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

Identification of MORN3 and LLGL2 as novel diagnostic biomarkers for latent tuberculosis infection using machine learning strategies and experimental verification

BACKGROUND

Current diagnostic methods cannot effectively distinguish between latent tuberculosis infection (LTBI) and active tuberculosis (ATB). This study aims to explore novel non-invasive diagnostic biomarkers for LTBI and to elucidate possible molecular mechanisms of LTBI pathogenesis.

METHODS

Three GEO datasets (GSE19439, GSE19444, and GSE62525) were utilized to analyze the differentially expressed genes (DEGs). Functional enrichment studies were then performed on these DEGs. To ascertain potential diagnostic biomarkers, we utilized two different machine learning techniques: LASSO and RF. ROC curves were constructed in both the training and validation datasets to assess the diagnostic efficacy. The expression of identified biomarkers was verified by RT-qPCR in our own Chinese cohort. Using CIBERSORT, we estimated the abundances of 22 immune cell types in LTBI group, and subsequently analyzed the relationship between biomarker expression and immune cell infiltration.

RESULTS

166 DEGs were identified between ATB and LTBI groups, which are primarily associated with immune responses, inflammatory signaling pathways, and infection factors. Following that, 22 candidate diagnostic biomarkers for LTBI were selected in the machine learning process. Three up-regulated genes, MORN3, LLGL2, and IFT140, whose expression levels were not previously reported in TB, were validated using the training and validation cohort datasets. In our own Chinese cohort, we also found that MORN3 and LLGL2 showed good diagnostic effect using RT-qPCR method. Finally, we revealed the specific infiltration features of immune cells in LTBI and observed a notable correlation between potential marker expression and immune cells.

CONCLUSIONS

MORN3 and LLGL2 emerged as candidate diagnostic biomarkers for LTBI, following the elucidation of the key immune cell types involved. Our findings will contribute to providing a potential target for early noninvasive diagnosis of LTBI patients.

A multistage Sendai virus vaccine incorporating latency-associated antigens induces protection against acute and latent tuberculosis

One-quarter of the world's population is infected with Mycobacterium tuberculosis (Mtb). After initial exposure, more immune-competent persons develop asymptomatic latent tuberculosis infection (LTBI) but not active diseases, creates an extensive reservoir at risk of developing active tuberculosis. Previously, we constructed a novel recombinant Sendai virus (SeV)-vectored vaccine encoding two dominant antigens of Mtb, which elicited immune protection against acute Mtb infection. In this study, nine Mtb latency-associated antigens were screened as potential supplementary vaccine candidate antigens, and three antigens (Rv2029c, Rv2028c, and Rv3126c) were selected based on their immune-therapeutic effect in mice, and their elevated immune responses in LTBI human populations. Then, a recombinant SeV-vectored vaccine, termed SeV986A, that expresses three latency-associated antigens and Ag85A was constructed. In murine models, the doses, titers, and inoculation sites of SeV986A were optimized, and its immunogenicity in BCG-primed and BCG-naive mice were determined. Enhanced immune protection against the Mtb challenge was shown in both acute-infection and latent-infection murine models. The expression levels of several T-cell exhaustion markers were significantly lower in the SeV986A-vaccinated group, suggesting that the expression of latency-associated antigens inhibited the T-cell exhaustion process in LTBI infection. Hence, the multistage quarter-antigenic SeV986A vaccine holds considerable promise as a novel post-exposure prophylaxis vaccine against tuberculosis.

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.

Peripheral blood MR1 tetramer-positive mucosal-associated invariant T-cell function is modulated by mammalian target of rapamycin complex 1 in patients with active tuberculosis

Tuberculosis (TB) is still an urgent global public health problem. Notably, mucosal-associated invariant T (MAIT) cells play an important role in early anti-TB immune response. Targeted control of them may be an effective method to improve vaccine efficacy and TB treatment. However, the biology and signal regulation mechanisms of MAIT cells in TB patients are still poorly understood. Previous studies have been limited by the lack of reagents to specifically identify MAIT cells. In addition, the use of alternative markers may subsume non-MAIT cell into MAIT cell populations. In this study, the human MR1 tetramer which can specifically identify MAIT cells was used to further explore the effect and mechanism of MAIT cells in anti-TB immune response. Our results showed that the tetramer+ MAIT cells in peripheral blood of TB patients were mainly CD8+ or CD4-CD8- cells, and very few were CD4+ cells. After BCG infecting autologous antigen-presenting cells, MAIT cells in patients produced significantly higher levels of cytokines, lysis and proliferation compared with healthy controls. After suppression of mTORC1 by the mTORC1-specific inhibitor rapamycin, the immune response of MAIT cells in patients was significantly reduced. This study demonstrates that peripheral blood tetramer+ MAIT cells from TB patients have significant anti-TB immune effect, which is regulated by mTORC1. This could provide ideas and potential therapeutic targets for the development of novel anti-TB immunotherapy.

Mixed methods study on latent tuberculosis among agate stone workers and advocacy for testing silica dust exposed individuals in India

The 2021 tuberculosis (TB) preventive treatment guidelines in India included silicosis as a screening group, yet latent TB infection (LTBI) testing for silica-dust-exposed individuals is underemphasized. Focusing on an estimated 52 million silica-dust-exposed workers, particularly agate-stone workers in Khambhat, Gujarat, our study aims to estimate LTBI prevalence, identify predictors, and gather insights from TB and silicosis experts. Employing a sequential explanatory mixed-methods approach, a cross-sectional study involved 463 agate-stone workers aged ≥ 20 years in Khambhat, using IGRA kits for LTBI testing. In-depth interviews with experts complemented quantitative findings. Among agate-stone workers, 58% tested positive for LTBI, with predictors including longer exposure, type of work, and BCG vaccination. Our findings reveal a nearly double burden of LTBI compared to the general population, particularly in occupations with higher silica dust exposure. Experts advocate for including silica-dust-exposed individuals in high-risk groups for LTBI testing, exploring cost-effective alternatives like improved skin sensitivity tests, and shorter TB preventive treatment regimens to enhance compliance. Future research should explore upfront TB preventive treatment for silica-dust-exposed individuals with high LTBI prevalence and optimal exposure duration. This study underscores the urgent need for policy changes and innovative approaches to TB prevention among silica-dust-exposed populations, impacting global occupational health strategies.

Reactivation Risk of Latent Tuberculosis or Inactive Hepatitis B Virus Infection and Effectiveness of Ustekinumab in Chinese Plaque Psoriasis Patients: A 28-Week Retrospective, Observational Study

Introduction

This study observed the effectiveness of ustekinumab and reactivation risk of concurrent latent tuberculosis infection (LTBI) and inactive hepatitis B virus (HBV) infection in Chinese mainland psoriasis patients on ustekinumab treatment.

Methods

This retrospective, multicenter, observational study was conducted in three centers in China. Adult patients with moderate to severe plaque psoriasis were treated with ustekinumab for 28 weeks. The effectiveness endpoint included 75% and 90% improvement in Psoriasis Area Severity Index (PASI75/90) response rate, percentage of PASI improvement, change of absolute PASI score and body surface area involvement (BSA) score, absolute PASI ≤1/3 and Physicians' Global Assessment (PGA)=0/1, as well as Dermatology life quality index (DLQI)=0/1 response rate at week 4, 16 and 28. Screening of tuberculosis and hepatitis were performed at baseline and week 28.

Results

A total of 82 patients were enrolled between March 2021 and May 2023 and the number of patients combined with LTBI and inactive HBV infection was 20 and 21 respectively. The PASI75 and PASI90 response rate at week 28 was 95.1% and 81.7% respectively. The mean PASI score decreased from 14.93 ± 12.07 at baseline to 0.78 ± 1.86 at week 28, and the mean BSA score decreased from 21% ± 18% at baseline to 1% ± 2% at week 28 (both P<0.001 compared with baseline). DLQI 0/1 response rate at week 28 was 73.2%. No reactivation of LTBI and inactive HBV infection and also no new-onset tuberculosis and hepatitis B occurred in patients without LTBI and inactive HBV infection at baseline.

Conclusion

Ustekinumab demonstrated great effectiveness in Chinese plaque psoriasis patients and good safety in psoriasis concurrent with LTBI and inactive HBV infection under the real-world setting.

