dc.contributor.author | Estévez Martínez, Olivia | |
dc.contributor.author | Anibarro, Luis | |
dc.contributor.author | Garet Fernández, María Elina | |
dc.contributor.author | Martinez Perez, Amparo | |
dc.contributor.author | Pena, Alberto | |
dc.contributor.author | Barcia, Laura | |
dc.contributor.author | Peleteiro Olmedo, Mercedes | |
dc.contributor.author | González Fernández, Maria Africa | |
dc.date.accessioned | 2024-02-23T09:45:00Z | |
dc.date.available | 2024-02-23T09:45:00Z | |
dc.date.issued | 2020-07 | |
dc.identifier.citation | Journal of Infection, 81(1): 57-71 (2020) | spa |
dc.identifier.issn | 01634453 | |
dc.identifier.uri | http://hdl.handle.net/11093/6332 | |
dc.description.abstract | Objectives: To identify new potential host biomarkers in blood to discriminate between active TB patients, uninfected (NoTBI) and latently infected contacts (LTBI).
Methods: A blood cell count was performed to study parent leukocyte populations. Peripheral blood mononuclear cells (PBMCs) were isolated and a multi-parameter flow cytometry assay was conducted to study the distribution of basal and Mycobacterium tuberculosis (Mtb)-stimulated lymphocytes. Differences between groups and the area under the ROC curve (AUC) were investigated to assess the diagnostic accuracy.
Results: Active TB patients presented higher Monocyte-to-lymphocyte and Neutrophil-to-lymphocyte ratios than LTBI and NoTBI contacts (p<0.0001; AUC>0.8). Lymphocyte subsets with differences (p >0.05; AUC >0.7) between active TB and both contact groups include the basal distribution of Th1/Th2 ratio, Th1-Th17, CD4+ Central Memory (TCM) or MAIT cells. Expression of CD154 is increased in Mtb-activated CD4+ TCM and Effector Memory T cells in active TB and LTBI compared to NoTBI. In CD4+T cells, expression of CD154 showed a higher accuracy than IFNγ to discriminate Mtb-specific activation.
Conclusions: We identified different cell subsets with potential use in tuberculosis diagnosis. Among them, distribution of CD4 TCM cells and their expression of CD154 after Mtb-activation are the most promising candidates. | spa |
dc.description.sponsorship | Xunta de Galicia | Ref. ED431C 2016/041 | spa |
dc.language.iso | eng | spa |
dc.publisher | Journal of Infection | spa |
dc.rights | Attribution-NonCommercial-NoDerivs 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.title | Multi-parameter flow cytometry immunophenotyping distinguishes different stages of tuberculosis infection | eng |
dc.type | article | spa |
dc.rights.accessRights | openAccess | spa |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/643558 | spa |
dc.identifier.doi | 10.1016/j.jinf.2020.03.064 | |
dc.identifier.editor | https://doi.org/10.1016/j.jinf.2020.03.064 | spa |
dc.publisher.departamento | Química Física | spa |
dc.publisher.departamento | Bioquímica, xenética e inmunoloxía | spa |
dc.publisher.grupoinvestigacion | Inmunoloxía | spa |
dc.subject.unesco | 2412.06 Inmunización | spa |
dc.subject.unesco | 2414.02 Fisiología Bacteriana | spa |
dc.date.updated | 2024-01-22T17:12:44Z | |
dc.computerCitation | pub_title=Journal of Infection|volume=81|journal_number=1|start_pag=57|end_pag=71 | spa |