Beijing Key Laboratory for Drug Resistant Tuberculosis Research, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Tuberculosis Department, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China.
Front Cell Infect Microbiol. 2019 Sep 10;9:323. doi: 10.3389/fcimb.2019.00323. eCollection 2019.
Tuberculous meningitis (TBM) is the most common and severe form of central nervous system tuberculosis. Due to the non-specific clinical presentation and lack of efficient diagnosis methods, it is difficult to discriminate TBM from other frequent types of meningitis, especially viral meningitis (VM). In order to identify the potential biomarkers for discriminating TBM and VM and to reveal the different pathophysiological processes between TBM and VM, a genome-wide miRNA screening of PBMCs from TBM, VM, and healthy controls (HCs) using microarray assay was performed (12 samples). Twenty-eight differentially expressed miRNAs were identified between TBM and VM, and 11 differentially expressed miRNAs were identified between TBM and HCs. The 6 overlapping miRNAs detected in both TBM vs. VM and TBM vs. HCs were verified by qPCR analysis and showed a 100% consistent expression patterns with that in microarray test. Statistically significant differences of 4 miRNAs (miR-126-3p, miR-130a-3p, miR-151a-3p, and miR-199a-5p) were further confirmed in TBM compared with VM and HCs in independent PBMCs sample set ( = 96, < 0.01). Three of which were also showed significantly different between TBM and VM in CSF samples ( = 70, < 0.05). The receiver operating characteristic curve (ROC) analysis showed that the area under the ROC curve (AUC) of these 4 miRNAs in PBMCs were more than 0.70 in discriminating TBM from VM. Combination of these 4 miRNAs could achieve better discriminative capacity [AUC = 0.893 (0.788-0.957)], with a sensitivity of 90.6% (75.0-98.0%), and a specificity of 86.7% (69.3-96.2%). Additional validation was performed to evaluate the diagnostic panel in another independent sample set ( = 49), which yielded a sensitivity of 81.8% (9/11), and specificity of 90.0% (9/10) in distinguishing TBM and VM, and a sensitivity of 81.8% (9/11), and a specificity of 84.6% (11/13) in discriminating TBM from other non-TBM patients. This study uncovered the miRNA profiles of TBM and VM patients, which can facilitate better understanding of the pathogenesis involved in these two diseases and identified 4 novel miRNAs in distinguishing TBM and VM.
结核性脑膜炎（TBM）是中枢神经系统结核最常见和最严重的形式。由于非特异性的临床表现和缺乏有效的诊断方法，TBM 与其他常见类型的脑膜炎，尤其是病毒性脑膜炎（VM），难以区分。为了鉴定鉴别 TBM 和 VM 的潜在生物标志物，并揭示 TBM 和 VM 之间不同的病理生理过程，采用微阵列分析对 TBM、VM 和健康对照者（HCs）的 PBMCs 进行了全基因组 miRNA 筛选（12 个样本）。在 TBM 与 VM 之间鉴定出 28 个差异表达的 miRNA，在 TBM 与 HCs 之间鉴定出 11 个差异表达的 miRNA。在 TBM 与 VM 和 TBM 与 HCs 均检测到的 6 个重叠 miRNA 通过 qPCR 分析进行验证，并与微阵列测试一致。在独立的 PBMC 样本集中，进一步确认了 4 个 miRNA（miR-126-3p、miR-130a-3p、miR-151a-3p 和 miR-199a-5p）在 TBM 与 VM 和 HCs 之间的统计学差异（ = 96， < 0.01）。在 CSF 样本中，其中 3 个 miRNA 在 TBM 与 VM 之间也显示出显著差异（ = 70， < 0.05）。受试者工作特征曲线（ROC）分析表明，这些 4 个 miRNA 在 PBMCs 中鉴别 TBM 与 VM 的 ROC 曲线下面积（AUC）均大于 0.70。这 4 个 miRNA 的组合具有更好的鉴别能力[AUC=0.893（0.788-0.957）]，灵敏度为 90.6%（75.0-98.0%），特异性为 86.7%（69.3-96.2%）。在另一个独立的样本集中（ = 49）进行了额外的验证，以评估诊断面板，结果显示在鉴别 TBM 和 VM 时，其灵敏度为 81.8%（9/11），特异性为 90.0%（9/10），在鉴别 TBM 与其他非 TBM 患者时，灵敏度为 81.8%（9/11），特异性为 84.6%（11/13）。本研究揭示了 TBM 和 VM 患者的 miRNA 谱，有助于更好地理解这两种疾病的发病机制，并鉴定出 4 个鉴别 TBM 和 VM 的新型 miRNA。
