Role of competitive endogenous RNA networks in the pathogenesis of coronary artery disease

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Coronary artery disease (CAD) poses a significant global health challenge.
• Understanding the molecular mechanisms underlying CAD pathogenesis is crucial for developing effective treatments.

Purpose of the Study:

• To construct a competitive endogenous RNA (ceRNA) network associated with coronary artery disease (CAD).
• To identify novel molecular targets for CAD treatment based on the ceRNA network.

Main Methods:

• Utilized bioinformatics approaches to analyze gene expression datasets (GSE68506, GSE59421, GSE20129) from the Gene Expression Omnibus (GEO) database.
• Employed databases such as miRcode, miRTarBase, miRDB, and TargetScan to predict interactions between long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs).
• Constructed a comprehensive mRNA-miRNA-lncRNA ceRNA network for CAD using Cytoscape.

Main Results:

• Identified significant numbers of differentially expressed lncRNAs (264), miRNAs (106), and mRNAs (1,879) between CAD and control groups.
• The constructed ceRNA network comprised 21 DElncRNAs, 13 DEmiRNAs, and 143 DEmRNAs.
• Key pathways implicated in CAD pathogenesis include PI3K-Akt and NF-κB signaling. Identified crucial genes within the protein-protein interaction network, including HSP90AA1, CDKN1A, and MCL1.

Conclusions:

• The developed ceRNA network provides novel candidate molecules for CAD treatment.
• Offers a more comprehensive and higher-quality basis for targeted therapeutic strategies in CAD.