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Diabetic kidney disease (DKD) is the leading cause of chronic kidney disease and end-stage kidney disease. Renin&ndash, angiotensin system inhibitors such as losartan are the predominant therapeutic options in clinical practice to treat DKD. Therefore, it is necessary to identify DKD-related metabolic profiles that are affected by losartan. To investigate the change in metabolism associated with the development of DKD, we performed global and targeted metabolic profiling using 800 MHz nuclear magnetic resonance spectroscopy of urine samples from streptozotocin-induced diabetic mice (DM) with or without losartan administration. A principal component analysis plot showed that the metabolic pattern in the losartan-treated diabetic mice returned from that in the DM group toward that in the control mice (CM). We found that 33 urinary metabolites were significantly changed in DM compared with CM, and the levels of 16 metabolites among them, namely, glucose, mannose, myo-inositol, pyruvate, fumarate, 2-hydroxyglutarate, isobutyrate, glycine, threonine, dimethylglycine, methyldantoin, isoleucine, leucine, acetylcarnitine, 3-hydroxy-3-methylglutarate, and taurine, shifted closer to the control level in response to losartan treatment. Pathway analysis revealed that these metabolites were associated with branched-chain amino acid degradation, taurine and hypotaurine metabolism, glycine, serine, and threonine metabolism, the tricarboxylic acid cycle, and galactose metabolism. Our results demonstrate that metabolomic analysis is a useful tool for identifying the metabolic pathways related to the development of DKD affected by losartan administration and may contribute to the discovery of new therapeutic agents for DKD.

Xanthii Fructus (XF) is known as a medicinal plant. It has been used as a traditional medicine because of its high biological efficacy. However, there have been few comprehensive studies on the specific chemical composition of the plant and consequently, the information is lacking for the mechanism of the natural product metabolites in humans. In this study, an efficient analytical method to characterize and discriminate two species of Xanthii Fructus (Xanthium canadense Mill. and Xanthium sibiricum Patrin ex Widder) was established. Volatile organic compounds (VOCs), polar metabolites, and fatty acids were classified by integrated sample preparation, which allowed a broad range for the detection of metabolites simultaneously. Gas chromatography-mass spectrometry (GC-MS) followed by a multivariate statistical analysis was employed to characterize the chemical compositions and subsequently to discriminate between the two species. The results demonstrate that the two species possess obviously diverse chemical characteristics of three different classifications, and discriminant analysis was successfully applied to a number of chemical markers that could be used for the discrimination of the two species. Additional quantitative results for the selected chemical markers consistently showed significant differences between the two species.