Blood transcriptional biomarkers for active pulmonary tuberculosis in a high-burden setting: a prospective, observational, diagnostic accuracy study

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.

A new rapid lipoarabinomannan urine assay for tuberculosis: a two-centre diagnostic accuracy evaluation in outpatients with and without HIV

Introduction

Non-sputum tests for people attending primary care with symptoms of tuberculosis (TB) are a global priority.

Methods

We performed a cross-sectional two-centre diagnostic accuracy study of a next-generation urine lipoarabinomannan assay (Biopromic TB LAM, BP-LAM) and the lateral flow Determine TB LAM Ag assay (LF-LAM) on urine from 629 adults with presumptive pulmonary TB (315 with TB) attending primary care in South Africa and Uganda. An extended sputum microbiological reference standard (eMRS) was used and, in South Africa, sputum induction done.

Results

BP-LAM had higher sensitivity than LF-LAM [95% confidence interval (CI) 63% (58, 69) vs. 22% (18, 27)] and similar specificity [93% (90, 96) vs. 89% (85, 92)]. BP-LAM sensitivity did not differ in HIV-positive vs. -negative people nor by CD4 counts. Specificity was diminished in PLHIV [90% (83, 94) vs. 96% (92, 99)]. The design-locked version of BP-LAM had improved specificity than the prototype [93% (90, 96) vs. 85% (80, 88)]. In people with TB who could not expectorate sputum, 67% (55, 79) were BP-LAM-positive; resulting in similar yield to sputum Xpert MTB/RIF Ultra [64% (49, 78)] in a programmatic scenario where sputum induction is unavailable. BP-LAM false-negatives had, vs. true-positives, less severe disease and were more likely to have previous TB. False-positive results were more likely to be from people who cultured only non-tuberculous mycobacteria [19% (4/21) vs. 4% (12/293) for true-negatives].

Conclusions

BP-LAM has higher sensitivity than LF-LAM, including in HIV-negative people, potentially permitting the expansion of urine LAM testing beyond people with advanced immunosuppression.

Funding

The Global Health Technology Fund (GHIT) programs RFP-TRP-2018-001 and RFP-PD-2020-002, EDCTP2 (RIA2020I-3305, CAGE-TB; TMA2020CDF-3209, RADIANT).

A DNA Methylation Signature From Buccal Swabs to Identify Tuberculosis Infection

BACKGROUND

Tuberculosis (TB) is among the largest infectious causes of death worldwide, and there is a need for a time- and resource-effective diagnostic methods. In this novel and exploratory study, we show the potential of using buccal swabs to collect human DNA and investigate the DNA methylation (DNAm) signatures as a diagnostic tool for TB.

METHODS

Buccal swabs were collected from patients with pulmonary TB (n = 7), TB-exposed persons (n = 7), and controls (n = 9) in Sweden. Using Illumina MethylationEPIC array, the DNAm status was determined.

RESULTS

We identified 5644 significant differentially methylated CpG sites between the patients and controls. Performing the analysis on a validation cohort of samples collected in Kenya and Peru (patients, n = 26; exposed, n = 9; control, n = 10) confirmed the DNAm signature. We identified a TB consensus disease module, significantly enriched in TB-associated genes. Last, we used machine learning to identify a panel of 7 CpG sites discriminative for TB and developed a TB classifier. In the validation cohort, the classifier performed with an area under the curve of 0.94, sensitivity of 0.92, and specificity of 1.

CONCLUSIONS

In summary, the result from this study shows clinical implications of using DNAm signatures from buccal swabs to explore new diagnostic strategies for TB.

BATF2/SINHCAF regulates the quantity and function of macrophages infected with Mycobacterium Tuberculosis via regulation of TTC23 through Wnt/β-catenin pathway

Elucidating the pathogenic mechanism of Tuberculosis (TB) can contribute to control TB. Basic leucine zipper transcription factor ATF-like 2 (BATF2) belonging to a large family of leucine zipper transcription factors (TFs) termed bZip proteins, had been verified to have important value in the diagnosis of TB. However, its role and mechanism in TB had not been elucidated. The study aimed to explore its function and molecular mechanism in macrophages infected with Mycobacterium tuberculosis (Mtb). The results indicated that BATF2 inhibited cell proliferation, promoted inflammatory response and impaired the antibacterial and antigen-presenting capacity in macrophages for T cells through regulating its downstream gene TTC23 by interacting with SINHCAF. Above roles and regulations were dependent on β-catenin functions in macrophages infected with Mtb. Clinical samples verified that the expressions of BATF2 and TTC23 were significantly higher in the blood of patients with pulmonary TB compared with health controls. Altogether, BATF2 interacted with SINHCAF to regulate the quantity and function of macrophages during Mtb infection by targeting TTC23 through Wnt/β-catenin pathway.

An ultra-early, transient interferon-associated innate immune response associates with protection from SARS-CoV-2 infection despite exposure

BACKGROUND

A proportion of individuals exposed to respiratory viruses avoid contracting detectable infection. We tested the hypothesis that early innate immune responses associate with resistance to detectable infection in close contacts of COVID-19 cases.

METHODS

48 recently-exposed household contacts of symptomatic COVID-19 cases were recruited in London, UK between May 2020 and March 2021 through a prospective, longitudinal observational study. Blood and nose and throat swabs were collected during the acute period of index case viral shedding and longitudinally thereafter. Magnitude of SARS-CoV-2 exposure was quantified, and serial PCR and serological assays used to determine infection status of contacts. Whole-blood RNA-seq was performed and analysed to identify transcriptomic signatures of early infection and resistance to infection.

FINDINGS

24 highly-exposed household contacts became PCR-positive and seropositive whilst 24 remained persistently PCR-negative and seronegative. A 96-gene transcriptomic signature of early SARS-CoV-2 infection was identified using RNA-seq of longitudinal blood samples from PCR-positive contacts. This signature was dominated by interferon-associated genes and expression correlated positively with viral load. Elevated expression of this 96-gene signature was also observed during exposure in 25% (6/24) of persistently PCR-negative, seronegative contacts. PCR-negative contacts with elevated signature expression had higher-magnitude SARS-CoV-2 exposure compared to those with low signature expression. We validated this signature in SARS-CoV-2-infected individuals in two independent cohorts. In naturally-exposed healthcare workers (HCWs) we found that 7/58 (12%) PCR-negative HCWs exhibited elevated signature expression. Comparing gene-signature expression in SARS-CoV-2 Controlled Human Infection Model (CHIM) volunteers pre- and post-inoculation, we observed that 14 signature genes were transiently upregulated as soon as 6 hr post-inoculation in PCR-negative volunteers, while in PCR-positive volunteers gene-signature upregulation did not occur until 3 days later.

