Longitudinal Dynamics of a Blood Transcriptomic Signature of Tuberculosis

Blood RNA biomarkers for tuberculosis screening in people living with HIV before antiretroviral therapy initiation: a diagnostic accuracy study

BACKGROUND

Undiagnosed tuberculosis remains a major threat for people living with HIV. Multiple blood transcriptomic biomarkers have shown promise for tuberculosis diagnosis. We sought to evaluate their diagnostic accuracy and clinical utility for systematic pre-antiretroviral therapy (ART) tuberculosis screening.

METHODS

We enrolled consecutive adults (age ≥18 years) referred to start ART at a community health centre in Cape Town, South Africa, irrespective of symptoms. Sputa were obtained (using induction if required) for two liquid cultures. Whole-blood RNA samples underwent transcriptional profiling using a custom Nanostring gene panel. We measured the diagnostic accuracy of seven candidate RNA signatures (one single gene biomarker [BATF2] and six multigene biomarkers) for the reference standard of Mycobacterium tuberculosis culture status, using area under the receiver-operating characteristic curve (AUROC) analysis, and sensitivity and specificity at prespecified thresholds (two standard scores above the mean of healthy controls; Z2). Clinical utility was assessed by calculating net benefit in decision curve analysis. We compared performance with C-reactive protein (CRP; threshold ≥5 mg/L), WHO four-symptom screen (W4SS), and the WHO target product profile for tuberculosis triage tests.

FINDINGS

A total of 707 people living with HIV (407 [58%] female and 300 [42%] male) were included, with median CD4 count 306 cells per mm3 (IQR 184-486). Of 676 participants with available sputum culture results, 89 (13%) had culture-confirmed tuberculosis. The seven RNA signatures were moderately to highly correlated (Spearman rank coefficients 0·42-0·93) and discriminated tuberculosis culture positivity with similar AUROCs (0·73-0·80), but none statistically better than CRP (AUROC 0·78, 95% CI 0·72-0·83). Diagnostic accuracy was similar across CD4 count strata, but lower among participants with negative W4SS (AUROCs 0·56-0·65) compared with positive (AUROCs 0·75-0·84). The RNA biomarker with the highest AUROC point estimate was a four-gene signature (Suliman4; AUROC 0·80, 95% CI 0·75-0·86), with sensitivity 83% (95% CI 74-90) and specificity 59% (55-63) at the Z2 threshold. In decision curve analysis, Suliman4 and CRP had similar clinical utility to guide confirmatory tuberculosis testing, but both had higher net benefit than W4SS. In exploratory analyses, an approach combining CRP (≥5 mg/L) and Suliman4 (≥Z2) had sensitivity of 80% (70-87), specificity of 70% (66-74), and higher net benefit than either biomarker alone.

INTERPRETATION

RNA biomarkers showed better clinical utility to guide confirmatory tuberculosis testing for people living with HIV before ART initiation than symptom-based screening, but their performance did not exceed that of CRP and fell short of WHO recommended targets. Interferon-independent approaches might be required to improve accuracy of host-response biomarkers to support tuberculosis screening before ART initiation.

FUNDING

South African Medical Research Council, European and Developing Countries Clinical Trials Partnership 2, National Institutes of Health National Institute of Allergy and Infectious Diseases, The Wellcome Trust, National Institute for Health and Care Research, Royal College of Physicians London.

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.

A half-century of research on tuberculosis: Successes and challenges

Great progress has been made over the past half-century, but TB remains a formidable global health problem, particularly in low- and middle-income countries. Understanding the mechanisms of pathogenesis and necessary and sufficient conditions for protection are critical. The need for inexpensive and sensitive point-of-care diagnostic tests for earlier detection of infection and disease, shorter and less-toxic drug regimens for drug-sensitive and -resistant TB, and a more effective vaccine than BCG is immense. New and better tools, greater support for international research, collaborations, and training will be required to dramatically reduce the burden of this devastating disease which still kills 1.6 million people annually.

Identification of cuproptosis-related molecular subtypes as a biomarker for differentiating active from latent tuberculosis in children

BACKGROUND

Cell death plays a crucial role in the progression of active tuberculosis (ATB) from latent infection (LTBI). Cuproptosis, a novel programmed cell death, has been reported to be associated with the pathology of various diseases. We aimed to identify cuproptosis-related molecular subtypes as biomarkers for distinguishing ATB from LTBI in pediatric patients.