Opinion review of drug resistant tuberculosis in West Africa: tackling the challenges for effective control

Drug-resistant (DR) tuberculosis (TB) is a major public health concern globally, complicating TB control and management efforts. West Africa has historically faced difficulty in combating DR-TB due to limited diagnostic skills, insufficient access to excellent healthcare, and ineffective healthcare systems. This has aided in the emergence and dissemination of DR Mycobacterium tuberculosis complex (MTBC) strains in the region. In the past, DR-TB patients faced insufficient resources, fragmented efforts, and suboptimal treatment outcomes. However, current efforts to combat DR-TB in the region are promising. These efforts include strengthening diagnostic capacities, improving access to quality healthcare services, and implementing evidence-based treatment regimens for DR-TB. Additionally, many West African National TB control programs are collaborating with international partners to scale up laboratory infrastructure, enhance surveillance systems, and promote infection control measures. Moreso, novel TB drugs and regimens, such as bedaquiline and delamanid, are being introduced to improve treatment outcomes for DR-TB cases. Despite these obstacles, there is optimism for the future of DR-TB control in West Africa. Investments are being made to improve healthcare systems, expand laboratory capacity, and support TB research and innovation. West African institutions are now supporting knowledge sharing, capacity building, and resource mobilization through collaborative initiatives such as the West African Network for TB, AIDS, and Malaria (WANETAM), the West African Health Organization (WAHO), and other regional or global partners. These efforts hold promise for improved diagnostics, optimized treatment regimens, and provide better patient outcomes in the future where drug-resistant TB in WA can be effectively controlled, reducing the burden of the disease, and improving the health outcomes of affected individuals.

Analysis of T-lymphocyte subsets and risk factors in children with tuberculosis

BACKGROUND

Tuberculosis (TB) is not only related to infection but also involves immune factors. This study explores the changes in T-lymphocyte subsets in children with TB who are human immunodeficiency virus (HIV)-negative and examines their relationship using chest computed tomography (CT) scans. Additionally, the study identifies risk factors for severe TB (STB) in children and establishes relevant risk prediction models.

METHODS

We recruited 235 participants between 2018 and 2022, comprising 176 paediatric patients with TB who were HIV-negative and 59 age-matched children with bacterial community-acquired pneumonia (CAP). We quantitatively analysed and compared T-lymphocyte subsets between the two groups and among different types of TB infection. Both univariate and multivariate analyses of clinical and laboratory characteristics were conducted to identify independent risk factors for STB in children and to establish a risk prediction model.

RESULTS

The absolute counts of CD3, CD4 and CD8 T-cells in children with TB infection decreased significantly compared with bacterial CAP. The percentage of CD8 T-cells increased, whereas the percentage of CD4 T-cells did not change significantly. The absolute count of CD3, CD4 and CD8 T-cells in extrapulmonary TB (EPTB) was significantly higher than in extra-respiratory TB, with unchanged subset percentages. According to chest CT lesion classification, CD4 T-cell counts decreased significantly in S3 compared with S1 or S2, with no significant change in CD3 and CD8 T-cell counts and percentages. No significant differences were observed in lymphocyte subset counts and percentages between S1 and S2. Univariate analyses indicated that factors such as age, symptom duration, white blood cell count, platelet count, neutrophil-to-lymphocyte ratio (NLR), erythrocyte sedimentation rate, prealbumin level, albumin level, globulin level, albumin/globulin (A/G) ratio, high-sensitivity C-reactive protein (Hs-CRP) level and CD4 and CD8 T-cell counts are associated with STB. Multivariate logistic regression analysis revealed that age, Hs-CRP level, NLR, symptom duration and A/G ratio are independent risk factors for STB in children. Increased age, Hs-CRP levels and NLR, along with decreased A/G, correlate with increased susceptibility to STB. A nomogram model, based on these independent risk factors, demonstrated an area under the receiver operating characteristics curve of 0.867 (95% CI: 0.813-0.921). Internal verification confirmed the model's accuracy, with the calibration curve approaching the ideal and the Hosmer-Lemeshow goodness-of-fit test showing consistent results (χ2 = 12.212, p = 0.142).

CONCLUSION

In paediatric patients with TB, the absolute counts of all lymphocyte subsets were considerably reduced compared with those in patients with bacterial CAP. Clinicians should consider the possibility of EPTB infection in addition to respiratory infections in children with TB who have higher CD3, CD4 and CD8 T-cell counts than the ERTB group. Furthermore, CD4 T-cell counts correlated closely with the severity of chest CT lesions. Age, symptom duration, A/G ratio, Hs-CRP level and NLR were established as independent risk factors for STB. The nomogram model, based on these factors, offers effective discrimination and calibration in predicting STB in children.

Global tuberculosis disease and infection in systemic lupus erythematosus patients: A systematic review and meta-analysis

BACKGROUND

Tuberculosis (TB) is one of the most common infections among systemic lupus erythematosus (SLE) patients. We aimed to evaluate the global prevalence of TB infection and disease, its type, and medication risk factors in SLE patients.

METHODS

We searched PubMed, Science Direct, EBSCO, and Web of Science databases from inception to April 30, 2023, and included studies assessing TB among SLE patients. We estimated the prevalence of TB disease (including type of TB disease), TB infection, and SLE medication as TB risk factors. Meta-analysis was performed using Stata 14.2 and Review Manager 5.3.

RESULTS

Twenty-seven studies met the eligibility criteria. The global prevalence of TB disease was 4% (95% confidence interval (CI): 3-4%, n = 25) and TB infection was 18% (95% CI: 10-26%, n = 3). The pooled prevalence of pulmonary TB, extrapulmonary TB, and disseminated TB were 2% (95% CI: 2-3%, n = 20), 1% (95% CI: 1-2%, n = 17), and 1% (95% CI: 0-1%, n = 6), respectively. The 1-year cumulative glucocorticoid (GC) dose in SLE patients contracting TB was higher than in those without TB, having a mean difference of 2.56 (95% CI: 0.22-4.91, p < .00001, n = 3). The odd ratio of TB was 2.11 (95% CI: 1.01-4.41, p = .05, n = 3) in SLE patients receiving methylprednisolone (MP) pulse therapy as compared to those without MP pulse therapy. Other immunosuppressive agents were not significantly associated with TB.

CONCLUSION

TB prevalence in SLE was relatively high and associated with GC. Awareness of TB and lowering GC dose are warranted to alleviate the TB burden in SLE.

Construction of novel multi-epitope-based diagnostic biomarker HP16118P and its application in the differential diagnosis of Mycobacterium tuberculosis latent infection

Tuberculosis (TB) is an infectious disease that significantly threatens human health. However, the differential diagnosis of latent tuberculosis infection (LTBI) and active tuberculosis (ATB) remains a challenge for clinicians in early detection and preventive intervention. In this study, we developed a novel biomarker named HP16118P, utilizing 16 helper T lymphocyte (HTL) epitopes, 11 cytotoxic T lymphocyte (CTL) epitopes, and 8 B cell epitopes identified from 15 antigens associated with LTBI-RD using the IEDB database. We analyzed the physicochemical properties, spatial structure, and immunological characteristics of HP16118P using various tools, which indicated that it is a hydrophilic and relatively stable alkaline protein. Furthermore, HP16118P exhibited good antigenicity and immunogenicity, while being non-toxic and non-allergenic, with the potential to induce immune responses. We observed that HP16118P can stimulate the production of high levels of IFN-γ+ T lymphocytes in individuals with ATB, LTBI, and health controls. IL-5 induced by HP16118P demonstrated potential in distinguishing LTBI individuals and ATB patients (p=0.0372, AUC=0.8214, 95% CI [0.5843 to 1.000]) with a sensitivity of 100% and specificity of 71.43%. Furthermore, we incorporated the GM-CSF, IL-23, IL-5, and MCP-3 induced by HP16118P into 15 machine learning algorithms to construct a model. It was found that the Quadratic discriminant analysis model exhibited the best diagnostic performance for discriminating between LTBI and ATB, with a sensitivity of 1.00, specificity of 0.86, and accuracy of 0.93. In summary, HP16118P has demonstrated strong antigenicity and immunogenicity, with the induction of GM-CSF, IL-23, IL-5, and MCP-3, suggesting their potential for the differential diagnosis of LTBI and ATB.

Construction of Immune-Related Diagnostic Model for Latent Tuberculosis Infection and Active Tuberculosis

Background

Tuberculosis (TB) is one of the most infectious diseases caused by Mycobacterium tuberculosis (M. tb), and the diagnosis of active tuberculosis (TB) and latent TB infection (LTBI) remains challenging.

Methods

Gene expression files were downloaded from the GEO database to identify the differentially expressed genes (DEGs). The ssGSEA algorithm was applied to assess the immunological characteristics of patients with LTBI and TB. Weighted gene co-expression network analysis, protein-protein interaction network, and the cytoHubba plug-in of Cytoscape were used to identify the real hub genes. Finally, a diagnostic model was constructed using real hub genes and validated using a validation set.

