结核病患者外周血单个核细胞内环状RNA表达谱分析及诊断标识的鉴定  

Profile analysis of circRNA expression and identification of diagnostic markers in peripheral blood mononuclear cells of tuberculosis patients

作　　者：王颖超 刘唯夷 姬秀秀 尚雪恬 贾红彦[1] 张蓝月 孙琦[1] 杜博平 朱传智 潘丽萍[1] 张宗德[1] Wang Yingchao;Liu Weiyi;Ji Xiuxiu;Shang Xuetian;Jia Hongyan;Zhang Lanyue;Sun Qi;Du Boping;Zhu Chuanzhi;Pan Liping;Zhang Zongde(Department of Molecular Biology/Beijing Key Laboratory for Drug-resistant Tuberculosis Research/Beijing Chest Hospital,Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute,Beijing 101149,China)

机构地区：[1]分子生物学实验室/耐药结核病研究北京市重点实验室/首都医科大学附属北京胸科医院/北京市结核病胸部肿瘤研究所,北京101149

出　　处：《中国防痨杂志》2025年第4期460-470,共11页Chinese Journal of Antituberculosis

基　　金：国家自然科学基金(82172279,82402641);北京市高层次公共卫生人才项目(G2024-2-007);北京市自然科学基金(7242025)。

摘　　要：目的:揭示结核病患者外周血单个核细胞(peripheral blood mononuclear cells,PBMCs)内环状RNA(circular RNA,circRNA)表达谱,并验证获得具有结核病诊断价值的潜在circRNAs,评估其诊断性能。方法:通过微阵列芯片检测,获得结核病患者及健康人PBMCs内circRNAs表达谱。使用加权基因共表达网络分析(weighted gene co-expression network analysis,WGCNA)筛选出结核病相关的关键模块。通过基因本体论(gene ontology,GO)、京都基因和基因组百科全书(Kyoto encyclopedia of genes and genomes,KEGG)及免疫浸润分析,探索关键模块中基因的功能。再通过验证集对关键模块中的部分circRNAs进行实时荧光定量PCR检测以验证芯片结果,并进行受试者工作特征(receiver operating characteristic,ROC)曲线分析,评估候选circRNAs的诊断效能,同时对候选circRNAs与临床特征进行Pearson相关性分析。结果:通过WGCNA分析,共确定16个模块,其中棕色模块是结核病最强相关模块。功能富集分析显示,棕色模块中基因主要富集于T细胞受体信号通路、丝裂原活化蛋白激酶信号通路、动物细胞线粒体自噬、铁死亡、泛素介导的蛋白水解等功能途径。基于棕色模块基因的免疫浸润分析提示,CD8^(+)T细胞(P<0.001)、静息记忆CD4^(+)T细胞(P<0.0001)、单核细胞(P<0.001)等细胞比例在两组间差异均有统计学意义。在棕色模块中,以P<0.05,差异倍数(fold change,fc)>4或<0.25,同时至少一组平均表达量均值>10为标准,筛选组间差异基因,共得到9个结核病特异性circRNAs,其中hsa_circ_0052124在结核病患者样本中明显低表达(Z=―6.328,P<0.0001),ROC曲线下面积为0.976(95%CI:0.940~1.000,P<0.0001),敏感度为90.0%(95%CI:73.5%~97.9%),特异度为100.0%(95%CI:88.4%~100.0%),可以有效区分结核病患者和健康对照。经Pearson相关性分析,结核病患者外周血载脂蛋白B(r=0.715)、脂蛋白(a)(r=0.598)、血糖(r=0.575)水平与hsa_circ_0052124水平均呈正Objective:This study aims to uncover the expression profile of circular RNAs(circRNAs)in peripheral blood mononuclear cells(PBMCs)from tuberculosis(TB)patients,and identify potential circRNAs as diagnostic biomarkers for TB.Methods:Microarray chip was used to get the circRNA expression profiles of PBMCs from TB patients and healthy controls(HCs).Weighted gene co-expression network analysis(WGCNA)was employed to identify critical gene modules strongly associated with TB.The functions of genes within these key modules were further explored through gene ontology(GO),Kyoto encyclopedia of genes and genomes(KEGG),and immune infiltration analysis.Subsequently,the circRNAs derived from the key modules and had significant differences between TB and HCs,were validated by real-time fluorescent quantitative PCR(qPCR)in an independent validation sample set,to verify the microarray results.The receiver operating characteristic(ROC)curve analysis was performed to assess the diagnostic performance of these candidate circRNAs.Additionally,Pearson correlation analysis was conducted for the candidate circRNAs and clinical features.Results:Through WGCNA analysis,a total of 16 gene modules were identified,with the brown module being the most strongly associated with TB.Functional enrichment analysis revealed that genes in the brown module were primarily enriched in T cell receptor signaling pathway,mitogen-activated protein kinase signaling pathway,mitochondrial autophagy in animal cells,ferroptosis,ubiquitin-mediated proteolysis and other functional pathways.Immune infiltration analysis based on the genes in the brown module indicated significant differences in the proportion of CD8^(+)T cells(P<0.001),resting memory CD4^(+)T cells(P<0.0001)and monocytes(P<0.001)between the TB and HCs group.In the brown module,nine TB-specific circRNAs were identified based on the selection criteria(P<0.05,fold change>4 or<0.25,and the mean expression value>10 in at least one group).Among them,hsa_circ_0052124’s expression level was significantly

关 键 词：结核 核糖核酸 分枝杆菌感染 基因表达 免疫 

分 类 号：R52[医药卫生—内科学]