![Sample our Bioscience journals, sign in here to start your access, Latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5925/TOC-Subject-Sample-2021-Bioscience.jpg"})
Abstract
Introduction
There is active interest in leveraging host immune responses as biomarkers of tuberculosis (TB) disease activity. We had previously evaluated an immunodiagnostic test called the antibody in lymphocyte supernatant (ALS) assay. Here, we aimed to evaluate a panel of inflammatory mediators and associate the responses with the ALS results to identify a biosignature to distinguish TB cases from controls.
Methodology
In this case–control study, adults with TB were compared to controls who were hospitalized for non-infectious conditions. Blood was collected at baseline and after 4 weeks of TB treatment (from TB cases only). Peripheral blood mononuclear cells were isolated and cultured without antigenic stimulation for 72 hours. Inflammatory mediators were measured using the Multiplex cytokine kit and compared between TB cases and controls; among TB cases, responses were compared over time. ALS and inflammatory mediator results were evaluated using generalized discriminant analysis to identify the optimal biosignature to predict TB.
Results
When comparing inflammatory mediators between groups, IL-1ra, IL-1β, and granulocyte macrophage-colony stimulating factor (GM-CSF) were lower in TB cases (P<0.002). Fibroblast growth factor-basic significantly increased from baseline to week-4 (P=0.002). Generalized discriminant analysis yielded a model with IL-2, tumor necrosis factor-alpha, vascular endothelial growth factor, and ALS, providing a sensitivity of 82.2% and specificity of 76.2%.
Conclusion
Our results suggest that IL-1ra, IL-1β, and GM-CSF might be used as diagnostic biomarkers to distinguish between TB cases and non-TB cases. We could not identify a group of mediators that outperformed the diagnostic accuracy of the ALS alone.
Acknowledgments
We are grateful to the study participants and research staff who helped to make these important findings possible. NIH D43 TW008270 and D43 TW006578 NIH/Fogarty International Center Global Infectious Disease Research Training Program at UVA supported this work. MS is supported by COSTECH – Commission of Science and Technology, Tan-zania and GIDRT fund through Centre of Global Health in UVA. NIH/NIAID K23-AI097197 supports TAT.
Author contributions
All authors contributed to data analysis, drafting or revising the article, gave final approval of the version to be published, and agree to be accountable for all aspects of the work.
Disclosure
The authors report no conflicts of interest in this work.