Identification of microRNAs and genes as biomarkers of atrial fibrillation using a bioinformatics approach. Issue 8 (August 2019)

• Record Type: Journal Article
• Authors: Li, Yingyuan; Tan, Wulin; Ye, Fang; Xue, Faling; Gao, Shaowei; Huang, Wenqi; Wang, Zhongxing
• Is Part Of: Journal of international medical research. Volume 47:Issue 8(2019)
• Page Start: 3580
• Page End: 3589
• Publication Date: 2019-08
• Subjects: MicroRNAs -- atrial fibrillation -- computational biology -- microarray analysis -- cyclin D kinase -- cyclin D3; Medicine -- Periodicals; Pharmacology -- Periodicals; 610.5
• DOI: 10.1177/0300060519852235
• Languages: English
• ISSNs: 0300-0605

Abstract

Objective: We aimed to explore potential microRNAs (miRNAs) and target genes related to atrial fibrillation (AF). Methods: Data for microarrays GSE70887 and GSE68475, both of which include AF and control groups, were downloaded from the Gene Expression Omnibus database. Differentially expressed miRNAs between AF and control groups were identified within each microarray, and the intersection of these two sets was obtained. These miRNAs were mapped to target genes in the miRNet database. Functional annotation and enrichment analysis of these target genes was performed in the DAVID database. The protein-protein interaction (PPI) network from the STRING database and the miRNA-target-gene network were merged into a PPI-miRNA network using Cytoscape software. Modules of this network containing miRNAs were detected and further analyzed. Results: Ten differentially expressed miRNAs and 1520 target genes were identified. Three PPI-miRNA modules were constructed, which contained miR-424, miR-15a, miR-542-3p, and miR-421 as well as their target genes, CDK1, CDK6, and CCND3 . Conclusion: The identified miRNAs and genes may be related to the pathogenesis of AF. Thus, they may be potential biomarkers for diagnosis and targets for treatment of AF.