Evaluation of cytokine levels using QuantiFERON-TB Gold Plus in patients with active tuberculosis

Current status and future landscape of diagnosing tuberculosis infection

Interferon-γ release assays (IGRAs), such as QuantiFERON-TB Gold (QFT) or T-SPOT.TB, are frequently used as tools for the diagnosis of tuberculosis (TB) infection in the 21st century. QFT-Plus recently emerged as the fourth generation of QFT assays and has replaced QFT In-Tube. However, IGRAs have several problems regarding the identification of active, latent, and cured TB infection, and the time-consuming diagnosis of TB infection because of the overnight incubation of clinical specimens or complexity of measuring the level of interferon (IFN)-γ. To easily diagnose TB infection and quickly compare it with conventional IGRAs, many in vitro tests are developed based on assays other than enzyme-linked immunosorbent assay or enzyme-linked immunospot, such as the fluorescent lateral flow assay that requires less manual operation and a shorter time. Simplified versions of IGRAs are emerging, including QIAreach QuantiFERON-TB. On the other hand, to distinguish active TB from latent or cured TB infection, new immunodiagnostic biomarkers beyond IFN-γ are evaluated using QFT supernatants. While IFN-γ or IFN-γ-related chemokine such as IFN-γ induced protein 10 is a potential biomarker in patients with active TB, interleukin-2 or latency-associated antigen such as heparin-binding hemagglutinin may be useful to distinguish active TB from latent or cured TB infection. There are no potential biomarkers to fully distinguish the time-phase of TB infection at present. It is necessary to discover new immunodiagnostic biomarkers to facilitate decisions on treatment selection for active or latent TB infection.

Assessing the Diagnostic Performance of New Commercial Interferon-γ Release Assays for Mycobacterium tuberculosis Infection: A Systematic Review and Meta-Analysis

BACKGROUND

We compared 6 new interferon-γ release assays (IGRAs; hereafter index tests: QFT-Plus, QFT-Plus CLIA, QIAreach, Wantai TB-IGRA, Standard E TB-Feron, and T-SPOT.TB/T-Cell Select) with World Health Organization (WHO)-endorsed tests for tuberculosis infection (hereafter reference tests).

METHODS

Data sources (1 January 2007-18 August 2021) were Medline, Embase, Web of Science, Cochrane Database of Systematic Reviews, and manufacturers' data. Cross-sectional and cohort studies comparing the diagnostic performance of index and reference tests were selected. The primary outcomes of interest were the pooled differences in sensitivity and specificity between index and reference tests. The certainty of evidence (CoE) was summarized using the GRADE approach.

RESULTS

Eighty-seven studies were included (44 evaluated the QFT-Plus, 4 QFT-Plus CLIA, 3 QIAreach, 26 TB-IGRA, 10 TB-Feron [1 assessing the QFT-Plus], and 1 T-SPOT.TB/T-Cell Select). Compared to the QFT-GIT, QFT Plus's sensitivity was 0.1 percentage points lower (95% confidence interval [CI], -2.8 to 2.6; CoE: moderate), and its specificity 0.9 percentage points lower (95% CI, -1.0 to -.9; CoE: moderate). Compared to QFT-GIT, TB-IGRA's sensitivity was 3.0 percentage points higher (95% CI, -.2 to 6.2; CoE: very low), and its specificity 2.6 percentage points lower (95% CI, -4.2 to -1.0; CoE: low). Agreement between the QFT-Plus CLIA and QIAreach with QFT-Plus was excellent (pooled κ statistics of 0.86 [95% CI, .78 to .94; CoE: low]; and 0.96 [95% CI, .92 to 1.00; CoE: low], respectively). The pooled κ statistic comparing the TB-Feron and the QFT-Plus or QFT-GIT was 0.85 (95% CI, .79 to .92; CoE: low).

CONCLUSIONS

The QFT-Plus and the TB-IGRA have very similar sensitivity and specificity as WHO-approved IGRAs.

