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Screening and identification of a six-cytokine biosignature for detecting TB infection and discriminating active from latent TB

BACKGROUND: The early and accurate diagnosis of tuberculosis (TB) is critical for controlling the global TB epidemic. Although early studies have supported the potential role of cytokine biomarkers in blood for the diagnosis of TB, this method requires further investigation and validation in differe...

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Autores principales: Wang, Sen, Li, Yang, Shen, Yaojie, Wu, Jing, Gao, Yan, Zhang, Shu, Shao, Lingyun, Jin, Jialin, Zhang, Ying, Zhang, Wenhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6054748/
https://www.ncbi.nlm.nih.gov/pubmed/30029650
http://dx.doi.org/10.1186/s12967-018-1572-x
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author Wang, Sen
Li, Yang
Shen, Yaojie
Wu, Jing
Gao, Yan
Zhang, Shu
Shao, Lingyun
Jin, Jialin
Zhang, Ying
Zhang, Wenhong
author_facet Wang, Sen
Li, Yang
Shen, Yaojie
Wu, Jing
Gao, Yan
Zhang, Shu
Shao, Lingyun
Jin, Jialin
Zhang, Ying
Zhang, Wenhong
author_sort Wang, Sen
collection PubMed
description BACKGROUND: The early and accurate diagnosis of tuberculosis (TB) is critical for controlling the global TB epidemic. Although early studies have supported the potential role of cytokine biomarkers in blood for the diagnosis of TB, this method requires further investigation and validation in different populations. A set of biomarkers that can discriminate between active TB (ATB) and latent TB infection (LTBI) remains elusive. METHODS: In the current study, we organized two retrospective cohorts and one prospective cohort to investigate the immune responses at different clinical stages of TB infection, as determined by candidate cytokine biomarkers detected with a multiplex cytokine platform. Using a pre-established diagnostic algorithm, participants were classified as ATB, LTBI, and TB uninfected controls (CON). Based on our multiplex cytokine assay, a multi-cytokine biosignature was modelled for the optimal recognition of the different TB infection status. RESULTS: Our analysis identified a six-cytokine biosignature of TB-antigen stimulated IFN-γ, IP-10, and IL-1Ra, and unstimulated IP-10, VEGF, and IL-12 (p70) for a biomarker screening group (n = 88). The diagnostic performance of the biosignature was then validated using a biomarker validation cohort (n = 216) and resulted in a sensitivity of 88.2% and a specificity of 92.1%. In a prospectively recruited clinical validation cohort (n = 194), the six-cytokine biosignature was further evaluated, and displayed a sensitivity of 85.7%, a specificity of 91.3% and an overall accuracy of 88.7%. CONCLUSIONS: We have identified a six-cytokine biosignature for accurately differentiating ATB patients from subjects with LTBI and CON. This approach holds promise as an early and rapid diagnostic test for ATB. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12967-018-1572-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-60547482018-07-23 Screening and identification of a six-cytokine biosignature for detecting TB infection and discriminating active from latent TB Wang, Sen Li, Yang Shen, Yaojie Wu, Jing Gao, Yan Zhang, Shu Shao, Lingyun Jin, Jialin Zhang, Ying Zhang, Wenhong J Transl Med Research BACKGROUND: The early and accurate diagnosis of tuberculosis (TB) is critical for controlling the global TB epidemic. Although early studies have supported the potential role of cytokine biomarkers in blood for the diagnosis of TB, this method requires further investigation and validation in different populations. A set of biomarkers that can discriminate between active TB (ATB) and latent TB infection (LTBI) remains elusive. METHODS: In the current study, we organized two retrospective cohorts and one prospective cohort to investigate the immune responses at different clinical stages of TB infection, as determined by candidate cytokine biomarkers detected with a multiplex cytokine platform. Using a pre-established diagnostic algorithm, participants were classified as ATB, LTBI, and TB uninfected controls (CON). Based on our multiplex cytokine assay, a multi-cytokine biosignature was modelled for the optimal recognition of the different TB infection status. RESULTS: Our analysis identified a six-cytokine biosignature of TB-antigen stimulated IFN-γ, IP-10, and IL-1Ra, and unstimulated IP-10, VEGF, and IL-12 (p70) for a biomarker screening group (n = 88). The diagnostic performance of the biosignature was then validated using a biomarker validation cohort (n = 216) and resulted in a sensitivity of 88.2% and a specificity of 92.1%. In a prospectively recruited clinical validation cohort (n = 194), the six-cytokine biosignature was further evaluated, and displayed a sensitivity of 85.7%, a specificity of 91.3% and an overall accuracy of 88.7%. CONCLUSIONS: We have identified a six-cytokine biosignature for accurately differentiating ATB patients from subjects with LTBI and CON. This approach holds promise as an early and rapid diagnostic test for ATB. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12967-018-1572-x) contains supplementary material, which is available to authorized users. BioMed Central 2018-07-20 /pmc/articles/PMC6054748/ /pubmed/30029650 http://dx.doi.org/10.1186/s12967-018-1572-x Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Wang, Sen
Li, Yang
Shen, Yaojie
Wu, Jing
Gao, Yan
Zhang, Shu
Shao, Lingyun
Jin, Jialin
Zhang, Ying
Zhang, Wenhong
Screening and identification of a six-cytokine biosignature for detecting TB infection and discriminating active from latent TB
title Screening and identification of a six-cytokine biosignature for detecting TB infection and discriminating active from latent TB
title_full Screening and identification of a six-cytokine biosignature for detecting TB infection and discriminating active from latent TB
title_fullStr Screening and identification of a six-cytokine biosignature for detecting TB infection and discriminating active from latent TB
title_full_unstemmed Screening and identification of a six-cytokine biosignature for detecting TB infection and discriminating active from latent TB
title_short Screening and identification of a six-cytokine biosignature for detecting TB infection and discriminating active from latent TB
title_sort screening and identification of a six-cytokine biosignature for detecting tb infection and discriminating active from latent tb
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6054748/
https://www.ncbi.nlm.nih.gov/pubmed/30029650
http://dx.doi.org/10.1186/s12967-018-1572-x
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