METHOD

The expression profiles of cuproptosis regulators and immune characteristics in pediatric patients with ATB and LTBI were analyzed based on GSE39939 downloaded from the Gene Expression Omnibus. From the 52 ATB samples, we investigated the molecular subtypes based on differentially expressed cuproptosis-related genes (DE-CRGs) via consensus clustering and related immune cell infiltration. Subtype-specific differentially expressed genes (DEGs) were found using the weighted gene co-expression network analysis. The optimum machine model was then determined by comparing the performance of the eXtreme Gradient Boost (XGB), the random forest model (RF), the general linear model (GLM), and the support vector machine model (SVM). Nomogram and test datasets (GSE39940) were used to verify the prediction accuracy.

RESULTS

Nine DE-CRGs (NFE2L2, NLRP3, FDX1, LIPT1, PDHB, MTF1, GLS, DBT, and DLST) associated with active immune responses were ascertained between ATB and LTBI patients. Two cuproptosis-related molecular subtypes were defined in ATB pediatrics. Single sample gene set enrichment analysis suggested that compared with Subtype 2, Subtype 1 was characterized by decreased lymphocytes and increased inflammatory activation. Gene set variation analysis showed that cluster-specific DEGs in Subtype 1 were closely associated with immune and inflammation responses and energy and amino acids metabolism. The SVM model exhibited the best discriminative performance with a higher area under the curve (AUC = 0.983) and relatively lower root mean square and residual error. A final 5-gene-based (MAN1C1, DKFZP434N035, SIRT4, BPGM, and APBA2) SVM model was created, demonstrating satisfactory performance in the test datasets (AUC = 0.905). The decision curve analysis and nomogram calibration curve also revealed the accuracy of differentiating ATB from LTBI in children.

CONCLUSION

Our study suggested that cuproptosis might be associated with the immunopathology of Mycobacterium tuberculosis infection in children. Additionally, we built a satisfactory prediction model to assess the cuproptosis subtype risk in ATB, which can be used as a reliable biomarker for the distinguishment between pediatric ATB and LTBI.

Blood RNA biomarkers for tuberculosis screening in people living with HIV prior to anti-retroviral therapy initiation: A diagnostic accuracy study

Background

Undiagnosed tuberculosis (TB) remains a major threat for people living with HIV (PLHIV). Multiple blood transcriptomic biomarkers have shown promise for TB diagnosis. We sought to evaluate their diagnostic accuracy and clinical utility for systematic pre-antiretroviral therapy (ART) TB screening.

Methods

We enrolled consecutive adults referred to start ART at a community health centre in Cape Town, South Africa, irrespective of symptoms. Sputa were obtained (using induction if required) for two liquid cultures. Whole-blood RNA samples underwent transcriptional profiling using a custom Nanostring gene-panel. We measured the diagnostic accuracy of seven candidate RNA biomarkers for the reference standard of Mycobacterium tuberculosis culture status, using area under the receiver-operating characteristic curve (AUROC) analysis, and sensitivity/specificity at pre-specified thresholds (two standard scores above the mean of healthy controls; Z2). Clinical utility was assessed using decision curve analysis. We compared performance to CRP (threshold ≥5mg/L), World Health Organisation (WHO) four-symptom screen (W4SS) and the WHO target product profile for TB triage tests.

Results

A total of 707 PLHIV were included, with median CD4 count 306 cells/mm3. Of 676 with available sputum culture results, 89 (13%) had culture-confirmed TB. The seven RNA biomarkers were moderately to highly correlated (Spearman rank coefficients 0.42-0.93) and discriminated TB culture-positivity with similar AUROCs (0.73-0.80), but none statistically better than CRP (AUROC 0.78; 95% CI 0.72-0.83). Diagnostic accuracy was similar across CD4 count strata, but lower among W4SS-negative (AUROCs 0.56-0.65) compared to W4SS-positive participants (AUROCs 0.75-0.84). The RNA biomarker with highest AUROC point estimate was a 4-gene signature (Suliman4; AUROC 0.80; 95% CI 0.75-0.86), with sensitivity 0.83 (0.74-0.90) and specificity 0.59 (0.55-0.63) at Z2 threshold. In decision curve analysis, Suliman4 and CRP had similar clinical utility to guide confirmatory TB testing, but both had higher net benefit than W4SS. In exploratory analyses, an approach combining CRP (≥5mg/L) and Suliman4 (≥Z2) had sensitivity of 0.80 (0.70-0.87), specificity of 0.70 (0.66-0.74) and higher net benefit than either biomarker alone.

Interpretation

RNA biomarkers showed better clinical utility to guide confirmatory TB testing for PLHIV prior to ART initiation than symptom-based screening, but their performance did not exceed that of CRP, and fell short of WHO recommended targets. Interferon-independent approaches may be required to improve accuracy of host-response biomarkers to support TB screening pre-ART initiation.

