Biomarkers for discrimination between latent tuberculosis infection and active tuberculosis disease

Integrating pathogen- and host-derived blood biomarkers for enhanced tuberculosis diagnosis: a comprehensive review

This review explores the evolving landscape of blood biomarkers in the diagnosis of tuberculosis (TB), focusing on biomarkers derived both from the pathogen and the host. These biomarkers provide critical insights that can improve diagnostic accuracy and timeliness, essential for effective TB management. The document highlights recent advancements in molecular techniques that have enhanced the detection and characterization of specific biomarkers. It also discusses the integration of these biomarkers into clinical practice, emphasizing their potential to revolutionize TB diagnostics by enabling more precise detection and monitoring of the disease progression. Challenges such as variability in biomarker expression and the need for standardized validation processes are addressed to ensure reliability across different populations and settings. The review calls for further research to refine these biomarkers and fully harness their potential in the fight against TB, suggesting a multidisciplinary approach to overcome existing barriers and optimize diagnostic strategies. This comprehensive analysis underscores the significance of blood biomarkers as invaluable tools in the global effort to control and eliminate TB.

Effect of tuberculosis-specific antigen stimulation on the diagnostic accuracy of interferon-γ inducible protein-10 in distinguishing active and latent tuberculosis infection: a meta-analysis

BACKGROUND

Identifying active tuberculosis (ATB) from latent tuberculosis infection (LTBI) persists as a challenge, and interferon-γ inducible protein-10 (IP-10) has been employed as the solution. To further improve its diagnostic performance, the sample can be stimulated with TB specific antigen (TBAg).

AIM

To perform meta-analysis on diagnostic accuracy of unstimulated and TBAg-stimulated IP-10 in differentiating ATB from LTBI.

METHODS

Systematic search was performed on five major scientific databases as of 29 November 2023. Observational studies reporting diagnostic values of unstimulated or TBAg-stimulated IP-10 in identifying ATB from LTBI were included. Meta-analysis was carried out using two-level mixed-effect logistic regression model.

RESULTS

Twenty-five studies recruiting 2301 patients (1137 ATB versus 1164 LTBI) were included in the quantitative analysis. The pooled sensitivity and specifity of IP-10 were 72% (95%CI: 0.59-0.82) and 78% (95%CI: 0.63-0.88), respectively. As for TBAg-stimulated IP-10, the sensitivity and specifity were 82% (95%CI: 0.76-0.87) and 85% (95%CI: 0.73-0.92), respectively. The senstivity was reduced signiticantly (p < 0.01) when the patients with human immunodeficiency virus infection were included, except after the TBAg stimulation.

CONCLUSION

Stimulating IP-10 with TBAg could improve the diagnostic accuracy in differentiating ATB from LTBI.

B cells in perivascular and peribronchiolar granuloma-associated lymphoid tissue and B-cell signatures identify asymptomatic Mycobacterium tuberculosis lung infection in Diversity Outbred mice

Because most humans resist Mycobacterium tuberculosis infection, there is a paucity of lung samples to study. To address this gap, we infected Diversity Outbred mice with M. tuberculosis and studied the lungs of mice in different disease states. After a low-dose aerosol infection, progressors succumbed to acute, inflammatory lung disease within 60 days, while controllers maintained asymptomatic infection for at least 60 days, and then developed chronic pulmonary tuberculosis (TB) lasting months to more than 1 year. Here, we identified features of asymptomatic M. tuberculosis infection by applying computational and statistical approaches to multimodal data sets. Cytokines and anti-M. tuberculosis cell wall antibodies discriminated progressors vs controllers with chronic pulmonary TB but could not classify mice with asymptomatic infection. However, a novel deep-learning neural network trained on lung granuloma images was able to accurately classify asymptomatically infected lungs vs acute pulmonary TB in progressors vs chronic pulmonary TB in controllers, and discrimination was based on perivascular and peribronchiolar lymphocytes. Because the discriminatory lesion was rich in lymphocytes and CD4 T cell-mediated immunity is required for resistance, we expected CD4 T-cell genes would be elevated in asymptomatic infection. However, the significantly different, highly expressed genes were from B-cell pathways (e.g., Bank1, Cd19, Cd79, Fcmr, Ms4a1, Pax5, and H2-Ob), and CD20+ B cells were enriched in the perivascular and peribronchiolar regions of mice with asymptomatic M. tuberculosis infection. Together, these results indicate that genetically controlled B-cell responses are important for establishing asymptomatic M. tuberculosis lung infection.

Multiple cytokine analysis based on QuantiFERON-TB gold plus in different tuberculosis infection status: an exploratory study

BACKGROUND

More efficient and convenient diagnostic method is a desperate need to reduce the burden of tuberculosis (TB). This study explores the multiple cytokines secretion based on QuantiFERON-TB Gold Plus (QFT-Plus), and screens for optimal cytokines with diagnostic potential to differentiate TB infection status.

METHODS

Twenty active tuberculosis (ATB) patients, fifteen patients with latent TB infection (LTBI), ten patients with previous TB and ten healthy controls (HC) were enrolled. Whole blood samples were collected and stimulated by QFT-Plus TB1 and TB2 antigens. The levels of IFN-γ, TNF-α, IL-2, IL-6, IL-5, IL-10, IP-10, IL-1Ra, CXCL-1 and MCP-1 in supernatant were measured by Luminex bead-based multiplex assays. The receiver operating characteristic curve was used to evaluate the diagnostic accuracy of cytokine for distinguishing different TB infection status.

RESULTS

After stimulation with QFT-Plus TB1 and TB2 antigens, the levels of all cytokines, except IL-5 in TB2 tube, in ATB group were significantly higher than that in HC group. The levels of IL-1Ra concurrently showed the equally highest AUC for distinguishing TB infection from HC, followed by the levels of IP-10 in both TB1 tube and TB2 tube. Moreover, IP-10 levels displayed the largest AUC for distinguishing ATB patients from non-ATB patients. Meanwhile, the levels of IP-10 also demonstrated the largest AUC in both TB1 tube and TB2 tube for distinguishing ATB patients from LTBI.

CONCLUSIONS

In addition to conventional detection of IFN-γ, measuring IP-10 and IL-1Ra based on QFT-Plus may have the more tremendous potential to discriminate different TB infection status.

Plasma CXCL8 and MCP-1 as surrogate plasma biomarkers of latent tuberculosis infection among household contacts-A cross-sectional study

Early detection of latent tuberculosis infection (LTBI) is critical to TB elimination in the current WHO vision of End Tuberculosis Strategy. The study investigates whether detecting plasma cytokines could aid in diagnosing LTBI across household contacts (HHCs) positive for IGRA, HHCs negative for IGRA, and healthy controls. The plasma cytokines were measured using a commercial Bio-Plex Pro Human Cytokine 17-plex assay. Increased plasma CXCL8 and decreased MCP-1, TNF-α, and IFN-γ were associated with LTBI. Regression analysis showed that a combination of CXCL8 and MCP-1 increased the risk of LTBI among HHCs to 14-fold. Our study suggests that CXCL-8 and MCP-1 could serve as the surrogate biomarkers of LTBI, particularly in resource-limited settings. Further laboratory investigations are warranted before extrapolating CXCL8 and MCP-1 for their usefulness as surrogate biomarkers of LTBI in resource-limited settings.

Plasma CXCL8 and MCP-1 as biomarkers of latent tuberculosis infection

Background

Early detection of latent tuberculosis infection (LTBI) is critical to TB elimination in the current WHO vision of End Tuberculosis Strategy.

Methods

We investigated whether detecting plasma cytokines could aid in diagnosing LTBI across household contacts (HHCs) positive for IGRA, HHCs negative for IGRA, and healthy controls. We also measured the plasma cytokines using a commercial Bio-Plex Pro Human Cytokine 17-plex assay.

Results

Increased plasma CXCL8 and decreased MCP-1, TNF-α, and IFN-γ were associated with LTBI. Regression analysis showed that a combination of CXCL8 and MCP-1 increased the risk of LTBI among HHCs to 14-fold.

Conclusions

We postulated that CXCL8 and MCP-1 could be the surrogate biomarkers of LTBI, especially in resource-limited settings.

Cytokine/chemokine profiles in people with recent infection by Mycobacterium tuberculosis

Introduction

The risk of progression to tuberculosis disease is highest within the first year after M. tuberculosis infection (TBI). We hypothesize that people with newly acquired TBI have a unique cytokine/chemokine profile that could be used as a potential biomarker.

Methods

We evaluated socio-demographic variables and 18 cytokines/chemokines in plasma samples from a cohort of people deprived of liberty (PDL) in two Colombian prisons: 47 people diagnosed with pulmonary TB, 24 with new TBI, and 47 non-infected individuals. We performed a multinomial regression to identify the immune parameters that differentiate the groups.

