Four-Gene Pan-African Blood Signature Predicts Progression to Tuberculosis

A blood-based 3-gene signature score for therapeutic monitoring in patients with pulmonary tuberculosis

OBJECTIVE

To assess the validity of Xpert Tuberculosis Fingerstick score for monitoring treatment response and analyze factors influencing its performance.

METHODS

122 adults with pulmonary tuberculosis were recruited and stratified into three cohorts: Diabetic-drug-susceptible-TB (DM-TB), Non-diabetic-drug-susceptible-TB (NDM-TB) and Non-diabetic Multidrug-resistant TB (MDR-TB). Fingerstick blood specimens were tested at treatment initiation (M0) and the end of the first (M1), second (M2), and sixth month (M6) to generate a TB-score.

RESULTS

The TB-score in all participants yielded an AUC of 0.707 (95% CI: 0.579-0.834) at M2 when its performance was evaluated against sputum culture conversion. In all non-diabetes patients, the AUC reached 0.88 (95% CI: 0.756-1.000) with an optimal cut-off value of 1.95 at which sensitivity was 90.0% (95% CI: 59.6-98.2%) and specificity was 81.3% (95% CI: 70.0-88.9%). The mean TB score was higher in patients with low bacterial loads (n = 31) than those with high bacterial loads (n = 91) at M0, M1, M2, and M6, and was higher in non-cavitary patients (n = 71) than those with cavitary lesions (n = 51) at M0, M1, and M2.

CONCLUSION

Xpert TB-score shows promising predictive value for culture conversion in non-diabetic TB patients. Sputum bacterial load and lung cavitation status have an influence on the value of TB score.

Whole-transcriptome sequencing of phagocytes reveals a ceRNA network contributing to natural resistance to tuberculosis infection

Tuberculosis (TB) is a major fatal infectious disease globally, exhibiting high morbidity rates and impacting public health and other socio-economic factors. However, some individuals are resistant to TB infection and are referred to as "Resisters". Resisters remain uninfected even after exposure to high load of Mycobacterium tuberculosis (Mtb). To delineate this further, this study aimed to investigate the factors and mechanisms influencing the Mtb resistance phenotype. We assayed the phagocytic capacity of peripheral blood mononuclear cells (PBMCs) collected from Resisters, patients with latent TB infection (LTBI), and patients with active TB (ATB), following infection with fluorescent Mycobacterium bovis Bacillus Calmette-Guérin (BCG). Phagocytosis was stronger in PBMCs from ATB patients, and comparable in LTBI patients and Resisters. Subsequently, phagocytes were isolated and subjected to whole transcriptome sequencing and small RNA sequencing to analyze transcriptional expression profiles and identify potential targets associated with the resistance phenotype. The results revealed that a total of 277 mRNAs, 589 long non-coding RNAs, 523 circular RNAs, and 35 microRNAs were differentially expressed in Resisters and LTBI patients. Further, the endogenous competitive RNA (ceRNA) network was constructed from differentially expressed genes after screening. Bioinformatics, statistical analysis, and quantitative real-time polymerase chain reaction were used for the identification and validation of potential crucial targets in the ceRNA network. As a result, we obtained a ceRNA network that contributes to the resistance phenotype. TCONS_00034796-F3, ENST00000629441-DDX43, hsa-ATAD3A_0003-CYP17A1, and XR_932996.2-CERS1 may be crucial association pairs for resistance to TB infection. Overall, this study demonstrated that the phagocytic capacity of PBMCs was not a determinant of the resistance phenotype and that some non-coding RNAs could be involved in the natural resistance to TB infection through a ceRNA mechanism.

Age and sex influence antibody profiles associated with tuberculosis progression

Antibody features vary with tuberculosis (TB) disease state. Whether clinical variables, such as age or sex, influence associations between Mycobacterium tuberculosis-specific antibody responses and disease state is not well explored. Here we profiled Mycobacterium tuberculosis-specific antibody responses in 140 TB-exposed South African individuals from the Adolescent Cohort Study. We identified distinct response features in individuals progressing to active TB from non-progressing, matched controls. A multivariate antibody score differentially associated with progression (SeroScore) identified progressors up to 2 years before TB diagnosis, earlier than that achieved with the RISK6 transcriptional signature of progression. We validated these antibody response features in the Grand Challenges 6-74 cohort. Both the SeroScore and RISK6 correlated better with risk of TB progression in adolescents compared with adults, and in males compared with females. This suggests that age and sex are important, underappreciated modifiers of antibody responses associated with TB progression.

Incipient tuberculosis: a comprehensive overview

In the context of the evolving global health landscape shaped by the COVID-19 pandemic, tuberculosis (TB) is gaining renewed attention as a reemerging threat even in low-endemic countries. Immunological tests such as the tuberculin skin test (TST) and interferon-gamma release assay (IGRA) are pivotal in identifying tuberculosis infection (TBI). However, their inability to distinguish between past and ongoing infection poses a diagnostic challenge, possibly leading to the unnecessary treatment of a significant portion of the population with potential side effects. This review delves into the concept of incipient tuberculosis (ITB), a dynamic, presymptomatic stage characterized by heightened Mycobacterium tuberculosis complex (MTC) metabolic activity and replication that result in minimal radiological changes, signifying a transitional state between TBI and TB. Key focus areas include epidemiological factors, underlying pathogenesis, imaging findings, and the ongoing challenges in the identification of individuals with ITB through the development of new biomarkers and the use of whole-genome sequencing-based analyses to implement early treatment strategies.

C1q and HBHA-specific IL-13 levels as surrogate plasma biomarkers for monitoring tuberculosis treatment efficacy: a cross-sectional cohort study in Paraguay

Introduction

New diagnostic tools are needed to rapidly assess the efficacy of pulmonary tuberculosis (PTB) treatment. The aim of this study was to evaluate several immune biomarkers in an observational and cross-sectional cohort study conducted in Paraguay.

Methods

Thirty-two patients with clinically and microbiologically confirmed PTB were evaluated before starting treatment (T0), after 2 months of treatment (T1) and at the end of treatment (T2). At each timepoint plasma levels of IFN-y, 17 pro- and anti-inflammatory cytokines/chemokines and complement factors C1q, C3 and C4 were assessed in unstimulated and Mtb-specific stimulated whole blood samples using QuantiFERON-TB gold plus and recombinant Mycobacterium smegmatis heparin binding hemagglutinin (rmsHBHA) as stimulation antigen. Complete blood counts and liver enzyme assays were also evaluated and correlated with biomarker levels in plasma.

Results

In unstimulated plasma, C1q (P<0.001), C4 (P<0.001), hemoglobin (P<0.001), lymphocyte proportion (P<0.001) and absolute white blood cell count (P=0.01) were significantly higher in PTB patients at baseline than in cured patients. C1q and C4 levels were found to be related to Mycobacterium tuberculosis load in sputum. Finally, a combinatorial analysis identified a plasma host signature comprising the detection of C1q and IL-13 levels in response to rmsHBHA as a tool differentiating PTB patients from cured TB profiles, with an AUC of 0.92 (sensitivity 94% and specificity 79%).

Conclusion

This observational study provides new insights on host immune responses throughout anti-TB treatment and emphasizes the role of host C1q and HBHA-specific IL-13 response as surrogate plasma biomarkers for monitoring TB treatment efficacy.

Activin A levels are raised during human tuberculosis and blockade of the activin signaling axis influences murine responses to M. tuberculosis infection

Activin A strongly influences immune responses; yet, few studies have examined its role in infectious diseases. We measured serum activin A levels in two independent tuberculosis (TB) patient cohorts and in patients with pneumonia and sarcoidosis. Serum activin A levels were increased in TB patients compared to healthy controls, including those with positive tuberculin skin tests, and paralleled severity of disease, assessed by X-ray scores. In pneumonia patients, serum activin A levels were also raised, but in sarcoidosis patients, levels were lower. To determine whether blockade of the activin A signaling axis could play a functional role in TB, we harnessed a soluble activin type IIB receptor fused to human IgG1 Fc, ActRIIB-Fc, as a ligand trap in a murine TB model. The administration of ActRIIB-Fc to Mycobacterium tuberculosis-infected mice resulted in decreased bacterial loads and increased numbers of CD4 effector T cells and tissue-resident memory T cells in the lung. Increased frequencies of tissue-resident memory T cells corresponded with downregulated T-bet expression in lung CD4 and CD8 T cells. Altogether, the results suggest a disease-exacerbating role of ActRIIB signaling pathways. Serum activin A may be useful as a biomarker for diagnostic triage of active TB or monitoring of anti-tuberculosis therapy.

