Immunometabolic signatures predict risk of progression to active tuberculosis and disease outcome

Duffy, F. J. et al. (2019) Immunometabolic signatures predict risk of progression to active tuberculosis and disease outcome. Frontiers in Immunology, 10, 527. (doi: 10.3389/fimmu.2019.00527) (PMID:30967866) (PMCID:PMC6440524)

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There remains a pressing need for biomarkers that can predict who will progress to active tuberculosis (TB) after exposure to Mycobacterium tuberculosis (MTB) bacterium. By analyzing cohorts of household contacts of TB index cases (HHCs) and a stringent non-human primate (NHP) challenge model, we evaluated whether integration of blood transcriptional profiling with serum metabolomic profiling can provide new understanding of disease processes and enable improved prediction of TB progression. Compared to either alone, the combined application of pre-existing transcriptome- and metabolome-based signatures more accurately predicted TB progression in the HHC cohorts and more accurately predicted disease severity in the NHPs. Pathway and data-driven correlation analyses of the integrated transcriptional and metabolomic datasets further identified novel immunometabolomic signatures significantly associated with TB progression in HHCs and NHPs, implicating cortisol, tryptophan, glutathione, and tRNA acylation networks. These results demonstrate the power of multi-omics analysis to provide new insights into complex disease processes.

Item Type:Articles
Additional Information:This work was supported by the Bill & Melinda Gates Foundation (BMGF) Grand Challenges in Global Health (GC6-74 grant 37772, OPP1055806 and OPP1087783 in conjunction with AERAS). This work was also supported by a Strategic Health Innovation Partnership grant from the South African Medical Research Council and Department of Science and Technology/South African Tuberculosis Bioinformatics Initiative. Additional support was provided by the European Union FP7 (ADITEC, 280873 and TBVAC2020, 643381) and the National Institutes of Health [U19 AI106761 and U19 AI135976]. FD was supported by the NCDIR (National Institutes of Health [P41 GM109824]). DT and GT were supported by South African Medical Research Council SHIP funding for the South African Tuberculosis Bioinformatics Initiative to GW.
Glasgow Author(s) Enlighten ID:Crampin, Professor Mia
Authors: Duffy, F. J., Weiner, J., Hansen, S., Tabb, D. L., Suliman, S., Thompson, E., Maertzdorf, J., Shankar, S., Tromp, G., Parida, S., Dover, D., Axthelm, M. K., Sutherland, J. S., Dockrell, H. M., Ottenhoff, T. H. M., Scriba, T. J., Picker, L. J., Walzl, G., Kaufmann, S. H. E., Zak, D. E., The GC6-74 Consortium, ., and ,
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Public Health
Journal Name:Frontiers in Immunology
Publisher:Frontiers Media
ISSN (Online):1664-3224
Copyright Holders:Copyright © Duffy, Weiner, Hansen, Tabb, Suliman, Thompson, Maertzdorf, Shankar, Tromp, Parida, Dover, Axthelm, Sutherland, Dockrell, Ottenhoff, Scriba, Picker, Walzl, Kaufmann, Zak and The GC6-74 Consortium.
First Published:First published in Frontiers in Immunology 10: 527
Publisher Policy:Reproduced under a Creative Commons License

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