Abstract

Purpose Atrial fibrillation (AF) is the most frequent arrhythmia in clinical practice. The pathogenesis of AF is not yet clear. Therefore, exploring the molecular information of AF displays much importance for AF therapy. Methods The GSE2240 data were acquired from the Gene Expression Omnibus (GEO) database. The R limma software package was used to screen DEGs. Based on the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) databases, we conducted the functions and pathway enrichment analyses. Then, the STRING and Cytoscape software were employed to build Protein-Protein Interaction (PPI) network and screen for hub genes. Finally, we used the Cell Counting Kit-8 (CCK-8) experiment to explore the effect of hub gene knockdown on the proliferation of AF cells. Result 906 differentially expressed genes (DEGs), including 542 significantly upregulated genes and 364 significantly downregulated genes, were screened in AF. The genes of AF were mainly enriched in vascular endothelial growth factor-activated receptor activity, alanine, regulation of histone deacetylase activity, and HCM. The PPI network constructed of significantly upregulated DEGs contained 404 nodes and 514 edges. Five hub genes, ASPM, DTL, STAT3, ANLN, and CDCA5, were identified through the PPI network. The PPI network constructed by significantly downregulated genes contained 327 nodes and 301 edges. Four hub genes, CDC42, CREB1, AR, and SP1, were identified through this PPI network. The results of CCK-8 experiments proved that knocking down the expression of CDCA5 gene could inhibit the proliferation of H9C2 cells. Conclusion Bioinformatics analyses revealed the hub genes and key pathways of AF. These genes and pathways provide information for studying the pathogenesis, treatment, and prognosis of AF and have the potential to become biomarkers in AF treatment.

Highlights

  • Atrial fibrillation (AF) is the most frequent arrhythmia; its incidence continues to increase, reaching 10% over 75 years [1]

  • This study used bioinformatics analyses to obtain hub genes and key pathways related to AF

  • Through Protein-Protein Interaction (PPI) network analysis, we found that the genes most associated with AF were ASPM, DTL, STAT3, ANLN, CDCA5, CDC42, CREB1, AR, and SP1

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Summary

Introduction

Atrial fibrillation (AF) is the most frequent arrhythmia; its incidence continues to increase, reaching 10% over 75 years [1]. The frequency of atrial activation in AF is 300-600 beats/min [2]. The heartbeat frequency of AF patients is often faster and more irregular than normal people’s, sometimes up to 100-160 beats/min. The patients with AF are mainly the elderly, and common inducing factors include rheumatic heart disease, coronary heart disease, hyperthyroidism, stroke, thromboembolism, and heart failure [4]. The stroke incidence in patients with nonvalvular AF is 5.6 times higher than that of average people and in patients with valvular AF is 17.6 times, and the brain caused by AF is 17.6 times. Medicine is still the main treatment for AF patients, which can restore sinus rhythm, reduce the ventricular rate, and prevent thromboembolic complications [7]. Nonpharmacological treatments for AF include electro conversion (conversion of sinus rhythm), radiofrequency ablation treatment, and surgical maze surgery (complete radical treatment of AF) [8]

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