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通过整合生物信息学和机器学习,识别与肺外结核病免疫透相关的诊断生物标志物

Yanan Wang¹, Faxiang Jin¹, Weifang Mao¹

¹Department of Clinical Laboratory, Affiliated Hospital of Shaoxing University, Shaoxing, Zhejiang, China.

Frontiers in microbiology

|February 22, 2024

概括

新的生物标志物CARD17和GBP5显示出肺外结核 (EPTB) 的高诊断效率. 这些基因与免疫细胞透有关,为改善EPTB诊断提供了一个有希望的途径.

科学领域:

* 免疫学免疫学
* 分子生物学 * 分子生物学
* 生物信息学是一门学科.

背景情况:

*结核病的诊断依赖于检测Mycobacterium结核病 (Mtb) 的情况.
* 肺外结核 (EPTB) 的诊断是具有挑战性的,因为细微的症状和不充分的诊断测试.
*确定EPTB可靠的生物标志物对于及时和准确的患者管理至关重要.

研究的目的:

* 为了确定肺外结核 (EPTB) 的新型诊断生物标志物.
* 调查EPTB患者潜在生物标志物和免疫细胞透之间的关系.
* 在独立数据集中验证已识别的基因的诊断能力.

主要方法:

*对GSE83456数据集的差异基因表达分析,以确定DEGs.
*权重基因共同表达网络分析 (WGCNA),以找到与EPTB相关的模块.
*使用LASSO和SVM-RFE进行特征选择,以确定关键基因.
* 在GSE144127数据集和RT-qPCR中验证候选基因.
*单个样本基因丰富分析 (ssGSEA) 用于评估免疫细胞透.

主要成果:

*确定了110个差异表达基因 (DEGs),这些基因在免疫和炎症途径中富含.
*与EPTB密切相关的WGCNA绿模块包含96个DEG.
* CARD17和GBP5成为具有高诊断能力的关键基因 (AUC分别为0.763和0.833).
* 在EPTB中观察到17种免疫细胞亚型的显著透.
*与对照组相比,EPTB患者的CARD17和GBP5表达水平较高.

结论:

* CARD17和GBP5显示了EPTB的显著诊断潜力.
* 这些生物标志物与EPTB中的特定免疫细胞透密切相关.
* 结果表明,CARD17和GBP5可以改善EPTB的诊断策略.

关键词:

拉索·拉索 (Lasso) 是一个在SVM-RFE中使用SVM-RFE.在WGCNA中,WGCNA是WGCNA.生物标志物生物标志物肺外结核 - 肺外结核

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