Key result
A diagnostic nomogram based on four immune-associated hub genes (C1QA, C1R, MET, and SDC4) accurately predicted post-operative atrial fibrillation with an AUC of 0.938.
Why the study?
Few studies have focused on post-operative AF, particularly using bioinformatics analysis and machine learning algorithms to identify immune-associated genes and construct ceRNA networks.
Observational (n=76)
Effect estimate: AUC 0.938
Bioinformatics analysis identified four immune-associated genes (C1QA, C1R, MET, SDC4) and a novel circRNA (circ_0007738) that may serve as diagnostic biomarkers and therapeutic targets for post-operative atrial fibrillation.
May support immune biomarker exploration for post-operative AF risk; hypothesis-generating and requires prospective clinical validation before any use.
Background: Atrial fibrillation (AF) is the most common arrhythmia. Previous studies mainly focused on identifying potential diagnostic biomarkers and treatment strategies for AF, while few studies concentrated on post-operative AF (POAF), particularly using bioinformatics analysis and machine learning algorithms. Therefore, our study aimed to identify immune-associated genes and provide the competing endogenous RNA (ceRNA) network for POAF. Methods: Three GSE datasets were downloaded from the GEO database, and we used a variety of bioinformatics strategies and machine learning algorithms to discover candidate hub genes. These techniques included identifying differentially expressed genes (DEGs) and circRNAs (DECs), building protein-protein interaction networks, selecting common genes, and filtering candidate hub genes via three machine learning algorithms. To assess the diagnostic value, we then created the nomogram and receiver operating curve (ROC). MiRNAs targeting DEGs and DECs were predicted using five tools and the competing endogenous RNA (ceRNA) network was built. Moreover, we performed the immune cell infiltration analysis to better elucidate the regulation of immune cells in POAF. Results: PPI network, which were mainly enriched in immune regulation. 15 common genes were selected using three CytoHubba algorithms. Following machine learning selection, the nomogram was created based on the four candidate hub genes. The area under curve (AUC) of the nomogram and individual gene were all over 0.75, showing the ideal diagnostic value. The dysregulation of macrophages may be critical in POAF pathogenesis. A novel circ_0007738 was discovered in POAF and the ceRNA network was eventually built. Conclusion: ) for POAF diagnosis through the creation of a nomogram and evaluation of its diagnostic value. The modulation of macrophages and the ceRNA network may represent further therapy methods.
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Zhou et al. (2022) conducted an observational in Post-operative atrial fibrillation (POAF) (n=76). Diagnostic nomogram based on four hub genes (C1QA, C1R, MET, SDC4) vs. Sinus rhythm (SR) was evaluated on Diagnostic value (Area Under the Curve) of the nomogram (AUC 0.938). A diagnostic nomogram based on four immune-associated hub genes (C1QA, C1R, MET, and SDC4) accurately predicted post-operative atrial fibrillation with an AUC of 0.938.
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