A multi-cohort study of the immune factors associated with M. tuberculosis infection outcomes

Abstract

Most infections with Mycobacterium tuberculosis (Mtb) manifest as a clinically asymptomatic, contained state, known as latent tuberculosis infection, that affects approximately one-quarter of the global population. Although fewer than one in ten individuals eventually progress to active disease, tuberculosis is a leading cause of death from infectious disease worldwide. Despite intense efforts, immune factors that influence the infection outcomes remain poorly defined. Here we used integrated analyses of multiple cohorts to identify stage-specific host responses to Mtb infection. First, using high-dimensional mass cytometry analyses and functional assays of a cohort of South African adolescents, we show that latent tuberculosis is associated with enhanced cytotoxic responses, which are mostly mediated by CD16 (also known as FcγRIIIa) and natural killer cells, and continuous inflammation coupled with immune deviations in both T and B cell compartments. Next, using cell-type deconvolution of transcriptomic data from several cohorts of different ages, genetic backgrounds, geographical locations and infection stages, we show that although deviations in peripheral B and T cell compartments generally start at latency, they are heterogeneous across cohorts. However, an increase in the abundance of circulating natural killer cells in tuberculosis latency, with a corresponding decrease during active disease and a return to baseline levels upon clinical cure are features that are common to all cohorts. Furthermore, by analysing three longitudinal cohorts, we find that changes in peripheral levels of natural killer cells can inform disease progression and treatment responses, and inversely correlate with the inflammatory state of the lungs of patients with active tuberculosis. Together, our findings offer crucial insights into the underlying pathophysiology of tuberculosis latency, and identify factors that may influence infection outcomes.

Blood RNA Signatures Predict Recent Tuberculosis Exposure in Mice, Macaques and Humans

“…Likewise, no other cell types estimated by the 'immunoStates' signature matrix showed significant differences over time in these cohorts (P > 0.05, linear mixed model, data not shown). This result with CD4+ α/β T cells and NK cells is consistent with the conclusion that the RNA signature of time since TB exposure is independent from the RNA signature of prospective TB risk, since both T cells and NK cells are known to decrease in circulation in active TB disease (25,41).…”

“…Building on this prior work, we assess RNA expression as a potential biomarker of recent exposure or infection with M.tb. Using our murine data and recently published studies in cynomolgus macaques and humans (21,22,24,25), we show for the first time that RNA expression predicts recent infection/exposure in all three species. Moreover, in both macaques and humans, these RNA signatures of recent infection/exposure are independent of the recently identified signatures of individual prospective TB disease risk.…”

“…This would synchronize a human study cohort to the time of an initial systemic T cell response to M.tb. To test this hypothesis we accessed public data from South African adolescents who acquired latent M.tb infection during longitudinal blood sampling every 6 months (25). We found that Regularized Logistic Regression was unable to predict the first time point of known IGRA conversion from 6 months post-first known IGRA conversion (0.54 AUC, 95% CI: 0.27-0.82, P = 0.64 on test set; Figure 3A).…”

“…Cell-type deconvolution algorithms have recently been used with genome-wide RNA expression data to help identify changes in immune cell proportions in the blood that are associated with TB disease, prospective TB disease risk and treatment success (25,40). To identify immune cell populations that are associated with time since TB exposure in the GC6-74 study, we used the leukocyte expression signature matrix 'immunoStates' and linear regression to infer leukocyte proportions for each subject's sample (40).…”

Persistent DNA Hyper-methylation Dampens Host Anti-Mycobacterial Immunity

“…1c). A recent report demonstrated that TB-exposed individuals who did not progress to active disease had increased abundance of cytotoxic NK cells 20 . Only household contacts that remained asymptomatic and did not progress to active TB disease for 12 months were included in this analysis and similar to the recent report, household contacts in this cohort that did not progress had increased IFN-γ, T-bet and perforin production from NK cells compared to individuals with TB ( Fig 1b; Supplemental Fig.…”