Use of a Contained Mycobacterium tuberculosis Mouse Infection Model to Predict Active Disease and Containment in Humans

Abstract

Previous studies have identified whole-blood transcriptional risk and disease signatures for tuberculosis; however, several lines of evidence suggest that these signatures primarily reflect bacterial burden, which increases before symptomatic disease. We found that the peripheral blood transcriptome of mice with contained Mycobacterium tuberculosis infection (CMTI) has striking similarities to that of humans with active tuberculosis and that a signature derived from these mice predicts human disease with accuracy comparable to that of signatures derived directly from humans. A set of genes associated with immune defense are up-regulated in mice with CMTI but not in humans with active tuberculosis, suggesting that their up-regulation is associated with bacterial containment. A signature comprising these genes predicts both protection from tuberculosis disease and successful treatment at early time points where current signatures are not predictive. These results suggest that detailed study of the CMTI model may enable identification of biomarkers for human tuberculosis.

Keywords: Tuberculosis; blood transcription; cross-species; signature of risk.

Figure 1.

Establishment of mouse contained infection leads to alterations in blood transcriptional state. A–C, Volcano plots of differentially expressed genes comparing transcriptional states after contained Mycobacterium tuberculosis infection (CMTI) initiation (days 10 [A], 28 [B], and 42 [C]) to those before CMTI initiation (day 0). Abbreviation: FDR, false discovery rate. D, Heat map of significant differential expression changes shown in A–C. Genes showing high expression at days 28–42 and consistently detected in multiple human data sets are indicated by the “consistently detected” annotation bar above the heat map.

Figure 2.

The contained Mycobacterium tuberculosis infection disease score (CMTI-DS) signature predicts human tuberculosis outcomes. A-C, Receiver operating characteristic (ROC) curves for the CMTI-DS and Adolescent Cohort Study–correlate of risk (ACS-CoR) signatures discriminating active from latent tuberculosis in the cohorts reported by Berry et al [1] (A) and Kaforou et al [2] (B, C). Abbreviation: HIV, human immunodeficiency virus. D, ROC curves for the CMTI-DS and ACS-CoR signatures tuberculosis progressors from nonprogressors in the ACS and CG6 cohorts Areas under the ROC curve and accompanying 95% confidence intervals are shown.

Figure 3.

Contained Mycobacterium tuberculosis infection (CMTI) containment signature genes. Heat map shows hierarchical clustering of log₂-transformed fold changes for contained infection signature genes (columns) for each comparison (rows). Positive fold changes are shown in red, and negative changes in blue. Genes are annotated as “concordant,” “opposite,” or “ambiguous,” based on the consistency of differential expression between CMTI and active versus latent human tuberculosis.

Figure 4.

The contained Mycobacterium tuberculosis infection (CMTI) containment (CMTI-CT) signature is increased in nonprogressors in a time-independent manner. A, Receiver operating characteristic (ROC) curves for the CMTI-CT signature discriminating tuberculosis nonprogressors from tuberculosis progressors ≥18 months from tuberculosis diagnosis in the Adolescent Cohort Study. ROC curves were calculated assuming tuberculosis nonprogressor scores were greater than those of progressors for CMTI-CT, and tuberculosis progressor scores were greater than those of nonprogressors for ACS–correlate of risk (CoR). B, C, Signature scores by time to tuberculosis for ACS tuberculosis progressors for each CMTI-CT and ACS-CoR. Points connected by lines represent multiple samples from the same individual progressor, while individual points represent progressors from whom only a single sample was collected. D, ROC curves for the CMTI-CT and ACS-CoR signature discriminating treatment success (definite cures) from failures (not cured) at the time of tuberculosis diagnosis, before treatment initiation in the Catalysis tuberculosis treatment cohort.