ArticlePeerJ2023
Bioinformatics prediction and experimental verification of a novel microRNA for myocardial fibrosis after myocardial infarction in rats.
Article in PeerJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 4 citations in OpenAlex.
- The potential impact of exosomal miR-484 on post-myocardial infarction angiogenesis using bioinformatics and experimental verification.BMC cardiovascular disorders · 2026Article
- Salvianolic acid B protects cardiac function via β3-AR/miRNA-1 axis-mediated cardiomyocyte proliferation in myocardial infarction rats.American journal of translational research · 2026Article
- Signaling Pathways and Therapeutic Approaches in Post-Myocardial Infarction Fibrosis.Medical science monitor : international medical journal of experimental and clinical research · 2025Review
- Myocardium miRNA Analysis Reveals Potential Biomarkers of Sudden Coronary Death in Rats.Current issues in molecular biology · 2025Article
- MicroRNAs regulating signaling pathways in cardiac fibrosis: potential role of the exercise training.American journal of physiology. Heart and circulatory physiology · 2024Review
Corrections and comments
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: MicroRNAs (miRNAs) are endogenous noncoding single-stranded small RNAs. Numerous studies have shown that miRNAs have pivotal roles in the occurrence and development of myocardial fibrosis (MF). However, miRNA expression profile in rats with MF after myocardial infarction (MI) is not well understood. The present study aimed to find the potential miRNA for MF post MI. Methods: SPF male Sprague-Dawley (SD) rat models of acute myocardial infarction (AMI) were established by ligating the anterior descending branch of the left coronary artery, while sham-operated rats were only threaded without ligation as a control group. Hematoxylin-eosin and Masson trichrome staining were used to detect myocardial histopathological changes for model evaluation. The differentially expressed miRNAs were detected by using the Agilent Rat miRNA gene chip in the myocardial tissue of the infarct marginal zone. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed by DAVID. The expression of miR-199a-5p was verified by real-time fluorescence quantitative PCR (qRT-PCR). Transfected miR-199a-5p mimics into cardiac fibroblasts (CFs) to construct cell models of miR-199a-5p overexpression. Dual-luciferase reporter assay was employed to validate the target gene of miR-199a-5p. The protein expression of the target gene in CFs transfected with miR-199a-5p mimics were detected by Western blot. Results: Myocardial fibrosis was exacerbated in the model group compared with the control group. Thirteen differentially expressed miRNAs between the two groups were screened and their expression levels in the model group were all higher than those in the control group. The expression of miR-199a-5p was significantly increased in the model group in qRT-PCR, which was consistent with the results of the gene chip. KEGG enrichment analysis showed that the target genes of miR-199a-5p were enriched in the insulin signaling pathway. Furthermore, dual-luciferase reporter assay indicated that miR-199a-5p could negatively regulate the expression of GSK-3β. After transfection, the expression of miR-199a-5p was increased in the miR-199a-5p mimics group. The protein expression of GSK-3β was decreased in CFs transfected with miR-199a-5p mimics. Conclusion: Our study identified miR-199a-5p could promote the progression of myocardial fibrosis after myocardial infarction by targeting GSK-3β, which provides novel targets for diagnosis and treatment of MF.
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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 OpenQuestion graph.