INTERPRETATION

Our interferon-associated signature of early SARS-CoV-2 infection characterises a subgroup of exposed, uninfected contacts in three independent cohorts who may have successfully aborted infection prior to induction of adaptive immunity. The earlier transient upregulation of signature genes in PCR-negative compared to PCR-positive CHIM volunteers suggests that ultra-early interferon-associated innate immune responses correlate with, and may contribute to, protection against SARS-CoV-2 infection.

FUNDING

This work was supported by the NIHR Health Protection Research Unit in Respiratory Infections, United Kingdom, NIHR Imperial College London, United Kingdom (Grant number: NIHR200927; AL) in partnership with the UK Health Security Agency and the NIHR Medical Research Council (MRC), United Kingdom (Grant number: MR/X004058/1). Support for sequencing was provided by the Imperial BRC Genomics Facility which is funded by the NIHR, United Kingdom. The development of the hybrid DABA assay used for quantification of SARS-CoV-2 anti-Spike RBD antibodies was supported by the MRC (MC_PC_19078).

Transcriptomic Signatures of Progression to Tuberculosis Disease Among Close Contacts in Brazil

BACKGROUND

Approximately 5% of people infected with Mycobacterium tuberculosis progress to tuberculosis (TB) disease without preventive therapy. There is a need for a prognostic test to identify those at highest risk of incident TB so that therapy can be targeted. We evaluated host blood transcriptomic signatures for progression to TB disease.

METHODS

Close contacts (≥4 hours of exposure per week) of adult patients with culture-confirmed pulmonary TB were enrolled in Brazil. Investigation for incident, microbiologically confirmed, or clinically diagnosed pulmonary or extrapulmonary TB disease through 24 months of follow-up was symptom triggered. Twenty previously validated blood TB transcriptomic signatures were measured at baseline by real-time quantitative polymerase chain reaction. Prognostic performance for incident TB was tested by receiver operating characteristic curve analysis at 6, 9, 12, and 24 months of follow-up.

RESULTS

Between June 2015 and June 2019, 1854 close contacts were enrolled. Twenty-five progressed to incident TB, of whom 13 had microbiologically confirmed disease. Baseline transcriptomic signature scores were measured in 1789 close contacts. Prognostic performance for all signatures was best within 6 months of diagnosis. Seven signatures (Gliddon4, Suliman4, Roe3, Roe1, Penn-Nicholson6, Francisco2, and Rajan5) met the minimum World Health Organization target product profile for a prognostic test through 6 months and 3 signatures (Gliddon4, Rajan5, and Duffy9) through 9 months. None met the target product profile threshold through ≥12 months of follow-up.

CONCLUSIONS

Blood transcriptomic signatures may be useful for predicting TB risk within 9 months of measurement among TB-exposed contacts to target preventive therapy administration.

Development of a Nomogram Based on Transcriptional Signatures, IFN-γ Response and Neutrophils for Diagnosis of Tuberculosis

PURPOSE

Tuberculosis (TB) is a major global health threat and its diagnosis remains challenging. This study aimed to develop a nomogram that incorporated peripheral blood transcriptional signatures and other blood tests for the diagnosis of tuberculosis.

PATIENTS AND METHODS

Patients with TB, patients with other definite pulmonary diseases (OPD), individuals with latent tuberculosis infection (LTBI), and healthy controls (HC) were retrospectively enrolled between May 2017 and April 2018. The results of the interferon-γ release assay (IGRA) and blood counts were obtained from medical records, and the transcripts of 10 genes were detected using reverse transcription polymerase chain reaction (RT-PCR). Variable selection was performed using least absolute shrinkage and selection operator regression (LASSO) and multivariate logistic regression was performed for the optimal prediction model with backward direction. The model was displayed as a nomogram, and its performance was evaluated for discrimination ability, calibration ability, and clinical usefulness. Internal validation of the prediction model was conducted using bootstrap resampling.

RESULTS

A total of 185 participants were enrolled, including 84 patients with TB and 101 controls. A prediction nomogram composed of IGRA, percentage of neutrophils, and expression levels of CD64, granzyme A (GZMA), and PR/SET domain 1 (PRDM1) was established. The nomogram demonstrated good discrimination, with an unadjusted area under the curve (AUC) of 0.914 (95% CI: 0.875-0.954) and a bootstrap-corrected AUC of 0.914 (95% CI: 0.874-0.947). With a cutoff value of 0.519, the sensitivity and specificity for discriminating PTB from controls were 0.81 and 0.871, respectively. The nomogram also showed good calibration with the Hosmer-Lemeshow test (P=0.58) and good clinical practicality displayed by the decision curve analysis.

CONCLUSION

A nomogram composed of IGRA, percentage of neutrophils, and expression of CD64, GZMA, and PRDM1 was established. The nomogram demonstrated a sensitivity and specificity of 81% and 87%, respectively, for differentiating TB from controls.

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.

Resolution of tuberculosis blood RNA signatures fails to discriminate persistent sputum culture positivity after 8 weeks of anti-tuberculous treatment

BACKGROUND

Concerted efforts aim to reduce the burden of 6 months of anti-tuberculous treatment for tuberculosis (TB). Treatment cessation at 8 weeks is effective for most but incurs increased risk of disease relapse. We tested the hypothesis that blood RNA signatures or C-reactive protein (CRP) measurements discriminate 8-week sputum culture status, as a prerequisite for a biomarker to stratify risk of relapse following treatment cessation at this time-point.

METHODS

We identified blood RNA signatures of TB disease or cure by systematic review. We evaluated these signatures and CRP measurements in a pulmonary TB cohort, pre-treatment, at 2 and 8 weeks of treatment, and sustained cure after treatment completion. We tested biomarker discrimination of 8-week sputum culture status using area under the receiver operating characteristic curve (AUROC) analysis and, secondarily, assessed correlation of biomarker scores with time to culture positivity at 8 weeks of treatment.

