Transcriptional Profiling of Human Peripheral Blood Mononuclear Cells Identifies Diagnostic Biomarkers That Distinguish Active and Latent Tuberculosis

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.

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.

Transcriptional analysis of human peripheral blood mononuclear cells stimulated by Mycobacterium tuberculosis antigen

Background

Mycobacterium tuberculosis antigen (Mtb-Ag) is a polypeptide component with a molecular weight of 10-14 kDa that is obtained from the supernatant of the H37Ra strain after heat treatment. It stimulates the activation and proliferation of γδT cells in the blood to produce an immune response against tuberculosis. Mtb-Ag is therefore crucial for classifying and detecting the central genes and key pathways involved in TB initiation and progression.

Methods

In this study, we performed high-throughput RNA sequencing of peripheral blood mononuclear cells (PBMC) from Mtb-Ag-stimulated and control samples to identify differentially expressed genes and used them for gene ontology (GO) and a Kyoto Encyclopedia of Genomes (KEGG) enrichment analysis. Meanwhile, we used PPI protein interaction network and Cytoscape analysis to identify key genes and qRT-PCR to verify differential gene expression. Single-gene enrichment analysis (GSEA) was used further to elucidate the potential biological functions of key genes. Analysis of immune cell infiltration and correlation of key genes with immune cells after Mtb-Ag-stimulated using R language.

Results

We identified 597 differentially expressed genes in Mtb-Ag stimulated PBMCs. KEGG and GSEA enrichment analyzed the cellular pathways related to immune function, and DEGs were found to be primarily involved in the TNF signaling pathway, the IL-17 signaling pathway, the JAK-STAT signaling pathway, cytokine-cytokine receptor interactions, and the NF-κB signaling pathway. Wayne analysis using GSEA, KEGG, and the protein-protein interaction (PPI) network showed that 34 genes, including PTGS2, IL-1β, IL-6, TNF and IFN-γ et al., were co-expressed in the five pathways and all were up-regulated by Mtb-Ag stimulation. Twenty-four DEGs were identified using qRT-PCR, including fourteen up-regulated genes (SERPINB7, IL20, IFNG, CSF2, PTGS2, TNF-α, IL36G, IL6, IL10, IL1A, CXCL1, CXCL8, IL4, and CXCL3) and ten down-regulated genes (RTN1, CSF1R CD14, C5AR1, CXCL16, PLXNB2, OLIG1, EEPD1, ENG, and CCR1). These findings were consistent with the RNA-Seq results.

Conclusion

The transcriptomic features associated with Mtb-Ag provide the scientific basis for exploring the intracellular immune mechanisms against Mtb. However, more studies on these DEGs in pathways associated with Mtb-Ag stimulation are needed to elucidate the underlying pathologic mechanisms of Mtb-Ag during Mtb infection.

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.

Identification of immune biomarkers in recent active pulmonary tuberculosis

Tuberculosis (TB) has remained an unsolved problem and a major public health issue, particularly in developing countries. Pakistan is one of the countries with the highest tuberculosis infection rates globally. However, methods or biomarkers to detect early signs of TB infection are limited. Here, we characterized the mRNA profiles of immune responses in unstimulated Peripheral blood mononuclear cells obtained from treatment naïve patients with early signs of active pulmonary tuberculosis without previous history of clinical TB. We identified a unique mRNA profile in active TB compared to uninfected controls, including cytokines such as IL-27, IL-15, IL-2RA, IL-24, and TGFβ, transcription factors such as STAT1 and NFATC1 and immune markers/receptors such as TLR4, IRF1, CD80, CD28, and PTGDR2 from an overall 84 different transcripts analyzed. Among 12 significant differentially expressed transcripts, we identified five gene signatures which included three upregulated IL-27, STAT1, TLR4 and two downregulated IL-24 and CD80 that best discriminate between active pulmonary TB and uninfected controls with AUC ranging from 0.9 to 1. Our data identified a molecular immune signature associated with the early stages of active pulmonary tuberculosis and it could be further investigated as a potential biomarker of pulmonary TB.

Transcriptomic identification of genes expressed in invasive S. aureus diabetic foot ulcer infection

Introduction

Infection in diabetic foot ulcers (DFUs) is one of the major complications associated with patients with diabetes. Staphylococcus aureus is the most common offending pathogen in patients with infected DFU. Previous studies have suggested the application of species-specific antibodies against S. aureus for diagnosis and monitoring treatment response. Early and accurate identification of the main pathogen is critical for management of DFU infection. Understanding the host immune response against species-specific infection may facilitate diagnosis and may suggest potential intervention options to promote healing infected DFUs. We sought to investigate evolving host transcriptome associated with surgical treatment of S. aureus- infected DFU.

