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Spatially segregated multiomics decodes metformin-mediated function-specific metabolic characteristics in diabetic kidney disease

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摘要 Understanding the specific metabolic changes in multiple regions of the kidney is crucial to revealing the underlying mechanism and developing effective targets for diabetic nephropathy(DN). In this study, integrated spatially resolved metabolomics and proteomics combined with mass spectrometry imaging(MSI) revealed a multi-scale region profile of the diabetic kidney. Based on anatomic location, spatial metabolomics revealed eight region-specific metabolite biomarkers uniquely localized to kidney segments, which were closely correlated to the clinical parameters of patients with DN. Specifically, treatment with metformin(MET) enriched inosinic acid, adenosine 3′,5′-diphosphate, nicotinamide adenine dinucleotide(NADH), and hydrated NADH(NADHX) levels in the cortex(Cor) and the outer stripe of kidney medulla(OM) anatomical subregions, while in the inner stripe of kidney medulla(IM) segmentation, the p-cresol sulfate level was downregulated. Comparing differently expressed proteins in each region showed that nephrosis 2(Nphs2) was the highest loading feature. A further region-specific analysis of pathway enrichment characteristics indicated that the purine and ether lipid metabolism pathways were enriched in the Cor and OM regions, whereas the pantothenate and coenzyme A(CoA) biosynthesis pathways were mainly enriched in the IM region in response to MET treatment. Taken together, the spatially segregated metabolomics and proteomics studies reveal MET-mediated proteins and function-specific therapeutic pathways related to the anatomical multiregion of diabetic mouse kidneys.
出处 《Life Metabolism》 2025年第5期23-37,共15页 生命代谢(英文)
基金 support from the Program of Natural Science Foundation of State (Grant Nos.81973745 and 82104733) the Hainan Province "Nanhai New Star" Science and Technology Innovation Talent Platform Project by Hainan Provincial Department of Science and Technology (NHXXRCXM202317) the Natural Science Foundation of Heilongjiang Province (YQ2019H030)。
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