Genome-Wide miRNA Analysis Identifies Potential Biomarkers in Distinguishing Tuberculous and Viral Meningitis - Pan, Liping; Liu, Fei; Zhang, Jinli; Li, Jing; Jia, Hongyan; Huang, Mailing; Liu, Xuehua; Chen, Weibi; Ding, Zeyu; Wang, Yajie; Du, Boping; Wei, Rongrong; et al. (Frontiers in Cellular and Infection Microbiology, 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 screenings 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 resultexpression 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 (n = 96, P < 0.01). Three of which were also showed significantly different between TBM and VM in CSF samples (n = 70, P < 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 (n = 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.