Genome-wide expression for diagnosis of pulmonary tuberculosis: a multicohort analysis

A Prospective Evaluation of a Three-Gene Host Response Signature to Classify Tuberculosis Severity in Children

BACKGROUND

Children with non-severe TB may benefit from short-course treatment, but point-of-care tools are needed to stratify disease severity. We prospectively evaluated the Cepheid Xpert MTB-Host Response (HR) prototype cartridge for distinguishing TB severity in children with pulmonary TB (PTB) in The Gambia and Uganda.

METHODS

We included children <15 with microbiologically confirmed or clinically diagnosed unconfirmed PTB. Severity was defined using the World Health Organization (WHO) guidelines for a four-month, drug-susceptible regimen. Capillary or venous blood was tested with the HR cartridge for PCR-based detection of 3 mRNA genes and calculation of a TB score from cycle thresholds. We generated receiver operating characteristic curves with the TB score to classify severe TB and assessed if Xpert-HR could achieve the WHO target accuracy for treatment optimization (≥90% sensitivity, ≥70% specificity).

RESULTS

Among 106 children, the median age was 4 years (IQR 1-7), 56.6% were female, and 13.2% were living with HIV. In all children with PTB, Xpert-HR achieved an AUC of 0.67 (95% CI 0.55-0.78), with 89.3% sensitivity (95% CI 71.8-97.7) and 29.5% specificity (95% CI 19.7-40.9, cutoff ≤ -0.60). By confirmation status, Xpert-HR approached the target accuracy in children with Confirmed TB, with 62.5% specificity (95% CI 24.5-91.5) at 91.7% sensitivity (95% CI 61.5-99.8, cut-off ≤ -1.349). Among children with Unconfirmed TB, specificity was lower (24.3%, 95% CI 14.8-36.0) at 93.8% sensitivity (95% CI 69.8-99.8, cutoff ≤ -0.450). Target accuracy was almost achieved in children 5-9 regardless of confirmation status (100% sensitivity [95% CI 71.5-100], 66.7% specificity [95% CI 43.0-85.4], cutoff ≤ -1.35), but specificity (28.2%, 95% CI 18.6-39.5) was lower for children < 5 (92.9% sensitivity, 95% CI 76.5-99.1, cutoff ≤ -0.550).

CONCLUSIONS

Xpert-HR approached the target accuracy to stratify PTB severity in older children and those with Confirmed TB but had lower specificity in children with Unconfirmed TB. Child-specific signatures may be needed to improve performance in younger children with paucibacillary disease.

Analysis of the cross-study replicability of tuberculosis gene signatures using 49 curated human transcriptomic datasets

BACKGROUND

Tuberculosis (TB) is the leading cause of infectious disease mortality worldwide. Numerous host blood-based gene expression signatures have been proposed in the literature as alternative tools for diagnosing TB infection. However, the generalizability of these signatures to different patient contexts is not well-characterized. There is a pressing need for a well-curated database of TB gene expression studies for the systematic assessment of existing and newly developed TB gene signatures.

RESULTS

We built curatedTBData, a manually-curated database of 49 human TB transcriptomic studies. This data resource is freely available through GitHub and as an R Bioconductor package that allows users to validate new and existing biomarkers without the challenges of harmonizing heterogeneous studies. We demonstrate the use of this data resource with cross-study comparisons for 72 human host blood-based TB gene signatures. For the comparison of subjects with active TB from healthy controls, 19 gene signatures had weighted mean AUC of 0.90 or greater, with the highest result of 0.94. In active TB disease versus latent TB infection, 7 gene signatures had weighted mean AUC of 0.90 or greater, with a maximum of 0.93.

CONCLUSIONS

The curatedTBData data package offers a comprehensive resource of curated human blood-based gene expression and clinically annotated data. This resource will facilitate the development of new signatures that are generalizable across cohorts or more applicable to specific subsets of patients.

Performance of 2 Finger-Stick Blood Tests to Triage Adults With Symptoms of Pulmonary Tuberculosis: A Prospective Multisite Diagnostic Accuracy Study

BACKGROUND

Non-sputum-based, point-of-care triage tests for pulmonary tuberculosis could enhance tuberculosis diagnostic programs. We assessed the diagnostic accuracy of 2 finger-stick blood tests: the Cepheid 3 gene host-response cartridge (Xpert-HR), which measures 3 host messenger RNA transcripts, and the 3-host protein multibiomarker test (MBT).

METHODS

We performed a prospective diagnostic accuracy study of consecutive participants with symptoms compatible with pulmonary tuberculosis in The Gambia, South Africa, Uganda, and Vietnam. A composite reference standard for active pulmonary tuberculosis incorporated chest radiography, symptom resolution, and sputum microbiological test results. A training-test set approach was used to evaluate test cutoff specificities at 90% sensitivity.

RESULTS

Between 1 November 2020 and 1 May 2023, we screened 1262 participants aged 12-70 years with cough lasting >2 weeks and another symptom suggestive of tuberculosis. Of those who were classifiable by reference tests, 1154 participants had evaluable Xpert-HR results and 961 had evaluable MBT results. Xpert-HR had an area under the receiver operating characteristic (AUROC) curve of 0.92 at a cutoff of -1.275 or below, with a sensitivity of 92.8%, specificity of 62.5%, positive predictive value of 47.9%, and negative predictive value of 95.9%. The MBT had an AUROC of 0.91 at a cutoff of ≥0.42, with a sensitivity of 91.4%, specificity of 73.2%, positive predictive value of 52.0%, and negative predictive value of 96.4%.

CONCLUSIONS

Our results show that both Xpert-HR and the MBT are promising non-sputum-based point-of-care tests. The MBT met the World Health Organization target product profile for a triage test, which suggests it should be further developed.

Applications of gene pair methods in clinical research: advancing precision medicine

The rapid evolution of high-throughput sequencing technologies has revolutionized biomedical research, producing vast amounts of gene expression data that hold immense potential for biological discovery and clinical applications. Effectively mining these large-scale, high-dimensional data is crucial for facilitating disease detection, subtype differentiation, and understanding the molecular mechanisms underlying disease progression. However, the conventional paradigm of single-gene profiling, measuring absolute expression levels of individual genes, faces critical limitations in clinical implementation. These include vulnerability to batch effects and platform-dependent normalization requirements. In contrast, emerging approaches analyzing relative expression relationships between gene pairs demonstrate unique advantages. By focusing on binary comparisons of two genes' expression magnitudes, these methods inherently normalize experimental variations while capturing biologically stable interaction patterns. In this review, we systematically evaluate gene pair-based analytical frameworks. We classify eleven computational approaches into two fundamental categories: expression value-based methods quantifying differential expression patterns, and rank-based methods exploiting transcriptional ordering relationships. To bridge methodological development with practical implementation, we establish a reproducible analytical pipeline incorporating feature selection, classifier construction, and model evaluation modules using real-world benchmark datasets from pulmonary tuberculosis studies. These findings position gene pair analysis as a transformative paradigm for mining high-dimensional omics data, with direct implications for precision biomarker discovery and mechanistic studies of disease progression.

Identification and evaluation of blood transcriptional biomarker for tuberculosis screening

OBJECTIVES

Non-sputum-based screening methods for active case finding are a priority for ending tuberculosis. We sought to identify and evaluate blood transcriptional biomarkers suitable for tuberculosis screening.

METHODS

We integrated five blood RNA-seq datasets from global tuberculosis patients and identified genes that are differentially expressed between tuberculosis patients and healthy controls, using resampling and exhaustive testing. Three candidate biomarker combinations were identified from seven microarray datasets and small-scale clinical samples. The performance of these combinations for screening was evaluated in a cohort of close contacts of pulmonary tuberculosis (PTB) patients, and the results compared with Xpert HR.

RESULTS

We identified three 3-gene biomarker combinations, each containing two upregulated genes (FCGR1A, BATF2, or GBP5) and one downregulated gene (KLF2), and used these combinations to screen 352 close contacts of PTB. The biomarker combinations distinguished confirmed PTB patients from other participants with AUCs ranging from 0.848 to 0.870. With specificity fixed at 70%, all three combinations showed sensitivities of 87.5%. In a cohort of 205 presumptive pulmonary tuberculosis patients, the AUCs for distinguishing confirmed tuberculosis patients from other diseases ranged from 0.784 to 0.806. At 70% specificity, sensitivities were 75.9-81.5%, and were significantly higher with larger sputum bacterial loads. The performances of the three combinations for tuberculosis screening or diagnosis were comparable to Xpert HR.

CONCLUSION

The three transcriptomic biomarkers identified in this study performed well for tuberculosis screening, nearly meeting the minimum WHO benchmarks for a triage test and showed potential utility in the development of new screening tools.