RESULTS

12 blood RNA signatures were reproduced in the dataset from 44 individuals with sputum culture-positive pulmonary TB. These normalised over time from TB treatment initiation. 11 out of 44 cases with blood RNA, CRP and sputum culture results were sputum culture-positive at 8 weeks of treatment. None of the contemporary blood RNA signatures discriminated sputum culture status at this time-point or correlated with bacterial load. CRP achieved modest discrimination with AUROC 0.69 (95% CI 0.52-0.87).

CONCLUSIONS

Selected TB blood RNA signatures and CRP do not provide biomarkers of microbiological clearance to support TB treatment cessation at 8 weeks. Resolution of blood transcriptional host responses in sputum culture-positive individuals suggests Mycobacterium tuberculosis may colonise the respiratory tract without triggering a detectable immune response.

Integration and validation of host transcript signatures, including a novel 3-transcript tuberculosis signature, to enable one-step multiclass diagnosis of childhood febrile disease

BACKGROUND

Whole blood host transcript signatures show great potential for diagnosis of infectious and inflammatory illness, with most published signatures performing binary classification tasks. Barriers to clinical implementation include validation studies, and development of strategies that enable simultaneous, multiclass diagnosis of febrile illness based on gene expression.

METHODS

We validated five distinct diagnostic signatures for paediatric infectious diseases in parallel using a single NanoString nCounter® experiment. We included a novel 3-transcript signature for childhood tuberculosis, and four published signatures which differentiate bacterial infection, viral infection, or Kawasaki disease from other febrile illnesses. Signature performance was assessed using receiver operating characteristic curve statistics. We also explored conceptual frameworks for multiclass diagnostic signatures, including additional transcripts found to be significantly differentially expressed in previous studies. Relaxed, regularised logistic regression models were used to derive two novel multiclass signatures: a mixed One-vs-All model (MOVA), running multiple binomial models in parallel, and a full-multiclass model. In-sample performance of these models was compared using radar-plots and confusion matrix statistics.

RESULTS

Samples from 91 children were included in the study: 23 bacterial infections (DB), 20 viral infections (DV), 14 Kawasaki disease (KD), 18 tuberculosis disease (TB), and 16 healthy controls. The five signatures tested demonstrated cross-platform performance similar to their primary discovery-validation cohorts. The signatures could differentiate: KD from other diseases with area under ROC curve (AUC) of 0.897 [95% confidence interval: 0.822-0.972]; DB from DV with AUC of 0.825 [0.691-0.959] (signature-1) and 0.867 [0.753-0.982] (signature-2); TB from other diseases with AUC of 0.882 [0.787-0.977] (novel signature); TB from healthy children with AUC of 0.910 [0.808-1.000]. Application of signatures outside of their designed context reduced performance. In-sample error rates for the multiclass models were 13.3% for the MOVA model and 0.0% for the full-multiclass model. The MOVA model misclassified DB cases most frequently (18.7%) and TB cases least (2.7%).

CONCLUSIONS

Our study demonstrates the feasibility of NanoString technology for cross-platform validation of multiple transcriptomic signatures in parallel. This external cohort validated performance of all five signatures, including a novel sparse TB signature. Two exploratory multi-class models showed high potential accuracy across four distinct diagnostic groups.

PARK2 as a susceptibility factor for nontuberculous mycobacterial pulmonary disease

BACKGROUND

The genetic signatures associated with the susceptibility to nontuberculous mycobacterial pulmonary disease (NTM-PD) are still unknown. In this study, we performed RNA sequencing to explore gene expression profiles and represent characteristic factor in NTM-PD.

METHODS

Peripheral blood samples were collected from patients with NTM-PD and healthy individuals (controls). Differentially expressed genes (DEGs) were identified by RNA sequencing and subjected to functional enrichment and immune cell deconvolution analyses.

RESULTS

We enrolled 48 participants, including 26 patients with NTM-PD (median age, 58.0 years; 84.6% female), and 22 healthy controls (median age, 58.5 years; 90.9% female). We identified 21 upregulated and 44 downregulated DEGs in the NTM-PD group compared to those in the control group. NTM infection did not have a significant impact on gene expression in the NTM-PD group compared to the control group, and there were no differences in the proportion of immune cells. However, through gene ontology (GO), gene set enrichment analysis (GSEA), and protein-protein interaction (PPI) analysis, we discovered that PARK2 is a key factor associated with NTM-PD. The PARK2 gene, which is linked to the ubiquitination pathway, was downregulated in the NTM-PD group (fold change, - 1.314, P = 0.047). The expression levels of PARK2 remained unaltered after favorable treatment outcomes, suggesting that the gene is associated with host susceptibility rather than with the outcomes of infection or inflammation. The area under the receiver operating characteristic curve for the PARK2 gene diagnosing NTM-PD was 0.813 (95% confidence interval, 0.694-0.932).

CONCLUSION

We identified the genetic signatures associated with NTM-PD in a cohort of Korean patients. The PARK2 gene presents as a potential susceptibility factor in NTM-PD .

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.

Pan-lineage Mycobacterium tuberculosis reference genome for enhanced molecular diagnosis

In Mycobacterium tuberculosis (MTB) control, whole genome sequencing-based molecular drug susceptibility testing (molDST-WGS) has emerged as a pivotal tool. However, the current reliance on a single-strain reference limits molDST-WGS's true potential. To address this, we introduce a new pan-lineage reference genome, 'MtbRf'. We assembled 'unmapped' reads from 3,614 MTB genomes (751 L1; 881 L2; 1,700 L3; and 282 L4) into 35 shared, annotated contigs (54 coding sequences [CDSs]). We constructed MtbRf through: (1) searching for contig homologues among genome database that precipitate results uniquely within Mycobacteria genus; (2) comparing genomes with H37Rv ('lift-over') to define 18 insertions; and (3) filling gaps in H37Rv with insertions. MtbRf adds 1.18% sequences to H37rv, salvaging >60% of previously unmapped reads. Transcriptomics confirmed gene expression of new CDSs. The new variants provided a moderate DST predictive value (AUROC 0.60-0.75). MtbRf thus unveils previously hidden genomic information and lays the foundation for lineage-specific molDST-WGS.

