Identification of potential novel biomarkers and therapeutic targets involved in human atrial fibrillation based on bioinformatics analysis
Identification of potential novel biomarkers and therapeutic targets involved in human atrial fibrillation based on bioinformatics analysis
复制标题
基于生物信息学分析识别人类心房颤动潜在的新型生物标志物和治疗靶点
DOI：
10.33963/kp.15339
复制
发表时间：
2020-08-25
影响因子：
3.3
通讯作者：
Wei, Jin
中科院分区：
文献类型：
--
作者：
Fan, Gang;Wei, Jin
背景房颤是最常见的心律失常。然而，房颤的确切分子机制仍不清楚。我们的研究旨在基于生物信息学分析确定与房颤相关的潜在生物标志物和途径。方法GSE79768人心脏组织数据集来自基因表达总表(GEO)数据库。共收集26例心脏组织标本，其中房颤14例，窦性心律12例，对差异表达基因(Deg)进行鉴定。结果房颤组和窦性心律组共鉴定出260个基因，其中上调基因150个，下调基因110个。功能和途径分析表明，DEGS主要参与炎症反应、免疫反应和受体介导的内吞作用。此外，CXCR4、CXCR2、C3、CXCL11、CCR2、AGTR2、CXCL1等也是蛋白质-蛋白质相互作用网络中的枢纽节点，模块分析表明这些枢纽节点还显著丰富了炎症反应、细胞因子-细胞因子受体相互作用、趋化因子信号转导和神经活性配体-受体相互作用途径。此外，miRNA靶向调控网络分析表明，58个miRNA参与了61个调控关系，其中9个上调，5个下调。结论本研究发现了一系列关键基因，包括CXCR4、CXCR2、CXCL11、CCR2、LRRK2、IL1B、C3、CXCL1，以及重要的miRNAs，如miR-3123、miR-548G-3p和miR-9-5p，以及与人类房颤关系最密切的通路。我们的结果可能为房颤的治疗提供新的分子机制和潜在的治疗靶点。
BACKGROUND Atrial fibrillation (AF) is the most common arrhythmia. However, exact molecular mechanism of AF remains unclear.AIMS Our study aimed to identify underlying biomarkers and pathways involved in AF based on bioinformatics analysis.METHODS The GSE79768 human heart tissue dataset was obtained from the Gene Expression Omnibus (GEO) database. A total of 26 heart tissue samples including 14 AF atrium heart tissue samples and 12 sinus rhythm heart tissue samples were used to identify the differentially expressed genes (DEGs). The functional enrichment analysis, protein-protein interaction network, and miRNA-targeted gene regulatory network analysis were performed.RESULTS A total of 260 DEGs were identified in the AF and sinus rhythm groups, including 150 up-regulated and 110 down-regulated genes. Functional and pathway enrichment analyses of DEGs indicated that they were mainly involved in inflammatory response, immune response, and receptor-mediated endocytosis. In addition, CXCR4, CXCR2, C3, CXCL11, CCR2, AGTR2, CXCL1, and others were the hub nodes in the protein-protein interaction network and module analysis revealed that these hub nodes were also significantly enriched in the inflammatory response, cytokine-cytokine receptor interaction, chemokine signaling, and neuro-active ligand-receptor interaction pathways. Furthermore, miRNA-targeted regulatory network analysis showed that 58 miRNA were involved in 61 regulatory relationships including 9 up-regulated and 5 down-regulated genes.CONCLUSIONS This study identified a series of key genes, including CXCR4, CXCR2, CXCL11, CCR2, LRRK2, IL1B, C3, CXCL1, and important miRNAs such as miR-3123, miR-548g-3p, and miR-9-5p, along with pathways that were most closely related to human AF. Our results may provide a novel molecular mechanism and potential therapeutic targets for AF.