Results

The concentration of immune parameters changed over time and was affected by the time of incarceration. The concentration of sCD14, IL-18 and IP-10 differed between individuals with new TBI and short and long times of incarceration. Among people with short incarceration, high concentrations of MIP-3α were associated with a higher risk of a new TBI, and higher concentrations of Eotaxin were associated with a lower risk of a new TBI. Higher concentrations of sCD14 and TNF-α were associated with a higher risk of TB disease, and higher concentrations of IL-18 and MCP-1 were associated with a lower risk of TB disease.

Conclusions

There were cytokines/chemokines associated with new TBI and TB disease. However, the concentration of immune mediators varies by the time of incarceration among people with new TBI. Further studies should evaluate the changes of these and other cytokines/chemokines over time to understand the immune mechanisms across the spectrum of TB.

Screening for diagnostic targets in tuberculosis and study on its pathogenic mechanism based on mRNA sequencing technology and miRNA-mRNA-pathway regulatory network

Purpose

Tuberculosis is common infectious diseases, characterized by infectivity, concealment and chronicity, and the early diagnosis is helpful to block the spread of tuberculosis and reduce the resistance of Mycobacterium tuberculosis to anti-tuberculosis drugs. At present, there are obvious limitations in the application of clinical detection methods used for the early diagnosis of tuberculosis. RNA sequencing (RNA-Seq) has become an economical and accurate gene sequencing method for quantifying transcripts and detecting unknown RNA species.

Methods

A peripheral blood mRNA sequencing was used to screen the differentially expressed genes between healthy people and tuberculosis patients. A protein-protein interaction (PPI) network of differentially expressed genes was constructed through Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The potential diagnostic targets of tuberculosis were screened by the calculation of degree, betweenness and closeness in Cytoscape 3.9.1 software. Finally, the functional pathways and the molecular mechanism of tuberculosis were clarified in combination of the prediction results of key gene miRNAs, and by Gene Ontology (GO) enrichment analysis and the Kyoto Encyclopedia Genes and Genomes (KEGG) pathway annotation analysis.

Results

556 Differential genes of tuberculosis were screened out by mRNA sequencing. Six key genes (AKT1, TP53, EGF, ARF1, CD274 and PRKCZ) were screened as the potential diagnostic targets for tuberculosis by analyzing the PPI regulatory network and using three algorithms. Three pathways related to the pathogenesis of tuberculosis were identified by KEGG pathway analysis, and two key miRNAs (has-miR-150-5p and has-miR-25-3p) that might participate in the pathogenesis of tuberculosis were screened out by constructing a miRNA-mRNA pathway regulatory network.

Conclusion

Six key genes and two important miRNAs that could regulate them were screened out by mRNA sequencing. The 6 key genes and 2 important miRNAs may participate in the pathogenesis of infection and invasion of Mycobacterium tuberculosis through herpes simplex virus 1 infection, endocytosis and B cell receptor signaling pathways.

Challenges and the Way forward in Diagnosis and Treatment of Tuberculosis Infection

Globally, it is estimated that one-quarter of the world's population is latently infected with Mycobacterium tuberculosis (Mtb), also known as latent tuberculosis infection (LTBI). Recently, this condition has been referred to as tuberculosis infection (TBI), considering the dynamic spectrum of the infection, as 5-10% of the latently infected population will develop active TB (ATB). The chances of TBI development increase due to close contact with index TB patients. The emergence of multidrug-resistant TB (MDR-TB) and the risk of development of latent MDR-TB has further complicated the situation. Detection of TBI is challenging as the infected individual does not present symptoms. Currently, there is no gold standard for TBI diagnosis, and the only screening tests are tuberculin skin test (TST) and interferon gamma release assays (IGRAs). However, these tests have several limitations, including the inability to differentiate between ATB and TBI, false-positive results in BCG-vaccinated individuals (only for TST), false-negative results in children, elderly, and immunocompromised patients, and the inability to predict the progression to ATB, among others. Thus, new host markers and Mtb-specific antigens are being tested to develop new diagnostic methods. Besides screening, TBI therapy is a key intervention for TB control. However, the long-course treatment and associated side effects result in non-adherence to the treatment. Additionally, the latent MDR strains are not susceptible to the current TBI treatments, which add an additional challenge. This review discusses the current situation of TBI, as well as the challenges and efforts involved in its control.

High Procalcitonin, C-Reactive Protein, and α-1 Acid Glycoprotein Levels in Whole Blood Samples Could Help Rapid Discrimination of Active Tuberculosis from Latent Tuberculosis Infection and Healthy Individuals

Tuberculosis (TB) management is important for prompt discrimination of latent TB infection (LTBI) from active TB and proper treatment. Whole blood Interferon-gamma (IFN-γ) release assay (IGRA) is used to diagnose LTBI based on the secretion of IFN-γ by T-cells in the whole blood by using a specific antigen of Mycobacterium tuberculosis. However, the ability of IGRA to distinguish active TB from LTBI is considerably limited. Distinguishing active TB from LTBI is necessary to identify indicators that can be used to effectively manage TB and develop diagnostic methods. In the present study, we used a Luminex multiplex bead array (a bead-based antibody−antigen sandwich method). The whole blood level of acute phase proteins (APPs), such as endoglin (ENG), procalcitonin (PCT), C-reactive protein (CRP), and α1-acid glycoprotein (AGP), in active TB, LTBI, and healthy individuals were analyzed and quantified. The APP test results for the serum and whole blood samples showed that the levels of PCT, CRP, and AGP were significantly increased (p < 0.0500; area under curve = 0.955) in active TB. The level of these markers in the whole blood of active TB, LTBI, and healthy individuals could provide data for effective diagnosis and treatment of TB.

Differential activation of innate and adaptive lymphocytes during latent or active infection with Mycobacterium tuberculosis

Most individuals infected with Mycobacterium tuberculosis (Mtb) have latent tuberculosis (TB), which can be diagnosed with tests (like the QuantiFERON test, QFT) that detect the production of IFN-γ by memory T cells in response to the Mtb-specific antigens ESAT-6, CFP-10 and TB7.7. However, the immunological mechanisms that determine if an individual will develop latent or active TB remain incompletely understood. Here we compared the response of innate and adaptive peripheral blood lymphocytes from healthy individuals without Mtb infection (QFT-negative) and from individuals with latent (QFT-positive) or active TB infection, in order to determine the characteristics of these cells that correlate with each condition. In active TB patients, the levels of IFN-γ that were produced in response to Mtb-specific antigens had high positive correlations with IL-1β, TNF-α, MCP-1, IL-6, IL-12p70 and IL-23, while the pro-inflammatory cytokines had high positive correlations between themselves and with IL-12p70 and IL-23. These correlations were not observed in QFT-negative or QFT-positive healthy volunteers. Activation with Mtb soluble extract (a mixture of Mtb antigens and pathogen-associated molecular patterns [PAMPs]) increased the percentage of IFN-γ/IL-17-producing NK cells and of IL-17-producing ILC3 in the peripheral blood of active TB patients, but not of QFT-negative or QFT-positive healthy volunteers. Thus, active TB patients have both adaptive and innate lymphocyte subsets that produce characteristic cytokine profiles in response to Mtb-specific antigens or PAMPs. These profiles are not observed in uninfected individuals or in individuals with latent TB, suggesting that they are a response to active TB infection. This article is protected by copyright. All rights reserved.

VEGF Profile in Early Undifferentiated Arthritis Cohort

Background and Objectives: Early undifferentiated arthritis (UA) is a group of inflammatory joint diseases that are not classified under any specific rheumatic or connective tissue disorder and might evolve into chronic inflammatory arthritis or may be a self-limiting condition. Early recognition and treatment are crucial for the future course of the disease. Vascular endothelial growth factor (VEGF) is an angiogenic regulator that induces the growth of new capillary blood vessels, which are important in joint invasion and destruction during the progression of chronic inflammatory arthritis. The aim of this study was to assess VEGF levels associated with sociodemographic, clinical, laboratory, and ultrasound findings in the early UA patient cohort as well as to evaluate VEGF as a potential prognostic marker for arthritis outcomes. Materials and Methods: Seventy-six patients with inflammatory arthritis in at least one joint, with a duration of arthritis <12 months at the study entry that did not meet any rheumatic disease classification criteria, were enrolled after informed consent was obtained. Patient’s sociodemographic, laboratory data, and clinical disease characteristics were recorded, VEGF levels were measured, and ultrasound (US) of tender and swollen joints was performed. Results: VEGF levels had positive correlation with conventional rheumatic disease activity and diagnostic markers: erythrocyte sedimentation rate (ESR), C−reactive protein (CRP), and rheumatoid factor (RF) (p < 0.05). RF-positive patients had higher VEGF values (p = 0.024). A statistically higher number of patients whose VEGF levels were below the median value presented with active infection (p = 0.046). In patients with a higher number of swollen joints, and a higher score of synovitis and power doppler (PD) seen on US, VEGF levels were statistically significantly higher. Patients who after 12-month follow-up developed rheumatoid arthritis (RA) had statistically higher VEGF levels at baseline compared with those who developed spondyloarthropathies (p = 0.028). Conclusions: This study demonstrated that VEGF levels significantly represented inflammatory processes that were present in the joints (number of swollen joints, synovitis, and PD changes) of the early UA cohort.

