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

In vitro stimulation with nontuberculous mycobacteria induced a stronger cytokine response in leukocytes isolated from individuals with latent tuberculosis compared to those isolated from active tuberculosis or cystic fibrosis patients

Mycobacterium tuberculosis and opportunistic environmental non-tuberculous mycobacteria (NTM) can cause severe infection. Why latent tuberculosis infection advances to active disease, and why some individuals with cystic fibrosis (CF) develop pulmonary infections with NTM is still poorly understood. The aim of this study was to investigate the effector function of peripheral blood mononuclear cells (PBMC) from individuals with active or latent tuberculosis, individuals with CF with or without pulmonary NTM-infection and healthy controls, by measuring cytokine response to in vitro stimulation with different species of NTMs. The cytokine concentrations of IL-17A, IL-22, IL-23, IL-10, IL12p70 and IFN-γ were measured in PBMC-culture supernatants after stimulation with NTMs. PBMCs from individuals with latent tuberculosis infection showed strong IL-17A, IL-22, and IFN-γ responses compared to individuals with active tuberculosis or CF. IL-10 production was low in both tuberculosis groups compared to the CF groups and controls. This study suggests that IL-17A and IL-22 might be important to keep tuberculosis in a latent phase and that individuals with CF with an ongoing NTM infection seem to have a low cytokine response.

Differential diagnostic value of simultaneous detection of CD69 and HLA-DR on host T and NK cells in QFT-TB assay for identifying active tuberculosis

BACKGROUND

Interferon-gamma release assay (IGRA) for tuberculosis (TB) remains limited in its ability to discriminate between active TB (ATB) and latent TB infection (LTBI). Activation markers on host T and NK cells are currently considered to be promising markers in the diagnosis of ATB.

METHODS

This prospective observational study enrolled 213 participants and the participants were divided into ATB, LTBI, other lung-related diseases (ORD), and health control (HC) groups. CD69 and HLA-DR on T and NK cells were detected in QFT-TB assay, and a composite scoring system (TB-Flow) was created for the diagnosis of ATB.

RESULTS

The expression of activation markers (CD69 and HLA-DR) were significantly increased in ATB. HLA-DR on NK cells, CD69 on T cells, and QFT-TB in the differential diagnosis of ATB and HC were all of good diagnostic value (AUC>0.90). In addition, the TB-Flow greatly improved the efficiency of differential diagnosis between ATB and LTBI (AUC=0.90, 95%CI: 0.84-0.96), with sensitivity and specificity of 79.17 % (95%CI: 64.60%-89.04 %) and 88.68 % (95%CI: 76.28%-95.31 %).

CONCLUSIONS

CD69 and HLA-DR on host T and NK cells are promising markers in distinguishing different TB infection status. Our blood-based TB-Flow scoring system can distinguish ATB from LTBI with good diagnostic efficacy.

Overexpression of LAG-3: a potential indicator of low immune function in tuberculosis

Background

Tuberculosis (TB) persists as a global health challenge, with its treatment hampered by the side effects of long-term combination drug therapies and the growing issue of drug resistance. Therefore, the development of novel therapeutic strategies is critical. This study focuses on the role of immune checkpoint molecules (ICs) and functions of CD8+ T cells in the search for new potential targets against TB.

Methods

We conducted differential expression genes analysis and CD8+ T cell functional gene analysis on 92 TB samples and 61 healthy individual (HI) samples from TB database GSE83456, which contains data on 34,603 genes. The GSE54992 dataset was used to validated the findings. Additionally, a cluster analysis on single-cell data from primates infected with mycobacterium tuberculosis and those vaccinated with BCG was performed.

Results

The overexpression of LAG-3 gene was found as a potentially important characteristic of both pulmonary TB (PTB) and extrapulmonary TB (EPTB). Further correlation analysis showed that LAG-3 gene was correlated with GZMB, perforin, IL-2 and IL-12. A significant temporal and spatial variation in LAG-3 expression was observed in T cells and macrophages during TB infection and after BCG vaccination.

Conclusion

LAG-3 was overexpressed in TB samples. Targeting LAG-3 may represent a potential therapeutic target for tuberculosis.

Whole-blood culture-derived cytokine combinations for the diagnosis of tuberculosis

Introduction

The diagnosis of tuberculosis (TB) disease and TB infection (TBI) remains a challenge, and there is a need for non-invasive and blood-based methods to differentiate TB from conditions mimicking TB (CMTB), TBI, and healthy controls (HC). We aimed to determine whether combination of cytokines and established biomarkers could discriminate between 1) TB and CMTB 2) TB and TBI 3) TBI and HC.

