DOI: 10.2337/db23-400-p ISSN: 0012-1797

400-P: Spatial Metabolomics Analysis by MSI-DeepPath Identifies Key Pathways in ZDF Diabetic Kidney Disease Model

  • Endocrinology, Diabetes and Metabolism
  • Internal Medicine

Background: The Zucker Diabetic Fatty (ZDF) rat is a popular model of type 2 diabetes as it develops pathologic changes in the kidney similar to human diabetic nephropathy. To identify metabolic pathways linked to pathologic features MALDI mass spectrometry imaging (MSI) can be a powerful platform. However, quantification of metabolites from MALDI-MSI is very challenging. Our MSI-DeepPath computational platform enables spatial quantitation of metabolites from any tissue section size.

Methods: Control and obese ZDF male rats (age 6mo, n=5/group) were studied. Spatial metabolomics analysis of kidney tissue sections was performed using MALDI-MSI at 20 µm resolution. Metabolites were detected at mass accuracy <2 ppm using Q-Exactive orbitrap MS followed by annotations using METASPACE. SygnaMap’s MSI-DeepPath computational platform was used to quantify the annotated metabolites.

Results: Of 400 metabolites annotated at m/z range 70-500 Da the top features were selected using t-test, p value and fold change analysis. The top 20 biomarkers that separated ZDF from controls included glucose, serine, histidine, and glutamate. The most significantly upregulated metabolite was tyrosinamide (8.2-fold, p=8.02 x 10-9 ). The most significant downregulated metabolite was L-threonine (0.3-fold, p=2.03 x 10-9). Pathway analysis revealed that aminoacyl-tRNA biosynthesis, galactose, glyoxylate and dicarboxylate metabolic pathways can discriminate healthy from diabetic kidney samples.

Conclusion: MSIDeepPath enables quantification of spatial metabolomics of tissue sections using MALDI-MSI data. This new tool can be applied across normal and diseased samples allowing for robust statistical analysis of spatial omics data. Using MSI-DeepPath on kidney sections from the ZDF rat we identified regulation of metabolites linked to key pathways of diabetic kidney disease.


L.Hejazi: None. S.Sharma: None. A.Ruiz: None. G.Zhang: None. F.C.Tucci: None. K.Sharma: Advisory Panel; Reata Pharmaceuticals, Inc., Otsuka America Pharmaceutical, Inc.


National Institutes of Health (1R43DK130732-01A1)

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