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

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. There is an urgent need for biomarkers of treatment response to aid treatment time shortening, clinical decision-making, and inform clinical trials. Objectives: To assess the abilities of selected 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 center 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. We assessed their ability to predict sputum Mycobacterium tuberculosis culture status at month-2 post initiation of treatment. Results: The changes in the levels of IL1ra, IL1β, IL6, IP10, MCP-1, and IFNγ were significantly different during treatment. A bio-signature comprising TTP, TNFα, PDGF-BB, IL9, and GCSF best predicted month 2 culture status 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. Among all the study patients, 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.