Key result
Bioinformatic analysis of microarray datasets identified 9 potential crucial genes, notably CXCR4, IGFBP2, IGFBP3, and FHL2, that are differentially expressed and may be associated with the risk of atrial fibrillation.
Why the study?
Atrial fibrillation is heritable, but a substantial proportion of its heritability remains unknown, prompting the identification of potential crucial genes through bioinformatic analyses.
Bioinformatic analysis of public microarray datasets identified 9 potential crucial genes and associated microRNAs that may serve as biomarkers or therapeutic targets for atrial fibrillation.
Hypothesis-generating for AF biomarkers; requires prospective validation before any clinical adoption.
Background Atrial fibrillation (AF) is clearly heritable, affecting 2-3% of the population in Europe and the USA. However, a substantial proportion of heritability is still lacking. In the present study, we aim to identify potential crucial genes associated with AF through bioinformatic analyses of public datasets.Methods Microarray data sets of GSE115574, GSE31821, GSE79768, GSE41177 and GSE14975 from the Gene Expression Omnibus (GEO) database were enrolled. After merging all microarray data and adjusted batch effect, differentially expressed genes (DEGs) were identified. Functional enrichment analyses based on Gene Ontology (GO) resource, Kyoto Encyclopedia of Genes and Genomes (KEGG) resource, Gene Set Enrichment Analysis (GSEA), Reactome Pathway Database and Disease Ontology (DO) were carried out for DEGs. Protein-protein interaction (PPI) network was constructed using the STRING database. Combined with aforementioned significant bioinformatics information, potential crucial genes were subsequently selected. The potential crucial genes coupled with corresponding predicted microRNAs involved in AF were then assessed.Result We identified 27 of DEGs with gene expression fold change (FC) ≥ 1.5 and 5 with FC ≥ 2 of AF patients compared with sinus rhythm controls. The most significantly enriched pathway was regulation of insulin-like growth factor transport and uptake by insulin-like growth factor binding proteins. IGFBP2, C1orf105, FHL2, CHGB, ATP1B4, IGFBP3, SLC26A9, CXCR4 and HTR2B were considered the potential crucial genes. Sixteen corresponding predicted microRNAs, of which 5 targeting IGFBP3 and 8 FHL2, might be associated with AF. The comparative toxicogenomics database (CTD) database showed CXCR4, IGFBP2, IGFBP3 and FHL2 had higher scores with AF.Conclusions The 9 potential crucial genes, especially CXCR4, IGFBP2, IGFBP3 and FHL2, may be associated with risk of AF. MicroRNAs targeting IGFBP3 and FHL2 may be potential biomarkers or therapeutic targets for AF. Our study provided new insights of AF into genetics, molecular pathogenesis and new therapeutic targets.
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Zhang et al. (2020) studied Atrial Fibrillation (n=77). Atrial fibrillation vs. Sinus rhythm was evaluated on Differentially expressed genes (DEGs) with |log2 FC| ≥ 0.58 and adjusted P < 0.05. Bioinformatic analysis of microarray datasets identified 9 potential crucial genes, notably CXCR4, IGFBP2, IGFBP3, and FHL2, that are differentially expressed and may be associated with the risk of atrial fibrillation.
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