Expression patterns of pyroptosis-related genes in atrial fibrillation and their application in diagnostic models

Atrial fibrillation (AF) is a common cardiac arrhythmia associated with substantial morbidity and mortality worldwide. However, its underlying mechanisms are still not completely understood. Emerging evidence suggests that pyroptosis may contribute to AF development. This study aimed to investigate the involvement of pyroptosis-related genes (PRGs) in AF and to develop a validated diagnostic model for this condition. Three AF-related datasets were obtained from the Gene Expression Omnibus. Data were processed using R packages, including GEOquery, sva for batch effect correction, and limma for normalization. Differentially expressed genes were identified and analyzed using clusterProfiler for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment. Gene set enrichment analysis and gene set variation analysis were performed. A protein-protein interaction network was generated using STRING, immune cell infiltration was assessed with cell-type identification by estimating relative subsets of RNA transcripts, and transcriptional regulatory networks were visualized using ChIPBase and StarBase. A total of 1107 differentially expressed genes (579 upregulated and 528 down-regulated) were identified. Among these, 21 PRGs, including ATP6AP1, PKM, and SPTBN1, showed significant dysregulation in AF. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed enrichment of PRGs in inflammation- and immune-related pathways. A diagnostic model incorporating 15 genes accurately distinguished AF patients from controls (area under the curve> 0.9). Gene set variation analysis further highlighted distinct pathway enrichment between high- and low-risk AF groups, underscoring potential therapeutic targets such as the TGF-β signaling pathway. This study provides new evidence that pyroptotic cell death contributes to AF pathogenesis. The proposed diagnostic model demonstrates strong clinical utility and may guide the future development of targeted therapies aimed at preventing AF onset or protecting against its progression.