Predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells

Abstract Tuberculosis (TB) is a deadly infectious disease, which kills millions of people every year. The causative pathogen, Mycobacterium tuberculosis (MTB), is estimated to have infected up to a third of the world’s population; however, only approximately 10% of infected healthy individuals progr...

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Autores principales:	John D. Blischak, Ludovic Tailleux, Marsha Myrthil, Cécile Charlois, Emmanuel Bergot, Aurélien Dinh, Gloria Morizot, Olivia Chény, Cassandre Von Platen, Jean-Louis Herrmann, Roland Brosch, Luis B. Barreiro, Yoav Gilad
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ffefa45ee3b3462d9dbdbe1fa3f7f223
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spelling	oai:doaj.org-article:ffefa45ee3b3462d9dbdbe1fa3f7f2232021-12-02T12:31:48ZPredicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells10.1038/s41598-017-05878-w2045-2322https://doaj.org/article/ffefa45ee3b3462d9dbdbe1fa3f7f2232017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-05878-whttps://doaj.org/toc/2045-2322Abstract Tuberculosis (TB) is a deadly infectious disease, which kills millions of people every year. The causative pathogen, Mycobacterium tuberculosis (MTB), is estimated to have infected up to a third of the world’s population; however, only approximately 10% of infected healthy individuals progress to active TB. Despite evidence for heritability, it is not currently possible to predict who may develop TB. To explore approaches to classify susceptibility to TB, we infected with MTB dendritic cells (DCs) from putatively resistant individuals diagnosed with latent TB, and from susceptible individuals that had recovered from active TB. We measured gene expression levels in infected and non-infected cells and found hundreds of differentially expressed genes between susceptible and resistant individuals in the non-infected cells. We further found that genetic polymorphisms nearby the differentially expressed genes between susceptible and resistant individuals are more likely to be associated with TB susceptibility in published GWAS data. Lastly, we trained a classifier based on the gene expression levels in the non-infected cells, and demonstrated reasonable performance on our data and an independent data set. Overall, our promising results from this small study suggest that training a classifier on a larger cohort may enable us to accurately predict TB susceptibility.John D. BlischakLudovic TailleuxMarsha MyrthilCécile CharloisEmmanuel BergotAurélien DinhGloria MorizotOlivia ChényCassandre Von PlatenJean-Louis HerrmannRoland BroschLuis B. BarreiroYoav GiladNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q John D. Blischak Ludovic Tailleux Marsha Myrthil Cécile Charlois Emmanuel Bergot Aurélien Dinh Gloria Morizot Olivia Chény Cassandre Von Platen Jean-Louis Herrmann Roland Brosch Luis B. Barreiro Yoav Gilad Predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells
description	Abstract Tuberculosis (TB) is a deadly infectious disease, which kills millions of people every year. The causative pathogen, Mycobacterium tuberculosis (MTB), is estimated to have infected up to a third of the world’s population; however, only approximately 10% of infected healthy individuals progress to active TB. Despite evidence for heritability, it is not currently possible to predict who may develop TB. To explore approaches to classify susceptibility to TB, we infected with MTB dendritic cells (DCs) from putatively resistant individuals diagnosed with latent TB, and from susceptible individuals that had recovered from active TB. We measured gene expression levels in infected and non-infected cells and found hundreds of differentially expressed genes between susceptible and resistant individuals in the non-infected cells. We further found that genetic polymorphisms nearby the differentially expressed genes between susceptible and resistant individuals are more likely to be associated with TB susceptibility in published GWAS data. Lastly, we trained a classifier based on the gene expression levels in the non-infected cells, and demonstrated reasonable performance on our data and an independent data set. Overall, our promising results from this small study suggest that training a classifier on a larger cohort may enable us to accurately predict TB susceptibility.
format	article
author	John D. Blischak Ludovic Tailleux Marsha Myrthil Cécile Charlois Emmanuel Bergot Aurélien Dinh Gloria Morizot Olivia Chény Cassandre Von Platen Jean-Louis Herrmann Roland Brosch Luis B. Barreiro Yoav Gilad
author_facet	John D. Blischak Ludovic Tailleux Marsha Myrthil Cécile Charlois Emmanuel Bergot Aurélien Dinh Gloria Morizot Olivia Chény Cassandre Von Platen Jean-Louis Herrmann Roland Brosch Luis B. Barreiro Yoav Gilad
author_sort	John D. Blischak
title	Predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells
title_short	Predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells
title_full	Predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells
title_fullStr	Predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells
title_full_unstemmed	Predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells
title_sort	predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/ffefa45ee3b3462d9dbdbe1fa3f7f223
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Predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells

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