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Updated: Jan 27, 2026
Acute Myocardial Infarction in Rats
Published on: February 16, 2011
Identification of Candidate Genes and MicroRNAs for Acute Myocardial Infarction by Weighted Gene Coexpression Network
Yan Li1,2, Xiao Nan He3, Chao Li4
1Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Background:
Identification of potential molecular targets of acute myocardial infarction is crucial to our comprehensive understanding of the disease mechanism. However, studies of gene coexpression analysis via jointing multiple microarray data of acute myocardial infarction still remain restricted.
Methods:
Microarray data of acute myocardial infarction (GSE48060, GSE66360, GSE97320, and GSE19339) were downloaded from Gene Expression Omnibus database. Three data sets without heterogeneity (GSE48060, GSE66360, and GSE97320) were subjected to differential expression analysis using MetaDE package. Differentially expressed genes having upper 25% variation across samples were imported in weighted gene coexpression network analysis. Functional and pathway enrichment analyses were conducted for genes in the most significant module using DAVID. The predicted microRNAs to regulate target genes in the most significant module were identified using TargetScan. Moreover, subpathway analyses using iSubpathwayMiner package and GenCLiP 2.0 were performed on hub genes with high connective weight in the most significant module.
Results:
A total of 1027 differentially expressed genes and 33 specific modules were screened out between acute myocardial infarction patients and control samples. Ficolin (collagen/fibrinogen domain containing) 1 (FCN1), CD14 molecule (CD14), S100 calcium binding protein A9 (S100A9), and mitochondrial aldehyde dehydrogenase 2 (ALDH2) were identified as critical target molecules; hsa-let-7d, hsa-let-7b, hsa-miR-124-3, and hsa-miR-9-1 were identified as potential regulators of the expression of the key genes in the two biggest modules.
Conclusions:
FCN1, CD14, S100A9, ALDH2, hsa-let-7d, hsa-let-7b, hsa-miR-124-3, and hsa-miR-9-1 were identified as potential candidate regulators in acute myocardial infarction. These findings might provide new comprehension into the underlying molecular mechanism of disease.
Insights
This study identifies key genes (FCN1, CD14, S100A9, ALDH2) and microRNAs (hsa-let-7d, hsa-let-7b, hsa-miR-124-3, hsa-miR-9-1) as potential regulators in acute myocardial infarction. These findings offer new insights into the molecular mechanisms of heart disease.
Area of Science:
- Cardiovascular Biology
- Molecular Genetics
- Bioinformatics
Background:
- Understanding acute myocardial infarction (AMI) molecular targets is vital for disease mechanism comprehension.
- Existing studies on AMI gene coexpression analysis using multiple microarray data are limited.
Purpose of the Study:
- To identify novel molecular targets and regulatory microRNAs in acute myocardial infarction through integrated bioinformatics analysis.
- To enhance the understanding of the underlying molecular mechanisms of AMI.
Main Methods:
- Downloaded and integrated AMI microarray datasets (GSE48060, GSE66360, GSE97320) for differential expression analysis.
- Performed weighted gene coexpression network analysis (WGCNA) on differentially expressed genes.
- Conducted functional enrichment, pathway analysis, and microRNA target prediction using DAVID, TargetScan, and other bioinformatics tools.
Main Results:
- Identified 1027 differentially expressed genes and 33 modules in AMI patients compared to controls.
- Highlighted Ficolin 1 (FCN1), CD14 molecule (CD14), S100A9, and ALDH2 as critical target molecules.
- Identified hsa-let-7d, hsa-let-7b, hsa-miR-124-3, and hsa-miR-9-1 as potential regulatory microRNAs for key genes.
Conclusions:
- FCN1, CD14, S100A9, ALDH2, and specific microRNAs (hsa-let-7d, hsa-let-7b, hsa-miR-124-3, hsa-miR-9-1) are potential regulators in acute myocardial infarction.
- These findings contribute to a deeper understanding of AMI's molecular mechanisms.
- The identified targets and regulators may serve as potential biomarkers or therapeutic targets for AMI.
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