Assessing the risk of TB progression: Advances in blood-based biomarker research

This review addresses the significant advancements in the identification of blood-based prognostic biomarkers for tuberculosis (TB), highlighting the importance of early detection to prevent disease progression. The manuscript discusses various biomarker categories, including transcriptomic, proteomic, metabolomic, immune cell-based, cytokine-based, and antibody response-based markers, emphasizing their potential in predicting TB incidence. Despite promising results, practical application is hindered by high costs, technical complexities, and the need for extensive validation across diverse populations. Transcriptomic biomarkers, such as the Risk16 signature, show high sensitivity and specificity, while proteomic and metabolic markers provide insights into protein-level changes and biochemical alterations linked to TB. Immune cell and cytokine markers offer real-time data on the body's response to infection. The manuscript also explores the role of single-nucleotide polymorphisms in TB susceptibility and the challenges of implementing novel RNA signatures as point-of-care tests in low-resource settings. The review concludes that, while significant progress has been made, further research and development are necessary to refine these biomarkers, improve their practical application, and achieve the World Health Organization's TB elimination goals.

A 5-transcript signature for discriminating viral and bacterial etiology in pediatric pneumonia

Pneumonia stands as the primary cause of death among children under five, yet current diagnosis methods often result in inadequate or unnecessary treatments. Our research seeks to address this gap by identifying host transcriptomic biomarkers in the blood of children with definitive viral and bacterial pneumonia. We performed RNA sequencing on 192 prospectively collected whole blood samples, including 38 controls and 154 pneumonia cases, uncovering a 5-transcript signature (genes FAM20A, BAG3, TDRD9, MXRA7, and KLF14) that effectively distinguishes bacterial from viral pneumonia (area under the curve (AUC): 0.95 [0.88-1.00]). Initial validation using combined definitive and probable cases yielded an AUC of 0.87 [0.77-0.97], while full validation in a new prospective cohort of 32 patients achieved an AUC of 0.92 [0.83-1.00]. This robust signature holds significant potential to enhance diagnostics accuracy for pediatric pneumonia, reducing diagnostic delays and unnecessary treatments and potentially transforming clinical practice.

Prospective Exploratory Evaluation of Cepheid Xpert Mycobacterium tuberculosis Host Response Cartridge: A Focus on Adolescents and Young Adults

BACKGROUND

An accurate, rapid, non-sputum-based triage test for diagnosing tuberculosis (TB) is needed.

METHODS

A prospective evaluation of the Cepheid GeneXpert Mycobacterium tuberculosis Host Response cartridge (Xpert-MTB-HR), a prototype blood-based host response mRNA signature assay, among individuals presenting with TB-like symptoms was performed in Pakistan and results were compared to 3 reference standards: Xpert MTB/RIF Ultra, bacteriological confirmation (Xpert MTB/RIF Ultra and/or culture positivity), and composite clinical diagnosis (clinician diagnosis, treatment initiation, Xpert MTB/RIF Ultra, and/or culture positivity). Analyses were conducted both for the entire study cohort and separately in the adolescent and young adult cohort (aged 10-24 years).

RESULTS

A total of 497 participants, aged 6-83 years, returned valid Xpert-MTB-HR results. When a diagnostic threshold was set for a sensitivity of >90%, specificity was 32% (95% confidence interval [CI], 28%-37%) compared to Xpert MTB/RIF Ultra, 29% (95% CI, 25%-34%) compared to a bacteriological confirmation, and 22% (95% CI, 18%-26%) compared to a composite clinical diagnosis. However, when evaluating only the adolescent and young adult cohort with a diagnostic threshold set for sensitivity of >90%, specificity was 82% (95% CI, 74%-89%) compared to Xpert MTB/RIF Ultra, 84% (95% CI, 75%-90%) compared to a bacteriological confirmation, and 54% (95% CI, 44%-64%) compared to a composite clinical diagnosis.

CONCLUSIONS

While the Xpert-MTB-HR does not meet World Health Organization minimum criteria in the general population, in our study it does meet the minimum sensitivity and specificity requirements for a non-sputum-based triage test among adolescents and young adults when compared to Xpert MTB/RIF Ultra or bacteriological confirmation.

Backtranslation of human RNA biosignatures of tuberculosis disease risk into the preclinical pipeline is condition dependent

It is unclear whether human progression to active tuberculosis disease (TB) risk signatures are viable endpoint criteria for evaluations of treatments in development. TB is the deadliest infectious disease globally and more efficacious vaccines are needed to reduce this mortality. However, the immune correlates of protection for either preventing infection with Mycobacterium tuberculosis or preventing TB disease have yet to be completely defined, making the advancement of candidate vaccines through the pipeline slow, costly, and fraught with risk. Human-derived correlate of risk (COR) gene signatures, which identify an individual's risk of progressing to active TB disease, provide an opportunity for evaluating new therapies for TB with clear and defined endpoints. Though prospective clinical trials with longitudinal sampling are prohibitively expensive, the characterization of COR gene signatures is practical with preclinical models. Using a 3Rs (replacement, reduction, and refinement) approach we reanalyzed heterogeneous publicly available transcriptional data sets to determine whether a specific set of COR signatures are viable endpoints in the preclinical pipeline. We selected RISK6, Sweeney3, and BATF2 human-derived blood-based RNA biosignatures because they require relatively few genes and have been carefully evaluated across several clinical cohorts. These data suggest that in certain experimental designs and in several tissue types, human COR signatures correlate with disease progression as measured by the bacterial burden in the preclinical TB model pipeline. We observed the best performance when the model most closely reflected human infection or disease conditions. Human-derived COR signatures offer an opportunity for high-throughput preclinical endpoint criteria of vaccine and drug therapy evaluations.

IMPORTANCE

Understanding the strengths or limitations of back-translating human-derived correlate of risk (COR) RNA signatures into the preclinical pipeline may help streamline down-selection of therapeutic vaccine and drug candidates and better align preclinical models with proposed clinical trial efficacy endpoints.

Detection of M. tuberculosis DNA in peripheral blood mononuclear cells of tuberculosis contacts does not associate with blood RNA signatures for incipient tuberculosis

Human exposure to Mycobacterium tuberculosis (Mtb) is thought to result in a spectrum of outcomes, including bacillary clearance, quiescent Mtb infection, incipient tuberculosis (TB), subclinical TB and active TB [1]. Incipient TB – defined as a prolonged asymptomatic phase of early disease preceding clinical presentation as active disease [2] – may be distinguished from quiescent Mtb infection by detection of host gene expression signatures in blood, whose presence associates with increased risk of progression to active TB [3].

Detection of M. tuberculosis DNA in TB contacts’ PBMCs does not associate with blood RNA signatures for incipient tuberculosis https://bit.ly/4dliODg

Assessment of transcriptional markers for the differentiation of Mycobacterium mungi infection status in free-ranging banded mongoose (Mungos mungo)

There is an increasingly urgent need to improve our ability to accurately forecast and control zoonotic diseases in wildlife reservoirs. We are confronted, however, with the continued challenge of accurately determining host infection status across space and time. This dilemma is epitomized with the Mycobacterium tuberculosis Complex (MTBC) pathogens and particularly in free-ranging wildlife, a critical global challenge for both human and animal health. In humans, transcriptional markers have been increasingly identified as a robust tool for diagnosing Mycobacterium tuberculosis (MTB) infection status but have rarely been utilized for diagnosing TB in free-ranging wildlife populations. Here, we report the first use of transcriptional markers to evaluate TB infection status in a free-ranging wildlife species, banded mongoose (Mungos mungo), infected with the MTBC pathogen, Mycobacterium mungi. In this study, we found that GBP5 and DUSP3 were significantly upregulated in free-ranging banded mongoose infected with M. mungi. These results provide the first step in developing an antemortem diagnostic tool for use in free-ranging wildlife species. Our results highlight the potential of transcriptional marker-based assays to advance our ability to detect and manage TB in free-ranging wildlife, especially in field studies and other scenarios when conventional diagnostics are not feasible.

Distinguish active tuberculosis with an immune-related signature and molecule subtypes: a multi-cohort analysis

BACKGROUND

Distinguishing latent tuberculosis infection (LTBI) from active tuberculosis (ATB) is very important. This study aims to analyze cases from multiple cohorts and get the signature that can distinguish LTBI from ATB.

METHODS

Thirteen datasets were downloaded from the gene expression omnibus (GEO) database. Three datasets were selected as discovery datasets, and the hub genes were discovered through WGCNA. In the training cohort, we use machine learning to establish the signature, verify the authentication ability of the signature in the remaining datasets, and compare it with other signatures. Cluster analysis was carried out on ATB cases, immune cell infiltration analysis, GSVA analysis, and drug sensitivity analysis were carried out on different clusters.

RESULTS

In the discovery datasets, we discovered five hub genes. A signature (SLC26A8, ANKRD22, and FCGR1B) is obtained in the training cohort. In the total cohort, the three-gene signature can separate LTBI from ATB (the total area under ROC curve (AUC) is 0.801, 95% CI 0.771-0.830). Compared with other author's signatures, our signature shows good identification ability. Immunological analysis showed that SLC26A8, ANKRD22, and FCGR1B were closely related to the infiltration of immune cells. According to the expression of the three genes, ATB can be divided into two clusters, which are different in immune cell infiltration analysis, gene set variation, and drug sensitivity.

