ReviewFrontiers in endocrinology2026
Metabolites as key signaling mediators: rethinking diabetic kidney disease from a network perspective.
Review in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Diabetic kidney disease (DKD) remains the leading cause of end-stage renal disease worldwide. Current diagnostic approaches rely mainly on albuminuria and eGFR, but these are insufficiently sensitive for detecting early lesions, and treatment options remain limited. Metabolites are not merely byproducts of metabolism but serve as central signaling hubs that orchestrate DKD progression. These metabolites can act as receptor ligands, substrates for epigenetic modifications, and cargoes of extracellular vesicles. Together, they form a complex metabolic signaling network that links systemic metabolic disturbances to local kidney injury. Adopting this metabolite-centric new perspective transforms DKD from a collection of isolated pathways into a systemic, network-level disease. Recent advances in multidimensional metabolomics technologies-including static profiling, spatial metabolomics, metabolic flux analysis, and multi-omics approaches-enable us to dissect the metabolic network of DKD with unprecedented resolution. This review synthesizes current knowledge on metabolite-driven mechanisms, including the AGEs-RAGE pathway, lipotoxicity, amino acid reprogramming, and EV-mediated crosstalk. It systematically categorizes metabolite biomarkers according to their clinical functions, covering early detection, progression prediction, and pathogenic drivers. In addition, emerging therapeutic strategies targeting specific metabolic nodes are discussed. Finally, building on these established findings, we propose a hypothetical roadmap toward metabolic precision medicine. This framework hypothesizes the stratification of patients into distinct metabolic phenotypes, such as the high-TMAO, high-BCAAs, and high-AGEs subtypes. It suggests that treatment regimens could be selected based on the underlying metabolic mechanisms and that therapeutic responses could be assessed by dynamic monitoring of circulating metabolites. If validated, this conceptual strategy holds promise for overcoming current diagnostic and therapeutic bottlenecks and improving outcomes for patients with DKD.
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