Issue 54, 2017, Issue in Progress

1H NMR studies on serum metabonomic changes over time in a kidney-Yang deficiency syndrome model

Abstract

The central aim of this study was to investigate metabolite changes in metabolic pathways via metabonomic approaches in rats suffering from Kidney-Yang Deficiency Syndrome (KYDS) induced by hydrocortisone. Metabonomic analysis using 1H NMR is a well-established approach for the study of metabolic changes in biofluids. In our study, serum samples were obtained at three specific time points during the progression of KYDS, and individual 1H NMR spectra were acquired and statistically assessed using two multivariate analyses (MVA): principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA). The profiles on the 15th, 23rd, and 30th day for each sample could be classified, further revealing progression axes from a normal status to KYDS status. Consequently, significant changes in seventeen metabolites, i.e. lactate, valine, alanine, methionine, succinate, glutamine, 3-hydroxybutyrate, creatine, choline, HDL, LDL, VLDL, TMAO, betaine, tyrosine, citrate, and glycerol, were identified. These biochemical changes were found to be directly related to disturbances in energy metabolism, amino acid metabolism, lipid metabolism, choline metabolism, and gut metabolism. We further determined that lactate and the other 16 metabolic markers may be used as specific markers of KYDS over time. Overall, this study demonstrates that this metabonomic method is a valuable tool for studying the pathologic changes of the Chinese medicine syndrome and the underlying mechanisms of KYDS.

Graphical abstract: 1H NMR studies on serum metabonomic changes over time in a kidney-Yang deficiency syndrome model

Supplementary files

Article information

Article type
Paper
Submitted
10 Apr 2017
Accepted
22 Jun 2017
First published
10 Jul 2017
This article is Open Access
Creative Commons BY license

RSC Adv., 2017,7, 34251-34261

1 H NMR studies on serum metabonomic changes over time in a kidney-Yang deficiency syndrome model

R. Chen, J. Wang, C. Liao, N. Ma, L. Zhang and X. Wang, RSC Adv., 2017, 7, 34251 DOI: 10.1039/C7RA04057A

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