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.
Acknowledgements
We acknowledge the study participants for the ScreenTB study, Dr. Mary Nsereko and the clinic, records, and data staff at the Uganda-Case Western Research Collaboration clinic for participant management. We also acknowledge Sophie Nalukwago, Paul Mutumba, Immaculate Kemigisha, Henry Ojiambo from the Uganda Case Western Research Collaboration Immunology lab, and all Mycobacteriology lab staff from the Joint Clinical Research Centre – Uganda for laboratory analysis and mycobacteriology assays for the study. We also acknowledge Prof. Martin Kidd from the Department of Statistics and the Actuarial Sciences University of Stellenbosch, Cape Town, South Africa for advanced statistical analysis.
Ethical approval
The study and the methods were performed following the relevant guidelines and regulations and received ethical approval from Makerere University, College of Health Sciences (Mak-CHS) (SBS 373), the Joint Clinical Research Centre (JCRC) institutional review boards, and the Uganda National Council of Science and Technology (UNCST) (HS2120). All subjects gave informed consent to participate in this study.
Author contributions
AR Namuganga designed this sub-study, performed laboratory sample analysis, initial statistical analysis, original drafting, and revision of the manuscript, while Bernard Bagaya, Harriet Mayanja-Kizza, Novel Chegou supervised the study and revised the manuscript until submission. All authors read and approved the final manuscript.
Disclosure statement
No potential conflict of interest was reported by the authors.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the corresponding author, without undue reservation upon request.