Wen Zilu, Wu Liwei, Wang Lin, Ou Qinfang, Ma Hui, Wu Qihang, Zhang Shulin, Song Yanzheng
Department of Scientific Research, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Department of Thoracic Surgery, Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.
Front Genet. 2022 Mar 7;13:832739. doi: 10.3389/fgene.2022.832739. eCollection 2022.
The purpose of this study is to use the data in the GEO database to analyze, screen biomarkers that can diagnose tuberculosis, and verification of candidate biomarkers. GSE158767 dataset were used to process WGCNA analysis, differential gene analysis, Gene ontology and KEGG analysis, protein-protein network analysis and hub genes analysis. Based on our previous study, the intersect between WGCNA and differential gene analysis could be used as candidate biomarkers. Then, the enzyme-linked immunosorbent assay was used to validate candidate biomarkers, and receiver operating characteristic was used to assess diagnose ability of candidate biomarkers. A total of 412 differential genes were screened. And we obtained 105 overlapping genes between DEGs and WGCNA. GO and KEGG analysis showed that most of the differential genes were significantly enriched in innate immunity. A total of 15 hub genes were screened, and four of them were verified by Enzyme-linked immunosorbent assay. CCL5 performed well in distinguishing the healthy group from the TB group (AUC = 0.723). And CCL19 performed well in distinguishing the TB group from the ORD groups (AUC = 0.811). CCL19, C1Qb, CCL5 and HLA-DMB may play important role in tuberculosis, which indicated four genes may become effective biomarkers and could be conveniently used to facilitate the individual tuberculosis diagnosis in Chinese people.
本研究的目的是利用基因表达综合数据库(GEO数据库)中的数据,分析、筛选可诊断结核病的生物标志物,并对候选生物标志物进行验证。使用GSE158767数据集进行加权基因共表达网络分析(WGCNA分析)、差异基因分析、基因本体论(Gene ontology)和京都基因与基因组百科全书(KEGG)分析、蛋白质-蛋白质网络分析以及枢纽基因分析。基于我们之前的研究,WGCNA分析与差异基因分析的交集可作为候选生物标志物。然后,采用酶联免疫吸附测定法验证候选生物标志物,并使用受试者工作特征曲线评估候选生物标志物的诊断能力。共筛选出412个差异基因。我们在差异表达基因(DEGs)和WGCNA之间获得了105个重叠基因。基因本体论和KEGG分析表明,大多数差异基因在固有免疫中显著富集。共筛选出15个枢纽基因,其中4个通过酶联免疫吸附测定法得到验证。趋化因子配体5(CCL5)在区分健康组和结核病组方面表现良好(曲线下面积[AUC]=0.723)。趋化因子配体19(CCL19)在区分结核病组和其他呼吸道疾病(ORD)组方面表现良好(AUC=0.811)。CCL19、补体C1q亚成分b(C1Qb)、CCL5和人组织相容性复合体Ⅱ类分子DR亚区MB链(HLA-DMB)可能在结核病中发挥重要作用,这表明这四个基因可能成为有效的生物标志物,可方便地用于促进中国人结核病的个体诊断。