Results

Macrophages and natural killer cells were identified as important immune cells strongly associated with TB. In total, 726 mRNAs were identified as DEGs. MX1, STAT1, IFIH1, DDX58, and IRF7 were identified as real hub immune-related genes. The diagnostic model generated by the five real hub genes could distinguish active TB from healthy controls or patients with LTBI.

Conclusion

Our study may provide implications for the diagnosis and drug development of M. tb infections.

Identification of hub genes and establishment of a diagnostic model in tuberculosis infection

Tuberculosis (TB) poses significant challenges due to its high transmissibility within populations and intrinsic resistance to treatment, rendering it a formidable respiratory disease with a substantial susceptibility burden. This study was designed to identify new potential therapeutic targets for TB and establish a diagnostic model. mRNA expression data for TB were from GEO database, followed by conducting differential expression analysis. The top 50 genes with differential expression were subjected to GO and KEGG enrichment analyses. To establish a PPI network, the STRING database was utilized, and hub genes were identified utilizing five algorithms (EPC, MCC, MNC, Radiality, and Stress) within the cytoHubba plugin of Cytoscape software. Furthermore, a hub gene co-expression network was constructed using the GeneMANIA database. Consistency clustering was performed on hub genes, and ssGSEA was utilized to analyze the extent of immune infiltration in different subgroups. LASSO analysis was employed to construct a diagnostic model, and ROC curves were used for validation. Through the analysis of GEO data, a total of 159 genes were identified as differentially expressed. Further, GO and KEGG enrichment analyses revealed that these genes were mainly enriched in viral defense, symbiotic defense, and innate immune response-related pathways. Hub genes, including DDX58, IFIT2, IFIH1, RSAD2, IFI44L, OAS2, OAS1, OASL, IFIT1, IFIT3, MX1, STAT1, and ISG15, were identified using cytoHubba analysis of the PPI network. The GeneMANIA analysis unmasked that the co-expression rate of hub genes was 81.55%, and the physical interaction rate was 12.27%. Consistency clustering divided TB patients into two subgroups, and ssGSEA revealed different degrees of immune infiltration in different subgroups. LASSO analysis identified IFIT1, IFIT2, IFIT3, IFIH1, RSAD2, OAS1, OAS2, and STAT1 as eight immune-related key genes, and a diagnostic model was constructed. The ROC curve demonstrated that the model exhibited excellent diagnostic performance. DDX58, IFIT2, IFIH1, RSAD2, IFI44L, OAS2, OAS1, OASL, IFIT1, IFIT3, MX1, STAT1, and ISG15 were hub genes in TB, and the diagnostic model based on eight immune-related key genes exhibited good diagnostic performance.

Evaluation of cytokine profiles related to Mycobacterium tuberculosis latent antigens using a whole-blood assay in the Philippines

Introduction

There is no useful method to discriminate between latent tuberculosis infection (LTBI) and active pulmonary tuberculosis (PTB). This study aimed to investigate the potential of cytokine profiles to discriminate between LTBI and active PTB using whole-blood stimulation with Mycobacterium tuberculosis (MTB) antigens, including latency-associated antigens.

Materials and methods

Patients with active PTB, household contacts of active PTB patients and community exposure subjects were recruited in Manila, the Philippines. Peripheral blood was collected from the participants and used for whole-blood stimulation (WBS) with either the early secretory antigenic target and the 10-kDa culture filtrate protein (ESAT-6/CFP-10), Rv3879c or latency-associated MTB antigens, including mycobacterial DNA-binding protein 1 (MDP-1), α-crystallin (Acr) and heparin-binding hemagglutinin (HBHA). Multiple cytokine concentrations were analyzed using the Bio-Plex™ multiplex cytokine assay.

Results

A total of 78 participants consisting of 15 active PTB patients, 48 household contacts and 15 community exposure subjects were eligible. The MDP-1-specific IFN-γ level in the active PTB group was significantly lower than that in the household contact group (p < 0.001) and the community exposure group (p < 0.001). The Acr-specific TNF-α and IL-10 levels in the active PTB group were significantly higher than those in the household contact (TNF-α; p = 0.001, IL-10; p = 0.001) and community exposure (TNF-α; p < 0.001, IL-10; p = 0.01) groups. However, there was no significant difference in the ESAT-6/CFP-10-specific IFN-γ levels among the groups.

Conclusion

The patterns of cytokine profiles induced by latency-associated MTB antigens using WBS have the potential to discriminate between LTBI and active PTB. In particular, combinations of IFN-γ and MDP-1, TNF-α and Acr, and IL-10 and Acr are promising. This study provides the first demonstration of the utility of MDP-1-specific cytokine responses in WBS.

Nanomedicine at the Pulmonary Frontier: Immune-Centric Approaches for Respiratory Disease Treatment

Respiratory diseases (RD) are a group of common ailments with a rapidly increasing global prevalence, posing a significant threat to humanity, especially the elderly population, and imposing a substantial burden on society and the economy. RD represents an unmet medical need that requires the development of viable pharmacotherapies. While various promising strategies have been devised to advance potential treatments for RD, their implementation has been hindered by difficulties in drug delivery, particularly in critically ill patients. Nanotechnology offers innovative solutions for delivering medications to the inflamed organ sites, such as the lungs. Although this approach is enticing, delivering nanomedicine to the lungs presents complex challenges that require sophisticated techniques. In this context, we review the potential of novel nanomedicine-based immunomodulatory strategies that could offer therapeutic benefits in managing this pressing health condition.

Mycobacterium tuberculosis latent infection in healthcare students: systematic review of prevalence

OBJECTIVE

The aim of this study was to synthesize the evidence on the prevalence of latent Mycobacterium tuberculosis infection (LTBI) among undergraduate health care students.

METHODS

A systematic review of prevalence with meta-analysis was conducted. Prospective and retrospective cohorts and cross-sectional studies involving probable exposure to M. tuberculosis during undergraduate education, along with the tuberculin skin test (TST) or interferon-γ release assay (IGRA) for investigation of latent tuberculosis were searched. Searches were conducted in MEDLINE, CINAHL, EMBASE, LILACS, Scopus, and Web of Science databases. Independent reviewers were responsible for the selection and inclusion of studies. Data were extracted, critically appraised, and synthesized using the JBI approach. PRISMA was used to report the study.

RESULTS

Twenty-two studies were analyzed. The overall prevalence in healthcare undergraduate students was 12.53%.

CONCLUSION

The prevalence of LTBI in undergraduate health students was high for such a highly educated population. Screening with TST and/or IGRA and chemoprophylaxis, when necessary, should be provided to undergraduate health students when in contact with respiratory symptomatic patients.

Association of neutrophil to lymphocyte ratio with bone mineral density in post-menopausal women: a systematic review and meta-analysis

BACKGROUND

We conducted a systematic review and meta-analysis to compare the neutrophil lymphocyte ratio (NLR) levels between women with post-menopausal osteopenia or osteoporosis to those with normal bone mineral density (BMD).

METHODS

We used Web of Science, PubMed, and Scopus to conduct a systematic search for relevant publications published before June 19, 2022, only in English language. We reported standardized mean difference (SMD) with a 95% confidence interval (CI). Because a significant level of heterogeneity was found, we used the random-effects model to calculate pooled effects. We used the Newcastle-Ottawa scale for quality assessment.

RESULTS

Overall, eight articles were included in the analysis. Post-menopausal women with osteoporosis had elevated levels of NLR compared to those without osteoporosis (SMD = 1.03, 95% CI = 0.18 to 1.88, p = 0.017, I2 = 98%). In addition, there was no difference between post-menopausal women with osteopenia and those without osteopenia in neutrophil lymphocyte ratio (NLR) levels (SMD = 0.58, 95% CI=-0.08 to 1.25, p = 0.085, I2 = 96.8%). However, there was no difference between post-menopausal women with osteoporosis and those with osteopenia in NLR levels (SMD = 0.75, 95% CI=-0.01 to 1.51, p = 0.05, I2 = 97.5%, random-effect model).

CONCLUSION

The results of this study point to NLR as a potential biomarker that may be easily introduced into clinical settings to help predict and prevent post-menopausal osteoporosis.

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.