IMPORTANCE

Tuberculosis remains the leading cause of death by a bacterial pathogen. The etiologic agent of tuberculosis, Mycobacterium tuberculosis, can remain dormant in the infected host for years before causing disease. Significant effort has been made to identify biomarkers that can discriminate between latently infected and actively diseased individuals. We found that serum levels of the cytokine activin A were associated with increased lung pathology and could discriminate between active tuberculosis and tuberculin skin-test-positive healthy controls. Activin A signals through the ActRIIB receptor, which can be blocked by administration of the ligand trap ActRIIB-Fc, a soluble activin type IIB receptor fused to human IgG1 Fc. In a murine model of tuberculosis, we found that ActRIIB-Fc treatment reduced mycobacterial loads. Strikingly, ActRIIB-Fc treatment significantly increased the number of tissue-resident memory T cells. These results suggest a role for ActRIIB signaling pathways in host responses to Mycobacterium tuberculosis and activin A as a biomarker of ongoing disease.

Large-scale analysis reveals splicing biomarkers for tuberculosis progression and prognosis

BACKGROUND

Emerging evidence suggests that aberrant alternative splicing (AS) may play an important role in tuberculosis (TB). However, current knowledge regarding the value of AS in TB progression and prognosis remains unclear.

METHOD

Public RNA-seq datasets related to TB progression and prognosis were searched and AS analyses were conducted based on SUPPA2. Percent spliced in (PSI) was used for quantifying AS events and multiple machine learning (ML) methods were employed to construct predictive models. Area under curve (AUC), sensitivity and specificity were calculated to evaluate the model performance.

RESULTS

A total of 1587 samples from 7 datasets were included. Among 923 TB-progression related differential AS events (DASEs), 3 events (GET1-skipping exon (SE), TPD52-alternative first exons (AF) and TIMM10-alternative 5' splice site (A5)) were selected as candidate biomarkers; however, their predictive performance was limited. For TB prognosis, 5 events (PHF23-AF, KIF1B-SE, MACROD2-alternative 3' splice site (A3), CD55-retained intron (RI) and GALNT11-AF) were selected as candidates from the 1282 DASEs. Six ML methods were used to integrate these 5 events and XGBoost outperformed than others. AUC, sensitivity and specificity of XGBoost model were 0.875, 81.1% and 83.5% in training set, while they were 0.805, 68.4% and 73.2% in test set.

CONCLUSION

GET1-SE, TPD52-AF and TIMM10-A5 showed limited role in predicting TB progression, while PHF23-AF, KIF1B-SE, MACROD2-A3, CD55-RI and GALNT11-AF could well predict TB prognosis and work as candidate biomarkers. This work preliminarily explored the value of AS in predicting TB progression and prognosis and offered potential targets for further research.

Single-Cell Sequencing Reveals Functional Alterations in Tuberculosis

Despite its importance, the functional heterogeneity surrounding the dynamics of interactions between mycobacterium tuberculosis and human immune cells in determining host immune strength and tuberculosis (TB) outcomes, remains far from understood. This work now describes the development of a new technological platform to elucidate the immune function differences in individuals with TB, integrating single-cell RNA sequencing and cell surface antibody sequencing to provide both genomic and phenotypic information from the same samples. Single-cell analysis of 23 990 peripheral blood mononuclear cells from a new cohort of primary TB patients and healthy controls enables to not only show four distinct immune phenotypes (TB, myeloid, and natural killer (NK) cells), but also determine the dynamic changes in cell population abundance, gene expression, developmental trajectory, transcriptomic regulation, and cell-cell signaling. In doing so, TB-related changes in immune cell functions demonstrate that the immune response is mediated through host T cells, myeloid cells, and NK cells, with TB patients showing decreased naive, cytotoxicity, and memory functions of T cells, rather than their immunoregulatory function. The platform also has the potential to identify new targets for immunotherapeutic treatment strategies to restore T cells from dysfunctional or exhausted states.

A Review Of Host-Specific Diagnostic And Surrogate Biomarkers In Children With Pulmonary Tuberculosis

BACKGROUND

Tuberculosis (TB) is one of the most common causes of mortality globally with a steady rise in paediatric cases in the past decade. Laboratory methods of diagnosing TB and monitoring response to treatment have limitations. Current research focuses on interrogating host- and/or pathogen-specific biomarkers to address this problem.

METHODS

We reviewed the literature on host-specific biomarkers in TB to determine their value in diagnosis and treatment response in TB infected and HIV/TB co-infected children on anti-tuberculosis treatment.

RESULTS AND CONCLUSION

While no single host-specific biomarker has been identified for diagnosis or treatment responses in children, several studies suggest predictive biosignatures for disease activity. Alarmingly, current data on host-specific biomarkers for diagnosing and assessing anti-tuberculosis treatment in TB/HIV co-infected children is inadequate. Various factors affecting host-specific biomarker responses should be considered in interpreting findings and designing future studies within specific clinical settings.

Whole blood RNA signatures in tuberculosis patients receiving H56:IC31 vaccine as adjunctive therapy

Introduction

Therapeutic vaccination in tuberculosis (TB) represents a Host Directed Therapy strategy which enhances immune responses in order to improve clinical outcomes and shorten TB treatment. Previously, we have shown that the subunit H56:IC31 vaccine induced both humoral and cellular immune responses when administered to TB patients adjunctive to standard TB treatment (TBCOX2 study, NCT02503839). Here we present the longitudinal whole blood gene expression patterns in H56:IC31 vaccinated TB patients compared to controls receiving standard TB treatment only.

Methods

The H56:IC31 group (N=11) and Control group (N=7) underwent first-line TB treatment for 182 days. The H56:IC31 group received 5 micrograms of the H56:IC31 vaccine (Statens Serum Institut; SSI, Valneva Austria GmbH) intramuscularly at day 84 and day 140. Total RNA was extracted from whole blood samples collected in PAXgene tubes on days 0, 84, 98, 140, 154, 182 and 238. The expression level of 183 immune-related genes was measured by high-throughput microfluidic qPCR (Biomark HD system, Standard BioTools).

Results

The targeted gene expression profiling unveiled the upregulation of modules such as interferon (IFN) signalling genes, pattern recognition receptors and small nucleotide guanosine triphosphate (GTP)-ases in the vaccinated group compared to controls two weeks after administration of the first H56:IC31 vaccine. Additionally, the longitudinal analysis of the Adolescent Cohort Study-Correlation of Risk (ACS-COR) signature showed a progressive downregulation in both study arms towards the end of TB treatment, in congruence with reported treatment responses and clinical improvements. Still, two months after the end of TB treatment, vaccinated patients, and especially those developing both cellular and humoral vaccine responses, showed a lower expression of the ACS-COR genes compared to controls.

Discussion

Our data report gene expression patterns following H56:IC31 vaccination which might be interpreted as a lower risk of relapse in therapeutically vaccinated patients. Further studies are needed to conclude if these gene expression patterns could be used as prognostic biosignatures for therapeutic TB vaccine responses.

Alterations of lipid-related genes during anti-tuberculosis treatment: insights into host immune responses and potential transcriptional biomarkers

Background

The optimal diagnosis and treatment of tuberculosis (TB) are challenging due to underdiagnosis and inadequate treatment monitoring. Lipid-related genes are crucial components of the host immune response in TB. However, their dynamic expression and potential usefulness for monitoring response to anti-TB treatment are unclear.

Methodology

In the present study, we used a targeted, knowledge-based approach to investigate the expression of lipid-related genes during anti-TB treatment and their potential use as biomarkers of treatment response.

Results and discussion

The expression levels of 10 genes (ARPC5, ACSL4, PLD4, LIPA, CHMP2B, RAB5A, GABARAPL2, PLA2G4A, MBOAT2, and MBOAT1) were significantly altered during standard anti-TB treatment. We evaluated the potential usefulness of this 10-lipid-gene signature for TB diagnosis and treatment monitoring in various clinical scenarios across multiple populations. We also compared this signature with other transcriptomic signatures. The 10-lipid-gene signature could distinguish patients with TB from those with latent tuberculosis infection and non-TB controls (area under the receiver operating characteristic curve > 0.7 for most cases); it could also be useful for monitoring response to anti-TB treatment. Although the performance of the new signature was not better than that of previous signatures (i.e., RISK6, Sambarey10, Long10), our results suggest the usefulness of metabolism-centric biomarkers.

Conclusions

Lipid-related genes play significant roles in TB pathophysiology and host immune responses. Furthermore, transcriptomic signatures related to the immune response and lipid-related gene may be useful for TB diagnosis and treatment monitoring.

