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阿尔茨海默病circRNA的差异表达及生物信息学分析
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Abstract:
目的：通过生物信息学方法，探讨阿尔茨海默病(AD)患者外周血中差异表达的环状RNA (circRNA)的生物学功能。方法：通过基因表达综合数据库(GEO)获取AD相关的数据集GSE186929，筛选AD患者外周血中差异表达的circRNAs，应用Circinteractome和miRDB数据库来预测circRNA靶向的miRNA，应用Starbase、miWalk、TargetScan8.0在线靶基因预测网站预测靶基因，利用jvenn获得靶基因合集，对差异表达的靶基因进行分析。运用David工具进行基因本体论(GO)和分析和京都基因与基因组百科全书(KEGG)通路分析。通过String在线网站构建蛋白互作(PPI)网络，应用Cytoscape筛选出3个关键基因。结果：共筛选出47个差异表达的circRNAs，其中13个下调，34个上调，选取最具有显著性差异的has_circRNA_0001928进一步预测miRNA，选取数据库中预测效果都较好的miR-142-5p进行靶基因预测，获得63个靶基因。GO和KEGG富集分析显示靶基因参与RNA转录、细胞分裂、基因表达调控等功能以及调节干细胞多能性的信号通路、脂质和动脉粥样硬化信号通路、人类巨细胞病毒感染等信号通路。3个关键基因为PUM2、OTUD4、RANBP2。结论：circRNA及其靶基因可能在AD的发病机制中发挥重要作用，circRNA可能是AD潜在的生物标志物和治疗靶点。
Objective: To investigate the biological functions of differentially expressed circular RNAs (circRNAs) in the peripheral blood of Alzheimer’s disease (AD) patients by bioinformatics methods. Methods: AD-related dataset GSE186929 was obtained from Gene Expression Omnibus (GEO), screening for differentially expressed circRNAs in the peripheral blood of AD patients, applying Circinteractome and miRDB databases to predict circRNA-targeted miRNAs, and applying Starbase, miWalk, TargetScan8.0 online target gene prediction website to predict target genes, and used jvenn to obtain target gene ensembles to analyze differentially expressed target genes. Gene ontology (GO) and analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using David tools. Protein Interaction (PPI) network was constructed through String online website and Cytoscape was applied to screen three key genes. Results: A total of 47 differentially expressed circRNAs were screened, of which 13 were down-regulated and 34 were up-regulated. The most significantly different has_circRNA_0001928 was selected for further miRNA prediction, and the miR-142-5p, which had good prediction results in the database, was selected for target gene prediction, resulting in 63 target genes. GO and KEGG enrichment analyses showed that the target genes were involved in the functions of RNA transcription, cell division, and regulation of gene expression as well as the signaling pathways regulating stem cell pluripotency, lipid and atherosclerosis signaling pathways, and human cytomegalovirus infection, etc. The three key genes were PUM2, OTUD4, and RANBP2. Conclusions: CircRNAs and their target genes may play an important role in the pathogenesis of AD, and circRNAs may be potential biomarkers and therapeutic targets for AD.
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