CONCLUSION

Our study produced an immune-related three-gene signature to distinguish LTBI from ATB, which may help us to manage and treat tuberculosis patients.

A DNA methylation signature identified in the buccal mucosa reflecting active tuberculosis is changing during tuberculosis treatment

Tuberculosis (TB) poses a significant global health threat, with high mortality rates if left untreated. Current sputum-based TB treatment monitoring methods face numerous challenges, particularly in relation to sample collection and analysis. This pilot study explores the potential of TB status assessment using DNA methylation (DNAm) signatures, which are gaining recognition as diagnostic and predictive tools for various diseases. We collected buccal swab samples from pulmonary TB patients at the commencement of TB treatment (n = 10), and at one, two, and six-month follow-up intervals. We also collected samples from healthy controls (n = 10) and individuals exposed to TB (n = 10). DNAm patterns were mapped using the Illumina Infinium Methylation EPIC 850 K platform. A DNAm profile distinct from controls was discovered in the oral mucosa of TB patients at the start of treatment, and this profile changed throughout the course of TB treatment. These findings were corroborated in a separate validation cohort of TB patients (n = 41), monitored at two and six months into their TB treatment. We developed a machine learning model to predict symptom scores using the identified DNAm TB profile. The model was trained and evaluated on the pilot, validation, and two additional independent cohorts, achieving an R2 of 0.80, Pearson correlation of 0.90, and mean absolute error of 0.13. While validation is needed in larger cohorts, the result opens the possibility of employing DNAm-based diagnostic and prognostic tools for TB in future clinical practice.

Transcriptional profile of Mycobacterium tuberculosis infection in people living with HIV

In people with HIV-1 (PWH), Mycobacterium tuberculosis (MTB) infection poses a significant threat. While active tuberculosis (TB) accelerates immunodeficiency, the interaction between MTB and HIV-1 during asymptomatic phases remains unclear. Analysis of peripheral blood mononuclear cells (PBMC) transcriptomic profiles in PWH, with and without controlled viral loads, revealed distinct clustering in MTB-infected individuals. Functional annotation identified alterations in IL-6, TNF, and KRAS pathways. Notably, MTB-related genes displayed an inverse correlation with HIV-1 viremia, at both individual and signature score levels. These findings suggest that MTB infection in PWH induces a shift in immune system activation, inversely related to HIV-1 viral load. These results may explain the observed enhanced antiretroviral control in MTB-infected PWH. This study highlights the complex interplay between MTB and HIV-1, emphasizing the importance of understanding their interaction for managing co-infections in this population.

Specific human gene expression in response to infection is an effective marker for diagnosis of latent and active tuberculosis

RNA sequencing and microarray analysis revealed transcriptional markers expressed in whole blood can differentiate active pulmonary TB (ATB) from other respiratory diseases (ORDs), and latent TB infection (LTBI) from healthy controls (HC). Here we describe a streamlined reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) assay that could be applied at near point-of-care for diagnosing and distinguishing ATB from ORDs and LTBI from HC. A literature review was undertaken to identify the most plausible host-gene markers (HGM) of TB infection. Primers, and dual labelled hydrolysis probes were designed and analytically evaluated for accuracy in an in-vitro model of infection using a lung fibroblast cell-line. Best performing genes were multiplexed into panels of 2-4 targets and taken forward for clinical evaluation. Mycobacteria Growth Indicator Tube and QuantiFERON-TB Gold Plus were used as reference tests for ATB and LTBI respectively. A total of 16 HGM were selected and incorporated into five multiplex RT-qPCR panels. PCR assay efficiency of all evaluated targets was ≥ 90% with a median analytical sensitivity of 292 copies/µl [IQR: 215.0-358.3 copies/µl], and a median limit of quantification of 61.7 copies/µl [IQR: 29.4-176.3 copies/µl]. Clinically, ATB was characterised by higher gene expression than ORDs, while LTBI was associated with lower gene expression than HC, Kruskal-Wallis p < 0.0001. Crucially, BATF2, CD64, GBP5, C1QB, GBP6, DUSP3, and GAS6 exhibited high differentiative ability for ATB from ORDs, LTBI or HC while KLF2, PTPRC, NEMF, ASUN, and ZNF296 independently discriminated LTBI from HC. Our results show that different HGM maybe required for ATB and LTBI differentiation from ORDs or HC respectively and demonstrate the feasibility of host gene-based RT-qPCR to diagnose ATB and LTBI at near point-of-care.

Whole blood transcriptional profiles and the pathogenesis of tuberculous meningitis

Mortality and morbidity from tuberculous meningitis (TBM) are common, primarily due to inflammatory response to Mycobacterium tuberculosis infection, yet the underlying mechanisms remain poorly understood. We aimed to uncover genes and pathways associated with TBM pathogenesis and mortality, and determine the best predictors of death, utilizing whole-blood RNA sequencing from 281 Vietnamese adults with TBM, 295 pulmonary tuberculosis (PTB), and 30 healthy controls. Through weighted gene co-expression network analysis, we identified hub genes and pathways linked to TBM severity and mortality, with a consensus analysis revealing distinct patterns between HIV-positive and HIV-negative individuals. We employed multivariate elastic-net Cox regression to select candidate predictors of death, then logistic regression and internal bootstrap validation to choose best predictors. Increased neutrophil activation and decreased T and B cell activation pathways were associated with TBM mortality. Among HIV-positive individuals, mortality associated with increased angiogenesis, while HIV-negative individuals exhibited elevated TNF signaling and impaired extracellular matrix organization. Four hub genes-MCEMP1, NELL2, ZNF354C, and CD4-were strong TBM mortality predictors. These findings indicate that TBM induces a systemic inflammatory response similar to PTB, highlighting critical genes and pathways related to death, offering insights for potential therapeutic targets alongside a novel four-gene biomarker for predicting outcomes.

Diagnostic Efficiency of the Blood-Based Cepheid 3-Gene Host Response Test and Urine-Based Lipoarabinomannan for Active Tuberculosis Case Detection at a General Hospital in China

Objective

To assess the diagnostic performance of the blood-based Cepheid 3-gene Host Response test (MTB-HR), urine-based Lipoarabinomannan (LAM), and a combination of MTB-HR and LAM (MTB-HR & LAM) for detecting active tuberculosis (ATB).

Methods

All participants were recruited from the First Affiliated Hospital, Zhejiang University School of Medicine, between June 8, 2023 and September 13, 2023. Subsequently, the participants were classified into the ATB group or non-active tuberculosis (non-ATB) group based on microbiological evidence. MTB-HR and LAM tests were performed using fingerstick blood and urine samples from each participant, respectively. The diagnostic performance of the tests was evaluated based on the sensitivity, specificity, Youden index, and Kappa value. Pairwise comparisons of the areas under the receiver operating characteristic curves (AUROCs) between different tests were conducted using nonparametric methods.

Results

A total of 297 participants were included. The MTB-HR test demonstrated diagnostic efficacy with a sensitivity of 77.37% (95% CI: 70.37-84.38) and a specificity of 85.63% (95% CI: 80.19-91.06). The LAM test demonstrated a high specificity of 97.50% (95% CI: 95.08-99.92), albeit with a lower sensitivity of 54.74% (95% CI: 46.41-63.082). The sensitivity and specificity of the MTB-HR & LAM were 83.21% (95% CI: 76.95-89.47) and 83.13% (95% CI: 77.32-88.93), respectively. Only MTB-HR & LAM exhibited higher values of area under the receiver operating characteristic curve than the LAM test (MTB-HR & LAM vs LAM: 0.83 vs 0.76, P=0.0031).

Conclusion

In this study, although both non-sputum-based triage MTB-HR and LAM do not meet the WHO diagnostic target currently, they show possible values for triage and diagnosis in ATB. Compared to single MTB-HR or LAM test, the combined MTB-HR & LAM does not demonstrate advantages.

Advances in tuberculosis biomarkers: unravelling risk factors, active disease and treatment success

Tuberculosis (TB) is a major global health threat and demands improved diagnostic and treatment monitoring methods. Conventional diagnostics, such as sputum smear microscopy and culture, are limited by slow results and low sensitivity, particularly in certain patient groups. Recent advances in biomarker research offer promising solutions in three key areas: risk of disease, diagnosis of active disease and monitoring of treatment response. For risk assessment, novel genetic signatures and metabolites show potential in predicting the progression from TB infection to active TB. A 16-gene signature, for example, predicts this progression with significant accuracy. In diagnosing active TB, RNA-based transcriptomic signatures provide higher diagnostic accuracy than traditional methods. These signatures, such as a three-gene RNA sequence, effectively differentiate active TB from other diseases and infections, addressing issues of specificity and sensitivity. Monitoring treatment response is crucial, given the varying response rates in treating TB. Emerging biomarkers focus on bacterial burden and host response. They offer more precise and timely assessments of treatment efficacy, enhance personalised treatment approaches and potentially improve patient outcomes. These advancements in biomarkers for TB risk, diagnosis and treatment response represent significant steps towards more effective TB management and control, aligning with global efforts to decrease the burden of TB. Here we aim to highlight several promising biomarkers used to predict risk of disease progression, active TB disease and treatment success.

