长链非编码RNA LOC107987438在抑郁障碍调控网络中的生物信息学分析

Bioinformatics analysis of regulatory network of long non-coding RNA LOC107987438 in depressive disorder

目的探讨差异表达长链非编码RNA(long non-coding RNA,lncRNA)LOC107987438在抑郁障碍发病机制中的调控作用,为其在抑郁障碍的临床应用提供理论依据。方法采用实时荧光定量聚合酶链反应(quantitative real-time polymerase chain reaction,qRT-PCR)在60例抑郁障碍患者和60例健康对照的外周血单核细胞(peripheral blood monocular cells,PBMCs)中验证LOC107987438的差异表达,并通过受试者工作特征(receiver operating characteristic,ROC)曲线评估其诊断价值。基于lncRNA的竞争性内源性RNA(competing endogenous RNA,ceRNA)机制,应用miRDB数据库预测LOC107987438的靶miRNA,选取其中目标评分数≥80的miRNA。再将筛选出的miRNA通过TargetScan 8.0、miRTarBase、mirDIP和miRPathDB 2.0数据库预测其潜在靶mRNA。随后,将预测的靶mRNA通过R 4.1.1的ClusterProfiler 4.0.5软件包进行基因本体论(gene ontology,GO)功能注释和京都基因和基因组百科全书(tokoyo encyclopedia of genes and genomes,KEGG)通路富集分析。最后利用STRING 11.5平台构建蛋白质相互作用网络并筛选出关键基因。结果qRT-PCR结果表明抑郁患者PBMCs中归一化的LOC107987438表达水平高于健康对照(抑郁障碍组:2.084±1.357;健康对照组:1.000±0.660,P<0.001)。ROC曲线结果显示LOC107987438的曲线下面积(area under curves,AUC)为0.759(95%CI:0.675~0.842,P<0.05),表明其具有较高的诊断价值。生物信息学分析发现hsa-miR-4670-3p、hsa-miR-619-3p、hsa-miR-6721-5p和hsa-miR-297是与LOC107987438结合度较高的miRNA。KEGG富集分析出的缺氧诱导因子-1(hypoxia-inducible factor 1,HIF-1)信号通路、磷脂酰肌醇3激酶-蛋白质丝氨酸苏氨酸激酶(phosphatidylinositol 3-kinase-AKT,PI3K-Akt)信号通路、酪氨酸激酶受体(erythroblastic oncogene B,ErbB)信号通路与抑郁障碍密切相关。通过蛋白质相互作用网络筛出前十的关键基因中,大鼠肉瘤病毒癌基因同源物(kirsten rats arcomaviral oncogene homolog,KRAS)、雄激素受体(androgen receptor,AR)、环腺苷酸反应元件结合蛋白1(cyclic-AMP response binding protein1,CREB1)、胰岛素样生长因子(insulin-like growth factor 1,IGF1)、细胞周期蛋白依赖性激酶抑制因子1B(cyclin-dependent kinase inhibitor 1B,CDKN1B)、钙/钙调素蛋白依赖性蛋白激酶Ⅱα(calcium/calmodulin-dependent protein kinase typeⅡalpha,CAMK2A)与抑郁障碍密切相关。结论抑郁障碍差异表达LOC107987438的ceRNA调控网络的建立为探索抑郁障碍的病理生理学机制提供理论基础。

Objective To investigate the regulatory role of defferentially expressed LOC107987438 in the pathogenesis of depressive disorder and provide a theoretical basis for its clinical application in depressive disorder.Methods Differential expression of LOC107987438 was verified by quantitative real-time polymerase chain reaction(qRT-PCR)in peripheral blood monocular cells(PBMCs)of 60 patients with depressive disorder and 60 health controls.In addition,its diagnostic value was assessed by receiver operating characteristic(ROC)curves.Based on the ceRNA mechanism of lncRNA,the miRDB database was applied to predict the target miRNAs of LOC107987438,and the miRNAs with target score≥80 among them were screened out.The screened miRNAs were then used to predict their potential target mRNAs through four databases which were TargetScan 8.0,miRTarBase,mirDIP and miRPathDB.Moreover,the predicted target mRNAs were annotated for gene ontology(GO)function annotation and tokoyo encyclopedia of genes and genomes(KEGG)pathway enrichment analysis via ClusterProfiler 4.0.5 package of R 4.1.1.Finally,a protein-protein interaction network was constructed using the STRING 11.5 platform to retrieve the interacting genes.Results The qRT-PCR results showed that normalized expression of LOC107987438 in PBMCs of patients with depressive disorder was higher than that in health controls(depressive disorder:2.084±1.357,health controls:1.000±0.660,P<0.001).The ROC curve results showed that the area under curves(AUC)of LOC107987438 was 0.759(95%CI:0.675-0.842,P<0.05),indicating its high potential diagnostic value.Bioinformatics analysis showed that hsa-miR-4670-3p,hsa-miR-619-3p,hsa-miR-6721-5p and hsa-miR-297 were the miRNAs with high bindings to LOC107987438.The results of KEGG signaling pathway enrichment revealed that hypoxia-inducible factor 1(HIF-1)signaling pathway,phosphatidylinositol 3-kinase-AKT(PI3K-Akt)signaling pathway and erythroblastic oncogene B(ErbB)signaling pathway were closely associated with depressive disorder.Among the top ten key genes screened by the protein-protein interaction network,kirsten rats arcomaviral oncogene homolog(KRAS),androgen receptor(AR),cyclic-AMP response binding protein1(CREB1),insulin-like growth factor 1(IGF1),cyclin-dependent kinase inhibitor 1B(CDKN1B)and calcium/calmodulin-dependent protein kinase typeⅡalpha(CAMK2A)were strongly associated with depressive disorder.Conclusion The establishment of ceRNA regulatory network of LOC107987438 provides a theoretical basis for exploring the pathophysiology of depressive disorders.