Abstract
Diabetic nephropathy (DN), a leading cause of chronic kidney disease and end-stage kidney disease (ESKD), poses global health challenges given its increasing prevalence. DN increases the risk of mortality and cardiovascular events. Early identification and appropriate DN management are crucial. However, current diagnostic methods rely on general traditional markers, highlighting the need for DN-specific diagnostics. Metabolomics, the study of small molecules produced by metabolic activity, promises to identify specific biomarkers that distinguish DN from other kidney diseases, decode the underlying disease mechanisms, and predict the disease course. Profound changes in metabolic pathways are apparent in individuals with DN, alterations in the tricarboxylic acid cycle and amino acid and lipid metabolism, suggestive of mitochondrial dysfunction. Metabolomics aids prediction of chronic kidney disease progression; several metabolites serve as indicators of renal functional decline and the risk of ESKD. Integration of such information with other omics data will further enhance our understanding of DN, paving the way to personalized treatment. In summary, metabolomics and multi-omics offer valuable insights into DN and are promising diagnostic and prognostic tools.