CXCL9/CXCL10 as biomarkers the monitoring of treatment responses in Pulmonary TB patients: a systematic review and meta-analysis

BACKGROUND

Tuberculosis (TB) remains a persistent threat to global public health and traditional treatment monitoring approaches are limited by their potential for contamination and need for timely evaluation. Therefore, new biomarkers are urgently required for monitoring the treatment efficacy of TB.

METHODS

This study aimed to elucidate the levels of CXCL10 and CXCL9 in pulmonary TB patients who underwent anti-TB treatment. The data was acquired from five databases, including PubMed, Ovid, Web of Science, Embase, and the Cochrane Library. A meta-analysis of CXCL10 data from all time points was conducted. Furthermore, a trend meta-analysis of temporal data of CXCL10 and CXCL9 from multiple time points was also performed.

RESULTS

It was revealed that patients who responded poorly to anti-TB treatment had higher serum levels relative to those who responded well (SMD: 1.23, 95% CI: -0.37-2.84) at the end of intensive treatment (2 months). Furthermore, heterogeneity was observed in these results, which might be because patients with a prior history of TB and different treatment monitoring methods than those selected in this study were also included. The analysis of alterations in CXCL10 and CXCL9 levels since the last collection time points indicated that their levels reduced with time.

CONCLUSION

In summary, the study revealed that reductions in CXCL10 levels during the first two months of anti-TB treatment are correlated with treatment responses. Furthermore, decreasing levels of CXCL9 during the treatment suggest that it may also serve as a biomarker with a similar value to CXCL10. Future in-depth studies are thus warranted to further probe the relevance of CXCL10 and CXCL9 in monitoring the treatment efficacy of TB.

Novel RNA biomarkers improve discrimination of children with tuberculosis disease from those with non-TB pneumonia after in vitro stimulation

The diagnosis of pediatric tuberculosis (TB) poses a challenge for clinical teams worldwide. TB-mediated changes in the expression of host genes in the peripheral blood can serve as diagnostic biomarkers and can provide better insights into the host immune mechanisms of childhood TB. Peripheral blood mononuclear cells (PBMCs) from children (n=102) with microbiologically confirmed TB disease, TB infection (TBI), pneumonia, and healthy controls (HC) were stimulated with either the Purified Protein Derivative (PPD) or the Early Secretory Antigen 6kDa-Culture Filtrate Protein 10 (ESAT6-CFP10) complex of Mycobacterium tuberculosis (Mtb). RNA was extracted and quantified using gene expression microarrays. Differential expression analysis was performed comparing microbiologically confirmed TB to the other diagnostic groups for the stimulated and unstimulated samples. Using variable selection, we identified sparse diagnostic gene signatures; one gene (PID1) was able to distinguish TB from pneumonia after ESAT6-CFP10 stimulation with an AUC of 100% in the test set, while a combination of two genes (STAT1 and IFI44) achieved an AUC of 91.7% (CI95% 75.0%-100%) in the test set after PPD stimulation. The number of significantly differentially expressed (SDE) genes was higher when contrasting TB to pneumonia or HC in stimulated samples, compared to unstimulated ones, leading to a larger pool of candidate diagnostic biomarkers. Our approach provides enlightened aspects of peripheral TB-specific responses and can form the basis for a point of care test meeting the World Health Organization (WHO) Target Product Profile (TPP) for pediatric TB.

Co-regulation of innate and adaptive immune responses induced by ID93+GLA-SE vaccination in humans

Introduction

Development of an effective vaccine against tuberculosis is a critical step towards reducing the global burden of disease. A therapeutic vaccine might also reduce the high rate of TB recurrence and help address the challenges of drug-resistant strains. ID93+GLA-SE is a candidate subunit vaccine that will soon be evaluated in a phase 2b efficacy trial for prevention of recurrent TB among patients undergoing TB treatment. ID93+GLA-SE vaccination was shown to elicit robust CD4+ T cell and IgG antibody responses among recently treated TB patients in the TBVPX-203 Phase 2a study (NCT02465216), but the mechanisms underlying these responses are not well understood.

Methods

In this study we used specimens from TBVPX-203 participants to describe the changes in peripheral blood gene expression that occur after ID93+GLA-SE vaccination.

Results

Analyses revealed several distinct modules of co-varying genes that were either up- or down-regulated after vaccination, including genes associated with innate immune pathways at 3 days post-vaccination and genes associated with lymphocyte expansion and B cell activation at 7 days post-vaccination. Notably, the regulation of these gene modules was affected by the dose schedule and by participant sex, and early innate gene signatures were correlated with the ID93-specific CD4+ T cell response.

Discussion

The results provide insight into the complex interplay of the innate and adaptive arms of the immune system in developing responses to vaccination with ID93+GLA-SE and demonstrate how dosing and schedule can affect vaccine responses.

Diagnostic value of lncRNAs LINC00152 and LARS2-AS1 and their regulatory roles in macrophage immune response in tuberculosis

OBJECTIVES

To determine the usefulness of LINC00152 and LARS2-AS1 as potential biomarkers for latent tuberculosis (LTB) and active tuberculosis (ATB), as well as their effect on Mycobacterium (Mtb) infection.

METHODS

The expression levels of LINC00152 and LARS2-AS1 in the health, patients with LTB and ATB were detected by qRT-PCR. The ROC curves were constructed to show their potential as biomarkers. The intracellular survival assays for Mtb and the levels of immune-related cytokines were determined to discover the effect of LINC00152 and LARS2-AS1 on Mtb infection. The relationships of miR-485-5p with LINC00152 and LARS2-AS1 were explored.

RESULTS

LINC00152 and LARS2-AS1 levels were significantly elevated in patients with ATB and LTB, and Mtb-infected macrophages. LINC00152 and LARS2-AS1 can distinguish the LTB from the health and ATB from LTB. LARS2-AS1 and LINC00152 knock-down reduced the intracellular Mtb survival and induced cellular immune response after Mtb challenge. miR-485-5p was a targeting miRNA for LINC00152 and LARS2-AS1.

CONCLUSIONS

LINC00152 and LARS2-AS1 can be considered as potential biomarkers for tuberculosis disease. LINC00152 and LARS2-AS1 have anti-Mtb effects.

The Ability of a 3-Gene Host Signature in Blood to Distinguish Tuberculous Meningitis From Other Brain Infections

BACKGROUND

Tuberculous meningitis (TBM) is difficult to diagnose. We investigated whether a 3-gene host response signature in blood can distinguish TBM from other brain infections.

METHODS

The expression of 3 genes (dual specificity phosphatase 3 [DUSP3], guanylate-binding protein [GBP5], krupple-like factor 2 [KLF2]) was analyzed by RNA sequencing of archived whole blood from 4 cohorts of Vietnamese adults: 281 with TBM, 279 with pulmonary tuberculosis, 50 with other brain infections, and 30 healthy controls. Tuberculosis scores (combined 3-gene expression) were calculated following published methodology and discriminatory performance compared using area under a receiver operator characteristic curve (AUC).

RESULTS

GBP5 was upregulated in TBM compared to other brain infections (P < .001), with no difference in DUSP3 and KLF2 expression. The diagnostic performance of GBP5 alone (AUC, 0.74; 95% confidence interval [CI], .67-.81) was slightly better than the 3-gene tuberculosis score (AUC, 0.66; 95% CI, .58-.73) in TBM. Both GBP5 expression and tuberculosis score were higher in participants with human immunodeficiency virus (HIV; P < .001), with good diagnostic performance of GBP5 alone (AUC, 0.86; 95% CI, .80-.93).

CONCLUSIONS

The 3-gene host signature in whole blood has the ability to discriminate TBM from other brain infections, including in individuals with HIV. Validation in large prospective diagnostic study is now required.

Integrating pathogen- and host-derived blood biomarkers for enhanced tuberculosis diagnosis: a comprehensive review

This review explores the evolving landscape of blood biomarkers in the diagnosis of tuberculosis (TB), focusing on biomarkers derived both from the pathogen and the host. These biomarkers provide critical insights that can improve diagnostic accuracy and timeliness, essential for effective TB management. The document highlights recent advancements in molecular techniques that have enhanced the detection and characterization of specific biomarkers. It also discusses the integration of these biomarkers into clinical practice, emphasizing their potential to revolutionize TB diagnostics by enabling more precise detection and monitoring of the disease progression. Challenges such as variability in biomarker expression and the need for standardized validation processes are addressed to ensure reliability across different populations and settings. The review calls for further research to refine these biomarkers and fully harness their potential in the fight against TB, suggesting a multidisciplinary approach to overcome existing barriers and optimize diagnostic strategies. This comprehensive analysis underscores the significance of blood biomarkers as invaluable tools in the global effort to control and eliminate TB.

