Department of Virology and Biotechnology, ICMR-National Institute for Research in Tuberculosis (NIRT), Chetpet, Chennai 600031, India.
Dr. DY Patil Medical College, Hospital and Research Centre, Pimpri, Pune 411018, India.
Genes (Basel). 2022 Mar 29;13(4):616. doi: 10.3390/genes13040616.
Tuberculosis (TB) is an infectious disease caused by (). Our integrative analysis aims to identify the transcriptional profiling and gene expression signature that distinguish individuals with active TB (ATB) disease, and those with latent tuberculosis infection (LTBI). In the present study, we reanalyzed a microarray dataset (GSE37250) from GEO database and explored the data for differential gene expression analysis between those with ATB and LTBI derived from Malawi and South African cohorts. We used BRB array tool to distinguish DEGs (differentially expressed genes) between ATB and LTBI. Pathway enrichment analysis of DEGs was performed using DAVID bioinformatics tool. The protein-protein interaction (PPI) network of most upregulated genes was constructed using STRING analysis. We have identified 375 upregulated genes and 152 downregulated genes differentially expressed between ATB and LTBI samples commonly shared among Malawi and South African cohorts. The constructed PPI network was significantly enriched with 76 nodes connected to 151 edges. The enriched GO term/pathways were mainly related to expression of IFN stimulated genes, interleukin-1 production, and NOD-like receptor signaling pathway. Downregulated genes were significantly enriched in the Wnt signaling, B cell development, and B cell receptor signaling pathways. The short-listed DEGs were validated in a microarray data from an independent cohort (GSE19491). ROC curve analysis was done to assess the diagnostic accuracy of the gene signature in discrimination of active and latent tuberculosis. Thus, we have derived a seven-gene signature, which included five upregulated genes , , , , and two downregulated genes and , as a biomarker for discrimination of active and latent tuberculosis. The identified genes have a sensitivity of 80-100% and specificity of 80-95%. Area under the curve (AUC) value of the genes ranged from 0.84 to 1. This seven-gene signature has a high diagnostic accuracy in discrimination of active and latent tuberculosis.
结核病(TB)是一种由()引起的传染病。我们的综合分析旨在确定区分活动性结核病(ATB)患者和潜伏性结核感染(LTBI)患者的转录谱和基因表达特征。在本研究中,我们重新分析了 GEO 数据库中的微阵列数据集(GSE37250),并探索了来自马拉维和南非队列的 ATB 和 LTBI 之间差异基因表达分析的数据。我们使用 BRB 阵列工具来区分 ATB 和 LTBI 之间的差异表达基因(DEGs)。使用 DAVID 生物信息学工具对 DEGs 进行通路富集分析。使用 STRING 分析构建大多数上调基因的蛋白质-蛋白质相互作用(PPI)网络。我们已经确定了 375 个上调基因和 152 个下调基因,这些基因在马拉维和南非队列中共同差异表达。构建的 PPI 网络与 151 个边缘连接的 76 个节点显著富集。富集的 GO 术语/途径主要与 IFN 刺激基因的表达、白细胞介素-1 产生和 NOD 样受体信号通路有关。下调基因在 Wnt 信号通路、B 细胞发育和 B 细胞受体信号通路中显著富集。在一个独立队列(GSE19491)的微阵列数据中验证了简表 DEGs。进行 ROC 曲线分析以评估基因特征在区分活动性和潜伏性结核病中的诊断准确性。因此,我们已经得出了一个由七个基因组成的特征,其中包括五个上调基因 、 、 、 、 和两个下调基因 和 ,作为区分活动性和潜伏性结核病的生物标志物。鉴定的基因具有 80-100%的敏感性和 80-95%的特异性。基因的曲线下面积(AUC)值范围为 0.84 至 1。该七个基因特征在区分活动性和潜伏性结核病方面具有较高的诊断准确性。