Methods

We used hemoglobin, total white blood cell count, neutrophils, monocytes, C-reactive protein, and ten Meso Scale Discovery analyzed cytokines (interleukin (IL)-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, interferon (IFN)-ɣ, and tumor necrosis factor (TNF)-α) in TruCulture whole blood tubes stimulated by lipopolysaccharides (LPS), zymosan (ZYM), anti-CD3/28 (CD3), and unstimulated (Null) to develop three index tests able to differentiate TB from CMTB and TBI, and TBI from HC.

Results

In 52 persons with CMTB (n=9), TB (n=23), TBI (n=10), and HC (n=10), a combination of cytokines (LPS-IFN-ɣ, ZYM-IFN-ɣ, ZYM-TNF-α, ZYM-IL-1β, LPS-IL-4, and ZYM-IL-6) and neutrophil count could differentiate TB from CMTB with a sensitivity of 52.2% (95% CI: 30.9%-73.4%) and a specificity of 100 % (66.4%-100%). Null- IFN-ɣ, Null-IL-8, CD3-IL-6, CD3-IL-8, CD3-IL-13, and ZYM IL-1b discriminated TB from TBI with a sensitivity of 73.9% (56.5% - 91.3%) and a specificity of 100% (69.2-100). Cytokines and established biomarkers failed to differentiate TBI from HC with ≥ 98% specificity.

Discussion

Selected cytokines may serve as blood-based add-on tests to detect TB in a low-endemic setting, although these results need to be validated.

Therapeutic Drug Monitoring and Biomarkers; towards Better Dosing of Antimicrobial Therapy

Due to variability in pharmacokinetics and pharmacodynamics, clinical outcomes of antimicrobial drug therapy vary between patients. As such, personalised medication management, considering both pharmacokinetics and pharmacodynamics, is a growing concept of interest in the field of infectious diseases. Therapeutic drug monitoring is used to adjust and individualise drug regimens until predefined pharmacokinetic exposure targets are achieved. Minimum inhibitory concentration (drug susceptibility) is the best available pharmacodynamic parameter but is associated with many limitations. Identification of other pharmacodynamic parameters is necessary. Repurposing diagnostic biomarkers as pharmacodynamic parameters to evaluate treatment response is attractive. When combined with therapeutic drug monitoring, it could facilitate making more informed dosing decisions. We believe the approach has potential and justifies further research.

Computational Approaches for the Structure-Based Identification of Novel Inhibitors Targeting Nucleoid-Associated Proteins in Mycobacterium Tuberculosis

Implementation of computational tools in the identification of novel drug targets for Tuberculosis (TB) has been a promising area of research. TB has been a chronic infectious disease caused by Mycobacterium tuberculosis (Mtb) localized primarily on the lungs and it has been one of the most successful pathogen in the history of mankind. Extensively arising drug resistivity in TB has made it a global challenge and need for new drugs has become utmost important.The involvement of Nucleoid-Associated Proteins (NAPs) in maintaining the structure of the genomic material and regulating various cellular processes like transcription, DNA replication, repair and recombination makes significant, has opened a new arena to find the drugs targeting Mtb. The current study aims to identify potential inhibitors of NAPs through a computational approach. In the present work we worked on the eight NAPs of Mtb, namely, Lsr2, EspR, HupB, HNS, NapA, mIHF and NapM. The structural modelling and analysis of these NAPs were carried out. Moreover, molecular interaction were checked and binding energy was identified for 2500 FDA-approved drugs that were selected for antagonist analysis to choose novel inhibitors targeting NAPs of Mtb. Drugs including Amikacin, streptomycin, kanamycin, and isoniazid along with eight FDA-approved molecules that were found to be potential novel targets for these mycobacterial NAPs and have an impact on their functions. The potentiality of several anti-tubercular drugs as therapeutic agents identified through computational modelling and simulation unlocks a new gateway for accomplishing the goal to treat TB.

Association Studies of Serum Levels of TNF- α, IL-10, IFN-γ and CXCL 5 with Latent Tuberculosis Infection in Close Contacts

Purpose

Early recognition and treatment of latent tuberculosis infection(LTBI) is key to tuberculosis(TB) prevention. However, the emergence of LTBI is influenced by a combination of factors, of which the role of individual immune cytokines remains controversial. The aim of this study is to explore the influencing factors of LTBI and their effects with cytokines on LTBI.

Patients and Methods

Close contacts of tuberculosis in Urumqi City from 2021 to 2022 were selected for the study to conduct a field survey. It used logistic regression model to analyse the influencing factors of LTBI, principal component analysis to extract a composite indicators of cytokines, and structural equation modelling to explore the direct and indirect effects of cytokines and influencing factors on LTBI.