Funding

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

Culture independent markers of nontuberculous mycobacterial (NTM) lung infection and disease in the cystic fibrosis airway

Nontuberculous mycobacteria (NTM) are opportunistic pathogens that affect a relatively small but significant portion of the people with cystic fibrosis (CF), and may cause increased morbidity and mortality in this population. Cultures from the airway are the only test currently in clinical use for detecting NTM. Culture techniques used in clinical laboratories are insensitive and poorly suited for population screening or to follow progression of disease or treatment response. The lack of sensitive and quantitative markers of NTM in the airway impedes patient care and clinical trial design, and has limited our understanding of patterns of acquisition, latency and pathogenesis of disease. Culture-independent markers of NTM infection have the potential to overcome many of the limitations of standard NTM cultures, especially the very slow growth, inability to quantitate bacterial burden, and low sensitivity due to required decontamination procedures. A range of markers have been identified in sputum, saliva, breath, blood, urine, as well as radiographic studies. Proposed markers to detect presence of NTM or transition to NTM disease include bacterial cell wall products and DNA, as well as markers of host immune response such as immunoglobulins and the gene expression of circulating leukocytes. In all cases the sensitivity of culture-independent markers is greater than standard cultures; however, most do not discriminate between various NTM species. Thus, each marker may be best suited for a specific clinical application, or combined with other markers and traditional cultures to improve diagnosis and monitoring of treatment response.

Isoniazid preventive therapy and tuberculosis transcriptional signatures in people with HIV

OBJECTIVES

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

DESIGN

Cross-sectional study.

METHODS

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

RESULTS

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

CONCLUSION

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

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

Funding

Mind the gap - Managing tuberculosis across the disease spectrum

We currently have a binomial approach to managing tuberculosis. Those with active disease, ideally confirmed microbiologically, are treated with a standard 6-month, multi-drug regimen and those with latent infection and no evidence of disease with shorter, one or two drug regimens. Clinicians frequently encounter patients that fall between these two management pathways with some but not all features of disease and this will occur more often with the increasing emphasis on chest X-ray-based systematic screening. The view of tuberculosis as a spectrum of disease states is being increasingly recognised and is leading to new diagnostic approaches for early disease. However, the 6-month regimen for treating disease was driven by the duration required to treat the most extensive forms of pulmonary TB and shorter durations appear sufficient for less extensive disease. It is time undertake clinical trials to better define the optimal treatment for tuberculosis across the disease spectrum.

Reimagining the status quo: How close are we to rapid sputum-free tuberculosis diagnostics for all?

Rapid, accurate, sputum-free tests for tuberculosis (TB) triage and confirmation are urgently needed to close the widening diagnostic gap. We summarise key technologies and review programmatic, systems, and resource issues that could affect the impact of diagnostics. Mid-to-early-stage technologies like artificial intelligence-based automated digital chest X-radiography and capillary blood point-of-care assays are particularly promising. Pitfalls in the diagnostic pipeline, included a lack of community-based tools. We outline how these technologies may complement one another within the context of the TB care cascade, help overturn current paradigms (eg, reducing syndromic triage reliance, permitting subclinical TB to be diagnosed), and expand options for extra-pulmonary TB. We review challenges such as the difficulty of detecting paucibacillary TB and the limitations of current reference standards, and discuss how researchers and developers can better design and evaluate assays to optimise programmatic uptake. Finally, we outline how leveraging the urgency and innovation applied to COVID-19 is critical to improving TB patients' diagnostic quality-of-care.

Prospective multicentre head-to-head validation of host blood transcriptomic biomarkers for pulmonary tuberculosis by real-time PCR

Background

Sensitive point-of-care screening tests are urgently needed to identify individuals at highest risk of tuberculosis. We prospectively tested performance of host-blood transcriptomic tuberculosis signatures.

Methods

Adults without suspicion of tuberculosis were recruited from five endemic South African communities. Eight parsimonious host-blood transcriptomic tuberculosis signatures were measured by microfluidic RT-qPCR at enrolment. Upper respiratory swab specimens were tested with a multiplex bacterial-viral RT-qPCR panel in a subset of participants. Diagnostic and prognostic performance for microbiologically confirmed prevalent and incident pulmonary tuberculosis was tested in all participants at baseline and during active surveillance through 15 months follow-up, respectively.

