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Genome-wide transcriptional profiling identifies potential signatures in discriminating active tuberculosis from latent infection

To better understand the host immune response involved in the progression from latent tuberculosis infection (LTBI) to active tuberculosis (TB) and identify the potential signatures for discriminating TB from LTBI, we performed a genome-wide transcriptional profile of Mycobacterium tuberculosis (M.T...

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Autores principales: Pan, Liping, Wei, Na, Jia, Hongyan, Gao, Mengqiu, Chen, Xiaoyou, Wei, Rongrong, Sun, Qi, Gu, Shuxiang, Du, Boping, Xing, Aiying, Zhang, Zongde
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5762561/
https://www.ncbi.nlm.nih.gov/pubmed/29348876
http://dx.doi.org/10.18632/oncotarget.22889
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author Pan, Liping
Wei, Na
Jia, Hongyan
Gao, Mengqiu
Chen, Xiaoyou
Wei, Rongrong
Sun, Qi
Gu, Shuxiang
Du, Boping
Xing, Aiying
Zhang, Zongde
author_facet Pan, Liping
Wei, Na
Jia, Hongyan
Gao, Mengqiu
Chen, Xiaoyou
Wei, Rongrong
Sun, Qi
Gu, Shuxiang
Du, Boping
Xing, Aiying
Zhang, Zongde
author_sort Pan, Liping
collection PubMed
description To better understand the host immune response involved in the progression from latent tuberculosis infection (LTBI) to active tuberculosis (TB) and identify the potential signatures for discriminating TB from LTBI, we performed a genome-wide transcriptional profile of Mycobacterium tuberculosis (M.TB)–specific antigens-stimulated peripheral blood mononuclear cells (PBMCs) from patients with TB, LTBI individuals and healthy controls (HCs). A total of 209 and 234 differentially expressed genes were detected in TB vs. LTBI and TB vs. HCs, respectively. Nineteen differentially expressed genes with top fold change between TB and the other 2 groups were validated using quantitative real-time PCR (qPCR), and showed 94.7% consistent expression pattern with microarray test. Six genes were selected for further validation in an independent sample set of 230 samples. Expression of the resistin (RETN) and kallikrein 1 (KLK1) genes showed the greatest difference between the TB and LTBI or HC groups (P < 0.0001). Receiver operating characteristic curve (ROC) analysis showed that the areas under the curve (AUC) for RETN and KLK1 were 0.844 (0.783–0.904) and 0.833 (0.769–0.897), respectively, when discriminating TB from LTBI. The combination of these two genes achieved the best discriminative capacity [AUC = 0.916 (0.872–0.961)], with a sensitivity of 71.2% (58.7%–81.7%) and a specificity of 93.6% (85.7%–97.9%). Our results provide a new potentially diagnostic signature for discriminating TB and LTBI and have important implications for better understanding the pathogenesis involved in the transition from latent infection to TB activation.
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spelling pubmed-57625612018-01-18 Genome-wide transcriptional profiling identifies potential signatures in discriminating active tuberculosis from latent infection Pan, Liping Wei, Na Jia, Hongyan Gao, Mengqiu Chen, Xiaoyou Wei, Rongrong Sun, Qi Gu, Shuxiang Du, Boping Xing, Aiying Zhang, Zongde Oncotarget Research Paper To better understand the host immune response involved in the progression from latent tuberculosis infection (LTBI) to active tuberculosis (TB) and identify the potential signatures for discriminating TB from LTBI, we performed a genome-wide transcriptional profile of Mycobacterium tuberculosis (M.TB)–specific antigens-stimulated peripheral blood mononuclear cells (PBMCs) from patients with TB, LTBI individuals and healthy controls (HCs). A total of 209 and 234 differentially expressed genes were detected in TB vs. LTBI and TB vs. HCs, respectively. Nineteen differentially expressed genes with top fold change between TB and the other 2 groups were validated using quantitative real-time PCR (qPCR), and showed 94.7% consistent expression pattern with microarray test. Six genes were selected for further validation in an independent sample set of 230 samples. Expression of the resistin (RETN) and kallikrein 1 (KLK1) genes showed the greatest difference between the TB and LTBI or HC groups (P < 0.0001). Receiver operating characteristic curve (ROC) analysis showed that the areas under the curve (AUC) for RETN and KLK1 were 0.844 (0.783–0.904) and 0.833 (0.769–0.897), respectively, when discriminating TB from LTBI. The combination of these two genes achieved the best discriminative capacity [AUC = 0.916 (0.872–0.961)], with a sensitivity of 71.2% (58.7%–81.7%) and a specificity of 93.6% (85.7%–97.9%). Our results provide a new potentially diagnostic signature for discriminating TB and LTBI and have important implications for better understanding the pathogenesis involved in the transition from latent infection to TB activation. Impact Journals LLC 2017-12-04 /pmc/articles/PMC5762561/ /pubmed/29348876 http://dx.doi.org/10.18632/oncotarget.22889 Text en Copyright: © 2017 Pan et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (http://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Pan, Liping
Wei, Na
Jia, Hongyan
Gao, Mengqiu
Chen, Xiaoyou
Wei, Rongrong
Sun, Qi
Gu, Shuxiang
Du, Boping
Xing, Aiying
Zhang, Zongde
Genome-wide transcriptional profiling identifies potential signatures in discriminating active tuberculosis from latent infection
title Genome-wide transcriptional profiling identifies potential signatures in discriminating active tuberculosis from latent infection
title_full Genome-wide transcriptional profiling identifies potential signatures in discriminating active tuberculosis from latent infection
title_fullStr Genome-wide transcriptional profiling identifies potential signatures in discriminating active tuberculosis from latent infection
title_full_unstemmed Genome-wide transcriptional profiling identifies potential signatures in discriminating active tuberculosis from latent infection
title_short Genome-wide transcriptional profiling identifies potential signatures in discriminating active tuberculosis from latent infection
title_sort genome-wide transcriptional profiling identifies potential signatures in discriminating active tuberculosis from latent infection
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5762561/
https://www.ncbi.nlm.nih.gov/pubmed/29348876
http://dx.doi.org/10.18632/oncotarget.22889
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