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.
Keywords:Cytokines; biomarkers; pulmonary tuberculosis; serum; treatment response.

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乐备实（上海优宁维生物科技股份有限公司旗下全资子公司），是国内专注于提供高质量蛋白检测以及组学分析服务的实验服务专家，自2018年成立以来，乐备实不断寻求突破，公司的服务技术平台已扩展到单细胞测序、空间多组学、流式检测、超敏电化学发光、Luminex多因子检测、抗体芯片、PCR Array、ELISA、Elispot、PLA蛋白互作、多色免疫组化、DSP空间多组学等30多个，建立起了一套涵盖基因、蛋白、细胞以及组织水平实验的完整检测体系。

 
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