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Biophysics  2022 

阿尔茨海默病ceRNA调控网络的生物信息学分析
Bioinformatics Analysis of ceRNA Regulatory Network in Alzheimer’s Disease

DOI: 10.12677/BIPHY.2022.101001, PP. 1-13

Keywords: 阿尔茨海默症,ceRNA,网络,Alzheimer’s Disease, ceRNA, Network

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Abstract:

阿尔茨海默病(Alzheimer’s disease, AD)是痴呆症最常见的病因,它会导致衰老大脑中神经元的损伤和认知功能的退化。有证据表明非编码RNA (ncRNAs)参与AD相关的发病过程,并揭示了AD与竞争性内源性RNA (ceRNA)网络之间的潜在联系。鉴于此,本研究深入探讨ceRNA调控网络与AD疾病发病机制的潜在关系,为临床治疗提供基础。方法:通过GEO2R筛选差异mRNA和miRNA。利用DAVID对差异表达的mRNA作GO富集分析,筛选与神经系统疾病相关的通路中的差异性表达mRNA用作后续研究。选取top 10的miRNA (5个上调表达的miRNA和5个下调表达的miRNA),使用miRWalk 3.0数据库预测其与目标差异表达mRNA之间的靶向关系,对预测的靶向mRNA和通路筛选到的目标差异表达mRNA取交集,此mRNA作为后续研究的目标差异表达mRNA,使用Cytoscape软件构建miRNA-mRNA靶向调控网络关系图。分别利用DIANA和ENCORI数据库做lncRNA-miRNA和circRNA-miRNA关系对的预测。最后构建circRNA-miRNA-mRNA和lncRNA-miRNA-mRNA ceRNA调控网络,并进行分析,这将有助于理解和阐明AD的发病机制,并为AD的临床诊断提供可能选择的生物标志物。
Alzheimer’s disease (AD) is the most common cause of dementia. It will lead to the damage of neurons in the aging brain and the degradation of cognitive function. There is evidence that non-coding RNAs (ncRNAs) are involved in the pathogenesis of AD and reveal the potential rela-tionship between AD and competitive endogenous RNA (ceRNA) network. In view of this, this study deeply discusses the potential relationship between ceRNA regulatory network and the pa-thogenesis of AD disease, so as to provide a basis for clinical treatment. Differential mRNA and miRNA were screened by GEO2R. DAVID was used for go enrichment analysis of differentially ex-pressed mRNA to screen differentially expressed mRNA in pathways related to nervous system diseases for follow-up study. The miRNAs of top 10 (5 up-regulated miRNAs and 5 down-regulated miRNAs) were selected, and the targeting relationship between them and the target differentially expressed mRNA was predicted using miRWalk 3.0 database. The intersection of the predicted target mRNA and the target differentially expressed mRNA screened by the pathway was taken as the target differentially expressed mRNA for subsequent research. The relationship diagram of miRNA-mRNA targeted regulation network was constructed by Cytoscape software. DIANA and ENCORI database was used to predict the relationship between lncRNA-miRNA and circRNA-miRNA. Finally, circRNA-miRNA-mRNA and lncRNA-miRNA-mRNA ceRNA regulatory networks were con-structed and analyzed, which will help to understand and clarify the pathogenesis of AD and pro-vide possible biomarkers for clinical diagnosis of AD.

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