Evaluation of tuberculosis diagnostic biomarkers in immunocompromised hosts based on cytokine levels in QuantiFERON-TB Gold Plus

Tuberculosis (TB) remains a serious health concern globally. QuantiFERON-TB (QFT) is a diagnostic tool for TB detection, and its sensitivity is reduced in immunocompromised hosts with low T lymphocyte counts or abnormal T cell function. This study aimed to evaluate the correlation between T cell and cytokine levels in patients with active TB using QFT-Plus. Forty-five patients with active TB were enrolled, and the cytokines in QFT-Plus tube supernatants were quantified using the MAGPIX System. CD4⁺ T cell count negatively correlated with patient age (p < 0.001, r = -0.51). The levels of TB1-responsive interleukin-1 receptor antagonist (IL-1Ra) and IL-2 correlated with CD4⁺ T cell count, whereas the levels of TB2-responsive IL-1Ra and IFN-γ-induced protein 10 correlated with both CD4⁺ and CD8⁺ T cell counts. Cytokines that correlated with CD4⁺ and CD8⁺ T cell counts might not be suitable TB diagnostic biomarkers in immunocompromised hosts. Notably, cytokines that did not correlate with the T cell counts, such as monocyte chemoattractant protein-1, might be candidate biomarkers for TB in immunocompromised hosts. Our findings might help improve TB diagnosis, which could enable prompt treatment and minimize poor disease outcomes.

QuantiFERON-TB Gold Plus Assay in Patients With Latent vs. Active Tuberculosis in a Low Incidence Setting: Level of IFN-γ, CD4/CD8 Responses, and Release of IL-2, IP-10, and MIG

Objectives

We analyzed the results of the QuantiFERON Glod Plus assay (QFT) and cytokine patterns associated with active tuberculosis (ATB) among patients with positive QFT.

Methods

A total of 195 patients are QFT-positive, among which 24 had an ATB and 171 had a latent tuberculosis infection (LTBI). Interferon-gamma (IFN-γ) secretion was analyzed relative to interleukin-2 (IL-2), IFN-γ inducible protein or CXCL-10 (IP-10), and monokine induced by IFN-γ or CXCL-9 (MIG) secretion, and then compared between two sets of peptide antigens [tube 1 - cluster of differentiation 4 (CD4+) T cell stimulation; tube 2 - CD4+/CD8+ T cell response].

Results

Higher IFN-γ responses were measured in the ATB group (p = 0.0089). The results showed that there was a lower ratio of tube 1/tube 2 IFN-γ concentrations in the ATB group (p = 0.0009), and a median [interquartile ranges (IQR)] difference between the two sets at −0.82 IU/ml (−1.67 to 0.18) vs. −0.07 IU/ml (−0.035 to 0.11, p &lt; 0.0001) in the ATB group compared to the LTBI group, respectively. In addition, patients with low ratios of IL-2/IFN-γ, IP-10/IFN-γ, and MIG/IFN-γ were much more likely to have ATB.

Conclusion

High levels of IFN-γ secretion, preferential IFN-γ response in tube 2, and lower secretion of IL-2, IP-10, and MIG release relative to IFN-γ secretion were more likely observed in subjects with ATB. These features of T cell response may be helpful in low prevalence settings to suspect ATB in patients tested positive for IFN-γ release assays (IGRA).

Evaluation of cytokine levels in response to mitogen among HIV-1-infected blood cells and their relationships to the number of T cells

BACKGROUND

Human immunodeficiency virus-1 (HIV-1) infection causes loss and anergy of CD4⁺ and CD8⁺ T cells, leading to opportunistic infections, including tuberculosis (TB). QuantiFERON®-TB (QFT) is used as a diagnostic tool to detect TB, but it exhibits limited accuracy among subjects with low CD4⁺ T cell numbers, including HIV-1-infected individuals. The present study aimed to determine the effect of HIV-1 infection and patients' blood T cell numbers on cytokine production in response to mitogen (Mit) stimulation.