Advancing tuberculosis management: the role of predictive, preventive, and personalized medicine

Tuberculosis is a major global health issue, with approximately 10 million people falling ill and 1.4 million dying yearly. One of the most significant challenges to public health is the emergence of drug-resistant tuberculosis. For the last half-century, treating tuberculosis has adhered to a uniform management strategy in most patients. However, treatment ineffectiveness in some individuals with pulmonary tuberculosis presents a major challenge to the global tuberculosis control initiative. Unfavorable outcomes of tuberculosis treatment (including mortality, treatment failure, loss of follow-up, and unevaluated cases) may result in increased transmission of tuberculosis and the emergence of drug-resistant strains. Treatment failure may occur due to drug-resistant strains, non-adherence to medication, inadequate absorption of drugs, or low-quality healthcare. Identifying the underlying cause and adjusting the treatment accordingly to address treatment failure is important. This is where approaches such as artificial intelligence, genetic screening, and whole genome sequencing can play a critical role. In this review, we suggest a set of particular clinical applications of these approaches, which might have the potential to influence decisions regarding the clinical management of tuberculosis patients.

Identification of circulating monocytes as producers of tuberculosis disease biomarker C1q

Tuberculosis (TB) is a prevalent disease causing an estimated 1.6 million deaths and 10.6 million new cases annually. Discriminating TB disease from differential diagnoses can be complex, particularly in the field. Increased levels of complement component C1q in serum have been identified as a specific and accessible biomarker for TB disease but the source of C1q in circulation has not been identified. Here, data and samples previously collected from human cohorts, a clinical trial and a non-human primate study were used to identify cells producing C1q in circulation. Cell subset frequencies were correlated with serum C1q levels and combined with single cell RNA sequencing and flow cytometry analyses. This identified monocytes as C1q producers in circulation, with a pronounced expression of C1q in classical and intermediate monocytes and variable expression in non-classical monocytes.

Overcoming the impacts of two-step batch effect correction on gene expression estimation and inference

Nonignorable technical variation is commonly observed across data from multiple experimental runs, platforms, or studies. These so-called batch effects can lead to difficulty in merging data from multiple sources, as they can severely bias the outcome of the analysis. Many groups have developed approaches for removing batch effects from data, usually by accommodating batch variables into the analysis (one-step correction) or by preprocessing the data prior to the formal or final analysis (two-step correction). One-step correction is often desirable due it its simplicity, but its flexibility is limited and it can be difficult to include batch variables uniformly when an analysis has multiple stages. Two-step correction allows for richer models of batch mean and variance. However, prior investigation has indicated that two-step correction can lead to incorrect statistical inference in downstream analysis. Generally speaking, two-step approaches introduce a correlation structure in the corrected data, which, if ignored, may lead to either exaggerated or diminished significance in downstream applications such as differential expression analysis. Here, we provide more intuitive and more formal evaluations of the impacts of two-step batch correction compared to existing literature. We demonstrate that the undesired impacts of two-step correction (exaggerated or diminished significance) depend on both the nature of the study design and the batch effects. We also provide strategies for overcoming these negative impacts in downstream analyses using the estimated correlation matrix of the corrected data. We compare the results of our proposed workflow with the results from other published one-step and two-step methods and show that our methods lead to more consistent false discovery controls and power of detection across a variety of batch effect scenarios. Software for our method is available through GitHub (https://github.com/jtleek/sva-devel) and will be available in future versions of the $\texttt{sva}$ R package in the Bioconductor project (https://bioconductor.org/packages/release/bioc/html/sva.html).

Characterizing the landscape of gene expression variance in humans

Gene expression variance has been linked to organismal function and fitness but remains a commonly neglected aspect of molecular research. As a result, we lack a comprehensive understanding of the patterns of transcriptional variance across genes, and how this variance is linked to context-specific gene regulation and gene function. Here, we use 57 large publicly available RNA-seq data sets to investigate the landscape of gene expression variance. These studies cover a wide range of tissues and allowed us to assess if there are consistently more or less variable genes across tissues and data sets and what mechanisms drive these patterns. We show that gene expression variance is broadly similar across tissues and studies, indicating that the pattern of transcriptional variance is consistent. We use this similarity to create both global and within-tissue rankings of variation, which we use to show that function, sequence variation, and gene regulatory signatures contribute to gene expression variance. Low-variance genes are associated with fundamental cell processes and have lower levels of genetic polymorphisms, have higher gene-gene connectivity, and tend to be associated with chromatin states associated with transcription. In contrast, high-variance genes are enriched for genes involved in immune response, environmentally responsive genes, immediate early genes, and are associated with higher levels of polymorphisms. These results show that the pattern of transcriptional variance is not noise. Instead, it is a consistent gene trait that seems to be functionally constrained in human populations. Furthermore, this commonly neglected aspect of molecular phenotypic variation harbors important information to understand complex traits and disease.

Field evaluation of a point-of-care triage test for active tuberculosis (TriageTB)

BACKGROUND

To improve tuberculosis (TB) diagnosis, the World Health Organisation (WHO) has called for a non-sputum based triage test to focus TB testing on people with a high likelihood of having active pulmonary tuberculosis (TB). Various host or pathogen biomarker-based testing devices are in design stage and require validity assessment. Host biomarkers have shown promise to accurately rule out active TB, but further research is required to determine generalisability. The TriageTB diagnostic test study aims to assess the accuracy of diagnostic test candidates, as well as field-test, finalise the design and biomarker signature, and validate a point-of-care multi-biomarker test (MBT).

METHODS

This observational diagnostic study will evaluate sensitivity and specificity of biomarker-based diagnostic candidates including the MBT and Xpert® TB Fingerstick cartridge compared with a gold-standard composite TB outcome classification defined by symptoms, sputum GeneXpert® Ultra, smear and culture, radiological features, response to TB therapy and presence of an alternative diagnosis. The study will be conducted in research sites in South Africa, Uganda, The Gambia and Vietnam which all have high TB prevalence. The two-phase design allows for finalisation of the MBT in Phase 1 in which candidate host proteins will be evaluated on stored serum from Asia, South Africa and South America and on fingerstick blood from 50 newly recruited participants per site. The MBT test will then be locked down and validated in Phase 2 on 250 participants per site.

DISCUSSION

By targeting confirmatory TB testing to those with a positive triage test, 75% of negative GXPU may be avoided, thereby reducing diagnostic costs and patient losses during the care cascade. This study builds on previous biomarker research and aims to identify a point-of-care test meeting or exceeding the minimum World Health Organisation target product profile of a 90% sensitivity and 70% specificity. Streamlining TB testing by identifying individuals with a high likelihood of TB should improve TB resources use and, in so doing, improve TB care.

TRIAL REGISTRATION

NCT04232618 (clinicaltrials.gov) Date of registration: 16 January 2020.

Research tests for the diagnosis of tuberculosis infection

INTRODUCTION

Despite huge efforts, tuberculosis (TB) is still a major public health threat worldwide, it is estimated that a quarter of the global population is infected by Mycobacterium tuberculosis (Mtb). For controlling TB and reducing Mtb transmission it is fundamental to diagnose TB infection (TBI) as well as the progressors from TBI to disease to identify those requiring preventive therapy. At present, there is no gold standard test for TBI diagnosis although several new methodologies have been attempted.

AREAS COVERED

This review provides an update on the most recent approaches to develop reliable tests to diagnose TBI and progressors from infection to disease. Experimental tests are based on either the direct identification of Mtb (i.e., Mtb DNA upon host cells isolation; Mtb proteins or peptides) or host response (i.e., levels and quality of specific anti-Mtb antibodies; host blood transcriptome signatures).

EXPERT OPINION

The experimental tests described are very interesting. However, further investigation and randomized clinical trials are needed to improve the sensitivity and specificity of these new research-based tests. More reliable proofs-of-concept and simplification of technical procedures are necessary to develop new diagnostic tools for identifying TBI patients and those that will progress from infection to TB disease.

Point-of-care test for tuberculosis: a boon in diagnosis

Rapid diagnosis of tuberculosis (TB) is an effective measure to eradicate this infectious disease worldwide. Traditional methods for screening TB patients do not provide an immediate diagnosis and thus delay treatment. There is an urgent need for the early detection of TB through point-of-care tests (POCTs). Several POCTs are widely available at primary healthcare facilities that assist in TB screening. In addition to the currently used POCTs, advancements in technology have led to the discovery of newer methods that provide accurate and fast information independent of access to laboratory facilities. In the present article, the authors tried to include and describe the potential POCTs for screening TB in patients. Several molecular diagnostic tests, such as nucleic acid amplification tests, including GeneXpert and TB-loop-mediated isothermal amplification, are currently being used as POCTs. Besides these methods, the pathogenic component of Mycobacterium tuberculosis can also be utilized as a biomarker for screening purposes through immunological assays. Similarly, the host immune response to infection has also been utilized as a marker for the diagnosis of TB. These novel biomarkers might include Mtb85, interferon-γ inducible protein-10, volatile organic compounds, acute-phase proteins, etc. Radiological tests have also been observed as POCTs in the TB screening POCT panel. Various POCTs are performed on samples other than sputum, which further eases the screening process. These POCTs should not require large-scale manpower and infrastructure. Hence, POCT should be able to identify patients with M. tuberculosis infection at the primary healthcare level only. There are several other advanced techniques that have been proposed as future POCTs and have been discussed in the present article.

