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

John D Blischak,Jean-Louis Herrmann,Yoav Gilad,Roland Brosch,Gloria Morizot,Cécile Charlois,Marsha Myrthil,Olivia Chény,Luis B Barreiro,Ludovic Tailleux,Aurélien Dinh,Emmanuel Bergot,Cassandre Von Platen

doi:10.1038/s41598-017-05878-w

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.

Highlights

Tuberculosis (TB) is a major public health issue
We differentiated dendritic cells (DCs) from monocytes isolated from individuals that had recovered from a past episode of active TB, which we refer to as susceptible, and from individuals with confirmed latent TB, which we refer to as putatively resistant
We discovered that the gene expression differences between innate immune cells from resistant and susceptible individuals were present primarily in the non-infected state, that these differentially expressed genes were enriched for nearby SNPs with low p-values in TB susceptibility genome wide association studies (GWAS), and that these gene expression levels could be used to classify individuals based on their susceptibility status

Summary

Introduction

Tuberculosis (TB) is a major public health issue. Worldwide, over a million people die of TB annually, and millions more currently live with the disease[1,2,3]. A third of the world’s population is estimated to be infected with MTB, but most are asymptomatic While these naturally resistant individuals are able to avoid active disease, MTB might persist in a dormant state, known as latent TB6. Due to the highly polygenic architecture, it may be informative to examine differences between susceptible and resistant individuals at a higher level of organization, e.g. gene regulatory networks Using this approach, previous studies have characterized gene expression profiles in innate immune cells isolated from individuals known to be susceptible or resistant to infectious diseases, including those with latent or active TB20 and acute rheumatic fever[21]. We hypothesized that gene expression profiles in innate immune cells may be used to classify individuals with respect to their susceptibility to develop active TB. We discovered that the gene expression differences between innate immune cells from resistant and susceptible individuals were present primarily in the non-infected state, that these differentially expressed genes were enriched for nearby SNPs with low p-values in TB susceptibility GWAS, and that these gene expression levels could be used to classify individuals based on their susceptibility status

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