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Zhongguo Zhong Xi Yi Jie He Za Zhi ; 35(12): 1427-32, 2015 Dec.
Article in Chinese | MEDLINE | ID: mdl-26882602

ABSTRACT

OBJECTIVE: To observe metabolomic changes in urine of chronic superficial gastritis (CSG) patients with Pi-qi deficiency syndrome (PQDS) or Pi-Wei dampness-heat syndrome (PWDHS), thereby providing scientific evidence for syndrome typing of them. METHODS: Urine samples were collected from CSG patients with PQDS/PWDHS and healthy volunteers, 10 in each group. Proton nuclear magnetic resonance spectroscopy (1H-NMR) based metabonomic analysis was performed on urine samples. Contents of related biomarkers were analyzed by principal component analysis (PCA), partial least square discriminant analysis (PLS-DA), and urivariate statistical analysis. RESULTS: PLS-DA analysis showed that metabolites among CSG patients with PQDS/PWDHS and healthy volunteers could be mutually distinguished. Seven differentially identified metabolites were screened from urines of CSG patients with PQDS and healthy volunteers included glutamate, methionine, α-oxoglutarate, dimethylglycine, creatinine, taurine, and glucose. Four differentially identified metabolites were screened from urines of CSG patients with PWDHS and healthy volunteers included 2-hydroxybutyric acid, trimethylamine oxide, taurine, and hippuric acid. Eleven differentially identified metabolites were screened from urines of CSG patients with PQDS and PWDHS included fucose, ß-hydroxybutyric acid, alanine, glutamate, methionine, succinic acid, citric acid, creatinine, glucose, hippuric acid, and lactic acid. CONCLUSION: The metabolic differences of CSG patients PQDS and PWDHS mainly manifested in glycometabolism, lipid metabolism, and amino acids catabolism, and 1H-NMR based metabonomics may be used in classified study of Chinese medical syndrome typing.


Subject(s)
Gastritis/urine , Medicine, Chinese Traditional , Proton Magnetic Resonance Spectroscopy , Biomarkers/urine , Discriminant Analysis , Hot Temperature , Humans , Hydroxybutyrates , Ketoglutaric Acids , Least-Squares Analysis , Metabolome/physiology , Metabolomics , Principal Component Analysis , Qi , Syndrome
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