Methods

This study compared the transcriptome profile of 21 patients with S. aureus- infected DFU who underwent initial foot salvage therapy with irrigation and debridement followed by intravenous antibiotic therapy. Blood samples were collected at the recruitment (0 weeks) and 8 weeks after therapy to isolate peripheral blood mononuclear cells (PBMCs). We analyzed the PBMC expression of transcriptomes at two different time points (0 versus 8 weeks). Subjects were further divided into two groups at 8 weeks: healed (n = 17, 80.95%) versus non-healed (n = 4, 19.05%) based on the wound healing status. DESeq2 differential gene analysis was performed.

Results and discussion

An increased expression of IGHG1, IGHG2, IGHG3, IGLV3-21, and IGLV6-57 was noted during active infection at 0 weeks compared with that at 8 weeks. Lysine- and arginine-rich histones (HIST1H2AJ, HIST1H2AL, HIST1H2BM, HIST1H3B, and HIST1H3G) were upregulated at the initial phase of active infection at 0 weeks. CD177 and RRM2 were also upregulated at the initial phase of active infection (0 weeks) compared with that at 8 weeks of follow-up. Genes of heat shock protein members (HSPA1A, HSPE1, and HSP90B1) were high in not healed patients compared with that in healed patients 8 weeks after therapy. The outcome of our study suggests that the identification of genes evolution based on a transcriptomic profiling could be a useful tool for diagnosing infection and assessing severity and host immune response to therapies.

Management of Tuberculosis Infection: Current Situation, Recent Developments and Operational Challenges

Tuberculosis infection (TBI) is defined as a state of infection in which individuals host live Mycobacterium tuberculosis with or without clinical signs of active TB. It is now understood as a dynamic process covering a spectrum of responses to infection resulting from the interaction between the TB bacilli and the host immune system. The global burden of TBI is about one-quarter of the world’s population, representing a reservoir of approximately 2 billion people. On average, 5–10% of people who are infected will develop TB disease over the course of their lives, but this risk is enhanced in a series of conditions, such as co-infection with HIV. The End-TB strategy promotes the programmatic management of TBI as a crucial endeavor to achieving global targets to end the TB epidemic. The current development of new diagnostic tests capable of discriminating between simple TBI and active TB, combined with novel short-course preventive treatments, will help achieve this goal. In this paper, we present the current situation and recent developments of management of TBI and the operational challenges.

Gene expression profiling identifies candidate biomarkers for new latent tuberculosis infections. A cohort study

Objective

To determine the gene expression profile in individuals with new latent tuberculosis infection (LTBI), and to compare them with people with active tuberculosis (TB) and those exposed to TB but not infected.

Design

A prospective cohort study. Recruitment and follow-up were conducted between September 2016 to December 2018. Gene expression and data processing and analysis from April 2019 to April 2021.

Setting

Two male Colombian prisons.

Participants

15 new tuberculin skin test (TST) converters (negative TST at baseline that became positive during follow-up), 11 people that continued with a negative TST after two years of follow-up, and 10 people with pulmonary ATB.

Main outcome measures

Gene expression profile using RNA sequencing from PBMC samples. The differential expression was assessed using the DESeq2 package in Bioconductor. Genes with |logFC| >1.0 and an adjusted p-value < 0.1 were differentially expressed. We analyzed the differences in the enrichment of KEGG pathways in each group using InterMiner.

Results

The gene expression was affected by the time of incarceration. We identified group-specific differentially expressed genes between the groups: 289 genes in people with a new LTBI and short incarceration (less than three months of incarceration), 117 in those with LTBI and long incarceration (one or more years of incarceration), 26 in ATB, and 276 in the exposed but non-infected individuals. Four pathways encompassed the largest number of down and up-regulated genes among individuals with LTBI and short incarceration: cytokine signaling, signal transduction, neutrophil degranulation, and innate immune system. In individuals with LTBI and long incarceration, the only enriched pathway within up-regulated genes was Emi1 phosphorylation.

Conclusions

Recent infection with MTB is associated with an identifiable RNA pattern related to innate immune system pathways that can be used to prioritize LTBI treatment for those at greatest risk for developing active TB.

