Analysis of the Potential Role of Key Genes in Atrial Fibrillation Based on Bioinformatics Approach

Objective: Our study aims to explore the key differentially expressed genes (DEGs) that may serve as potential biomarkers for the diagnosis and treatment of atrial fibrillation (AF) using bioinformatics tools. Methods: Microarray datasets of GSE31821 and GSE79768 were downloaded from Gene Expression Synthesis (GEO) database. DEGs were analyzed after merging all microarray data and adjusting batch effect. The screened DEGs were further used for Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis. Protein-protein interaction (PPI) network was constructed using the STRING database，and PPI nodes were counted by R software. Finally, combined with the above important bioinformatics information, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to detect some DEGs in the tissues of patients with AF. Results: 114 DEGs (|log2 FC|≥0.5) were identified in the AF group compared with the control group. Combining DEGs, enrichment analysis and PPI results, CXCL10, TLR7, DDX58, CCR2, RSAD2, KIT, LYN, and CXCL11 were identified as potential key genes. The expression of two key genes (RSAD2 and CXCL11) was also verified by qRT-PCR in the tissues of AF patients, illustrating the reliability and biomarker potential of the key genes. Conclusion: 8 potential key genes may play an important role in the development of AF, and they may serve as potential biomarkers for the diagnosis and treatment of AF.