Dataset Information

Genome-Wide miRNA Analysis Identifies Potential Biomarkers in Distinguishing Tuberculous and Viral Meningitis.

ABSTRACT: 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.

SUBMITTER: Pan L

PROVIDER: S-EPMC6749153 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Genome-Wide miRNA Analysis Identifies Potential Biomarkers in Distinguishing Tuberculous and Viral Meningitis.

Pan Liping L Liu Fei F Zhang Jinli J Li Jing J Jia Hongyan H Huang Mailing M Liu Xuehua X Chen Weibi W Ding Zeyu Z Wang Yajie Y Du Boping B Wei Rongrong R Sun Qi Q Xing Aiying A Zhang Zongde Z

Frontiers in cellular and infection microbiology 20190910

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 T ...[more]

PMID: 31572691

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Project description:Tuberculous meningitis (TBM) is the most severe form of tuberculosis and results in high morbidity and mortality in children. Diagnostic delay contributes to the poor outcome. There is an urgent need for new tools for the rapid diagnosis of TBM, especially in children. We collected serum samples from children in whom TBM was suspected at a tertiary hospital in Cape Town, South Africa. Children were subsequently classified as having TBM or no TBM using a published uniform research case-definition. Using a multiplex cytokine array platform, we investigated the concentrations of serum biomarkers comprising biomarkers that were previously found to be of value in the diagnosis of adult pulmonary TB (CRP, SAA, CFH, IFN-γ, IP-10, Apo-AI, and transthyretin) plus other potentially useful host biomarkers as diagnostic candidates for TBM. Out of 47 children included in the study, 23 (48.9%) had a final diagnosis of TBM and six were HIV infected. A modified version of the adult 7-marker biosignature in which transthyretin was replaced by NCAM1, diagnosed TBM in children with AUC of 0.80 (95% CI, 0.67–0.92), sensitivity of 73.9% (95% CI, 51.6–89.8%) and specificity of 66.7% (95% CI, 44.7–84.4%), with the other six proteins in the signature (CRP, IFN-γ, IP-10, CFH, Apo-A1, and SAA) only achieving and AUC of 0.75 (95% CI, 0.61–0.90) when used in combination. A new childhood TBM specific 3-marker biosignature (adipsin, Aβ42, and IL-10) showed potential in the diagnosis of TBM, with AUC of 0.84 (95% CI, 0.73–0.96), sensitivity of 82.6% (95 CI, 61.2–95.0%) and specificity of 75.0% (95% CI, 53.3–90.2%) after leave-one-out cross validation. A previously described adult 7-marker serum protein biosignature showed potential in the diagnosis of TBM in children. However, a smaller childhood TBM-specific 3-marker signature demonstrated improved performance characteristics. Our data indicates that blood-based biomarkers may be useful in the diagnosis of childhood TBM and requires further validation in larger cohort studies.

Project description:BackgroundTuberculous meningitis (TBM) leads to death or disability in half the affected individuals. Tools to assess severity and predict outcome are lacking. Neurospecific biomarkers could serve as markers of the severity and evolution of brain injury, but have not been widely explored in TBM. We examined biomarkers of neurological injury (neuromarkers) and inflammation in pediatric TBM and their association with outcome.MethodsBlood and cerebrospinal fluid (CSF) of children with TBM and hydrocephalus taken on admission and over 3 weeks were analyzed for the neuromarkers S100B, neuron-specific enolase (NSE), and glial fibrillary acidic protein (GFAP), in addition to multiple inflammatory markers. Results were compared with 2 control groups: patients with (1) a fatty filum (abnormal filum terminale of the spinal cord); and (2) pulmonary tuberculosis (PTB). Imaging was conducted on admission and at 3 weeks. Outcome was assessed at 6 months.ResultsData were collected from 44 patients with TBM (cases; median age, 3.3 [min-max 0.3-13.1] years), 11 fatty filum controls (median age, 2.8 [min-max 0.8-8] years) and 9 PTB controls (median age, 3.7 [min-max 1.3-11.8] years). Seven cases (16%) died and 16 (36%) had disabilities. Neuromarkers and inflammatory markers were elevated in CSF on admission and for up to 3 weeks, but not in serum. Initial and highest concentrations in week 1 of S100B and NSE were associated with poor outcome, as were highest concentration overall and an increasing profile over time in S100B, NSE, and GFAP. Combined neuromarker concentrations increased over time in patients who died, whereas inflammatory markers decreased. Cerebral infarcts were associated with highest overall neuromarker concentrations and an increasing profile over time. Tuberculomas were associated with elevated interleukin (IL) 12p40, interferon-inducible protein 10, and monocyte chemoattractant protein 1 concentrations, whereas infarcts were associated with elevated tumor necrosis factor ?, macrophage inflammatory protein 1?, IL-6, and IL-8.ConclusionsCSF neuromarkers are promising biomarkers of injury severity and are predictive of mortality. An increasing trend suggested ongoing brain injury, even though markers of inflammation declined with treatment. These findings could offer novel insight into the pathophysiology of TBM.

Dataset Information

Genome-Wide miRNA Analysis Identifies Potential Biomarkers in Distinguishing Tuberculous and Viral Meningitis.

Publications

Genome-Wide miRNA Analysis Identifies Potential Biomarkers in Distinguishing Tuberculous and Viral Meningitis.

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