Exploring the causality and pathogenesis of atrial fibrillation with dilated cardiomyopathy: An integrated multi-omics approach

Background : Atrial fibrillation (AF) is the most prevalent sustained arrhythmia, and recent evidence indicates the presence of cardiac enlargement in patients with AF. Dilated cardiomyopathy (DCM), the most common form of cardiomyopathy, is characterized by significant heart dilation and AF. However, the risk factors and underlying mechanisms linking DCM to AF remain poorly understood. Methods : Mendelian randomization (MR) analysis was initially used to explore the potential causal relationship between AF and DCM. Data were sourced from the public database Gene Expression Omnibus (GEO), and differentially expressed genes (DEGs) and significant module genes were identified using the Limma package and weighted gene co-expression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, as well as a protein-protein interaction (PPI) network analysis, were performed on the intersected genes. Hub genes were screened using machine learning algorithms. The identification of hub genes within the DCM GSE17800 dataset was achieved using the receiver operating characteristic (ROC) curve and nomogram, which were employed to assess the diagnostic efficacy of these hub genes. Finally, the immune infiltration of DCM and the microRNA (miRNA) interaction network involving hub genes were evaluated. Results : MR analysis demonstrated that genetic susceptibility to AF was significantly associated with an increased risk of DCM (β: 20.44, 95% CI: 15.00-25.88, p =0.0002). The AF dataset included 1850 DEGs and 572 significant module genes, and the DCM dataset included 6463 DEGs, which had a total of 209 intersected genes with module genes for AF. After correlation enrichment analysis and PPI interaction network on the intersected genes, machine learning was used to screen two hub genes (VSNL1 and ETNPPL) that had high diagnostic efficacy (area under the curve from 0.81 0.89). Immune infiltration analysis of these genes revealed a relatively normal immune status for DCM, with a wider miRNA interaction network for VSNL1. Conclusion : MR data suggests that genetic changes in the presence of AF are significantly associated with an increased risk of DCM. The two identified hub genes (VSNL1 and ETNPPL) can be used to diagnose comorbid DCM in patients with AF.