A Novel, 5-Transcript, Whole-blood Gene-expression Signature for Tuberculosis Screening Among People Living With Human Immunodeficiency Virus

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.

Gene signature discovery and systematic validation across diverse clinical cohorts for TB prognosis and response to treatment

While blood gene signatures have shown promise in tuberculosis (TB) diagnosis and treatment monitoring, most signatures derived from a single cohort may be insufficient to capture TB heterogeneity in populations and individuals. Here we report a new generalized approach combining a network-based meta-analysis with machine-learning modeling to leverage the power of heterogeneity among studies. The transcriptome datasets from 57 studies (37 TB and 20 viral infections) across demographics and TB disease states were used for gene signature discovery and model training and validation. The network-based meta-analysis identified a common 45-gene signature specific to active TB disease across studies. Two optimized random forest regression models, using the full or partial 45-gene signature, were then established to model the continuum from Mycobacterium tuberculosis infection to disease and treatment response. In model validation, using pooled multi-cohort datasets to mimic the real-world setting, the model provides robust predictive performance for incipient to active TB risk over a 2.5-year period with an AUROC of 0.85, 74.2% sensitivity, and 78.3% specificity, which approximates the minimum criteria (>75% sensitivity and >75% specificity) within the WHO target product profile for prediction of progression to TB. Moreover, the model strongly discriminates active TB from viral infection (AUROC 0.93, 95% CI 0.91-0.94). For treatment monitoring, the TB scores generated by the model statistically correlate with treatment responses over time and were predictive, even before treatment initiation, of standard treatment clinical outcomes. We demonstrate an end-to-end gene signature model development scheme that considers heterogeneity for TB risk estimation and treatment monitoring.

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.

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.

The Role of C-Reactive Protein as a Triage Tool for Pulmonary Tuberculosis in Children

BACKGROUND

C-reactive protein (CRP) has shown promise as a triage tool for pulmonary tuberculosis (TB) in adults living with the human immunodeficiency virus. We performed the first assessment of CRP for TB triage in children.

METHODS

Symptomatic children less than 15 years old were prospectively enrolled in Kampala, Uganda. We completed a standard TB evaluation and measured CRP using a point-of-care assay. We determined the sensitivity and specificity of CRP to identify pulmonary TB in children using 10 mg/L and 5 mg/L cut-off points and generated a receiver operating characteristic (ROC) curve to determine alternative cut-offs that could approach the target accuracy for a triage test (≥90% sensitivity and ≥70% specificity).

RESULTS

We included 332 children (median age 3 years old, interquartile range [IQR]: 1-6). The median CRP level was low at 3.0 mg/L (IQR: 2.5-26.6) but was higher in children with Confirmed TB than in children with Unlikely TB (9.5 mg/L vs. 2.9 mg/L, P-value = .03). At a 10 mg/L cut-off, CRP sensitivity was 50.0% (95% confidence interval [CI], 37.0-63.0) among Confirmed TB cases and specificity was 63.3% (95% CI, 54.7-71.3) among children with Unlikely TB. Sensitivity increased to 56.5% (95% CI, 43.3-69.0) at the 5 mg/L cut-off, but specificity decreased to 54.0% (95% CI, 45.3-62.4). The area under the ROC curve was 0.59 (95% CI, 0.51-0.67), and the highest sensitivity achieved was 66.1% at a specificity of 46.8%.

CONCLUSIONS

CRP levels were low in children with pulmonary TB, and CRP was unable to achieve the accuracy targets for a TB triage test.

Analysis of real-time PCR Melanocortin 3 (MC3R) gene expression to identify new biomarkers inflammation in tuberculosis

Background

Diagnosis of tuberculosis (TB) in the era of technological sophistication requires accuracy and speed to provide as much information as possible so that TB treatment can be carried out quickly and precisely. New studies have also begun to be carried out to diagnose TB, one of which is by examining genes, either by looking at polymorphisms, mutations, or expressions. Several previous studies have confirmed the association of MC3R and TB genes with polymorphisms; MC3R is a gene that participates in the regulation of the inflammatory process and is also found in macrophages; therefore, we tried to analyze gene expression in the active TB group, household contacts, and healthy controls for looked at the differences between the three groups and confirmed the correlation of MC3R with TB by seeing which group's gene expression increased the most expression of the three groups so that the results can be considered as a TB diagnostic biomarker in the future.