Identification of ferroptosis-related gene signature for tuberculosis diagnosis and therapy efficacy

Diagnosis of tuberculosis remains a challenge when microbiological tests are negative. Immune cell atlas of patients with tuberculosis and healthy controls were established by single-cell transcriptome. Through integrated analysis of scRNA-seq with microarray and bulk RNA sequencing data, a ferroptosis-related gene signature containing ACSL4, CTSB, and TLR4 genes that were associated with tuberculosis disease was identified. Four gene expression datasets from blood samples of patients with tuberculosis, latent tuberculosis infection, and healthy controls were used to assess the diagnostic value of the gene signature. The areas under the ROC curve for the combined gene signature were 1.000, 0.866, 0.912, and 0.786, respectively, in differentiating active tuberculosis from latent infection. During anti-tuberculosis treatment, the expression of the gene signature decreased significantly in cured patients with tuberculosis. In conclusion, the ferroptosis-related gene signature was associated with tuberculosis treatment efficacy and was a promising biomarker for differentiating active tuberculosis from latent infection.

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.

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.

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.

GeneXpert MTB/RIF Ultra vs Unstimulated Interferon γ (IRISA-TB) for the Diagnosis of Tuberculous Pericarditis in a Tuberculosis-Endemic Setting

Background

Tuberculous pericarditis (TBP) is a paucibacillary disease, where host biomarkers such as unstimulated interferon γ (IRISA-TB) have high diagnostic accuracy. However, DNA-based diagnostic tests (GeneXpert Ultra), more sensitive than an earlier versions, have recently become available. Given that the diagnosis of TBP is challenging, we performed a comparative diagnostic accuracy study comparing both assays.

Methods

We recruited 99 consecutive patients with suspected TBP in Cape Town, South Africa. Definite TBP was defined by microbiological confirmation of tuberculosis (TB) on pericardial fluid culture or an alternative polymerase chain reaction-based test (GeneXpert MTB/RIF) or by use of sputum (polymerase chain reaction or culture). Probable TBP was defined as a high clinical suspicion of TB accompanied by anti-TB treatment, while non-TBP was defined as negative microbiological test results for TB without initiation of TB treatment and/or the presence of an alternative diagnosis.

Results

There were 39 patients with definite TBP, 35 with probable TBP, and 23 with non-TBP. Approximately 70% of participants who received TB treatment were HIV coinfected. Overall, IRISA-TB was more sensitive than Xpert Ultra (88.6% [95% CI, 74.1%-95.5%] vs 71.5% [55.0%-83.7%], n = 53) and significantly more sensitive in participants who were HIV uninfected (100% [95% CI, 72.3%-100.0%] vs 60% [31.3%-83.2%], P = .03). In patients with definite and probable TBP combined (n = 84), sensitivity was significantly higher with IRISA-TB (77.3% [95% CI, 65.9%-85.8%] vs 37.9 [27.2%-50.0%], P < .0001). A similar pattern was seen in persons who were HIV uninfected (88.3% vs 35.3%, P = .002). Specificity was high for both assays (>95%).

Conclusions

Unstimulated interferon γ (IRISA-TB) was significantly more sensitive than Xpert Ultra for the diagnosis of TB pericarditis in a TB-endemic resource-poor setting.

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.

Tuberculosis-targeted next-generation sequencing and machine learning: An ultrasensitive diagnostic strategy for paucibacillary pulmonary tuberculosis and tuberculous meningitis

BACKGROUND

Existing diagnostic approaches for paucibacillary tuberculosis (TB) are limited by the low sensitivity of testing methods and difficulty in obtaining suitable samples.

METHODS

An ultrasensitive TB diagnostic strategy was established, integrating efficient and specific TB targeted next-generation sequencing and machine learning models, and validated in clinical cohorts to test plasma cfDNA, cerebrospinal fluid (CSF) DNA collected from tuberculous meningitis (TBM) and pediatric pulmonary TB (PPTB) patients.

RESULTS

In the detection of 227 samples, application of the specific thresholds of CSF DNA (AUC = 0.974) and plasma cfDNA (AUC = 0.908) yielded sensitivity of 97.01 % and the specificity of 95.65 % in CSF samples and sensitivity of 82.61 % and specificity of 86.36 % in plasma samples, respectively. In the analysis of 44 paired samples from TBM patients, our strategy had a high concordance of 90.91 % (40/44) in plasma cfDNA and CSF DNA with both sensitivity of 95.45 % (42/44). In the PPTB patient, the sensitivity of the TB diagnostic strategy yielded higher sensitivity on plasma specimen than Xpert assay on gastric lavage (28.57 % VS. 15.38 %).

CONCLUSIONS

Our TB diagnostic strategy provides greater detection sensitivity for paucibacillary TB, while plasma cfDNA as an easily collected specimen, could be an appropriate sample type for PTB and TBM diagnosis.

Distinguishing infectivity in patients with pulmonary tuberculosis using deep learning

Introduction

This study aimed to develop and assess a deep-learning model based on CT images for distinguishing infectivity in patients with pulmonary tuberculosis (PTB).

Methods

We labeled all 925 patients from four centers with weak and strong infectivity based on multiple sputum smears within a month for our deep-learning model named TBINet's training. We compared TBINet's performance in identifying infectious patients to that of the conventional 3D ResNet model. For model explainability, we used gradient-weighted class activation mapping (Grad-CAM) technology to identify the site of lesion activation in the CT images.

Results

The TBINet model demonstrated superior performance with an area under the curve (AUC) of 0.819 and 0.753 on the validation and external test sets, respectively, compared to existing deep learning methods. Furthermore, using Grad-CAM, we observed that CT images with higher levels of consolidation, voids, upper lobe involvement, and enlarged lymph nodes were more likely to come from patients with highly infectious forms of PTB.

Conclusion

Our study proves the feasibility of using CT images to identify the infectivity of PTB patients based on the deep learning method.

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.

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

Background

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

Methodology

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

Results and discussion

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

Conclusions

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

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.

Trends and challenges of multi-drug resistance in childhood tuberculosis

Drug-resistant tuberculosis (DR-TB) in children is a growing global health concern, This review provides an overview of the current epidemiology of childhood TB and DR-TB, including prevalence, incidence, and mortality. We discuss the challenges in diagnosing TB and DR-TB in children and the limitations of current diagnostic tools. We summarize the challenges associated with treating multi-drug resistance TB in childhood, including limitations of current treatment options, drug adverse effects, prolonged regimens, and managing and monitoring during treatment. We highlight the urgent need for improved diagnosis and treatment of DR-TB in children. The treatment of children with multidrug-resistant tuberculosis will be expanded to include the evaluation of new drugs or new combinations of drugs. Basic research is needed to support the technological development of biomarkers to assess the phase of therapy, as well as the urgent need for improved diagnostic and treatment options.

