Comprehensive Analysis of Pertinent Genes and Pathways in Atrial Fibrillation

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.

Figure 1

Hierarchical clustering heat map of all DEGs in AF. Yellow is upregulated DEGs, and purple is downregulated DEGs.

Figure 2

GO and KEGG enrichment analysis of upregulated DEGs in AF. (a–c) Top 10 BP, CC, and MF terms in which the upregulated DEGs were enriched. (d) Top 10 KEGG pathways in which the upregulated DEGs were enriched.

Figure 3

GO and KEGG enrichment of downregulated DEGs in AF. (a–c) Top 10 BP, CC, and MF terms in which the upregulated DEGs were enriched. (d) Top 10 KEGG pathways in which the downregulated DEGs were enriched.

Figure 4

GSEA analysis of pathways related with AF based on dataset GSE2240. (a) The gene set of aldosterone-regulated sodium reabsorption was significantly enriched in AF patient samples. (b) The gene set of olfactory transduction was significantly enriched in AF patient samples. (c) The gene set of vibrio cholerae infection was significantly enriched in AF patient samples.

Figure 5

The constructed PPI network for upregulated DEGs. The PPI network contains 404 nodes and 514 edges. Nodes mean proteins and edges mean the interaction of proteins.

Figure 6

The expression level of (a) STAT3, (b) ASPM, (c) ANLN, (d) CDCA5, and (e) DTL in myocardial tissues of AF was significantly higher than that in myocardial tissues of sinus rhythm.

Figure 7

The constructed PPI network for downregulated DEGs. The PPI network contains 327 nodes and 301 edges. Nodes mean proteins and edges mean the interaction of proteins.

Figure 8

The expression levels of (a) SP1, (b) AR, (c) CDC42, and (d) CREB1 in myocardial tissues of AF were significantly lower than those in myocardial tissues of sinus rhythm.

Figure 9

CDCA5 knockdown inhibited the proliferation of H9C2 cells. The x-axis is the number of days, and the y-axis is the OD value at 450 nm corresponding to the number of days. ^∗P < 0.05.