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Published on: June 15, 2018
CDKN2B-AS may indirectly regulate coronary artery disease-associated genes via targeting miR-92a
Ming Cheng1, Shoukuan An1, Junquan Li2
1Department of Cardiac Surgery, The Second Affiliated Hospital of Harbin Medical University, Nangang, Harbin 150086, Heilongjiang, People's Republic of China.
Insights
This study investigated the pathogenesis of coronary artery disease (CAD) by analyzing gene expression data. Key genes like GATA2, MAP1B, and ARG1 were identified as potentially involved in CAD through a CDKN2B-AS-miR-92a regulatory network.
Area of Science:
- Genomics and Bioinformatics
- Molecular Biology
- Cardiovascular Research
Background:
- Coronary artery disease (CAD) is a leading cause of mortality, encompassing conditions like angina, myocardial infarction, and sudden cardiac death.
- Understanding the complex pathogenesis of CAD is crucial for developing effective therapeutic strategies.
Purpose of the Study:
- To explore the molecular mechanisms and pathogenesis underlying coronary artery disease (CAD).
- To identify key genes, microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) involved in CAD development.
Main Methods:
- Utilized gene expression datasets (GSE20680, GSE20681) from the Gene Expression Omnibus database.
- Identified differentially expressed genes (DEGs) and constructed regulatory networks involving miRNAs and lncRNAs using bioinformatics databases and tools.
- Employed a support vector machine (SVM) classifier to identify feature genes for CAD classification.
Main Results:
- Identified 1208 differentially expressed genes (DEGs) and 5 CAD-associated miRNAs, including miR-92a.
- Constructed a lncRNA-miRNA-DEG regulatory network, revealing CDKN2B-AS targeting miR-92a.
- Highlighted GATA2, MAP1B, and ARG1 as key genes within the CDKN2B-AS-miR-92a regulatory network.
Conclusions:
- The lncRNA CDKN2B-AS, through its regulation of miR-92a, potentially influences CAD pathogenesis.
- GATA2, MAP1B, and ARG1 are implicated in CAD, possibly via indirect regulation by CDKN2B-AS and miR-92a.
Objective:
Coronary artery disease (CAD) has a high mortality rate and consists of multiple condition, including stable/unstable angina, sudden cardiac death, and myocardial infarction. This study is aimed to explore the pathogenesis of CAD.
Methods:
Datasets of GSE20680 (including 87 CAD samples and 52 normal samples) and GSE20681 (including 99 CAD samples and 99 normal samples) were obtained from Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified by MetaDE. Effect Sizes in MetaDE package, and then were hierarchical clustered using pheatmap package in R. Subsequently, CAD-associated microRNAs (miRNAs) and their targets were obtained separately by miR2Disease and miRTarBase databases, and then used to construct an associated-miRNA-DEG regulatory network based on BioGRID, HPRD and DIP databases. Enrichment analysis was conducted for the involved DEGs using Fisher's exact test, and a support vector machine (SVM) classifier was constructed to optimize the feature genes. After CAD-associated long non-coding RNAs (lncRNAs) were predicted by lncRNA Disease database and their target miRNAs were predicted using miRcode and starBase databases, lncRNA-miRNA-DEG regulatory network was constructed.
Results:
Total 1208 DEGs were screened, and 5 CAD-associated miRNAs (including miR-92a) were predicted associated with CAD. The SVM classifier was constructed based on the 41 featured genes and had high recognition efficiency. Only one lncRNA CDKN2B-AS targeting miR-92a was obtained. Finally, GATA2, MAP1B and ARG1 were involved in the CDKN2B-AS-miR-92a-feature gene regulatory network.
Conclusion:
GATA2, MAP1B and ARG1 indirectly regulated by CDKN2B-AS through miR-92a might be involved in CAD.
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