Background:Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is a persistent infectious disease threatening human health. The existing diagnostic methods still have significant shortcomings, including a low positivity rate in pathogen-based diagnoses and the inability of immunological diagnostics to detect active TB. Hence, it is urgent to develop new techniques to detect TB more accurate and earlier. This research aims to scrutinize and authenticate DNA methylation markers suitable for tuberculosis diagnosis. Concurrently, Providing a new approach for tuberculosis diagnosis.Methods:Blood samples from patients with newly diagnosed tuberculosis and healthy controls (HC) were utilized in this study. Examining methylation microarray data from 40 whole blood samples (22TB + 18HC), we employed two procedures: signature gene methylated position analysis and signature region methylated position analysis to pinpoint distinctive methylated positions. Based on the screening results, diagnostic classifiers are constructed through machine learning, and validation was conducted through pyrosequencing in a separate queue (22TB + 18HC). Culminating in the development of a new tuberculosis diagnostic method via quantitative real-time methylation specific PCR (qMSP).Results:The combination of the two procedures revealed a total of 10 methylated positions, all of which were located in the promoter region. These 10 signature methylated positions facilitated the construction of a diagnostic classifier, exhibiting robust diagnostic accuracy in both cross-validation and external test sets. The LDA model demonstrated the best classification performance, achieving an AUC of 0.83, specificity of 0.8, and sensitivity of 0.86 on the external test set. Furthermore, the validation of signature methylated positions through pyrosequencing demonstrated high agreement with screening outcomes. Additionally, qMSP detection of 2 potential hypomethylated positions (cg04552852 and cg12464638) exhibited promising results, yielding an AUC of 0.794, specificity of 0.720, and sensitivity of 0.816.Conclusion:Our study demonstrates that the validated signature methylated positions through pyrosequencing emerge as plausible biomarkers for tuberculosis diagnosis. The specific methylation markers in the TSPAN4 gene, identified in whole blood samples, hold promise for improving tuberculosis diagnosis. This approach could significantly enhance diagnostic accuracy and speed, offering a new avenue for early detection and treatment.

中文翻译：

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探索 TSPAN4 启动子甲基化作为结核病诊断生物标志物

背景：结核病（TB），由以下原因引起：结核分枝杆菌结核分枝杆菌（Mtb）是一种威胁人类健康的持续性传染病。现有的诊断方法仍然存在明显的缺点，包括基于病原体的诊断阳性率较低以及免疫学诊断无法检测活动性结核病。因此，迫切需要开发新技术来更准确、更早地检测结核病。本研究旨在审查和验证适用于结核病诊断的 DNA 甲基化标记。同时，也为结核病的诊断提供了一种新的方法。方法：本研究采用初诊结核病患者和健康对照者（HC）的血液样本。检查来自 40 个全血样本 (22TB + 18HC) 的甲基化微阵列数据，我们采用了两种程序：特征基因甲基化位置分析和特征区域甲基化位置分析，以查明独特的甲基化位置。根据筛选结果，通过机器学习构建诊断分类器，并通过单独队列（22TB + 18HC）中的焦磷酸测序进行验证。最终通过定量实时甲基化特异性 PCR (qMSP) 开发了一种新的结核病诊断方法。结果：两种方法的结合总共揭示了 10 个甲基化位置，全部位于启动子区域。这 10 个特征甲基化位置促进了诊断分类器的构建，在交叉验证和外部测试集中表现出强大的诊断准确性。 LDA 模型展示了最佳的分类性能，在外部测试集上实现了 0.83 的 AUC、0.8 的特异性和 0.86 的敏感性。此外，通过焦磷酸测序对特征甲基化位置的验证表明与筛选结果高度一致。此外，对 2 个潜在低甲基化位置（cg04552852 和 cg12464638）的 qMSP 检测显示出有希望的结果，AUC 为 0.794，特异性为 0.720，灵敏度为 0.816。 结论：我们的研究表明，通过焦磷酸测序验证的特征甲基化位置成为合理的生物标志物用于结核病诊断。特定的甲基化标记TSPAN4在全血样本中鉴定出的基因有望改善结核病的诊断。这种方法可以显着提高诊断准确性和速度，为早期检测和治疗提供新途径。