Systematic review of diagnostic and prognostic host blood transcriptomic signatures of tuberculosis disease in people living with HIV

Background HIV-associated tuberculosis (TB) has high mortality; however, current triage and prognostic tools offer poor sensitivity and specificity, respectively. We conducted a systematic review of diagnostic and prognostic host-blood transcriptomic signatures of TB in people living with HIV (PLHIV). Methods We systematically searched online databases for studies published in English between 1990-2020. Eligible studies included PLHIV of any age in test or validation cohorts, and used microbiological or composite reference standards for TB diagnosis. Inclusion was not restricted by setting or participant age. Study selection, quality appraisal using the QUADAS-2 tool, and data extraction were conducted independently by two reviewers. Thereafter, narrative synthesis of included studies, and comparison of signatures performance, was performed. Results We screened 1,580 records and included 12 studies evaluating 31 host-blood transcriptomic signatures in 10 test or validation cohorts of PLHIV that differentiated individuals with TB from those with HIV alone, latent Mycobacterium tuberculosis infection, or other diseases (OD). Two (2/10; 20%) cohorts were prospective (29 TB cases; 51 OD) and 8 (80%) case-control (353 TB cases; 606 controls) design. All cohorts (10/10) were recruited in Sub-Saharan Africa and 9/10 (90%) had a high risk of bias. Ten signatures (10/31; 32%) met minimum WHO Target Product Profile (TPP) criteria for TB triage tests. Only one study (1/12; 8%) evaluated prognostic performance of a transcriptomic signature for progression to TB in PLHIV, which did not meet the minimum WHO prognostic TPP. Conclusions Generalisability of reported findings is limited by few studies enrolling PLHIV, limited geographical diversity, and predominantly case-control design, which also introduces spectrum bias. New prospective cohort studies are needed that include PLHIV and are conducted in diverse settings. Further research exploring the effect of HIV clinical, virological, and immunological factors on diagnostic performance is necessary for development and implementation of TB transcriptomic signatures in PLHIV.

Predictive performance of interferon-gamma release assays and the tuberculin skin test for incident tuberculosis: an individual participant data meta-analysis

BACKGROUND

Evidence on the comparative performance of purified protein derivative tuberculin skin tests (TST) and interferon-gamma release assays (IGRA) for predicting incident active tuberculosis (TB) remains conflicting. We conducted an individual participant data meta-analysis to directly compare the predictive performance for incident TB disease between TST and IGRA to inform policy.

METHODS

We searched Medline and Embase from 1 January 2002 to 4 September 2020, and studies that were included in previous systematic reviews. We included prospective longitudinal studies in which participants received both TST and IGRA and estimated performance as hazard ratios (HR) for the development of all diagnoses of TB in participants with dichotomised positive test results compared to negative results, using different thresholds of positivity for TST. Secondary analyses included an evaluation of the impact of background TB incidence. We also estimated the sensitivity and specificity for predicting TB. We explored heterogeneity through pre-defined sub-group analyses (e.g. country-level TB incidence). Publication bias was assessed using funnel plots and Egger's test. This review is registered with PROSPERO, CRD42020205667.

FINDINGS

We obtained data from 13 studies out of 40 that were considered eligible (N = 32,034 participants: 36% from countries with TB incidence rate ≥100 per 100,000 population). All reported data on TST and QuantiFERON Gold in-Tube (QFT-GIT). The point estimate for the TST was highest with higher cut-offs for positivity and particularly when stratified by bacillus Calmette-Guérin vaccine (BCG) status (15 mm if BCG vaccinated and 5 mm if not [TST^{5/15 mm}]) at 2.88 (95% CI 1.69-4.90). The pooled HR for QFT-GIT was higher than for TST at 4.15 (95% CI 1.97-8.75). The difference was large in countries with TB incidence rate <100 per 100,000 population (HR 10.38, 95% CI 4.17-25.87 for QFT-GIT VS. HR 5.36, 95% CI 3.82-7.51 for TST^{5/15 mm}) but much of this difference was driven by a single study (HR 5.13, 95% CI 3.58-7.35 for TST^{5/15 mm} VS. 7.18, 95% CI 4.48-11.51 for QFT-GIT, when excluding the study, in which all 19 TB cases had positive QFT-GIT results). The comparative performance was similar in the higher burden countries (HR 1.61, 95% CI 1.23-2.10 for QFT-GIT VS. HR 1.72, 95% CI 0.98-3.01 for TST^{5/15 mm}). The predictive performance of both tests was higher in countries with TB incidence rate <100 per 100,000 population. In the lower TB incidence countries, the specificity of TST (76% for TST^{5/15 mm}) and QFT-GIT (74%) for predicting active TB approached the minimum World Health Organization target (≥75%), but the sensitivity was below the target of ≥75% (63% for TST^{5/15 mm} and 65% for QFT-GIT). The absolute differences in positive and negative predictive values between TST^{15 mm} and QFT-GIT were small (positive predictive values 2.74% VS. 2.46%; negative predictive values 99.42% VS. 99.52% in low-incidence countries). Egger's test did not show evidence of publication bias (0.74 for TST^{15 mm} and p = 0.68 for QFT-GIT).

INTERPRETATION

IGRA appears to have higher predictive performance than the TST in low TB incidence countries, but the difference was driven by a single study. Any advantage in clinical performance may be small, given the numerically similar positive and negative predictive values. Both IGRA and TST had lower performance in countries with high TB incidence. Test choice should be contextual and made considering operational and likely clinical impact of test results.

FUNDING

YH, IA, and MXR were supported by the National Institute for Health and Care Research (NIHR), United Kingdom (RP-PG-0217-20009). MQ was supported by the Medical Research Council [MC_UU_00004/07].

Comparison of gene set scoring methods for reproducible evaluation of multiple tuberculosis gene signatures

Rationale

Many blood-based transcriptional gene signatures for tuberculosis (TB) have been developed with potential use to diagnose disease, predict risk of progression from infection to disease, and monitor TB treatment outcomes. However, an unresolved issue is whether gene set enrichment analysis (GSEA) of the signature transcripts alone is sufficient for prediction and differentiation, or whether it is necessary to use the original statistical model created when the signature was derived. Intra-method comparison is complicated by the unavailability of original training data, missing details about the original trained model, and inadequate publicly-available software tools or source code implementing models. To facilitate these signatures' replicability and appropriate utilization in TB research, comprehensive comparisons between gene set scoring methods with cross-data validation of original model implementations are needed.

Objectives

We compared the performance of 19 TB gene signatures across 24 transcriptomic datasets using both re-rebuilt original models and gene set scoring methods to evaluate whether gene set scoring is a reasonable proxy to the performance of the original trained model. We have provided an open-access software implementation of the original models for all 19 signatures for future use.

Methods

We considered existing gene set scoring and machine learning methods, including ssGSEA, GSVA, PLAGE, Singscore, and Zscore, as alternative approaches to profile gene signature performance. The sample-size-weighted mean area under the curve (AUC) value was computed to measure each signature's performance across datasets. Correlation analysis and Wilcoxon paired tests were used to analyze the performance of enrichment methods with the original models.

Measurement and Main Results

For many signatures, the predictions from gene set scoring methods were highly correlated and statistically equivalent to the results given by the original diagnostic models. PLAGE outperformed all other gene scoring methods. In some cases, PLAGE outperformed the original models when considering signatures' weighted mean AUC values and the AUC results within individual studies.

Conclusion

Gene set enrichment scoring of existing blood-based biomarker gene sets can distinguish patients with active TB disease from latent TB infection and other clinical conditions with equivalent or improved accuracy compared to the original methods and models. These data justify using gene set scoring methods of published TB gene signatures for predicting TB risk and treatment outcomes, especially when original models are difficult to apply or implement.

