潜伏性结核感染和活动性结核病的免疫相关诊断模型构建
Construction of Immune-Related Diagnostic Model for Latent Tuberculosis Infection and Active Tuberculosis.
作者信息
Zhang Zhihua, Wang Yuhong, Zhang Yankun, Geng Shujun, Wu Haifeng, Shao Yanxin, Kang Guannan
机构信息
Department of Science & Education, Hebei Chest Hospital, Hebei Provincial Key Laboratory of Lung Disease, Shijiazhuang, People's Republic of China.
Department of Tuberculosis, Hebei Chest Hospital, Hebei Provincial Key Laboratory of Lung Disease, Shijiazhuang, People's Republic of China.
出版信息
J Inflamm Res. 2024 Apr 24;17:2499-2511. doi: 10.2147/JIR.S451338. eCollection 2024.
BACKGROUND
Tuberculosis (TB) is one of the most infectious diseases caused by (), and the diagnosis of active tuberculosis (TB) and latent TB infection (LTBI) remains challenging.
METHODS
Gene expression files were downloaded from the GEO database to identify the differentially expressed genes (DEGs). The ssGSEA algorithm was applied to assess the immunological characteristics of patients with LTBI and TB. Weighted gene co-expression network analysis, protein-protein interaction network, and the cytoHubba plug-in of Cytoscape were used to identify the real hub genes. Finally, a diagnostic model was constructed using real hub genes and validated using a validation set.
RESULTS
Macrophages and natural killer cells were identified as important immune cells strongly associated with TB. In total, 726 mRNAs were identified as DEGs. MX1, STAT1, IFIH1, DDX58, and IRF7 were identified as real hub immune-related genes. The diagnostic model generated by the five real hub genes could distinguish active TB from healthy controls or patients with LTBI.
CONCLUSION
Our study may provide implications for the diagnosis and drug development of infections.
背景
结核病（TB）是由（）引起的最具传染性的疾病之一，活动性结核病（TB）和潜伏性结核感染（LTBI）的诊断仍然具有挑战性。
方法
从GEO数据库下载基因表达文件以鉴定差异表达基因（DEG）。应用单样本基因集富集分析（ssGSEA）算法评估LTBI和TB患者的免疫特征。使用加权基因共表达网络分析、蛋白质-蛋白质相互作用网络以及Cytoscape的cytoHubba插件来鉴定真正的核心基因。最后，使用真正的核心基因构建诊断模型并使用验证集进行验证。
结果
巨噬细胞和自然杀伤细胞被确定为与TB密切相关的重要免疫细胞。总共鉴定出726个mRNA作为DEG。MX1、STAT1、IFI1、DDX58和IRF7被确定为真正的核心免疫相关基因。由这五个真正的核心基因生成的诊断模型可以区分活动性TB与健康对照或LTBI患者。
结论
我们的研究可能为感染的诊断和药物开发提供启示。
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