ArticleScientific reports2025
Identification of metabolic pathways and serum biomarkers in diabetic cardiomyopathy using untargeted metabolomics.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
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4 authors.
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Abstract
Diabetic cardiomyopathy represents a significant and irreversible chronic cardiovascular complication among diabetic patients. The condition is characterised by early diastolic dysfunction, myocardial fibrosis, cardiac hypertrophy, systolic dysfunction, and other complex pathophysiological events that ultimately lead to heart failure. Untargeted metabolomic analysis represents a powerful tool for the discovery of novel biomarkers. It can not only reveal the metabolic disorder model of diabetic cardiomyopathy, and find specific biomarkers, but also help analyse its pathogenesis and provide new clues for developing treatment strategies. Nevertheless, the precise mechanisms that give rise to diabetic cardiomyopathy remain unclear. In this study, we established a rat model of diabetic cardiomyopathy. We evaluated the model using various established methods, including fasting glucose, glycated hemoglobin, insulin resistance index, cardiac histopathology, and cardiac ultrasound. We then proceeded to identify diabetic cardiomyopathy serum biomarkers by untargeted metabolomics. The potential metabolic pathways of the multiple metabolic differentials were mainly related to amino acid metabolism and arachidonic acid metabolism. Two common metabolites, 5-OxoETE and D-Glutamine, were identified through various cross-comparisons. These two metabolites have good diagnostic ability, especially between DCM vs. CTR, DCM vs. NDCM, and NDCM vs. CTR. These findings may provide new insights into the study of DCM.
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