Detection of a combination of serum IgG and IgA antibodies against selected mycobacterial targets provides promising diagnostic signatures for active TB

Abstract

Immunoglobulin G (IgG) based tests for the diagnosis of active tuberculosis (TB) disease often show a lack of specificity in TB endemic regions, which is mainly due to a high background prevalence of LTBI. Here, we investigated the combined performance of the responses of different Ig classes to selected mycobacterial antigens in primary healthcare clinic attendees with signs and symptoms suggestive of TB. The sensitivity and specificity of IgA, IgG and/or IgM to LAM and 7 mycobacterial protein antigens (ESAT-6, Tpx, PstS1, AlaDH, MPT64, 16kDa and 19kDa) and 2 antigen combinations (TUB, TB-LTBI) in the plasma of 63 individuals who underwent diagnostic work-up for TB after presenting with symptoms and signs compatible with possible active TB were evaluated. Active TB was excluded in 42 individuals of whom 21 has LTBI whereas active TB was confirmed in 21 patients of whom 19 had a follow-up blood draw at the end of 6-month anti-TB treatment. The leading single serodiagnostic markers to differentiate between the presence or absence of active TB were anti-16 kDa IgA, anti-MPT64 IgA with sensitivity and specificity of 90%/90% and 95%/90%, respectively. The combined use of 3 or 4 antibodies further improved this performance to accuracies above 95%. After successful completion of anti-TB treatment at month 6, the levels of 16 kDa IgA and 16 kDa IgM dropped significantly whereas LAM IgG and TB-LTBI IgG increased. These results show the potential of extending investigation of anti-tuberculous IgG responses to include IgM and IgA responses against selected protein and non-protein antigens in differentiating active TB from other respiratory diseases in TB endemic settings.

Keywords: Ig class; antibody; biomarker; diagnosis; tuberculosis.

Figure 1. Plasma concentrations of serodiagnostic markers in TB and ORD

Concentrations of plasma serodiagnostic markers were measured in 21 TB patients, and 42 ORD cases. The ORD group comprised 21 LTBI individuals and 21 QFT-negative ORD. Representative plots are shown for diagnostic markers showing significant differences between groups and the vertical bars denote the mean and 95% confidence intervals. Corrections were applied within analyses of markers using Fischer Least Significant Differences post hoc test or Games- Howell post hoc test depending on homogeneity of variance. All the reported significant p-values were adjusted.

Figure 2. Receiver operator characteristics (ROC) curves of top single serodiagnostic markers for discriminating 21 active tuberculosis patients from 42 other respiratory disease cases

Figure 3. Plasma concentrations of serodiagnostic markers in individuals with tuberculosis, latently infected tuberculosis and QFT-negative other respiratory diseases

Concentrations of plasma serodiagnostic markers were measured in 21 tuberculosis patients, 21 latently infected tuberculosis individuals and 21 QFT-negative other respiratory diseases. Representative plots are shown for diagnostic markers showing significant differences between groups and the vertical bars denote 95% confidence intervals. Significant difference between different groups p<0.05 is shown with the different alphabetical letters. The same alphabetical letters are used when there is no significant difference p>0.05 between the different groups. Corrections were applied within analyses of markers using Fischer Least Significant Differences post hoc testing or Games Howell post hoc depending on homogeneity of variance. All the reported significant p-values were adjusted.

Figure 4. Receiving operating characteristics (ROC) curves of top single serodiagnostic markers for discriminating 21 active tuberculosis patients from 21 latently infected individuals

Figure 5. Plasma concentrations of serodiagnostic markers of tuberculosis patients during anti-TB treatment

Concentrations of plasma serodiagnostic markers were measured in 21 TB patients at baseline (BSL) and in 19 TB patients who were followed up at end of month 6 anti-TB treatment. Representative plots are shown for diagnostic markers showing significant differences between the two time points and the vertical bars denote 95% confidence intervals. Corrections were applied within analyses of markers using Fischer Least Significant Differences post hoc testing or Games Howell post hoc depending on homogeneity of variance. All the reported significant p-values were adjusted.