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

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

Updating the WHO target product profile for next-generation Mycobacterium tuberculosis drug susceptibility testing at peripheral centres

There were approximately 10 million tuberculosis (TB) cases in 2020, of which 500,000 were drug-resistant. Only one third of drug-resistant TB cases were diagnosed and enrolled on appropriate treatment, an issue partly driven by a lack of rapid, accurate drug-susceptibility testing (DST) tools deployable in peripheral settings. In 2014, World Health Organization (WHO) published target product profiles (TPPs) which detailed minimal and optimal criteria to address high-priority TB diagnostic needs, including DST. Since then, the TB community's needs have evolved; new treatment regimens, changes in TB definitions, further emergence of drug resistance, technological advances, and changing end-users requirements have necessitated an update. The DST TPP's revision was therefore undertaken by WHO with the Stop TB Partnership New Diagnostics Working Group. We describe the process of updating the TPP for next-generation TB DST for use at peripheral centres, highlight key updates, and discuss guidance regarding technical and operational specifications.

Treatment Strategy for Rifampin-Susceptible Tuberculosis

BACKGROUND

Tuberculosis is usually treated with a 6-month rifampin-based regimen. Whether a strategy involving shorter initial treatment may lead to similar outcomes is unclear.

METHODS

In this adaptive, open-label, noninferiority trial, we randomly assigned participants with rifampin-susceptible pulmonary tuberculosis to undergo either standard treatment (rifampin and isoniazid for 24 weeks with pyrazinamide and ethambutol for the first 8 weeks) or a strategy involving initial treatment with an 8-week regimen, extended treatment for persistent clinical disease, monitoring after treatment, and retreatment for relapse. There were four strategy groups with different initial regimens; noninferiority was assessed in the two strategy groups with complete enrollment, which had initial regimens of high-dose rifampin-linezolid and bedaquiline-linezolid (each with isoniazid, pyrazinamide, and ethambutol). The primary outcome was a composite of death, ongoing treatment, or active disease at week 96. The noninferiority margin was 12 percentage points.

RESULTS

Of the 674 participants in the intention-to-treat population, 4 (0.6%) withdrew consent or were lost to follow-up. A primary-outcome event occurred in 7 of the 181 participants (3.9%) in the standard-treatment group, as compared with 21 of the 184 participants (11.4%) in the strategy group with an initial rifampin-linezolid regimen (adjusted difference, 7.4 percentage points; 97.5% confidence interval [CI], 1.7 to 13.2; noninferiority not met) and 11 of the 189 participants (5.8%) in the strategy group with an initial bedaquiline-linezolid regimen (adjusted difference, 0.8 percentage points; 97.5% CI, -3.4 to 5.1; noninferiority met). The mean total duration of treatment was 180 days in the standard-treatment group, 106 days in the rifampin-linezolid strategy group, and 85 days in the bedaquiline-linezolid strategy group. The incidences of grade 3 or 4 adverse events and serious adverse events were similar in the three groups.

CONCLUSIONS

A strategy involving initial treatment with an 8-week bedaquiline-linezolid regimen was noninferior to standard treatment for tuberculosis with respect to clinical outcomes. The strategy was associated with a shorter total duration of treatment and with no evident safety concerns. (Funded by the Singapore National Medical Research Council and others; TRUNCATE-TB ClinicalTrials.gov number, NCT03474198.).

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.

Comprehensive lipid profiles investigation reveals host metabolic and immune alterations during anti-tuberculosis treatment: Implications for therapeutic monitoring

In this study, we investigated the lipidome of tuberculosis patients during standard chemotherapy to discover biosignatures that could aid therapeutic monitoring. UPLC-QToF MS was used to analyze 82 baseline and treatment plasma samples of patients with pulmonary tuberculosis. Subsequently, a data-driven and knowledge-based workflow, including robust annotation, statistical analysis, and functional analysis, was applied to assess lipid profiles during treatment. Overall, the lipids species from 17 lipid subclasses were significantly altered by anti-tuberculosis chemotherapy. Cholesterol ester (CE), monoacylglycerols, and phosphatidylcholine (PC) were upregulated, whereas triacylglycerols, sphingomyelin, and ether-linked phosphatidylethanolamines (PE O-) were downregulated. Notably, PCs demonstrated a clear upward expression pattern during tuberculosis treatment. Several lipid species were identified as potential biomarkers for therapeutic monitoring, such as PC(42:6), PE(O-40:5), CE(24:6), and dihexosylceramide Hex2Cer(34:2;2 O). Functional and lipid gene enrichment analysis revealed alterations in pathways related to lipid metabolism and host immune responses. In conclusion, this study provides a foundation for the use of lipids as biomarkers for clinical management of tuberculosis.

Circular RNAs and tuberculosis infection

Tuberculosis (TB) is a deadly infectious disease caused by Mycobacterium tuberculosis (Mtb) that affects the immune system chronically. Therefore, effective control and treatment of tuberculosis requires rapid and accurate diagnostic strategies. Tuberculosis has always been a global burden on health, social and economic systems due to the lack of standard curative and diagnostic (bio)markers. Accordingly, the management and monitoring of patients with active TB at the primary care level may be possible through new, rapid and cost-effective non-sputum-based diagnostic procedures. Biomarkers can help diagnose various diseases, including circular RNA (circRNA), which has recently been introduced as an endogenous, abundant and stable RNA in the cytoplasm with unique tissue specificity. There are frequent reports of circRNA involvement in many pathological and physiological processes in human beings. Recent studies have highlighted the presence of circRNAs in serum and their role as promising biomarkers in the diagnosis of the disease, potentially due to the continuous, stable, closed covalent circular structures and lack of easy degradation by nucleases. The purpose of this review article is to scrutinize the behavior of circulating plasma RNAs in relation to the pathogenesis and diagnosis of tuberculosis.