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).

Differential Diagnosis of Latent Tuberculosis Infection and Active Tuberculosis: A Key to a Successful Tuberculosis Control Strategy

As an ancient infectious disease, tuberculosis (TB) is still the leading cause of death from a single infectious agent worldwide. Latent TB infection (LTBI) has been recognized as the largest source of new TB cases and is one of the biggest obstacles to achieving the aim of the End TB Strategy. The latest data indicate that a considerable percentage of the population with LTBI and the lack of differential diagnosis between LTBI and active TB (aTB) may be potential reasons for the high TB morbidity and mortality in countries with high TB burdens. The tuberculin skin test (TST) has been used to diagnose TB for > 100 years, but it fails to distinguish patients with LTBI from those with aTB and people who have received Bacillus Calmette–Guérin vaccination. To overcome the limitations of TST, several new skin tests and interferon-gamma release assays have been developed, such as the Diaskintest, C-Tb skin test, EC-Test, and T-cell spot of the TB assay, QuantiFERON-TB Gold In-Tube, QuantiFERON-TB Gold-Plus, LIAISON QuantiFERON-TB Gold Plus test, and LIOFeron TB/LTBI. However, these methods cannot distinguish LTBI from aTB. To investigate the reasons why all these methods cannot distinguish LTBI from aTB, we have explained the concept and definition of LTBI and expounded on the immunological mechanism of LTBI in this review. In addition, we have outlined the research status, future directions, and challenges of LTBI differential diagnosis, including novel biomarkers derived from Mycobacterium tuberculosis and hosts, new models and algorithms, omics technologies, and microbiota.

Harnessing the Potential of Multiomics Studies for Precision Medicine in Infectious Disease

The field of infectious diseases currently takes a reactive approach and treats infections as they present in patients. Although certain populations are known to be at greater risk of developing infection (eg, immunocompromised), we lack a systems approach to define the true risk of future infection for a patient. Guided by impressive gains in "omics" technologies, future strategies to infectious diseases should take a precision approach to infection through identification of patients at intermediate and high-risk of infection and deploy targeted preventative measures (ie, prophylaxis). The advances of high-throughput immune profiling by multiomics approaches (ie, transcriptomics, epigenomics, metabolomics, proteomics) hold the promise to identify patients at increased risk of infection and enable risk-stratifying approaches to be applied in the clinic. Integration of patient-specific data using machine learning improves the effectiveness of prediction, providing the necessary technologies needed to propel the field of infectious diseases medicine into the era of personalized medicine.

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.

Revisiting tuberculosis screening: An insight to complementary diagnosis and prospective molecular approaches for the recognition of the dormant TB infection in human and cattle hosts

Tuberculosis (TB) is defined as a chronic infection in both human and cattle hosts and many subclinical cases remain undetected. After the pathogen is inhaled by a host, phagocyted bacilli can persist inside macrophages surviving intracellularly. Hosts develop granulomatous lesions in the lungs or lymph nodes, limiting infection. However, bacilli become persister cells. Immunological diagnosis of TB is performed basically by routine tuberculin skin test (TST), and in some cases, by ancillary interferon-gamma release assay (IGRA). The concept of human latent TB infection (LTBI) by M. tuberculosis is recognized in cohorts without symptoms by routine clinical diagnostic tests, and nowadays IGRA tests are used to confirm LTBI with either active or latent specific antigens of M. tuberculosis. On the other hand, dormant infection in cattle by M. bovis has not been described by TST or IGRA testing as complications occur by cross-reactive immune responses to homolog antigens of environmental mycobacteria or a false-negative test by anergic states of a wained bovine immunity, evidencing the need for deciphering more specific biomarkers by new-generation platforms of analysis for detection of M. bovis dormant infection. The study and description of bovine latent TB infection (boLTBI) would permit the recognition of hidden animal infection with an increase in the sensitivity of routine tests for an accurate estimation of infected dairy cattle. Evidence of immunological and experimental analysis of LTBI should be taken into account to improve the study and the description of the still neglected boLTBI.

CCL1 and IL-2Ra differentiate Tuberculosis disease from latent infection Irrespective of HIV infection in low TB burden countries

OBJECTIVES

To evaluate the performance of selected host immunological biomarkers in differentiating tuberculosis (TB) disease from latent TB infection (LTBI) in HIV uninfected and infected individuals enrolled in TB low-burden countries.

DESIGN

Participants with TB disease (N = 85) and LTBI (N = 150) were recruited from prospective cohorts at hospitals in Norway and Denmark. Plasma concentrations of 54 host markers were assessed by Luminex multiplex immunoassays. Using receiver operator characteristic curves and general discriminant analysis, we determined the abilities of individual and combined biomarkers to discriminate between TB disease and LTBI including when patients were stratified according to HIV infection status.

RESULTS

Regardless of the groups compared, CCL1 and IL-2Ra were the most accurate single biomarkers in differentiating TB disease from LTBI. Regardless of HIV status, a 4-marker signature (CCL1+RANTES+CRP+MIP-1α) derived from a training set (n = 155) differentiated TB disease from LTBI in the test set (n = 67) with a sensitivity of 56.0% (95% CI, 34.9-75.6) and a specificity of 85.7% (95% CI, 71.5-94.6). A 5-marker signature derived from the HIV uninfected group (CCL1+RANTES+MIP-1α+procalcitonin+IP-10) performed in HIV-infected individuals with a sensitivity of 75.0% and a specificity of 96.7% after leave-one-out cross validation. A 2-marker signature (CCL1+TNF-α) identified in HIV-infected persons performed in HIV-uninfected with a sensitivity and specificity of 66.7% and 100% respectively in the test set.

CONCLUSIONS

Plasma CCL1 and IL-2Ra have potential as biomarkers for differentiating TB disease from LTBI in low TB burden settings unaffected by HIV infection. Combinations between these and other biomarkers in bio-signatures for global use warrant further exploration.

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.

Combination of Blood Routine Examination and T-SPOT.TB Assay for Distinguishing Between Active Tuberculosis and Latent Tuberculosis Infection

Background

Distinguishing between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging.

Methods

Between 2013 and 2019, 2,059 (1,097 ATB and 962 LTBI) and another 883 (372 ATB and 511 LTBI) participants were recruited based on positive T-SPOT.TB (T-SPOT) results from Qiaokou (training) and Caidian (validation) cohorts, respectively. Blood routine examination (BRE) was performed simultaneously. Diagnostic model was established according to multivariate logistic regression.

Results

Significant differences were observed in all indicators of BRE and T-SPOT assay between ATB and LTBI. Diagnostic model built on BRE showed area under the curve (AUC) of 0.846 and 0.850 for discriminating ATB from LTBI in the training and validation cohorts, respectively. Meanwhile, TB-specific antigens spot-forming cells (SFC) (the larger of early secreted antigenic target 6 and culture filtrate protein 10 SFC in T-SPOT assay) produced lower AUC of 0.775 and 0.800 in the training and validation cohorts, respectively. The diagnostic model based on combination of BRE and T-SPOT showed an AUC of 0.909 for differentiating ATB from LTBI, with 78.03% sensitivity and 90.23% specificity when a cutoff value of 0.587 was used in the training cohort. Application of the model to the validation cohort showed similar performance. The AUC, sensitivity, and specificity were 0.910, 78.23%, and 90.02%, respectively. Furthermore, we also assessed the performance of our model in differentiating ATB from LTBI with lung lesions. Receiver operating characteristic analysis showed that the AUC of established model was 0.885, while a threshold of 0.587 yield a sensitivity of 78.03% and a specificity of 85.69%, respectively.

Conclusions

The diagnostic model based on combination of BRE and T-SPOT could provide a reliable differentiation between ATB and LTBI.

The Diagnostic Value of Blood and Urine IP-10 Test in Children Having Active Tuberculosis or Latent Tuberculosis Infection

Objective This study aimed to investigate interferon-gamma-inducible protein-10 (IP-10) values in serum and urine in pediatric patients in the diagnosis of active tuberculosis (TB) or latent TB infection (LTBI). It also aimed to investigate whether it can be used as a biomarker to distinguish between active TB and LTBI.

