ABSTRACT
OBJECTIVE: We aimed to identify plasma cytokine biomarkers that differentiate the infection stages of Mycobacterium tuberculosis (MTB). METHODS: This study included a total of 227 subjects consisting of active tuberculosis (ATB) patients, latent tuberculosis infection (LTBI) individuals, and healthy controls (HC). We analyzed the expressions of 38 plasma cytokines in the discovery cohort to identify the biosignatures for differentiating MTB infection states, area under the curve (AUC) were used to evaluate the diagnostic efficiency. The AUC of unique plasma biomarker was confirmed in the validation cohort. RESULTS: In the discovery cohort, the AUC of the 8-marker biosignature (eotaxin, MIP-1α, MDC, IP-10, MCP-1, IL-1α, IL-10, and TNF-α) in diagnosing ATB was 1.0. The sensitivity and specificity of the 5-marker biosignature (IP-10, MCP-1, IL-1α, IL-10, and TNF-α) in diagnosing LTBI were 94% and 81.25%, respectively. The AUC of the 3-signature biosignature (eotaxin, MDC, MCP-1) in differentiating ATB from LTBI was 0.94, with the sensitivity and specificity of 87.76% and 91.84%, respectively. Moreover, among all the single cytokine biomarkers, MCP-1 exhibited the highest AUC in diagnosing ATB (0.98) and differentiating ATB from LTBI (0.91). In the subsequent validation cohort analysis, we identified that the AUC of MCP-1 in diagnosing ATB and differentiating ATB from LTBI were 0.97 and 0.89, respectively, which was generally consistent with the results of the discovery cohort. CONCLUSION: Cytokine levels in plasma can be used as biosignatures to diagnose ATB. The cytokine concentrations vary during the different stages of MTB infection, which might serve as biomarkers in differentiating ATB from LTBI. Future studies with a larger population and data from multiple institutions are needed to validate our findings.
