Metabolites as key signaling mediators: rethinking diabetic kidney disease from a network perspective
- 1State Key Laboratory of Integration and Innovation of Classic Formula and Modern Chinese Medicine, Heilongjiang University of Chinese Medicine
- 2Qiqihar Medical University
- 3Heilongjiang University of Chinese Medicine
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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BibTeX
@article{li2026metabolites,
title = {{Metabolites as key signaling mediators: rethinking diabetic kidney disease from a network perspective}},
author = {Xin Li and Xu Wang and Cheng Fang and Zhonghong Yan and Lei Liu and Jinwei Han and Liangyou Zhao and Xiuhong Wu},
journal = {Frontiers in Endocrinology},
year = {2026},
month = oct,
doi = {10.3389/fendo.2026.1969901},
url = {https://www.frontiersin.org/articles/10.3389/fendo.2026.1969901/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Metabolites as key signaling mediators: rethinking diabetic kidney disease from a network perspective
AU - Xin Li
AU - Xu Wang
AU - Cheng Fang
AU - Zhonghong Yan
AU - Lei Liu
AU - Jinwei Han
AU - Liangyou Zhao
AU - Xiuhong Wu
PY - 2026
DA - 2026/10/23
JO - Frontiers in Endocrinology
DO - 10.3389/fendo.2026.1969901
UR - https://www.frontiersin.org/articles/10.3389/fendo.2026.1969901/full
AB - 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.
SN - 1664-2392
ER -