Diabetic kidney disease (DKD) is a microvascular complication of diabetes, characterized by region‑specific metabolic reprogramming that disrupts kidney function and markedly impairs patient prognosis. By enabling in situ visualization and analysis of metabolite distribution within kidney tissue, spatial metabolomics offers a unique advantage in detecting spatial heterogeneity in metabolic alterations, which is inaccessible through conventional metabolomics. This approach not only enhances the understanding of DKD pathophysiology but also provides a solid foundation for the development of precision nephrology strategies informed by spatial metabolite data. The present review discusses the fundamental workflows and spatial resolution capabilities of spatial metabolomics, summarizing the key metabolites involved in regional metabolic disruptions in multiple DKD animal models. Moreover, it highlights notable metabolites, including glucose, succinate, phosphatidylserine, lysophosphatidylglycerol, phosphatidylglycerol, sphingomyelin, phosphatidylcholine, phosphatidylethanolamine, taurine, glutamate, L‑carnitine, choline, adenosine monophosphate and guanosine monophosphate. The continued advancement of imaging technologies and data analysis methodologies is expected to further refine the spatial resolution and precision of spatial metabolomics, thereby facilitating its broader application in clinical practice.
Li et al. (Thu,) studied this question.
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