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Host blood RNA signatures predict the outcome of tuberculosis treatment - 22/11/17

Doi : 10.1016/j.tube.2017.08.004 
Ethan G. Thompson a, Ying Du a, Stephanus T. Malherbe b, c, Smitha Shankar a, Jackie Braun a, Joe Valvo a, Katharina Ronacher b, c, d, Gerard Tromp b, c, David L. Tabb b, c, David Alland e, Shubhada Shenai e, Laura E. Via f, g, James Warwick h, i, Alan Aderem a, Thomas J. Scriba j, Jill Winter k, Gerhard Walzl b, c, Daniel E. Zak a,

the Catalysis TB–Biomarker Consortium1

  A full list of members and affiliations appears in the Acknowledgments.
Nelita Du Plessis l, m, Andre G. Loxton l, m, Novel N. Chegou l, m, Myungsun Lee n
l Department of Science and Technology, National Research Foundation Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa 
m South African Medical Research Council, Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa 
n International Tuberculosis Research Center, Seoul, South Korea 

a The Center for Infectious Disease Research, Seattle, WA, USA 
b Department of Science and Technology, National Research Foundation Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa 
c South African Medical Research Council, Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa 
d Mater Medical Research Institute, The University of Queensland, Brisbane, Australia 
e Center for Emerging Pathogens, Department of Medicine, Rutgers New Jersey Medical School, Rutgers Biomedical & Health Sciences, Newark, NJ, USA 
f Tuberculosis Research Section, Laboratory of Clinical Infectious Diseases, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA 
g Institute of Infectious Disease and Molecular Medicine, Department of Clinical Laboratory Sciences, University of Cape Town, Cape Town, South Africa 
h Western Cape Academic Positron Emission Tomography–Computed Tomography Centre, Tygerberg Academic Hospital, Cape Town, South Africa 
i Division of Nuclear Medicine, Department of Medical Imaging and Clinical Oncology, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa 
j South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine & Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa 
k Catalysis Foundation for Health, Emeryville, CA, USA 

Corresponding author.

Abstract

Biomarkers for tuberculosis treatment outcome will assist in guiding individualized treatment and evaluation of new therapies. To identify candidate biomarkers, RNA sequencing of whole blood from a well-characterized TB treatment cohort was performed. Application of a validated transcriptional correlate of risk for TB revealed symmetry in host gene expression during progression from latent TB infection to active TB disease and resolution of disease during treatment, including return to control levels after drug therapy. The symmetry was also seen in a TB disease signature, constructed from the TB treatment cohort, that also functioned as a strong correlate of risk. Both signatures identified patients at risk of treatment failure 1–4 weeks after start of therapy. Further mining of the transcriptomes revealed an association between treatment failure and suppressed expression of mitochondrial genes before treatment initiation, leading to development of a novel baseline (pre-treatment) signature of treatment failure. These novel host responses to TB treatment were integrated into a five-gene real-time PCR-based signature that captures the clinically relevant responses to TB treatment and provides a convenient platform for stratifying patients according to their risk of treatment failure. Furthermore, this 5-gene signature is shown to correlate with the pulmonary inflammatory state (as measured by PET-CT) and can complement sputum-based Gene Xpert for patient stratification, providing a rapid and accurate alternative to current methods.

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Keywords : Tuberculosis treatment, Host response, Transcriptome, Biomarkers, Mitochondria


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Vol 107

P. 48-58 - décembre 2017 Retour au numéro
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