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

代谢组学 代谢物 内科学 代谢途径 内分泌学 化学 糖尿病 医学 新陈代谢 色谱法
作者
LEILA HEJAZI,SHOBA SHARMA,A. López Ruiz,Guanshi Zhang,Fábio C. Tucci,KUMAR SHARMA
出处
期刊:Diabetes [American Diabetes Association]
卷期号:72 (Supplement_1)
标识
DOI:10.2337/db23-400-p
摘要

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. Disclosure 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. Funding National Institutes of Health (1R43DK130732-01A1)
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