Published in

American Association of Immunologists, The Journal of Immunology, 12(197), p. 4817-4828, 2016

DOI: 10.4049/jimmunol.1601138

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Early Whole Blood Transcriptional Signatures Are Associated with Severity of Lung Inflammation in Cynomolgus Macaques with Mycobacterium tuberculosis Infection

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract Whole blood transcriptional profiling offers great diagnostic and prognostic potential. Although studies identified signatures for pulmonary tuberculosis (TB) and transcripts that predict the risk for developing active TB in humans, the early transcriptional changes immediately following Mycobacterium tuberculosis infection have not been evaluated. We evaluated the gene expression changes in the cynomolgus macaque model of TB, which recapitulates all clinical aspects of human M. tuberculosis infection, using a human microarray and analytics platform. We performed genome-wide blood transcriptional analysis on 38 macaques at 11 postinfection time points during the first 6 mo of M. tuberculosis infection. Of 6371 differentially expressed transcripts between preinfection and postinfection, the greatest change in transcriptional activity occurred 20–56 d postinfection, during which fluctuation of innate and adaptive immune response–related transcripts was observed. Modest transcriptional differences between active TB and latent infection were observed over the time course with substantial overlap. The pattern of module activity previously published for human active TB was similar in macaques with active disease. Blood transcript activity was highly correlated with lung inflammation (lung [18F]fluorodeoxyglucose [FDG] avidity) measured by positron emission tomography and computed tomography at early time points postinfection. The differential signatures between animals with high and low lung FDG were stronger than between clinical outcomes. Analysis of preinfection signatures of macaques revealed that IFN signatures could influence eventual clinical outcomes and lung FDG avidity, even before infection. Our data support that transcriptional changes in the macaque model are translatable to human M. tuberculosis infection and offer important insights into early events of M. tuberculosis infection.