Results

LTBI infection rate of 33.3% among 288 TB close contacts. A multifactorial Logistic model showed that factors influencing LTBI included education, daily contact hours, eating animal liver, and drinking coffee (P<0.05); After controlling for confounding factors and extracting composite indicators of cytokines using principal component analysis, CXCL5 and IFN-γ is a protective factor for LTBI(OR=0.572, P=0.047), IL-10 and TNF-α is a risk factor for LTBI(OR=2.119, P=0.010); Structural equation modelling shows drinking coffee, eating animal liver, daily contact hours, and IL-10 and TNF-α had direct effects on LTBI and educations had indirect effects on LTBI(P<0.05).

Conclusion

IL-10 and TNF-α are involved in the immune response and are directly related to LTBI. By monitoring the cytokine levels of TB close contacts and paying attention to their dietary habits and exposure, we can detect and intervene in LTBI at an early stage and control their progression to TB.

Using immune clusters for classifying Mycobacterium tuberculosis infection

BACKGROUND

The differential diagnosis between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) is still a challenge worldwide.

METHODS

Immune indicators involved in innate, humoral, and cellular immune cells, as well as antigen-specific cells were simultaneously assessed in patients with ATB and LTBI.

RESULTS

Of 54 immune indicators, no indicator could distinguish ATB from LTBI, likely due to an obvious heterogeneity of immune indicators noticed in ATB patients. Cluster analysis of ATB patients identified three immune clusters with different severity. Cluster 1 (42.1 %) was a ''Treg/Th1/Tfh unbalance type" cluster, whereas cluster 2 (42.1 %) was an "effector type'' cluster, and cluster 3 was a ''inhibition type'' cluster (15.8 %) which showed the highest severity. A prediction model based on immune indicators was established and showed potential in classifying Mycobacterium tuberculosis infection.

CONCLUSIONS

We depicted the immune landscape of patients with ATB and LTBI. Three immune subtypes were identified in ATB patients with different severity.

QuantiFERON Gold-In-Tube for the diagnosis of mycobacterial tuberculosis infection in children under 5 years of age: A systematic review and meta-analysis

BACKGROUND

Previous meta-analysis regarding the performance of QuantiFERON Gold-In-Tube in children have yielded contrasting results. Emerging data in children younger than 5 years of age necessitates a new analysis.

METHODS

Systematic searches were conducted of MedLINE, EMBASE and Cochrane databases between 1998-2023. Pooled estimates of sensitivities and specificities of QFT-GIT compared to tuberculin skin test (TST) were calculated. The Kappa (k) coefficient was calculated for each study to determine the degree of congruence between TST and QFT-GIT results. Studies including patients co-infected with HIV or other immune compromising conditions or those treated with anti-tubercular treatment were excluded.

RESULTS

Seventeen studies (4335 patients) were included in quantitative analysis. All studies were conducted in middle to high income countries. They were conducted across 14 countries and 4 studies in countries with high TB incidence. The pooled sensitivity, specificity and DOR were 0.45 (0.42-0.48), 0.96 (0.96-0.97) and 18.84 (7.33-48.41) respectively. The ability of QFT-GIT to discriminate with disease and no disease was "good" as demonstrated by a summary receiver operating characteristic curve with area under curve of 0.7812. The average Kappa (k) co-efficient was 0.501 with a wide variety of values between studies (0.167 to 0.800).

CONCLUSION

The findings of this meta-analysis support the judicious use of QFT-GIT in children 5 years and under, with caution as a sole test to exclude Tuberculosis in this age group. The heterogeneity and methodological quality of diagnostic studies limits the generalisability of results.

Air pollutants in bronchoalveolar lavage fluid and pulmonary tuberculosis: A mediation analysis of gene-specific methylation

Particulate matter (PM) exposure could alter the risk of tuberculosis, but the underlying mechanism is still unclear. We enrolled 132 pulmonary tuberculosis (PTB) patients and 30 controls. Bronchoalveolar lavage fluid samples were collected from all participants to detect organochlorine pesticides, polycyclic aromatic hydrocarbons, metal elements, and DNA methylation of immunity-related genes. We observed that γ-HCH, Bap, Sr, Ag, and Sn were related to an increased risk of PTB, while Cu and Ba had a negative effect. IFN-γ, IL-17A, IL-2, and IL-23 had a higher level in the PTB group, while IL-4 was lower. The methylation of 18 CpG sites was statistically associated with PTB risk. The methylation at the IL-4_06_121 site showed a significant mediating role on γ-HCH, Sr, and Sn. Our study suggests that PM exposure can increase the risk of tuberculosis by affecting DNA methylation and cytokine expression.

