Antigen-specific chemokine CCL3 as a biomarker for distinguishing between recent and remote tuberculosis infection
Infection, 2025
Chang C., Ma Z., Ren W., Wang W., Liu H., Zhong R., Li S., Gao M., Pang Y.
| Disease area | Application area | Sample type | Products |
|---|---|---|---|
Infectious Diseases | Patient Stratification | Plasma |  Olink Target 96 |
Abstract
Background
Identifying recent tuberculosis (TB) infection individuals and administering TB preventive therapy (TPT) are critical strategies for controlling TB. However, current diagnostics fail to identify these individuals at high risk for developing active TB. Herein, we aimed to explore the candidate biomarkers to distinguish recent TB infection from remote TB infection individuals.
Methods
Close contacts of TB patients were continuously recruited. A total of 121 participants meeting study inclusion criteria were assigned to screening and validation cohorts, consisting of 45 participants assigned to screening cohort, and 76 participants assigned to validation cohort. The inflammation-related protein biomarkers in Mtb antigen-stimulated blood plasma were measured in the screening cohort using the Olink targeted proteomics. The candidate biomarkers were verified in validation cohort with the customized Luminex-based multiplex microbead array.
Results
Quantitative proteomics analysis reveals that significant differences in Mycobacterium tuberculosis (Mtb) antigen-stimulated blood plasma levels of CCL3, CCL20, CCL23 and TNF-α between remote and recent TB infection group. The different response profiles of memory immune cells to Mtb antigens could stem from activation of the NF-κB signaling pathway. The levels of CCL3, CCL20 and TNF-α were predictive of recent TB infection group, of which CCL3 exhibited the best performance with an AUC value of 0.859, yielding a sensitivity and specificity of 86.4% and 75%, respectively.
Conclusions
The Mtb antigen-specific assay utilizing CCL3 exhibits superior diagnostic performance and could potentially enhance diagnostic accuracy for identifying recent TB infection patients among LTBI individuals.