ArticleBMC medical genomics2020
Identification of potential crucial genes in atrial fibrillation: a bioinformatic analysis.
Article in BMC medical genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
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Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 41 citations in OpenAlex.
- Freely available genomic datasets for atrial fibrillation research: current resources and analytical pipeline.Frontiers in genetics · 2026Pooled it
- Meta-analysis of Transcriptomic Data Reveals Pathophysiological Modules Involved with Atrial Fibrillation.Molecular diagnosis & therapy · 2020Pooled it
- Atrial Cardiomyopathy: Pathophysiology, Diagnostic Approaches, and Prognostic Implications-A Narrative Review.Journal of clinical medicine · 2026Review
- Genetic background is associated with distinct patterns of proarrhythmogenic remodeling leading to atrial fibrillation in pigs with ischemic heart failure.Basic research in cardiology · 2026Article
- Association of serum bile acid profiles with the risk of gastrointestinal autonomic neuropathy in patients with type 2 diabetes mellitus.World journal of diabetes · 2026Article
- Genome-Wide Association Study of Body Mass Index in a Commercial Landrace × Yorkshire Crossbred Pig Population.Veterinary sciences · 2026Article
- Article
- An integrated bioinformatics approach for identification of key modulators and biomarkers involved in atrial fibrillation.Journal of cardiovascular and thoracic research · 2025Article
- Myeloid-specific S100A8/A9 deficiency attenuates atrial fibrillation through prevention of TLR4/NF-kB-mediated immune cell recruitment and inflammation.Frontiers in immunology · 2025Article
- Decoding core genes and intercellular communication in osteosarcoma: bioinformatic investigation and immune cell profiling for diagnostic and therapeutic insights.Discover oncology · 2024Article
- Cellular and Molecular Network Characteristics ofInternational journal of molecular sciences · 2024Article
- A centrosome-related gene signature for predicting the overall survival of uveal melanoma.Translational cancer research · 2024Article
- Integrated analysis and validation of ferroptosis-related genes and immune infiltration in acute myocardial infarction.BMC cardiovascular disorders · 2024Article
- Identification of Potential Crucial Biomarkers in STEMI Through Integrated Bioinformatic Analysis.Arquivos brasileiros de cardiologia · 2024Article
- Identification of atrial fibrillation-related genes through transcriptome data analysis and Mendelian randomization.Frontiers in cardiovascular medicine · 2024Article
- Bioinformatic Identification of Potential RNA Alterations on the Atrial Fibrillation Remodeling from Human Pulmonary Veins.International journal of molecular sciences · 2023Article
- Ablation of CXCR4 expression in cardiomyocytes exacerbates isoproterenol‑induced cell death and heart failure.International journal of molecular medicine · 2023Article
- Exploring the pathogenesis and immune infiltration in dilated cardiomyopathy complicated with atrial fibrillation by bioinformatics analysis.Frontiers in immunology · 2023Article
- Screening and Bioinformatics Analysis of Crucial Gene of Heart Failure and Atrial Fibrillation Based on GEO Database.Medicina (Kaunas, Lithuania) · 2022Article
- FAM201A, a long noncoding RNA potentially associated with atrial fibrillation identified by ceRNA network analyses and WGCNA.BMC medical genomics · 2022Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundAtrial fibrillation (AF) is at least partially 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.
methodsMicroarray data sets of GSE115574, GSE31821, GSE79768, GSE41177 and GSE14975 from the Gene Expression Omnibus (GEO) database were retrieved. After merging all microarray data and adjusting 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. Protein-protein interaction (PPI) network was constructed using the STRING database. Combined with aforementioned significant bioinformatics information, potential crucial genes were subsequently selected. The comparative toxicogenomics database (CTD) was used to explore the interaction between potential crucial genes and AF.
resultWe identified 27 of DEGs with gene expression fold change (FC) ≥ 1.5 or ≤ 2/3 (|log2 FC| ≥ 0.58) and 5 with FC ≥ 2 or ≤ 0.5 (|log2 FC| ≥ 1) 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. CTD showed CXCR4, IGFBP2, IGFBP3 and FHL2 had higher scores with AF.
conclusionsThe 9 potential crucial genes, especially CXCR4, IGFBP2, IGFBP3 and FHL2, may be associated with risk of AF. Our study provided new insights of AF into genetics, molecular pathogenesis and new therapeutic targets.
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