Comparison of the Standard E TB-Feron ELISA and QuantiFERON-TB Gold PLUS assays: the advantageous use of whole recombinant protein antigens for latent tuberculosis diagnosis

The laboratory diagnosis of latent tuberculosis is often performed using interferon-gamma release assays. Here, we compared two enzyme-linked immunosorbent assay-based interferon-gamma release assays, namely, the newly developed Standard E TB-Feron enzyme-linked immunosorbent assay (STFE) and the QuantiFERON-TB Gold PLUS assay (QFT-GP), using samples from 155 participants. The STFE is based on using whole EAST6 and CFP10 recombinant antigens for latent tuberculosis diagnosis. The participants were classified into four groups and screened using both assays per the manufacturers' instructions. Thereafter, two statistical analyses were conducted to compare the obtained results. First, the STFE results were compared with the QTF-GP results (used as the gold standard) to calculate the total concordance, sensitivity, and specificity of STFE. Second, positivity and negativity concordances were calculated to differentiate healthy participants from participants with tuberculosis. The STFE showed 97% and 94% sensitivity and specificity, respectively. Furthermore, its positivity and negativity concordances were 91% and 98%, respectively. These results indicate the coordinated clinical performance of STFE in detecting latent tuberculosis and its improved performance in targeting tuberculosis-infected participants. Based on the comparison of the latent tuberculosis diagnostic abilities of STFE and QFT-GP, we establish the suitability and superior performance of STFE as a diagnostic tool.

Integrated bioinformatics analysis of dendritic cells hub genes reveal potential early tuberculosis diagnostic markers

BACKGROUND

Dendritic cells (DCs) are most potent antigen-processing cells and play key roles in host defense against Mycobacterium tuberculosis (MTB) infection. In this study, hub genes in DCs during MTB infection were first investigated using bioinformatics approaches and further validated in Monocyte-derived DCs.

METHODS

Microarray datasets were obtained from Gene Expression Omnibus (GEO) database. Principal component analysis (PCA) and immune infiltration analysis were performed to select suitable samples for further analysis. Differential analysis and functional enrichment analysis were conducted on DC samples, comparing live MTB-infected and non-infected (NI) groups. The CytoHubba plugin in Cytoscape was used to identify hub genes from the differentially expressed genes (DEGs). The expression of the hub genes was validated using two datasets and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) in human monocyte-derived DCs. Enzyme-linked immunosorbent assay (ELISA) was used to validate interferon (IFN) secretion. Transcription factors (TFs) and microRNAs (miRNAs) that interact with the hub genes were predicted using prediction databases. The diagnostic value of the hub genes was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC) values.

RESULTS

A total of 1835 common DEGs among three comparison groups (18 h, 48 h, 72 h after MTB infection) were identified. Six DEGs (IFIT1, IFIT2, IFIT3, ISG15, MX1, and RSAD2) were determined as hub genes. Functions enrichment analysis revealed that all hub genes all related to IFN response. RT-qPCR showed that the expression levels of six hub genes were significantly increased after DC stimulated by live MTB. According to the results of ELISA, the secretion of IFN-γ, but not IFN-α/β, was upregulated in MTB-stimulated DCs. AUC values of six hub genes ranged from 84 to 94% and AUC values of 5 joint indicators of two hub genes were higher than the two hub genes alone.

CONCLUSION

The study identified 6 hub genes associated with IFN response pathway. These genes may serve as potential diagnostic biomarkers in tuberculosis (TB). The findings provide insights into the molecular mechanisms involved in the host immune response to MTB infection and highlight the diagnostic potential of these hub genes in TB.

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.

Novel Biomarker Panel of Let-7d-5p and MiR-140-5p Can Distinguish Latent Tuberculosis Infection from Active Tuberculosis Patients

Background

Mycobacterium tuberculosis (Mtb) survives inside a human host for a long time in the form of latent tuberculosis infection (LTBI). Latent infection of tuberculosis has the opportunity of developing into active tuberculosis (ATB), which has greatly endangered human health. The existing diagnostic methods cannot effectively distinguish LTBI from ATB. Therefore, more effective diagnostic biomarkers and methods are urgently needed.

Methods

Here, we screened the GEO data set, conducted joint differential analysis and target gene enrichment analysis, after filtering the disease-related database, we screened the differential miRNA related to TB. The qPCR was used to verify the miRNAs in 84 serum samples. Different combinations of biomarkers were evaluated by logistic regression to obtain a biomarker panel with good performance for diagnosing LTBI.

Results

A panel with two miRNAs (hsa-let-7d-5p, hsa-miR-140-5p) was established to differentiate LTBI from ATB. Receiver operating characteristic (ROC) curve showed that the area under the curve (AUC) are 0.930 (sensitivity = 100%, specificity = 88.5%) and 0.923 (sensitivity = 100%, specificity = 92.3%) with the biomarker panel for the training set and test set respectively.

Conclusion

The findings indicated that the logistic regression model built by let-7d-5p and miR-140-5p has the ability to distinguish LTBI from active TB patients.

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.

