scholarly journals Activation Phenotype of Mycobacterium tuberculosis-Specific CD4+ T Cells Promoting the Discrimination Between Active Tuberculosis and Latent Tuberculosis Infection

2021 ◽  
Vol 12 ◽  
Author(s):  
Ying Luo ◽  
Ying Xue ◽  
Liyan Mao ◽  
Qun Lin ◽  
Guoxing Tang ◽  
...  
Keyword(s):  
T Cells ◽  
Mycobacterium Tuberculosis ◽  
Latent Tuberculosis Infection ◽  
Latent Tuberculosis ◽  
Active Tuberculosis ◽  
Tuberculosis Infection ◽  
Antigen Stimulation ◽  
Hla Dr ◽  
Tnf Α ◽  
Ifn Γ

BackgroundRapid and effective discrimination between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains a challenge. There is an urgent need for developing practical and affordable approaches targeting this issue.MethodsParticipants with ATB and LTBI were recruited at Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort) based on positive T-SPOT results from June 2020 to January 2021. The expression of activation markers including HLA-DR, CD38, CD69, and CD25 was examined on Mycobacterium tuberculosis (MTB)-specific CD4+ T cells defined by IFN-γ, TNF-α, and IL-2 expression upon MTB antigen stimulation.ResultsA total of 90 (40 ATB and 50 LTBI) and another 64 (29 ATB and 35 LTBI) subjects were recruited from the Qiaokou cohort and Caidian cohort, respectively. The expression patterns of Th1 cytokines including IFN-γ, TNF-α, and IL-2 upon MTB antigen stimulation could not differentiate ATB patients from LTBI individuals well. However, both HLA-DR and CD38 on MTB-specific cells showed discriminatory value in distinguishing between ATB patients and LTBI individuals. As for developing a single candidate biomarker, HLA-DR had the advantage over CD38. Moreover, HLA-DR on TNF-α+ or IL-2+ cells had superiority over that on IFN-γ+ cells in differentiating ATB patients from LTBI individuals. Besides, HLA-DR on MTB-specific cells defined by multiple cytokine co-expression had a higher ability to discriminate patients with ATB from LTBI individuals than that of MTB-specific cells defined by one kind of cytokine expression. Specially, HLA-DR on TNF-α+IL-2+ cells produced an AUC of 0.901 (95% CI, 0.833–0.969), with a sensitivity of 93.75% (95% CI, 79.85–98.27%) and specificity of 72.97% (95% CI, 57.02–84.60%) as a threshold of 44% was used. Furthermore, the performance of HLA-DR on TNF-α+IL-2+ cells for differential diagnosis was obtained with validation cohort data: 90.91% (95% CI, 72.19–97.47%) sensitivity and 68.97% (95% CI, 50.77–82.73%) specificity.ConclusionsWe demonstrated that HLA-DR on MTB-specific cells was a potentially useful biomarker for accurate discrimination between ATB and LTBI.

scholarly journals Utility of interferon gamma/tumor necrosis factor alpha FluoroSpot assay in differentiation between active tuberculosis and latent tuberculosis infection: a pilot study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lifan Zhang ◽  
Shijun Wan ◽  
Ziyue Zhou ◽  
Yueqiu Zhang ◽  
Xiaoqing Liu
Keyword(s):  
T Cells ◽  
Pilot Study ◽  
Diagnostic Accuracy ◽  
Latent Tuberculosis Infection ◽  
Latent Tuberculosis ◽  
Active Tuberculosis ◽  
Tuberculosis Infection ◽  
Tnf Α ◽  
Ifn Γ ◽  
Sensitivity Specificity

