Atrial 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. Microarray 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. We 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. The 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.

中文翻译：

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心房颤动中潜在关键基因的鉴定：一种生物信息学分析。

心房颤动（AF）至少可以部分遗传，影响欧洲和美国2–3％的人口。但是，仍然缺乏相当大的遗传力。在本研究中，我们旨在通过公共数据集的生物信息学分析鉴定与房颤相关的潜在关键基因。从Gene Expression Omnibus（GEO）数据库中检索了GSE115574，GSE31821，GSE79768，GSE41177和GSE14975的微阵列数据集。合并所有微阵列数据并调整批处理效果后，鉴定出差异表达基因（DEG）。进行了基于基因本体论（GO）资源，京都基因与基因组百科全书（KEGG）资源，基因集富集分析（GSEA），反应组通路数据库和疾病本体论（DO）的功能富集分析。使用STRING数据库构建蛋白质-蛋白质相互作用（PPI）网络。结合上述重要的生物信息学信息，随后选择了潜在的关键基因。比较毒理基因组学数据库（CTD）用于探索潜在关键基因和AF之间的相互作用。与房颤患者相比，我们确定了27例基因表达倍数变化（FC）≥1.5或≤2/3（| log2 FC |≥0.58）的DEG和5例FC≥2或≤0.5（| log2 FC |≥1）的DEG。窦性心律控制。最显着富集的途径是调节胰岛素样生长因子转运和胰岛素样生长因子结合蛋白的摄取。IGFBP2，C1orf105，FHL2，CHGB，ATP1B4，IGFBP3，SLC26A9，CXCR4和HTR2B被认为是潜在的关键基因。CTD显示CXCR4，IGFBP2，IGFBP3和FHL2在AF方面得分较高。9种潜在的关键基因，尤其是CXCR4，IGFBP2，IGFBP3和FHL2，可能与房颤风险有关。我们的研究提供了AF遗传学，分子发病机制和新的治疗靶点的新见解。