Prediction of anti-tuberculosis treatment duration based on a 22-gene transcriptomic model

Abstract

BackgroundThe World Health Organization recommends standardised treatment durations for patients with tuberculosis. We identified and validated a host-RNA signature as a biomarker for individualised therapy durations for patients with drug-susceptible (DS)- and multidrug-resistant (MDR)-tuberculosis.MethodsAdult patients with pulmonary tuberculosis were prospectively enrolled into 5 independent cohorts in Germany and Romania. Clinical and microbiological data, and whole-blood for RNA transcriptomic analysis were collected at pre-defined timepoints throughout therapy. Treatment outcomes were ascertained Treatment outcomes were ascertained by TBNET criteria (6-month culture status/one-year follow-up). A whole-blood RNA therapy end model was developed in a multi-step process involving a machine-learning algorithm to identify hypothetical individual end-of-treatment timepoints.ResultsFifty patients with drug-susceptible (DS)-tuberculosis and 30 patients with MDR-tuberculosis were recruited in the German identification cohorts (DS- and MDR-GIC), 28 patients with DS-tuberculosis and 32 patients with MDR-tuberculosis in the German validation cohorts (DS- and MDR-GVC), and 52 patients with MDR-tuberculosis in the Romanian validation cohort (MDR-RVC). A 22-gene RNA model that defined cure-associated end-of-therapy timepoints was derived from the DS- and MDR-GIC data. The model was superior to other published signatures to accurately predict clinical outcomes for patients in the DS-GVC (AUC=0.94 [95%CI:0.9–0.98]) and suggests that cure may be achieved with shorter treatment durations for tuberculosis patients in the MDR-GIC (mean reduction 218.0 days, 34.2%, p<0.001), the MDR-GVC (mean reduction 211.0 days, 32.9%, p<0.001), and the MDR-RVC (mean reduction of 161.0 days, 23.4%, p=0.001).ConclusionBiomarker-guided management may substantially shorten the duration of therapy for many patients with MDR-tuberculosis.

Transcriptional profiles predict treatment outcome in patients with tuberculosis and diabetes at diagnosis and at two weeks after initiation of anti-tuberculosis treatment

“…In this study, we identified peripheral blood transcriptional signatures which predict anti-TB treatment success and failure in TB patients with or without concomitant hyperglycaemia or DM. Previous studies developing biomarker signatures of TB treatment success, recurrence or failure [24][25][26]56 did not include people with DM comorbidity, and we have previously found concomitant DM impairs existing TB diagnosis signature accuracy. 32 Here we showed DM also affects existing TB treatment-response biomarker signatures in the RNA-Seq dataset, suggesting that they should be derived with cohorts including this population.…”

Anti-tuberculosis treatment strategies and drug development: challenges and priorities

“…A five-gene signature that correlates with the pulmonary inflammatory state, as measured by PET–CT, identified patients at risk of treatment failure 1–4 weeks after start of therapy 85 . More recently, a 22-gene transcriptomic model that predicts cure-associated end-of-therapy was defined for patients infected with drug-susceptible and MDR M. tuberculosis strains 86 . Developing rapid and affordable point-of-care tests that quantify these biomarkers and deploying assays and adapted treatment guidelines are the major unmet needs.…”

Clinical standards for drug-susceptible pulmonary TB

“…Biomarkers to individualise the duration of anti-TB therapies are currently under evaluation. 67 The current recommendation for the duration of PTB treatment with the standard 2HRZ(E)/4HR regimen is 6 months. Monitoring to evaluate treatment response in patients with PTB is recommended; patients should have a repeat sputum for smear and culture at Month 2.…”