Latent Tuberculosis Infection Diagnosis among Household Contacts in a High Tuberculosis-Burden Area: a Comparison between Transcript Signature and Interferon Gamma Release Assay

Diagnosis of latent tuberculosis infection (LTBI) using biomarkers in order to identify the risk of progressing to active TB and therefore predicting a preventive therapy has been the main bottleneck in eradication of tuberculosis. We compared two assays for the diagnosis of LTBI: transcript signatures and interferon gamma release assay (IGRA), among household contacts (HHCs) in a high tuberculosis-burden population. HHCs of active TB cases were recruited for our study; these were confirmed to be clinically negative for active TB disease. Eighty HHCs were screened by IGRA using QuantiFERON-TB Gold Plus (QFT-Plus) to identify LTBI and uninfected cohorts; further, quantitative levels of transcript for selected six genes (TNFRSF10C, ASUN, NEMF, FCGR1B, GBP1, and GBP5) were determined. Machine learning (ML) was used to construct models of different gene combinations, with a view to identify hidden but significant underlying patterns of their transcript levels. Forty-three HHCs were found to be IGRA positive (LTBI) and thirty-seven were IGRA negative (uninfected). FCGR1B, GBP1, and GBP5 transcripts differentiated LTBI from uninfected among HHCs using Livak method. ML and ROC (Receiver Operator Characteristic) analysis validated this transcript signature to have a specificity of 72.7%. In this study, we compared a quantitative transcript signature with IGRA to assess the diagnostic ability of the two, for detection of LTBI cases among HHCs of a high-TB burden population; we concluded that a three gene (FCGR1B, GBP1, and GBP5) transcript signature can be used as a biomarker for rapid screening.

IMPORTANCE The study compares potential of transcript signature and IGRA to diagnose LTBI. It is first of its kind study to screen household contacts (HHCs) in high TB burden area of India. A transcript signature (FCGR1B, GBP1, & GBP5) is identified as potential biomarker for LTBI. These results can lead to development of point-of-care (POC) like device for LTBI screening in a high TB burdened area.

Combination of HLA-DR on Mycobacterium tuberculosis-Specific Cells and Tuberculosis Antigen/Phytohemagglutinin Ratio for Discriminating Active Tuberculosis From Latent Tuberculosis Infection

Background

Novel approaches for tuberculosis (TB) diagnosis, especially for distinguishing active TB (ATB) from latent TB infection (LTBI), are urgently warranted. The present study aims to determine whether the combination of HLA-DR on Mycobacterium tuberculosis (MTB)-specific cells and TB antigen/phytohemagglutinin (TBAg/PHA) ratio could facilitate MTB infection status discrimination.

Methods

Between June 2020 and June 2021, participants with ATB and LTBI were recruited from Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort), respectively. The detection of HLA-DR on MTB-specific cells upon TB antigen stimulation and T-SPOT assay were simultaneously performed on all subjects.

Results

A total of 116 (54 ATB and 62 LTBI) and another 84 (43 ATB and 41 LTBI) cases were respectively enrolled from Qiaokou cohort and Caidian cohort. Both HLA-DR on IFN-γ⁺TNF-α⁺ cells and TBAg/PHA ratio showed discriminatory value in distinguishing between ATB and LTBI. Receiver operator characteristic (ROC) curve analysis showed that HLA-DR on IFN-γ⁺TNF-α⁺ cells produced an area under the ROC curve (AUC) of 0.886. Besides, TBAg/PHA ratio yield an AUC of 0.736. Furthermore, the combination of these two indicators resulted in the accurate discrimination with an AUC of 0.937. When the threshold was set as 0.36, the diagnostic model could differentiate ATB from LTBI with a sensitivity of 92.00% and a specificity of 81.82%. The performance obtained in Qiaokou cohort was further validated in Caidian cohort.

Conclusions

The combination of HLA-DR on MTB-specific cells and TBAg/PHA ratio could serve as a robust tool to determine TB disease states.

Activation Phenotype of Mycobacterium tuberculosis-Specific CD4+ T Cells Promoting the Discrimination Between Active Tuberculosis and Latent Tuberculosis Infection

Background

Rapid and effective discrimination between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains a challenge. There is an urgent need for developing practical and affordable approaches targeting this issue.

Methods

Participants with ATB and LTBI were recruited at Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort) based on positive T-SPOT results from June 2020 to January 2021. The expression of activation markers including HLA-DR, CD38, CD69, and CD25 was examined on Mycobacterium tuberculosis (MTB)-specific CD4⁺ T cells defined by IFN-γ, TNF-α, and IL-2 expression upon MTB antigen stimulation.

