ArticleMediators of inflammation2026
Biomarkers in QuantiFERON Supernatants May Help Distinguish Latent Tuberculosis Infection From Active Tuberculosis: Preliminary Report.
Article in Mediators of inflammation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Biomarkers in QuantiFERON Supernatants May Help Distinguish Latent Tuberculosis Infection From Active Tuberculosis: Preliminary Report.Mediators of inflammation · 2026Article
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4 authors.
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Abstract
backgroundLatent tuberculosis infection (LTBI) is an important public health problem and a major source of future active tuberculosis (ATB) cases. In this preliminary study, we sought to identify host biomarkers that could potential differentiate between LTBI and ATB.
methodsA total of 145 plasma samples obtained from antigen tubes of the QuantiFERON-TB Gold Plus assay were analysed. Concentrations of 20 selected cytokines were determined using a multiplex bead-based immunoassay (Luminex xMAP Technology). Cytokine profiles were compared between patients with ATB, LTBI, and non-tuberculosis (TB)/LTBI controls. Diagnostic performance was assessed using receiver operating characteristic (ROC) analysis and multivariable logistic regression modelling.
resultsComparison of cytokine profiles showed significant differences in 13 of 20 analysed markers between LTBI and ATB. Among all evaluated biomarkers, interleukin-7 (IL-7) demonstrated the highest diagnostic potential in differentiating the two conditions (95.9%), outperforming interferon-gamma (IFN-γ), the key component of current IFN-γ release assay (IGRA) assays. A logistic regression model based on IL-7 and IFN-γ achieved high diagnostic accuracy (98.1%) in this study cohort.
conclusionThese preliminary findings suggest that IL-7, in combination with IFN-γ, may serve as a promising candidate biomarker signature for distinguishing LTBI from ATB. Nevertheless, these findings are based on a single-centre dataset and represent internal, non-externally validated results. Therefore, external validation in independent multicentre cohorts is essential before any clinical application can be considered.
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