Diagnosis and biomarkers for ocular tuberculosis: From the present into the future

Tuberculosis is an airborne disease caused by Mycobacterium tuberculosis (Mtb) and can manifest both pulmonary and extrapulmonary disease, including ocular tuberculosis (OTB). Accurate diagnosis and swift optimal treatment initiation for OTB is faced by many challenges combined with the lack of standardized treatment regimens this results in uncertain OTB outcomes. The purpose of this study is to summarize existing diagnostic approaches and recently discovered biomarkers that may contribute to establishing OTB diagnosis, choice of anti-tubercular therapy (ATT) regimen, and treatment monitoring. The keywords ocular tuberculosis, tuberculosis, Mycobacterium, biomarkers, molecular diagnosis, multi-omics, proteomics, genomics, transcriptomics, metabolomics, T-lymphocytes profiling were searched on PubMed and MEDLINE databases. Articles and books published with at least one of the keywords were included and screened for relevance. There was no time limit for study inclusion. More emphasis was placed on recent publications that contributed new information about the pathogenesis, diagnosis, or treatment of OTB. We excluded abstracts and articles that were not written in the English language. References cited within the identified articles were used to further supplement the search. We found 10 studies evaluating the sensitivity and specificity of interferon-gamma release assay (IGRA), and 6 studies evaluating that of tuberculin skin test (TST) in OTB patients. IGRA (Sp = 71-100%, Se = 36-100%) achieves overall better sensitivity and specificity than TST (Sp = 51.1-85.7%; Se = 70.9-98.5%). For nuclear acid amplification tests (NAAT), we found 7 studies on uniplex polymerase chain reaction (PCR) with different Mtb targets, 7 studies on DNA-based multiplex PCR, 1 study on mRNA-based multiplex PCR, 4 studies on loop-mediated isothermal amplification (LAMP) assay with different Mtb targets, 3 studies on GeneXpert assay, 1 study on GeneXpert Ultra assay and 1 study for MTBDRplus assay for OTB. Specificity is overall improved but sensitivity is highly variable for NAATs (excluding uniplex PCR, Sp = 50-100%; Se = 10.5-98%) as compared to IGRA. We also found 3 transcriptomic studies, 6 proteomic studies, 2 studies on stimulation assays, 1 study on intraocular protein analysis and 1 study on T-lymphocyte profiling in OTB patients. All except 1 study evaluated novel, previously undiscovered biomarkers. Only 1 study has been externally validated by a large independent cohort. Future theranostic marker discovery by a multi-omics approach is essential to deepen pathophysiological understanding of OTB. Combined these might result in swift, optimal and personalized treatment regimens to modulate the heterogeneous mechanisms of OTB. Eventually, these studies could improve the current cumbersome diagnosis and management of OTB.

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.

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

BACKGROUND

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

METHOD

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

RESULTS

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

CONCLUSION

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

Clinical utility of C-reactive protein-based triage for presumptive pulmonary tuberculosis in South African adults

BACKGROUND

Identification of an accurate, low-cost triage test for pulmonary TB among people presenting to healthcare facilities is an urgent global research priority. We assessed the diagnostic accuracy and clinical utility of C-reactive protein (CRP) for TB triage among symptomatic adult outpatients, irrespective of HIV status.

METHODS

We prospectively enrolled adults reporting at least one (for people with HIV) or two (for people without HIV) symptoms of cough, fever, night sweats, or weight loss at two TB clinics in Cape Town, South Africa. Participants provided sputum for culture and Xpert MTB/RIF Ultra. We evaluated the diagnostic accuracy of CRP (measured using a laboratory-based assay) against a TB-culture reference standard as the area under the receiver operating characteristic curve (AUROC), and sensitivity and specificity at pre-specified thresholds. We assessed clinical utility using decision curve analysis and benchmarked against WHO recommendations.

RESULTS

Of 932 included individuals, 255 (27%) had culture-confirmed pulmonary TB and 389 (42%) were living with HIV. CRP demonstrated an AUROC of 0·80 (95% confidence interval 0·77-0·83), with sensitivity 93% (89-95%) and specificity 54% (50-58%) using a primary cut-off of ≥10 mg/L. Performance was similar among people with HIV to those without. In decision curve analysis, CRP-based triage offered greater clinical utility than confirmatory testing for all up to a number willing to test threshold of 20 confirmatory tests per true positive pulmonary TB case diagnosed (threshold probability 5%). If it is possible to perform more confirmatory tests than this, a 'confirmatory test for all' strategy performed better.

CONCLUSIONS

CRP achieved the WHO-defined sensitivity, but not specificity, targets for a triage test for pulmonary TB and showed evidence of clinical utility among symptomatic outpatients, irrespective of HIV status.

FUNDING

South African Medical Research Council, EDCTP2, Royal Society Newton Advanced Fellowship, Wellcome Trust, National Institute of Health Research, Royal College of Physicians.

Development of diagnostic algorithm using machine learning for distinguishing between active tuberculosis and latent tuberculosis infection

BACKGROUND

The discrimination between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging. The present study aims to investigate the value of diagnostic models established by machine learning based on multiple laboratory data for distinguishing Mycobacterium tuberculosis (Mtb) infection status.

METHODS

T-SPOT, lymphocyte characteristic detection, and routine laboratory tests were performed on participants. Diagnostic models were built according to various algorithms.

RESULTS

A total of 892 participants (468 ATB and 424 LTBI) and another 263 participants (125 ATB and 138 LTBI), were respectively enrolled at Tongji Hospital (discovery cohort) and Sino-French New City Hospital (validation cohort). Receiver operating characteristic (ROC) curve analysis showed that the value of individual indicator for differentiating ATB from LTBI was limited (area under the ROC curve (AUC) < 0.8). A total of 28 models were successfully established using machine learning. Among them, the AUCs of 25 models were more than 0.9 in test set. It was found that conditional random forests (cforest) model, based on the implementation of the random forest and bagging ensemble algorithms utilizing conditional inference trees as base learners, presented best discriminative power in segregating ATB from LTBI. Specially, cforest model presented an AUC of 0.978, with the sensitivity of 93.39% and the specificity of 91.18%. Mtb-specific response represented by early secreted antigenic target 6 (ESAT-6) and culture filtrate protein 10 (CFP-10) spot-forming cell (SFC) in T-SPOT assay, as well as global adaptive immunity assessed by CD4 cell IFN-γ secretion, CD8 cell IFN-γ secretion, and CD4 cell number, were found to contribute greatly to the cforest model. Superior performance obtained in the discovery cohort was further confirmed in the validation cohort. The sensitivity and specificity of cforest model in validation set were 92.80% and 89.86%, respectively.