Results

A total of 90 (40 ATB and 50 LTBI) and another 64 (29 ATB and 35 LTBI) subjects were recruited from the Qiaokou cohort and Caidian cohort, respectively. The expression patterns of Th1 cytokines including IFN-γ, TNF-α, and IL-2 upon MTB antigen stimulation could not differentiate ATB patients from LTBI individuals well. However, both HLA-DR and CD38 on MTB-specific cells showed discriminatory value in distinguishing between ATB patients and LTBI individuals. As for developing a single candidate biomarker, HLA-DR had the advantage over CD38. Moreover, HLA-DR on TNF-α⁺ or IL-2⁺ cells had superiority over that on IFN-γ⁺ cells in differentiating ATB patients from LTBI individuals. Besides, HLA-DR on MTB-specific cells defined by multiple cytokine co-expression had a higher ability to discriminate patients with ATB from LTBI individuals than that of MTB-specific cells defined by one kind of cytokine expression. Specially, HLA-DR on TNF-α⁺IL-2⁺ cells produced an AUC of 0.901 (95% CI, 0.833–0.969), with a sensitivity of 93.75% (95% CI, 79.85–98.27%) and specificity of 72.97% (95% CI, 57.02–84.60%) as a threshold of 44% was used. Furthermore, the performance of HLA-DR on TNF-α⁺IL-2⁺ cells for differential diagnosis was obtained with validation cohort data: 90.91% (95% CI, 72.19–97.47%) sensitivity and 68.97% (95% CI, 50.77–82.73%) specificity.

Conclusions

We demonstrated that HLA-DR on MTB-specific cells was a potentially useful biomarker for accurate discrimination between ATB and LTBI.

Transcriptional Profiling of Human Peripheral Blood Mononuclear Cells Stimulated by Mycobacterium tuberculosis PPE57 Identifies Characteristic Genes Associated With Type I Interferon Signaling

Proline-glutamic acid (PE)- and proline-proline-glutamic acid (PPE)-containing proteins are exclusive to Mycobacterium tuberculosis (MTB), the leading cause of tuberculosis (TB). In this study, we performed global transcriptome sequencing (RNA-Seq) on PPE57-stimulated peripheral blood mononuclear cells (PBMCs) and control samples to quantitatively measure the expression level of key transcripts of interest. A total of 1367 differentially expressed genes (DEGs) were observed in response to a 6 h exposure to PPE57, with 685 being up-regulated and 682 down-regulated. Immune-related gene functions and pathways associated with these genes were evaluated, revealing that the type I IFN signaling pathway was the most significantly enriched pathway in our RNA-seq dataset, with 14 DEGs identified therein including ISG15, MX2, IRF9, IFIT3, IFIT2, OAS3, IFIT1, IFI6, OAS2, OASL, RSAD2, OAS1, IRF7, and MX1. These PPE57-related transcriptomic profiles have implications for a better understanding of host global immune mechanisms underlying MTB infection outcomes. However, more studies regarding these DEGs and type I IFN signaling in this infectious context are necessary to more fully clarify the underlying mechanisms that arise in response to PPE57 during MTB infection.

Identification of differentially expressed lncRNAs as potential plasma biomarkers for active tuberculosis

BACKGROUND

Tuberculosis, one of the deadliest infectious diseases worldwide, is difficult to diagnose. As long noncoding RNAs (lncRNAs) were demonstrated to be promising biomarkers, we aimed to identify lncRNAs in plasma as potential biomarkers for tuberculosis.

METHODS

We analyzed a GEO dataset (GSE94907) to identify the differential lncRNAs in serum exosomes between active tuberculosis (ATB) patients and healthy controls. To search for promising candidates that can be used for tuberculosis diagnosis, we excluded low-abundance lncRNAs using a cutoff value of FPKM >5. Four lncRNAs were selected for validation using real-time quantitative PCR in 69 ATB patients and 69 healthy individuals. A receiver operating characteristic (ROC) curve was constructed to evaluate the diagnostic value of these lncRNAs for ATB.

RESULTS

Integrated analysis of the GEO dataset and NONCODE database identified nine dysregulated lncRNAs in ATB patient serum exosomes. Compared with the heathy controls, NONHSAT101518.2, NONHSAT067134.2, NONHSAT148822.1 and NONHSAT078957.2 were significantly downregulated in ATB patient plasma. ROC curve analysis suggests that these four lncRNAs can discriminate ATB from healthy individuals with high specificity and sensitivity.

CONCLUSION

We identified four differentially expressed lncRNAs in ATB patient plasma that can be used as potential diagnostic biomarkers of ATB.