Methods

This study included 122 people, 49 patients with confirmed TB, 46 close relatives of patients, and 27 healthy controls. This study used a real-time PCR technique to analyze MC3R gene expression in the three groups, and all data were analyzed using Bio-Rad CFXTM software version 3.1 and one-way ANOVA using SPSS 21.0.

Results

The value of MC3R gene expression in the active TB group increased 3.6-fold in the healthy group (p = 0.143), and that of gene expression in the healthy control group increased 1.09-fold in the healthy group (p = 0.007).

Conclusion

There is a relationship between MC3R and TB based on the results of gene expression analysis that increased in the active TB group compared to the household contact group and healthy controls.

Tuberculosis screening improves preventive therapy uptake (TB SCRIPT) trial among people living with HIV in Uganda: a study protocol of an individual randomized controlled trial

Background

People living with HIV (PLHIV) have an increased risk of developing active tuberculosis (TB). To reduce the burden of TB among PLHIV, the World Health Organization (WHO) recommends systematic TB screening followed by (1) confirmatory TB testing for all who screen positive and (2) TB preventive therapy (TPT) for all TPT-eligible PLHIV who screen negative. Symptom-based screening remains the standard of care in most high TB burden settings, including Uganda. Despite having high sensitivity for active TB among antiretroviral-naïve PLHIV, symptom screening has poor specificity; as such, many high-risk PLHIV without active TB are not referred for TPT. C-reactive protein (CRP) is a promising alternative strategy for TB screening that has comparable sensitivity and higher specificity than symptom screening, and was endorsed by WHO in 2021. However, the impact of CRP-based TB screening on TB burden for PLHIV remains unclear.

Methods

TB SCRIPT (TB Screening Improves Preventive Therapy Uptake) is a phase 3, multi-center, single-blinded, individual (1:1) randomized controlled trial evaluating the effectiveness of CRP-based TB screening on clinical outcomes of PLHIV. The trial aims to compare the effectiveness of a TB screening strategy based on CRP levels using a point-of-care (POC) assay on 2-year TB incidence and all-cause mortality (composite primary trial endpoint) and prevalent TB case detection and uptake of TPT (intermediate outcomes), relative to symptom-based TB screening (current practice).

Discussion

This study will be critical to improving selection of eligible PLHIV for TPT and helping guide the scale-up and integration of TB screening and TPT activities. This work will enable the field to improve TB screening by removing barriers to TPT initiation among eligible PLHIV, and provide randomized evidence to inform and strengthen WHO guidelines.

Trial registration

ClinicalTrials.gov NCT04557176. Registered on September 21, 2020.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06371-0.

Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics

The epidemiology of infectious causes of meningitis in sub-Saharan Africa is not well understood, and a common cause of meningitis in this region, Mycobacterium tuberculosis (TB), is notoriously hard to diagnose. Here we show that integrating cerebrospinal fluid (CSF) metagenomic next-generation sequencing (mNGS) with a host gene expression-based machine learning classifier (MLC) enhances diagnostic accuracy for TB meningitis (TBM) and its mimics. 368 HIV-infected Ugandan adults with subacute meningitis were prospectively enrolled. Total RNA and DNA CSF mNGS libraries were sequenced to identify meningitis pathogens. In parallel, a CSF host transcriptomic MLC to distinguish between TBM and other infections was trained and then evaluated in a blinded fashion on an independent dataset. mNGS identifies an array of infectious TBM mimics (and co-infections), including emerging, treatable, and vaccine-preventable pathogens including Wesselsbron virus, Toxoplasma gondii, Streptococcus pneumoniae, Nocardia brasiliensis, measles virus and cytomegalovirus. By leveraging the specificity of mNGS and the sensitivity of an MLC created from CSF host transcriptomes, the combined assay has high sensitivity (88.9%) and specificity (86.7%) for the detection of TBM and its many mimics. Furthermore, we achieve comparable combined assay performance at sequencing depths more amenable to performing diagnostic mNGS in low resource settings.

Tuberculous meningitis is difficult to differentiate from meningitis caused by other pathogens. Here, the authors combine metagenomics-based pathogen detection in cerebrospinal fluid with a host gene expression-based machine learning classifier for diagnosis.

