Cargando…

Transcriptional Profiling of Human Peripheral Blood Mononuclear Cells Identifies Diagnostic Biomarkers That Distinguish Active and Latent Tuberculosis

Mycobacterium tuberculosis (M. tuberculosis) infection in humans can cause active disease or latent infection. However, the factors contributing to the maintenance of latent infection vs. disease progression are poorly understood. In this study, we used a genome-wide RNA sequencing (RNA-seq) approac...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Sen, He, Lei, Wu, Jing, Zhou, Zumo, Gao, Yan, Chen, Jiazhen, Shao, Lingyun, Zhang, Ying, Zhang, Wenhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6930242/
https://www.ncbi.nlm.nih.gov/pubmed/31921195
http://dx.doi.org/10.3389/fimmu.2019.02948
_version_ 1783482854315917312
author Wang, Sen
He, Lei
Wu, Jing
Zhou, Zumo
Gao, Yan
Chen, Jiazhen
Shao, Lingyun
Zhang, Ying
Zhang, Wenhong
author_facet Wang, Sen
He, Lei
Wu, Jing
Zhou, Zumo
Gao, Yan
Chen, Jiazhen
Shao, Lingyun
Zhang, Ying
Zhang, Wenhong
author_sort Wang, Sen
collection PubMed
description Mycobacterium tuberculosis (M. tuberculosis) infection in humans can cause active disease or latent infection. However, the factors contributing to the maintenance of latent infection vs. disease progression are poorly understood. In this study, we used a genome-wide RNA sequencing (RNA-seq) approach to identify host factors associated with M. tuberculosis infection status and a novel gene signature that can distinguish active disease from latent infection. By RNA-seq, we characterized transcriptional differences in purified protein derivative (PPD)-stimulated peripheral blood mononuclear cells (PBMCs) among three groups: patients with active tuberculosis (ATB), individuals with latent TB infection (LTBI), and TB-uninfected controls (CON). A total of 401 differentially expressed genes enabled grouping of individuals into three clusters. A validation study by quantitative real-time PCR (qRT-PCR) confirmed the differential expression of TNFRSF10C, IFNG, PGM5, EBF3, and A2ML1 between the ATB and LTBI groups. Additional clinical validation was performed to evaluate the diagnostic performance of these five biomarkers using 130 subjects. The 3-gene signature set of TNFRSF10C, EBF3, and A2ML1 enabled correct classification of 91.5% of individuals, with a high sensitivity of 86.2% and specificity of 94.9%. Diagnostic performance of the 3-gene signature set was validated using a clinical cohort of 147 subjects with suspected ATB. The sensitivity and specificity of the 3-gene set for ATB were 82.4 and 92.4%, respectively. In conclusion, we detected distinct gene expression patterns in PBMCs stimulated by PPD depending on the status of M. tuberculosis infection. Furthermore, we identified a 3-gene signature set that could distinguish ATB from LTBI, which may facilitate rapid diagnosis and treatment for more effective disease control.
format Online
Article
Text
id pubmed-6930242
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-69302422020-01-09 Transcriptional Profiling of Human Peripheral Blood Mononuclear Cells Identifies Diagnostic Biomarkers That Distinguish Active and Latent Tuberculosis Wang, Sen He, Lei Wu, Jing Zhou, Zumo Gao, Yan Chen, Jiazhen Shao, Lingyun Zhang, Ying Zhang, Wenhong Front Immunol Immunology Mycobacterium tuberculosis (M. tuberculosis) infection in humans can cause active disease or latent infection. However, the factors contributing to the maintenance of latent infection vs. disease progression are poorly understood. In this study, we used a genome-wide RNA sequencing (RNA-seq) approach to identify host factors associated with M. tuberculosis infection status and a novel gene signature that can distinguish active disease from latent infection. By RNA-seq, we characterized transcriptional differences in purified protein derivative (PPD)-stimulated peripheral blood mononuclear cells (PBMCs) among three groups: patients with active tuberculosis (ATB), individuals with latent TB infection (LTBI), and TB-uninfected controls (CON). A