Publication Details

AFRICAN RESEARCH NEXUS

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medicine

CCL1 and IL-2Ra differentiate Tuberculosis disease from latent infection Irrespective of HIV infection in low TB burden countries

Journal of Infection, Volume 83, No. 4, Year 2021

Objectives: To evaluate the performance of selected host immunological biomarkers in differentiating tuberculosis (TB) disease from latent TB infection (LTBI) in HIV uninfected and infected individuals enrolled in TB low-burden countries. Design: Participants with TB disease (N = 85) and LTBI (N = 150) were recruited from prospective cohorts at hospitals in Norway and Denmark. Plasma concentrations of 54 host markers were assessed by Luminex multiplex immunoassays. Using receiver operator characteristic curves and general discriminant analysis, we determined the abilities of individual and combined biomarkers to discriminate between TB disease and LTBI including when patients were stratified according to HIV infection status. Results: Regardless of the groups compared, CCL1 and IL-2Ra were the most accurate single biomarkers in differentiating TB disease from LTBI. Regardless of HIV status, a 4-marker signature (CCL1+RANTES+CRP+MIP-1α) derived from a training set (n = 155) differentiated TB disease from LTBI in the test set (n = 67) with a sensitivity of 56.0% (95% CI, 34.9–75.6) and a specificity of 85.7% (95% CI, 71.5–94.6). A 5-marker signature derived from the HIV uninfected group (CCL1+RANTES+MIP-1α+procalcitonin+IP-10) performed in HIV-infected individuals with a sensitivity of 75.0% and a specificity of 96.7% after leave-one-out cross validation. A 2-marker signature (CCL1+TNF-α) identified in HIV-infected persons performed in HIV-uninfected with a sensitivity and specificity of 66.7% and 100% respectively in the test set. Conclusions: Plasma CCL1 and IL-2Ra have potential as biomarkers for differentiating TB disease from LTBI in low TB burden settings unaffected by HIV infection. Combinations between these and other biomarkers in bio-signatures for global use warrant further exploration.
Statistics
Citations: 10
Authors: 10
Affiliations: 4
Identifiers
Research Areas
Infectious Diseases
Study Design
Cohort Study