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Blood transcriptomic diagnosis of pulmonary and extrapulmonary tuberculosis

BACKGROUND. Novel rapid diagnostics for active tuberculosis (TB) are required to overcome the time delays and inadequate sensitivity of current microbiological tests that are critically dependent on sampling the site of disease. Multiparametric blood transcriptomic signatures of TB have been describ...

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Autores principales: Roe, Jennifer K, Thomas, Niclas, Gil, Eliza, Best, Katharine, Tsaliki, Evdokia, Morris‑Jones, Stephen, Stafford, Sian, Simpson, Nandi, Witt, Karolina D, Chain, Benjamin, Miller, Robert F, Martineau, Adrian, Noursadeghi, Mahdad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Clinical Investigation 2016
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5053151/
https://www.ncbi.nlm.nih.gov/pubmed/27734027
http://dx.doi.org/10.1172/jci.insight.87238
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author Roe, Jennifer K
Thomas, Niclas
Gil, Eliza
Best, Katharine
Tsaliki, Evdokia
Morris‑Jones, Stephen
Stafford, Sian
Simpson, Nandi
Witt, Karolina D
Chain, Benjamin
Miller, Robert F
Martineau, Adrian
Noursadeghi, Mahdad
author_facet Roe, Jennifer K
Thomas, Niclas
Gil, Eliza
Best, Katharine
Tsaliki, Evdokia
Morris‑Jones, Stephen
Stafford, Sian
Simpson, Nandi
Witt, Karolina D
Chain, Benjamin
Miller, Robert F
Martineau, Adrian
Noursadeghi, Mahdad
author_sort Roe, Jennifer K
collection PubMed
description BACKGROUND. Novel rapid diagnostics for active tuberculosis (TB) are required to overcome the time delays and inadequate sensitivity of current microbiological tests that are critically dependent on sampling the site of disease. Multiparametric blood transcriptomic signatures of TB have been described as potential diagnostic tests. We sought to identify the best transcript candidates as host biomarkers for active TB, extend the evaluation of their specificity by comparison with other infectious diseases, and to test their performance in both pulmonary and extrapulmonary TB. METHODS. Support vector machine learning, combined with feature selection, was applied to new and previously published blood transcriptional profiles in order to identify the minimal TB‑specific transcriptional signature shared by multiple patient cohorts including pulmonary and extrapulmonary TB, and individuals with and without HIV-1 coinfection. RESULTS. We identified and validated elevated blood basic leucine zipper transcription factor 2 (BATF2) transcript levels as a single sensitive biomarker that discriminated active pulmonary and extrapulmonary TB from healthy individuals, with receiver operating characteristic (ROC) area under the curve (AUC) scores of 0.93 to 0.99 in multiple cohorts of HIV-1–negative individuals, and 0.85 in HIV-1–infected individuals. In addition, we identified and validated a potentially novel 4-gene signature comprising CD177, haptoglobin, immunoglobin J chain, and galectin 10 that discriminated active pulmonary and extrapulmonary TB from other febrile infections, giving ROC AUCs of 0.94 to 1. CONCLUSIONS. Elevated blood BATF2 transcript levels provide a sensitive biomarker that discriminates active TB from healthy individuals, and a potentially novel 4-gene transcriptional signature differentiates between active TB and other infectious diseases in individuals presenting with fever. FUNDING. MRC, Wellcome Trust, Rosetrees Trust, British Lung Foundation, NIHR.
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spelling pubmed-50531512016-10-12 Blood transcriptomic diagnosis of pulmonary and extrapulmonary tuberculosis Roe, Jennifer K Thomas, Niclas Gil, Eliza Best, Katharine Tsaliki, Evdokia Morris‑Jones, Stephen Stafford, Sian Simpson, Nandi Witt, Karolina D Chain, Benjamin Miller, Robert F Martineau, Adrian Noursadeghi, Mahdad JCI Insight Clinical Medicine BACKGROUND. Novel rapid diagnostics for active tuberculosis (TB) are required to overcome the time delays and inadequate sensitivity of current microbiological tests that are critically dependent on sampling the site of disease. Multiparametric blood transcriptomic signatures of TB have been described as potential diagnostic tests. We sought to identify the best transcript candidates as host biomarkers for active TB, extend the evaluation of their specificity by comparison with other infectious diseases, and to test their performance in both pulmonary and extrapulmonary TB. METHODS. Support vector machine learning, combined with feature selection, was applied to new and previously published blood transcriptional profiles in order to identify the minimal TB‑specific transcriptional signature shared by multiple patient cohorts including pulmonary and extrapulmonary TB, and individuals with and without HIV-1 coinfection. RESULTS. We identified and validated elevated blood basic leucine zipper transcription factor 2 (BATF2) transcript levels as a single sensitive biomarker that discriminated active pulmonary and extrapulmonary TB from healthy individuals, with receiver operating characteristic (ROC) area under the curve (AUC) scores of 0.93 to 0.99 in multiple cohorts of HIV-1–negative individuals, and 0.85 in HIV-1–infected individuals. In addition, we identified and validated a potentially novel 4-gene signature comprising CD177, haptoglobin, immunoglobin J chain, and galectin 10 that discriminated active pulmonary and extrapulmonary TB from other febrile infections, giving ROC AUCs of 0.94 to 1. CONCLUSIONS. Elevated blood BATF2 transcript levels provide a sensitive biomarker that discriminates active TB from healthy individuals, and a potentially novel 4-gene transcriptional signature differentiates between active TB and other infectious diseases in individuals presenting with fever. FUNDING. MRC, Wellcome Trust, Rosetrees Trust, British Lung Foundation, NIHR. American Society for Clinical Investigation 2016-10-06 /pmc/articles/PMC5053151/ /pubmed/27734027 http://dx.doi.org/10.1172/jci.insight.87238 Text en Copyright © 2016 Roe et al. http://creativecommons.org/licenses/by/4.0/ This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Clinical Medicine
Roe, Jennifer K
Thomas, Niclas
Gil, Eliza
Best, Katharine
Tsaliki, Evdokia
Morris‑Jones, Stephen
Stafford, Sian
Simpson, Nandi
Witt, Karolina D
Chain, Benjamin
Miller, Robert F
Martineau, Adrian
Noursadeghi, Mahdad
Blood transcriptomic diagnosis of pulmonary and extrapulmonary tuberculosis
title Blood transcriptomic diagnosis of pulmonary and extrapulmonary tuberculosis
title_full Blood transcriptomic diagnosis of pulmonary and extrapulmonary tuberculosis
title_fullStr Blood transcriptomic diagnosis of pulmonary and extrapulmonary tuberculosis
title_full_unstemmed Blood transcriptomic diagnosis of pulmonary and extrapulmonary tuberculosis
title_short Blood transcriptomic diagnosis of pulmonary and extrapulmonary tuberculosis
title_sort blood transcriptomic diagnosis of pulmonary and extrapulmonary tuberculosis
topic Clinical Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5053151/
https://www.ncbi.nlm.nih.gov/pubmed/27734027
http://dx.doi.org/10.1172/jci.insight.87238
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