Key result
In silico atrial tissue analysis identifies five key differentially expressed genes in AF versus SR.
Why the study?
The precise molecular mechanisms of AF pathogenesis remain unclear, prompting the use of bioinformatics tools to identify novel key genes and potential therapeutic targets.
This bioinformatics study identified five key genes (FGL2, IGFBP5, NNMT, PLA2G2A, and TNC) that may serve as potential biomarkers and therapeutic targets for atrial fibrillation.
May highlight novel AF biomarkers and targets; hypothesis-generating and requires validation before clinical consideration.
Atrial fibrillation (AF) is a prevalent cardiac arrhythmia worldwide and is characterized by a high risk of thromboembolism, ischemic stroke, and fatality. The precise molecular mechanisms of AF pathogenesis remain unclear. The purpose of this study was to use bioinformatics tools to identify novel key genes in AF, provide deeper insights into the molecular pathogenesis of AF, and uncover potential therapeutic targets. Four publicly available raw RNA-Seq datasets obtained through the ENA Browser, as well as proteomic analysis results, both derived from atrial tissues, were used in this analysis. Differential gene expression analysis was performed and cross-validated with proteomics results to identify common genes/proteins between them. A functional enrichment pathway analysis was performed. Cross-validation analysis revealed five differentially expressed genes, namely FGL2, IGFBP5, NNMT, PLA2G2A, and TNC, in patients with AF compared with those with sinus rhythm (SR). These genes play crucial roles in various cardiovascular functions and may be part of the molecular signature of AF. Furthermore, functional enrichment analysis revealed several pathways related to the extracellular matrix, inflammation, and structural remodeling. This study highlighted five key genes that constitute promising candidates for further experimental exploration as biomarkers as well as therapeutic targets for AF.
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Atzemian et al. (2023) studied Atrial fibrillation. In silico bioinformatics analysis vs. Sinus rhythm was evaluated on Differentially expressed genes and functional enrichment pathways. In silico analysis of atrial tissues identified five key differentially expressed genes (FGL2, IGFBP5, NNMT, PLA2G2A, and TNC) in patients with atrial fibrillation compared with sinus rhythm.
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