This analysis demonstrates blood transcriptomic signatures predict poor outcomes in adults with pulmonary TB, suggesting new biomarker-guided treatment strategies.
Background Non-sputum biomarkers to monitor tuberculosis treatment and predict poor outcomes are lacking. We evaluated host-blood transcriptomic signatures for treatment monitoring and prognosis (death, treatment failure, recurrence) in adults with pulmonary tuberculosis. Methods Adults with culture-confirmed, drug-susceptible pulmonary tuberculosis were enrolled at five Brazilian sites. Whole-blood PAXgene samples were collected at baseline, month 2 (M2), and end of treatment (EoT). Treatment failure was defined as sputum culture positivity at month 5 or later. Participants were followed for 24 months from treatment initiation for clinical or microbiological tuberculosis recurrence. Unfavourable outcomes were matched ∼1:3 to recurrence-free cure. Twenty-two published blood transcriptomic signatures were measured by microfluidic RT-qPCR and benchmarked against the WHO Target Product Profile (TPP) criteria. Main results We matched 263 participants with recurrence-free cure to 33 with treatment failure, 24 who died (tuberculosis/unknown cause), and 9 with recurrence. Signature scores generally declined from baseline to EoT. Multiple signatures measured at baseline and M2 predicted recurrence (AUC range 0.71-0.91), with waning performance when measured at EoT (AUC range 0.42-0.89). Against the WHO TPP, 2/22 signatures met minimum criteria at baseline, 13/22 at M2, and none at EoT. Prediction of treatment failure was poor across timepoints (AUC < 0.70). In contrast, several signatures measured at baseline predicted death during treatment or follow-up (AUC ≥ 0.80). Conclusions Blood transcriptomic signatures tracked treatment response and predicted recurrence and death, meeting WHO TPP benchmarks at baseline and M2. These findings support prospective, biomarker-guided trials to individualise tuberculosis therapy—shortening regimens for early responders and intensifying care for high-risk patients.
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Mendelsohn et al. (2026) studied this question.
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