Mycobacterium tuberculosis: immune response, biomarkers, and therapeutic intervention

Although tuberculosis (TB) is an infectious disease, the progression of the disease following Mycobacterium tuberculosis (MTB) infection is closely associated with the host's immune response. In this review, a comprehensive analysis of TB prevention, diagnosis, and treatment was conducted from an immunological perspective. First, we delved into the host's immune response mechanisms against MTB infection as well as the immune evasion mechanisms of the bacteria. Addressing the challenges currently faced in TB diagnosis and treatment, we also emphasized the importance of protein, genetic, and immunological biomarkers, aiming to provide new insights for early and personalized diagnosis and treatment of TB. Building upon this foundation, we further discussed intervention strategies involving chemical and immunological treatments for the increasingly critical issue of drug-resistant TB and other forms of TB. Finally, we summarized TB prevention, diagnosis, and treatment challenges and put forward future perspectives. Overall, these findings provide valuable insights into the immunological aspects of TB and offer new directions toward achieving the WHO's goal of eradicating TB by 2035.

A novel chemokine biomarker to distinguish active tuberculosis from latent tuberculosis: a cohort study

BACKGROUND

Interferon-γ release assays (IGRAs), which are widely used to diagnose tuberculosis (TB), cannot effectively discriminate latent TB infection (LTBI) from active TB (ATB). This study aimed to identify potential antigen-specific biomarkers for differentiating LTBI cases from ATB cases.

METHODS

Ongoing recruitment was conducted of individuals meeting study inclusion criteria at Beijing Chest Hospital from May 2020 to April 2022; 208 participants were enrolled and assigned to three groups: HC (60 healthy controls), LTBI (52 subjects with LTBI) and ATB (96 ATB patients). After participants were assigned to the discovery cohort (20 or 21 subjects/group), all others were assigned to the verification cohort. Discovery cohort blood levels of 40 chemokines were measured using Luminex assays to identify chemokines that could be used to discriminate LTBI cases from ATB cases; candidate biomarkers were verified using enzyme-linked immunosorbent assay-based testing of validation cohort samples.

RESULTS

Luminex results revealed highest ATB group levels of numerous cytokines, growth factors and chemokines. Receiving operating characteristic curve-based analysis of 40 biomarkers revealed CCL8 (AUC = 0.890) and CXCL9 (AUC = 0.883) effectively discriminated between LTBI and TB cases; greatest diagnostic efficiency was obtained using both markers together (AUC = 0.929). Interpretation of CCL8 and CXCL9 levels for validation cohort IGRA-positive subjects (based on a 0.658-ng/ml cutoff) revealed ATB group CCL8-based sensitivity and specificity rates approaching 90.79% and 100.00%, respectively.

CONCLUSION

TB-specific chemokines hold promise as ATB diagnostic biomarkers. Additional laboratory confirmation is needed to establish whether CCL8-based assays can differentiate between ATB and LTBI cases, especially for bacteriologically unconfirmed TB cases.

Pathogenicity and virulence of Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, an infectious disease with one of the highest morbidity and mortality rates worldwide. Leveraging its highly evolved repertoire of non-protein and protein virulence factors, Mtb invades through the airway, subverts host immunity, establishes its survival niche, and ultimately escapes in the setting of active disease to initiate another round of infection in a naive host. In this review, we will provide a concise synopsis of the infectious life cycle of Mtb and its clinical and epidemiologic significance. We will also take stock of its virulence factors and pathogenic mechanisms that modulate host immunity and facilitate its spread. Developing a greater understanding of the interface between Mtb virulence factors and host defences will enable progress toward improved vaccines and therapeutics to prevent and treat tuberculosis.

Prevalence of indeterminate tuberculosis interferon-gamma release assays in COVID-19 patients: Systematic review and meta-analysis

Background and Aims

The reliability of interferon-gamma-release-assays (IGRAs) for tuberculosis (TB) testing in coronavirus disease 2019 (COVID-19) patients is unknown. This study aimed to systematically review the prevalence of indeterminate TB-IGRA following SARS-CoV-2 infection or vaccination and to review associated factors.

Methods

This systematic literature review was guided according to the PRISMA guidelines by searching PubMed, Scopus, Web of Science, Clinicalkey, and Cochrane Library. Studies reporting results of TB-IGRA tests (QuantiFERON [QFT]-TB, T-SPOT.TB) in COVID-19 patients or vaccines were included. The random effects model was used to assess the prevalence of indeterminate IGRA results. Heterogeneity was evaluated using the Τ 2 and 95% predictive interval.

Results

Of the 273 citations screened, 12 articles were included in the final analysis including a total of 2107 patients. The overall pooled effect size proportion of indeterminate QFT-TB results, estimated in eight studies using the QFT-TB Plus assay, was 0.26 (95% CI: 0.205-0.324, Τ 2 = 0.158). The mean true effect size was 0.26 (95% predictive interval: [0.110-0.500]). A subgroup analysis was not undertaken due to the small number of studies. Indeterminate QFT-TB rates were associated with COVID-19 severity, steroid treatment, inflammation-related parameters, neutrophilia, and lymphopenia.

Conclusion

Indeterminate QFT-TB results in COVID-19 patients occur in almost one-quarter of tests performed. Further studies are needed to assess associated factors.

Near-infrared molecular sensor for visualizing and tracking ONOO- during the process of anti-tuberculosis drug-induced liver damage

Isoniazid (INH) and pyrazinamide (PZA) are both the first-line anti-tuberculosis drugs in clinical treatment. It is notable that there are serious side effects of the drugs along with upregulation of reactive nitrogen species, mainly including peripheral neuritis, gastrointestinal reactions, and acute drug-induced liver injury (DILI). Among them, DILI is the most common clinical symptom as well as the basic reason of treatment interruption, protocol change, and drug resistance. As vital reactive nitrogen species (RNS), peroxynitrite (ONOO-) has been demonstrated as a biomarker for evaluation and pre-diagnosis of drug-induced liver injury (DILI). In this work, we developed a red-emitting D-π-A type fluorescence probe DIC-NP which was based on 4'-hydroxy-4-biphenylcarbonitrile modified with dicyanoisophorone as a fluorescent reporter and diphenyl phosphinic chloride group as the reaction site for highly selective and sensitive sensing ONOO-. Probe DIC-NP displayed a low detection limit (14.9 nM) and 60-fold fluorescent enhancement at 669 nm in the sensing of ONOO-. Probe DIC-NP was successfully applied to monitor exogenous and endogenous ONOO- in living HeLa cells and zebrafish. Furthermore, we verified the toxicity of isoniazid (INH) and pyrazinamide (PZA) by taking the oxidative stress induced by APAP as a reference, and successfully imaged anti-tuberculosis drug-induced endogenous ONOO- in HepG2 cells. More importantly, we developed a series of mice models of liver injury and investigated the hepatotoxicity caused by the treatment of anti-tuberculosis drugs. At the same time, H&E of mice organs (heart, liver, spleen, lung, kidney) further confirmed the competence of probe DIC-NP for estimating the degree of drug-induced liver injury, which laid a solid foundation for medical research.

From immunology to artificial intelligence: revolutionizing latent tuberculosis infection diagnosis with machine learning

Latent tuberculosis infection (LTBI) has become a major source of active tuberculosis (ATB). Although the tuberculin skin test and interferon-gamma release assay can be used to diagnose LTBI, these methods can only differentiate infected individuals from healthy ones but cannot discriminate between LTBI and ATB. Thus, the diagnosis of LTBI faces many challenges, such as the lack of effective biomarkers from Mycobacterium tuberculosis (MTB) for distinguishing LTBI, the low diagnostic efficacy of biomarkers derived from the human host, and the absence of a gold standard to differentiate between LTBI and ATB. Sputum culture, as the gold standard for diagnosing tuberculosis, is time-consuming and cannot distinguish between ATB and LTBI. In this article, we review the pathogenesis of MTB and the immune mechanisms of the host in LTBI, including the innate and adaptive immune responses, multiple immune evasion mechanisms of MTB, and epigenetic regulation. Based on this knowledge, we summarize the current status and challenges in diagnosing LTBI and present the application of machine learning (ML) in LTBI diagnosis, as well as the advantages and limitations of ML in this context. Finally, we discuss the future development directions of ML applied to LTBI diagnosis.