Methods Our study comprised active TB (25 patients), LTBI (25 patients), and the “infected” group (50 patients) formed by combining the two groups. As the control group, 37 healthy children were included in the study. TB skin test, plasma IP-10, and urine IP-10 measurements were performed in all patients included in the study. An additional QuantiFERON-TB Gold In-Tube (QFT-GIT) test was performed on patients evaluated as active TB or LTBI.

Results Plasma IP-10 levels of the patients in the active TB, LTBI, and the “infected” groups were significantly higher than the control group (p = 0.022, p = 0.028, and p = 0.007, respectively). Urine IP-10 was successful in distinguishing the active TB and “infected” groups from the control group (p = 0.007 and p = 0.047, respectively). Also, in the combined use of the tests, when QFT-GIT and urine IP-10 were positive together, active TB and LTBI could be distinguished (p = 0.044). Urine IP-10 levels were found to be significantly higher in those with pulmonary TB than those with extrapulmonary TB (p = 0.012).

Conclusion Our findings suggest that IP-10 can be used as a useful biomarker in the diagnosis of active TB in children.

Combined analysis of whole blood interferon gamma release assay and complete blood count analysis for rapid discrimination of active tuberculosis and latent tuberculosis infection

Tuberculosis (TB), which is caused by Mycobacterium tuberculosis (MTB), is a serious infectious disease with high infection and mortality rates and is a public health problem around the world. According to the World Health Organization (WHO) report, one-third of the world's population is latently infected with MTB, and 5 to 10% of those with latent TB infection (LTBI) have the potential to develop active TB once in their lifetime. Therefore, TB management for promptly distinguishing LTBI from active TB and for proper treatment is important. LTBI is currently diagnosed using the tuberculin skin test (TST) and interferon gamma (IFN-γ) release assay (IGRA). However, this test is substantially limited by its inability to distinguish active TB from LTBI. It is necessary to discover indicators that can be used for effective TB management and to develop diagnostic methods. In the present study, we used IGRA and complete blood count (CBC) analysis for discrimination of active TB, LTBI, and healthy control groups. The results showed that the number of WBC was significantly increased in the group with active TB (p < 0.0100) and level of hemoglobin (Hb) was significantly decreased (p < 0.0010) in the CBC than those of the healthy control and LTBI groups. In the WBC differential count, the number of neutrophils and monocytes were increased (p < 0.0010) in active TB group, where as those of lymphocytes were significantly decreased (p < 0.0100) in active TB group compared healthy control group. Results verified that the levels of total WBC, Hb, neutrophils, lymphocytes and monocytes were statistically significant (p < 0.0500) and the AUC was approximately 0.8613. In addition, receiver operating characteristic (ROC) curve analysis was performed to confirm the clinical usefulness between active TB and healthy control groups. In conclusion, based on these data demonstrated that the usefulness of these potential indicators for differential diagnosis, according to the result can be provided for effective diagnosis and treatment by comparing the expression patterns of the markers in the whole blood of the active TB, LTBI, and healthy control groups. Furthermore, this study needs to investigate a larger number of clinical specimens later to develop biomarkers according to the state of infection with MTB such as LTBI and active TB, as well as after treatment.

High sensitivity and specificity of a 5-analyte protein and microRNA biosignature for identification of active tuberculosis

Objectives

Non‐sputum‐based tests to accurately identify active tuberculosis (TB) disease and monitor response to therapy are urgently needed. This study examined the biomarker capacity of a panel of plasma proteins alone, and in conjunction with a previously identified miRNA signature, to identify active TB disease.

Methods

The expression of nine proteins (IP‐10, MCP‐1, sTNFR1, RANTES, VEGF, IL‐6, IL‐10, TNF and Eotaxin) was measured in the plasma of 100 control subjects and 100 TB patients, at diagnosis (treatment naïve) and over the course of treatment (1‐, 2‐ and 6‐month intervals). The diagnostic performance of the nine proteins alone, and with the miRNA, was assessed.

Results

Six proteins were significantly up‐regulated in the plasma of TB patients at diagnosis compared to controls. Receiver operator characteristic curve analysis demonstrated that IP‐10 with an AUC = 0.874, sensitivity of 75% and specificity of 87% was the best single biomarker candidate to distinguish TB patients from controls. IP‐10 and IL‐6 levels fell significantly within one month of commencing treatment and may have potential as indicators of a positive response to therapy. The combined protein and miRNA panel gave an AUC of 1.00. A smaller panel of only five analytes (IP‐10, miR‐29a, miR‐146a, miR‐99b and miR‐221) showed an AUC = 0.995, sensitivity of 96% and specificity of 97%.

Conclusions

A novel combination of miRNA and proteins significantly improves the sensitivity and specificity as a biosignature over single biomarker candidates and may be useful for the development of a non‐sputum test to aid the diagnosis of active TB disease.

Cytokine Biosignature of Active and Latent Mycobacterium Tuberculosis Infection in Children

None of the currently used diagnostic tools are efficient enough in diagnosing Mycobacterium tuberculosis (M.tb) infection in children. The study was aimed to identify cytokine biosignatures characterizing active and latent tuberculosis (TB) in children. Using a multiplex bead-based technology, we analyzed the levels of 53 Th17-related cytokines and inflammatory mediators in sera from 216 BCG-vaccinated children diagnosed with active TB (TB) or latent TB (LTBI) as well as uninfected controls (HC). Children with active TB, compared to HC children, showed reduced serum levels of IL-17A, MMP-2, OPN, PTX-3, and markedly elevated concentrations of APRIL/TNFSF13. IL-21, sCD40L, MMP-2, and IL-8 were significantly differentially expressed in the comparisons between groups: (1) HC versus TB and LTBI (jointly), and (2) TB versus LTBI. The panel consisting of APRIL/TNFSF13, sCD30/TNFRSF8, IFN-α2, IFN-γ, IL-2, sIL-6Rα, IL-8, IL-11, IL-29/IFN-λ1, LIGHT/TNFSF14, MMP-1, MMP-2, MMP-3, osteocalcin, osteopontin, TSLP, and TWEAK/TNFSF12 possessed a discriminatory potential for the differentiation between TB and LTBI children. Serum-based host biosignatures carry the potential to aid the diagnosis of childhood M.tb infections. The proposed panels of markers allow distinguishing not only children infected with M.tb from uninfected individuals but also children with active TB from those with latent TB.

Combination of prealbumin and tuberculosis-specific antigen/phytohemagglutinin ratio for discriminating active tuberculosis from latent tuberculosis infection

BACKGROUND

Given that there is no rapid and effective method for distinguishing active tuberculosis (ATB) from latent tuberculosis infection (LTBI), the discrimination between these two statuses remains challenging. This study sought to investigate the value of nutritional indexes and tuberculosis-specific antigen/phytohemagglutinin ratio (TBAg/PHA ratio) for distinguishing ATB from LTBI.

METHODS

Participants were consecutively recruited based on positive T-SPOT.TB results between January 2018 and January 2020. ATB was diagnosed by positive mycobacterial culture and/or positive GeneXpert MTB/RIF, with clinical symptoms and radiological characteristics suggestive of ATB. Individuals with positive T-SPOT.TB but without the evidence of ATB were defined as LTBI. Patients younger than 17 years and undergoing anti-TB treatment were excluded.

RESULTS

A total of 709 (312 ATB and 397 LTBI) and another 309 (120 ATB and 189 LTBI) subjects were respectively recruited from Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort). The level of prealbumin was significantly lower in ATB than in LTBI. With a cut-off value of 139 mg/L, the sensitivity and specificity of prealbumin in distinguishing ATB from LTBI were 50.96% (45.41%-56.51%) and 91.69% (88.97%-94.40%). Meanwhile, TBAg/PHA ratio was found statistically higher in ATB compared with LTBI. If using the threshold of 0.29, the sensitivity and specificity of TBAg/PHA ratio were 65.71% (60.44%-70.97%) and 90.93% (88.11%-93.76%), respectively. Moreover, the combination of prealbumin and TBAg/PHA ratio (obtaining by diagnostic model) yielded better specificity (90.18%, [87.25%-93.10%]) and sensitivity (87.18%, [83.47%-90.89%]), while the clinical utility index (CUI) positive and CUI negative were respectively 0.76 and 0.81. After anti-TB treatment, TBAg/PHA ratio was declined while the level of prealbumin was restored (Wilcoxon test, P < 0.001). Furthermore, the performance of diagnostic model obtained in Qiaokou cohort was confirmed in Caidian cohort.

CONCLUSIONS

The diagnostic model based on combination of prealbumin and TBAg/PHA ratio is a rapid and accurate tool for discriminating ATB from LTBI.