A systematic review of potential screening biomarkers for active TB disease

INTRODUCTION

The standard TB Four Symptom Screen does not meet the World Health Organization (WHO) ideal screening criteria for having greater than 90% sensitivity to identify active TB disease, regardless of HIV status. To identify novel screening biomarkers for active TB, we performed a systematic review of any cohort or case-control study reporting associations between screening biomarkers and active TB disease.

METHODS

We searched PubMed and Embase for articles published before October 10, 2021. We included studies from high or medium tuberculosis burden countries. We excluded articles focusing on C-reactive protein and lipoarabinomannan. For all included biomarkers, we calculated sensitivity, specificity and 95% confidence intervals, and assessed study quality using a tool adapted from the QUADAS-2 risk of bias.

RESULTS

From 8,062 abstracts screened, we included 79 articles. The articles described 302 unique biomarkers, including host antibodies, host proteins, TB antigens, microRNAs, whole blood gene PCRs, and combinations of biomarkers. Of these, 23 biomarkers had sensitivity greater than 90% and specificity greater than 70%, meeting WHO criteria for an ideal screening test. Among the eleven biomarkers described in people living with HIV, only one had a sensitivity greater than 90% and specificity greater than 70% for active TB.

CONCLUSION

Further evaluation of biomarkers of active TB should be pursued to accelerate identification of TB disease.

Validation of Differentially Expressed Immune Biomarkers in Latent and Active Tuberculosis by Real-Time PCR

Tuberculosis (TB) remains a major global threat and diagnosis of active TB ((ATB) both extra-pulmonary (EPTB), pulmonary (PTB)) and latent TB (LTBI) infection remains challenging, particularly in high-burden countries which still rely heavily on conventional methods. Although molecular diagnostic methods are available, e.g., Cepheid GeneXpert, they are not universally available in all high TB burden countries. There is intense focus on immune biomarkers for use in TB diagnosis, which could provide alternative low-cost, rapid diagnostic solutions. In our previous gene expression studies, we identified peripheral blood leukocyte (PBL) mRNA biomarkers in a non-human primate TB aerosol-challenge model. Here, we describe a study to further validate select mRNA biomarkers from this prior study in new cohorts of patients and controls, as a prerequisite for further development. Whole blood mRNA was purified from ATB patients recruited in the UK and India, LTBI and two groups of controls from the UK (i) a low TB incidence region (CNTRLA) and (ii) individuals variably-domiciled in the UK and Asia ((CNTRLB), the latter TB high incidence regions). Seventy-two mRNA biomarker gene targets were analyzed by qPCR using the Roche Lightcycler 480 qPCR platform and data analyzed using GeneSpring™ 14.9 bioinformatics software. Differential expression of fifty-three biomarkers was confirmed between MTB infected, LTBI groups and controls, seventeen of which were significant using analysis of variance (ANOVA): CALCOCO2, CD52, GBP1, GBP2, GBP5, HLA-B, IFIT3, IFITM3, IRF1, LOC400759 (GBP1P1), NCF1C, PF4V1, SAMD9L, S100A11, TAF10, TAPBP, and TRIM25. These were analyzed using receiver operating characteristic (ROC) curve analysis. Single biomarkers and biomarker combinations were further assessed using simple arithmetic algorithms. Minimal combination biomarker panels were delineated for primary diagnosis of ATB (both PTB and EPTB), LTBI and identifying LTBI individuals at high risk of progression which showed good performance characteristics. These were assessed for suitability for progression against the standards for new TB diagnostic tests delineated in the published World Health Organization (WHO) technology product profiles (TPPs).

A Two-Gene Signature for Tuberculosis Diagnosis in Persons With Advanced HIV

Background: Transcriptomic signatures for tuberculosis (TB) have been proposed and represent a promising diagnostic tool. Data remain limited in persons with advanced HIV.

Methods: We enrolled 30 patients with advanced HIV (CD4 <100 cells/mm³) in India; 16 with active TB and 14 without. Whole-blood RNA sequencing was performed; these data were merged with a publicly available dataset from Uganda (n = 33; 18 with TB and 15 without). Transcriptomic profiling and machine learning algorithms identified an optimal gene signature for TB classification. Receiver operating characteristic analysis was used to assess performance.