Advanced drug delivery and therapeutic strategies for tuberculosis treatment

Tuberculosis (TB) remains a significant global health challenge, necessitating innovative approaches for effective treatment. Conventional TB therapy encounters several limitations, including extended treatment duration, drug resistance, patient noncompliance, poor bioavailability, and suboptimal targeting. Advanced drug delivery strategies have emerged as a promising approach to address these challenges. They have the potential to enhance therapeutic outcomes and improve TB patient compliance by providing benefits such as multiple drug encapsulation, sustained release, targeted delivery, reduced dosing frequency, and minimal side effects. This review examines the current landscape of drug delivery strategies for effective TB management, specifically highlighting lipid nanoparticles, polymer nanoparticles, inorganic nanoparticles, emulsion-based systems, carbon nanotubes, graphene, and hydrogels as promising approaches. Furthermore, emerging therapeutic strategies like targeted therapy, long-acting therapeutics, extrapulmonary therapy, phototherapy, and immunotherapy are emphasized. The review also discusses the future trajectory and challenges of developing drug delivery systems for TB. In conclusion, nanomedicine has made substantial progress in addressing the challenges posed by conventional TB drugs. Moreover, by harnessing the unique targeting abilities, extended duration of action, and specificity of advanced therapeutics, innovative solutions are offered that have the potential to revolutionize TB therapy, thereby enhancing treatment outcomes and patient compliance.

Identification and validation of a pyroptosis-related signature in identifying active tuberculosis via a deep learning algorithm

Introduction

Active tuberculosis (ATB), instigated by Mycobacterium tuberculosis (M.tb), rises as a primary instigator of morbidity and mortality within the realm of infectious illnesses. A significant portion of M.tb infections maintain an asymptomatic nature, recognizably termed as latent tuberculosis infections (LTBI). The complexities inherent to its diagnosis significantly hamper the initiatives aimed at its control and eventual eradication.

Methodology

Utilizing the Gene Expression Omnibus (GEO), we procured two dedicated microarray datasets, labeled GSE39940 and GSE37250. The technique of weighted correlation network analysis was employed to discern the co-expression modules from the differentially expressed genes derived from the first dataset, GSE39940. Consequently, a pyroptosis-related module was garnered, facilitating the identification of a pyroptosis-related signature (PRS) diagnostic model through the application of a neural network algorithm. With the aid of Single Sample Gene Set Enrichment Analysis (ssGSEA), we further examined the immune cells engaged in the pyroptosis process in the context of active ATB. Lastly, dataset GSE37250 played a crucial role as a validating cohort, aimed at evaluating the diagnostic prowess of our model.

Results

In executing the Weighted Gene Co-expression Network Analysis (WGCNA), a total of nine discrete co-expression modules were lucidly elucidated. Module 1 demonstrated a potent correlation with pyroptosis. A predictive diagnostic paradigm comprising three pyroptosis-related signatures, specifically AIM2, CASP8, and NAIP, was devised accordingly. The established PRS model exhibited outstanding accuracy across both cohorts, with the area under the curve (AUC) being respectively articulated as 0.946 and 0.787.

Conclusion

The present research succeeded in identifying the pyroptosis-related signature within the pathogenetic framework of ATB. Furthermore, we developed a diagnostic model which exuded a remarkable potential for efficient and accurate diagnosis.

Latent Tuberculosis: Challenges in Diagnosis and Treatment, Perspectives, and the Crucial Role of Biomarkers

Tuberculosis (TB) is the major cause of morbidity and mortality globally, which is caused by a single infectious agent Mycobacterium tuberculosis. For years, many TB control programmes are established for effective diagnosis and treatment of active TB cases, but these approaches alone are insufficient for TB eradication. This review aims to discourse on the crucial management of latent tuberculosis infection. This review will first summarize the current status, and methods for diagnosing latent tuberculosis then describes the challenges involved in the diagnosis and treatment of latent tuberculosis, and finally encounters the purpose of biomarkers as predicting tool in latent tuberculosis.

Immunotherapy and biomarkers in patients with lung cancer with tuberculosis: Recent advances and future Directions

Lung cancer (LC) and tuberculosis (TB) are two major global public health problems, and the incidence of LC-TB is currently on the rise. Therefore effective clinical interventions are crucial for LC-TB. The aim of this review is to provide up-to-date information on the immunological profile and therapeutic biomarkers in patients with LC-TB. We discuss the immune mechanisms involved, including the immune checkpoints that play an important role in the treatment of patients with LC-TB. In addition, we explore the susceptibility of patients with LC to TB and summarise the latest research on LC-TB. Finally, we discuss future prospects in this field, including the identification of potential targets for immune intervention. In conclusion, this review provides important insights into the complex relationship between LC and TB and highlights new advances in the detection and treatment of both diseases.

Primary Tuberculosis of Buccal and Labial Mucosa: Literature Review and a Rare Case Report of a Public Health Menace

Tuberculosis (TB) is a chronic granulomatous infectious disorder, caused by Mycobacterium tuberculosis. Despite the recent advancements in antitubercular therapy (ATT), it remains a global public health concern. TB is a leading infectious cause of global mortality, second only to coronavirus disease 2019 (COVID-19). TB of the oral cavity is an uncommon occurrence and may be classified as a primary and secondary form. The primary tubercular lesions are extremely rare, as the intact oral squamous epithelium resists the entry of tubercle bacilli. The commonest oral TB lesion is solitary ulceration with undermined edges, usually on the tongue, that does not exhibit healing with conservative therapies. Owing to the atypical presentation, the oral TB lesions often go unnoticed during clinical examination; hence, an oral physician should be familiar with the various oral manifestations of TB. A timely diagnosis coupled with interdisciplinary treatment is the key to combat disease dissemination. This manuscript aims to report a rare case of primary tuberculosis of the buccal and labial mucosa in a 43-year-old immunocompetent male patient. Buccal and labial mucosa are the infrequently affected sites for primary oral TB lesions. A detailed literature search carried out on the Google Scholar and PubMed search engines revealed only fifteen case reports and two case series of primary tuberculosis of the buccal mucosa and labial mucosa.

Evaluation of the diagnostic efficacy of EC-Test for latent tuberculosis infection in ambulatory people with HIV

BACKGROUND

Latent tuberculosis infection (LTBI) co-infected with human immunodeficiency virus (HIV) is more likely to develop into active tuberculosis (ATB), recombinant Mycobacterium tuberculosis fusion protein ESAT6/CFP10 (EC-Test) is a latest developed method for LTBI. Compared with the interferon γ release test assays (IGRAs), the diagnostic performance of EC-Test to LTBI screening in HIV needs to be evaluated.

METHODS

A population-based multicenter prospective study was conducted in Guangxi Province, China. The baseline data was collected and LTBI were measured by QuantiFERON-TB Gold In-Tube (QFT-GIT), EC-Test and T-cell spot of the TB assay (T-SPOT.TB).

RESULTS

A total of 1478 patients were enrolled. when taking T-SPOT.TB as reference, the value of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and consistency that EC-Test to diagnosis LTBI in HIV was 40.42, 97.98, 85.26, 85.04 and 85.06% respectively; when taking QFT-GIT as reference, the value was 36.00, 92.57, 55.10, 85.09 and 81.13%, respectively. When the CD4 + cell count was <200 cells/μl, the accuracies of EC-Test to T-SPOT.TB and QFT-GIT were 87.12 and 88.89%, respectively; when it was 200 ≤ CD4 + ≤ 500 cells/μl, the accuracies of EC-Test was 86.20 and 83.18%, respectively; when the CD4 + cell count >500 cells/μl, the accuracies of EC-Test were 84.29 and 77.94%, respectively. The incidence of adverse reactions in EC-Test was 34.23% and the serious adverse reactions were 1.15%.

CONCLUSION

EC-Test has good consistency compared with IGRAs in detecting LTBI in HIV no matter in different immunosuppression status or different regions, and the safety of EC-Test is also well, suitable for LTBI screening in HIV in high prevalence settings.

Single-Cell Transcriptomics of Mtb/HIV Co-Infection

Tuberculosis (TB) and Human Immunodeficiency Virus (HIV) co-infection continues to pose a significant healthcare burden. HIV co-infection during TB predisposes the host to the reactivation of latent TB infection (LTBI), worsening disease conditions and mortality. There is a lack of biomarkers of LTBI reactivation and/or immune-related transcriptional signatures to distinguish active TB from LTBI and predict TB reactivation upon HIV co-infection. Characterizing individual cells using next-generation sequencing-based technologies has facilitated novel biological discoveries about infectious diseases, including TB and HIV pathogenesis. Compared to the more conventional sequencing techniques that provide a bulk assessment, single-cell RNA sequencing (scRNA-seq) can reveal complex and new cell types and identify more high-resolution cellular heterogeneity. This review will summarize the progress made in defining the immune atlas of TB and HIV infections using scRNA-seq, including host-pathogen interactions, heterogeneity in HIV pathogenesis, and the animal models employed to model disease. This review will also address the tools needed to bridge the gap between disease outcomes in single infection vs. co-infection. Finally, it will elaborate on the translational benefits of single-cell sequencing in TB/HIV diagnosis in humans.