Abstract Background The differential diagnosis of active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging in clinical practice. We aimed to evaluate the diagnostic accuracy of the IFN-γ/TNF-α FluoroSpot assay for differentiating ATB from LTBI. Methods We conducted a pilot study of case-control design, using the FluoroSpot assay to simultaneously detect IFN-γ and TNF-α secretion at the single-cell level. The frequencies of antigen-specific single TNF-α-, total TNF-α-, single IFN-γ-, total IFN-γ- and dual IFN-γ/TNF-α-secreting T cells were detected. The optimal cutoffs value of frequencies for differentiating ATB from LTBI were determined according to receiver operating characteristic curve analysis. The sensitivity, specificity, predictive values (PV) and likelihood ratios (LR) of the FluoroSpot assay were calculated. Results Thirty patients diagnosed microbiologically with ATB, 36 healthcare workers with LTBI and 36 healthy controls were enrolled. After stimulated by ESAT-6 or CFP-10 peptides, the median frequencies of single TNF-α-, total TNF-α-, single IFN-γ-, total IFN-γ- and dual IFN-γ/TNF-α-secreting T cells in ATB patients were all significantly higher than those in LTBI and HC groups (P < 0.01). The frequencies of total IFN-γ-secreting T cells detected by FluoroSpot assay correlated significantly with those of T-SPOT.TB (r = 0.910 for ESAT-6, P < 0.001, r = 0.845 for CFP-10, P < 0.001). After stimulated by ESAT-6 peptides, with total TNF-α-secreting T cells frequencies at a cut off value of 21 iSFCs/250,000 PBMCs, the sensitivity, specificity, PLR, NLR, PPV, NPV of IFN-γ/TNF-α FluoroSpot assay in differentiating ATB from LTBI were 96.7% (95%CI, 82.8–99.9%), 94.3% (95%CI, 80.8–99.3%), 16.92 (95%CI, 4.40–65.08), 0.04 (95%CI, 0.01–0.24), 93.6% (95%CI,78.6–99.2%) and 97.1% (95%CI, 84.7–99.9%), respectively. With the frequencies of total TNF-α- and total IFN-γ-secreting T cells stimulated by ESAT-6 peptides combined, the specificity was increased to 97.1%, and the positive likelihood ratio to 31.5. The combination with CFP-10 might not improve the diagnostic accuracy of the ESAT-6 for differentiating ATB from LTBI. Conclusions IFN-γ/TNF-α FluoroSpot assay might have potential to help differentiate ATB from LTBI, but the findings need to be further verified by cross-sectional or prospective cohort studies.

scholarly journals 1405. The Accuracy of Mycobacterium tuberculosis Specific IFN-γ/IL-2/TNF-α- FluoroSpot in Differential Diagnosis of Active Tuberculosis and Latent Tuberculosis Infection: A Case-Control Study

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S786-S787
Author(s):  
Lifan Zhang ◽  
Huimin Ma ◽  
Qiping Ge ◽  
Yueqiu Zhang ◽  
Xiaochun Shi ◽  
...  
Keyword(s):  
T Cells ◽  
Differential Diagnosis ◽  
Mycobacterium Tuberculosis ◽  
Latent Tuberculosis Infection ◽  
Specific Antigen ◽  
Latent Tuberculosis ◽  
Active Tuberculosis ◽  
Tnf Α ◽  
Ifn Γ ◽  
Stimulation Of

Abstract Background To establish the Mycobacterium tuberculosis (MTB) specific IFN-γ/IL-2/TNF-α-FluoroSpot assay, and preliminarily evaluate its accuracy of differential diagnosis of active tuberculosis (ATB) and latent tuberculosis infection (LTBI). Methods Patients with pathologically confirmed and clinically diagnosed ATB in Peking Union Medical College Hospital and Beijing Chest Hospital from April 2020 to May 2021 were enrolled as case group, while patients with LTBI in the same period were enrolled as control group. The FluoroSpot assay was used to simultaneously detect the secretion of IFN-γ, IL-2 and TNF-α in T cells stimulated by the MTB specific antigens ESAT-6 and CFP-10 at the single-cell level. A binary logistic regression model was used to fit the combined diagnostic parameters, and the sensitivity, specificity, predictive value and likelihood ratio of the differential diagnosis of ATB and LTBI were calculated. Figure 1. Schematic diagram of FluoroSpot (IFN-γ/IL-2/TNF-α) detecting cytokine-secreting specific T cells after stimulation with MTB specific antigen. A. The green spots are the total IFN-γ-secreting T cells; B. The red spots are the total IL-2-secreting T cells; C. The blue spots are the total TNF-α-secreting T cells; D. The green spots are the single IFN-γ-secreting T cells; the red spots are the single IL-2-secreting T cells; the blue spots are the single TNF-α-secreting T cells; the yellow spots are the dual IFN-γ/IL-2-secreting T cells; the cyan spots are the dual IFN-γ/TNF-α-secreting T cells; the purple spots are the dual IL-2/TNF-α-secreting T cells; the white spots are the triple IFN-γ/IL-2/TNF-α-secreting T cells. Results 62 patients with ATB (37 pathogen-confirmed ATB, 25 clinical diagnosed ATB), 87 patients with LTBI were included. There was significant correlation of the frequencies of total IFN-γ-secreting T cells detected by IFN-γ/IL-2/TNF-α-FluoroSpot assay compared with T-SPOT.TB after stimulation of MTB-specific antigen (r=0.829 for ESAT-6, P&lt; 0.001, r=0.804 for CFP-10, P&lt; 0.001). ROC curve was drawn for both T-SPOT.TB and Fluorospot. For T-SPOT.TB, the AUROC was 0.669 (95%CI 0.574-0.765), the sensitivity and specificity of differentiating ATB from LTBI were 70.97% (95%CI 58.05%-81.80%) and 56.32% (95CI 45.26%-66.94%) respectively. While for Fluorospot, the AUROC was 0.906 (95 CI 0.856-0.957), the sensitivity and specificity of differentiating ATB from LTBI were 80.65% (95%CI 68.63% - 89.58%) and 88.51% (95%CI 79.88% - 94.35%) respectively. Figure 2. Correlation between the frequencies of total IFN-γ-secreting T cells detected by FluoroSpot assay and those of T-SPOT.TB. (A) Stimulated by EAST-6. (B) Stimulated by CFP-10. Figure 3. ROC curves and the corresponding AUROC for measurement of frequencies of specific T cells in differentiating ATB and LTBI under stimulation of ESAT-6 or CFP-10. The blue line is drawn with the frequency of IFN-γ-secreting T cells detected by T-SPOT.TB, and the AUC is 0.669 (95%CI, 0.574-0.765). The red line is drawn with combination of the frequencies and proportion of single IFN-γ-'single IL-2-'single TNF-α-'dual IFN-γ/IL-2-'dual IFN-γ/ /TNF-α-'dual IL-2/TNF-α-secreting T cells detected by FluoroSpot, and the AUC is 0.906 (95% CI, 0.856-0.957). Table 1. Diagnostic value of T-SPOT.TB and FluoroSpot for differentiating ATB from LTBI Conclusion Compared with T-SPOT.TB, the IFN-γ/IL-2/TNF-α-Fluorospot assay may be helpful to distinguish ATB from LTBI, and the results need to be verified by large sample prospective cohort study. Disclosures All Authors: No reported disclosures

