Prognostic utility of immune biomarkers for identifying individuals at risk of unfavourable treatment outcomes in pulmonary tuberculosis
5 affiliations
- 1Prof. M. Viswanathan Diabetes Research Center
- 2Division of TB Prevention and Elimination Research, ICMR- National Institute for Research in Tuberculosis
- 3National Institutes of Health-National Institute for Research in Tuberculosis (NIRT)- International Center for Excellence in Research
- 4Laboratory of Parasitic Diseases (LPD), of National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH)
- 5UMass Chan Medical School
Abstract
Introduction: Tuberculosis remains a major global health challenge, with many patients expe- riencing unfavourable treatment outcomes despite standard therapy. Host immune biomarkers, including cytokines, chemokines, and matrix metalloproteinases (MMPs), have shown promise in predicting disease severity and treatment response, but require validation across independent cohorts.
Methods: We validated previously identified immune biomarkers using baseline plasma samples from a nested case–control cohort within the RePORT India consortium (cases: n=74; controls: n=161). Cytokines (IL-2, IFN-γ, TNF-α, IL-6, IL-1β, IL-10, IL-17A, and GM-CSF), chemokines (CCL2, CCL3, CCL4, CXCL1, CXCL8, and CXCL10), and matrix metalloproteinases (MMP-1, MMP-2, MMP-7, and MMP-9) were quantified using multiplex ELISA on the Luminex platform. Statistical analyses included group comparisons, ROC analysis, logistic regression, random forest modelling, princi- pal component analysis, and stability selection to identify optimal biomarker combinations.
Results: Elevated levels of IL-2, IFN-γ, TNF-α, IL-6, CCL2, CXCL8, CXCL10, MMP-2, MMP-7, and MMP-9 were associated with unfavourable out- comes. IL-2, CXCL8, CCL2, and MMP-2 showed strong individual predictive performance (AUC ≥0.80). Multivariable analysis identified CCL2, CXCL8, and CXCL10 as significant predictors of poor outcomes. A combined biomarker panel comprising CXCL8, MMP-2, and CCL2 demonstrated excellent predictive accu- racy (AUC ~0.90), with sensitivity ranging from 89% to 98% and specificity ranging from 80% to 90%, depending on the biomarker combination and the selected ROC cut-off.
Discussion: These findings validate key immune biomarkers and support a multi- marker host biomarker panel for early risk stratification and personalized TB management.
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BibTeX
@article{vanamudhu2026prognostic,
title = {{Prognostic utility of immune biomarkers for identifying individuals at risk of unfavourable treatment outcomes in pulmonary tuberculosis}},
author = {Agalya Vanamudhu and Vijay Viswanathan and Guruprashath Mohan and Nivedha Krishna Rao and Kannan Thiruvengadam and Syed Hissar and Bhavani Permal Kannabiran and Subash Babu and Hardy Kornfeld and Nathella Pavan Kumar},
journal = {Frontiers in Immunology},
year = {2026},
month = oct,
doi = {10.3389/fimmu.2026.1928573},
url = {https://www.frontiersin.org/articles/10.3389/fimmu.2026.1928573/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Prognostic utility of immune biomarkers for identifying individuals at risk of unfavourable treatment outcomes in pulmonary tuberculosis
AU - Agalya Vanamudhu
AU - Vijay Viswanathan
AU - Guruprashath Mohan
AU - Nivedha Krishna Rao
AU - Kannan Thiruvengadam
AU - Syed Hissar
AU - Bhavani Permal Kannabiran
AU - Subash Babu
AU - Hardy Kornfeld
AU - Nathella Pavan Kumar
PY - 2026
DA - 2026/10/05
JO - Frontiers in Immunology
DO - 10.3389/fimmu.2026.1928573
UR - https://www.frontiersin.org/articles/10.3389/fimmu.2026.1928573/full
AB - Introduction: Tuberculosis remains a major global health challenge, with many patients expe- riencing unfavourable treatment outcomes despite standard therapy. Host immune biomarkers, including cytokines, chemokines, and matrix metalloproteinases (MMPs), have shown promise in predicting disease severity and treatment response, but require validation across independent cohorts. Methods: We validated previously identified immune biomarkers using baseline plasma samples from a nested case–control cohort within the RePORT India consortium (cases: n=74; controls: n=161). Cytokines (IL-2, IFN-γ, TNF-α, IL-6, IL-1β, IL-10, IL-17A, and GM-CSF), chemokines (CCL2, CCL3, CCL4, CXCL1, CXCL8, and CXCL10), and matrix metalloproteinases (MMP-1, MMP-2, MMP-7, and MMP-9) were quantified using multiplex ELISA on the Luminex platform. Statistical analyses included group comparisons, ROC analysis, logistic regression, random forest modelling, princi- pal component analysis, and stability selection to identify optimal biomarker combinations. Results: Elevated levels of IL-2, IFN-γ, TNF-α, IL-6, CCL2, CXCL8, CXCL10, MMP-2, MMP-7, and MMP-9 were associated with unfavourable out- comes. IL-2, CXCL8, CCL2, and MMP-2 showed strong individual predictive performance (AUC ≥0.80). Multivariable analysis identified CCL2, CXCL8, and CXCL10 as significant predictors of poor outcomes. A combined biomarker panel comprising CXCL8, MMP-2, and CCL2 demonstrated excellent predictive accu- racy (AUC ~0.90), with sensitivity ranging from 89% to 98% and specificity ranging from 80% to 90%, depending on the biomarker combination and the selected ROC cut-off. Discussion: These findings validate key immune biomarkers and support a multi- marker host biomarker panel for early risk stratification and personalized TB management.
SN - 1664-3224
ER -