Host blood-based biosignatures for subclinical TB and incipient TB: A prospective study of adult TB household contacts in Southern India

A large proportion of the global tuberculosis (TB) burden is asymptomatic and not detectable by symptom-based screening, driving the TB epidemic through continued M. tuberculosis transmission. Currently, no validated tools exist to diagnose incipient and subclinical TB. Nested within a large prospective study in household contacts of pulmonary TB cases in Southern India, we assessed 35 incipient TB and 12 subclinical TB cases, along with corresponding household active TB cases (n=11), and household controls (n=39) using high throughput methods for transcriptional and protein profiling. We split the data into training and test sets and applied a support vector machine classifier followed by a Lasso regression model to identify signatures. The Lasso regression model identified an 11-gene signature (ABLIM2, C20orf197, CTC-543D15.3, CTD-2503O16.3, HLADRB3, METRNL, RAB11B-AS1, RP4-614C10.2, RNA5SP345, RSU1P1, and UACA) that distinguished subclinical TB from incipient TB with a very good discriminatory power by AUCs in both training and test sets. Further, we identified an 8-protein signature comprising b-FGF, IFNγ, IL1RA, IL7, IL12p70, IL13, PDGF-BB, and VEGF that differentiated subclinical TB from incipient TB with good and moderate discriminatory power by AUCs in the training and test sets, respectively. The identified 11-gene signature discriminated well between the distinct stages of the TB disease spectrum, with very good discriminatory power, suggesting it could be useful for predicting TB progression in household contacts. However, the high discriminatory power could partly be due to over-fitting, and validation in other studies is warranted to confirm the potential of the immune biosignatures for identifying subclinical TB.

Systematic review of diagnostic and prognostic host blood transcriptomic signatures of tuberculosis disease in people living with HIV

Background HIV-associated tuberculosis (TB) has high mortality; however, current triage and prognostic tools offer poor sensitivity and specificity, respectively. We conducted a systematic review of diagnostic and prognostic host-blood transcriptomic signatures of TB in people living with HIV (PLHIV). Methods We systematically searched online databases for studies published in English between 1990-2020. Eligible studies included PLHIV of any age in test or validation cohorts, and used microbiological or composite reference standards for TB diagnosis. Inclusion was not restricted by setting or participant age. Study selection, quality appraisal using the QUADAS-2 tool, and data extraction were conducted independently by two reviewers. Thereafter, narrative synthesis of included studies, and comparison of signatures performance, was performed. Results We screened 1,580 records and included 12 studies evaluating 31 host-blood transcriptomic signatures in 10 test or validation cohorts of PLHIV that differentiated individuals with TB from those with HIV alone, latent Mycobacterium tuberculosis infection, or other diseases (OD). Two (2/10; 20%) cohorts were prospective (29 TB cases; 51 OD) and 8 (80%) case-control (353 TB cases; 606 controls) design. All cohorts (10/10) were recruited in Sub-Saharan Africa and 9/10 (90%) had a high risk of bias. Ten signatures (10/31; 32%) met minimum WHO Target Product Profile (TPP) criteria for TB triage tests. Only one study (1/12; 8%) evaluated prognostic performance of a transcriptomic signature for progression to TB in PLHIV, which did not meet the minimum WHO prognostic TPP. Conclusions Generalisability of reported findings is limited by few studies enrolling PLHIV, limited geographical diversity, and predominantly case-control design, which also introduces spectrum bias. New prospective cohort studies are needed that include PLHIV and are conducted in diverse settings. Further research exploring the effect of HIV clinical, virological, and immunological factors on diagnostic performance is necessary for development and implementation of TB transcriptomic signatures in PLHIV.

T cell receptor repertoires associated with control and disease progression following Mycobacterium tuberculosis infection

Antigen-specific, MHC-restricted αβ T cells are necessary for protective immunity against Mycobacterium tuberculosis, but the ability to broadly study these responses has been limited. In the present study, we used single-cell and bulk T cell receptor (TCR) sequencing and the GLIPH2 algorithm to analyze M. tuberculosis-specific sequences in two longitudinal cohorts, comprising 166 individuals with M. tuberculosis infection who progressed to either tuberculosis (n = 48) or controlled infection (n = 118). We found 24 T cell groups with similar TCR-β sequences, predicted by GLIPH2 to have common TCR specificities, which were associated with control of infection (n = 17), and others that were associated with progression to disease (n = 7). Using a genome-wide M. tuberculosis antigen screen, we identified peptides targeted by T cell similarity groups enriched either in controllers or in progressors. We propose that antigens recognized by T cell similarity groups associated with control of infection can be considered as high-priority targets for future vaccine development.

Determinants of QuantiFERON Plus-diagnosed tuberculosis infection in adult Ugandan TB contacts: A cross-sectional study

BACKGROUND

The tuberculin skin test is commonly used to diagnose latent tuberculosis infection (LTBI) in resource-limited settings, but its specificity is limited by factors including cross-reactivity with BCG vaccine and environmental mycobacteria. Interferon-gamma release assays (IGRA) overcome this problem by detecting M. tuberculosis complex-specific responses, but studies to determine risk factors for IGRA-positivity in high TB burden settings are lacking.

METHODS

We conducted a cross-sectional study to determine factors associated with a positive IGRA by employing the QuantiFERON-TB® Gold-plus (QFT Plus) assay in a cohort of asymptomatic adult TB contacts in Kampala, Uganda. Multivariate logistic regression analysis with forward stepwise logit function was employed to identify independent correlates of QFT Plus-positivity.

RESULTS

Of the 202 participants enrolled, 129/202 (64%) were female, 173/202 (86%) had a BCG scar, and 67/202 (33%) were HIV-infected. Overall, 105/192 (54%, 95% CI 0.48-0.62) participants had a positive QFT Plus result. Increased risk of QFT-Plus positivity was independently associated with casual employment/unemployment vs. non-casual employment (adjusted odds ratio (aOR) 2.18, 95% CI 1.01-4.72), a family vs. non-family relation to the index patient (aOR 2.87, 95% CI 1.33-6.18), living in the same vs. a different house as the index (aOR 3.05, 95% CI 1.28-7.29), a higher body mass index (BMI) (aOR per additional kg/m2 1.09, 95% CI 1.00-1.18) and tobacco smoking vs. not (aOR 2.94, 95% CI 1.00-8.60). HIV infection was not associated with QFT-Plus positivity (aOR 0.91, 95% CI 0.42-1.96).

CONCLUSION

Interferon Gamma Release Assay positivity in this study population was lower than previously estimated. Tobacco smoking and BMI were determinants of IGRA positivity that were previously unappreciated.

Utility of a three-gene transcriptomic signature in the diagnosis of tuberculosis in a low-endemic hospital setting

BACKGROUND

Host transcriptomic blood signatures have demonstrated diagnostic potential for tuberculosis (TB), requiring further validation across different geographical settings. Discriminating TB from other diseases with similar clinical manifestations is crucial for the development of an accurate immunodiagnostic tool. In this exploratory cohort study, we evaluated the performance of potential blood-based transcriptomic signatures in distinguishing TB disease from non-TB lower respiratory tract infections in hospitalised patients in a TB low-endemic country.

METHOD

Quantitative real-time polymerase chain reaction qPCR) was used to evaluate 26 previously published genes in blood from 31 patients (14 TB and 17 lower respiratory tract infection cases) admitted to Oslo University Hospital in Norway. The diagnostic accuracies of differentially expressed genes were determined by receiver operating characteristic curves.

RESULTS

A significant difference (p < .01) in the age distribution was observed between patients with TB (mean age, 40 ± 15 years) and lower respiratory tract infection (mean age 59 ± 12 years). Following adjustment for age, ETV7, GBP1, GBP5, P2RY14 and BLK were significantly differentially expressed between patients with TB and those with LRI. A general discriminant analysis generated a three-gene signature (BAFT2, ETV7 and CD1C), which diagnosed TB with an area under the receiver operating characteristic curve (AUC) of 0.86 (95% CI, 0.69 - 1.00), sensitivity of 69.23% (95% CI, 38.57%-90.91%) and specificity of 94.12% (95% CI, 71.31%-99.85%).

CONCLUSION

The three-genes signature may have potential to improve diagnosis of TB in a hospitalised low-burden setting. However, the influence of confounding variables or covariates such as age requires further evaluation in larger studies.

Functions of exosomal non-coding RNAs to the infection with Mycobacterium tuberculosis

Tuberculosis (TB) is a major infectious disease induced by Mycobacterium tuberculosis (M. tb) which causes the world's dominant fatal bacterial contagious disease. Increasing studies have indicated that exosomes may be a novel option for the diagnosis and treatment of TB. Exosomes are nanovesicles (30-150 nm) containing lipids, proteins and non-coding RNAs (ncRNAs) released from various cells, and can transfer their cargos and communicate between cells. Furthermore, exosomal ncRNAs exhibit diagnosis potential in bacterial infections, including TB. Additionally, differential exosomal ncRNAs regulate the physiological and pathological functions of M. tb-infected cells and act as diagnostic markers for TB. This current review explored the potential biological roles and the diagnostic application prospects of exosomal ncRNAs, and included recent information on their pathogenic and therapeutic functions in TB.

