Diagnostic Accuracy of Monocyte Chemotactic Protein (MCP)-2 as Biomarker in Response to PE35/PPE68 Proteins: A Promising Diagnostic Method for the Discrimination of Active and Latent Tuberculosis

Current approaches for diagnosis of subclinical pulmonary tuberculosis, clinical implications and future perspectives: a scoping review

INTRODUCTION

Subclinical tuberculosis (TB) is the presence of TB disease among people who are either asymptomatic or have minimal symptoms.

AREAS COVERED

Currently, there are no accurate diagnostic tools and clear treatment approaches for subclinical TB. In this study, a comprehensive literature search was conducted across major databases. This review aimed to uncover the latest advancements in diagnostic approaches, explore their clinical implications, and outline potential future perspectives. While innovative technologies are in development to enable sputum-free TB tests, there remains a critical need for precise diagnostic tools tailored to the unique characteristics of subclinical TB. Given the complexity of subclinical TB, a multidisciplinary approach involving clinicians, microbiologists, epidemiologists, and public health experts is essential. Further research is needed to establish standardized diagnostic criteria and treatment guidelines specifically tailored for subclinical TB, acknowledging the unique challenges posed by this elusive stage of the disease.

EXPERT OPINION

Efforts are needed for the detection, diagnosis, and treatment of subclinical TB. In this review, we describe the importance of subclinical TB, both from a clinical and public health perspective and highlight the diagnostic and treatment gaps of this stage.

Immunological Characterization of Proteins Expressed by Genes Located in Mycobacterium tuberculosis-Specific Genomic Regions Encoding the ESAT6-like Proteins

The 6 kDa early secreted antigen target (ESAT6) is a low molecular weight and highly immunogenic protein of Mycobacterium tuberculosis with relevance in the diagnosis of tuberculosis and subunit vaccine development. The gene encoding the ESAT6 protein is located in the M. tuberculosis-specific genomic region known as the region of difference (RD)1. There are 11 M. tuberculosis-specific RDs absent in all of the vaccine strains of BCG, and three of them (RD1, RD7, and RD9) encode immunodominant proteins. Each of these RDs has genes for a pair of ESAT6-like proteins. The immunological characterizations of all the possible proteins encoded by genes in RD1, RD7 and RD9 have shown that, besides ESAT-6 like proteins, several other proteins are major antigens useful for the development of subunit vaccines to substitute or supplement BCG. Furthermore, some of these proteins may replace the purified protein derivative of M. tuberculosis in the specific diagnosis of tuberculosis by using interferon-gamma release assays and/or tuberculin-type skin tests. At least three subunit vaccine candidates containing ESAT6-like proteins as antigen components of multimeric proteins have shown efficacy in phase 1 and phase II clinical trials in humans.

Prevalence and Risk Factors of Latent Tuberculosis Infection (LTBI) in Patients with Type 2 Diabetes Mellitus (T2DM)

Type 2 diabetes mellitus (T2DM) and tuberculosis (TB) together impose a high disease burden in terms of both mortality and health economics worldwide. The objective of this study was to estimate the prevalence and risk factors of latent TB infection (LTBI) in patients with T2DM in Malaysia. A cross-sectional study was performed, and adult T2DM patients (n = 299) were included. Simple and multiple logistic regression analyses were performed to identify the LTBI-associated risk factors in patients with T2DM. Multiple logistic regression was used to estimate adjusted odds ratios (aOR) and 95% confidence intervals (CIs) between T2DM and LTBI and was adjusted for potential confounders. The prevalence of LTBI in patients with T2DM was 11.4% (95% CI: 8.0-15.0%). There was no significant difference in the socio-demographic characteristics between LTBI and non-LTBI subjects. No significant difference in the smoking status, the duration of smoking, and the duration of T2DM, HbA1c, or treatments was observed. Interestingly, a higher level of education was observed to be associated with a lower prevalence of LTBI in T2DM patients (aOR: 0.08, 95% CI: 0.01-0.70, p = 0.02). Although the prevalence of LTBI in T2DM was low, it is important to screen for it in T2DM patients due to the risk of developing severe active TB.

Differential Gene Expression of ASUN, NEMF, PTPRC and DHX29: Candidate Biomarkers for the Diagnosis of Active and Latent Tuberculosis

Tuberculosis (TB) remains one of the most important infectious causes of death throughout the world. A wide range of technologies have been used for the diagnosis of TB. However, current diagnostic tests are inadequate. The aim of this study was to evaluate the expression of four genes, namely ASUN, NEMF, PTPRC and DHX29 as candidate biomarkers for the diagnosis of Latent tuberculosis infection (LTBI) and active TB and discrimination of active TB and LTBI. ; Materials and Methods: The expression of the mentioned four genes as well as ACTB as a housekeeping gene was evaluated by real-time PCR. Receiver operating characteristic (ROC) curve analysis was conducted to assess the specificity and sensitivity of each validated biomarker. ; Results: Our results showed that the expression of theASUN gene could discriminate between active TB cases and healthy BCG vaccinated volunteers with an AUC value of 0.76, combing with a sensitivity of 68% and a specificity of 67%. It should be noted that the PTPRC gene also has the potential for the diagnosis of active TB with an AUC value of 0.67 and a sensitivity of 64.5% and a specificity of 70%. The curve revealed that cases with LTBI could be distinguished from healthy BCG vaccinated volunteers according to their expression of the ASUN gene with an AUC value of 0.81. The cut-off value for diagnosing was 11, with a sensitivity of 73% and a specificity of 79%. Moreover, the expression of the NEMF gene might be considered as a diagnostic tool for the diagnosis of LTBI. The analysis showed an AUC value of 0.75. The highest sensitivity (60%) and specificity (81%) were obtained with a cut off value of 12. ; Conclusion: According to our results, the expression of ASUN and NEMF genes might be considered as a diagnostic tool for the diagnosis of LTBI. Our study showed that the expression of ASUN and PTPRC was obviously higher in active TB patients than those in healthy BCG vaccinated controls. On the other hand, DHX29 and PTPRC genes might be helpful in differentiating active TB and LTBI. However, our findings deserve further validation in larger studies.

ATBdiscrimination: An in Silico Tool for Identification of Active Tuberculosis Disease Based on Routine Blood Test and T-SPOT.TB Detection Results

Tuberculosis remains one of the deadliest infectious diseases worldwide. Only 5-15% of people infected with Mycobacterium tuberculosis develop active TB disease (ATB), while others remain latently infected (LTBI) during their lifetime, which has a completely different clinical treatment schedule. However, most current clinical diagnostic methods are based on the immune response of M. tuberculosis infections and cannot distinguish ATB from LTBIs. Thus, the rapid diagnosis of active or latent tuberculosis infections remains a serious challenge for clinicians. In this work, based on the test data of a total of 478 patients, 36 blood biochemical data were specially included with T-SPOT.TB detection results which are all from routine clinical practice as commercially available. Then a discrimination method to detect ATB infections was successfully developed based on these data by the random forest algorithm. This method presents a robust classification performance with AUC as 0.9256 and 0.8731 for the cross-validation set and the external validation set, respectively. This work suggests an innovative strategy for identification of ATB disease from a single drop of blood with advantages of being timely, efficient, and economical. It also provides valuable information for the comprehensive understanding of TB with deep associations between TB infection and routine blood test data. The web server of this identification method, called ATBdiscrimination, is now available online at http://lishuyan.lzu.edu.cn/ATB/ATBdiscrimination.html .