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Updated: Jul 31, 2025
Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
Published on: July 20, 2022
Identification and verification of FN1, P4HA1 and CREBBP as potential biomarkers in human atrial fibrillation
Miao Zhu1, Tao Yan1, Shijie Zhu1
1Department of Cardiovascular Surgery, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai 200032, China.
Insights
Atrial fibrillation (AF) mechanisms were explored using bioinformatics. Three key genes (FN1, P4HA1, CREBBP) were identified as potential biomarkers for AF, showing elevated expression in patients.
Area of Science:
- Cardiology
- Bioinformatics
- Molecular Biology
Background:
- Atrial fibrillation (AF) is a prevalent arrhythmia linked to cardiac complications.
- The underlying mechanisms driving AF progression remain incompletely understood.
- Identifying novel biomarkers and molecular pathways is crucial for AF management.
Purpose of the Study:
- To investigate potential biomarkers and elucidate the molecular mechanisms associated with atrial fibrillation (AF).
- To identify key genes and pathways involved in the pathogenesis of AF using a bioinformatics approach.
Main Methods:
- Differential gene expression analysis of AF versus normal sinus rhythm (SR) samples using the "limma" R package.
- Weighted gene co-expression network analysis (WGCNA) to identify gene modules and functional relationships.
- Enrichment analyses (GO, KEGG) and protein-protein interaction network construction to pinpoint hub genes.
Main Results:
- 2,589 differentially expressed genes (DEGs) were identified and clustered into 10 modules.
- Enrichment analysis highlighted pathways related to extracellular matrix organization and cell adhesion.
- Three hub genes (FN1, P4HA1, CREBBP) were identified with significantly elevated mRNA expression in AF patients.
Conclusions:
- FN1, P4HA1, and CREBBP are strongly implicated in AF pathogenesis.
- These genes exhibit elevated expression and central roles in molecular networks within AF patients.
- The identified hub genes represent promising candidates for novel AF biomarkers and therapeutic targets.
Background:
Atrial fibrillation (AF) is a common arrhythmia that can lead to cardiac complications. The mechanisms involved in AF remain elusive. We aimed to explore the potential biomarkers and mechanisms underpinning AF.
Methods:
An independent dataset, GSE2240, was obtained from the Gene Expression Omnibus database. The R package, "limma", was used to screen for differentially expressed genes (DEGs) in individuals with AF and normal sinus rhythm (SR). Weighted gene co-expression network analysis (WGCNA) was applied to cluster DEGs into different modules based on functional disparities. Enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction network was constructed, and hub genes were identified using cytoHubba. Quantitative reverse-transcription PCR was used to validate mRNA expression in individuals with AF and SR.
Results:
We identified 2, 589 DEGs clustered into 10 modules using WGCNA. Gene Ontology analysis showed specific clustered genes significantly enriched in pathways associated with the extracellular matrix and collagen organization. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the target genes were mainly enriched for proteoglycans in cancer, extracellular matrix-receptor interaction, focal adhesion, and the PI3K-Akt signaling pathway. Three hub genes, FN1, P4HA1 and CREBBP, were identified, which were highly correlated with AF endogenesis. mRNA expression of hub genes in patients with AF were higher than in individuals with normal SR, consistent with the results of bioinformatics analysis.
Conclusions:
FN1, P4HA1, and CREBBP may play critical roles in AF. Using bioinformatics, we found that expression of these genes was significantly elevated in patients with AF than in individuals with normal SR. Furthermore, these genes were elevated at core positions in the mRNA interaction network. These genes should be further explored as novel biomarkers and target candidates for AF therapy.
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