biostudies-literatureWang RNational Natural Science Foundation of China2629https://www.ebi.ac.uk/biostudies/studies/S-EPMC9454849biostudies-literatureUnknown11(17)Atrial fibrillation (AF) is a form of sustained cardiac arrhythmia and microRNAs (miRs) play crucial roles in the pathophysiology of AF. To identify novel miR-mRNA pairs, we performed RNA-seq from atrial biopsies of persistent AF patients and non-AF patients with normal sinus rhythm (SR). Differentially expressed miRs (11 down and 9 up) and mRNAs (95 up and 82 down) were identified and hierarchically clustered in a heat map. Subsequently, GO, KEGG, and GSEA analyses were run to identify deregulated pathways. Then, miR targets were predicted in the miRDB database, and a regulatory network of negatively correlated miR-mRNA pairs was constructed using Cytoscape. To select potential candidate genes from GSEA analysis, the top-50 enriched genes in GSEA were overlaid with predicted targets of diCellsIntegrated Analysis of the microRNA-mRNA Network Predicts Potential Regulators of Atrial Fibrillation in Humans.PMC945484981970282Huang SWang RChen JChen MHan WWang XWang YZhong JBektik EMeng XSakon PfalseIntegrated Analysis of the microRNA-mRNA Network Predicts Potential Regulators of Atrial Fibrillation in Humans.Atrial fibrillation (AF) is a form of sustained cardiac arrhythmia and microRNAs (miRs) play crucial roles in the pathophysiology of AF. To identify novel miR-mRNA pairs, we performed RNA-seq from atrial biopsies of persistent AF patients and non-AF patients with normal sinus rhythm (SR). Differentially expressed miRs (11 down and 9 up) and mRNAs (95 up and 82 down) were identified and hierarchically clustered in a heat map. Subsequently, GO, KEGG, and GSEA analyses were run to identify deregulated pathways. Then, miR targets were predicted in the miRDB database, and a regulatory network of negatively correlated miR-mRNA pairs was constructed using Cytoscape. To select potential candidate genes from GSEA analysis, the top-50 enriched genes in GSEA were overlaid with predicted targets of di2022-01-01T00:00:00Z2022 Aug2025-04-04T03:24:32.611Z2025-04-04T03:24:32.611ZS-EPMC94548493607803710.3390/cells11172629