The paradigm shift in the approach to management of latent tuberculosis infection in high tuberculosis burden countries

Introduction: Addressing the reservoir of Latent Tuberculosis Infection (LTBI) is critical to TB elimination because if left untreated LTBI can progress to active TB disease. This additional burden can prevent achieving the global targets of TB elimination. Management of LTBI has been a low priority target for National TB Elimination Programs (NTEP) due to various challenges in the field settings.Areas covered: This article reviews the most recent advances in the field of LTBI management including newer diagnostics, treatments, vaccines, programmatic challenges, and gaps and suggests a way forward that can be adopted by NTEPs for LTBI. We searched the electronic databases of PubMed, Scopus, and Web of Science for studies published between 2010 to 2020 using MeSH terms: Latent TB Diagnosis, TB preventive therapy, Vaccines, LTBI, and HIV/ COVID.Expert opinion: NTEPs of developing countries should offer a better, point-of-care diagnostic, and effective treatment for LTBI to reduce the number of new TB cases arising from people infected with M.tb. Awareness about LTBI should be increased among the health system staff and the public. More funding is needed to advance research as well as implement the newer findings in the NTEP to achieve the End TB targets by 2035.

Evidence for the Effect of Vaccination on Host-Pathogen Interactions in a Murine Model of Pulmonary Tuberculosis by Mycobacterium tuberculosis

The global control of Tuberculosis remains elusive, and Bacillus Calmette-Guérin (BCG) -the most widely used vaccine in history-has proven insufficient for reversing this epidemic. Several authors have suggested that the mass presence of vaccinated hosts might have affected the Mycobacterium tuberculosis (MTB) population structure, and this could in turn be reflected in a prevalence of strains with higher ability to circumvent BCG-induced immunity, such as the recent Beijing genotype. The effect of vaccination on vaccine-escape variants has been well-documented in several bacterial pathogens; however the effect of the interaction between MTB strains and vaccinated hosts has never been previously described. In this study we show for the first time the interaction between MTB Beijing-genotype strains and BCG-vaccinated hosts. Using a well-controlled murine model of progressive pulmonary tuberculosis, we vaccinated BALB/c mice with two different sub-strains of BCG (BCG-Phipps and BCG-Vietnam). Following vaccination, the mice were infected with either one of three selected MTB strains. Strains were selected based on lineage, and included two Beijing-family clinical isolates (strains 46 and 48) and a well-characterized laboratory strain (H37Rv). Two months after infection, mice were euthanized and the bacteria extracted from their lungs. We characterized the genomic composite of the bacteria before and after exposure to vaccinated hosts, and also characterized the local response to the bacteria by sequencing the lung transcriptome in animals during the infection. Results from this study show that the interaction within the lungs of the vaccinated hosts results in the selection of higher-virulence bacteria, specifically for the Beijing genotype strains 46 and 48. After exposure to the BCG-induced immune response, strains 46 and 48 acquire genomic mutations associated with several virulence factors. As a result, the bacteria collected from these vaccinated hosts have an increased ability for immune evasion, as shown in both the host transcriptome and the histopathology studies, and replicates far more efficiently compared to bacteria collected from unvaccinated hosts or to the original-stock strain. Further research is warranted to ascertain the pathways associated with the genomic alterations. However, our results highlight novel host-pathogen interactions induced by exposure of MTB to BCG vaccinated hosts.

Advancing new diagnostic tests for latent tuberculosis infection due to multidrug-resistant strains of Mycobacterium tuberculosis - End of the road?

An estimated 1.8 billion people worldwide have a latent tuberculosis infection (LTBI), with wide variations in LTBI rates across countries. LTBI can be due to infection with either drug-sensitive or drug-resistant Mycobacterium tuberculosis (Mtb) strains. Accurate data on the prevalence of LTBI due to multidrug-resistant (MDR) Mtb strains are unavailable, since the strains cannot be isolated for resistance testing. There are no 'gold standard' tests for accurately diagnosing LTBI. Only three tests are currently available and approved by the World Health Organization (WHO) for the diagnosis of LTBI: the now outdated tuberculin skin test (TST), developed a century year ago, and the two interferon-gamma release assays (IGRAs) developed and rolled out over the past decade, the QuantiFERON (Qiagen, Germany) and T-SPOT.TB (Oxford Immunotec, United Kingdom) tests. These latter tests are not ideal due to issues of sensitivity, specificity, inability to distinguish infection with MDR-Mtb strains, and high costs. Achieving the WHO End TB Strategy target of an 80% reduction in global TB incidence by 2030 will require a major reduction in the number of persons with LTBI progressing to active TB disease. Critical to this will be the development of new diagnostic tests that are better than currently available LTBI tests at predicting who is at risk of progression to active TB disease. The diagnostic product development portfolio for LTBI appears to have reached the end of the road. Every attempt to make optimal use of currently available IGRAs using WHO LTBI guidelines for LTBI testing and treatment must be made to achieve WHO End TB strategy targets.