Plasma metabolic fingerprinting of childhood obesity by GC/MS in conjunction with multivariate statistical analysis.

Metabolic fingerprinting is a powerful tool for exploring systemic metabolic perturbations and potential biomarkers, thus may shed light on the pathophysiological mechanism of diseases. In this work, a new strategy of metabolic fingerprinting was proposed to exploit the disturbances of metabolic patterns and biomarker candidates of childhood obesity. Plasma samples from children with normal weight, overweight and obesity were first profiled by GC/MS. ULDA (uncorrelated linear discriminant analysis) then revealed that the metabolic patterns of the three groups were different. Furthermore, several metabolites, say isoleucine, glyceric acid, serine, 2,3,4-trihydroxybutyric acid and phenylalanine were screened as potential biomarkers of childhood obesity by both ULDA and CCA (canonical correlation analysis). CCA also shows satisfactory correlation between the metabolic patterns and clinical parameters, and the results further suggest that WHR (waist-hip ratio) together with TG (total triglycerides), TC (total cholesterol), HDL (high density lipoprotein) and LDL (low density lipoprotein) were the most important parameters which are associated closely with the metabolic perturbations of childhood obesity, so as to be paid more attention for dealing with metabolic disturbances of childhood obesity in clinical practice rather than regularly monitored BMI (body-mass index). The results have demonstrated that the proposed metabolic fingerprinting approach may be a useful tool for discovering metabolic abnormalities and possible biomarkers for childhood obesity.