Metabonomic study of blood plasma in the assessment of liver graft function.
- Author:
Qi ZHANG
1
;
Jing GAO
;
Ling LI
;
He-Bing CHEN
;
Xin-Quan LI
;
Xian-Zhong YAN
Author Information
- Publication Type:Journal Article
- MeSH: Acetone; blood; chemistry; Alanine; blood; chemistry; Biomarkers; blood; chemistry; Blood Glucose; chemistry; metabolism; Carcinoma; blood; chemistry; surgery; Choline; blood; chemistry; Glutamine; blood; chemistry; Humans; Lactic Acid; blood; chemistry; Liver; metabolism; Liver Neoplasms; blood; chemistry; surgery; Liver Transplantation; physiology; Magnetic Resonance Spectroscopy; Male; Metabolome; Succinic Acid; blood; chemistry; Treatment Outcome; Valine; blood; chemistry
- From: Acta Academiae Medicinae Sinicae 2007;29(6):725-729
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo access the capability of 1H nuclear magnetic resonance (NMR) -based metabonomics in the evaluation of graft function in the perioperation period of liver transplantation.
METHODSPlasma samples of 15 male primary hepatic carcinoma patients were collected for clinical biochemical analysis and 1H NMR spectroscopy 1 day before operation, 1 day and 1 week after the operation. The NMR data were analyzed using principal component analysis.
RESULTSMetabonomic analysis indicated that, compared with those before operation, blood concentrations of valine, alanine, acetone, succinic acid, glutamine, choline, lactate, and glucose increased significantly 1 day after transplantation. One week later, the levels of lipids and choline increased notably, while those of glucose and amino acids decreased. Principal component analysis showed significant difference between metabolic profiles of plasma samples of variant periods of liver transplantation, due to the variation of the levels of glucose, lipids, lactate, and choline. A good agreement was observed between clinical chemistry and metabonomic data.
CONCLUSIONSMetabonomic analysis can clearly identify the difference between the plasma samples of primary hepatic carcinoma patients at different time during the perioperation period of liver transplantation. It therefore may be a promising new technology in predicting the outcomes of liver transplantation.