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H NMR spectroscopy in combination with multivariate statistical analysis was applied to explore the metabolic variability in urine and serum of high fat-fed rats relative to normal chow-fed ones. Metabolites contributing to intergroup discrimination identified by partial least squares discriminant analysis include 3-hydroxybutyrate, glutamate, glutamine, citrate, choline, hippurate, alanine, lactate, creatinine, taurine, acetate, etc. The aging effect along with long-term feeding was delineated with metabolic trajectory in principal component analysis score plot and age-related differences on metabolic profiling under different dietary intervention were recognised. The identified metabolites responsible for obesity were all imported into a web tool for network-based interpretation of compound lists to interpret their functional context, molecular mechanisms and disturbed signalling pathway globally and systematically. The results are useful for interpreting the pathology of obesity and further probing into the relationship between dietary-induced obesity and type 2 diabetes mellitus. [ABSTRACT FROM AUTHOR]

Background: Hepatic alveolar echinococcosis (HAE) is caused by the growth of Echinococcus multilocularis larvae in the liver. It is a chronic and potentially lethal parasitic disease. Early stage diagnosis for this disease is currently not available due to its long asymptomatic incubation period. In this study, a proton nuclear magnetic resonance (1H NMR)-based metabolomics approach was applied in conjunction with multivariate statistical analysis to investigate the altered metabolic profiles in blood serum and urine samples obtained from HAE patients. The aim of the study was to identify the metabolic signatures associated with HAE. Results: A total of 21 distinct metabolic differences between HAE patients and healthy individuals were identified, and they are associated with perturbations in amino acid metabolism, energy metabolism, glyoxylate and dicarboxylate metabolism. Furthermore, the present results showed that the Fischer ratio, which is the molar ratio of branched-chain amino acids to aromatic amino acids, was significantly lower (P < 0.001) in the blood serum obtained from the HAE patients than it was in the healthy patient group. Conclusions: The altered Fischer ratio, together with perturbations in metabolic pathways identified in the present study, may provide new insights into the mechanistic understanding of HAE pathogenesis and potential therapeutic interventions. [ABSTRACT FROM AUTHOR]

Abstract: Statistical two-dimensional correlation spectroscopy combined with pattern recognition is demonstrated for coanalysis of NMR spectroscopic data from different sources. The urine and serum 1H NMR spectra from metabolomics datasets of diabetes and hyperthyroidism are taken as examples. The intrinsic covariance of certain molecules between urine and serum spectra is identified. The highly urine-serum-correlated metabolites are further analyzed by using the projection to latent structure discriminant analysis (PLS-DA) method. To illustrate the applicability of the method, the metabolomics datasets of diabetes and hyperthyroidism are imported separately to calculate the corresponding two-dimensional urine-serum correlation coefficient matrixes. The results show that creatinine (δ 4.08) and succinate (δ 2.45) are found to be highly correlated between urine and serum from diabetes patients, and choline (δ 3.21) and pyruvate (δ 2.33) are highly correlated between urine and serum from hyperthyroidism patients. This study offers a new angle of view for interpreting metabolomics data and demonstrates the potential of the correlation analysis of spectra from different biological sources as a new systems biology tool. [Copyright &y& Elsevier]