Cytokine and Chemokine mRNA Expressions after Mycobacterium tuberculosis-Specific Antigen Stimulation in Whole Blood from Hemodialysis Patients with Latent Tuberculosis Infection

There have been few reports on the kinetics of hemodialyzed (HD) patients’ immune responses in latent tuberculosis infection (LTBI). Therefore, in the present study, messenger ribonucleic acid (mRNA) expression levels of nine immune markers were analyzed to discriminate between HD patients with LTBI and healthy individuals. Nine cytokines and chemokines were screened through relative mRNA expression levels in whole blood samples after stimulation with Mycobacterium tuberculosis (MTB)-specific antigens from HD patients with LTBI (HD/LTBI), HD patients without LTBI, and healthy individuals, and results were compared with the QuantiFERON-TB Gold In-Tube (QFT-GIT) test. We confirmed that the C-C motif chemokine 11 (CCL11) mRNA expression level of the HD/LTBI group was significantly higher than the other two groups. Especially, the CCL11 mRNA expression level of the >0.7 IU/mL group in the QFT-GIT test was significantly higher than the <0.2 IU/mL group in the QFT-GIT test and the 0.2–0.7 IU/mL group in the QFT-GIT test (p = 0.0043). The present study reveals that the relative mRNA expression of CCL11 was statistically different in LTBI based on the current cut-off value (i.e., ≥0.35 IU/mL) and in the >0.7 IU/mL group. These results suggest that CCL11 mRNA expression might be an alternative biomarker for LTBI diagnosis in HD patients.

Elevated levels of inflammatory plasma biomarkers are associated with risk of HIV infection

BACKGROUND

To determine if individuals, from HIV-1 serodiscordant couple cohorts from Rwanda and Zambia, who become HIV-positive have a distinct inflammatory biomarker profile compared to individuals who remain HIV-negative, we compared levels of biomarkers in plasma of HIV-negative individuals who either seroconverted (pre-infection) and became HIV-positive or remained HIV-negative (uninfected).

RESULTS

We observed that individuals in the combined cohort, as well as those in the individual country cohorts, who later became HIV-1 infected had significantly higher baseline levels of multiple inflammatory cytokines/chemokines compared to individuals who remained HIV-negative. Genital inflammation/ulceration or schistosome infections were not associated with this elevated profile. Defined levels of ITAC and IL-7 were significant predictors of later HIV acquisition in ROC predictive analyses, whereas the classical Th1 and Th2 inflammatory cytokines such as IL-12 and interferon-γ or IL-4, IL-5 and Il-13 were not.

CONCLUSIONS

Overall, the data show a significant association between increased plasma biomarkers linked to inflammation and immune activation and HIV acquisition and suggests that pre-existing conditions that increase systemic biomarkers represent a factor for increased risk of HIV infection.

Evaluation of Interleukin-2 to Detect Active and Latent Tuberculosis among Household Contacts of Pulmonary Tuberculosis Cases

Background: The interferon-gamma release assays (IGRAs) are the most important diagnostic approach to Mycobacterium tuberculosis infection diagnosis. However, they cannot discriminate between latent tuberculosis infection (LTBI) and active tuberculosis (TB). Some recent studies suggested that interleukin-2 (IL-2) response to M. tuberculosis could be utilized as a potential biomarker to discriminate active disease from LTBI. Objectives: The current study aimed at evaluating the potential role of IL-2 to detect both active TB and LTBI among household contacts of patients with pulmonary TB in two TB-endemic regions of Iran. Methods: A total of 650 household contacts of patients with TB were invited to participate in the current study. All subjects were diagnosed on extensive clinical evaluation of active TB and LTBI based on clinical manifestations and laboratory findings. The IGRA test was performed using QuantiFERON®-TB Gold Plus. The serum level of IL-2 was measured using the ELISA Development Kit. Results: A total of 237 household contacts entered the final analysis, including 132 patients with LTBI and three with active TB. In addition, 14 subjects were included as TB controls and 102 as TB-uninfected controls. The serum level of IL-2 was significantly higher in active TB and LTBI patients than TB-uninfected controls. The ROC curve was plotted between active TB and LTBI, revealing that the cutoff point of 25.5 pg/mL identifies the active form with 88.24% sensitivity and 36.36% specificity. Conclusions: The current study indicated that the IL-2 assay could not discriminate between active TB and LTBI with acceptable sensitivity.

Active and prospective latent tuberculosis are associated with different metabolomic profiles: clinical potential for the identification of rapid and non-invasive biomarkers

Although 23% of world population is infected with Mycobacterium tuberculosis (M. tb), only 5-10% manifest the disease. Individuals surely exposed to M. tb that remain asymptomatic are considered potential latent TB (LTB) cases. Such asymptomatic M. tb.-exposed individuals represent a reservoir for active TB cases. Although accurate discrimination and early treatment of patients with active TB and asymptomatic M. tb.-exposed individuals are necessary to control TB, identifying those individuals at risk of developing active TB still remains a tremendous clinical challenge. This study aimed to characterize the differences in the serum metabolic profile specifically associated to active TB infected individuals or to asymptomatic M. tb.-exposed population. Interestingly, significant changes in a specific set of metabolites were shared when comparing either asymptomatic house-hold contacts of active TB patients (HHC-TB) or active TB patients (A-TB) to clinically healthy controls (HC). Furthermore, this analysis revealed statistically significant lower serum levels of aminoacids such as alanine, lysine, glutamate and glutamine, and citrate and choline in patients with A-TB, when compared to HHC-TB. The predictive ability of these metabolic changes was also evaluated. Although further validation in independent cohorts and comparison with other pulmonary infectious diseases will be necessary to assess the clinical potential, this analysis enabled the discrimination between HHC-TB and A-TB patients with an AUC value of 0.904 (confidence interval 0.81-1.00, p-value < 0.0001). Overall, the strategy described in this work could provide a sensitive, specific, and minimally invasive method that could eventually be translated into a clinical tool for TB control.

Is interleukin-2 an optimal marker for diagnosing tuberculosis infection? A systematic review and meta-analysis

BACKGROUND

Latent tuberculosis infection (LTBI) is a huge reservoir for the deadlier TB disease. Accurate identification of LTBI is a key strategy to eliminate TB. Therefore, a systematic review and meta-analysis approach was used to assess diagnostic potential of IL-2 for LTBI.

METHODS

PubMed, Web of Science, the Cochrane Library and Embase were searched. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), area under the summary receiver operating characteristic curve (AUROC) and hierarchical summary receiver operating characteristic curve (HSROC) were estimated by bivariate and HSROC models.

RESULTS

Twenty-seven studies including 1404 participants and 1986 samples met the inclusion criteria. The pooled sensitivity, specificity, PLR, NLR, DOR and AUROC of IL-2 were separately as 87%, 98%, 34.78, 0.14, 256.41 and 0.98, indicating a very powerful differentiating ability of IL-2 for LTBI from non-TB controls. For differentiating ATB from LTBI, the pooled sensitivity, specificity, PLR, NLR, DOR and AUROC of IL-2 were 83%, 76%, 3.41, 0.22, 15.47 and 0.87, respectively, suggesting a good differentiating ability of IL-2.

CONCLUSIONS

These findings showed that IL-2 is a powerful marker for differentiating LTBI from non-TB controls and a good marker for differentiating ATB from LTBI individuals.

Immune profiling enables stratification of patients with active TB disease or M. tuberculosis infection

Background

Tuberculosis (TB) is caused by Mycobacterium tuberculosis (Mtb) infection and is a major public health problem. Clinical challenges include the lack of a blood-based test for active disease. Current blood-based tests, such as QuantiFERON (QFT) do not distinguish active TB disease from asymptomatic Mtb infection.

Methods

We hypothesized that TruCulture, an immunomonitoring method for whole-blood stimulation, could discriminate active disease from latent Mtb infection (LTBI). We stimulated whole blood from patients with active TB and compared with LTBI donors. Mtb-specific antigens and live bacillus Calmette-Guérin (BCG) were used as stimuli, with direct comparison to QFT. Protein analyses were performed using conventional and digital enzyme-linked immunosorbent assay (ELISA), as well as Luminex.

Results

TruCulture showed discrimination of active TB cases from LTBI (P < .0001, AUC = .81) compared with QFT (P = .45, AUC = .56), based on an interferon γ (IFNγ) readout after Mtb antigen (Ag) stimulation. This result was replicated in an independent cohort (AUC = .89). In exploratory analyses, TB stratification could be further improved by the Mtb antigen to BCG IFNγ ratio (P < .0001, AUC = .91). Finally, the combination of digital ELISA and transcriptional analysis showed that LTBI donors with high IFNγ clustered with patients with TB, suggesting the possibility to identify subclinical disease.

