Mycobacterium tuberculosis-Specific T Cell Functional, Memory, and Activation Profiles in QuantiFERON-Reverters Are Consistent With Controlled Infection.

Reversion of immune sensitization tests for Mycobacterium tuberculosis (M.tb) infection, such as interferon-gamma release assays or tuberculin skin test, has been reported in multiple studies. We hypothesized that QuantiFERON-TB Gold (QFT) reversion is associated with a decline of M.tb-specific functional T cell responses, and a distinct pattern of T cell and innate responses compared to persistent QFT+ and QFT- individuals. We compared groups of healthy adolescents (n=~30 each), defined by four, 6-monthly QFT tests: reverters (QFT+/+/-/-), non-converters (QFT-/-/-/-) and persistent positives (QFT+/+/+/+). We stimulated peripheral blood mononuclear cells with M.tb antigens (M.tb lysate; CFP-10/ESAT-6 and EspC/EspF/Rv2348 peptide pools) and measured M.tb-specific adaptive T cell memory, activation, and functional profiles; as well as functional innate (monocytes, natural killer cells), donor-unrestricted T cells (DURT: γδ T cells, mucosal-associated invariant T and natural killer T-like cells) and B cells by flow cytometry. Projection to latent space discriminant analysis was applied to determine features that best distinguished between QFT reverters, non-converters and persistent positives. No longitudinal changes in immune responses to M.tb were observed upon QFT reversion. M.tb-specific Th1 responses detected in reverters were of intermediate magnitude, higher than responses in QFT non-converters and lower than responses in persistent positives. About one third of reverters had a robust response to CFP-10/ESAT-6. Among those with measurable responses, lower proportions of TSCM (CD45RA+CCR7+CD27+) and early differentiated (CD45RA-) IFN-γ-TNF+IL-2- M.tb lysate-specific CD4+ cells were observed in reverters compared with non-converters. Conversely, higher proportions of early differentiated and lower proportions of effector (CD45RA-CCR7-) CFP10/ESAT6-specific Th1 cells were observed in reverters compared to persistent-positives. No differences in M.tb-specific innate, DURT or B cell functional responses were observed between the groups. Statistical modelling misclassified the majority of reverters as non-converters more frequently than they were correctly classified as reverters or misclassified as persistent positives. These findings suggest that QFT reversion occurs in a heterogeneous group of individuals with low M.tb-specific T cell responses. In some individuals QFT reversion may result from assay variability, while in others the magnitude and differentiation status of M.tb-specific Th1 cells are consistent with well-controlled M.tb infection.

Multidimensional analysis of immune responses identified biomarkers of recent Mycobacterium tuberculosis infection.

The risk of tuberculosis (TB) disease is higher in individuals with recent Mycobacterium tuberculosis (M.tb) infection compared to individuals with more remote, established infection. We aimed to define blood-based biomarkers to distinguish between recent and remote infection, which would allow targeting of recently infected individuals for preventive TB treatment. We hypothesized that integration of multiple immune measurements would outperform the diagnostic performance of a single biomarker. Analysis was performed on different components of the immune system, including adaptive and innate responses to mycobacteria, measured on recently and remotely M.tb infected adolescents. The datasets were standardized using variance stabilizing scaling and missing values were imputed using a multiple factor analysis-based approach. For data integration, we compared the performance of a Multiple Tuning Parameter Elastic Net (MTP-EN) to a standard EN model, which was built to the individual adaptive and innate datasets. Biomarkers with non-zero coefficients from the optimal single data EN models were then isolated to build logistic regression models. A decision tree and random forest model were used for statistical confirmation. We found no difference in the predictive performances of the optimal MTP-EN model and the EN model [average area under the receiver operating curve (AUROC) = 0.93]. EN models built to the integrated dataset and the adaptive dataset yielded identically high AUROC values (average AUROC = 0.91), while the innate data EN model performed poorly (average AUROC = 0.62). Results also indicated that integration of adaptive and innate biomarkers did not outperform the adaptive biomarkers alone (Likelihood Ratio Test χ2 = 6.09, p = 0.808). From a total of 193 variables, the level of HLA-DR on ESAT6/CFP10-specific Th1 cytokine-expressing CD4 cells was the strongest biomarker for recent M.tb infection. The discriminatory ability of this variable was confirmed in both tree-based models. A single biomarker measuring M.tb-specific T cell activation yielded excellent diagnostic potential to distinguish between recent and remote M.tb infection.

Antigen-Specific T-Cell Activation Distinguishes between Recent and Remote Tuberculosis Infection.

Rationale: Current diagnostic tests fail to identify individuals at higher risk of progression to tuberculosis disease, such as those with recent Mycobacterium tuberculosis infection, who should be prioritized for targeted preventive treatment. Objectives: To define a blood-based biomarker, measured with a simple flow cytometry assay, that can stratify different stages of tuberculosis infection to infer risk of disease. Methods: South African adolescents were serially tested with QuantiFERON-TB Gold to define recent (QuantiFERON-TB conversion <6 mo) and persistent (QuantiFERON-TB+ for >1 yr) infection. We defined the ΔHLA-DR median fluorescence intensity biomarker as the difference in HLA-DR expression between IFN-γ+ TNF+Mycobacterium tuberculosis-specific T cells and total CD3+ T cells. Biomarker performance was assessed by blinded prediction in untouched test cohorts with recent versus persistent infection or tuberculosis disease and by unblinded analysis of asymptomatic adolescents with tuberculosis infection who remained healthy (nonprogressors) or who progressed to microbiologically confirmed disease (progressors). Measurements and Main Results: In the test cohorts, frequencies of Mycobacterium tuberculosis-specific T cells differentiated between QuantiFERON-TB- (n = 25) and QuantiFERON-TB+ (n = 47) individuals (area under the receiver operating characteristic curve, 0.94; 95% confidence interval, 0.87-1.00). ΔHLA-DR significantly discriminated between recent (n = 20) and persistent (n = 22) QuantiFERON-TB+ (0.91; 0.83-1.00); persistent QuantiFERON-TB+ and newly diagnosed tuberculosis (n = 19; 0.99; 0.96-1.00); and tuberculosis progressors (n = 22) and nonprogressors (n = 34; 0.75; 0.63-0.87). However, ΔHLA-DR median fluorescent intensity could not discriminate between recent QuantiFERON-TB+ and tuberculosis (0.67; 0.50-0.84). Conclusions: The ΔHLA-DR biomarker can identify individuals with recent QuantiFERON-TB conversion and those with disease progression, allowing targeted provision of preventive treatment to those at highest risk of tuberculosis. Further validation studies of this novel immune biomarker in various settings and populations at risk are warranted.