Identification of Potential Key Biomarkers of Atrial Fibrillation and Their Correlation with Immune Infiltration in Atrial Tissue.

Jie Liu,Xiahuan Chen,Meilin Liu,Osamah Ibrahim Khalaf

doi:10.1155/2022/4029840

Jie Liu, Xiahuan Chen + Show 2 more

Open Access

https://doi.org/10.1155/2022/4029840

Copy DOI

Abstract

Objective To identify potential key biomarkers and characterize immune infiltration in atrial tissue of patients with atrial fibrillation (AF) through bioinformatics analysis. Methods Differentially expressed genes (DEGs) were identified by the LIMMA package in Bioconductor, and functional and pathway enrichment analyses were undertaken using GO and KEGG. The LASSO logistic regression and BORUTA algorithm were employed to screen for potential novel key markers of AF from all DEGs. Gene set variation analysis was also performed. Single-sample gene set enrichment analysis was employed to quantify the infiltration levels for each immune cell type, and the correlation between hub genes and infiltrating immune cells was analyzed. Results A total of 52 DEGs were identified, including of 26 downregulated DEGs and 26 upregulated DEGs. DEGs were primarily enriched in the Major Histocompatibility Complex class II protein complex, glucose homeostasis, protein tetramerization, regulation of synapse organization, cytokine activity, heart morphogenesis, and blood circulation. Three downregulated genes and three upregulated genes were screened by LASSO logistic regression and the BORUTA algorithm. Finally, immune infiltration analysis indicated that the atrial tissue of AF patients contained significant infiltration of APC_co_inhibition, Mast_cell, neutrophils, pDCs, T_cell_costimulation, and Th1_cells compared with paired sinus rhythm (SR) atrial tissue, and the three downregulated genes were negatively correlated with the six kinds of immune cells mentioned above. Conclusion The hub genes identified in this study and the differences in immune infiltration of atrial tissue observed between AF and SR tissue might help to characterize the occurrence and progression of AF.

Highlights

Atrial fibrillation (AF) is a type of supraventricular tachyarrhythmia that is characterized by rapid and disordered atrial electrical activity [1]
Our data showed that the clustering of the two groups of samples was more obvious after normalization, indicating that the sample source was reliable
The gene expression matrix was analyzed by using R software, and a total of 52 Differentially expressed genes (DEGs) were detected, consisting of 26 downregulated DEGs and 26 upregulated DEGs

Summary

Introduction

Atrial fibrillation (AF) is a type of supraventricular tachyarrhythmia that is characterized by rapid and disordered atrial electrical activity [1]. AF has been determined to affect up to 1% of the general population worldwide, and its prevalence increases exponentially with age, possibly reaching 8% in the elderly population (age > 80 years) [2]. No consensus has been reached concerning the exact etiology and pathological changes involved in AF. Previous studies have shown that the etiology of AF is multifactorial, including both genetic and nongenetic factors. Several recent studies have employed genome-wide association studies (GWASs) to identify over 100 genetic loci associated with AF, including PITX2, TBX5, PRRX1, and ZFHX3 [5–7]. These genetic factors serve to establish electrophysiological substrates that determine individual vulnerability to AF occurrence and maintenance [8]. To date, few studies have investigated the molecular mechanism underlying the pathology of AF

Methods

Results

Conclusion