Bioinformatics analysis of immune-associated, chromatin-regulating genes as biomarkers of persistent atrial fibrillation

Abstract

Abstract Aims: Atrial fibrillation (AF) is the most common arrhythmia associated with high morbidity and mortality.Chromatin regulators an analysis of the expression and immunological correlation of CRs in pAF and normal tissues was conducted to assess their potential as diagnostic biomarkers. Methods: GSE31821, GSE411777, and GSE79768 datasets from the gene expression database, Gene Expression Omnibus, were combined into an integrated dataset for use as a training set. GSE2240 was used as a validation dataset. The merge function in R language was used to obtain the intersection of CRs and the included study data. The “Limma” software package was used to identify CR-related, differentially expressed genes (CR DEGs) in normal and pAF tissues, and the protein-protein interaction (PPI) network was used to search for hub genes. A logistic regression model was constructed based on these immHub genes to predict the occurrence of pAF. Results: We observed increased expression of 48 genes, including 29 immune-related genes. Correlation of CR DEGS and the hub genes yielded six immHub genes (RBBP4, KAT7, KANSL2, ACTB, TRRAP, and KAT2B). The AUC values in the ROC analysis were 0.861 in the training dataset and 0.83 in the validation dataset. Conclusions: Biomarkers such as RBBP4, KAT7, KANSL2, ACTB, TRRAP, and KAT2B may be associated with pAF, and relevant regulated microRNAs may be used as biomarkers or targets for the treatment of pAF. These findings could provide insights into the diagnosis, treatment, and prognosis evaluation of patients with pAF.