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January 22, 2021Medical Science Monitor15 citationsOpen Access

Potential Target Genes in the Development of Atrial Fibrillation: A Comprehensive Bioinformatics Analysis

LLLiang LiuYYYun YuLHLonglong Hu

Key Result

A comprehensive bioinformatics analysis identified 6 key genes (FCGR3B, CLEC10A, FPR2, IGSF6, S100A9, and S100A12) as potential biomarkers and therapeutic targets for atrial fibrillation.

Structured PICO

P
Population
74 atrial appendage tissue samples (51 with persistent atrial fibrillation and 23 with normal sinus rhythm) analyzed via bioinformatics to identify differentially expressed genes.
C
Comparator
Sinus rhythm (SR) samples
O
Outcome
Identification of differentially expressed genes (DEGs) and key target genes for atrial fibrillation developmentsurrogate

Bioinformatics analysis identified six key genes involved in immune response and inflammation that may serve as potential therapeutic targets or biomarkers for atrial fibrillation.

Limitations

  • Clinical atrial tissue samples were not analyzed in the laboratory
  • Sample sizes were relatively small
  • Further investigation is required to determine whether the 6 key genes activate pathways known to induce AF in humans

Abstract

BACKGROUND Atrial fibrillation (AF) is the most prevalent arrhythmia worldwide. Although it is not life-threatening, the accompanying rapid and irregular ventricular rate can lead to hemodynamic deterioration and obvious symptoms, especially the risk of cerebrovascular embolism. Our study aimed to identify novel and promising genes that could explain the underlying mechanism of AF development. MATERIAL AND METHODS Expression profiles GSE41177, GSE79768, and GSE14975 were acquired from the Gene Expression Omnibus Database. R software was used for identifying differentially expressed genes (DEGs), and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were subsequently performed. A protein-protein interaction network was constructed in Cytoscape software. Next, a least absolute shrinkage and selection operator (LASSO) model was constructed and receiver-operating characteristic curve analysis was conducted to assess the specificity and sensitivity of the key genes. RESULTS We obtained 204 DEGs from the datasets. The DEGs were mostly involved in immune response and cell communication. The primary pathways of the DEGs were related to the course or maintenance of autoimmune and chronic inflammatory diseases. The top 20 hub genes (high scores in cytoHubba) were selected in the PPI network. Finally, we identified 6 key genes (FCGR3B, CLEC10A, FPR2, IGSF6, S100A9, and S100A12) via the LASSO model. CONCLUSIONS We present 6 target genes that are potentially involved in the molecular mechanisms of AF development. In addition, these genes are likely to serve as potential therapeutic targets.

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Cite This Study

Liu et al. (2021) studied Atrial Fibrillation (n=74). Atrial Fibrillation vs. Sinus rhythm was evaluated on Identification of key genes associated with atrial fibrillation. A comprehensive bioinformatics analysis identified 6 key genes (FCGR3B, CLEC10A, FPR2, IGSF6, S100A9, and S100A12) as potential biomarkers and therapeutic targets for atrial fibrillation.

synapsesocial.com/papers/6a9b8757bf09d7dcb67f2a62https://doi.org/10.12659/msm.928366
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