Abstract

BackgroundThe complex relationship between atrial fibrillation (AF) and type 2 diabetes mellitus (T2DM) suggests a potential role for epicardial adipose tissue (EAT) that requires further investigation. This study employs bioinformatics and experimental approaches to clarify EAT's role in linking T2DM and AF, aiming to unravel the biological mechanisms involved. MethodBioinformatics analysis initially identified common differentially expressed genes (DEGs) in EAT from T2DM and AF datasets. Pathway enrichment and network analyses were then performed to determine the biological significance and network connections of these DEGs. Hub genes were identified through six CytoHubba algorithms and subsequently validated biologically. Experimentally, db/db mice were utilized to establish a T2DM model. AF induction was executed via programmed transesophageal electrical stimulation and burst pacing, focusing on comparing the incidence and duration of AF. Frozen sections and Hematoxylin and Eosin (H&E) staining were utilized to illuminate the structures of the heart and EAT. Moreover, quantitative PCR (qPCR) measured the expression of hub genes. ResultsThe study identified 106 DEGs in EAT from T2DM and AF datasets, underscoring significant pathways in energy metabolism and immune regulation. Three hub genes, CEBPZ, PAK1IP1, and BCCIP, emerged as pivotal in this context. In db/db mice, a marked predisposition towards AF induction and extended duration was observed, with HE staining verifying the presence of EAT. Additionally, qPCR validated significant changes in hub genes expression in db/db mice EAT. In-depth analysis identified 299 miRNAs and 33 TFs as potential regulators, notably GRHL1 and MYC. GeneMANIA analysis highlighted the hub genes' critical roles in stress responses and leukocyte differentiation, while immune profile correlations highlighted their impact on mast cells and neutrophils, emphasizing the genes' significant influence on immune regulation within the context of T2DM and AF. ConclusionThis investigation reveals the molecular links between T2DM and AF with a focus on EAT. Targeting these pathways, especially EAT-related ones, may enable personalized treatments and improved outcomes.

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