Combined IFN-γ and TNF-α release assay for differentiating active tuberculosis from latent tuberculosis infection

2018 ◽  
Vol 77 (4) ◽  
pp. 314-320 ◽  
Author(s):  
Ji Yeun Kim ◽  
Joung Ha Park ◽  
Min-Chul Kim ◽  
Hye Hee Cha ◽  
Na-Young Jeon ◽  
...  
Keyword(s):  
Latent Tuberculosis Infection ◽  
Latent Tuberculosis ◽  
Active Tuberculosis ◽  
Tuberculosis Infection ◽  
Tnf Α ◽  
Release Assay ◽  
Ifn Γ

Treatment of latent tuberculosis infection induces changes in multifunctional Mycobacterium tuberculosis-specific CD4+ T cells

2015 ◽  
Vol 205 (1) ◽  
pp. 37-45 ◽  
Author(s):  
Ilaria Sauzullo ◽  
Fabio Mengoni ◽  
Claudia Mascia ◽  
Raffaella Rossi ◽  
Miriam Lichtner ◽  
...  
Keyword(s):  
T Cells ◽  
Mycobacterium Tuberculosis ◽  
Cd4 T Cells ◽  
Latent Tuberculosis Infection ◽  
Latent Tuberculosis ◽  
Tuberculosis Infection

scholarly journals Evaluation of cytokines as a biomarker to distinguish active tuberculosis from latent tuberculosis infection: a diagnostic meta-analysis

BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e039501
Author(s):  
Beibei Qiu ◽  
Qiao Liu ◽  
Zhongqi Li ◽  
Huan Song ◽  
Dian Xu ◽  
...  
Keyword(s):  
Latent Tuberculosis Infection ◽  
Meta Analysis ◽  
Latent Tuberculosis ◽  
Active Tuberculosis ◽  
Tuberculosis Infection ◽  
Cochrane Library ◽  
Effective Vaccine ◽  
Specific Method ◽  
Case Control Studies ◽  
Ifn Γ

ObjectivesWith a marginally effective vaccine and no significant breakthroughs in new treatments, a sensitive and specific method to distinguish active tuberculosis from latent tuberculosis infection (LTBI) would allow for early diagnosis and limit the spread of the pathogen. The analysis of multiple cytokine profiles provides the possibility to differentiate the two diseases.DesignSystematic review and meta-analysis.Data sourcesPubMed, Cochrane Library, Clinical Key and EMBASE databases were searched on 31 December 2019.Eligibility criteriaWe included case–control studies, cohort studies and randomised controlled trials considering IFN-γ, TNF-α, IP-10, IL-2, IL-10, IL-12 and VEGF as biomarkers to distinguish active tuberculosis and LTBI.Data extraction and synthesisTwo students independently extracted data and assessed the risk of bias. Diagnostic OR, sensitivity, specificity, positive and negative likelihood ratios and area under the curve (AUC) together with 95% CI were used to estimate the diagnostic value.ResultsOf 1315 records identified, 14 studies were considered eligible. IL-2 had the highest sensitivity (0.84, 95% CI: 0.72 to 0.92), while VEGF had the highest specificity (0.87, 95% CI: 0.73 to 0.94). The highest AUC was observed for VEGF (0.85, 95% CI: 0.81 to 0.88), followed by IFN-γ (0.84, 95% CI: 0.80 to 0.87) and IL-2 (0.84, 95% CI: 0.81 to 0.87).ConclusionCytokines, such as IL-2, IFN-γ and VEGF, can be utilised as promising biomarkers to distinguish active tuberculosis from LTBI.PROSPERO registration numberCRD42020170725.

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