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

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, and Yoav Gilad

Subjects
Medicine, Science
Abstract

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.

Published
2017
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2. Predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells

Author

Roland Brosch, Aurélien Dinh, Luis B. Barreiro, Yoav Gilad, John D. Blischak, Cécile Charlois, Cassandre Von Platen, Olivia Chény, Ludovic Tailleux, Jean-Louis Herrmann, Gloria Morizot, Marsha Myrthil, E. Bergot, University of Chicago, Pathogénomique mycobactérienne intégrée - Integrated Mycobacterial Pathogenomics, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Direction de l'Action Sociale de l'Enfance et de la Santé (DASES), Mairie de Paris, Hôpital Côte de Nacre [CHU Caen], CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN), Service des Maladies Infectieuses et Tropicales [CHU Raymond Poincaré], Hôpital Raymond Poincaré [AP-HP], Investigation Clinique et d’Accès aux Ressources Biologiques (Plate-forme) - Clinical Investigation and Access to BioResources (ICAReB), Institut Pasteur [Paris], Centre de Recherche Translationnelle - Center for Translational Science (CRT), Infection et inflammation (2I), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), CHU Sainte Justine [Montréal], Université de Montréal (UdeM), This study was funded by National Institutes of Health (NIH) Grant AI087658 to Y.G. and L.T. J.D.B. was supported by NIH Grant T32GM007197., Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Institut Pasteur [Paris] (IP), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
0301 basic medicine, Male, Tuberculosis, Science, Population, [SDV.MHEP.PSR]Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, Article, Mycobacterium tuberculosis, 03 medical and health sciences, 0302 clinical medicine, Latent Tuberculosis, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Gene expression, [SDV.BC.IC]Life Sciences [q-bio]/Cellular Biology/Cell Behavior [q-bio.CB], medicine, Humans, Genetic Predisposition to Disease, education, Pathogen, 030304 developmental biology, 0303 health sciences, education.field_of_study, Multidisciplinary, biology, business.industry, Gene Expression Profiling, Dendritic Cells, medicine.disease, biology.organism_classification, [SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology, 3. Good health, Gene expression profiling, 030104 developmental biology, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, Infectious disease (medical specialty), Immunology, Cohort, Medicine, France, business, 030217 neurology & neurosurgery
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.

Published
2017

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