METHODS

The number of CD4⁺ and CD8⁺ T cells in HIV-1-infected individuals was quantified. Levels of various cytokines in Mit-stimulated and un-stimulated (Nil) supernatants of QFT gold "in tube" were assessed using a MAGPIX System. The correlation between cytokine levels and CD4⁺/CD8⁺ T cell counts in response to Mit was analyzed. The cytokine levels were compared between HIV-1-infected and healthy subjects.

RESULTS

HIV-1-infected individuals (110) and control subjects (27) were enrolled. Interferon (IFN)-γ, interleukin-1 receptor antagonist (IL-1RA), IL-6, IL-8, and regulated on activation, normal T cell expressed and secreted (RANTES) values in Mit-Nil tubes showed a significant correlation with CD4⁺ T cell counts, while IFN-γ, IL-6, and IFN-γ-induced protein 10 (IP-10) values in Mit-Nil tubes had significant correlation with CD8⁺ T cell counts. IL-1RA, IL-8, IP-10, platelet-derived growth factor (PDGF)-BB, and RANTES levels in Nil tubes were significantly higher in the HIV-1-infected group. IFN-γ, IL-2, IL-5, IL-6, IP-10, and macrophage inflammatory protein-1β values in Mit-Nil tubes were significantly higher, and PDGF-BB and RANTES levels were significantly lower in the HIV-1-infected group.

CONCLUSION

The functions of HIV-1-infected T cells and uninfected T cells, such as spontaneous and responsive cytokine production in response to Mit, were different. Our findings may be useful for developing new clinical tools for patients with low T cell counts. Additionally, the study provides new insights into the pathogenesis of HIV-1 infection.

MCP-1: Function, regulation, and involvement in disease

MCP-1 (Monocyte chemoattractant protein-1), also known as Chemokine (CC-motif) ligand 2 (CCL2), is from family of CC chemokines. It has a vital role in the process of inflammation, where it attracts or enhances the expression of other inflammatory factors/cells. It leads to the advancement of many disorders by this main mechanism of migration and infiltration of inflammatory cells like monocytes/macrophages and other cytokines at the site of inflammation. MCP-1 has been inculpated in the pathogenesis of numerous disease conditions either directly or indirectly like novel corona virus, cancers, neuroinflammatory diseases, rheumatoid arthritis, cardiovascular diseases. The elevated MCP-1 level has been observed in COVID-19 patients and proven to be a biomarker associated with the extremity of disease along with IP-10. This review will focus on involvement and role of MCP-1 in various pathological conditions.

Recent advances in the detection of interferon-gamma as a TB biomarker

Tuberculosis (TB) is one of the main infectious diseases worldwide and accounts for many deaths. It is caused by Mycobacterium tuberculosis usually affecting the lungs of patients. Early diagnosis and treatment are essential to control the TB epidemic. Interferon-gamma (IFN-γ) is a cytokine that plays a part in the body’s immune response when fighting infection. Current conventional antibody-based TB sensing techniques which are commonly used include enzyme-linked immunosorbent assay (ELISA) and interferon-gamma release assays (IGRAs). However, these methods have major drawbacks, such as being time-consuming, low sensitivity, and inability to distinguish between the different stages of the TB disease. Several electrochemical biosensor systems have been reported for the detection of interferon-gamma with high sensitivity and selectivity. Microfluidic techniques coupled with multiplex analysis in regular format and as lab-on-chip platforms have also been reported for the detection of IFN-γ. This article is a review of the techniques for detection of interferon-gamma as a TB disease biomarker. The objective is to provide a concise assessment of the available IFN-γ detection techniques (including conventional assays, biosensors, microfluidics, and multiplex analysis) and their ability to distinguish the different stages of the TB disease.

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

Background

Rapid 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.

Methods

Participants 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.

Results

A 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.

Conclusions

We demonstrated that HLA-DR on MTB-specific cells was a potentially useful biomarker for accurate discrimination between ATB and LTBI.

Lymphocyte-Related Immunological Indicators for Stratifying Mycobacterium tuberculosis Infection

Background

Easily accessible tools that reliably stratify Mycobacterium tuberculosis (MTB) infection are needed to facilitate the improvement of clinical management. The current study attempts to reveal lymphocyte-related immune characteristics of active tuberculosis (ATB) patients and establish immunodiagnostic model for discriminating ATB from latent tuberculosis infection (LTBI) and healthy controls (HC).