A robust host-response-based signature distinguishes bacterial and viral infections across diverse global populations

Limited sensitivity and specificity of current diagnostics lead to the erroneous prescription of antibiotics. Host-response-based diagnostics could address these challenges. However, using 4,200 samples across 69 blood transcriptome datasets from 20 countries from patients with bacterial or viral infections representing a broad spectrum of biological, clinical, and technical heterogeneity, we show current host-response-based gene signatures have lower accuracy to distinguish intracellular bacterial infections from viral infections than extracellular bacterial infections. Using these 69 datasets, we identify an 8-gene signature to distinguish intracellular or extracellular bacterial infections from viral infections with an area under the receiver operating characteristic curve (AUROC) > 0.91 (85.9% specificity and 90.2% sensitivity). In prospective cohorts from Nepal and Laos, the 8-gene classifier distinguished bacterial infections from viral infections with an AUROC of 0.94 (87.9% specificity and 91% sensitivity). The 8-gene signature meets the target product profile proposed by the World Health Organization and others for distinguishing bacterial and viral infections.

Immune cell interactions in tuberculosis

Despite having been identified as the organism that causes tuberculosis in 1882, Mycobacterium tuberculosis has managed to still evade our understanding of the protective immune response against it, defying the development of an effective vaccine. Technology and novel experimental models have revealed much new knowledge, particularly with respect to the heterogeneity of the bacillus and the host response. This review focuses on certain immunological elements that have recently yielded exciting data and highlights the importance of taking a holistic approach to understanding the interaction of M. tuberculosis with the many host cells that contribute to the development of protective immunity.

Plasma host protein signatures correlating with Mycobacterium tuberculosis activity prior to and during antituberculosis treatment

There is a need for rapid non-sputum-based tests to identify and treat patients infected with Mycobacterium tuberculosis (Mtb). The overall objective of this study was to measure and compare the expression of a selected panel of human plasma proteins in patients with active pulmonary tuberculosis (ATB) throughout anti-TB treatment (from baseline to the end of treatment), in Mtb-infected individuals (TBI) and healthy donors (HD) to identify a putative host-protein signature useful for both TB diagnosis and treatment monitoring. A panel of seven human host proteins CLEC3B, SELL, IGFBP3, IP10, CD14, ECM1 and C1Q were measured in the plasma isolated from an HIV-negative prospective cohort of 37 ATB, 24 TBI and 23 HD. The protein signatures were assessed using a Luminex xMAP® to quantify the plasmatic levels in unstimulated blood of the different clinical group as well as the protein levels at baseline and at three timepoints during the 6-months ATB treatment, to compare the plasma protein levels between culture slow and fast converters that may contribute to monitor the TB treatment outcome. Protein signatures were defined using the CombiROC algorithm and multivariate models. The studied plasma host proteins showed different levels between the clinical groups and during the TB treatment. Six of the plasma proteins (CLEC3B, SELL, IGFBP3, IP10, CD14 and C1Q) showed significant differences in normalised median fluorescence intensities when comparing ATB vs HD or TBI groups while ECM1 revealed a significant difference between fast and slow sputum culture converters after 2 months following treatment (p = 0.006). The expression of a four-host protein markers (CLEC3B-ECM1-IP10-SELL) was significantly different between ATB from HD or TBI groups (respectively, p < 0.05). The expression of the same signature was significantly different between the slow vs the fast sputum culture converters after 2 months of treatment (p < 0.05). The results suggest a promising 4 host-plasma marker signature that would be associated with both TB diagnostic and treatment monitoring.

Metabolites enhance innate resistance to human Mycobacterium tuberculosis infection

To determine the mechanisms that mediate resistance to Mycobacterium tuberculosis (M. tuberculosis) infection in household contacts (HHCs) of patients with tuberculosis (TB), we followed 452 latent TB infection-negative (LTBI-) HHCs for 2 years. Those who remained LTBI- throughout the study were identified as nonconverters. At baseline, nonconverters had a higher percentage of CD14+ and CD3-CD56+CD27+CCR7+ memory-like natural killer (NK) cells. Using a whole-transcriptome and metabolomic approach, we identified deoxycorticosterone acetate as a metabolite with elevated concentrations in the plasma of nonconverters, and further studies showed that this metabolite enhanced glycolytic ATP flux in macrophages and restricted M. tuberculosis growth by enhancing antimicrobial peptide production through the expression of the surface receptor sialic acid binding Ig-like lectin-14. Another metabolite, 4-hydroxypyridine, from the plasma of nonconverters significantly enhanced the expansion of memory-like NK cells. Our findings demonstrate that increased levels of specific metabolites can regulate innate resistance against M. tuberculosis infection in HHCs of patients with TB who never develop LTBI or active TB.

A protein signature associated with active tuberculosis identified by plasma profiling and network-based analysis

Annually, approximately 10 million people are diagnosed with active tuberculosis (TB), and 1.4 million die of the disease. If left untreated, each person with active TB will infect 10-15 new individuals. The lack of non-sputum-based diagnostic tests leads to delayed diagnoses of active pulmonary TB cases, contributing to continued disease transmission. In this exploratory study, we aimed to identify biomarkers associated with active TB. We assessed the plasma levels of 92 proteins associated with inflammation in individuals with active TB (n = 20), latent TB (n = 14), or healthy controls (n = 10). Using co-expression network analysis, we identified one module of proteins with strong association with active TB. We removed proteins from the module that had low abundance or were associated with non-TB diseases in published transcriptomic datasets, resulting in a 12-protein plasma signature that was highly enriched in individuals with pulmonary and extrapulmonary TB and was further associated with disease severity.

Subsequent AS01-adjuvanted vaccinations induce similar transcriptional responses in populations with different disease statuses

Transcriptional responses to adjuvanted vaccines can vary substantially among populations. Interindividual diversity in levels of pathogen exposure, and thus of cell-mediated immunological memory at baseline, may be an important determinant of population differences in vaccine responses. Adjuvant System AS01 is used in licensed or candidate vaccines for several diseases and populations, yet the impact of pre-existing immunity on its adjuvanticity remains to be elucidated. In this exploratory post-hoc analysis of clinical trial samples (clinicalTrials.gov: NCT01424501), we compared gene expression patterns elicited by two immunizations with the candidate tuberculosis (TB) vaccine M72/AS01, between three groups of individuals with different levels of memory responses to TB antigens before vaccination. Analyzed were one group of TB-disease-treated individuals, and two groups of TB-disease-naïve individuals who were (based on purified protein derivative [PPD] skin-test results) stratified into PPD-positive and PPD-negative groups. Although TB-disease-treated individuals displayed slightly stronger transcriptional responses after each vaccine dose, functional gene signatures were overall not distinctly different between groups. Considering the similarities with the signatures found previously for other AS01-adjuvanted vaccines, many features of the response appeared to be adjuvant-driven. Across groups, cell proliferation-related signals at 7 days post-dose 1 were associated with increased anti-M72 antibody response magnitudes. These early signals were stronger in the TB-disease-treated group as compared to both TB-disease-naïve groups. Interindividual homogeneity in gene expression levels was also higher for TB-disease-treated individuals post-dose 1, but increased in all groups post-dose 2 to attain similar levels between the three groups. Altogether, strong cell-mediated memory responses at baseline accelerated and amplified transcriptional responses to a single dose of this AS01-adjuvanted vaccine, resulting in more homogenous gene expression levels among the highly-primed individuals as compared to the disease-naïve individuals. However, after a second vaccination, response heterogeneity decreased and was similar across groups, irrespective of the degree of immune memory acquired at baseline. This information can support the design and analysis of future clinical trials evaluating AS01-adjuvanted vaccines.

System-wide identification of myeloid markers of TB disease and HIV-induced reactivation in the macaque model of Mtb infection and Mtb/SIV co-infection

Mycobacterium tuberculosis (Mtb) has developed specialized mechanisms to parasitize its host cell, the macrophage. These mechanisms allow it to overcome killing by oxidative burst and persist in the wake of an inflammatory response. Mtb infection in the majority of those exposed is controlled in an asymptomatic form referred to as latent tuberculosis infection (LTBI). HIV is a well-known catalyst of reactivation of LTBI to active TB infection (ATB). Through the use of nonhuman primates (NHPs) co-infected with Mtb and Simian Immunodeficiency Virus (Mtb/SIV), we are able to simulate human progression of TB/AIDS comorbidity. The advantage of NHP models is that they recapitulate the breadth of human TB outcomes, including immune control of infection, and loss of this control due to SIV co-infection. Identifying correlates of immune control of infection is important for both vaccine and therapeutics development. Using macaques infected with Mtb or Mtb/SIV and with different clinical outcomes we attempted to identify signatures between those that progress to active infection after SIV challenge (reactivators) and those that control the infection (non-reactivators). We particularly focused on pathways relevant to myeloid origin cells such as macrophages, as these innate immunocytes have an important contribution to the initial control or the lack thereof, following Mtb infection. Using bacterial burden, C-reactive protein (CRP), and other clinical indicators of disease severity as a guide, we were able to establish gene signatures of host disease state and progression. In addition to gene signatures, clustering algorithms were used to differentiate between host disease states and identify relationships between genes. This allowed us to identify clusters of genes which exhibited differential expression profiles between the three groups of macaques: ATB, LTBI and Mtb/SIV. The gene signatures were associated with pathways relevant to apoptosis, ATP production, phagocytosis, cell migration, and Type I interferon (IFN), which are related to macrophage function. Our results suggest novel macrophage functions that may play roles in the control of Mtb infection with and without co-infection with SIV. These results particularly point towards an interplay between Type I IFN signaling and IFN-γ signaling, and the resulting impact on lung macrophages as an important determinant of progression to TB.