Spatial-temporal patterns and influencing factors for pulmonary tuberculosis transmission in China: an analysis based on 15 years of surveillance data

Profiting from a series of anti-tuberculosis programs in China, the number of tuberculosis (TB) cases has diminished dramatically in the past decades. However, long-term spatial-temporal variations, regional trends of prevalence, and mechanisms of determinant factors remain unclear. Age-period-cohort analysis and Bayesian space-time hierarchy statistics were conducted to identify high-risk populations and areas in mainland China, and the geographical detector model was used to evaluate the important drivers of the disease. The prevalence of pulmonary TB has declined from 73.3/100,000 in 2004 to 55.45/100,000 in 2018. A bimodal distribution was found in age groups, and the birth cohorts before 1978 had relative higher risk. The high-risk areas were mainly distributed in western China and south-central China, and several provinces in eastern China showed a potential increasing trend, including Beijing, Shanghai, Liaoning, and Guangdong province. The index of night light (Q = 0.46), the population density (Q = 0.41), PM10 (Q = 0.38), urbanization rate (Q = 0.32), and PM 2.5 (Q = 0.31) contributed substantially to the spatial distribution of pulmonary tuberculosis. The identifications of epidemic patterns, high-risk areas and influence factors would help design targeted intervention measures to achieve milestones of the end TB strategy.

Safety of secukinumab in the treatment of patients with axial spondyloarthritis and concurrent hepatitis B virus infection or latent tuberculosis infection

OBJECTIVE

To evaluate the safety of secukinumab (SEC) in the treatment of patients with axial spondyloarthritis (axSpA) and concurrent hepatitis B virus (HBV) infection or latent tuberculosis infection (LTBI).

METHODS

This is a retrospective cohort study. Adult axSpA patients with HBV infection or LTBI receiving SEC treatment for at least 3 months from March 2020 to July 2022 in Guangdong Provincial People's Hospital were included. Patients were screened for HBV infection and LTBI before SEC treatment. During follow-up, reactivation of HBV infection and LTBI was monitored. Relevant data were collected and analyzed.

RESULTS

A total of 43 axSpA patients with HBV infection or LTBI were included, of whom 37 were with HBV infection, 6 were with LTBI. Six out of thirty-seven (16.2%) patients with axSpA and concurrent HBV infection exhibited HBV reactivation after 9.0 ± 5.7 months of SEC treatment. Among them, 3 patients had chronic HBV infection and received anti-HBV prophylaxis, 2 patients had chronic HBV infection but did not receive anti-HBV prophylaxis, and 1 patient had occult HBV infection and did not receive antiviral prophylaxis. None of the 6 axSpA patients with LTBI developed reactivation of LTBI, whether received anti-TB prophylaxis or not.

CONCLUSIONS

HBV reactivation can occur in axSpA patients with different types of HBV infection undergoing SEC treatment, whether receive antiviral prophylaxis or not. Close monitoring of HBV reactivation in axSpA patients with HBV infection undergoing SEC treatment is mandatory. Anti-HBV prophylaxis may be beneficial. In contrast, SEC may be safe in axSpA patients with LTBI, even in patients not receiving anti-TB prophylaxis. Key Points •Currently, most evidence about the safety of SEC in patients with HBV infection and LTBI were from patients with psoriasis. Our study adds data about the safety of SEC in Chinese axSpA patients with concurrent HBV infection or LTBI in real-world clinical setting. •Our study showed that HBV reactivation can occur in axSpA patients with different types of HBV infection undergoing SEC treatment, whether receive antiviral prophylaxis or not. •Close monitoring of serum HBV markers, HBV DNA load, and liver function is mandatory in axSpA patients with chronic, occult, and resolved HBV infection undergoing SEC treatment. Anti-HBV prophylaxis may be beneficial in all HBsAg-positive patients and HBsAg-negative, HBcAb-positive patients at high risk of HBV reactivation who are receiving SEC therapy. •None of the axSpA patients with LTBI, whether received anti-TB prophylaxis or not, developed reactivation of LTBI in our study. SEC may be safe in axSpA patients with LTBI, even in patients not receiving anti-TB prophylaxis.

Advances in protein subunit vaccines against tuberculosis

Tuberculosis (TB), also known as the "White Plague", is caused by Mycobacterium tuberculosis (Mtb). Before the COVID-19 epidemic, TB had the highest mortality rate of any single infectious disease. Vaccination is considered one of the most effective strategies for controlling TB. Despite the limitations of the Bacille Calmette-Guérin (BCG) vaccine in terms of protection against TB among adults, it is currently the only licensed TB vaccine. Recently, with the evolution of bioinformatics and structural biology techniques to screen and optimize protective antigens of Mtb, the tremendous potential of protein subunit vaccines is being exploited. Multistage subunit vaccines obtained by fusing immunodominant antigens from different stages of TB infection are being used both to prevent and to treat TB. Additionally, the development of novel adjuvants is compensating for weaknesses of immunogenicity, which is conducive to the flourishing of subunit vaccines. With advances in the development of animal models, preclinical vaccine protection assessments are becoming increasingly accurate. This review summarizes progress in the research of protein subunit TB vaccines during the past decades to facilitate the further optimization of protein subunit vaccines that may eradicate TB.

The Use of Particulate Systems for Tuberculosis Prophylaxis and Treatment: Opportunities and Challenges

The use of particles to develop vaccines and treatments for a wide variety of diseases has increased, and their success has been demonstrated in preclinical investigations. Accurately targeting cells and minimizing doses and adverse side effects, while inducing an adequate biological response, are important advantages that particulate systems offer. The most used particulate systems are liposomes and their derivatives, immunostimulatory complexes, virus-like particles, and organic or inorganic nano- and microparticles. Most of these systems have been proven using therapeutic or prophylactic approaches to control tuberculosis, one of the most important infectious diseases worldwide. This article reviews the progress and current state of the use of particles for the administration of TB vaccines and treatments in vitro and in vivo, with a special emphasis on polymeric particles. In addition, we discuss the challenges and benefits of using these particulate systems to provide researchers with an overview of the most promising strategies in current preclinical trials, offering a perspective on their progress to clinical trials.

Next-Generation TB Vaccines: Progress, Challenges, and Prospects

Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), is a prevalent global infectious disease and a leading cause of mortality worldwide. Currently, the only available vaccine for TB prevention is Bacillus Calmette-Guérin (BCG). However, BCG demonstrates limited efficacy, particularly in adults. Efforts to develop effective TB vaccines have been ongoing for nearly a century. In this review, we have examined the current obstacles in TB vaccine research and emphasized the significance of understanding the interaction mechanism between MTB and hosts in order to provide new avenues for research and establish a solid foundation for the development of novel vaccines. We have also assessed various TB vaccine candidates, including inactivated vaccines, attenuated live vaccines, subunit vaccines, viral vector vaccines, DNA vaccines, and the emerging mRNA vaccines as well as virus-like particle (VLP)-based vaccines, which are currently in preclinical stages or clinical trials. Furthermore, we have discussed the challenges and opportunities associated with developing different types of TB vaccines and outlined future directions for TB vaccine research, aiming to expedite the development of effective vaccines. This comprehensive review offers a summary of the progress made in the field of novel TB vaccines.

LTBI-negative close contacts of tuberculosis are more likely to develop the disease: enlightenment and lessons from a cluster outbreak

Background

Tuberculosis (TB) prevention and control among groups living together, such as students, workers, older adults in nursing homes, and prisoners, present many challenges due to their particular age and environmental factors, which can make them more susceptible to TB clusters with significant societal impact. This study aimed to evaluate a TB cluster outbreak epidemic in a university and provide suggestions for improving TB control strategies for groups living together.

Methods

Pulmonary TB screening and close-contact investigation were conducted using acid-fast staining, sputum culture, GeneXpert testing, tuberculin skin testing (TST), interferon-gamma release assay (IGRA), and chest computed tomography (CT). GraphPad Prism 9.5.1 was utilized for data analysis. Collected epidemic data were comprehensively analyzed by rate comparison.