Epigenetic orchestration of host immune defences by Mycobacterium tuberculosis

Being among the top 10 causes of adult deaths, tuberculosis (TB) disease is considered a major global public health concern to address. The human tuberculosis pathogen, Mycobacterium tuberculosis (Mtb), is an extremely competent and well-versed pathogen that promotes pathogenesis by evading the host immune systems through numerous tactics. Investigations revealed that Mtb could evade the host defense mechanisms by reconfiguring the host gene transcription and causing epigenetic changes. Although results indicate the link between epigenetics and disease manifestation in other bacterial infections, little is known regarding the kinetics of the epigenetic alterations in mycobacterial infection. This literature review discusses the studies in Mtb-induced epigenetic alterations inside the host and its contribution in the host immune evasion strategies. It also discusses how the Mtb-induced alterations could be used as 'epibiomarkers' to diagnose TB. Additionally, this review also discusses therapeutic interventions to be enhanced through remodification by 'epidrugs'.

Glutathione Modulates Efficacious Changes in the Immune Response against Tuberculosis

Glutathione (GSH) is an antioxidant in human cells that is utilized to prevent damage occurred by reactive oxygen species, free radicals, peroxides, lipid peroxides, and heavy metals. Due to its immunological role in tuberculosis (TB), GSH is hypothesized to play an important part in the immune response against M. tb infection. In fact, one of the hallmark structures of TB is granuloma formation, which involves many types of immune cells. T cells, specifically, are a major component and are involved in the release of cytokines and activation of macrophages. GSH also serves an important function in macrophages, natural killer cells, and T cells in modulating their activation, their metabolism, proper cytokine release, proper redox activity, and free radical levels. For patients with increased susceptibility, such as those with HIV and type 2 diabetes, the demand for higher GSH levels is increased. GSH acts as an important immunomodulatory antioxidant by stabilizing redox activity, shifting of cytokine profile toward Th1 type response, and enhancing T lymphocytes. This review compiles reports showing the benefits of GSH in improving the immune responses against M. tb infection and the use of GSH as an adjunctive therapy for TB.

Long-Term Immunogenicity and In Vitro Prophylactic Protective Efficacy of M. tuberculosis Fusion Protein DR2 Combined with Liposomal Adjuvant DIMQ as a Boosting Vaccine for BCG

The resuscitation of dormant Mycobacterium tuberculosis is an important cause of adult tuberculosis (TB) transmission. According to the interaction mechanism between M. tuberculosis and the host, the latency antigen Rv0572c and region of difference 9 (RD9) antigen Rv3621c were selected in this study to prepare the fusion protein DR2. Stimulating clinically diagnosed active tuberculosis infections (i.e., TB patients), latent tuberculosis infections, and healthy controls confirmed that T lymphocytes could recognize DR2 protein in the peripheral blood of TB-infected individuals more than subcomponent protein. The DR2 protein was then emulsified in the liposome adjuvant dimethyl dioctadecyl ammonium bromide, and imiquimod (DIMQ) was administered to C57BL/6 mice immunized with Bacillus Calmette-Guérin (BCG) vaccine to evaluate their immunogenicity. Studies have shown that DR2/DIMQ, a booster vaccine for BCG primary immunization, can elicit robust CD4⁺ Th1 cell immune response and predominant IFN-γ⁺ CD4⁺ effector memory T cells (T_EM) subsets. Furthermore, the serum antibody level and the expression of related cytokines increased significantly with the extension of immunization time, with IL2⁺, CD4⁺, or CD8⁺ central memory T cells (T_CM) subsets predominant in the long term. This immunization strategy showed matched prophylactic protective efficacy by performing in vitro challenge experiment. This result provides robust evidence that the novel subunit vaccine prepared by fusion protein DR2 combined with liposomal adjuvant DIMQ is a promising TB vaccine candidate for further preclinical trials as a booster vaccine for BCG.

Commercially available CD4 + and CD8 + IFN-γ release assays combined with an HBHA-induced IGRA improve the characterization of the tuberculosis spectrum and monitoring of treatment in children

Commercially available Interferon-γ release assays (IGRAs), including the last-generation QuantiFERON TB-Plus (QFT-Plus), are effective in aiding the diagnosis of tuberculosis (TB) infection but cannot distinguish latent TB subjects from active TB patients. The aim of this study was to prospectively evaluate the performance of an HBHA-based IGRA, combined with commercially available IGRAs, to assess their usefulness as a prognostic biomarkers and aid in the monitoring of TB treatment in children. Following clinical, microbiological, and radiological assessment, children younger than 18 years of age classified as either LTBI or active TB were tested at baseline and during treatment by the QuantiFERON TB-Plus (QFT) assay and an aliquot of whole-blood was stimulated with HBHA. Among the 655 children evaluated, 559 (85.3%) were classified as "Non TB", 44 patients (6.7%) with active TB, and 52 (7.9%) with LTBI. The median HBHA-IGRA IFN-gamma responses were able to discriminate active TB from LTBI (0.13 IU/ml vs 1.995, (p < 0,0001), those with asymptomatic TB from those with symptomatic TB (1.01 IU/ml vs 0.115 IU/ml, p 0.017), or more severe TB (p 0.022), and significantly raised during successful TB treatment (p < 0.0001). Conversely, CD4 + and CD8 + responses were similar in all groups of patients, although active TB patients had higher CD4 + responses and LTBI higher CD8 + responses.  Conclusion: HBHA-based IGRA, combined with CD4 + and CD8 + responses assessed by commercially available IGRAs, is a useful support in the characterization of the TB spectrum in children and monitoring of TB-therapy. What is Known: • Current immune diagnostics are not able to discriminate active and latent Ttuberculosis, including the recently approved QFT-PLUS.. • New immunological assays with prognostic value are highly needed. What is New: • HBHA-based IGRA, combined with CD4+ and CD8+ responses assessed by commercially available IGRAs, is a useful support for the differentiation of active and latent TB in children.. • HBHA-based IGRA, combined with CD4+ and CD8+ responses assessed by commercially available IGRAs, is a useful support in the monitoring of TBtherapy in children..

