Transcriptomic signatures for diagnosing tuberculosis in clinical practice: a prospective, multicentre cohort study

Abstract

Summary Background Blood transcriptomic signatures for diagnosis of tuberculosis have shown promise in case-control studies, but none have been prospectively designed or validated in adults presenting with the full clinical spectrum of suspected tuberculosis, including extrapulmonary tuberculosis and common differential diagnoses that clinically resemble tuberculosis. We aimed to evaluate the diagnostic accuracy of transcriptomic signatures in patients presenting with clinically suspected tuberculosis in routine practice. Methods The Validation of New Technologies for Diagnostic Evaluation of Tuberculosis (VANTDET) study was nested within a prospective, multicentre cohort study in secondary care in England (IDEA 11/H0722/8). Patients (aged ≥16 years) suspected of having tuberculosis in the routine clinical inpatient and outpatient setting were recruited at ten National Health Service hospitals in England for IDEA and were included in VANTDET if they provided consent for genomic analysis. Patients had whole blood taken for microarray analysis to measure abundance of transcripts and were followed up for 6–12 months to determine final diagnoses on the basis of predefined diagnostic criteria. The diagnostic accuracy of six signatures derived from the cohort and three previously published transcriptomic signatures with potentially high diagnostic performance were assessed by calculating area under the receiver-operating characteristic curves (AUC-ROCs), sensitivities, and specificities. Findings Between Nov 25, 2011, and Dec 31, 2013, 1162 participants were enrolled. 628 participants (aged ≥16 years) were included in the analysis, of whom 212 (34%) had culture-confirmed tuberculosis, 89 (14%) had highly probable tuberculosis, and 327 (52%) had tuberculosis excluded. The novel signature with highest performance for identifying all active tuberculosis gave an AUC-ROC of 0·87 (95% CI 0·81–0·92), sensitivity of 77% (66–87), and specificity of 84% (74–91). The best-performing published signature gave an AUC-ROC of 0·83 (0·80–0·86), sensitivity of 78% (73–83), and specificity of 76% (70–80). For detecting highly probable tuberculosis, the best novel signature yielded results of 0·86 (0·71–0·95), 77% (56–94%), and 77% (57–95%). None of the relevant cohort-derived or previously published signatures achieved the WHO-defined targets of paired sensitivity and specificity for a non-sputum-based diagnostic test. Interpretation In a clinically representative cohort in routine practice in a low-incidence setting, transcriptomic signatures did not have adequate accuracy for diagnosis of tuberculosis, including in patients with highly probable tuberculosis where the unmet need is greatest. These findings suggest that transcriptomic signatures have little clinical utility for diagnostic assessment of suspected tuberculosis. Funding National Institute for Health Research.

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

“… Triage Collection method and not a test itself - Studies are few and heterogenous, no pooled performance estimates exist - Ultra applied to a single swab had a sensitivity of 88% in outpatients 41 but only 43% sensitivity when used for active case finding in a prison 40 - TB-LAMP 42 applied to oral swabs had sensitivities ranging from 33-50% - FLOQSwabs (Copan Italia) preferred 41 - Self-swabbing, comparable to health worker-administered swabs for other pathogens 44 , appears feasible - Potential for paediatric TB 43 - Insufficient Mtb may be recovered from swabs in patients with low sputum bacillary load 40 - Performance of novel assays (e.g., next-generation LAM and NAATs unknown) may overcome sensitivity limitations associated - Optimal number of swabs, swab design, and the processing method are under evaluation and may improve the release of material from swabs -No tests purpose-built for tongue swabs yet exist Blood Host transcriptome mRNA blood signatures associated with the immune system's response to Mtb have shown promise for diagnosis. 68 Triage Xpert Host Response (Cepheid) - A multicentre study showed 90% sensitivity and 86% specificity 64 -Other studies have shown lower specificities (26% 101 , 53% 102 ) at >90% sensitivity - Limited data with small numbers of cases, however, multicentre studies are emerging - Xpert HR has the most data available - RNA is labile and, for Xpert HR, time from blood collection to testing must be <30 min and stabilisation agents may be required - Cost unclear, but likely high - Potential utility treatment response monitoring, management of diseases other than TB (signature-positive patients without TB could have other infections 95 ), and false-positive TB PCR results 65 , which are frequent in people with previous TB 68 , 84 , 103 - Signatures (including Sweeney3 in Xpert HR) measured using ultra-sensitive methods (sequencing, Nanostring) 68 struggle to meet WHO TPPs 65 , 66 ...…”

Personalised Medicine for Tuberculosis and Non-Tuberculous Mycobacterial Pulmonary Disease

“…Furthermore various transcriptomic signatures that distinguish between latent and active disease in high-incidence settings have been reported [20,21]. Recently however in a whole blood microarray analysis of TB patients in a low-incidence setting, transcriptomic signatures were not found to be sufficiently sensitive or specific to diagnose TB [22]. Additionally, a review has found that the diagnostic accuracy of previously published transcriptomic signatures for TB was lower than reported [117].…”

“…In an adult population in a high-incidence setting, a 44-transcript signature was used to calculate a disease risk score for patients which was found to differentiate between active TB and other diseases with a sensitivity of 93% and specificity of 88% [21]. In a prospective study from a low-incidence setting, the highest performing transcriptomic signature indicative of active TB had both a sensitivity and specificity of 77%, which was insufficient to meet World Health Organisation (WHO) diagnostic cut-offs for non-sputum tests for smear-negative TB [22].…”

Contribution and Future of High-Throughput Transcriptomics in Battling Tuberculosis

“…Jacobsen et al, 2007;Mistry et al, 2007;Berry et al, 2010;Maertzdorf et al, 2011a,b;Anderson et al, 2014;Cai et al, 2014;Zak et al, 2016;Singhania et al, 2018;Estévez et al, 2020 • Biomarkers that differentiate TB from other infectious diseases. Berry et al, 2010;Maertzdorf et al, 2012;Bloom et al, 2013;Kaforou et al, 2013;Anderson et al, 2014;Hoang et al, 2021 • Biomarkers for extrapulmonary TB.…”

“…The scientific community has made efforts in discriminating the TB gene signature from extrapulmonary TB ( Roe et al, 2016 ) and other diseases ( Berry et al, 2010 ; Maertzdorf et al, 2012 ; Bloom et al, 2013 ), specially other pulmonary diseases or co-infecting diseases that are highly prevalent in TB endemic areas. Multicenter studies ( Kaforou et al, 2013 ; Anderson et al, 2014 ; Hoang et al, 2021 ) included a superior number of patients suffering from TB and other diseases, including HIV-coinfection.…”