Results

The TB cluster outbreak epidemic was identified with an index case confirmed positive. The initial screening was conducted on potential close contacts of the index case, and the TST's positive rate (diameter ≥ 5 mm) and strong positive rate (diameter ≥ 15 mm) among these close contacts were 65.60% (21/32) and 34.40% (11/32), respectively. Moreover, the latent TB infection (LTBI) rate (diameter ≥ 10 mm) was 43.75% (14/32), and the IGRA's positive rate was 9.30% (3/32). Chest CT scans did not reveal any abnormalities. Surprisingly, 5 of the close contacts developed active TB in the second screening, accompanied by changes from negative to positive TST and/or IGRA results, after 3 months of follow-up. Accordingly, we expanded the screening scope to include another 28 general contacts. We found that the positive rate (78.00%, 25/32), strong positive rate (50.00%, 16/32), and LTBI rate (62.50%, 20/32) of the 32 close contacts were significantly higher than those of the additional general contacts (28.00%, 8/28; 14.3%, 4/28; 25.00%, 7/28), as indicated by p < 0.05.

Conclusion

In the event of an epidemic TB outbreak, it is essential to rapidly identify the source of infection and initiate timely screening of close contacts. The initial screening should be focused on individuals without LTBI, who are at higher risk of developing TB. In purified protein derivative-negative individuals living in groups, additional vaccination or revaccination with Bacille Calmette-Guérin may help prevent cluster outbreaks of TB.

Characterization of peripheral cytokine-secreting cells responses in HIV/TB co-infection

Background

Currently the responses of peripheral cytokine-secreting cells in the natural course of human immunodeficiency virus (HIV) and tuberculosis (TB) co-infection haven't been fully elucidated.

Methods

The function of peripheral proinflammatory, regulatory and cytotoxic cytokine-secreting cells were investigated by direct intracellular cytokine staining (ICS) and flow cytometry, additionally, the absolute numbers of different cytokine-secreting cells were measured among patients with HIV/TB co-infection (HT group), and compared them with the healthy controls (HC group), patients with TB (TB group) and patients with HIV infection (HIV group). After one week's anti-TB treatment, the changes of the percentages of cytokine-secreting cells were further evaluated in TB and HT groups.

Results

Totally 26 individuals in the HC group, 51 in the TB group, 26 in the HIV group and 29 in the HT group were enrolled. The HT. HT group exhibited significantly lower absolute numbers of IFN-γ⁺CD4⁺, IFN-γ⁺CD8⁺, TNF-α⁺CD4⁺, IL17A⁺CD4⁺ T cells and TNF-α⁺CD14⁺ monocytes than the TB and HIV groups. Compared with the TB group, the percentages of CD8⁺ T cells secreting IFN-γ and perforin (p=0.010; p=0.043) were significantly lower among the HT group. Compared with the HIV group, the percentages of CD4⁺, CD8⁺ T cells and CD14⁺ monocytes secreting TNF-α (p=0.013; p=0.001; p<0.001) were significantly decreased, and the percentage of CD8⁺ T cells secreting IL-17A (p=0.015) was significantly increased among the HT group. Both the percentages of CD4⁺ T cells secreting TGF-β (p<0.001; p=0.001), and CD4⁺ and CD8⁺ T cells secreting granzyme A (all p<0.001), were significantly higher among the HT group than among the TB group and HIV group. After one week's anti-TB treatment, an increased percentage of CD4⁺ T cells secreting TNF-α (p=0.003) was found in the TB group, and an increased percentage of CD8⁺ T cells secreting TNF-α (p=0.029) was found in the HT group.

Conclusion

Significantly different functional profiles of peripheral proinflammatory, regulatory, and cytotoxic cytokine-secreting cells were observed in the natural course of HIV/TB co-infection compared to TB and HIV infection alone, even though the absolute numbers of those cells were significantly lower in HIV/TB co-infection. TNF-α-secreting CD8⁺ T cells may be a more sensitive marker for early evaluation of anti-TB treatment efficacy in patients with HIV/TB co-infection.

PP19128R, a Multiepitope Vaccine Designed to Prevent Latent Tuberculosis Infection, Induced Immune Responses In Silico and In Vitro Assays

Background: Latent tuberculosis infection (LTBI) is the primary source of active tuberculosis (ATB), but a preventive vaccine against LTBI is lacking. Methods: In this study, dominant helper T lymphocyte (HTL), cytotoxic T lymphocyte (CTL), and B-cell epitopes were identified from nine antigens related to LTBI and regions of difference (RDs). These epitopes were used to construct a novel multiepitope vaccine (MEV) based on their antigenicity, immunogenicity, sensitization, and toxicity. The immunological characteristics of the MEV were analyzed with immunoinformatics technology and verified by enzyme-linked immunospot assay and Th1/Th2/Th17 cytokine assay in vitro. Results: A novel MEV, designated PP19128R, containing 19 HTL epitopes, 12 CTL epitopes, 8 B-cell epitopes, toll-like receptor (TLR) agonists, and helper peptides, was successfully constructed. Bioinformatics analysis showed that the antigenicity, immunogenicity, and solubility of PP19128R were 0.8067, 9.29811, and 0.900675, respectively. The global population coverage of PP19128R in HLA class I and II alleles reached 82.24% and 93.71%, respectively. The binding energies of the PP19128R-TLR2 and PP19128R-TLR4 complexes were -1324.77 kcal/mol and -1278 kcal/mol, respectively. In vitro experiments showed that the PP19128R vaccine significantly increased the number of interferon gamma-positive (IFN-γ⁺) T lymphocytes and the levels of cytokines, such as IFN-γ, tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and IL-10. Furthermore, positive correlations were observed between PP19128R-specific cytokines in ATB patients and individuals with LTBI. Conclusions: The PP19128R vaccine is a promising MEV with excellent antigenicity and immunogenicity and no toxicity or sensitization that can induce robust immune responses in silico and in vitro. This study provides a vaccine candidate for the prevention of LTBI in the future.

Convolutional neural network based on T-SPOT.TB assay promoting the discrimination between active tuberculosis and latent tuberculosis infection

OBJECTIVES

The study aims to investigate the potential of convolutional neural network (CNN) based on spot image of T-SPOT assay for distinguishing active tuberculosis (ATB) from latent tuberculosis infection (LTBI).

METHODS

CNN was applied to recognize and classify T-SPOT spot image. Logistic regression was used to establish prediction model based on CNN.

RESULTS

Areas under the receiver operating characteristic curve (AUCs) of early secreted antigenic target 6 (ESAT-6) CNN, culture filtrate protein 10 (CFP-10) CNN, and phytohemagglutinin (PHA) CNN were more than 0.7 in differentiating ATB from LTBI, while the performance of these indicators was significantly better than that of spot number. Furthermore, prediction model based on the combination of CNNs yielded an AUC of 0.898. The model presented a sensitivity of 85.76% and a specificity of 90.23%.

CONCLUSIONS

The current study identified CNN based on T-SPOT spot image with the potential to serve as a tool for TB diagnostics.

A diagnostic model for distinguishing between active tuberculosis and latent tuberculosis infection based on the blood expression profiles of autophagy-related genes

BACKGROUND

Autophagy is closely involved in the control of mycobacterial infection.

OBJECTIVES

Here, a diagnostic model was developed using the levels of autophagy-related genes (ARGs) in the blood to differentiate active tuberculosis (ATB) and latent tuberculosis infection (LTBI).

DESIGN

Secondary data analysis of three prospective cohorts.

METHODS

The expression of ARGs in patients with ATB and LTBI were analyzed using the GSE37250, GSE19491, and GSE28623 datasets from the GEO database.

RESULTS

Twenty-two differentially expressed ARGs were identified in the training dataset GSE37250. Using least absolute shrinkage and selection operator and multivariate logistic regression, three ARGs (FOXO1, CCL2, and ITGA3) were found that were positively associated with adaptive immune-related lymphocytes and negatively associated with myeloid and inflammatory cells. A nomogram was constructed using the three ARGs. The accuracy, consistency, and clinical relevance of the nomogram were evaluated using receiver operating characteristic curves, the C-index, calibration curves, and validation in the datasets GSE19491 and GSE28623. The nomogram showed good predictive performance.

CONCLUSION

The nomogram was able to accurately differentiate between ATB and LTBI patients. These findings provide evidence for future study on the pathology of autophagy in tuberculosis infection.

Development of diagnostic algorithm using machine learning for distinguishing between active tuberculosis and latent tuberculosis infection

BACKGROUND

The discrimination between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging. The present study aims to investigate the value of diagnostic models established by machine learning based on multiple laboratory data for distinguishing Mycobacterium tuberculosis (Mtb) infection status.

METHODS

T-SPOT, lymphocyte characteristic detection, and routine laboratory tests were performed on participants. Diagnostic models were built according to various algorithms.