Differential expression of host protein biomarkers among symptomatic clinic attendees finally diagnosed with tuberculosis and other respiratory diseases with or without latent Mycobacterium tuberculosis infection

BACKGROUND

There is a need for new tools for the diagnosis of tuberculosis (TB) amongst patients who present at primary health care centers with symptoms suggestive of TB.

OBJECTIVES

To assess the abilities of selected blood-based host biomarkers to discriminate between patients who self-presented with symptoms suggestive of TB and were subsequently diagnosed with pulmonary tuberculosis (PTB), other respiratory diseases (ORD) with latent Mycobacterium tuberculosis infection (ORD_LTBI) or ORD without latent infection (ORD_NoLTBI).

METHODS

Presumptive TB patients (n = 161) were enrolled at a TB Clinic in Kampala, Uganda, and blood was collected. Participants were later classified as having PTB or ORD using standard microbiological confirmatory tests. Patients with ORD were subsequently classified as having LTBI or no LTBI using the QuantiFERON Gold-plus test. The concentrations of 27 host biomarkers were evaluated in patient sera using the Luminex platform, followed by an evaluation of their abilities to discriminate between PTB, ORD_LTBI, and ORD_NoLTBI.

RESULTS

Multiple host biomarkers including IP10, IL6, IL2, IL1β, TNFα, IFNγ, and IL12p70, were significantly different between patients with PTB (n = 55), ORDs (n = 106), and between PTB and the two ORD sub-groups. A bio-signature comprising IP10, IL6, TNFα IL1β, IL1ra, and IL12p70 best diagnosed PTB disease, with an area under the ROC curve of 90.

CONCLUSION

We identified host biomarkers that discriminated between different M.tb infection states amongst patients who presented with symptoms requiring investigation for TB. The biomarkers that showed diagnostic potential in our study may be considered as additional candidate markers for future active PTB rapid screening tests.

Current progress of functional nanobiosensors for potential tuberculosis diagnosis: The novel way for TB control?

Tuberculosis (TB), induced by the foxy Mycobacterium tuberculosis (Mtb), is still one of the top killers worldwide among infectious diseases. Although several antibiotics have been developed to significantly relieve the tuberculosis epidemics worldwide, there are still several important scientific challenges for tuberculosis. As one of the most critical issues for tuberculosis control, the accurate and timely diagnosis of tuberculosis is critical for the following therapy of tuberculosis and thus responsible for the effective control of drug-resistant tuberculosis. Current tuberculosis diagnostic methods in clinic are still facing the difficulties that they can't provide the rapid diagnostic results with high sensitivity and accuracy, which therefore requires the development of more effective novel diagnostic strategies. In recent decades, nanomaterials have been proved to show promising potentials for novel nanobiosensor construction based on their outstanding physical, chemical and biological properties. Taking these promising advantages, nanomaterial-based biosensors show the potential to allow the rapid, sensitive and accurate tuberculosis diagnosis. Here, aiming to increase the development of more effective tuberculosis diagnostic strategy, we summarized the current progress of nanobiosensors for potential tuberculosis diagnosis application. We discussed the different kind diagnostic targets for tuberculosis diagnosis based on nanobiosensors, ranging from the detection of bacterial components from M. tuberculosis, such as DNA and proteins, to the host immunological responses, such as specific cytokine production, and to the direct whole cell detection of M. tuberculosis. We believe that this review would enhance our understandings of nanobiosensors for potential tuberculosis diagnosis, and further promote the future research on nanobiosensor-based tuberculosis diagnosis to benefit the more effective control of tuberculosis epidemic.

