摘要
目的对阿尔茨海默病(Alzheimer’s disease,AD)患者血液相关内源性竞争RNA(Competing endogenous RNAs,ceRNA)网络综合分析,寻找诊断治疗的新方向。方法从基因表达综合数据库(Gene expression omnibus,GEO)下载AD患者血液相关芯片数据,对数据进行整理并筛选差异表达的长链非编码RNA(Long non-coding RNA,lncRNA)及信使RNA(Messenger RNA,mRNA)基因;利用miRcode,TargetScan,miRTarBase和miRDB数据库对lncRNA和微小RNA(MicroRNA,miRNA)进行预测并取对应数据的交集来构建ceRNA网络;使用Cytoscape的cytoHubba插件筛选ceRNA网络关键lncRNA;通过临床数据计算各关键LncRNA的AUC值来评估各关键LncRNA的诊断性能;使用STRING构建蛋白-蛋白相互作用(Protein-protein interaction,PPI)网络,再使用MCODE插件筛选关键基因模块;利用DAVID数据库对关键模块中的基因进行基因本体论(Gene ontology,GO)和京都基因与基因组百科全书(Kyoto encyclopedia of genes and genomes,KEGG)通路分析。结果共筛选出9个关键lncRNA[X染色体失活特异转录因子(X inactive specific transcription factor,XIST)、RNA聚合酶2亚基J4(RNA polymerase II subunit J4,POLR2J4)、多聚胞嘧啶结合蛋白1反义RNA1(Poly C binding protein-1 antisense RNA1,PCBP1-AS1)、Opa相互作用蛋白5反义RNA1(Opa interacting protein 5 antisense RNA1,OIP5-AS1)、核旁斑组装转录本1(Nuclear paraspeckle assembly transcript 1,NEAT1)、母系表达基因3(Maternally expressed 3,MEG3)、肺癌转移相关转录本1(Metastasis associated lung adenocarcinoma transcript 1,MALAT1)、钾电压阀门通道,混合器相关亚家族,β成员1反义转录物1(Potassium voltage-gated channel subfamily Q member 1 opposite strand/Antisense transcript 1,KCNQ1OT1)、DnaJ热休克蛋白家族成员C27反义RNA1(DnaJ heat shock protein family member C27 antisense RNA1,DNAJC27-AS1)],计算各lncRNA的AUC值发现MALAT1(AUC=1.000),NEAT1(AUC=0.878),XIST(AUC=0.967)、PCBP1-AS1(AUC=0.889)的诊断性能较好;对蛋白互作网络的关
Objective A comprehensive analysis of the blood-related competing endogenous RNAs(ceRNA) network of Alzheimer’s disease was conducted to find a new direction for diagnosis and treatment.Methods AD blood-related chip data were downloaded from GEO database, and differentally expressed Long non-coding RNA(lncRNA) and MicroRNA(mRNA) genes were sorted and screened. LncRNA and miRNA were predicted using miRcode, Target scan, miRTarBase and miRDB databases, and the intersection of corresponding results was taken to construct the ceRNA network. The hub lncRNAs of ceRNA network are identified using cytoHubbaplug-in. The diagnostic performance of each hub LncRNA was evaluated by calculating the AUC value. STRING was used to reconstructProtein-Protein Interaction(PPI) network, and the modules in the PPI network were identified using MCODE plug-in. DAVID was used to analyze the Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathways of genes in hub modules. Results A total of 9 hub lncRNAs were identified. They were X Inactive Specific Transcription Factor(XIST), RNA Polymerase II Subunit J4(POLR2 J4),Poly C Binding Protein-1 Antisense RNA1(PCBP1-AS1), Opa Interacting Protein 5 Antisense RNA 1(OIP5-AS1), Nuclear Paraspeckle Assembly Transcript 1(NEAT1), Maternally Expressed 3(MEG3), Metastasis Associated Lung Adenocarcinoma Transcript 1(MALAT1),Potassium Voltage-gated Channel Subfamily Q Member 1 Opposite Strand/Antisense Transcript 1(KCNQ1 OT1) and DnaJ Heat Shock Protein Family Member C27 Antisense RNA 1(DNAJC27-AS1). The Area Under The Curve(AUC) values of each lncRNA were calculated, and it was found that MALAT1(AUC=1.000), NEAT1(AUC=0.878), XIST(AUC=0.967) and PCBP1-AS1(AUC=0.889) had better diagnostic performance. Gene enrichment analysis showed that it was mainly concentrated in MAPK, PI3 K/Akt and insulin signaling pathways. Conclusion The ceRNA network in the blood promotes the occurrence and development of AD by regulating various pathways, among which MALAT1, NEAT1, XIST and PCBP1-AS1 have g
作者
张亚恒
魏冕
于亚亮
吕建周
安惠娟
王志涛
余晓斐
韩亚
马丹
徐品丽
Zhang Yaheng;Wei Mian;Yu Yaliang(Department of Neurology,the Second Affiliated Hospital and College of Clinical Medicine of Henan University of Science,Luoyang Henan 471003)
出处
《卒中与神经疾病》
2021年第4期396-401,共6页
Stroke and Nervous Diseases
基金
河南省医学科技攻关计划(联合共建)项目(LHGJ20200598)。
