Uncovering potential novel biomarkers and immune infiltration characteristics in persistent atrial fibrillation using integrated bioinformatics analysis

Atrial fibrillation (AF) is the most common cardiac arrhythmia. This study aimed to identify potential novel biomarkers for persistent AF (pAF) using integrated analyses and explore the immune cell infiltration in this pathological process. Three pAF datasets (GSE31821, GSE41177, and GSE79768) from the Gene Expression Omnibus (GEO) database were integrated with the elimination of batch effects. 264 differentially expressed genes (DEGs) were identified using Linear models for microarray data (LIMMA), 12 modules were screened out by weighted gene co-expression network analysis (WGCNA) in pAF compared with normal controls. Subsequently, common genes (CGs) were identified as the intersection of DEGs and genes in the most significant module. Functional enrichment analysis showed that CGs were mainly enriched in the "Calcineurin-NFAT (nuclear factor of activated T-cells)" signaling pathway, particularly regulator of calcineurin 1 (RCAN1), and protein phosphatase 3 regulatory subunit B, alpha (PPP3R1). Ulteriorly, the microRNA-transcription factor-mRNA network revealed that microRNA-34a-5p could target both RCAN1 and PPP3R1 in the pAF pathogenesis. Finally, immune infiltration analysis by CIBERSORT, a versatile computational method, displayed a higher level of monocytes, dendritic cells and neutrophils, as well as a lower level of CD8+ T cells and T cells regulatory (Tregs) in pAF compared with the control group. In conclusion, our present study revealed several novel pAF-associated genes, miRNAs, and pathways, including microRNA-34a-5p, which might target RCAN1 and PPP3R1 to regulate pAF through the calcineurin-NFAT signaling pathway. In addition, there was a difference in immune infiltration between patients with pAF and normal groups and immune cells might interact with specific genes in pAF.