No abstract

Background A rapid, blood-based triage test that allows targeted investigation for tuberculosis at the point of care could shorten the time to tuberculosis treatment and reduce mortality. We aimed to test the performance of a host blood transcriptomic signature (RISK11) in diagnosing tuberculosis and predicting progression to active pulmonary disease (prognosis) in people with HIV in a community setting.Methods In this prospective diagnostic and prognostic accuracy study, adults (aged 18-59 years) with HIV were recruited from five communities in South Africa. Individuals with a history of tuberculosis or household exposure to multidrug-resistant tuberculosis within the past 3 years, comorbid risk factors for tuberculosis, or any condition that would interfere with the study were excluded. RISK11 status was assessed at baseline by real-time PCR; participants and study staff were masked to the result. Participants underwent active surveillance for microbiologically confirmed tuberculosis by providing spontaneously expectorated sputum samples at baseline, if symptomatic during 15 months of follow-up, and at 15 months (the end of the study). The coprimary outcomes were the prevalence and cumulative incidence of tuberculosis disease confirmed by a positive Xpert MTB/RIF, Xpert Ultra, or Mycobacteria Growth Indicator Tube culture, or a combination of such, on at least two separate sputum samples collected within any 30-day period.

Background Recent Mycobacterium tuberculosis (M.tb) infection is associated with a higher risk of progression to tuberculosis disease, compared to persistent infection after remote exposure. However, current immunodiagnostic tools fail to distinguish between recent and remote infection. We aimed to characterise the immunobiology associated with acquisition of M.tb infection and identify a biomarker that can distinguish recent from remote infection. Methods Healthy South African adolescents were serially tested with QuantiFERON-TB Gold to define recent (QuantiFERON-TB conversion <6 months) and persistent (QuantiFERON-TB+ for >1.5 year) infection. We characterised M.tb-specific CD4 T cell functional (IFN-γ, TNF, IL-2, CD107, CD154), memory (CD45RA, CCR7, CD27, KLRG-1) and activation (HLA-DR) profiles by flow cytometry after CFP-10/ESAT-6 peptide pool or M.tb lysate stimulation. We then assessed the diagnostic performance of immune profiles that were differentially expressed between individuals with recent or persistent QuantiFERON-TB+. Findings CFP-10/ESAT-6-specific CD4 T cell activation but not functional or memory phenotypes distinguished between individuals with recent and persistent QuantiFERON-TB+. In response to M.tb lysate, recent QuantiFERON-TB+ individuals had lower proportions of highly differentiated IFN-γ+TNF+ CD4 T cells expressing a KLRG-1+ effector phenotype and higher proportions of early differentiated IFN-γ-TNF+IL-2+ and activated CD4 T cells compared to persistent QuantiFERON-TB+ individuals. Among all differentially expressed T cell features CFP-10/ESAT-6-specific CD4 T cell activation was the best performing diagnostic biomarker of recent infection. Interpretation Recent M.tb infection is associated with highly activated and moderately differentiated functional M.tb-specific T cell subsets, that can be used as biomarkers to distinguish between recent and remote infection. Funding US National Institutes of Health (NIH), Bill and Melinda Gates Foundation, South African National Research Foundation, South African Medical Research Council, and Aeras.

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.

Background: Provision of tuberculosis preventive treatment (TPT) to individuals with Mycobacterium tuberculosis (M.tb) infection (TBI) is a key strategy to reduce the global tuberculosis burden. Tuberculosis risk is significantly higher after recent compared to remote TBI. We aimed to define a blood-based biomarker, measured with a simple flow cytometry assay, to stratify different stages of TBI to infer risk of disease. Methods: Healthy adolescents were serially tested with QuantiFERON-TB Gold (QFT) to define recent (QFT conversion <6 months) and remote (persistent QFT+ for >1 year) TBI. M.tb-specific T cells were defined as IFN-γ+TNF+CD3+ cells upon CFP-10/ESAT-6 or M.tb lysate stimulation. ΔHLA-DR median fluorescence intensity (MFI) was defined as the difference in HLA-DR expression between M.tb-specific and total T cells. Biomarker performance was assessed by blinded prediction in untouched test cohorts with recent versus remote TBI or tuberculosis disease, and unblinded analysis of asymptomatic adolescents with TBI who remained healthy (non-progressors) or who progressed to microbiologically-confirmed disease (progressors). Findings: In the test cohorts, frequencies of M.tb-specific T cells differentiated between QFT- (n=25) and QFT+ (n=47) individuals [area under the ROC curve (AUCROC): 0.94; 95%CI: 0.87-1.00]. ΔHLA-DR MFI significantly discriminated between recent (n=20) and remote (n=22) TBI (AUCROC 0.91; 95%CI: 0.83-1.00); remote TBI and newly diagnosed tuberculosis (n=19; AUCROC 0.99; 95%CI: 0.96-1.00); and between tuberculosis progressors (n=22) and non-progressors (n=34; AUCROC 0.75, 95%CI: 0.63-0.87). Interpretation: The ΔHLA-DR MFI biomarker can identify individuals with recent TBI and those with disease progression, allowing targeted provision of TPT to those at highest risk of tuberculosis.

BackgroundRecent Mycobacterium tuberculosis (M.tb) infection is associated with a higher risk of progression to tuberculosis disease, compared to persistent infection after remote exposure. However, current immunodiagnostic tools fail to distinguish between recent and remote infection. We aimed to characterise the immunobiology associated with acquisition of M.tb infection and identify a biomarker that can distinguish recent from remote infection.MethodsHealthy South African adolescents were serially tested with QuantiFERON-TB Gold to define recent (QuantiFERON-TB conversion <6 months) and persistent (QuantiFERON-TB+ for >1.5 year) infection. We characterized M.tb-specific CD4 T cell functional (IFN-γ, TNF, IL-2, CD107, CD154), memory (CD45RA, CCR7, CD27, KLRG-1) and activation (HLA-DR) profiles by flow cytometry after CFP-10/ESAT-6 peptide pool or M.tb lysate stimulation. We then assessed the diagnostic performance of immune profiles that were differentially expressed between individuals with recent or persistent QuantiFERON-TB+.FindingsCFP-10/ESAT-6-specific CD4 T cell activation but not functional or memory phenotypes distinguished between individuals with recent and persistent QuantiFERON-TB+. In response to M.tb lysate, recent QuantiFERON-TB+ individuals had lower proportions of highly differentiated IFN-γ+TNF+ CD4 T cells expressing a KLRG-1+ effector phenotype and higher proportions of early differentiated IFN-γ-TNF+IL-2+ and activated CD4 T cells compared to persistent QuantiFERON-TB+ individuals. Among all differentially expressed T cell features CFP-10/ESAT-6-specific CD4 T cell activation was the best performing diagnostic biomarker of recent infection.InterpretationRecent M.tb infection is associated with highly activated and moderately differentiated functional M.tb-specific T cell subsets, that can be used as biomarkers to distinguish between recent and remote 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.

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 my-cobacteria, measured on recently and remotely M.tb infected adolescents. The datasets were standardized using variance stabilizing (vast) 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 single 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 validation. 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.