Blood transcriptomic signatures for symptomatic tuberculosis in an African multicohort study

BACKGROUND

Multiple host blood transcriptional signatures have been developed as non-sputum triage tests for tuberculosis (TB). We aimed to compare the diagnostic performance of 20 blood transcriptomic TB signatures for differentiating between symptomatic patients who have TB versus other respiratory diseases (ORD).

METHODS

As part of a nested case-control study, individuals presenting with respiratory symptoms at primary healthcare clinics in Ethiopia, Malawi, Namibia, Uganda, South Africa and The Gambia were enrolled. TB was diagnosed based on clinical, microbiological and radiological findings. Transcriptomic signatures were measured in whole blood using microfluidic real-time quantitative PCR. Diagnostic performance was benchmarked against the World Health Organization Target Product Profile (TPP) for a non-sputum TB triage test.

RESULTS

Among 579 participants, 158 had definite, microbiologically confirmed TB, 32 had probable TB, while 389 participants had ORD. Nine signatures differentiated between ORD and TB with equivalent performance (Satproedprai7: area under the curve 0.83 (95% CI 0.79-0.87); Jacobsen3: 0.83 (95% CI 0.79-0.86); Suliman2: 0.82 (95% CI 0.78-0.86); Roe1: 0.82 (95% CI 0.78-0.86); Kaforou22: 0.82 (95% CI 0.78-0.86); Sambarey10: 0.81 (95% CI 0.77-0.85); Duffy9: 0.81 (95% CI 0.76-0.86); Gliddon3: 0.8 (95% CI 0.75-0.85); Suliman4 0.79 (95% CI 0.75-0.84)). Benchmarked against a 90% sensitivity, these signatures achieved specificities between 44% (95% CI 38-49%) and 54% (95% CI 49-59%), not meeting the TPP criteria. Signature scores significantly varied by HIV status and country. In country-specific analyses, several signatures, such as Satproedprai7 and Penn-Nicholson6, met the minimal TPP criteria for a triage test in Ethiopia, Malawi and South Africa.

CONCLUSION

No signatures met the TPP criteria in a pooled analysis of all countries, but several signatures met the minimum criteria for a non-sputum TB triage test in some countries.

Sex-specific blood-derived RNA biomarkers for childhood tuberculosis

Confirmatory diagnosis of childhood tuberculosis (TB) remains a challenge mainly due to its dependence on sputum samples and the paucibacillary nature of the disease. Thus, only ~ 30% of suspected cases in children are diagnosed and the need for minimally invasive, non-sputum-based biomarkers remains unmet. Understanding host molecular changes by measuring blood-based transcriptomic markers has shown promise as a diagnostic tool for TB. However, the implication of sex contributing to disease heterogeneity and therefore diagnosis remains to be understood. Using publicly available gene expression data (GSE39939, GSE39940; n = 370), we report a sex-specific RNA biomarker signature that could improve the diagnosis of TB disease in children. We found four gene biomarker signatures for male (SLAMF8, GBP2, WARS, and FCGR1C) and female pediatric patients (GBP6, CELSR3, ALDH1A1, and GBP4) from Kenya, South Africa, and Malawi. Both signatures achieved a sensitivity of 85% and a specificity of 70%, which approaches the WHO-recommended target product profile for a triage test. Our gene signatures outperform most other gene signatures reported previously for childhood TB diagnosis.

Blood RNA signatures outperform CRP triage of tuberculosis lymphadenitis and pericarditis

Background

Limited data are available on the diagnostic accuracy of blood RNA biomarker signatures for extrapulmonary TB (EPTB). We addressed this question among people investigated for TB lymphadenitis and TB pericarditis, in Cape Town, South Africa.

Methods

We enrolled 440 consecutive adults referred to a hospital for invasive sampling for presumptive TB lymphadenitis (n=300) or presumptive TB pericarditis (n=140). Samples from the site of disease underwent culture and/or molecular testing for Mycobacterium tuberculosis complex (Mtb). Discrimination of patients with and without TB defined by microbiology or cytology reference standards was evaluated using seven previously reported blood RNA signatures by area under the receiver-operating characteristic curve (AUROC) and sensitivity/specificity at predefined thresholds, benchmarked against blood C-reactive protein (CRP) and the World Health Organization (WHO) target product profile (TPP) for a TB triage test. Decision curve analysis (DCA) was used to evaluate the clinical utility of the best performing blood RNA signature and CRP.

Results

Data from 374 patients for whom results were available from at least one microbiological test from the site of disease, and blood CRP and RNA measurements, were included. Using microbiological results as the reference standard in the primary analysis (N=204 with TB), performance was similar across lymphadenitis and pericarditis patients. In the pooled analysis of both cohorts, all RNA signatures had comparable discrimination with AUROC point estimates ranging 0.77-0.82, superior to that of CRP (0.61, 95% confidence interval 0.56-0.67). The best performing signature (Roe3) achieved an AUROC of 0.82 (0.77-0.86). At a predefined threshold of 2 standard deviations (Z2) above the mean of a healthy reference control group, this signature achieved 78% (72-83%) sensitivity and 69% (62-75%) specificity. In this setting, DCA revealed that Roe3 offered greater net benefit than other approaches for services aiming to reduce the number needed to investigate with confirmatory testing to <4 to identify each case of TB.

Interpretation

RNA biomarkers show better accuracy and clinical utility than CRP to trigger confirmatory TB testing in patients with TB lymphadenitis and TB pericarditis, but still fall short of the WHO TPP for TB triage tests.

Funding

South African MRC, EDCTP2, NIH/NIAID, Wellcome Trust, NIHR, Royal College of Physicians London.

Research in context

Evidence before this study: Blood RNA biomarker signatures and CRP measurements have emerged as potential triage tests for TB, but evidence is mostly limited to their performance in pulmonary TB. Microbiological diagnosis of extrapulmonary TB (EPTB) is made challenging by the need for invasive sampling to obtain tissue from the site of disease. This is compounded by lower sensitivity of confirmatory molecular tests for EPTB compared to their performance in pulmonary disease. We performed a systematic review of diagnostic accuracy studies of blood RNA biomarkers or CRP measurements for EPTB, which could mitigate the need for site-of-disease sampling for the diagnosis of TB. We searched PubMed up to 1 st August 2023, using the following criteria: "extrapulmonary [title/abstract] AND tuberculosis [title/abstract] AND biomarker [title/abstract]". Although extrapulmonary TB was included in several studies, none focused specifically on EPTB or included an adequate number of EPTB cases to provide precise estimates of test accuracy. Added value of this study: To the best of our knowledge, we report the first diagnostic accuracy study of blood RNA biomarkers and CRP for TB among people with EPTB syndromes. We examined the performance of seven previously identified blood RNA biomarkers as triage tests for TB lymphadenitis and TB pericarditis compared to a microbiology reference standard among people referred to hospital for invasive sampling in a high TB and HIV prevalence setting. Multiple blood RNA biomarkers showed comparable diagnostic accuracy to that previously reported for pulmonary TB in both EPTB disease cohorts, irrespective of HIV status. All seven blood RNA biomarkers showed superior diagnostic accuracy to CRP for both lymphadenitis and pericarditis, but failed to meet the combined >90% sensitivity and >70% specificity recommended for a blood-based diagnostic triage test by WHO. Nonetheless, in decision curve analysis, an approach of using the best performing blood RNA biomarker to trigger confirmatory microbiological testing showed superior clinical utility in clinical services seeking to reduce the number needed to test (using invasive confirmatory testing) to less than 4 for each EPTB case detected. If acceptable to undertake invasive testing in more than 4 people for each true case detected, then a test-all approach will provide greater net benefit in this TB/HIV hyperendemic setting.Implications of all the available evidence: Blood RNA biomarkers show some potential as diagnostic triage tests for TB lymphadenitis and TB pericarditis, but do not provide the level of accuracy for blood-based triage tests recommended by WHO for community-based tests. CRP has inferior diagnostic accuracy to blood RNA biomarkers and cannot be recommended for diagnostic triage among people with EPTB syndromes referred for invasive sampling.