T-cell deficiency and hyperinflammatory monocyte responses associate with Mycobacterium avium complex lung disease

Immunological mechanisms of susceptibility to nontuberculous mycobacterial (NTM) disease are poorly understood. To understand NTM pathogenesis, we evaluated innate and antigen-specific adaptive immune responses to Mycobacterium avium complex (MAC) in asymptomatic individuals with a previous history of MAC lung disease (MACDZ). We hypothesized that Mav-specific immune responses are associated with susceptibility to MAC lung disease. We measured MAC-, NTM-, or MAC/Mtb-specific T-cell responses by cytokine production, expression of surface markers, and analysis of global gene expression in 27 MACDZ individuals and 32 healthy controls. We also analyzed global gene expression in Mycobacterium avium-infected and uninfected peripheral blood monocytes from 17 MACDZ and 17 healthy controls. We were unable to detect increased T-cell responses against MAC-specific reagents in MACDZ compared to controls, while the responses to non-mycobacteria derived antigens were preserved. MACDZ individuals had a lower frequency of Th1 and Th1* T-cell populations. In addition, MACDZ subjects had lower transcriptional responses in PBMCs stimulated with a mycobacterial peptide pool (MTB300). By contrast, global gene expression analysis demonstrated upregulation of proinflammatory pathways in uninfected and M. avium-infected monocytes, i.e. a hyperinflammatory in vitro response, derived from MACDZ subjects compared to controls. Together, these data suggest a novel immunologic defect which underlies MAC pathogenesis and includes concurrent innate and adaptive dysregulation which persists years after completion of treatment.

Malnutrition leads to increased inflammation and expression of tuberculosis risk signatures in recently exposed household contacts of pulmonary tuberculosis

Background

Most individuals exposed to Mycobacterium tuberculosis (Mtb) develop latent tuberculosis infection (LTBI) and remain at risk for progressing to active tuberculosis disease (TB). Malnutrition is an important risk factor driving progression from LTBI to TB. However, the performance of blood-based TB risk signatures in malnourished individuals with LTBI remains unexplored. The aim of this study was to determine if malnourished and control individuals had differences in gene expression, immune pathways and TB risk signatures.

Methods

We utilized data from 50 tuberculin skin test positive household contacts of persons with TB - 18 malnourished participants (body mass index [BMI] < 18.5 kg/m2) and 32 controls (individuals with BMI ≥ 18.5 kg/m2). Whole blood RNA-sequencing was conducted to identify differentially expressed genes (DEGs). Ingenuity Pathway Analysis was applied to the DEGs to identify top canonical pathways and gene regulators. Gene enrichment methods were then employed to score the performance of published gene signatures associated with progression from LTBI to TB.

Results

Malnourished individuals had increased activation of inflammatory pathways, including pathways involved in neutrophil activation, T-cell activation and proinflammatory IL-1 and IL-6 cytokine signaling. Consistent with known association of inflammatory pathway activation with progression to TB disease, we found significantly increased expression of the RISK4 (area under the curve [AUC] = 0.734) and PREDICT29 (AUC = 0.736) progression signatures in malnourished individuals.

Conclusion

Malnourished individuals display a peripheral immune response profile reflective of increased inflammation and a concomitant increased expression of risk signatures predicting progression to TB. With validation in prospective clinical cohorts, TB risk biomarkers have the potential to identify malnourished LTBI for targeted therapy.

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.

Isoniazid preventive therapy and tuberculosis transcriptional signatures in people with HIV

OBJECTIVES

To examine the association between isoniazid preventive therapy (IPT) or nontuberculous mycobacteria (NTM) sputum culture positivity and tuberculosis (TB) transcriptional signatures in people with HIV.

DESIGN

Cross-sectional study.

METHODS

We enrolled adults living with HIV who were IPT-naive or had completed IPT more than 6 months prior at HIV care clinics in western Kenya. We calculated TB signatures using gene expression data from qRT-PCR. We used multivariable linear regression to analyze the association between prior receipt of IPT or NTM sputum culture positivity with a transcriptional TB risk score, RISK6 (range 0-1). In secondary analyses, we explored the association between IPT or NTM positivity and four other TB transcriptional signatures.

RESULTS

Among 381 participants, 99.7% were receiving antiretroviral therapy and 86.6% had received IPT (completed median of 1.1 years prior). RISK6 scores were lower (mean difference 0.10; 95% confidence interval (CI): 0.06-0.15; P  < 0.001) among participants who received IPT than those who did not. In a model that adjusted for age, sex, duration of ART, and plasma HIV RNA, the RISK6 score was 52.8% lower in those with a history of IPT ( P  < 0.001). No significant association between year of IPT receipt and RISK6 scores was detected. There was no association between NTM sputum culture positivity and RISK6 scores.

CONCLUSION

In people with HIV, IPT was associated with significantly lower RISK6 scores compared with persons who did not receive IPT. These data support investigations of its performance as a TB preventive therapy response biomarker.

Transcriptional profiles predict treatment outcome in patients with tuberculosis and diabetes at diagnosis and at two weeks after initiation of anti-tuberculosis treatment

BACKGROUND

Globally, the tuberculosis (TB) treatment success rate is approximately 85%, with treatment failure, relapse and death occurring in a significant proportion of pulmonary TB patients. Treatment success is lower among people with diabetes mellitus (DM). Predicting treatment outcome early after diagnosis, especially in TB-DM patients, would allow early treatment adaptation for individuals and may improve global TB control.

METHODS

Samples were collected in a longitudinal cohort study of adult TB patients from South Africa (n  =  94) and Indonesia (n  =  81), who had concomitant DM (n  =  59), intermediate hyperglycaemia (n  =  79) or normal glycaemia/no DM (n  =  37). Treatment outcome was monitored, and patients were categorized as having a good (cured) or poor (failed, recurrence, died) outcome during treatment and 12 months follow-up. Whole blood transcriptional profiles before, during and at the end of TB treatment were characterized using unbiased RNA-Seq and targeted gene dcRT-MLPA.

FINDINGS

We report differences in whole blood transcriptome profiles, which were observed before initiation of treatment and throughout treatment, between patients with a good versus poor TB treatment outcome. An eight-gene and a 22-gene blood transcriptional signature distinguished patients with a good TB treatment outcome from patients with a poor TB treatment outcome at diagnosis (AUC = 0·815) or two weeks (AUC = 0·834) after initiation of TB treatment, respectively. High accuracy was obtained by cross-validating this signature in an external cohort (AUC = 0·749).

INTERPRETATION

These findings suggest that transcriptional profiles can be used as a prognostic biomarker for treatment failure and success, even in patients with concomitant DM.

FUNDING

The research leading to these results, as part of the TANDEM Consortium, received funding from the European Community's Seventh Framework Programme (FP7/2007-2013 Grant Agreement No. 305279) and the Netherlands Organization for Scientific Research (NWO-TOP Grant Agreement No. 91214038). The research leading to the results presented in the Indian validation cohort was supported by Research Council of Norway Global Health and Vaccination Research (GLOBVAC) projects: RCN 179342, 192534, and 248042, the University of Bergen (Norway).

Are mRNA based transcriptomic signatures ready for diagnosing tuberculosis in the clinic? - A review of evidence and the technological landscape

Funding

End-point definition and trial design to advance tuberculosis vaccine development

Tuberculosis (TB) remains a leading infectious cause of death worldwide and the coronavirus disease 2019 pandemic has negatively impacted the global TB burden of disease indicators. If the targets of TB mortality and incidence reduction set by the international community are to be met, new more effective adult and adolescent TB vaccines are urgently needed. There are several new vaccine candidates at different stages of clinical development. Given the limited funding for vaccine development, it is crucial that trial designs are as efficient as possible. Prevention of infection (POI) approaches offer an attractive opportunity to accelerate new candidate vaccines to advance into large and expensive prevention of disease (POD) efficacy trials. However, POI approaches are limited by imperfect current tools to measure Mycobacterium tuberculosis infection end-points. POD trials need to carefully consider the type and number of microbiological tests that define TB disease and, if efficacy against subclinical (asymptomatic) TB disease is to be tested, POD trials need to explore how best to define and measure this form of TB. Prevention of recurrence trials are an alternative approach to generate proof of concept for efficacy, but optimal timing of vaccination relative to treatment must still be explored. Novel and efficient approaches to efficacy trial design, in addition to an increasing number of candidates entering phase 2-3 trials, would accelerate the long-standing quest for a new TB vaccine.

