Dual Arrhythmogenic Mechanisms in Arrhythmogenic Right Ventricular Cardiomyopathy: Insights From Transcriptomic Profiling

Background and Aims Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) is an inherited and progressive disease associated with ventricular arrhythmias (VAs) and sudden cardiac death in young individuals. While fibrofatty replacement is a hallmark feature, the molecular mechanisms linking structural remodelling and cellular dysfunction remain incompletely defined. This study aimed to characterise transcriptomic alterations and identify key pathways contributing to arrhythmogenesis in ARVC. Methods Publicly available RNA-seq datasets of right ventricular tissue (GSE107475 for ARVC; GSE107156 for controls) and induced pluripotent stem cell-derived cardiomyocytes (GSE115621) for validation were analysed. Differential expression analysis was performed using limma (adjusted p-values < 0.05). Principal component analysis and hierarchical clustering assessed sample variability and group separation. Functional enrichment analyses were conducted using Gene Ontology and KEGG pathways. Protein-protein interaction (PPI) networks were constructed via STRING to identify key hub genes. Results A total of 1,442 differentially expressed genes were identified from 25,367 analysed transcripts. Principal component analysis demonstrated heterogeneity among ARVC samples, with partial separation from controls. Enrichment analyses revealed significant upregulation of pathways related to extracellular matrix (ECM) organisation, mitochondrial metabolism, oxidative phosphorylation, and oxidative stress responses. PPI network analysis highlighted key hub genes, including COL1A1, GREM1, WNT9A, SOX2, HSPA2, and GDNF, suggesting interconnected networks linking fibrotic remodeling and metabolic stress pathways. Conclusion ARVC exhibits a dual arrhythmogenic mechanism characterised by ECM remodelling facilitating reentry and metabolic dysregulation promoting triggered activity. These findings provide mechanistic insight and highlight potential molecular targets for arrhythmia risk stratification and therapeutic development.