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

Carolin T Turner, Rishi K Gupta, Evdokia Tsaliki, Jennifer K Roe, Prasenjit Mondal, Georgina R Nyawo, Zaida Palmer, Robert F Miller, Byron Wp Reeve, Grant Theron, Mahdad Noursadeghi, Carolin T Turner, Rishi K Gupta, Evdokia Tsaliki, Jennifer K Roe, Prasenjit Mondal, Georgina R Nyawo, Zaida Palmer, Robert F Miller, Byron Wp Reeve, Grant Theron, Mahdad Noursadeghi

Abstract

Background: Blood transcriptional signatures are candidates for non-sputum triage or confirmatory tests of tuberculosis. Prospective head-to-head comparisons of their diagnostic accuracy in real-world settings are necessary to assess their clinical use. We aimed to compare the diagnostic accuracy of candidate transcriptional signatures identified by systematic review, in a setting with a high burden of tuberculosis and HIV.

Methods: We did a prospective observational study nested within a diagnostic accuracy study of sputum Xpert MTB/RIF (Xpert) and Xpert MTB/RIF Ultra (Ultra) tests for pulmonary tuberculosis. We recruited consecutive symptomatic adults aged 18 years or older self-presenting to a tuberculosis clinic in Cape Town, South Africa. Participants provided blood for RNA sequencing, and sputum samples for liquid culture and molecular testing using Xpert and Ultra. We assessed the diagnostic accuracy of candidate blood transcriptional signatures for active tuberculosis (including those intended to distinguish active tuberculosis from other diseases) identified by systematic review, compared with culture or Xpert MTB/RIF positivity as the standard reference. In our primary analysis, patients with tuberculosis were defined as those with either a positive liquid culture or Xpert result. Patients with missing blood RNA or sputum results were excluded. Our primary objective was to benchmark the diagnostic accuracy of candidate transcriptional signatures against the WHO target product profile (TPP) for a tuberculosis triage test.

Findings: Between Feb 12, 2016, and July 18, 2017, we obtained paired sputum and RNA sequencing data from 181 participants, 54 (30%) of whom had confirmed pulmonary tuberculosis. Of 27 eligible signatures identified by systematic review, four achieved the highest diagnostic accuracy with similar area under the receiver operating characteristic curves (Sweeney3: 90·6% [95% CI 85·6-95·6]; Kaforou25: 86·9% [80·9-92·9]; Roe3: 86·9% [80·3-93·5]; and BATF2: 86·8% [80·6-93·1]), independent of age, sex, HIV status, previous tuberculosis, or sputum smear result. At test thresholds that gave 70% specificity (the minimum WHO TPP specificity for a triage test), these four signatures achieved sensitivities between 83·3% (95% CI 71·3-91·0) and 90·7% (80·1-96·0). No signature met the optimum criteria, of 95% sensitivity and 80% specificity proposed by WHO for a triage test, or the minimum criteria (of 65% sensitivity and 98% specificity) for a confirmatory test, but all four correctly identified Ultra-positive, culture-negative patients.

Interpretation: Selected blood transcriptional signatures met the minimum WHO benchmarks for a tuberculosis triage test but not for a confirmatory test. Further development of the signatures is warranted to investigate their possible effects on clinical and health economic outcomes as part of a triage strategy, or when used as add-on confirmatory test in conjunction with the highly sensitive Ultra test for Mycobacterium tuberculosis DNA.

Funding: Royal Society Newton Advanced Fellowship, Wellcome Trust, National Institute of Health Research, and UK Medical Research Council.

Copyright © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Figures

Figure 1
Figure 1
Study flowchart
Figure 2
Figure 2
Tuberculosis scores of the four transcriptional signatures with the highest diagnostic accuracy overall and stratified by HIV status Red lines represent the score threshold of the maximal Youden index, identified from analysis of all patients. The score difference between individuals with and without tuberculosis was significant for all four signatures in both the total cohort and in HIV-stratified cohort subsets (Mann-Whitney test p

Figure 3

ROC curves for the four…

Figure 3

ROC curves for the four transcriptional signatures with the highest diagnostic accuracy in…

Figure 3
ROC curves for the four transcriptional signatures with the highest diagnostic accuracy in HIV-infected versus HIV-uninfected patients Shaded areas represent the 95% CI of the ROC curve sensitivities, plotted at 1% specificity intervals (red shading represents HIV-infected patients and blue shading represents HIV-uninfected patients). AUROC values are reported with 95% CIs in brackets. p values are derived from pairwise comparison of ROC curves, using DeLong tests. AUROC values and CIs are also in appendix 1 (p 10). ROC=receiver operating characteristic. AUROC=area under the ROC curve.