Discovery of urinary biosignatures for tuberculosis and nontuberculous mycobacteria classification using metabolomics and machine learning

Nontuberculous mycobacteria (NTM) infection diagnosis remains a challenge due to its overlapping clinical symptoms with tuberculosis (TB), leading to inappropriate treatment. Herein, we employed noninvasive metabolic phenotyping coupled with comprehensive statistical modeling to discover potential biomarkers for the differential diagnosis of NTM infection versus TB. Urine samples from 19 NTM and 35 TB patients were collected, and untargeted metabolomics was performed using rapid liquid chromatography-mass spectrometry. The urine metabolome was analyzed using a combination of univariate and multivariate statistical approaches, incorporating machine learning. Univariate analysis revealed significant alterations in amino acids, especially tryptophan metabolism, in NTM infection compared to TB. Specifically, NTM infection was associated with upregulated levels of methionine but downregulated levels of glutarate, valine, 3-hydroxyanthranilate, and tryptophan. Five machine learning models were used to classify NTM and TB. Notably, the random forest model demonstrated excellent performance [area under the receiver operating characteristic (ROC) curve greater than 0.8] in distinguishing NTM from TB. Six potential biomarkers for NTM infection diagnosis, including methionine, valine, glutarate, 3-hydroxyanthranilate, corticosterone, and indole-3-carboxyaldehyde, were revealed from univariate ROC analysis and machine learning models. Altogether, our study suggested new noninvasive biomarkers and laid a foundation for applying machine learning to NTM differential diagnosis.

A computational framework to improve cross-platform implementation of transcriptomics signatures

The emergence of next-generation sequencing technologies and computational advances have expanded our understanding of gene expression regulation (i.e., the transcriptome). This has also led to an increased interest in using transcriptomic biomarkers to improve disease diagnosis and stratification, to assess prognosis and predict the response to treatment. Significant progress in identifying transcriptomic signatures for various clinical needs has been made, with large discovery studies accounting for challenges such as patient variability, unwanted batch effects, and data complexities; however, obstacles related to the technical aspects of cross-platform implementation still hinder the successful integration of transcriptomic technologies into standard diagnostic workflows. In this article, we discuss the challenges associated with integrating transcriptomic signatures derived using high-throughput technologies (such as RNA-sequencing) into clinical diagnostic tools using nucleic acid amplification (NAA) techniques. The novelty of the proposed approach lies in our aim to embed constraints related to cross-platform implementation in the process of signature discovery. These constraints could include technical limitations of amplification platform and chemistry, the maximal number of targets imposed by the chosen multiplexing strategy, and the genomic context of identified RNA biomarkers. Finally, we propose to build a computational framework that would integrate these constraints in combination with existing statistical and machine learning models used for signature identification. We envision that this could accelerate the integration of RNA signatures discovered by high-throughput technologies into NAA-based approaches suitable for clinical applications.

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.

Computational reassessment of RNA-seq data reveals key genes in active tuberculosis

BACKGROUND

Tuberculosis is a serious life-threatening disease among the top global health challenges and rapid and effective diagnostic biomarkers are vital for early diagnosis especially given the increasing prevalence of multidrug resistance.

METHODS

Two human whole blood microarray datasets, GSE42826 and GSE42830 were retrieved from publicly available gene expression omnibus (GEO) database. Deregulated genes (DEGs) were identified using GEO2R online tool and Gene Ontology (GO), protein-protein interaction (PPI) network analysis was performed using Metascape and STRING databases. Significant genes (n = 8) were identified using T-test/ANOVA and Molecular Complex Detection (MCODE) score ≥10, which was validated in GSE34608 dataset. The diagnostic potential of three biomarkers was assessed using Area Under Curve (AUC) of Receiver Operating Characteristic (ROC) plot. The transcriptional levels of these genes were also examined in a separate dataset GSE31348, to monitor the patterns of variation during tuberculosis treatment.

RESULTS

A total of 62 common DEGs (57 upregulated, 7 downregulated genes) were identified in two discovery datasets. GO functions and pathway enrichment analysis shed light on the functional roles of these DEGs in immune response and type-II interferon signaling. The genes in Module-1 (n = 18) were linked to innate immune response, interferon-gamma signaling. The common genes (n = 8) were validated in GSE34608 dataset, that corroborates the results obtained from discovery sets. The gene expression levels demonstrated responsiveness to Mtb infection during anti-TB therapy in GSE31348 dataset. In GSE34608 dataset, the expression levels of three specific genes, GBP5, IFITM3, and EPSTI1, emerged as potential diagnostic makers. In combination, these genes scored remarkable diagnostic performance with 100% sensitivity and 89% specificity, resulting in an impressive Area Under Curve (AUC) of 0.958. However, GBP5 alone showed the highest AUC of 0.986 with 100% sensitivity and 89% specificity.

CONCLUSIONS

The study presents valuable insights into the critical gene network perturbed during tuberculosis. These genes are determinants for assessing the effectiveness of an anti-TB response and distinguishing between active TB and healthy individuals. GBP5, IFITM3 and EPSTI1 emerged as candidate core genes in TB and holds potential as novel molecular targets for the development of interventions in the treatment of TB.

Backtranslation of human RNA biosignatures of tuberculosis disease risk into the preclinical pipeline is condition dependent

It is not clear whether human progression to active tuberculosis disease (TB) risk signatures are viable endpoint criteria for evaluations of treatments in clinical or preclinical development. TB is the deadliest infectious disease globally and more efficacious vaccines are needed to reduce this mortality. However, the immune correlates of protection for either preventing infection with Mycobacterium tuberculosis or preventing TB disease have yet to be completely defined, making the advancement of candidate vaccines through the pipeline slow, costly, and fraught with risk. Human-derived correlate of risk (COR) gene signatures, which identify an individual's risk to progressing to active TB disease, provide an opportunity for evaluating new therapies for TB with clear and defined endpoints. Though prospective clinical trials with longitudinal sampling are prohibitively expensive, characterization of COR gene signatures is practical with preclinical models. Using a 3Rs (Replacement, Reduction and Refinement) approach we reanalyzed heterogeneous publicly available transcriptional datasets to determine whether a specific set of COR signatures are viable endpoints in the preclinical pipeline. We selected RISK6, Sweeney3 and BATF2 human-derived blood-based RNA biosignatures because they require relatively few genes to assign a score and have been carefully evaluated across several clinical cohorts. Excitingly, these data provide proof-of-concept that human COR signatures seem to have high fidelity across several tissue types in the preclinical TB model pipeline and show best performance when the model most closely reflected human infection or disease conditions. Human-derived COR signatures offer an opportunity for high-throughput preclinical endpoint criteria of vaccine and drug therapy evaluations.

One Sentence Summary

Human-derived biosignatures of tuberculosis disease progression were evaluated for their predictive fidelity across preclinical species and derived tissues using available public data sets.

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

BACKGROUND

Blood-based transcriptional gene signatures for tuberculosis (TB) have been developed with potential use to diagnose disease. However, an unresolved issue is whether gene set enrichment analysis of the signature transcripts alone is sufficient for prediction and differentiation or whether it is necessary to use the original model created when the signature was derived. Intra-method comparison is complicated by the unavailability of original training data and missing details about the original trained model. To facilitate the utilization of these signatures in TB research, comparisons between gene set scoring methods cross-data validation of original model implementations are needed.

METHODS

We compared the performance of 19 TB gene signatures across 24 transcriptomic datasets using both rrebuilt original models and gene set scoring methods. Existing gene set scoring methods, including ssGSEA, GSVA, PLAGE, Singscore, and Zscore, were used as alternative approaches to obtain the profile scores. The area under the ROC curve (AUC) value was computed to measure performance. Correlation analysis and Wilcoxon paired tests were used to compare the performance of enrichment methods with the original models.

RESULTS

For many signatures, the predictions from gene set scoring methods were highly correlated and statistically equivalent to the results given by the original models. 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 gene sets can distinguish patients with active TB disease from 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.

Cost-Effective Whole Transcriptome Sequencing Landscape and Diagnostic Potential Biomarkers in Active Tuberculosis

Tuberculosis (TB) is a prevalent and severe infectious disease that poses a significant threat to human health. However, it is frequently disregarded as there are not enough quick and accurate ways to diagnose tuberculosis. Here, we develop a strategy for tuberculosis detection to address the challenges, including an experimental strategy, namely, Double Adapter Directional Capture sequencing (DADCSeq), an easily operated and low-cost whole transcriptome sequencing method, and a computational method to identify hub differentially expressed genes as well as the diagnosis of TB based on whole transcriptome data using DADCSeq on peripheral blood mononuclear cells (PBMCs) from active TB and latent TB or healthy control. Applying our approach to create a robust and stable TB multi-mRNA risk probability model (TBMMRP) that can accurately distinguish active and latent TB patients, including active TB and healthy controls in clinical cohorts, this diagnostic biomarker was successfully validated by several independent cross-platform cohorts with favorable performance in differentiating active TB from latent TB or active TB from healthy controls and further demonstrated superior or similar diagnostic accuracy compared to previous diagnostic markers. Overall, we develop a low-cost and effective strategy for tuberculosis diagnosis; as the clinical cohort increases, we can expand to different disease kinds and learn new features through our disease diagnosis strategy.

