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Published on: February 4, 2021
Bioinformatics-Based Identification of CircRNA-MicroRNA-mRNA Network for Calcific Aortic Valve Disease
Linghong Song1, Yubing Wang1, Yufei Feng1
1NHC Key Laboratory of Prevention and Treatment of Central Asia High Incidence Diseases (First Affiliated Hospital, School of Medicine, Shihezi University), Department of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases, Shihezi University School of Medicine, Shihezi, Xinjiang, China.
Insights
This study identifies novel circRNA-miRNA-mRNA networks involved in calcific aortic valve disease (CAVD) pathogenesis. These findings offer potential new therapeutic targets for treating this common heart valve condition.
Area of Science:
- Cardiovascular Biology
- Molecular Genetics
- Bioinformatics
Background:
- Calcific aortic valve disease (CAVD) is the most prevalent native valve disease, characterized by valvular interstitial cell (VIC) osteogenic differentiation and valvular endothelial cell (VEC) dysfunction.
- Circular RNAs (circRNAs) regulate osteogenic differentiation and disease progression, but their role in CAVD is not yet understood.
Purpose of the Study:
- To investigate the function and significance of circRNA-miRNA-mRNA networks in the pathogenesis of calcific aortic valve disease (CAVD).
- To identify potential therapeutic targets for CAVD based on these regulatory networks.
Main Methods:
- Utilized mRNA, miRNA, and circRNA datasets from CAVD patients obtained from GEO.
- Identified differentially expressed (DE) circRNAs, miRNAs, and mRNAs.
- Constructed circRNA-miRNA-mRNA networks using bioinformatics tools and predicted regulatory interactions.
- Performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses.
- Identified hub genes via protein-protein interaction (PPI) networks.
Main Results:
- Identified 32 DE-circRNAs, 206 DE-miRNAs, and 2170 DE-mRNAs.
- Fifty-nine common mRNAs (FmRNAs) were identified for network construction.
- KEGG analysis revealed enrichment in pathways including cancer, JAK-STAT signaling, cell cycle, and MAPK signaling.
- GO analysis highlighted enrichment in transcription, nucleolus, and protein homodimerization activity.
- Eight hub genes were identified, leading to the construction of three potential regulatory networks in CAVD: hsa_circ_0026817-hsa-miR-211-5p-CACNA1C, hsa_circ_0007215-hsa-miR-1252-5p-MECP2, and hsa_circ_0007215-hsa-miR-1343-3p-RBL1.
Conclusions:
- Bioinformatic analysis reveals the functional role of circRNA-miRNA-mRNA networks in CAVD pathogenesis.
- These identified networks and their components represent novel therapeutic targets for CAVD treatment.
Background:
Calcific aortic valve disease (CAVD) is the most common native valve disease. Valvular interstitial cell (VIC) osteogenic differentiation and valvular endothelial cell (VEC) dysfunction are key steps in CAVD progression. Circular RNA (circRNAs) is involved in regulating osteogenic differentiation with mesenchymal cells and is associated with multiple disease progression, but the function of circRNAs in CAVD remains unknown. Here, we aimed to investigate the effect and potential significance of circRNA-miRNA-mRNA networks in CAVD.
Methods:
Two mRNA datasets, one miRNA dataset, and one circRNA dataset of CAVD downloaded from GEO were used to identify DE-circRNAs, DE-miRNAs, and DE-mRNAs. Based on the online website prediction function, the common mRNAs (FmRNAs) for constructing circRNA-miRNA-mRNA networks were identified. GO and KEGG enrichment analyses were performed on FmRNAs. In addition, hub genes were identified by PPI networks. Based on the expression of each data set, the circRNA-miRNA-hub gene network was constructed by Cytoscape (version 3.6.1).
Results:
32 DE-circRNAs, 206 DE-miRNAs, and 2170 DE-mRNAs were identified. Fifty-nine FmRNAs were obtained by intersection. The KEGG pathway analysis of FmRNAs was enriched in pathways in cancer, JAK-STAT signaling pathway, cell cycle, and MAPK signaling pathway. Meanwhile, transcription, nucleolus, and protein homodimerization activity were significantly enriched in GO analysis. Eight hub genes were identified based on the PPI network. Three possible regulatory networks in CAVD disease were obtained based on the biological functions of circRNAs including: hsa_circ_0026817-hsa-miR-211-5p-CACNA1C, hsa_circ_0007215-hsa-miR-1252-5p-MECP2, and hsa_circ_0007215-hsa-miR-1343-3p- RBL1.
Conclusion:
The present bionformatics analysis suggests the functional effect for the circRNA-miRNA-mRNA network in CAVD pathogenesis and provides new targets for therapeutics.