Figure 4

ROC curves of the four…

Figure 4

ROC curves of the four transcriptional signatures with the highest diagnostic accuracy benchmarked…

Figure 4
ROC curves of the four transcriptional signatures with the highest diagnostic accuracy benchmarked against WHO target product profile criteria (A) Blue shaded areas represent the 95% CIs of the ROC curve sensitivities, plotted at 1% specificity intervals. AUROC values are reported with 95% CIs in brackets. (B) ROC curves are replicated with restricted y axes, and benchmarked against target criteria for a tuberculosis triage test. Minimum criteria (90% sensitivity, 70% specificity) are indicated by the dashed black boxes, optimum criteria (95% sensitivity, 80% specificity) are indicated by the blue boxes. Light blue shaded areas represent the 95% CIs. (C) ROC curves are replicated with restricted x axes and benchmarked against minimum criteria for a confirmatory test (dashed black box: 65% sensitivity, 98% specificity). Light blue shaded areas represent the 95% CIs. ROC=receiver operating characteristic. AUROC=area under the ROC curve.

Figure 5

Tuberculosis scores of the four…

Figure 5

Tuberculosis scores of the four transcriptional signatures with the highest diagnostic accuracy in…

Figure 5
Tuberculosis scores of the four transcriptional signatures with the highest diagnostic accuracy in patients with Ultra-positive results Patients with Ultra-positive results were grouped as true-positive tuberculosis (culture-positive or Xpert-positive) and false-positive non-tuberculosis (culture-negative or Xpert-negative). (A) Pie charts representing the proportion of Ultra-positive patients with tuberculosis and individuals without tuberculosis with a history of previous tuberculosis disease. (B) Scores of the four transcriptional signatures with the highest diagnostic accuracy in patients with Ultra-positive results. Red dots indicate patients for whom only traces of Mycobacterium tuberculosis were detected by Ultra analysis. Dashed lines represent the score thresholds of the maximum Youden index, identified from analysis of all patients. The score difference between patients with and without tuberculosis was significant for all four signatures (Mann-Whitney test p<0·0001).
Figure 3
Figure 3
ROC curves for the four transcriptional signatures with the highest diagnostic accuracy in HIV-infected versus HIV-uninfected patients Shaded areas represent the 95% CI of the ROC curve sensitivities, plotted at 1% specificity intervals (red shading represents HIV-infected patients and blue shading represents HIV-uninfected patients). AUROC values are reported with 95% CIs in brackets. p values are derived from pairwise comparison of ROC curves, using DeLong tests. AUROC values and CIs are also in appendix 1 (p 10). ROC=receiver operating characteristic. AUROC=area under the ROC curve.
Figure 4
Figure 4
ROC curves of the four transcriptional signatures with the highest diagnostic accuracy benchmarked against WHO target product profile criteria (A) Blue shaded areas represent the 95% CIs of the ROC curve sensitivities, plotted at 1% specificity intervals. AUROC values are reported with 95% CIs in brackets. (B) ROC curves are replicated with restricted y axes, and benchmarked against target criteria for a tuberculosis triage test. Minimum criteria (90% sensitivity, 70% specificity) are indicated by the dashed black boxes, optimum criteria (95% sensitivity, 80% specificity) are indicated by the blue boxes. Light blue shaded areas represent the 95% CIs. (C) ROC curves are replicated with restricted x axes and benchmarked against minimum criteria for a confirmatory test (dashed black box: 65% sensitivity, 98% specificity). Light blue shaded areas represent the 95% CIs. ROC=receiver operating characteristic. AUROC=area under the ROC curve.
Figure 5
Figure 5
Tuberculosis scores of the four transcriptional signatures with the highest diagnostic accuracy in patients with Ultra-positive results Patients with Ultra-positive results were grouped as true-positive tuberculosis (culture-positive or Xpert-positive) and false-positive non-tuberculosis (culture-negative or Xpert-negative). (A) Pie charts representing the proportion of Ultra-positive patients with tuberculosis and individuals without tuberculosis with a history of previous tuberculosis disease. (B) Scores of the four transcriptional signatures with the highest diagnostic accuracy in patients with Ultra-positive results. Red dots indicate patients for whom only traces of Mycobacterium tuberculosis were detected by Ultra analysis. Dashed lines represent the score thresholds of the maximum Youden index, identified from analysis of all patients. The score difference between patients with and without tuberculosis was significant for all four signatures (Mann-Whitney test p<0·0001).

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Source: PubMed

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