Results

Among 20,207 HIV-uninfected and 963 HIV-infected adults screened; 2923 and 861 were enroled. There were 61 HIV-uninfected (weighted prevalence 1.1%) and 10 HIV-infected (prevalence 1.2%) tuberculosis cases at baseline. Parsimonious signature diagnostic performance was superior among symptomatic (AUCs 0.85-0.98) as compared to asymptomatic (AUCs 0.61-0.78) HIV-uninfected participants. Thereafter, 24 HIV-uninfected and 9 HIV-infected participants progressed to incident tuberculosis (1.1 and 1.0 per 100 person-years, respectively). Among HIV-uninfected individuals, prognostic performance for incident tuberculosis occurring within 6-12 months was higher relative to 15 months. 1000 HIV-uninfected participants were tested for respiratory microorganisms and 413 HIV-infected for HIV plasma viral load; 7/8 signature scores were higher (p < 0.05) in participants with viral respiratory infections or detectable HIV viraemia than those without.

Conclusions

Several parsimonious tuberculosis transcriptomic signatures met triage test targets among symptomatic participants, and incipient test targets within 6 months. However, the signatures were upregulated with viral infection and offered poor specificity for diagnosing sub-clinical tuberculosis.

The effect of host factors on discriminatory performance of a transcriptomic signature of tuberculosis risk

Background

We aimed to understand host factors that affect discriminatory performance of a transcriptomic signature of tuberculosis risk (RISK11).

Methods

HIV-negative adults aged 18–60 years were evaluated in a prospective study of RISK11 and surveilled for tuberculosis through 15 months. Generalised linear models and receiver-operating characteristic (ROC) regression were used to estimate effect of host factors on RISK11 score (%marginal effect) and on discriminatory performance for tuberculosis disease (area under the curve, AUC), respectively.

Findings

Among 2923 participants including 74 prevalent and 56 incident tuberculosis cases, percentage marginal effects on RISK11 score were increased among those with prevalent tuberculosis (+18·90%, 95%CI 12·66−25·13), night sweats (+14·65%, 95%CI 5·39−23·91), incident tuberculosis (+7·29%, 95%CI 1·46−13·11), flu-like symptoms (+5·13%, 95%CI 1·58−8·68), and smoking history (+2·41%, 95%CI 0·89−3·93) than those without; and reduced in males (−6·68%, 95%CI −8·31−5·04) and with every unit increase in BMI (−0·13%, −95%CI −0·25−0·01). Adjustment for host factors affecting controls did not change RISK11 discriminatory performance. Cough was associated with 72·55% higher RISK11 score in prevalent tuberculosis cases. Stratification by cough improved diagnostic performance from AUC = 0·74 (95%CI 0·67−0·82) overall, to 0·97 (95%CI 0·90−1·00, p < 0·001) in cough-positive participants. Combining host factors with RISK11 improved prognostic performance, compared to RISK11 alone, (AUC = 0·76, 95%CI 0·69−0·83 versus 0·56, 95%CI 0·46−0·68, p < 0·001) over a 15-month predictive horizon.

Interpretation

Several host factors affected RISK11 score, but only adjustment for cough affected diagnostic performance. Combining host factors with RISK11 should be considered to improve prognostic performance.

Funding

Bill and Melinda Gates Foundation, South African Medical Research Council.

Development and Validation of a Parsimonious Tuberculosis Gene Signature Using the digital NanoString nCounter Platform

BACKGROUND

Blood-based biomarkers for diagnosing active tuberculosis (TB), monitoring treatment response, and predicting risk of progression to TB disease have been reported. However, validation of the biomarkers across multiple independent cohorts is scarce. A robust platform to validate TB biomarkers in different populations with clinical end points is essential to the development of a point-of-care clinical test. NanoString nCounter technology is an amplification-free digital detection platform that directly measures mRNA transcripts with high specificity. Here, we determined whether NanoString could serve as a platform for extensive validation of candidate TB biomarkers.

METHODS

The NanoString platform was used for performance evaluation of existing TB gene signatures in a cohort in which signatures were previously evaluated on an RNA-seq dataset. A NanoString codeset that probes 107 genes comprising 12 TB signatures and 6 housekeeping genes (NS-TB107) was developed and applied to total RNA derived from whole blood samples of TB patients and individuals with latent TB infection (LTBI) from South India. The TBSignatureProfiler tool was used to score samples for each signature. An ensemble of machine learning algorithms was used to derive a parsimonious biomarker.

RESULTS

Gene signatures present in NS-TB107 had statistically significant discriminative power for segregating TB from LTBI. Further analysis of the data yielded a NanoString 6-gene set (NANO6) that when tested on 10 published datasets was highly diagnostic for active TB.

CONCLUSIONS

The NanoString nCounter system provides a robust platform for validating existing TB biomarkers and deriving a parsimonious gene signature with enhanced diagnostic performance.