CONCLUSIONS

Cforest model developed upon machine learning could serve as a valuable and prospective tool for identifying Mtb infection status. The present study provided a novel and viable idea for realizing the clinical diagnostic application of the combination of machine learning and laboratory findings.

Biofabrication of Multiplexed Electrochemical Immunosensors for Simultaneous Detection of Clinical Biomarkers in Complex Fluids

Simultaneous detection of multiple disease biomarkers in unprocessed whole blood is considered the gold standard for accurate clinical diagnosis. Here, this study reports the development of a 4-plex electrochemical (EC) immunosensor with on-chip negative control capable of detecting a range of biomarkers in small volumes (15 µL) of complex biological fluids, including serum, plasma, and whole blood. A framework for fabricating and optimizing multiplexed sandwich immunoassays is presented that is enabled by use of EC sensor chips coated with an ultra-selective, antifouling, and nanocomposite coating. Cyclic voltammetry evaluation of sensor performance is carried out by monitoring the local precipitation of an electroactive product generated by horseradish peroxidase linked to a secondary antibody. EC immunosensors demonstrate high sensitivity and specificity without background signal with a limit of detection in single-digit picogram per milliliter in multiple complex biological fluids. These multiplexed immunosensors enable the simultaneous detection of four different biomarkers in plasma and whole blood with excellent sensitivity and selectivity. This rapid and cost-effective biosensor platform can be further adapted for use with different high affinity probes for any biomarker, and thereby create for a new class of highly sensitive and specific multiplexed diagnostics.

Comprehensive lipid and lipid-related gene investigations of host immune responses to characterize metabolism-centric biomarkers for pulmonary tuberculosis

Despite remarkable success in the prevention and treatment of tuberculosis (TB), it remains one of the most devastating infectious diseases worldwide. Management of TB requires an efficient and timely diagnostic strategy. In this study, we comprehensively characterized the plasma lipidome of TB patients, then selected candidate lipid and lipid-related gene biomarkers using a data-driven, knowledge-based framework. Among 93 lipids that were identified as potential biomarker candidates, ether-linked phosphatidylcholine (PC O–) and phosphatidylcholine (PC) were generally upregulated, while free fatty acids and triglycerides with longer fatty acyl chains were downregulated in the TB group. Lipid-related gene enrichment analysis revealed significantly altered metabolic pathways (e.g., ether lipid, linolenic acid, and cholesterol) and immune response signaling pathways. Based on these potential biomarkers, TB patients could be differentiated from controls in the internal validation (random forest model, area under the curve [AUC] 0.936, 95% confidence interval [CI] 0.865–0.992). PC(O-40:4), PC(O-42:5), PC(36:0), and PC(34:4) were robust biomarkers able to distinguish TB patients from individuals with latent infection and healthy controls, as shown in the external validation. Small changes in expression were identified for 162 significant lipid-related genes in the comparison of TB patients vs. controls; in the random forest model, their utilities were demonstrated by AUCs that ranged from 0.829 to 0.956 in three cohorts. In conclusion, this study introduced a potential framework that can be used to identify and validate metabolism-centric biomarkers.

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

Funding

Diagnosing Tuberculosis: What Do New Technologies Allow Us to (Not) Do?

New tuberculosis (TB) diagnostics are at a crossroads: their development, evaluation, and implementation is severely damaged by resource diversion due to COVID-19. Yet several technologies, especially those with potential for non-invasive non-sputum-based testing, hold promise for efficiently triaging and rapidly confirming TB near point-of-care. Such tests are, however, progressing through the pipeline slowly and will take years to reach patients and health workers. Compellingly, such tests will create new opportunities for difficult-to-diagnose populations, including primary care attendees (all-comers in high burden settings irrespective of reason for presentation) and community members (with early stage disease or risk factors like HIV), many of whom cannot easily produce sputum. Critically, all upcoming technologies have limitations that implementers and health workers need to be cognizant of to ensure optimal deployment without undermining confidence in a technology that still offers improvements over the status quo. In this state-of-the-art review, we critically appraise such technologies for active pulmonary TB diagnosis. We highlight strengths, limitations, outstanding research questions, and how current and future tests could be used in the presence of these limitations and uncertainties. Among triage tests, CRP (for which commercial near point-of-care devices exist) and computer-aided detection software with digital chest X-ray hold promise, together with late-stage blood-based assays that detect host and/or microbial biomarkers; however, aside from a handful of prototypes, the latter category has a shortage of promising late-stage alternatives. Furthermore, positive results from new triage tests may have utility in people without TB; however, their utility for informing diagnostic pathways for other diseases is under-researched (most sick people tested for TB do not have TB). For confirmatory tests, few true point-of-care options will be available soon; however, combining novel approaches like tongue swabs with established tests like Ultra have short-term promise but first require optimizations to specimen collection and processing procedures. Concerningly, no technologies yet have compelling evidence of meeting the World Health Organization optimal target product profile performance criteria, especially for important operational criteria crucial for field deployment. This is alarming as the target product profile criteria are themselves almost a decade old and require urgent revision, especially to cater for technologies made prominent by the COVID-19 diagnostic response (e.g., at-home testing and connectivity solutions). Throughout the review, we underscore the importance of how target populations and settings affect test performance and how the criteria by which these tests should be judged vary by use case, including in active case finding. Lastly, we advocate for health workers and researchers to themselves be vocal proponents of the uptake of both new tests and those - already available tests that remain suboptimally utilized.

Evaluating the efficacy of stool sample on Xpert MTB/RIF Ultra and its comparison with other sample types by meta-analysis for TB diagnostics

Precise and timely detection of tuberculosis (TB) is crucial to reduce transmission. This study aims to assess the accuracy of Xpert MTB/RIF Ultra on stool samples and systematically review the performance of Xpert MTB/RIF Ultra with different sample types by meta-analysis. Stool samples of smear-negative pulmonary TB (PTB), cervical lymph node TB, and abdominal TB patients were tested on the Xpert MTB/RIF Ultra system. Meta-analysis was performed on a set of 44 studies. Data were grouped by sample type, and the pooled sensitivity and specificity of Xpert MTB/RIF Ultra were calculated. The sensitivity of Xpert MTB/RIF Ultra with stool samples was 100% for smear-negative PTB, 27.27% for cervical lymph node TB, and 50% for abdominal TB patients, with 100% specificity for all included TB groups. The summary estimate for all PTB samples showed 84.2% sensitivity and 94.5% specificity, and EPTB samples showed 88.6% sensitivity and 96.4% specificity. Among all sample types included in our meta-analysis, urine showed the best performance for EPTB diagnosis. This pilot study supports the use of stool as an alternative non-invasive sample on Xpert MTB/RIF Ultra for rapid testing, suitable for both PTB and EPTB diagnosis.