Circulating cell-free RNA in blood as a host response biomarker for detection of tuberculosis

Tuberculosis (TB) remains a leading cause of death from an infectious disease worldwide, partly due to a lack of effective strategies to screen and triage individuals with potential TB. Whole blood RNA signatures have been tested as biomarkers for TB, but have failed to meet the World Health Organization's (WHO) optimal target product profiles (TPP). Here, we use RNA sequencing and machine-learning to investigate the utility of plasma cell-free RNA (cfRNA) as a host-response biomarker for TB in cohorts from Uganda, Vietnam and Philippines. We report a 6-gene cfRNA signature, which differentiates TB-positive and TB-negative individuals with AUC = 0.95, 0.92, and 0.95 in test, training and validation, respectively. This signature meets WHO TPPs (sensitivity: 97.1% [95% CI: 80.9-100%], specificity: 85.2% [95% CI: 72.4-100%]) regardless of geographic location, sample collection method and HIV status. Overall, our results identify plasma cfRNA as a promising host response biomarker to diagnose TB.

Advances in technology for the laboratory diagnosis of individuals with HIV/AIDS coinfected with Mycobacterium tuberculosis

The high morbidity and mortality rate of individuals with human immunodeficiency virus (HIV) / acquired immunodeficiency syndrome (AIDS) coinfected with Mycobacterium tuberculosis (MTB) is a tough challenge for current global tuberculosis prevention and control efforts. HIV/MTB coinfection is more complex than a single infection, and the interaction between the two diseases aggravates the deterioration caused by the disease, resulting in increased hospitalizations and deaths. Rapid screening and early diagnosis facilitate the timely initiation of anti-tuberculosis treatment in HIV/MTB coinfected individuals, thereby reducing transmission and the incidence of adverse prognoses. To date, pathogenic detection has remained the gold standard for diagnosing tuberculosis, but its sensitivity and specificity are greatly affected by the body's immune status, which limits its application in the diagnosis of HIV/MTB coinfection. Recently, immunology and molecular detection technology has developed rapidly. New detection technologies, such as interferon-γ release assays, interferon-gamma inducible protein 10, and GeneXpert MTB/RIF assay have overcome the limitations of traditional detection methods, significantly improved the sensitivity and specificity of tuberculosis diagnosis, and brought new hope to the detection of HIV/MTB coinfection. In this article, the principle, scope of application, and latest research progress of relevant detection methods are reviewed to provide a reference for the early diagnosis of HIV/MTB coinfection.

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.

DNA-based molecular classifiers for the profiling of gene expression signatures

Although gene expression signatures offer tremendous potential in diseases diagnostic and prognostic, but massive gene expression signatures caused challenges for experimental detection and computational analysis in clinical setting. Here, we introduce a universal DNA-based molecular classifier for profiling gene expression signatures and generating immediate diagnostic outcomes. The molecular classifier begins with feature transformation, a modular and programmable strategy was used to capture relative relationships of low-concentration RNAs and convert them to general coding inputs. Then, competitive inhibition of the DNA catalytic reaction enables strict weight assignment for different inputs according to their importance, followed by summation, annihilation and reporting to accurately implement the mathematical model of the classifier. We validated the entire workflow by utilizing miRNA expression levels for the diagnosis of hepatocellular carcinoma (HCC) in clinical samples with an accuracy 85.7%. The results demonstrate the molecular classifier provides a universal solution to explore the correlation between gene expression patterns and disease diagnostics, monitoring, and prognosis, and supports personalized healthcare in primary care.

A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health

Modern machine learning approaches have led to performant diagnostic models for a variety of health conditions. Several machine learning approaches, such as decision trees and deep neural networks, can, in principle, approximate any function. However, this power can be considered to be both a gift and a curse, as the propensity toward overfitting is magnified when the input data are heterogeneous and high dimensional and the output class is highly nonlinear. This issue can especially plague diagnostic systems that predict behavioral and psychiatric conditions that are diagnosed with subjective criteria. An emerging solution to this issue is crowdsourcing, where crowd workers are paid to annotate complex behavioral features in return for monetary compensation or a gamified experience. These labels can then be used to derive a diagnosis, either directly or by using the labels as inputs to a diagnostic machine learning model. This viewpoint describes existing work in this emerging field and discusses ongoing challenges and opportunities with crowd-powered diagnostic systems, a nascent field of study. With the correct considerations, the addition of crowdsourcing to human-in-the-loop machine learning workflows for the prediction of complex and nuanced health conditions can accelerate screening, diagnostics, and ultimately access to care.

Exploring the Role of Extracellular Vesicles in the Pathogenesis of Tuberculosis

Tuberculosis (TB) remains a significant global health concern, necessitating accurate diagnosis and treatment monitoring. Extracellular vesicles (EVs), including exosomes, play crucial roles in disease progression, with their associated genes serving as potential biomarkers and therapeutic targets. Leveraging publicly available RNA-Seq datasets of TB patients and healthy controls (HCs), to identify differentially expressed genes (DEGs) and their associated protein-protein interaction networks and immune cell profiles, the common EV-related DEGs were identified and validated in the GSE42830 and GSE40553 datasets. We have identified nine common EV-related DEGs (SERPINA1, TNFAIP6, MAPK14, STAT1, ITGA2B, VAMP5, CTSL, CEACAM1, and PLAUR) upregulated in TB patients. Immune cell infiltration analysis revealed significant differences between TB patients and HCs, highlighting increased proportions of various immune cells in TB patients. These DEGs are involved in crucial cellular processes and pathways related to exocytosis and immune response regulation. Notably, VAMP5 exhibited excellent diagnostic performance (AUC-0.993, sensitivity-93.8%, specificity-100%), with potential as a novel biomarker for TB. The EV-related genes can serve as novel potential biomarkers that can distinguish between TB and HCs. VAMP5, which functions in exosome biogenesis and showed significant upregulation in TB, can be targeted for therapeutic interventions and treatment outcomes.

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.

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.

The elusive allure of a rapid host blood signature for tuberculosis disease

A rapid host transcriptional signature cartridge could be a major advancement for tuberculosis diagnosis and treatment monitoring. In a recent study, M. Li, Y. Qiu, M. Guo, R. Qu, et al. (J Clin Microbiol 61:e00911-23, 2023, https://doi.org/10.1128/jcm.00911-23) conducted an evaluation of the Cepheid 3-gene assay (Xpert-MTB-HR) within a diagnostic case-control study in China. While the study provides a strong contribution for determining the value of the Xpert-MTB-HR assay for diagnostic accuracy and treatment response, further assay optimization and more prospective studies are necessary before adaptation into clinical practice.

Diagnostic accuracy of a three-gene Mycobacterium tuberculosis host response cartridge using fingerstick blood for childhood tuberculosis: a multicentre prospective study in low-income and middle-income countries

BACKGROUND

Childhood tuberculosis remains a major cause of morbidity and mortality in part due to missed diagnosis. Diagnostic methods with enhanced sensitivity using easy-to-obtain specimens are needed. We aimed to assess the diagnostic accuracy of the Cepheid Mycobacterium tuberculosis Host Response prototype cartridge (MTB-HR), a candidate test measuring a three-gene transcriptomic signature from fingerstick blood, in children with presumptive tuberculosis disease.

METHODS

RaPaed-TB was a prospective diagnostic accuracy study conducted at four sites in African countries (Malawi, Mozambique, South Africa, and Tanzania) and one site in India. Children younger than 15 years with presumptive pulmonary or extrapulmonary tuberculosis were enrolled between Jan 21, 2019, and June 30, 2021. MTB-HR was performed at baseline and at 1 month in all children and was repeated at 3 months and 6 months in children on tuberculosis treatment. Accuracy was compared with tuberculosis status based on standardised microbiological, radiological, and clinical data.

FINDINGS

5313 potentially eligible children were screened, of whom 975 were eligible. 784 children had MTB-HR test results, of whom 639 had a diagnostic classification and were included in the analysis. MTB-HR differentiated children with culture-confirmed tuberculosis from those with unlikely tuberculosis with a sensitivity of 59·8% (95% CI 50·8-68·4). Using any microbiological confirmation (culture, Xpert MTB/RIF Ultra, or both), sensitivity was 41·6% (34·7-48·7), and using a composite clinical reference standard, sensitivity was 29·6% (25·4-34·2). Specificity for all three reference standards was 90·3% (95% CI 85·5-94·0). Performance was similar in different age groups and by malnutrition status. Among children living with HIV, accuracy against the strict reference standard tended to be lower (sensitivity 50·0%, 15·7-84·3) compared with those without HIV (61·0%, 51·6-69·9), although the difference did not reach statistical significance. Combining baseline MTB-HR result with one Ultra result identified 71·2% of children with microbiologically confirmed tuberculosis.

INTERPRETATION

MTB-HR showed promising diagnostic accuracy for culture-confirmed tuberculosis in this large, geographically diverse, paediatric cohort and hard-to-diagnose subgroups.

FUNDING

European and Developing Countries Clinical Trials Partnership, UK Medical Research Council, Swedish International Development Cooperation Agency, Bundesministerium für Bildung und Forschung; German Center for Infection Research (DZIF).

