Evaluation of ESAT6-CFP10 Skin Test for Mycobacterium tuberculosis Infection among Persons Living with HIV in China

Tuberculosis in pregnancy and assisted reproductive technology

Tuberculosis is a chronic infectious disease caused by mycobacterium tuberculosis infection. In the world, tuberculosis is an important factor affecting women's reproductive health, which can cause reproductive tract anatomy abnormalities, embryo implantation obstacles, ovarian reserve and ovulation dysfunction, leading to female infertility. This group of women usually need to seek assisted reproductive technology to conceive. Latent tuberculosis infection during pregnancy has no clinical manifestation, but may develop into active tuberculosis, leading to adverse pregnancy outcomes. Most pregnant women do not need to be treated for latent tuberculosis infection, unless they are combined with high-risk factors for tuberculosis progress, but they need close follow-up. Early diagnosis and treatment of active tuberculosis in pregnancy can reduce the incidence rate and mortality of pregnant women and newborns, and treatment needs multidisciplinary cooperation.

Capturing Recent Mycobacterium tuberculosis Infection by Tuberculin Skin Test vs. Interferon-Gamma Release Assay

Reductions in tuberculosis (TB) incidence require identification of individuals at high risk of developing active disease, such as those with recent Mycobacterium tuberculosis (Mtb) infection. Using a prospective household contact (HHC) study in Kampala, Uganda, we diagnosed new Mtb infection using both the tuberculin skin test (TST) and interferon-gamma release assay (IGRA). Our study aimed to determine if the TST adds additional value to the characterization of IGRA converters. We identified 13 HHCs who only converted the IGRA (QFT-only converters), 39 HHCs who only converted their TST (TST-only converters), and 24 HHCs who converted both tests (QFT/TST converters). Univariate analysis revealed that TST-only converters were older. Additionally, increased odds of TST-only conversion were associated with older age (p = 0.02) and crowdedness (p = 0.025). QFT/TST converters had higher QFT quantitative values at conversion than QFT-only converters and a bigger change in TST quantitative values at conversion than TST-only converters. Collectively, these data indicate that TST conversion alone likely overestimates Mtb infection. Its correlation to older age suggests an "environmental" boosting response due to prolonged exposure to environmental mycobacteria. This result also suggests that QFT/TST conversion may be associated with a more robust immune response, which should be considered when planning vaccine studies.

Is the new tuberculous antigen-based skin test ready for use as an alternative to tuberculin skin test/interferon-gamma release assay for tuberculous diagnosis? A narrative review

In recent years, novel specific Mycobacteria tuberculous (TB) antigen-based skin test (TBST) has become available for clinical use. The mechanism of TBST is similar to the interferon-gamma release assay (IGRA), making it a potential alternative for identifying latent tuberculous infection (LTBI), especially in subjects with history of bacille Calmette-Guérin vaccination. Three different commercial brands have been developed in Denmark, Russia, and China. Clinical studies in the respective countries have shown promising sensitivity, specificity, and safety profile. Some studies attempted to address the applicability of TBST in specific subject groups but the discrepancy in defining LTBI and problematic methodologies undermine the generalisation of the results to other communities across the world. Limited cost-effectiveness studies for TBST have been conducted without exploring the health economics for preventing development of LTBI into active TB. Unlike IGRA, no clinical studies have addressed the correlation of TBST results (magnitude of induration) with the likelihood of development of active TB. Moreover, the different TBSTs are not widely available for clinical use. While TBST is a promising test to overcome the shortcomings of tuberculin skin tests, more clinical data are needed to support its general application globally for the diagnosis of LTBI.

Diagnostic performance of a novel ESAT6-CFP10 skin test for tuberculosis infection in school tuberculosis outbreak in China

Background

The ESAT6-CFP10 (EC) skin test is recommended by the World Health Organization for latent tuberculosis infection (LTBI). However, it is still unknown how the EC skin test performs in students during a school tuberculosis outbreak.

Methods

We conducted an epidemiological investigation to assess the performance of the EC skin test in this high-risk population.

Results

A total of 9 active student patients were confirmed in the same class as the index case, with an incidence rate of 18.0% (9/50). Among the 50 close contacts, 14 (28%) were over 15 years old and had a chest X-ray (CXR), and none of them had abnormal CXR findings. The rates of positive tuberculin skin test (TST) ≥ 5 mm and < 10 mm, ≥ 10 mm and < 15 mm, and ≥ 15 mm were 12.0% (6/50), 16.0% (8/50), and 10.0% (5/50), respectively. On the second screening, 44 students with the same class as the index case had the EC skin test, of which 31 (70.5%) had positive EC tests. All patients had negative sputum smear results, of whom 4 (44.4%) had positive Xpert results; three had a TST induration diameter between 5 mm and 10 mm, but all of them had an EC diameter > 15 mm; 5 (55.6%) had abnormal CXR results, but all the confirmed patients had abnormal CT results; Except for four cases that were diagnosed by Xpert, the remaining five were confirmed by CT scan.

Conclusion

The novel EC skin test performed well in students during the school tuberculosis outbreak. In some special conditions, such as when the index case is bacteriologically positive for tuberculosis and the rate of LTBI is higher than the average for the local same-age group, secondary screening is recommended 2-3 months after the first screening. Furthermore, we cannot ignore the role of CT in the diagnosis of early student tuberculosis.

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.

Molecular Markers of Early Immune Response in Tuberculosis: Prospects of Application in Predictive Medicine

Tuberculosis (TB) remains an important public health problem and one of the leading causes of death. Individuals with latent tuberculosis infection (LTBI) have an increased risk of developing active TB. The problem of the diagnosis of the various stages of TB and the identification of infected patients in the early stages has not yet been solved. The existing tests (the tuberculin skin test and the interferon-gamma release assay) are useful to distinguish between active and latent infections. But these tests cannot be used to predict the development of active TB in individuals with LTBI. The purpose of this review was to analyze the extant data of the interaction of M. tuberculosis with immune cells and identify molecular predictive markers and markers of the early stages of TB. An analysis of more than 90 sources from the literature allowed us to determine various subpopulations of immune cells involved in the pathogenesis of TB, namely, macrophages, dendritic cells, B lymphocytes, T helper cells, cytotoxic T lymphocytes, and NK cells. The key molecular markers of the immune response to M. tuberculosis are cytokines (IL-1β, IL-6, IL-8, IL-10, IL-12, IL-17, IL-22b, IFNɣ, TNFa, and TGFß), matrix metalloproteinases (MMP-1, MMP-3, and MMP-9), and their inhibitors (TIMP-1, TIMP-2, TIMP-3, and TIMP-4). It is supposed that these molecules could be used as biomarkers to characterize different stages of TB infection, to evaluate the effectiveness of its treatment, and as targets of pharmacotherapy.