Korma Workneh, Mihret Adane, Chang Yunhee, Tarekegn Azeb, Tegegn Metasebiya, Tuha Adem, Hwang Dasom, Asefa Mesfin, Hasen Mahlet O, Kim Seoyoung, Tesema Tesfaye S, Lee Hyeyoung
Molecular Diagnostic Laboratory, Department of Biomedical Laboratory Sciences, Yonsei University, Wonju 26493, Korea.
Institute of Biotechnology, Addis Ababa University, Addis Ababa, P.O. Box 1176, Ethiopia.
Diagnostics (Basel). 2020 Sep 18;10(9):716. doi: 10.3390/diagnostics10090716.
Tuberculosis infection exhibits different forms, namely, pulmonary, extrapulmonary, and latent. Here, diagnostic markers based on the gene expression of cytokines and chemokines for differentiating between tuberculosis infection state(s) were identified. Gene expression of seven cytokines (Interferon gamma (IFN-γ), Interferon gamma-induced protein 10 (IP-10), Interleukin-2 receptor (IL-2R), C-X-C Motif Chemokine Ligand 9 (CXCL-9), Interleukin 10 (IL-10), Interleukin 4 (IL-4), and Tumor Necrosis Factor alpha (TNF-α)) in response to tuberculosis antigen was analyzed using real-time polymerase reaction. The sensitivity and specificity of relative quantification (2^) of mRNA expression were analyzed by constructing receiver operating characteristic curves and measuring the area under the curve (AUC) values. Combinations of cytokines were analyzed using the R statistical software package. IFN-γ, IP-10, IL2R, and CXCL-9 showed high expression in latent and active tuberculosis patients ( = 0.001), with a decrease in IL10 expression, and no statistical difference in IL-4 levels among all the groups ( = 0.999). IL-10 differentiated pulmonary tuberculosis patients from latent cases with an AUC of 0.731. IL10 combined with CXCL-9 distinguished pulmonary tuberculosis patients from extrapulmonary cases with a sensitivity, specificity, and accuracy of 85.7%, 73.9%, and 81.0%, respectively. IL-10 together with IP-10 and IL-4 differentiated pulmonary tuberculosis from latent cases with a sensitivity and specificity of 77.1% and 88.1%, respectively. Decision tree analysis demonstrated that IFN-γ IL-2R, and IL-4 can diagnose tuberculosis infection with a sensitivity, specificity, and accuracy of 89.7%, 96.1%, and 92.7%, respectively. A combination of gene expression of cytokines and chemokines might serve as an effective marker to differentiate tuberculosis infection state(s).
结核病感染呈现出不同的形式,即肺结核、肺外结核和潜伏性结核。在此,确定了基于细胞因子和趋化因子基因表达的诊断标志物,用于区分结核病感染状态。使用实时聚合酶反应分析了七种细胞因子(干扰素γ(IFN-γ)、干扰素γ诱导蛋白10(IP-10)、白细胞介素-2受体(IL-2R)、C-X-C基序趋化因子配体9(CXCL-9)、白细胞介素10(IL-10)、白细胞介素4(IL-4)和肿瘤坏死因子α(TNF-α))对结核抗原的基因表达。通过构建受试者工作特征曲线并测量曲线下面积(AUC)值,分析了mRNA表达相对定量(2^)的敏感性和特异性。使用R统计软件包分析细胞因子的组合。IFN-γ、IP-10、IL2R和CXCL-9在潜伏性和活动性结核病患者中表现出高表达(P = 0.001),IL10表达降低,且所有组中IL-4水平无统计学差异(P = 0.999)。IL-10区分肺结核患者和潜伏病例的AUC为0.731。IL10与CXCL-9联合区分肺结核患者和肺外结核病例的敏感性、特异性和准确性分别为85.7%、73.9%和81.0%。IL-10与IP-10和IL-4联合区分肺结核和潜伏病例的敏感性和特异性分别为77.1%和88.1%。决策树分析表明,IFN-γ、IL-2R和IL-4诊断结核病感染的敏感性、特异性和准确性分别为89.7%、96.1%和92.7%。细胞因子和趋化因子的基因表达组合可能作为区分结核病感染状态的有效标志物。