total of 401 differentially expressed genes enabled grouping of individuals into three clusters. A validation study by quantitative real-time PCR (qRT-PCR) confirmed the differential expression of TNFRSF10C, IFNG, PGM5, EBF3, and A2ML1 between the ATB and LTBI groups. Additional clinical validation was performed to evaluate the diagnostic performance of these five biomarkers using 130 subjects. The 3-gene signature set of TNFRSF10C, EBF3, and A2ML1 enabled correct classification of 91.5% of individuals, with a high sensitivity of 86.2% and specificity of 94.9%. Diagnostic performance of the 3-gene signature set was validated using a clinical cohort of 147 subjects with suspected ATB. The sensitivity and specificity of the 3-gene set for ATB were 82.4 and 92.4%, respectively. In conclusion, we detected distinct gene expression patterns in PBMCs stimulated by PPD depending on the status of M. tuberculosis infection. Furthermore, we identified a 3-gene signature set that could distinguish ATB from LTBI, which may facilitate rapid diagnosis and treatment for more effective disease control. Frontiers Media S.A. 2019-12-18 /pmc/articles/PMC6930242/ /pubmed/31921195 http://dx.doi.org/10.3389/fimmu.2019.02948 Text en Copyright © 2019 Wang, He, Wu, Zhou, Gao, Chen, Shao, Zhang and Zhang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Wang, Sen
He, Lei
Wu, Jing
Zhou, Zumo
Gao, Yan
Chen, Jiazhen
Shao, Lingyun
Zhang, Ying
Zhang, Wenhong
Transcriptional Profiling of Human Peripheral Blood Mononuclear Cells Identifies Diagnostic Biomarkers That Distinguish Active and Latent Tuberculosis
title Transcriptional Profiling of Human Peripheral Blood Mononuclear Cells Identifies Diagnostic Biomarkers That Distinguish Active and Latent Tuberculosis
title_full Transcriptional Profiling of Human Peripheral Blood Mononuclear Cells Identifies Diagnostic Biomarkers That Distinguish Active and Latent Tuberculosis
title_fullStr Transcriptional Profiling of Human Peripheral Blood Mononuclear Cells Identifies Diagnostic Biomarkers That Distinguish Active and Latent Tuberculosis
title_full_unstemmed Transcriptional Profiling of Human Peripheral Blood Mononuclear Cells Identifies Diagnostic Biomarkers That Distinguish Active and Latent Tuberculosis
title_short Transcriptional Profiling of Human Peripheral Blood Mononuclear Cells Identifies Diagnostic Biomarkers That Distinguish Active and Latent Tuberculosis
title_sort transcriptional profiling of human peripheral blood mononuclear cells identifies diagnostic biomarkers that distinguish active and latent tuberculosis
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6930242/
https://www.ncbi.nlm.nih.gov/pubmed/31921195
http://dx.doi.org/10.3389/fimmu.2019.02948
work_keys_str_mv AT wangsen transcriptionalprofilingofhumanperipheralbloodmononuclearcellsidentifiesdiagnosticbiomarkersthatdistinguishactiveandlatenttuberculosis
AT helei transcriptionalprofilingofhumanperipheralbloodmononuclearcellsidentifiesdiagnosticbiomarkersthatdistinguishactiveandlatenttuberculosis
AT wujing transcriptionalprofilingofhumanperipheralbloodmononuclearcellsidentifiesdiagnosticbiomarkersthatdistinguishactiveandlatenttuberculosis
AT zhouzumo transcriptionalprofilingofhumanperipheralbloodmononuclearcellsidentifiesdiagnosticbiomarkersthatdistinguishactiveandlatenttuberculosis
AT gaoyan transcriptionalprofilingofhumanperipheralbloodmononuclearcellsidentifiesdiagnosticbiomarkersthatdistinguishactiveandlatenttuberculosis
AT chenjiazhen transcriptionalprofilingofhumanperipheralbloodmononuclearcellsidentifiesdiagnosticbiomarkersthatdistinguishactiveandlatenttuberculosis
AT shaolingyun transcriptionalprofilingofhumanperipheralbloodmononuclearcellsidentifiesdiagnosticbiomarkersthatdistinguishactiveandlatenttuberculosis
AT zhangying transcriptionalprofilingofhumanperipheralbloodmononuclearcellsidentifiesdiagnosticbiomarkersthatdistinguishactiveandlatenttuberculosis
AT zhangwenhong transcriptionalprofilingofhumanperipheralbloodmononuclearcellsidentifiesdiagnosticbiomarkersthatdistinguishactiveandlatenttuberculosis