Evaluation of the Xpert MTB Host Response assay for the triage of patients with presumed pulmonary tuberculosis: a prospective diagnostic accuracy study in Viet Nam, India, the Philippines, Uganda, and South Africa

BACKGROUND

Non-sputum-based triage tests for tuberculosis are a priority for ending tuberculosis. We aimed to evaluate the diagnostic accuracy of the late-prototype Xpert MTB Host Response (Xpert HR) blood-based assay.

METHODS

We conducted a prospective diagnostic accuracy study among outpatients with presumed tuberculosis in outpatient clinics in Viet Nam, India, the Philippines, Uganda, and South Africa. Eligible participants were aged 18 years or older and reported cough lasting at least 2 weeks. We excluded those receiving tuberculosis treatment in the preceding 12 months and those who were unwilling to consent. Xpert HR was performed on capillary or venous blood. Reference standard testing included sputum Xpert MTB/RIF Ultra and mycobacterial culture. We performed receiver operating characteristic (ROC) analysis to identify the optimal cutoff value for the Xpert HR to achieve the target sensitivity of 90% or more while maximising specificity, then calculated diagnostic accuracy using this cutoff value. This study was prospectively registered with ClinicalTrials.gov, NCT04923958.

FINDINGS

Between July 13, 2021, and Aug 15, 2022, 2046 adults with at least 2 weeks of cough were identified, of whom 1499 adults (686 [45·8%] females and 813 [54·2%] males) had valid Xpert HR and reference standard results. 329 (21·9%) had microbiologically confirmed tuberculosis. Xpert HR had an area under the ROC curve of 0·89 (95% CI 0·86-0·91). The optimal cutoff value was less than or equal to -1·25, giving a sensitivity of 90·3% (95% CI 86·5-93·3; 297 of 329) and a specificity of 62·6% (95% CI 59·7-65·3; 732 of 1170). Sensitivity was similar across countries, by sex, and by subgroups, although specificity was lower in people living with HIV (45·1%, 95% CI 37·8-52·6) than in those not living with HIV (65·9%, 62·8-68·8; difference of 20·8%, 95% CI 13·0-28·6; p<0·0001). Xpert HR had high negative predictive value (95·8%, 95% CI 94·1-97·1), but positive predictive value was only 40·1% (95% CI 36·8-44·1). Using the Xpert HR as a triage test would have reduced confirmatory sputum testing by 57·3% (95% CI 54·2-60·4).

INTERPRETATION

Xpert HR did not meet WHO minimum specificity targets for a non-sputum-based triage test for pulmonary tuberculosis. Despite promise as a rule-out test that could reduce confirmatory sputum testing, further cost-effectiveness modelling and data on acceptability and usability are needed to inform policy recommendations.

FUNDING

National Institute of Allergy and Infectious Diseases of the US National Institutes of Health.

TRANSLATIONS

For the Vietnamese and Tagalog translations of the abstract see Supplementary Materials section.

Compact RNA sensors for increasingly complex functions of multiple inputs

Designing single molecules that compute general functions of input molecular partners represents a major unsolved challenge in molecular design. Here, we demonstrate that high-throughput, iterative experimental testing of diverse RNA designs crowdsourced from Eterna yields sensors of increasingly complex functions of input oligonucleotide concentrations. After designing single-input RNA sensors with activation ratios beyond our detection limits, we created logic gates, including challenging XOR and XNOR gates, and sensors that respond to the ratio of two inputs. Finally, we describe the OpenTB challenge, which elicited 85-nucleotide sensors that compute a score for diagnosing active tuberculosis, based on the ratio of products of three gene segments. Building on OpenTB design strategies, we created an algorithm Nucleologic that produces similarly compact sensors for the three-gene score based on RNA and DNA. These results open new avenues for diverse applications of compact, single molecule sensors previously limited by design complexity.

Computational Characterization of Undifferentially Expressed Genes with Altered Transcription Regulation in Lung Cancer

A transcriptome profiles the expression levels of genes in cells and has accumulated a huge amount of public data. Most of the existing biomarker-related studies investigated the differential expression of individual transcriptomic features under the assumption of inter-feature independence. Many transcriptomic features without differential expression were ignored from the biomarker lists. This study proposed a computational analysis protocol (mqTrans) to analyze transcriptomes from the view of high-dimensional inter-feature correlations. The mqTrans protocol trained a regression model to predict the expression of an mRNA feature from those of the transcription factors (TFs). The difference between the predicted and real expression of an mRNA feature in a query sample was defined as the mqTrans feature. The new mqTrans view facilitated the detection of thirteen transcriptomic features with differentially expressed mqTrans features, but without differential expression in the original transcriptomic values in three independent datasets of lung cancer. These features were called dark biomarkers because they would have been ignored in a conventional differential analysis. The detailed discussion of one dark biomarker, GBP5, and additional validation experiments suggested that the overlapping long non-coding RNAs might have contributed to this interesting phenomenon. In summary, this study aimed to find undifferentially expressed genes with significantly changed mqTrans values in lung cancer. These genes were usually ignored in most biomarker detection studies of undifferential expression. However, their differentially expressed mqTrans values in three independent datasets suggested their strong associations with lung cancer.

Assessment of the Cepheid 3-gene Host Response Fingerstick Blood Test (MTB-HR) on rapid diagnosis of tuberculosis

ABSTRACTThe World Health Organization has identified high-priority target product profiles for new TB diagnostics which include rapid biomarker-based, non-sputum-based diagnostic testing, using an easily accessible sample. The Cepheid 3-gene Host Response Fingerstick Blood Prototype Test (MTB-HR) quantifies relative mRNA levels of a 3-gene signature (GBP5, DUSP3, and KLF2) from a whole-blood sample on the GeneXpert platform. The objective of the present study was to evaluate the performance of the MTB-HR to distinguish between active tuberculosis (ATB), latent Mycobacterium tuberculosis infection (LTBI), other pulmonary diseases, and healthy volunteers at a tertiary care centre. Among 653 participants enrolled in this study, 192 were diagnosed as having ATB, and the remaining 461 were classified as non-ATB, including 137 cases of LTBI, 224 cases of other pulmonary diseases, and 100 healthy volunteers. The corresponding AUCs of the MTB-HR in distinguishing untreated ATB from non-ATB, LTBI, other pulmonary diseases, and healthy volunteers were 0.814 (95% CI, 0.760-0.868, sensitivity 76.1%, specificity 71.6%), 0.739 (95% CI, 0.667-0.812, sensitivity 59.7%, specificity 78.1%), 0.825 (95% CI, 0.770-0.880, sensitivity 82.1%, specificity 65.6%), 0.892 (95% CI, 0.839-0.945, sensitivity 76.1%, specificity 88.0%), respectively. When only samples with TAT of less than 1 h were included, the AUC of the MTB-HR in distinguishing untreated ATB from non-ATB was largest, 0.920 (95% CI, 0.822-1.000, sensitivity 81.3%, specificity 87.7%). In conclusion, the MTB-HR assay shows potential as a rapid, blood-based screening and triage test for ATB, especially for untreated ATB, with the advantage of increased diagnostic yield since blood is more readily available.

Evaluation of the Cepheid 3-gene host response blood test for tuberculosis diagnosis and treatment response monitoring in a primary-level clinic in rural China

A rapid, accurate, non-sputum-based triage test for diagnosing tuberculosis (TB) is a high-priority need. Cepheid developed a novel prototype blood test, Xpert Mycobacterium tuberculosis Host Response (Xpert-MTB-HR), which generates a TB score based on the mRNA expression of three genes. We conducted a case-control study with prospective recruitment to evaluate its accuracy in the clinic of the Wusheng County Centers for Disease Prevention and Control in China. We enrolled 149 TB patients, 248 other respiratory diseases (ORD) patients, and 193 healthy controls. In addition, whole-blood samples taken from TB patients after 2, 5, and 6 months of treatment were tested with Xpert-MTB-HR to evaluate its ability to monitor treatment response. Xpert-MTB-HR discriminated between TB and healthy controls with an area under the curve (AUC) of 0.912 (95% CI, 0.878-0.945). With the specificity of 70% envisioned for a triage test, its sensitivity was 90.1% (84.9%-94.6%). Xpert-MTB-HR discriminated between TB and ORD with an AUC of 0.798 (0.750-0.847), and at specificity of 70%, the sensitivity was only 75.8% (68.5%-82.8%). In patients determined by Ultra to have medium or high sputum bacillary loads, with specificity of 70%, the sensitivity for discriminating patients with TB from healthy controls was 100.0% (100.0-100.0) and from patients with ORD, 95.1% (89.8-100.0). The TB scores generally increased by 2 months of treatment and then remained stable. Xpert-MTB-HR met the criteria for a triage test to discriminate between TB and healthy controls, but not between TB and ORD, except when limited to patients with high sputum bacillary loads. Xpert-MTB-HR showed promise for monitoring response to treatment but needs to be further evaluated in larger prospective studies.