QuantiFERON Supernatant-based Host Biomarkers Predicting Progression to Active Tuberculosis Disease Among Household Contacts of Tuberculosis Patients

Background. The positive predictive value of tuberculin skin test and current generation interferon gamma release assays are very low leading to high numbers needed to treat. Therefore, it is critical to identify new biomarkers with high predictive accuracy to identify individuals bearing high risk of progression to active tuberculosis (TB).Methods. We used stored QuantiFERON supernatants from 14 household contacts of index TB patients who developed incident active TB during a 2-year follow-up and 20 age and sex-matched non-progressors. The supernatants were tested for an expanded panel of 45 cytokines, chemokines, and growth factors using the Luminex Multiplex Array kit.Results. We found significant differences in the levels of TB-antigen induced production of several analytes between progressors and non-progressors. Dominance analysis identified 15 key predictive biomarkers based on relative percentage importance. Principal component analysis revealed that these biomarkers could robustly distinguish between the 2 groups. Receiver operating characteristic analysis identified interferon-gamma inducible protein (IP)-10, chemokine ligand (CCL)19, interferon (IFN)-gamma, interleukin (IL)-1ra, CCL3, and granulocyte-macrophage colony-stimulating factor (GM-CSF) as the most promising predictive markers, with area under the curve (AUC) >= 90. IP-10/CCL19 ratio exhibited maximum sensitivity and specificity (100%) for predicting progression. Through Classification and Regression Tree analysis, a cutoff of 0.24 for IP-10/ CCL19 ratio was found to be ideal for predicting short-term risk of progression to TB disease with a positive predictive value of 100 (95% confidence interval [CI] 85.8-100).Conclusions. The biomarkers identified in this study will pave way for the development of a more accurate test that can identify individuals at high risk for immediate progression to TB disease for targeted intervention.

Automated summary

The study identified novel biomarkers with high predictive accuracy for progression to active tuberculosis, paving the way for the development of a more targeted intervention.