Conclusions

TruCulture offers a next-generation solution for whole-blood stimulation and immunomonitoring with the possibility to discriminate active and latent infection.

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

OBJECTIVES

With 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.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

PubMed, Cochrane Library, Clinical Key and EMBASE databases were searched on 31 December 2019.

ELIGIBILITY CRITERIA

We 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 SYNTHESIS

Two 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.

RESULTS

Of 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).

CONCLUSION

Cytokines, such as IL-2, IFN-γ and VEGF, can be utilised as promising biomarkers to distinguish active tuberculosis from LTBI.

PROSPERO REGISTRATION NUMBER

CRD42020170725.

Mycobacterium tuberculosis-specific cytokine biomarkers to differentiate active TB and LTBI: A systematic review

OBJECTIVES

New tests are needed to overcome the limitations of existing immunodiagnostic tests for tuberculosis (TB) infection, including their inability to differentiate between active TB and latent TB infection (LTBI). This review aimed to identify the most promising cytokine biomarkers for use as stage-specific markers of TB infection.

METHODS

A systematic review was done using electronic databases to identify studies that have investigated Mycobacterium tuberculosis (MTB)-specific cytokine responses as diagnostic tools to differentiate between LTBI and active TB.

RESULTS

The 56 studies included in this systematic review measured the MTB-specific responses of 100 cytokines, the most frequently studied of which were IFN-γ, IL-2, TNF-α, IP-10, IL-10 and IL-13. Ten studies assessed combinations of cytokines, most commonly IL-2 and IFN-γ. For most cytokines, findings were heterogenous between studies. The variation in results likely relates to differences in the study design and laboratory methods, as well as participant and environmental factors.

CONCLUSIONS

Although several cytokines show promise as stage-specific markers of TB infection, this review highlights the need for further well-designed studies, in both adult and paediatric populations, to establish which cytokine(s) will be of most use in a new generation of immunodiagnostic tests.

The meta-analysis for ideal cytokines to distinguish the latent and active TB infection

Background

One forth whole-world population is infected with Mycobacterium tuberculosis (Mtb), but 90% of them are asymptotic latent infection without any symptoms but positive result in IFN-γ release assay. There is lack of ideal strategy to distinguish active tuberculosis (TB) and latent tuberculosis infection (LTBI). Some scientist had focused on a set of cytokines as biomarkers besides interferon- gamma (IFN-γ) to distinguish active TB and LTBI, but with considerable variance of results. This meta-analysis aimed to evaluate the overall discriminative ability of potential immune molecules to distinguish active TB and LTBI.

Methods

PubMed, the Cochrane Library, and Web of Science databases were searched to identify studies assessing diagnostic roles of cytokines for distinguishing active TB and LTBI published up to August 2018. The quality of enrolled studies was assessed using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The pooled diagnostic sensitivity and specificity of each cytokine was calculated by using Meta-DiSc software. Area under the summary receiver operating characteristic curve (AUC) was used to summarize the overall diagnostic performance of each biomarker.

Results

Fourteen studies with 982 subjects met the inclusion criteria, including 526 active TB and 456 LTBI patients. Pooled sensitivity, specificity and AUC for discriminating between active TB and LTBI were analyzed for IL-2 (0.87, 0.61 and 0.9093), IP-10 (0.77, 0.73 and 0.8609), IL-5 (0.64, 0.75 and 0.8533), IL-13 (0.75, 0.71 and 0.8491), IFN-γ (0.67, 0.75 and 0.8031), IL-10 (0.68, 0.74 and 0.7957) and TNF-α (0.67, 0.64 and 0.7783). The heterogeneous subgroup analysis showed that cytokine detection assays, TB incidence, and stimulator with Mtb antigens are main influence factors for their diagnostic performance.

Conclusions

The meta-analysis showed cytokine production could assist the distinction between active TB and LTBI, IL-2 with the highest overall accuracy. No single biomarker is likely to show sufficiently diagnostic performance due to limited sensitivity and specificity. Further prospective studies are needed to identify the optimal combination of biomarkers to enhanced diagnostic capacity in clinical practice.

Identification of Mycobacterium tuberculosis Peptides in Serum Extracellular Vesicles from Persons with Latent Tuberculosis Infection

Identification of biomarkers for latent Mycobacterium tuberculosis infection and risk of progression to tuberculosis (TB) disease are needed to better identify individuals to target for preventive therapy, predict disease risk, and potentially predict preventive therapy efficacy. Our group developed multiple reaction monitoring mass spectrometry (MRM-MS) assays that detected M. tuberculosis peptides in serum extracellular vesicles from TB patients. We subsequently optimized this MRM-MS assay to selectively identify 40 M. tuberculosis peptides from 19 proteins that most commonly copurify with serum vesicles of patients with TB. Here, we used this technology to evaluate if M. tuberculosis peptides can also be detected in individuals with latent TB infection (LTBI). Serum extracellular vesicles from 74 individuals presumed to have latent M. tuberculosis infection (LTBI) based on close contact with a household member with TB or a recent tuberculin skin test (TST) conversion were included in this study. Twenty-nine samples from individuals with no evidence of TB infection by TST and no known exposure to TB were used as controls to establish a threshold to account for nonspecific/background signal. We identified at least one of the 40 M. tuberculosis peptides in 70 (95%) individuals with LTBI. A single peptide from the glutamine synthetase (GlnA1) enzyme was identified in 61/74 (82%) individuals with LTBI, suggesting peptides from M. tuberculosis proteins involved in nitrogen metabolism might be candidates for pathogen-specific biomarkers for detection of LTBI. The detection of M. tuberculosis peptides in serum extracellular vesicles from persons with LTBI represents a potential advance in the diagnosis of LTBI.

Gaps in Study Design for Immune Parameter Research for Latent Tuberculosis Infection: A Systematic Review

Background

Immune parameters (IP) have been extensively studied to distinguish between latent tuberculosis (LTBI) and active tuberculosis (TB).

Objective

To determine the IP associated with LTBI, compared to active TB and individuals not infected by M. tuberculosis published in literature.

Methods

We conducted a systematic search using Google Scholar and PubMed databases, combining the MeSH terms latent tuberculosis, Mycobacterium tuberculosis, cytokines, and biological markers, with the free terms, biomarkers and cytokines. Spanish, English, and Portuguese articles comparing the concentration of IP associated with LTBI, either in plasma/serum or in vitro, in adults and nonimmunocompromised versus individuals with TB or without M. tuberculosis infection between 2006 July and 2018 July were included. Two blinded reviewers carried out the searches, read the abstracts, and selected the articles for analysis. Participants' information, diagnostic criteria, IP, detection methods, and biases were collected.

Results

We analyzed 36 articles (of 637 abstracts) with 93 different biomarkers in different samples. We found 24 parameters that were increased only in active TB (TGF-α, CSF3, CSF2, CCL1 [I-309], IL-7, TGF-β1, CCL3 [MIP-1α], sIL-2R, TNF-β, CCL7 [MCP-3], IFN-α, fractalkine, I-TAG, CCL8 [MCP-2], CCL21 [6Ckine], PDGF, IL-22, VEGF-A, LXA4, PGE2, PGF2α, sCD163, sCD14, and 15-Epi-LXA4), five were elevated in LTBI (IL-5, IL-17F, IL-1, CCL20 [MIP-3α], and ICAM-1), and two substances were increased among uninfected individuals (IL-23 and basic FGF). We found high heterogeneity between studies including failure to account for the time/illness of the individuals studied; varied samples and protocols; different clinical classification of TB; different laboratory methods for IP detection, which in turn leads to variable units of measurement and assay sensitivities; and selection bias regarding TST and booster effect. None of the studies adjusted the analysis for the effect of ethnicity.

Conclusions

It is mandatory to harmonize the study of immune parameters for LTBI diagnosis. This systematic review is registered with PROSPERO CRD42017073289.

A study on the relationship between air pollution and pulmonary tuberculosis based on the general additive model in Wulumuqi, China

OBJECTIVE

This study aimed to explore the impact of atmospheric pollutants on the incidence of tuberculosis (TB), and provide new ideas for the prevention and control of TB in the future.

METHODS

It explored the relationship between air pollutants and meteorological factors, as well as between air pollutants and heating through Spearman correlation analysis and rank sum test. Additionally, it analyzed the relationship between air pollutants and TB incidence using the general additive model. Statistical analysis results at the p<0.05 level were considered significant.