Results: Among 565 differentially expressed genes identified for TB, 40 were shared across India and Uganda cohorts. Common upregulated pathways reflect Toll-like receptor cascades and neutrophil degranulation. The machine-learning decision-tree algorithm selected gene expression values from RAB20 and INSL3 as most informative for TB classification. The signature accurately classified TB in discovery cohorts (India AUC 0.95 and Uganda AUC 1.0; p < 0.001); accuracy was fair in external validation cohorts.

Conclusions: Expression values of RAB20 and INSL3 genes in peripheral blood compose a biosignature that accurately classified TB status among patients with advanced HIV in two geographically distinct cohorts. The functional analysis suggests pathways previously reported in TB pathogenesis.

Evaluation of cytokines as a biomarker to distinguish active tuberculosis from latent tuberculosis infection: a diagnostic meta-analysis

OBJECTIVES

With a marginally effective vaccine and no significant breakthroughs in new treatments, a sensitive and specific method to distinguish active tuberculosis from latent tuberculosis infection (LTBI) would allow for early diagnosis and limit the spread of the pathogen. The analysis of multiple cytokine profiles provides the possibility to differentiate the two diseases.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

PubMed, Cochrane Library, Clinical Key and EMBASE databases were searched on 31 December 2019.

ELIGIBILITY CRITERIA

We included case-control studies, cohort studies and randomised controlled trials considering IFN-γ, TNF-α, IP-10, IL-2, IL-10, IL-12 and VEGF as biomarkers to distinguish active tuberculosis and LTBI.

DATA EXTRACTION AND SYNTHESIS

Two students independently extracted data and assessed the risk of bias. Diagnostic OR, sensitivity, specificity, positive and negative likelihood ratios and area under the curve (AUC) together with 95% CI were used to estimate the diagnostic value.

RESULTS

Of 1315 records identified, 14 studies were considered eligible. IL-2 had the highest sensitivity (0.84, 95% CI: 0.72 to 0.92), while VEGF had the highest specificity (0.87, 95% CI: 0.73 to 0.94). The highest AUC was observed for VEGF (0.85, 95% CI: 0.81 to 0.88), followed by IFN-γ (0.84, 95% CI: 0.80 to 0.87) and IL-2 (0.84, 95% CI: 0.81 to 0.87).

CONCLUSION

Cytokines, such as IL-2, IFN-γ and VEGF, can be utilised as promising biomarkers to distinguish active tuberculosis from LTBI.

PROSPERO REGISTRATION NUMBER

CRD42020170725.

Evaluation of multi-antigen serological screening for active tuberculosis among people living with HIV

Better triage tests for screening tuberculosis (TB) disease are needed for people living with HIV (PLHIV). We performed the first evaluation of a previously-validated 8-antigen serological panel to screen PLHIV for pulmonary TB in Kampala, Uganda. We selected a random 1:1 sample with and without TB (defined by sputum culture) from a cohort of PLHIV initiating antiretroviral therapy. We used a multiplex microbead immunoassay and an ensemble machine learning classifier to determine the area under the receiver operating characteristic curve (AUC) for Ag85A, Ag85B, Ag85C, Rv0934-P38, Rv3881, Rv3841-BfrB, Rv3873, and Rv2878c. We then assessed the performance with the addition of four TB-specific antigens ESAT-6, CFP-10, Rv1980-MPT64, and Rv2031-HSPX, and every antigen combination. Of 262 participants (median CD4 cell-count 152 cells/μL [IQR 65-279]), 138 (53%) had culture-confirmed TB. The 8-antigen panel had an AUC of 0.53 (95% CI 0.40-0.66), and the additional 4 antigens did not improve performance (AUC 0.51, 95% CI 0.39-0.64). When sensitivity was restricted to ≥90% for the 8- and 12-antigen panel, specificity was 2.2% (95% CI 0-17.7%) and 8.1% (95% CI 0-23.9%), respectively. A three-antigen combination (Rv0934-P38, Ag85A, and Rv2031-HSPX) outperformed both panels, with an AUC of 0.60 (95% CI 0.48-0.73), 90% sensitivity (95% CI 78.2-96.7%) and 29.7% specificity (95% CI 15.9-47%). The multi-antigen panels did not achieve the target accuracy for a TB triage test among PLHIV. We identified a new combination that improved performance for TB screening in an HIV-positive sample compared to an existing serological panel in Uganda, and suggests an approach to identify novel antigen combinations specifically for screening TB in PLHIV.

