Serum biomarkers for monitoring response to tuberculosis treatment: an assessment of the effect of different covariates among slow and fast treatment responders

Abstract

Introduction The long duration of tuberculosis treatment, as well as the 2-year post-treatment follow-up period often required for predicting relapse, present a hindrance to drug development and treatment monitoring efforts. Therefore, there is need for treatment response biomarkers to inform treatment time shortening, clinical decision-making, and inform clinical trials. Objectives To assess the abilities of serum host biomarkers to predict treatment response among active PTB patients. Methods Active pulmonary TB patients (n = 53) as confirmed by sputum MGIT culture were enrolled at a TB treatment centre in Kampala, Uganda. We evaluated concentrations of 27 serum host biomarkers at baseline, month 2, and month 6 following the initiation of anti-tuberculosis treatment using the luminex platform for their ability to predict sputum culture status at month-2 post treatment initiation. Results There were significant differences in concentrations of IL1ra, IL1β, IL6, IP10, MCP-1, and IFNγ during treatment. A bio-signature comprising TTP, TNFα, PDGF-BB, IL9, and GCSF best predicted month 2 culture conversion with sensitivity and specificity of 82% (95% CI; 66 -92% and 57 -96% respectively). Slow anti-TB treatment responders had higher pro-inflammatory marker levels during treatment. The strongest correlation was observed between VEGF and IL12p70 (0.94), IL17A and basic FGF (0.92), basic FGF, and IL2 (0.88), and IL10 with IL17A (0.87). Conclusion We identified host biomarkers that predicted early response to PTB treatment, which may be valuable in future clinical trials and treatment monitoring. Similarly, strong correlations between biomarkers provide options for biomarkers substitutions during the development of treatment response monitoring tools or point of care tests.