Machine learning based on routine laboratory indicators promoting the discrimination between active tuberculosis and latent tuberculosis infection

BACKGROUND

Discriminating active tuberculosis (ATB) from latent tuberculosis infection (LTBI) remains challenging. The present study aims to evaluate the performance of diagnostic models established using machine learning based on routine laboratory indicators in differentiating ATB from LTBI.

METHODS

Participants were respectively enrolled at Tongji Hospital (discovery cohort) and Sino-French New City Hospital (validation cohort). Diagnostic models were established based on routine laboratory indicators using machine learning.

RESULTS

A total of 2619 participants (1025 ATB and 1594 LTBI) were enrolled in discovery cohort and another 942 subjects (388 ATB and 554 LTBI) were recruited in validation cohort. ATB patients had significantly higher levels of tuberculosis-specific antigen/phytohemagglutinin ratio and coefficient variation of red blood cell volume distribution width, and lower levels of albumin and lymphocyte count than those of LTBI individuals. Six models were built and the optimal performance was obtained from GBM model. GBM model derived from training set (n = 1965) differentiated ATB from LTBI in the test set (n = 654) with a sensitivity of 84.38% (95% CI, 79.42%-88.31%) and a specificity of 92.71% (95% CI, 89.73%-94.88%). Further validation by an independent cohort confirmed its encouraging value with a sensitivity of 87.63% (95% CI, 83.98%-90.54%) and specificity of 91.34% (95% CI, 88.70%-93.40%), respectively.

CONCLUSIONS

We successfully developed a model with promising diagnostic value based on machine learning for the first time. Our study proposed that GBM model may be of great benefit served as a tool for the accurate identification of ATB.

Up-regulated SAMD9L modulated by TLR2 and HIF-1α as a promising biomarker in tuberculosis

The aim of this study was to identify potential biomarkers of TB in blood and determine their function in Mtb-infected macrophages. First of all, WGCNA was used to analyse 9451 genes with significant changes in TB patients' whole blood. The 220 interferon-γ-related genes were identified, and then 30 key genes were screened using Cytoscape. Then, the AUC values of key genes were calculated to further narrow the gene range. Finally, we identified 9 genes from GSE19444. ROC analysis showed that SAMD9L, among 9 genes, had a high diagnostic value (AUC = 0.925) and a differential diagnostic value (AUC>0.865). To further narrow down the range of DEGs, the top 10 hub-connecting genes were screened from monocytes (GSE19443). Finally, we obtained 4 genes (SAMD9L, GBP1, GBP5 and STAT1) by intersections of genes from monocytes and whole blood. Among them, it was found that the function of SAMD9L was unknown after data review, so this paper studied this gene. Our results showed that SAMD9L is up-regulated and suppresses cell necrosis, and might be regulated by TLR2 and HIF-1α during Mtb infection. In addition, miR-181b-5p is significantly up-regulated in the peripheral blood plasma of tuberculosis patients, which has a high diagnostic value (AUC = 0.969).

Point-of-care diagnostic tests for tuberculosis disease

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

Whole blood GBP5 protein levels in patients with and without active tuberculosis

Background

The host blood transcriptional levels of several genes, such as guanylate binding protein 5 (GBP5), have been reported as potential biomarkers for active tuberculosis (aTB) diagnosis. The aim of this study was to investigate whole blood GBP5 protein levels in aTB and non-tuberculosis patients.

Methods

An in-house immunoassay for testing GBP5 protein levels in whole blood was developed, and suspected aTB patients were recruited. Whole blood samples were collected and tested at enrolment using interferon-gamma release assay (IGRA) and the GBP5 assay.

Results

A total of 470 participants were enrolled, and 232 and 238 patients were finally diagnosed with aTB and non-TB, respectively. The GBP5 protein levels of aTB patients were significantly higher than those of non-tuberculosis patients (p < 0.001), and the area under the ROC curve of the GBP5 assay for aTB diagnosis was 0.76. The reactivity of the GBP5 assay between pulmonary and extrapulmonary tuberculosis patients was comparable (p = 0.661). With the optimal cut-off value, the sensitivity and specificity of the GBP5 assay for diagnosing aTB were 78.02 and 66.81%, respectively, while those of IGRA were 77.59 and 76.47%. The combination of the GBP5 assay and IGRA results in 88.52% accuracy for diagnosing aTB in 63.83% of suspected patients with a positive predictive value of 89.57% and a negative predictive value of 87.59%.

Conclusions

Whole blood GBP5 protein is a valuable biomarker for diagnosing of aTB. This study provides an important idea for realizing the clinical application of whole blood transcriptomics findings by immunological methods.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07214-8.

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.

mtTB: A Web-Based R/Shiny App for Pulmonary Tuberculosis Screening

Pulmonary tuberculosis caused by Mycobacterium tuberculosis remains a global issue. However, the diagnosis of active pulmonary tuberculosis (TB) remains a challenge in the clinic. Small non-coding RNAs are potential diagnostic biomarkers for pulmonary tuberculosis. However, the current normalization methods are not stable and usually fail to reliably detect differentially expressed sncRNAs. To identify reliable biomarkers for pulmonary tuberculosis screening, we utilized the ratio-based method on the newly discovered mitochondria-derived small RNAs in human peripheral blood mononuclear cells. The prediction model of seven mtRNA biomarkers noteworthily enables the discrimination between pulmonary tuberculosis patients and controls in discovery (AUC = 0.906, 23 patients) and independent validation cohort (AUC = 0.968, 20 patients). Moreover, we present mtTB (https://tuberculosis.shinyapps.io/mtTB/), a novel R Graphical User Interface (GUI) that provides reliable biomarkers for the feasibility of blood-based screening, and produce a more accurate tool for pulmonary tuberculosis diagnosis in real clinical practice.

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.