Format

Send to

Choose Destination
Sci Rep. 2017 Jul 18;7(1):5702. doi: 10.1038/s41598-017-05878-w.

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

Author information

1
Department of Human Genetics, University of Chicago, Chicago, Illinois, USA.
2
Committee on Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, Illinois, USA.
3
Integrated Mycobacterial Pathogenomics, Institut Pasteur, Paris, France. tailleux@pasteur.fr.
4
Centre de Lutte Antituberculeuse de Paris, DASES Mairie de Paris, 75013, Paris, France.
5
Service de pneumologie et oncologie thoracique, CHU Côte de Nacre, 14033, Caen, France.
6
Maladies Infectieuses, AP-HP, Hôpital Universitaire Raymond-Poincaré, Garches, 92380, France.
7
Clinical Investigation & Access Biological Resources (ICAReB), Institut Pasteur, Paris, France.
8
Clinical Core, Centre for Translational Science, Institut Pasteur, Paris, France.
9
INSERM, U1173, UFR Simone Veil, Université de Versailles Saint Quentin, Saint Quentin en Yvelines, France.
10
APHP, Groupe Hospitalo-Universitaire Paris Île-de-France Ouest, Garches et Boulogne-Billancourt, France.
11
Integrated Mycobacterial Pathogenomics, Institut Pasteur, Paris, France.
12
Department of Genetics, CHU Sainte-Justine Research Center, Montreal, Québec, Canada. luis.barreiro@umontreal.ca.
13
Department of Pediatrics, University of Montreal, Montreal, Québec, Canada. luis.barreiro@umontreal.ca.
14
Department of Human Genetics, University of Chicago, Chicago, Illinois, USA. gilad@uchicago.edu.
15
Department of Medicine, University of Chicago, Chicago, Illinois, USA. gilad@uchicago.edu.

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.

Supplemental Content

Full text links

Icon for Nature Publishing Group Icon for PubMed Central
Loading ...
Support Center