Atrial fibrillation (AF) and related cardiovascular complications pose a heavy burden to patients and society. Mounting evidence suggests a close association between nonalcoholic fatty liver disease (NAFLD) and AF. NAFLD and AF transcriptomic datasets were obtained from GEO database and analyzed using several bioinformatics approaches. We established a NAFLD-AF associated gene diagnostic signature (NAGDS) using protein-protein interaction analysis and machine learning, which was further quantified through RT-qPCR. Potential miRNA targeting NAGDS were predicted. Gene modules highly correlated with NAFLD liver pathology or AF occurrence were identified by WGCNA. Enrichment analysis of the overlapped genes from key module revealed that T-cell activation plays essential roles in NAFLD and AF, which was further confirmed by immune infiltration. Furthermore, an integrated SVM-RFE and LASSO algorithm was used to identify CCL4, CD48, ITGB2, and RNASE6 as NAGDS, all of which were found to be upregulated in NAFLD and AF mouse tissues. Patients with higher NAGDS showed augmented T cell and macrophage immunity, more advanced liver pathological characteristics, and prolonged AF duration. Additionally, hsa-miR-26a-5p played a central role in the regulation of NAGDS. Our findings highlight the central role of T-cell immune response in linking NAFLD to AF, and established an accurate NAGDS diagnostic model, which could serve as potential targets for immunoregulatory therapy.
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