Identification of potential biomarkers of disease progression in bovine tuberculosis
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-? release assays [IGRA]. Positive animals are separated from the herd and sacrificed. The cost of this procedure is difficult to afford for deve...
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| Otros Autores: | , |
| Formato: | Artículo |
| Lenguaje: | Español |
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| Acceso en línea: | http://ri.agro.uba.ar/files/intranet/articulo/2014blanco.pdf LINK AL EDITOR |
| Aporte de: | Registro referencial: Solicitar el recurso aquí |
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| 100 | 1 | |9 70699 |a Blanco, Federico Carlos | |
| 245 | 0 | 0 | |a Identification of potential biomarkers of disease progression in bovine tuberculosis |
| 520 | |a 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-? 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 percent vs. 86.7 percent]. 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. | ||
| 653 | 0 | |a ANIMAL EXPERIMENT | |
| 653 | 0 | |a ANIMALIA | |
| 653 | 0 | |a BIOMARKER | |
| 653 | 0 | |a BOS | |
| 653 | 0 | |a BOVINAE | |
| 653 | 0 | |a BOVINE TUBERCULOSIS | |
| 653 | 0 | |a CD4+ T LYMPHOCYTE | |
| 653 | 0 | |a CD8+ T LYMPHOCYTE | |
| 653 | 0 | |a DISCRIMINANT ANALYSIS | |
| 653 | 0 | |a DISEASE COURSE | |
| 653 | 0 | |a ENZYME LINKED IMMUNOSORBENT ASSAY | |
| 653 | 0 | |a FLOW CYTOMETRY | |
| 653 | 0 | |a FLUORESCENCE ACTIVATED CELL SORTING | |
| 653 | 0 | |a GAMMA INTERFERON | |
| 653 | 0 | |a IL-17 | |
| 653 | 0 | |a IMMUNOLOGICAL PARAMETERS | |
| 653 | 0 | |a INTERFERON GAMMA RELEASE ASSAY | |
| 653 | 0 | |a INTERLEUKIN 10 | |
| 653 | 0 | |a INTERLEUKIN 17 | |
| 653 | 0 | |a INTERLEUKIN 2 | |
| 653 | 0 | |a INTERLEUKIN 4 | |
| 653 | 0 | |a K NEAREST NEIGHBOR | |
| 653 | 0 | |a LUNG LESION | |
| 653 | 0 | |a MYCOBACTERIUM BOVIS | |
| 653 | 0 | |a NONHUMAN | |
| 653 | 0 | |a PERIPHERAL BLOOD MONONUCLEAR CELL | |
| 653 | 0 | |a PREDICTION | |
| 653 | 0 | |a PROTEIN EXPRESSION | |
| 653 | 0 | |a QUANTITATIVE ANALYSIS | |
| 653 | 0 | |a REVERSE TRANSCRIPTION POLYMERASE CHAIN REACTION | |
| 653 | 0 | |a SKIN TEST | |
| 653 | 0 | |a TUBERCULIN TEST | |
| 700 | 1 | |9 48059 |a Bigi, Fabiana | |
| 700 | 1 | |9 49057 |a Soria, Marcelo Abel | |
| 773 | |t Veterinary Immunology and Immunopathology |g vol.160, no.3-4 (2014), p.177-183 | ||
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| 900 | |a ^tIdentification of potential biomarkers of disease progression in bovine tuberculosis | ||
| 900 | |a ^aBlanco^bF.C. | ||
| 900 | |a ^aBigi^bF. | ||
| 900 | |a ^aSoria^bM.A. | ||
| 900 | |a ^aBlanco^bF. C. | ||
| 900 | |a ^aBigi^bF. | ||
| 900 | |a ^aSoria^bM. A. | ||
| 900 | |a Blanco, F.C. Instituto de Biotecnología, CICVyA-INTA, N. Repetto y De los Reseros, 1686 Hurlingham, Buenos Aires, Argentina | ||
| 900 | |a Bigi, F. Instituto de Biotecnología, CICVyA-INTA, N. Repetto y De los Reseros, 1686 Hurlingham, Buenos Aires, Argentina | ||
| 900 | |a Soria, M.A. Microbiología Agrícola, Facultad de Agronomía, Universidad de Buenos Aires, INBA Consejo Nacional de Investigaciones Científicas y Técnicas, Ciudad de Buenos Aires, Argentina | ||
| 900 | |a ^tVeterinary Immunology and Immunopathology^cVet. Immunol. Immunopathol. | ||
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| 900 | |a Vol. 160, no. 3-4 | ||
| 900 | |a 183 | ||
| 900 | |a ANIMAL EXPERIMENT | ||
| 900 | |a ANIMALIA | ||
| 900 | |a BIOMARKER | ||
| 900 | |a BOS | ||
| 900 | |a BOVINAE | ||
| 900 | |a BOVINE TUBERCULOSIS | ||
| 900 | |a CD4+ T LYMPHOCYTE | ||
| 900 | |a CD8+ T LYMPHOCYTE | ||
| 900 | |a DISCRIMINANT ANALYSIS | ||
| 900 | |a DISEASE COURSE | ||
| 900 | |a ENZYME LINKED IMMUNOSORBENT ASSAY | ||
| 900 | |a FLOW CYTOMETRY | ||
| 900 | |a FLUORESCENCE ACTIVATED CELL SORTING | ||
| 900 | |a GAMMA INTERFERON | ||
| 900 | |a IL-17 | ||
| 900 | |a IMMUNOLOGICAL PARAMETERS | ||
| 900 | |a INTERFERON GAMMA RELEASE ASSAY | ||
| 900 | |a INTERLEUKIN 10 | ||
| 900 | |a INTERLEUKIN 17 | ||
| 900 | |a INTERLEUKIN 2 | ||
| 900 | |a INTERLEUKIN 4 | ||
| 900 | |a K NEAREST NEIGHBOR | ||
| 900 | |a LUNG LESION | ||
| 900 | |a MYCOBACTERIUM BOVIS | ||
| 900 | |a NONHUMAN | ||
| 900 | |a PERIPHERAL BLOOD MONONUCLEAR CELL | ||
| 900 | |a PREDICTION | ||
| 900 | |a PROTEIN EXPRESSION | ||
| 900 | |a QUANTITATIVE ANALYSIS | ||
| 900 | |a REVERSE TRANSCRIPTION POLYMERASE CHAIN REACTION | ||
| 900 | |a SKIN TEST | ||
| 900 | |a TUBERCULIN TEST | ||
| 900 | |a 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-? 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 percent vs. 86.7 percent]. 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. | ||
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