ArticleMedicine2017
Identifying key genes associated with acute myocardial infarction.
Article in Medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- MetaDE-Based Analysis of circRNA Expression Profiles Involved in Gastric Cancer.Digestive diseases and sciences · 2020Pooled it
- Review
- Microarray Analysis for Transcriptomic Profiling of Myocardium in Patients with Fatal Myocardial Infarction.Biomedicines · 2023Article
- Article
- Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction.Frontiers in cardiovascular medicine · 2022Article
- NR4A3 and CCL20 clusters dominate the genetic networks in CD146European journal of medical research · 2021Article
- Specific protein 1 inhibitor mithramycin A protects cardiomyocytes from myocardial infarction via interacting with PARP.In vitro cellular & developmental biology. Animal · 2021Article
- Collapsing the list of myocardial infarction-related differentially expressed genes into a diagnostic signature.Journal of translational medicine · 2020Article
- Adverse Cardiac Remodelling after Acute Myocardial Infarction: Old and New Biomarkers.Disease markers · 2020 · on this mapReview
- Identification of Post-myocardial Infarction Blood Expression Signatures Using Multiple Feature Selection Strategies.Frontiers in physiology · 2020Article
- Using NGS-methylation profiling to understand the molecular pathogenesis of young MI patients who have subsequent cardiac events.Epigenetics · 2019Article
- Metabolic Disturbances Identified in Plasma Samples from ST-Segment Elevation Myocardial Infarction Patients.Disease markers · 2019Article
- Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 2 countries.
Funding
Abstract
backgroundThis study aimed to identify key genes associated with acute myocardial infarction (AMI) by reanalyzing microarray data.
methodsThree gene expression profile datasets GSE66360, GSE34198, and GSE48060 were downloaded from GEO database. After data preprocessing, genes without heterogeneity across different platforms were subjected to differential expression analysis between the AMI group and the control group using metaDE package. P < .05 was used as the cutoff for a differentially expressed gene (DEG). The expression data matrices of DEGs were imported in ReactomeFIViz to construct a gene functional interaction (FI) network. Then, DEGs in each module were subjected to pathway enrichment analysis using DAVID. MiRNAs and transcription factors predicted to regulate target DEGs were identified. Quantitative real-time polymerase chain reaction (RT-PCR) was applied to verify the expression of genes.
resultA total of 913 upregulated genes and 1060 downregulated genes were identified in the AMI group. A FI network consists of 21 modules and DEGs in 12 modules were significantly enriched in pathways. The transcription factor-miRNA-gene network contains 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p. RT-PCR validations showed that expression levels of FOXO3 and MYBL2 were significantly increased in AMI, and expression levels of hsa-miR-21-5p and hsa-miR-30c-5p were obviously decreased in AMI.
conclusionA total of 41 DEGs, such as SOCS3, VAPA, and COL5A2, are speculated to have roles in the pathogenesis of AMI; 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p may be involved in the regulation of the expression of these DEGs.
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Registered trials
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