Immunopathogenic overlap between COVID-19 and tuberculosis identified from transcriptomic meta-analysis and human macrophage infection

Current and previous tuberculosis (TB) increase the risk of COVID-19 mortality and severe disease. To identify mechanisms of immunopathogenic interaction between COVID-19 and TB, we performed a systematic review and patient-level meta-analysis of COVID-19 transcriptomic signatures, spanning disease severity, from whole blood, PBMCs, and BALF. 35 eligible signatures were profiled on 1181 RNA-seq samples from 853 individuals across the spectrum of TB infection. Thirteen COVID-19 gene-signatures had significantly higher "COVID-19 risk scores" in active TB and latent TB progressors compared with non-progressors and uninfected controls (p<0·005), in three independent cohorts. Integrative single-cell-RNAseq analysis identified FCN1- and SPP1-expressing macrophages enriched in severe COVID-19 BALF and active TB blood. Gene ontology and protein-protein interaction networks identified 12-gene disease-exacerbation hot spots between COVID-19 and TB. Finally, we in vitro validated that SARS-CoV-2 infection is increased in human macrophages cultured in the inflammatory milieu of Mtb-infected macrophages, correlating with TMPRSS2, IFNA1, IFNB1, IFNG, TNF, and IL1B induction.

Mycobacterium tuberculosis infection, immune activation, and risk of HIV acquisition

BACKGROUND

Although immune activation is associated with HIV acquisition, the nature of inflammatory profiles that increase HIV risk, which may include responses to M. tuberculosis (Mtb) infection, are not well characterized.

METHODS

We conducted a nested case-control study using cryopreserved samples from persons who did and did not acquire HIV during the multinational Step clinical trial of the MRKAd5 HIV-1 vaccine. PBMCs from the last HIV-negative sample from incident HIV cases and controls were stimulated with Mtb-specific antigens (ESAT-6/CFP-10) and analyzed by flow cytometry with intracellular cytokine staining and scored with COMPASS. We measured inflammatory profiles with five Correlates of TB Risk (CoR) transcriptomic signatures. Our primary analysis examined the association of latent Mtb infection (LTBI; IFNγ+CD4+ T cell frequency) or RISK6 CoR signature with HIV acquisition. Conditional logistic regression analyses, adjusted for known predictors of HIV acquisition, were employed to assess whether TB-associated immune markers were associated with HIV acquisition.

RESULTS

Among 465 participants, LTBI prevalence (21.5% controls vs 19.1% cases, p = 0.51) and the RISK6 signature were not higher in those who acquired HIV. In exploratory analyses, Mtb antigen-specific polyfunctional CD4+ T cell COMPASS scores (aOR 0.96, 95% CI 0.77, 1.20) were not higher in those who acquired HIV. Two CoR signatures, Sweeney3 (aOR 1.38 (1.07, 1.78) per SD change) and RESPONSE5 (0.78 (0.61, 0.98)), were associated with HIV acquisition. The transcriptomic pattern used to differentiate active vs latent TB (Sweeney3) was most strongly associated with acquiring HIV.

CONCLUSIONS

LTBI, Mtb polyfunctional antigen-specific CD4+ T cell activation, and RISK6 were not identified as risks for HIV acquisition. In exploratory transcriptomic analyses, two CoR signatures were associated with HIV risk after adjustment for known behavioral and clinical risk factors. We identified host gene expression signatures associated with HIV acquisition, but the observed effects are likely not mediated through Mtb infection.

A systematic review on Correlates of Risk of TB disease in children and adults

BACKGROUND

Tuberculosis (TB) remains one of the leading causes of death in the world. Targeted treatment to prevent progression from TB exposure and infection to disease is a key element of WHO End-TB strategy. A systematic review to identify and develop correlates of risk (COR) of TB disease is timely.

METHOD

EMBASE, MEDLINE, PUBMED were searched using relevant keywords and MeSH terms published between 2000 and 2020 on COR of TB disease in children and adults. Preferred Reporting Items for Systematic reviews and Meta-analysis (PRISMA) framework was used for structuring and reporting of outcomes. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies tool-2 (QUADAS-2).

RESULTS

4105 studies were identified. Following eligibility screening, 27 studies were quality assessed. Risk of bias was high in all studies. Broad variations in COR type, study population, methodology and result reporting were observed. Tuberculin skin test (TST) and interferon gamma release essays (IGRA) are poor COR. Transcriptomic signatures although promising require validation studies to assess wider applicability. Performance consistency of other CORs-cell marker, cytokines and metabolites are much needed.

CONCLUSION

This review identifies the need for a standardized approach to identify a universally applicable COR signature to achieve the WHO END-TB targets.

The Association between Circulating microRNAs and the Risk of Active Disease Development from Latent Tuberculosis Infection: a Nested Case-Control Study

Tuberculosis (TB) remains one of the deadliest communicable diseases. Biomarkers predicting the risk of active disease development from latent tuberculosis infection (LTBI) are urgently needed for precise intervention. This study aimed to identify potential circulating microRNAs (miRNAs) playing such a role in Chinese population. Based on a prospective study aiming to track the development of active TB among rural residents with LTBI, the baseline levels of circulating miRNAs were retrospectively compared between those who developed TB (case group) and those age-gender matched controls remain free of TB (contraol group) during the follow-up. Agilent human miRNA microarray were used to select differently expressed circulating miRNAs and verified by subsequent real-time quantitative PCR (RT-qPCR). Six candidate miRNAs were expressed at statistically significant levels between the two groups at the baseline, as determined by microarray. Following verification among 150 study participants by RT-qPCR, the levels of hsa-miR-16-5p (P < 0.001) and hsa-miR-451a (P < 0.001) were found to be significantly lower in case group compared to control group. The combined areas under curves (AUCs) and precision-recall curves (PRCs) were 0.84, 0.86 and 0.85, 0.87 for hsa-miR-16-5p and hsa-miR-451a, respectively. hsa-miR-451a combined with body mass index (BMI) and prior history of TB presented the best performance, with a sensitivity of 80.82% and an acceptable specificity of 79.22%. After adjusting the two co-variables, the AUC of hsa-miR-451a was 0.78. Circulating levels of hsa-miR-451a showed potential to predict development of active TB from LTBI in a Chinese population. Further studies are warranted to verify these findings in varied study settings.

IMPORTANCE Approximately a quarter of the world population are infected with M. tuberculosis and about 5% to 10% of these might develop active disease in their lifetime. Preventive treatment could effectively protect individuals at a high risk of developing active disease from LTBI, and is regarded as a critical component of End TB Strategies. Biomarkers which could accurately identify high-risk population and predict the risk of disease development are urgently needed for developing local guidelines of LTBI management and precise intervention. A nested case-control study was designed to explore possible microRNAs related with TB occurrence based on a previous prospective study, which aimed to track the development of active TB among rural residents with LTBI. The baseline circulating levels of hsa-miR-16-5p and hsa-miR-451a were significantly lower in TB cases compared to those in LTBI controls. Further receiver operator characteristic (ROC) curve analysis found that hsa-miR-451a showed considerable potential to predict the development of active TB from LTBI.

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.

Point-of-care diagnostic tests for tuberculosis disease

Rapid diagnosis is one key pillar to end tuberculosis (TB). Point-of-care tests (POCTs) facilitate early detection, immediate treatment, and reduced transmission of TB disease. This Review evaluates current diagnostic assays endorsed by the World Health Organization and identifies the gaps between existing conventional tests and the ideal POCT. We discuss the commercial development of new rapid tests and research studies on nonsputum-based diagnostic biomarkers from both pathogen and host. Last, we highlight advances in integrated microfluidics technology that may aid the development of new POCTs.

Diagnostic Advances in Childhood Tuberculosis—Improving Specimen Collection and Yield of Microbiological Diagnosis for Intrathoracic Tuberculosis

There is no microbiological gold standard for childhood tuberculosis (TB) diagnosis. The paucibacillary nature of the disease, challenges in sample collection in young children, and the limitations of currently available microbiological tests restrict microbiological confirmation of intrathoracic TB to the minority of children. Recent WHO guidelines recommend the use of novel rapid molecular assays as initial diagnostic tests for TB and endorse alternative sample collection methods for children. However, the uptake of these tools in high-endemic settings remains low. In this review, we appraise historic and new microbiological tests and sample collection techniques that can be used for the diagnosis of intrathoracic TB in children. We explore challenges and possible ways to improve diagnostic yield despite limitations, and identify research gaps to address in order to improve the microbiological diagnosis of intrathoracic TB in children.