Detection of <em>Mycobacterium tuberculosis</em> GlcB or HspX Antigens or <em>devR</em> DNA Impacts the Rapid Diagnosis of Tuberculous Meningitis in Children

<div><h3>Background</h3><p>Tuberculous meningitis (TBM) is the most common form of neurotuberculosis and the fifth most common form of extrapulmonary TB. Early diagnosis and prompt treatment are the cornerstones of effective disease management. The accurate diagnosis of TBM poses a challenge due to an extensive differential diagnosis, low bacterial load and paucity of cerebrospinal fluid (CSF) especially in children.</p> <h3>Methodology/Principal Findings</h3><p>We describe the utility of ELISA and qPCR for the detection of <em>Mycobacterium tuberculosis</em> (<em>M. tb</em>) proteins (GlcB, HspX, MPT51, Ag85B and PstS1) and DNA for the rapid diagnosis of TBM. CSF filtrates (n = 532) derived from children were classified as ‘Definite’ TBM (<em>M. tb</em> culture positive, n = 29), ‘Probable and Possible’ TBM (n = 165) and ‘Not-TBM’ including other cases of meningitis or neurological disorders (n = 338). ROC curves were generated from ELISA and qPCR data of ‘Definite’ TBM and Non-Tuberculous infectious meningitis (NTIM) samples and cut-off values were derived to provide ≥95% specificity. <em>devR</em> qPCR, GlcB, HspX and PstS1 ELISAs showed 100% (88;100) sensitivity and 96–97% specificity in ‘Definite’ TBM samples. The application of these cut-offs to ‘Probable and Possible’ TBM groups yielded excellent sensitivity (98%, 94;99) and specificity (98%, 96;99) for qPCR and for GlcB, HspX and MPT51 antigen ELISAs (sensitivity 92–95% and specificity 93–96%). A test combination of qPCR with GlcB and HspX ELISAs accurately detected all TBM samples at a specificity of ∼90%. Logistic regression analysis indicated that these tests significantly added value to the currently used algorithms for TBM diagnosis.</p> <h3>Conclusions</h3><p>The detection of <em>M. tb</em> GlcB/HspX antigens/<em>devR</em> DNA in CSF is likely to improve the utility of existing algorithms for TBM diagnosis and also hasten the speed of diagnosis.</p> </div

Antigen detection in CSF filtrates by ELISA.

<p>Scatter plots of GlcB, HspX, MPT51, Ag85B and PstS1 antigens (in 5 µl of CSF) showing ΔOD values. Using ROC curves generated from ΔOD values in CSF of ‘Definite’ TBM and NTIM group, ΔOD cut-off values at 0.095, 0.125, 0.1, 0.105 and 0.095 were selected for GlcB, HspX, MPT51, Ag85B and PstS1, respectively. The horizontal bar denotes the median value (black line in individual data sets) and the cut-off points (blue line across the plots).</p

Comparison of <i>M. tb</i> DNA <i>vs.</i> antigen amount in CSF.

<p>A representative graph of HspX is shown. All other antigens showed a similar pattern (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0044630#pone.0044630.s003" target="_blank">Figure S3</a>). Starting amounts of DNA and antigen in 5 µl CSF were quantitated by qPCR and ELISA, respectively.</p

DNA quantitation in CSF filtrates by qPCR.

<p>Scatter plot of starting bacterial DNA load (in 5 µl of CSF). The horizontal bar denotes the median value (black line in individual data sets) and the cut-off points (blue line across the plot). The cut-off points were determined by ROC curve analysis of DNA amounts in CSF from ‘Definite’ TBM (true positives) and NTIM (true negatives) groups.</p

Antigen concentrations in TBM CSF filtrates.

<p>^#GlcB concentration was significantly lower (p<0.05) than that of HspX, MPT51 and PstS1 in ‘Definite’ TBM and all 4 antigens in ‘Probable and Possible’ TBM groups; ^##PstS1 concentration was significantly higher (p<0.05) within both ‘Definite’ (all antigens) and ‘Probable and Possible’ TBM (all antigens except Ag85B) groups. **PstS1 concentration was also significantly higher (p<0.01) in ‘Definite’ TBM group <i>vs.</i> ‘Probable and Possible’ TBM groups.</p

Performance of ELISA and PCR assays in Definite TBM subjects.^a

a<p>using cut-offs determined from ROC analysis of ELISA/qPCR data from ‘Definite’ TBM and NTIM groups (true positives and true negatives, respectively).</p>b<p>Values are in percentages, values in brackets denote 95% confidence intervals.</p

ROC curves for logistic regression analysis of ‘Probable and Possible’ TBM samples.

<p>Predictor model (18 predictors) applied to ‘Probable and Possible’ TBM combined with ELISA/qPCR.</p

Categorization of CSF samples.

<p>*Suspected TBM were classified into ‘Definite’, ‘Probable’ and ‘Possible’ categories; ‘Not-TBM’ included Non Tuberculous infectious meningitis (NTIM), Infectious neurological disorders (IND) and Non-infectious neurological disorders.</p

Additional file 1 of Development of a cost of illness inventory questionnaire for children with autism spectrum disorder in South Asia

Additional file 1: Supplementary material

Study recruitment profile.

<p>Study recruitment profile.</p