ArticleCardiology journal2020
Identification of biomarkers and mechanisms of diabetic cardiomyopathy using microarray data.
Article in Cardiology journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Investigating the biomarkers of diabetic-cardiomyopathy with the high mobility group box-1 as a potential anti-inflammatory therapeutic target: Systematic Review and meta-analysis.Frontiers in endocrinology · 2025Pooled it
- Divergent Atrial Transcriptomic Signatures in Diabetic and Nondiabetic Atrial Fibrillation.Journal of arrhythmia · 2026Article
- Review
- Advances in diabetic cardiomyopathy: current and potential management strategies and emerging biomarkers.Annals of medicine and surgery (2012) · 2025Review
- Identification of key genes of diabetic cardiomyopathy in hiPSCs-CMs based on bioinformatics analysis.Molecular and cellular biochemistry · 2024Article
- Hmgcs2 is the hub gene in diabetic cardiomyopathy and is negatively regulated by Hmgcs2, promoting high glucose-induced cardiomyocyte injury.Immunity, inflammation and disease · 2024Article
- Inhibition of ERK 1/2 pathway downregulates YAP1/TAZ signaling in human cardiomyocytes exposed to hyperglycemic conditions.Biochemical and biophysical research communications · 2023Article
- The Effect of Polyphenol Extract from Rosa Roxburghii Fruit on Plasma Metabolome and Gut Microbiota in Type 2 Diabetic Mice.Foods (Basel, Switzerland) · 2022Article
- HMGCS2 silencing attenuates high glucose-induced in vitro diabetic cardiomyopathy by increasing cell viability, and inhibiting apoptosis, inflammation, and oxidative stress.Bioengineered · 2022Article
- Identification of Key Pathways and Genes in Obesity Using Bioinformatics Analysis and Molecular Docking Studies.Frontiers in endocrinology · 2021Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe study aimed to uncover the regulation mechanisms of diabetic cardiomyopathy (DCM) and provide novel prognostic biomarkers.
methodsThe dataset GSE62203 downloaded from the Gene Expression Omnibus database was utilized in the present study. After pretreatment using the Affy package, differentially expressed genes (DEGs) were identified by the limma package, followed by functional enrichment analysis and protein- protein interaction (PPI) network analysis. Furthermore, module analysis was conducted using MCODE plug-in of Cytoscape, and functional enrichment analysis was also performed for genes in the modules.
resultsA set of 560 DEGs were screened, mainly enriched in the metabolic process and cell cycle related process. Hub nodes in the PPI network were LDHA (lactate dehydrogenase A), ALDOC (aldolase C, fructose-bisphosphate) and ABCE1 (ATP Binding Cassette Subfamily E Member 1), which were also highlighted in Module 1 or Module 2 and predominantly enriched in the processes of glycolysis and ribosome biogenesis. Additionally, LDHA were linked with ALDOC in the PPI network. Besides, activating transcription factor 4 (ATF4) was prominent in Module 3; while myosin heavy chain 6 (MYH6) was highlighted in Module 4 and was mainly involved in muscle cells related biological processes.
conclusionsFive potential biomarkers including LDHA, ALDOC, ABCE1, ATF4 and MYH6 were identified for DCM prognosis.
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Registered trials
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.