Identification of potential biomarkers of disease progression in bovine tuberculosis

Autores
Blanco, Federico Carlos; Bigi, Fabiana; Soria, Marcelo Abel
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Bovine tuberculosis (bTB) remains an important animal and zoonotic disease in many countries. The diagnosis of bTB is based on tuberculin skin test and IFN-γ release assays (IGRA). Positive animals are separated from the herd and sacrificed. The cost of this procedure is difficult to afford for developing countries with high prevalence of bTB; therefore, the improvement of diagnostic methods and the identification of animals in different stages of the disease will be helpful to control the infection. To identify biomarkers that can discriminate between tuberculin positive cattle with and without tuberculosis lesions (ML+ and ML-, respectively), we assessed a group of immunological parameters with three different classification methods: lineal discriminant analysis (LDA), quadratic discriminant analysis (QDA) and K nearest neighbors (k-nn). For this purpose, we used data from 30 experimentally infected cattle. All the classifiers (LDA, QDA and k-nn) selected IL-2 and IL-17 as the most discriminatory variables. The best classification method was LDA using IL-17 and IL-2 as predictors. The addition of IL-10 to LDA improves the performance of the classifier to discriminate ML-individuals (93.3% vs. 86.7%). Thus, the expression of IL-17, IL-2 and, in some cases, IL-10 would serve as an additional tool to study disease progression in herds with a history of bTB.
Fil: Blanco, Federico Carlos. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina
Fil: Bigi, Fabiana. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina
Fil: Soria, Marcelo Abel. Universidad de Buenos Aires. Facultad de Agronomía; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Biología Aplicada y Alimentos. Cátedra de Microbiología Agrícola; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales; Argentina
Materia
Bovine Tuberculosis
Il-17
Discriminant Analysis
Biomarker
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/33659

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spelling Identification of potential biomarkers of disease progression in bovine tuberculosisBlanco, Federico CarlosBigi, FabianaSoria, Marcelo AbelBovine TuberculosisIl-17Discriminant AnalysisBiomarkerhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Bovine tuberculosis (bTB) remains an important animal and zoonotic disease in many countries. The diagnosis of bTB is based on tuberculin skin test and IFN-γ release assays (IGRA). Positive animals are separated from the herd and sacrificed. The cost of this procedure is difficult to afford for developing countries with high prevalence of bTB; therefore, the improvement of diagnostic methods and the identification of animals in different stages of the disease will be helpful to control the infection. To identify biomarkers that can discriminate between tuberculin positive cattle with and without tuberculosis lesions (ML+ and ML-, respectively), we assessed a group of immunological parameters with three different classification methods: lineal discriminant analysis (LDA), quadratic discriminant analysis (QDA) and K nearest neighbors (k-nn). For this purpose, we used data from 30 experimentally infected cattle. All the classifiers (LDA, QDA and k-nn) selected IL-2 and IL-17 as the most discriminatory variables. The best classification method was LDA using IL-17 and IL-2 as predictors. The addition of IL-10 to LDA improves the performance of the classifier to discriminate ML-individuals (93.3% vs. 86.7%). Thus, the expression of IL-17, IL-2 and, in some cases, IL-10 would serve as an additional tool to study disease progression in herds with a history of bTB.Fil: Blanco, Federico Carlos. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; ArgentinaFil: Bigi, Fabiana. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; ArgentinaFil: Soria, Marcelo Abel. Universidad de Buenos Aires. Facultad de Agronomía; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Biología Aplicada y Alimentos. Cátedra de Microbiología Agrícola; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales; ArgentinaElsevier2014-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/33659Soria, Marcelo Abel; Bigi, Fabiana; Blanco, Federico Carlos; Identification of potential biomarkers of disease progression in bovine tuberculosis; Elsevier; Veterinary Immunology And Immunopathology; 160; 3-4; 5-2014; 177-1830165-2427CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.vetimm.2014.04.008info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0165242714001111info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:05:32Zoai:ri.conicet.gov.ar:11336/33659instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-10 13:05:32.302CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Identification of potential biomarkers of disease progression in bovine tuberculosis
title Identification of potential biomarkers of disease progression in bovine tuberculosis
spellingShingle Identification of potential biomarkers of disease progression in bovine tuberculosis
Blanco, Federico Carlos
Bovine Tuberculosis
Il-17
Discriminant Analysis
Biomarker
