Evidence mapPaperPMID 40437131Full record

ArticleScientific reports2025

Identification of metabolic pathways and serum biomarkers in diabetic cardiomyopathy using untargeted metabolomics.

Jialong Li, Huaming Qiu, Yanjun Wu, Li Su

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In one paragraph

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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0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Jialong LiDepartment of Cardiology, The Second Afffliated Hospital, Chongqing Medical University, Chongqing, China.
Huaming QiuGuizhou University of Traditional Chinese Medicine, Guizhou, Guiyang, China.
Yanjun WuGuizhou University of Traditional Chinese Medicine, Guizhou, Guiyang, China.
Li SuDepartment of Cardiology, The Second Afffliated Hospital, Chongqing Medical University, Chongqing, China. sulicq@hospital.cqmu.edu.cn.

Funding

the Chongqing Science and Technology Bureau project cstc021jcyj-msxmX0208the Guizhou Provincial Science and Technology Plan project Qianke Total [2024] General 360
6 · The paper itself

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.

Indexed as

BiomarkersDiabetic CardiomyopathiesMetabolic Networks and PathwaysMetabolomicsAnimalsDiabetes Mellitus, ExperimentalDisease Models, AnimalMaleMetabolomeMyocardiumRatsRats, Sprague-DawleyBiomarkersCardiac ultrasoundDiabetic cardiomyopathyDiagnostic biomarkersEjection fractionUntargeted metabolomics

Identifiers

PMID40437131
PMCPMC12119909

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.