Potential Impact of Long-Acting Products on the Control of Tuberculosis: Preclinical Advancements and Translational Tools in Preventive Treatment

A key component of global tuberculosis (TB) control is the treatment of latent TB infection. The use of long-acting technologies to administer TB preventive treatment has the potential to significantly improve the delivery and impact of this important public health intervention. For example, an ideal long-acting treatment could consist of a single dose that could be administered in the clinic (ie, a "1-shot cure" for latent TB). Interest in long-acting formulations for TB preventive therapy has gained considerable traction in recent years. This article presents an overview of the specific considerations and current preclinical advancements relevant for the development of long-acting technologies of TB drugs for treatment of latent infection, including attributes of target product profiles, suitability of drugs for long-acting formulations, ongoing research efforts, and translation to clinical studies.

MicroRNAs as diagnostic biomarkers for Tuberculosis: A systematic review and meta- analysis

Background

The early diagnosis of tuberculosis using novel non-sputum-based biomarkers is of high priority in the End TB strategy. MicroRNAs (miRNAs) are significant regulators of TB pathogenesis and their differential expression pattern among healthy, latent, and active TB population has revealed their potentiality as biomarkers in recent studies. Thus, we systematically reviewed and performed a meta-analysis on the role of host miRNAs in TB diagnosis. We also reviewed the involvement of miRNAs in the immune response to Mycobacterium tuberculosis (Mtb).

Methods

Pubmed, Ovid and Cochrane databases were searched to retrieve published literature from 2000 to 2020 using predefined keywords. We screened relevant studies based on inclusion and exclusion criteria and the included studies were assessed for their quality using STARD guidelines and QUADAS-2 tool. Funnel plots were constructed to assess the publication bias. The heterogeneity of studies and overall pooled results of sensitivity, specificity and DOR were determined using forest plots.

Results

We retrieved a total of 447 studies collectively from all the databases, out of which 21 studies were included for qualitative analysis. In these studies, miR-29, miR-31, miR-125b, miR146a and miR-155 were consistently reported. The overall sensitivity, specificity and DOR of these miRNAs were found to be 87.9% (81.7-92.2), 81.2% (74.5-86.5) and 43.1(20.3-91.3) respectively. Among these, miR-31 had the maximum diagnostic accuracy, with a sensitivity of 96% (89.7-98.5), specificity of 89% (81.2-93.8) and DOR of 345.9 (90.2-1326.3), meeting the minimal target product profile (TPP) for TB diagnostics.

Conclusion

miRNAs can thus be exploited as potential biomarkers for rapid detection of tuberculosis as evident from their diagnostic performance.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021226559 PROSPERO (CRD42021226559).

Host biomarkers other than interferon gamma in QFT-TB supernatants for identifying active tuberculosis

Interferon gamma release assays (IGRAs) for tuberculosis (TB) remain limited in their ability to discriminate between active TB (ATB) and latent TB infection (LTBI). The objective of our study was to evaluate the value of additional cytokines/chemokines other than interferon gamma (IFN-γ) as biomarkers to identify different TB infection status. A total of 128 subjects were enrolled to detect the quantification of IL-2, IP-10, MCP-1 and RANTES in the supernatants of QuantiFERON®-TB (QFT-TB). Area under the curve (AUC) was used to evaluate the diagnostic efficiency. Notably, Mycobacterium tuberculosis (Mtb) induced cytokines/chemokines of ATB patients were significantly higher than those of the LTBI, other lung related diseases (ORD) and healthy controls (HC). Moreover, ROC analysis indicated that all cytokine/chemokine parameters detected were more capable of distinguishing ATB from LTBI than IFN-γ, especially IL-2. The diagnostic model including TB specific IL-2 and RANTES improved the performance in distinguishing ATB from LTBI, which was superior to single cytokines/chemokines in QFT-TB supernatants. Our results suggest that the combination of Mtb specific cytokines/chemokines has great prospects in the diagnosis of ATB, and the diagnostic model based on IL-2 and RANTES can be used as an alternative to distinguish ATB from LTBI.

Elevated IP-10 at the Protein and Gene Level Associates With Pulmonary TB

There is an urgent need for accurate and sensitive diagnostic tools that can overcome the current challenge to distinguish individuals with latent tuberculosis infection (LTBI) from individuals with active tuberculosis (TB). Recent literature has suggested that a group of cytokines may serve as biomarkers of TB disease progression. Using a multiplex ELISA, we quantified 27 circulatory markers present within the unstimulated plasma of individuals in Durban, South Africa who were healthy (n=20), LTBI (n=13), or had active TB (n=30). RT-qPCR was performed to measure gene expression of the cytokines of interest, using RNA isolated from healthy (n=20), LTBI (n=20), or active TB (n=30). We found that at the protein level, IL-1RA, IL-6, and IP-10 were significantly more abundant in participants with active TB (p< 0.05) compared to those with LTBI individuals. IP-10 also showed the strongest association with active TB compared to healthy and LTBI at mRNA level. Our data shows that these proteins may serve as biomarkers of TB at both the protein and gene level.