RESULTS

Three months after exposure to air pollutants (PM_2.5, SO₂, NO₂, and CO) TB incidence increased. However, TB incidence increased 9 months after exposure to PM₁₀. The single pollutant model showed when concentrations of PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃ increased by 1μg/m³ (or 1mg/m³), the number of TB cases increased by 0.09%, 0.08%, 0.58%, 0.42%, 6.9%, and 0.57%, respectively. The optimal multi-pollutant model was a two-factor model (PM₁₀+NO₂).

CONCLUSION

Air pollutants including PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃ increased the risk of TB. Few studies have been conducted in this area of research, especially regarding the mechanism. The results of this study should contribute to the understanding of TB incidence and prompt additional research.

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

OBJECTIVES

A recently released new QuantiFERON (QFT) product, QFT TB Gold plus (QFT-plus), is optimized for both CD4 and CD8 responses and reported to have higher sensitivity compared to the former QFT-3 G. Previously, using supernatants of QFT-3 G, we and others have demonstrated that cytokines other than IFN-γ may be useful in diagnosing tuberculosis. The present study aimed to identify cytokines that are useful for accurately diagnosing active tuberculosis by using QFT-plus and compared the data to those with QFT-3 G.

METHODS

Eighty-three active tuberculosis patients and 70 healthy control subjects who were examined by QFT at Tokyo National Hospital from June 2017 to July 2018 were enrolled. QFT-3 G and QFT-plus were performed according to the manufacturer's instructions. At the same time, blood cell culture supernatants were collected and assayed for their cytokine levels using R&D Systems Luminex Assay and MAGPIX System. The levels of cytokines were compared between different antigen-containing tubes (3 G Ag, TB1 and TB2 tubes), as well as between the patients and the control subjects. ROC curves were drawn, and the AUCs were calculated.

RESULTS

Five cytokines, i.e., IL-2, IL-6, IL-8, IP-10 and MIP-1β, produced by human blood cells in three independent tubes containing different tuberculosis antigens were higher in the 3 G Ag tube compared to both the TB1 and TB2 tubes. Further, when the TB1 and TB2 tubes were compared, TB2 showed greater production of only PDGF-BB, and less production of IL-6 and TNF-α. For diagnosing active tuberculosis, the levels of IP-10 were superior to the level of IFN-γ based on showing a larger AUC for ROC curves in our present study setting. Finally, the levels of IFN-γ, IL-1RA, IL-2, IP-10, MCP-1 and MIP-1β were distinctly different between the active tuberculosis patients and healthy controls.

CONCLUSIONS

In summary, there was no cytokine that was higher in the tubes of QFT-plus compared to the tube of QFT-3 G, suggesting inferiority of QFT-plus antigens to 3 G Ag in terms of elicitation of cytokine production. Our results also suggest the usefulness of cytokines that showed a significant difference between the active tuberculosis patients and the healthy controls-namely, IFN-γ, IL-1RA, IL-2, IP-10, MCP-1 and MIP-1β-for diagnosing tuberculosis, but the roles of these cytokines in the pathogenesis of tuberculosis need to be elucidated (UMIN000035253).

Immune Biomarkers for Diagnosis and Treatment Monitoring of Tuberculosis: Current Developments and Future Prospects

Tuberculosis (TB) treatment monitoring is paramount to clinical decision-making and the host biomarkers appears to play a significant role. The currently available diagnostic technology for TB detection is inadequate. Although GeneXpert detects total DNA present in the sample regardless live or dead bacilli present in clinical samples, all the commercial tests available thus far have low sensitivity. Humoral responses against Mycobacterium tuberculosis (Mtb) antigens are generally low, which precludes the use of serological tests for TB diagnosis, prognosis, and treatment monitoring. Mtb-specific CD4⁺ T cells correlate with Mtb antigen/bacilli burden and hence might serve as good biomarkers for monitoring treatment progress. Omics-based techniques are capable of providing a more holistic picture for disease mechanisms and are more accurate in predicting TB disease outcomes. The current review aims to discuss some of the recent advances on TB biomarkers, particularly host biomarkers that have the potential to diagnose and differentiate active TB and LTBI as well as their use in disease prognosis and treatment monitoring.

Biomarkers for Detecting Resilience against Mycobacterial Disease in Animals

Paratuberculosis and bovine tuberculosis are two mycobacterial diseases of ruminants which have a considerable impact on livestock health, welfare, and production. These are chronic "iceberg" diseases which take years to manifest and in which many subclinical cases remain undetected. Suggested biomarkers to detect infected or diseased animals are numerous and include cytokines, peptides, and expression of specific genes; however, these do not provide a strong correlation to disease. Despite these advances, disease detection still relies heavily on dated methods such as detection of pathogen shedding, skin tests, or serology. Here we review the evidence for suitable biomarkers and their mechanisms of action, with a focus on identifying animals that are resilient to disease. A better understanding of these factors will help establish new strategies to control the spread of these diseases.

IL-18/IL-37/IP-10 signalling complex as a potential biomarker for discriminating active and latent TB

Background

Currently, there are serious limitations in the direct diagnosis of active tuberculosis (ATB). We evaluated the levels of the IL-18/IL-37/IP-10 signalling complex proteins in Mycobacterium tuberculosis (M.tb)-specific antigen-stimulated QuantiFERON® Gold In-Tube (QFT) cultures and in serum samples from ATB patients, healthy individuals with latent M.tb infection (LTBI) and healthy controls (HC) to examine whether combined analyses of these proteins were useful in the differentiation of M.tb states.

Methods

The concentrations of IL-18, IL-18BP, IFN-γ, IL-37 and IP-10 in the serum and QFT supernatants were measured using specific enzyme-linked immunosorbent assay (ELISA) kits. Free IL-18 levels were calculated using the law of mass action.

Results

Increased concentrations of total and free IL-18, IL-18BP, IFN-γ and IP-10 in the sera of ATB patients were detected. These increases were not counterbalanced by the overproduction of IL-37. Complex co-expression of serum IL-18BP and IL-37, IP-10 and IFN-γ was identified as the highest discriminative biomarker set for the diagnosis of ATB.

Conclusions

Our results suggest that the IL-18 signalling complex might be exploited by M. tuberculosis to expand the clinical manifestations of pulmonary TB. Therefore, direct analysis of the serum components of the IL-18/IL-37 signalling complex and IP-10 may be applicable in designing novel diagnostic tests for ATB.

Biomarkers of cell-mediated immunity to bovine tuberculosis

Whole blood based assays, particularly interferon gamma (IFN-γ) release assays (IGRAs), are used for the diagnosis of both bovine and human tuberculosis (TB). The aim of the current study was to evaluate a panel of cytokines and chemokines for potential use as diagnostic readouts indicative of Mycobacterium bovis (M. bovis) infection in cattle. A gene expression assay was used to determine the kinetics of the response to M. bovis purified protein derivative and a fusion protein consisting of ESAT-6, CFP10, and Rv3615c upon aerosol infection with ∼10⁴ cfu of M. bovis. The panel of biomarkers included: IFN-γ, CXCL9, CXCL10, CCL2, CCL3, TNF-α, IL-1α, IL-1β, IL-1Ra, IL-22, IL-21 and IL-13. Protein levels of IFN-γ, CXCL9, and CXCL10 were determined by ELISA. Findings suggest that CXCL9, CXCL10, IL-21, IL-13, and several acute phase cytokines may be worth pursuing as diagnostic biomarkers of M. bovis infection in cattle.

Diagnostic accuracy of interferon (IFN)-γ inducible protein 10 (IP-10) as a biomarker for the discrimination of active and latent tuberculosis

To assess the potency of Interferon (IFN)-γ inducible protein 10 (IP-10) stimulated by recombinant PE35 and PPE68 as a biomarker in differentiating between active and latent tuberculosis. Patients with active pulmonary TB (PTB) (n = 30), latent TB infection (LTBI) (n = 29), and BCG-vaccinated healthy controls (HCs) (n = 30) were enrolled and blood samples were taken from them. The diagnostic performance of IP-10 was evaluated by the Receiver operator characteristic (ROC) curve and the area under the curve (AUC) and their 95% confidence intervals (CI) were calculated. The median IP-10 concentrations following stimulation with recombinant PE35 and PPE68 were significantly higher in TB-infected group (both PTB and LTBI) compared with HCs (P < 0.05). It was also significantly higher in PTB patients compared with individuals with LTBI (P < 0.05). The discriminatory performance of IP-10 following stimulation with recombinant PE35 and PPE68 (assessed by AUC) between TB patients and HCs were similar (AUC: 0.79 [95% CI 0.68-0.89] and 0.79 [95% CI 0.69-0.89], respectively). AUCs of IP-10 following stimulation with recombinant PE35 and PPE68 for distinguishing between PTB and LTBI groups were 0.63 (95% CI 0.47-0.79) and 0.61 (0.45-0.77), respectively. Under the selected cut-off values, the sensitivity and specificity of IP-10 for distinguishing of TB-infected and HCs after stimulation with recombinant PE35 was 74.5% and 73%, respectively and after stimulation with recombinant PPE68 were 76.5% and 63%, respectively. Moreover, the sensitivity and specificity of IP-10 for differentiating of PTB and LTBI following stimulation with recombinant PE35 and PPE68 were 770 pg/ml (sensitivity: 63%; specificity: 62%) and 502 pg/ml (sensitivity: 80%; specificity: 52%), respectively. IP-10 stimulated by recombinant PE35 and PPE68 is a promising biomarker for TB diagnosis. However, it doesn't have desirable sensitivity and specificity in distinguishing between PTB and LTBI.

