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

Simple item page
dc.contributor.authorChendi, Bih H.en_ZA
dc.contributor.authorTveiten, Hallgeiren_Za
dc.contributor.authorSnyders, Candice I.en_ZA
dc.contributor.authorTonby, Kristianen_ZA
dc.contributor.authorJenum, Synneen_ZA
dc.contributor.authorNielsen, Susanne Damen_ZA
dc.contributor.authorHove-Skovsgaard, Maleneen_ZA
dc.contributor.authorWalzl, Gerharden_ZA
dc.contributor.authorChegou, Novel N.en_ZA
dc.contributor.authorDyrhol-Riise, Anne Men_ZA
dc.date.accessioned2023-03-20T08:43:09Zen_ZA
dc.date.available2023-03-20T08:43:09Zen_ZA
dc.date.issued2021-10en_ZA
dc.descriptionCITATION: Chendi, Bih H. et al. 2021. CCL1 and IL-2Ra differentiate Tuberculosis disease from latent infection Irrespective of HIV infection in low TB burden countries. Journal of Infection 83(4):11 pages. doi.10.1016/j.jinf.2021.07.036en_ZA
dc.descriptionThe original publication is available at: sciencedirect.comen_ZA
dc.description.abstractObjectives: To evaluate the performance of selected host immunological biomarkers in differentiating tu- berculosis (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 co- horts 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-1 α) 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- 1 α+ procalcitonin + IP-10) performed in HIV-infected individuals with a sensitivity of 75.0% and a speci- ficity 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% respec- tively 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.en_ZA
dc.description.versionPublisher’s versionen_ZA
dc.format.extent11 pagesen_ZA
dc.identifier.citationChendi, Bih H. et al. 2021. CCL1 and IL-2Ra differentiate Tuberculosis disease from latent infection Irrespective of HIV infection in low TB burden countries. Journal of Infection 83(4):11 pages. doi.10.1016/j.jinf.2021.07.036en_ZA
dc.identifier.issn0163-4453 (online)en_ZA
dc.identifier.otherdoi.10.1016/j.jinf.2021.07.036en_ZA
dc.identifier.urihttp://hdl.handle.net/10019.1/126680en_ZA
dc.language.isoen_ZAen_ZA
dc.publisherElsevierLtden_ZA
dc.rights.holderAuthors retain copyrighten_ZA
dc.subjectBiochemical markersen_ZA
dc.subjectMycobacterium tuberculosisen_ZA
dc.subjectDiagnostic virologyen_ZA
dc.subjectHIV infectionsen_ZA
dc.subjectBiosignaturesen_ZA
dc.subjectUCTDen_ZA
dc.subjectLow endemic countriesen_ZA
dc.titleCCL1 and IL-2Ra differentiate Tuberculosis disease from latent infection Irrespective of HIV infection in low TB burden countriesen_ZA
dc.typeArticleen_ZA
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
bih_ccl1_2021.pdf
Size:
2.22 MB
Format:
Adobe Portable Document Format
Description:
download article
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Research Articles (Molecular Biology and Human Genetics)