Machine learning based on routine laboratory indicators promoting the discrimination between active tuberculosis and latent tuberculosis infection

BACKGROUND

Discriminating active tuberculosis (ATB) from latent tuberculosis infection (LTBI) remains challenging. The present study aims to evaluate the performance of diagnostic models established using machine learning based on routine laboratory indicators in differentiating ATB from LTBI.

METHODS

Participants were respectively enrolled at Tongji Hospital (discovery cohort) and Sino-French New City Hospital (validation cohort). Diagnostic models were established based on routine laboratory indicators using machine learning.

RESULTS

A total of 2619 participants (1025 ATB and 1594 LTBI) were enrolled in discovery cohort and another 942 subjects (388 ATB and 554 LTBI) were recruited in validation cohort. ATB patients had significantly higher levels of tuberculosis-specific antigen/phytohemagglutinin ratio and coefficient variation of red blood cell volume distribution width, and lower levels of albumin and lymphocyte count than those of LTBI individuals. Six models were built and the optimal performance was obtained from GBM model. GBM model derived from training set (n = 1965) differentiated ATB from LTBI in the test set (n = 654) with a sensitivity of 84.38% (95% CI, 79.42%-88.31%) and a specificity of 92.71% (95% CI, 89.73%-94.88%). Further validation by an independent cohort confirmed its encouraging value with a sensitivity of 87.63% (95% CI, 83.98%-90.54%) and specificity of 91.34% (95% CI, 88.70%-93.40%), respectively.

CONCLUSIONS

We successfully developed a model with promising diagnostic value based on machine learning for the first time. Our study proposed that GBM model may be of great benefit served as a tool for the accurate identification of ATB.

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.

Plasma chemokines as immune biomarkers for diagnosis of pediatric tuberculosis

Background

Diagnosing tuberculosis (TB) in children is challenging due to paucibacillary disease, and lack of ability for microbiologic confirmation. Hence, we measured the plasma chemokines as biomarkers for diagnosis of pediatric tuberculosis.

Methods

We conducted a prospective case control study using children with confirmed, unconfirmed and unlikely TB. Multiplex assay was performed to examine the plasma CC and CXC levels of chemokines.

Results

Baseline levels of CCL1, CCL3, CXCL1, CXCL2 and CXCL10 were significantly higher in active TB (confirmed TB and unconfirmed TB) in comparison to unlikely TB children. Receiver operating characteristics curve analysis revealed that CCL1, CXCL1 and CXCL10 could act as biomarkers distinguishing confirmed or unconfirmed TB from unlikely TB with the sensitivity and specificity of more than 80%. In addition, combiROC exhibited more than 90% sensitivity and specificity in distinguishing confirmed and unconfirmed TB from unlikely TB. Finally, classification and regression tree models also offered more than 90% sensitivity and specificity for CCL1 with a cutoff value of 28 pg/ml, which clearly classify active TB from unlikely TB. The levels of CCL1, CXCL1, CXCL2 and CXCL10 exhibited a significant reduction following anti-TB treatment.

Conclusion

Thus, a baseline chemokine signature of CCL1/CXCL1/CXCL10 could serve as an accurate biomarker for the diagnosis of pediatric tuberculosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06749-6.

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.

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.

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.

Antiretroviral Treatment-Induced Decrease in Immune Activation Contributes to Reduced Susceptibility to Tuberculosis in HIV-1/Mtb Co-infected Persons

Antiretroviral treatment (ART) reduces the risk of developing active tuberculosis (TB) in HIV-1 co-infected persons. In order to understand host immune responses during ART in the context of Mycobacterium tuberculosis (Mtb) sensitization, we performed RNAseq analysis of whole blood-derived RNA from individuals with latent TB infection coinfected with HIV-1, during the first 6 months of ART. A significant fall in RNA sequence abundance of the Hallmark IFN-alpha, IFN-gamma, IL-6/JAK/STAT3 signaling, and inflammatory response pathway genes indicated reduced immune activation and inflammation at 6 months of ART compared to day 0. Further exploratory evaluation of 65 soluble analytes in plasma confirmed the significant decrease of inflammatory markers after 6 months of ART. Next, we evaluated 30 soluble analytes in QuantiFERON Gold in-tube (QFT) samples from the Ag stimulated and Nil tubes, during the first 6 months of ART in 30 patients. There was a significant decrease in IL-1alpha and IL-1beta (Ag-Nil) concentrations as well as MCP-1 (Nil), supporting decreased immune activation and inflammation. At the same time, IP-10 (Ag-nil) concentrations significantly increased, together with chemokine receptor-expressing CD4 T cell numbers. Our data indicate that ART-induced decrease in immune activation combined with improved antigen responsiveness may contribute to reduced susceptibility to tuberculosis in HIV-1/Mtb co-infected persons.