title_short Identification of potential biomarkers of disease progression in bovine tuberculosis
title_full Identification of potential biomarkers of disease progression in bovine tuberculosis
title_fullStr Identification of potential biomarkers of disease progression in bovine tuberculosis
title_full_unstemmed Identification of potential biomarkers of disease progression in bovine tuberculosis
title_sort Identification of potential biomarkers of disease progression in bovine tuberculosis
dc.creator.none.fl_str_mv Blanco, Federico Carlos
Bigi, Fabiana
Soria, Marcelo Abel
author Blanco, Federico Carlos
author_facet Blanco, Federico Carlos
Bigi, Fabiana
Soria, Marcelo Abel
author_role author
author2 Bigi, Fabiana
Soria, Marcelo Abel
author2_role author
author
dc.subject.none.fl_str_mv Bovine Tuberculosis
Il-17
Discriminant Analysis
Biomarker
topic Bovine Tuberculosis
Il-17
Discriminant Analysis
Biomarker
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Bovine tuberculosis (bTB) remains an important animal and zoonotic disease in many countries. The diagnosis of bTB is based on tuberculin skin test and IFN-γ release assays (IGRA). Positive animals are separated from the herd and sacrificed. The cost of this procedure is difficult to afford for developing countries with high prevalence of bTB; therefore, the improvement of diagnostic methods and the identification of animals in different stages of the disease will be helpful to control the infection. To identify biomarkers that can discriminate between tuberculin positive cattle with and without tuberculosis lesions (ML+ and ML-, respectively), we assessed a group of immunological parameters with three different classification methods: lineal discriminant analysis (LDA), quadratic discriminant analysis (QDA) and K nearest neighbors (k-nn). For this purpose, we used data from 30 experimentally infected cattle. All the classifiers (LDA, QDA and k-nn) selected IL-2 and IL-17 as the most discriminatory variables. The best classification method was LDA using IL-17 and IL-2 as predictors. The addition of IL-10 to LDA improves the performance of the classifier to discriminate ML-individuals (93.3% vs. 86.7%). Thus, the expression of IL-17, IL-2 and, in some cases, IL-10 would serve as an additional tool to study disease progression in herds with a history of bTB.
Fil: Blanco, Federico Carlos. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina
Fil: Bigi, Fabiana. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina
Fil: Soria, Marcelo Abel. Universidad de Buenos Aires. Facultad de Agronomía; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Biología Aplicada y Alimentos. Cátedra de Microbiología Agrícola; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales; Argentina
description Bovine tuberculosis (bTB) remains an important animal and zoonotic disease in many countries. The diagnosis of bTB is based on tuberculin skin test and IFN-γ release assays (IGRA). Positive animals are separated from the herd and sacrificed. The cost of this procedure is difficult to afford for developing countries with high prevalence of bTB; therefore, the improvement of diagnostic methods and the identification of animals in different stages of the disease will be helpful to control the infection. To identify biomarkers that can discriminate between tuberculin positive cattle with and without tuberculosis lesions (ML+ and ML-, respectively), we assessed a group of immunological parameters with three different classification methods: lineal discriminant analysis (LDA), quadratic discriminant analysis (QDA) and K nearest neighbors (k-nn). For this purpose, we used data from 30 experimentally infected cattle. All the classifiers (LDA, QDA and k-nn) selected IL-2 and IL-17 as the most discriminatory variables. The best classification method was LDA using IL-17 and IL-2 as predictors. The addition of IL-10 to LDA improves the performance of the classifier to discriminate ML-individuals (93.3% vs. 86.7%). Thus, the expression of IL-17, IL-2 and, in some cases, IL-10 would serve as an additional tool to study disease progression in herds with a history of bTB.
publishDate 2014
dc.date.none.fl_str_mv 2014-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/33659
Soria, Marcelo Abel; Bigi, Fabiana; Blanco, Federico Carlos; Identification of potential biomarkers of disease progression in bovine tuberculosis; Elsevier; Veterinary Immunology And Immunopathology; 160; 3-4; 5-2014; 177-183
0165-2427
CONICET Digital
CONICET
url http://hdl.handle.net/11336/33659
identifier_str_mv Soria, Marcelo Abel; Bigi, Fabiana; Blanco, Federico Carlos; Identification of potential biomarkers of disease progression in bovine tuberculosis; Elsevier; Veterinary Immunology And Immunopathology; 160; 3-4; 5-2014; 177-183
0165-2427
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.vetimm.2014.04.008
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0165242714001111
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
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instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
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repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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