RESULTS

A total of 892 participants (468 ATB and 424 LTBI) and another 263 participants (125 ATB and 138 LTBI), were respectively enrolled at Tongji Hospital (discovery cohort) and Sino-French New City Hospital (validation cohort). Receiver operating characteristic (ROC) curve analysis showed that the value of individual indicator for differentiating ATB from LTBI was limited (area under the ROC curve (AUC) < 0.8). A total of 28 models were successfully established using machine learning. Among them, the AUCs of 25 models were more than 0.9 in test set. It was found that conditional random forests (cforest) model, based on the implementation of the random forest and bagging ensemble algorithms utilizing conditional inference trees as base learners, presented best discriminative power in segregating ATB from LTBI. Specially, cforest model presented an AUC of 0.978, with the sensitivity of 93.39% and the specificity of 91.18%. Mtb-specific response represented by early secreted antigenic target 6 (ESAT-6) and culture filtrate protein 10 (CFP-10) spot-forming cell (SFC) in T-SPOT assay, as well as global adaptive immunity assessed by CD4 cell IFN-γ secretion, CD8 cell IFN-γ secretion, and CD4 cell number, were found to contribute greatly to the cforest model. Superior performance obtained in the discovery cohort was further confirmed in the validation cohort. The sensitivity and specificity of cforest model in validation set were 92.80% and 89.86%, respectively.

CONCLUSIONS

Cforest model developed upon machine learning could serve as a valuable and prospective tool for identifying Mtb infection status. The present study provided a novel and viable idea for realizing the clinical diagnostic application of the combination of machine learning and laboratory findings.

The Subunit AEC/BC02 Vaccine Combined with Antibiotics Provides Protection in Mycobacterium tuberculosis-Infected Guinea Pigs

A latent tuberculosis infection (LTBI) is a major source of active tuberculosis, and addressing an LTBI is crucial for the elimination of tuberculosis. The treatment of tuberculosis often requires a 6-month course of multidrug therapy, and for drug-resistant tuberculosis, a longer course of multidrug therapy is needed, which has many drawbacks. At present, vaccines are proposed as an adjunct to chemotherapy to protect populations with an LTBI and delay its recurrence. In this study, we analyzed the protective effect of a novel subunit vaccine, AEC/BC02, in a guinea pig latent infection model. Through the optimization of different chemotherapy durations and immunization times, it was found that 4 weeks of administration of isoniazid-rifampin tablets combined with three or six injections of the vaccine could significantly reduce the gross pathological score and bacterial load in organs and improve the pathological lesions. This treatment regimen had a better protective effect than the other administration methods. Furthermore, no drug resistance of Mycobacterium tuberculosis was detected after 2 or 4 weeks of administration of the isoniazid-rifampin tablets, indicating a low risk of developing drug-resistant bacteria during short-term chemotherapy. The above results provided the foundation for an AEC/BC02 clinical protocol.

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.

Cost effectiveness analysis of single and sequential testing strategies for tuberculosis infection in adults living with HIV in the United States

Tuberculosis infection (TBI) frequently progresses to tuberculosis (TB) disease in people co-infected with human immunodeficiency virus (HIV). We examined the cost-effectiveness of single, sequential and no testing (total 12) strategies of TBI in HIV-infected people from the perspective of US healthcare provider. A decision-analytic model (20-year timeframe) was constructed to simulate TB-related outcomes: Direct medical cost and quality-adjusted life-years (QALYs). In the base-case analysis, the "confirm negative TST followed by QFT-Plus" strategy gained 0.1170 QALY at a total cost of USD3377. In the probabilistic sensitivity analysis of 10,000 Monte Carlo simulations, the probability of "confirm negative TST followed by QFT-Plus" to be accepted as cost-effective was the highest of all 12 strategies when the willingness-to-pay threshold exceeded 2340 USD/QALY. In conclusion, the strategy of "confirm negative TST followed by QFT-Plus" appears to be the preferred cost-effective option for TBI testing in HIV-infected people from the US healthcare provider's perspective.

Effect of Lymphocyte Subsets on Bone Density in Senile Osteoporosis: A Retrospective Study

Background

Several studies have shown that lymphocyte subsets can mediate the occurrence of osteoporosis (OP); however, the predictive ability of lymphocyte subsets in senile OP has not been elucidated.

Purpose

To investigate the ability of lymphocyte subsets to predict senile osteoporosis (OP).

Methods and Materials

This study included 44 patients with senile OP and 44 without OP. Dual-energy X-ray absorptiometry (DEXA) was used to determine bone mineral density (BMD). Flow cytometry was used to analyze the absolute counts of the lymphocyte subsets and cytokine levels. Finally, the correlation between BMD and lymphocyte subset counts in the two groups was analyzed.

Results

There were no significant differences in age, sex, or weight between the OP and non-OP groups. The absolute counts of total T lymphocytes and CD8+ T lymphocytes in the OP group were significantly lower than those in the non-OP group. The levels of IFN-γ or TNF-α in the OP group were significantly higher or lower, respectively, than those in the non-OP group. PCA showed that age, BMI, total T lymphocytes, CD4+ T lymphocytes, CD8+ T lymphocytes, and B lymphocytes were the principal components of senile OP. The linear regression equation showed that BMD of the right femoral neck significantly decreased with a decline in CD8+ T lymphocyte counts.

Conclusion

BMD decreased with a decrease in CD8+ T lymphocytes. The mechanism by which lower lymphocyte subsets lead to lower BMD may be related to abnormal bone metabolism caused by immune aging. Therefore, we considered that CD8+ T lymphocytes could be used to predict the incidence of senile OP.

An insight into the discovery, clinical studies, compositions, and patents of macozinone: A drug targeting the DprE1 enzyme of Mycobacterium tuberculosis

Decaprenyl-phosphoryl-ribose 2'-epimerase (DprE1) inhibitors are an innovative and futuristic orally active group of antituberculosis agents. A few DprE1 inhibitors are in the clinical trial for tuberculosis (TB), including macozinone. This review highlights the discovery, developmental status, clinical studies, patents, and prospects of macozinone (MCZ). The patent and non-patent literature search was done by entering keywords such as macozinone; MCZ; PBTZ169; PBTZ-169 in Pubmed, Espacenet, Patentscope, and the USPTO databases. However, data on Sci-Finder was searched using CAS registry number: 1377239-83-2. MCZ clinical trial studies were retrieved from the clinicaltrials.gov database using the exact keywords. The chemical structure of MCZ was disclosed in 2009. Accordingly, patents/patent applications published from 2009 to June 12, 2022, have been discussed herein. MCZ and MCZ hydrochloride salt patents were granted in 2014 and 2019, respectively, in the USA. The patent literature and the clinical trial studies suggest capsule, tablet, and suspension formulations of crystalline MCZ and its hydrochloride salt as the possible and prospective dosage forms to treat TB. Some combinations of MCZ with other drugs (chloroquine, telacebec, tafenoquine, TBI-166, and sanfetrinem) with improved anti-TB efficacy have been documented. Based on the literature covered in this review article on the clinical studies and patents applied/granted to MCZ, it can be inferred that MCZ seems to be a promising DprE1 inhibitor and could help to tackle the emerging dilemma of drug-resistant either as a monotherapy or in combination with additional anti-TB agents. Furthermore, the authors anticipate the development of new combinations, salts, and polymorphs of MCZ as anti-TB agents shortly. This review article might prove beneficial to the scientific community as it summarizes chemistry, pharmacology and provides an update on the clinical studies and patents/patent applications of one of the emerging anti-TB drugs in one place.

Evidence, Challenges, and Knowledge Gaps Regarding Latent Tuberculosis in Animals

Mycobacterium bovis and other Mycobacterium tuberculosis complex (MTBC) pathogens that cause domestic animal and wildlife tuberculosis have received considerably less attention than M. tuberculosis, the primary cause of human tuberculosis (TB). Human TB studies have shown that different stages of infection can exist, driven by host-pathogen interactions. This results in the emergence of heterogeneous subpopulations of mycobacteria in different phenotypic states, which range from actively replicating (AR) cells to viable but slowly or non-replicating (VBNR), viable but non-culturable (VBNC), and dormant mycobacteria. The VBNR, VBNC, and dormant subpopulations are believed to underlie latent tuberculosis (LTB) in humans; however, it is unclear if a similar phenomenon could be happening in animals. This review discusses the evidence, challenges, and knowledge gaps regarding LTB in animals, and possible host-pathogen differences in the MTBC strains M. tuberculosis and M. bovis during infection. We further consider models that might be adapted from human TB research to investigate how the different phenotypic states of bacteria could influence TB stages in animals. In addition, we explore potential host biomarkers and mycobacterial changes in the DosR regulon, transcriptional sigma factors, and resuscitation-promoting factors that may influence the development of LTB.

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.