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Identification of candidate host serum and saliva biomarkers for a better diagnosis of active and latent tuberculosis infection
In our work, we aim to identify new candidate host biomarkers to discriminate between active TB patients (n = 28), latent infection (LTBI; n = 27) and uninfected (NoTBI; n = 42) individuals. For that, active TB patients and their contacts were recruited that donated serum and saliva samples. A multi...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7371182/ https://www.ncbi.nlm.nih.gov/pubmed/32687494 http://dx.doi.org/10.1371/journal.pone.0235859 |
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author | Estévez, Olivia Anibarro, Luis Garet, Elina Pallares, Ángeles Pena, Alberto Villaverde, Carlos del Campo, Víctor González-Fernández, África |
author_facet | Estévez, Olivia Anibarro, Luis Garet, Elina Pallares, Ángeles Pena, Alberto Villaverde, Carlos del Campo, Víctor González-Fernández, África |
author_sort | Estévez, Olivia |
collection | PubMed |
description | In our work, we aim to identify new candidate host biomarkers to discriminate between active TB patients (n = 28), latent infection (LTBI; n = 27) and uninfected (NoTBI; n = 42) individuals. For that, active TB patients and their contacts were recruited that donated serum and saliva samples. A multiplex assay was performed to study the concentration of different cytokines, chemokines and growth factors. Proteins with significant differences between groups were selected and logistic regression and the area under the ROC curve (AUC) was used to assess the diagnostic accuracy. The best marker combinations that discriminate active TB from NoTBI contacts were [IP-10 + IL-7] in serum and [Fractalkine + IP-10 + IL-1α + VEGF] in saliva. Best discrimination between active TB and LTBI was achieved using [IP-10 + BCA-1] in serum (AUC = 0.83) and IP-10 in saliva (p = 0.0007; AUC = 0.78). The levels of TNFα (p = 0.003; AUC = 0.73) in serum and the combination of [Fractalkine+IL-12p40] (AUC = 0.83) in saliva, were able to differentiate between NoTBI and LTBI contacts. In conclusion, different individual and combined protein markers could help to discriminate between active TB and both uninfected and latently-infected contacts. The most promising ones include [IP-10 + IL-7], [IP-10 + BCA-1] and TNFα in serum and [Fractalkine + IP-10 + IL-1α + VEGF], IP-10 and [Fractalkine+IL-12p40] in saliva. |
format | Online Article Text |
id | pubmed-7371182 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-73711822020-07-29 Identification of candidate host serum and saliva biomarkers for a better diagnosis of active and latent tuberculosis infection Estévez, Olivia Anibarro, Luis Garet, Elina Pallares, Ángeles Pena, Alberto Villaverde, Carlos del Campo, Víctor González-Fernández, África PLoS One Research Article In our work, we aim to identify new candidate host biomarkers to discriminate between active TB patients (n = 28), latent infection (LTBI; n = 27) and uninfected (NoTBI; n = 42) individuals. For that, active TB patients and their contacts were recruited that donated serum and saliva samples. A multiplex assay was performed to study the concentration of different cytokines, chemokines and growth factors. Proteins with significant differences between groups were selected and logistic regression and the area under the ROC curve (AUC) was used to assess the diagnostic accuracy. The best marker combinations that discriminate active TB from NoTBI contacts were [IP-10 + IL-7] in serum and [Fractalkine + IP-10 + IL-1α + VEGF] in saliva. Best discrimination between active TB and LTBI was achieved using [IP-10 + BCA-1] in serum (AUC = 0.83) and IP-10 in saliva (p = 0.0007; AUC = 0.78). The levels of TNFα (p = 0.003; AUC = 0.73) in serum and the combination of [Fractalkine+IL-12p40] (AUC = 0.83) in saliva, were able to differentiate between NoTBI and LTBI contacts. In conclusion, different individual and combined protein markers could help to discriminate between active TB and both uninfected and latently-infected contacts. The most promising ones include [IP-10 + IL-7], [IP-10 + BCA-1] and TNFα in serum and [Fractalkine + IP-10 + IL-1α + VEGF], IP-10 and [Fractalkine+IL-12p40] in saliva. Public Library of Science 2020-07-20 /pmc/articles/PMC7371182/ /pubmed/32687494 http://dx.doi.org/10.1371/journal.pone.0235859 Text en © 2020 Estévez et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Estévez, Olivia Anibarro, Luis Garet, Elina Pallares, Ángeles Pena, Alberto Villaverde, Carlos del Campo, Víctor González-Fernández, África Identification of candidate host serum and saliva biomarkers for a better diagnosis of active and latent tuberculosis infection |
title | Identification of candidate host serum and saliva biomarkers for a better diagnosis of active and latent tuberculosis infection |
title_full | Identification of candidate host serum and saliva biomarkers for a better diagnosis of active and latent tuberculosis infection |
title_fullStr | Identification of candidate host serum and saliva biomarkers for a better diagnosis of active and latent tuberculosis infection |
title_full_unstemmed | Identification of candidate host serum and saliva biomarkers for a better diagnosis of active and latent tuberculosis infection |
title_short | Identification of candidate host serum and saliva biomarkers for a better diagnosis of active and latent tuberculosis infection |
title_sort | identification of candidate host serum and saliva biomarkers for a better diagnosis of active and latent tuberculosis infection |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7371182/ https://www.ncbi.nlm.nih.gov/pubmed/32687494 http://dx.doi.org/10.1371/journal.pone.0235859 |
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