Establishing ¹H nuclear magnetic resonance based metabonomics fingerprinting profile for spinal cord injury: a pilot study.
- Author:
Hua JIANG
1
;
Jin PENG
;
Zhi-yuan ZHOU
;
Yu DUAN
;
Wei CHEN
;
Bin CAI
;
Hao YANG
;
Wei ZHANG
Author Information
- Publication Type:Journal Article
- MeSH: Amino Acids; metabolism; Animals; Magnetic Resonance Spectroscopy; methods; Male; Metabolomics; methods; Pilot Projects; Principal Component Analysis; Rats; Rats, Sprague-Dawley; Spinal Cord Injuries; metabolism
- From: Chinese Medical Journal 2010;123(17):2315-2319
- CountryChina
- Language:English
-
Abstract:
BACKGROUNDSpinal cord injury (SCI) is a complex trauma that consists of multiple pathological mechanisms involving cytotoxic, oxidation stress and immune-endocrine. This study aimed to establish plasma metabonomics fingerprinting atlas for SCI using (1)H nuclear magnetic resonance (NMR) based metabonomics methodology and principal component analysis techniques.
METHODSNine Sprague-Dawley (SD) male rats were randomly divided into SCI, normal and sham-operation control groups. Plasma samples were collected for (1)H NMR spectroscopy 3 days after operation. The NMR data were analyzed using principal component analysis technique with Matlab software.
RESULTSMetabonomics analysis was able to distinguish the three groups (SCI, normal control, sham-operation). The fingerprinting atlas indicated that, compared with those without SCI, the SCI group demonstrated the following characteristics with regard to second principal component: it is made up of fatty acids, myc-inositol, arginine, very low-density lipoprotein (VLDL), low-density lipoprotein (LDL), triglyceride (TG), glucose, and 3-methyl-histamine.
CONCLUSIONSThe data indicated that SCI results in several significant changes in plasma metabolism early on and that a metabonomics approach based on (1)H NMR spectroscopy can provide a metabolic profile comprising several metabolite classes and allow for relative quantification of such changes. The results also provided support for further development and application of metabonomics technologies for studying SCI and for the utilization of multivariate models for classifying the extent of trauma within an individual.