Cost effectiveness of testing HIV infected individuals for TB in a low TB/HIV setting

OBJECTIVES

Guidelines recommend routine testing for latent TB infection (LTBI) in people living with HIV. However there are few cost-effectiveness studies to justify this in contemporary high resource, low TB/HIV incidence settings. We sought to assess the uptake, yield and cost-effectiveness of testing for latent and active TB.

METHODS

Adults attending an ambulatory HIV clinic in London, UK were prospectively recruited by stratified selection and tested for TB infection using symptom questionnaires, chest radiograph (CXR), tuberculin skin test (TST), T-Spot.TB and induced sputum. From this, 30 testing strategies were compared in a cost-effectiveness model including probabilistic sensitivity analysis using Monte Carlo simulation.

RESULTS

219 subjects were assessed; 95% were using antiretroviral therapy (ART). Smear negative, culture positive TB was present in 0.9% asymptomatic subjects, LTBI in 9%. Only strategies testing those from subSaharan Africa with a TST or interferon gamma release assay (IGRA) with or without CXR, or testing those from countries with a TB incidence of >40/100,000 with TST alone were cost-effective using a £30,000/QALY threshold.

CONCLUSIONS

Cost-effectiveness analysis in an adult HIV cohort with high ART usage suggests there is limited benefit beyond routine testing for latent TB in people from high and possibly medium TB incidence settings.

Concise whole blood transcriptional signatures for incipient tuberculosis: a systematic review and patient-level pooled meta-analysis

BACKGROUND

Multiple blood transcriptional signatures have been proposed for identification of active and incipient tuberculosis. We aimed to compare the performance of systematically identified candidate signatures for incipient tuberculosis and to benchmark these against WHO targets.

METHODS

We did a systematic review and individual participant data meta-analysis. We searched Medline and Embase for candidate whole blood mRNA signatures discovered with the primary objective of diagnosis of active or incipient tuberculosis, compared with controls who were healthy or had latent tuberculosis infection. We tested the performance of eligible signatures in whole blood transcriptomic datasets, in which sampling before tuberculosis diagnosis was done and time to disease was available. Culture-confirmed and clinically or radiologically diagnosed pulmonary or extrapulmonary tuberculosis cases were included. Non-progressor (individuals who remained tuberculosis-free during follow-up) samples with less than 6 months of follow-up from the date of sample collection were excluded, as were participants with prevalent tuberculosis and those who received preventive therapy. Scores were calculated for candidate signatures for each participant in the pooled dataset. Receiver operating characteristic curves, sensitivities, and specificities were examined using prespecified intervals to tuberculosis (<3 months, <6 months, <1 year, and <2 years) from sample collection. This study is registered with PROSPERO, number CRD42019135618.

RESULTS

We tested 17 candidate mRNA signatures in a pooled dataset from four eligible studies comprising 1126 samples. This dataset included 183 samples from 127 incipient tuberculosis cases in South Africa, Ethiopia, The Gambia, and the UK. Eight signatures (comprising 1-25 transcripts) that predominantly reflect interferon and tumour necrosis factor-inducible gene expression, had equivalent diagnostic accuracy for incipient tuberculosis over a 2-year period with areas under the receiver operating characteristic curves ranging from 0·70 (95% CI 0·64-0·76) to 0·77 (0·71-0·82). The sensitivity of all eight signatures declined with increasing disease-free time interval. Using a threshold derived from two SDs above the mean of uninfected controls to prioritise specificity and positive-predictive value, the eight signatures achieved sensitivities of 24·7-39·9% over 24 months and of 47·1-81·0% over 3 months, with corresponding specificities of more than 90%. Based on pre-test probability of 2%, the eight signatures achieved positive-predictive values ranging from 6·8-9·4% over 24 months and 11·2-14·4% over 3 months. When using biomarker thresholds maximising sensitivity and specificity with equal weighting to both, no signature met the minimum WHO target product profile parameters for incipient tuberculosis biomarkers over a 2-year period.

INTERPRETATION

Blood transcriptional biomarkers reflect short-term risk of tuberculosis and only exceed WHO benchmarks if applied to 3-6-month intervals. Serial testing among carefully selected target groups might be required for optimal implementation of these biomarkers.

FUNDING

Wellcome Trust and National Institute for Health Research.