Methods

A total of 171 subjects consisted of 54 ATB, 57 LTBI, and 60 HC were consecutively recruited at Tongji hospital from January 2019 to January 2021. All participants were tested for lymphocyte subsets, phenotype, and function. Other examination including T-SPOT and microbiological detection for MTB were performed simultaneously.

Results

Compared with LTBI and HC, ATB patients exhibited significantly lower number and function of lymphocytes including CD4⁺ T cells, CD8⁺ T cells and NK cells, and significantly higher T cell activation represented by HLA-DR and proportion of immunosuppressive cells represented by Treg. An immunodiagnostic model based on the combination of NK cell number, HLA-DR⁺CD3⁺ T cells, Treg, CD4⁺ T cell function, and NK cell function was built using logistic regression. Based on receiver operating characteristic curve analysis, the area under the curve (AUC) of the diagnostic model was 0.920 (95% CI, 0.867-0.973) in distinguishing ATB from LTBI, while the cut-off value of 0.676 produced a sensitivity of 81.48% (95% CI, 69.16%-89.62%) and specificity of 91.23% (95% CI, 81.06%-96.20%). Meanwhile, AUC analysis between ATB and HC according to the diagnostic model was 0.911 (95% CI, 0.855-0.967), with a sensitivity of 81.48% (95% CI, 69.16%-89.62%) and a specificity of 90.00% (95% CI, 79.85%-95.34%).

Conclusions

Our study demonstrated that the immunodiagnostic model established by the combination of lymphocyte-related indicators could facilitate the status differentiation of MTB infection.

Lymphocyte Non-Specific Function Detection Facilitating the Stratification of Mycobacterium tuberculosis Infection

Background

Inadequate tuberculosis (TB) diagnostics, especially for discrimination between active TB (ATB) and latent TB infection (LTBI), are major hurdle in the reduction of the disease burden. The present study aims to investigate the role of lymphocyte non-specific function detection for TB diagnosis in clinical practice.

Methods

A total of 208 participants including 49 ATB patients, 64 LTBI individuals, and 95 healthy controls were recruited at Tongji hospital from January 2019 to October 2020. All subjects were tested with lymphocyte non-specific function detection and T-SPOT assay.

Results

Significantly positive correlation existed between lymphocyte non-specific function and phytohemagglutinin (PHA) spot number. CD4⁺ T cell non-specific function showed the potential for differentiating patients with negative T-SPOT results from those with positive T-SPOT results with an area under the curve (AUC) of 0.732 (95% CI, 0.572-0.893). The non-specific function of CD4⁺ T cells, CD8⁺ T cells, and NK cells was found significantly lower in ATB patients than in LTBI individuals. The AUCs presented by CD4⁺ T cell non-specific function, CD8⁺ T cell non-specific function, and NK cell non-specific function for discriminating ATB patients from LTBI individuals were 0.845 (95% CI, 0.767-0.925), 0.770 (95% CI, 0.683-0.857), and 0.691 (95% CI, 0.593-0.789), respectively. Application of multivariable logistic regression resulted in the combination of CD4⁺ T cell non-specific function, NK cell non-specific function, and culture filtrate protein-10 (CFP-10) spot number as the optimally diagnostic model for differentiating ATB from LTBI. The AUC of the model in distinguishing between ATB and LTBI was 0.939 (95% CI, 0.898-0.981). The sensitivity and specificity were 83.67% (95% CI, 70.96%-91.49%) and 90.63% (95% CI, 81.02%-95.63%) with the threshold as 0.57. Our established model showed superior performance to TB-specific antigen (TBAg)/PHA ratio in stratifying TB infection status.

Conclusions

Lymphocyte non-specific function detection offers an attractive alternative to facilitate TB diagnosis. The three-index diagnostic model was proved to be a potent tool for the identification of different events involved in TB infection, which is helpful for the treatment and management of patients.