机构：[1]Beijing Key Laboratory for Drug Resistant Tuberculosis Research, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China[2]Tuberculosis Department, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China,[3]Neurology Department, Chinese People’s Liberation Army 263 Hospital, Beijing, China[4]Hyperbaric Oxygen Department, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China[5]Neurology Department, Xuanwu Hospital, Capital Medical University, Beijing, China神经科系统神经内科首都医科大学宣武医院[6]Neurology Department, Beijing Tiantan Hospital, Capital Medical University, Beijing, China重点科室诊疗科室神经病学中心神经病学中心首都医科大学附属天坛医院[7]Laboratory Medical Center, Beijing Ditan Hospital, Capital Medical University, Beijing, China
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 (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.
基金：
Beijing Natural Science FoundationBeijing Natural Science Foundation [7192038, 7164245]; Beijing Nova ProgramBeijing Municipal Science & Technology Commission [Z161100004916080]; National Science and Technology Major Project of China [2015ZX10004801-003, 2017ZX10201301-004]; Beijing Municipal Administration of Hospitals Youth Programme [QML20151501]; Collaborative Innovation Center of Infectious Diseases [PXM2016_ 014226_ 000052]; Tongzhou Yunhe Project [YH201807, YH201921]; Beijing Municipal Administration of Hospitals Ascent Plan [DFL20181601, DFL20151501]; National Natural Science FoundationNational Natural Science Foundation of China [81702097]
第一作者机构：[1]Beijing Key Laboratory for Drug Resistant Tuberculosis Research, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
共同第一作者：
通讯作者：
通讯机构：[1]Beijing Key Laboratory for Drug Resistant Tuberculosis Research, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing, China
推荐引用方式(GB/T 7714)：
Pan Liping,Liu Fei,Zhang Jinli,et al.Genome-Wide miRNA Analysis Identifies Potential Biomarkers in Distinguishing Tuberculous and Viral Meningitis[J].Frontiers in cellular and infection microbiology.2019,9:-.doi:10.3389/fcimb.2019.00323.
APA：
Pan, Liping,Liu, Fei,Zhang, Jinli,Li, Jing,Jia, Hongyan...&Zhang, Zongde.(2019).Genome-Wide miRNA Analysis Identifies Potential Biomarkers in Distinguishing Tuberculous and Viral Meningitis.Frontiers in cellular and infection microbiology,9,
MLA：
Pan, Liping,et al."Genome-Wide miRNA Analysis Identifies Potential Biomarkers in Distinguishing Tuberculous and Viral Meningitis".Frontiers in cellular and infection microbiology 9.(2019):-
