapeutic effect of AP on it. The blood samples of rats in the control group, renal fibrosis model group, and AP treatment group collected on the 21st day were analyzed by metabolomics method based on UPLC-Q-TOF-MS. Principal component analysis (PCA) showed that clustering was obvious and significantly separated, and paired partial least squares discriminant analysis (OPLS-DA) was used for further analysis. Combined with the network databases such as HMDB and KEGG and a large number of literatures, 32 potential biomarkers related to renal fibrosis were preliminarily screened out and further verified by MS/MS secondary debris information. After pretreatment with AP, 20 biomarkers were significantly regulated, and correlated with phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, arachidonic acid metabolism, etc. It also revealed the metabolic changes of renal fibrosis and intervention effect of AP. These data uncover a link between metabolism and the molecular mechanism with potential implications in the understanding of the intervention effect of AP. Conclusively, UPLC-Q-TOF-MS–based metabolomics can be valuable and promising strategy to understand the disease mechanism and natural drug pretreatment.