Diabetic kidney disease (DKD), a highly prevalent complication of diabetes mellitus, is a major cause of mortality in patients. However, identifying circulatory markers to diagnose DKD requires a thorough understanding of the metabolic mechanisms of DKD. In this study, we performed ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) to reveal altered metabolic profiles of amino acids (AAs) in patients with DKD. We found decreased plasma levels of histidine and valine, increased urine levels of proline, decreased urine levels of histidine and valine, and increased saliva levels of arginine in patients with DKD compared with the levels in patients with type 2 diabetes mellitus (T2DM) and in healthy controls. Our analyses of the key metabolites and metabolic enzymes involved in histidine and valine metabolism indicated that the AAs level alterations may be due to enhanced carnosine hydrolysis, decreased degradation of homocarnosine and anserine, enhanced histidine methylation, and systemic enhancement of valine metabolism in patients with DKD. Notably, we generated a distinct diagnostic model with an AUC of 0.957 and an accuracy up to 92.2% on the basis of the AA profiles in plasma, urine and saliva differing in patients with DKD using logistic regression and receiver operating characteristic analyses. In conclusion, our results suggest that altered AA metabolic profiles are associated with the progression of DKD. Our DKD diagnostic model on the basis of AA levels in plasma, urine, and saliva may provide a theoretical basis for innovative strategies to diagnose DKD that may replace cumbersome kidney biopsies.
Keywords: Amino acids; Diabetic kidney disease; Diagnostic model; LC–MS/MS; Metabolomics.
© 2023. The Author(s).