Integration of immunomonitoring assays with PET/CT in TB patients identifies on-treatment biomarkers
Journal:
bioRxiv
Published Date:
May 14, 2026
Abstract
Tuberculosis (TB) continues to pose a significant global public health challenge with substantial morbidity and mortality. Current TB biomarkers lack sufficient resolution to inform treatment response and patient stratification. We previously demonstrated that TruCulture whole blood stimulation distinguishes asymptomatic from active TB. Here, we extend this approach to longitudinally monitor treatment responses in Predict-TB trial participants before, during, and after 6 months of antibiotic therapy. We stimulated whole blood from TB patients (n=40) using TruCulture under four conditions (Null, Mtb-Ag, LPS, and IL-1{beta}) at baseline (week 0), during treatment (weeks 16 and 24), and one-year follow-up post-treatment (week 72). 20/25 measured cytokines exhibited significant changes throughout treatment, with several continuing to evolve during post-therapy follow-up. Machine learning based analysis identified Mtb-Ag-induced IL-1RA and LPS-induced NLRP3 as the best protein and transcriptional biomarkers for treatment response. Combining these results with lung lesion assessed by PET/CT, we showed direct disease relevance for these blood-based biomarkers. The identified biomarker profiles hold promise for improving TB patient care through early prediction of treatment responses and real-time therapy monitoring.