A Model Based on the Combination of IFN-γ, IP-10, Ferritin and 25-Hydroxyvitamin D for Discriminating Latent From Active Tuberculosis in Children

In recent years, pediatric research on tuberculosis (TB) has focused on addressing new biomarkers with the potential to be used as immunological non-sputum-based methods for the diagnosis of TB in children. The aim of this study was to characterize a set of cytokines and a series of individual factors (ferritin, 25-hydroxyvitamin D [25(OH)D], parasite infections, and nutritional status) to assess different patterns for discriminating between active TB and latent TB infection (LTBI) in children. The levels of 13 cytokines in QuantiFERON-TB Gold In-Tube (QFT-GIT) supernatants were analyzed in 166 children: 74 with active TB, 37 with LTBI, and 55 uninfected controls. All cytokines were quantified using Luminex or ELISA. Ferritin and 25(OH)D were also evaluated using CLIA, and Toxocara canis Ig-G antibodies were detected with a commercial ELISA kit. The combination of IP-10, IFN-γ, ferritin, and 25(OH)D achieved the best diagnostic performance to discriminate between active TB and LTBI cases in children in relation to the area under receiver operating characteristic (ROC) curve 0.955 (confidence interval 95%: 0.91–1.00), achieving optimal sensitivity and specificity for the development of a new test (93.2 and 90.0%, respectively). Children with TB showed higher ferritin levels and an inverse correlation between 25(OH)D and IFN-γ levels. The model proposed includes a combination of biomarkers for discriminating between active TB and LTBI in children to improve the accuracy of TB diagnosis in children. This combination of biomarkers might have potential for identifying the onset of primary TB in children.

Diagnostic accuracy of interferon-gamma-induced protein 10 for differentiating active tuberculosis from latent tuberculosis: A meta-analysis

Tuberculin skin test and interferon-gamma release assay are not good at differentiating active tuberculosis from latent tuberculosis. Interferon-gamma-induced protein 10 (IP-10) has been widely used to detect tuberculosis infection. However, its values of discriminating active and latent tuberculosis is unknown. To estimate the diagnostic potential of IP-10 for differentiating active tuberculosis from latent tuberculosis, we searched PubMed, Web of Science, Embase, the Cochrane Library, CNKI, Wanfang, VIP and CBM databases. Eleven studies, accounting for 706 participants (853 samples), were included. We used a bivariate diagnostic random-effects model to conduct the primary data. The overall pooled sensitivity, specificity, negative likelihood rate, positive likelihood rate, diagnostic odds ratio and area under the summary receiver operating characteristic curve were 0.72 (95% CI: 0.68-0.76), 0.83 (95% CI: 0.79-0.87), 0.32 (95% CI: 0.22-0.46), 4.63 (95% CI: 2.79-7.69), 17.86 (95% CI: 2.89-38.49) and 0.8638, respectively. This study shows that IP-10 is a potential biomarker for differentiating active tuberculosis from latent tuberculosis.

Prospective evaluation of host biomarkers other than interferon gamma in QuantiFERON Plus supernatants as candidates for the diagnosis of tuberculosis in symptomatic individuals

BACKGROUND

There is an urgent need for new tools for the diagnosis of TB. We evaluated the usefulness recently described host biomarkers in supernatants from the newest generation of the QuantiFERON test (QuantiFERON Plus) as tools for the diagnosis of active TB.

METHODS

We recruited individuals presenting at primary health care clinics in Cape Town, South Africa with symptoms requiring investigation for TB disease, prior to the establishment of a clinical diagnosis. Participants were later classified as TB or other respiratory diseases (ORD) based on the results of clinical and laboratory tests. Using a multiplex platform, we evaluated the concentrations of 37 host biomarkers in QuantiFERON Plus supernatants from study participants as tools for the diagnosis of TB.

RESULTS

Out of 120 study participants, 35(29.2%) were diagnosed with active TB, 69(57.5%) with ORD whereas 16(13.3%) were excluded. 14(11.6%) of the study participants were HIV infected. Although individual host markers showed potential as diagnostic candidates, the main finding of the study was the identification of a six-marker biosignature in unstimulated supernatants (Apo-ACIII, CXCL1, CXCL9, CCL8, CCL-1, CD56) which diagnosed TB with sensitivity and specificity of 73.9%(95% CI; 51.6-87.8) and 87.6%(95% CI; 77.2-94.5), respectively, after leave-one-out cross validation. Combinations between TB-antigen specific biomarkers also showed potential (sensitivity of 77.3% and specificity of 69.2%, respectively), with multiple biomarkers being significantly different between TB patients, Quantiferon Plus Positive and Quantiferon Plus negative individuals with ORD, regardless of HIV status.

CONCLUSIONS

Biomarkers detected in QuantiFERON Plus supernatants may contribute to adjunctive diagnosis of TB.

Levels of vitamin D-associated cytokines distinguish between active and latent tuberculosis following a tuberculosis outbreak

BACKGROUND

Vitamin D levels are associated with the extent of mycobactericidal activity. Interleukin (IL)-15 and IL-32 play roles in the vitamin D-mediated tuberculosis (TB) defense mechanism. Vitamin D induces IL-1β, which plays an important role in terms of resistance to TB. We evaluated whether the levels of vitamin D-related cytokines distinguished between those with active TB and latent TB infection (LTBI).

METHODS

In total, 50 TB-infected patients (25 with active TB and 25 with LTBI following a TB outbreak in a high school) were enrolled. Plasma 25-hydroxyvitamin D (25[OH]D), IL-15, IL-32, and IL-1β levels were measured via enzyme-linked immunosorbent assays. Mycobacterium tuberculosis-specific antigen-induced and unstimulated cytokine levels were measured in the supernatants of the QuantiFERON TB Gold-In-Tube (QFT-GIT) assay.

RESULTS

Plasma 25(OH)D and plasma IL-15 levels were lower in patients with active TB than in LTBI subjects (25(OH)D: 16.64 ng/mL vs. 21.6 ng/mL, P = 0.031; IL-15: 148.9 pg/mL vs. 189.8 pg/mL, P = 0.013). Plasma 25(OH)D levels correlated with the plasma levels of IL-15 and IL-1β in TB-infected patients. In addition, the plasma 25(OH)D levels correlated positively with the level of unstimulated IL-15 (IL-15nil) and negatively with that of TB antigen-stimulated IL-32 (IL-32TB) in QFT-GIT supernatants. Although the IL-15nil and IL-15TB levels were higher in LTBI subjects than patients with active TB, the IL-32nil and IL-32TB levels were higher in the latter patients. A combination of the IL-15nil and IL-32TB levels accurately predicted 91.3% of active TB patients and latent subjects, with an area under the curve of 0.964.

CONCLUSIONS

Our preliminary data showed that the levels of the vitamin D-related cytokines IL-15 and IL-32 differed between active TB patients and LTBI subjects. This result might be used as a basic data for developing biomarkers distinguishing between active TB and LTBI.

Current approaches toward identifying a correlate of immune protection from tuberculosis

INTRODUCTION

Mycobacterium tuberculosis kills more people than any other pathogen. Vaccination is the most cost-effective control measure for any infectious disease. Development of an effective vaccine against tuberculosis is hindered by the uncertain predictive value of preclinical animal models, incomplete understanding of protective immunity and lack of validated immune correlates of protection (COP).

AREAS COVERED

Here we review what is known about protective immunity against M.tb, the preclinical and clinical cohorts that can be utilized to identify COP, and COP that have been identified to date.

EXPERT COMMENTARY

The identification of COP would allow the rational design and development of vaccine candidates which can then be optimized and prioritized based on the induction of these immune responses. Once validated in field efficacy trials, such COP could potentially facilitate the development and licensure of vaccines, in combination with human efficacy data. The identification and validation of COP would represent a very significant advance in TB vaccine development. Every opportunity to collect samples and cohorts on which to cross-validate pre-existing COP and identify novel COP should be exploited. Furthermore, global cooperation and collaboration on such samples will ensure that the utility of such precious samples is fully exploited.