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Tuberculosis diagnosis: algorithm that May discriminate latent from active tuberculosis
Diagnosis of tuberculosis still faces a lot of challenges and is one of the priorities in the field of tuberculosis management. Deciphering the complex tuberculosis pathogenicity network could provide biomarkers for diagnosis. We discussed the distribution of HLA-B17, -DQB and -DRB together with Qua...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806400/ https://www.ncbi.nlm.nih.gov/pubmed/31692671 http://dx.doi.org/10.1016/j.heliyon.2019.e02559 |
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author | Ndzi, Elvis Ndukong Nkenfou, Celine Nguefeu Pefura, Eric Walter Yone Mekue, Linda Chapdeleine Mouafo Guiedem, Elise Nguefeu, Carine Nkenfou Ngoufack, Marie Nicole Elong, Elise Yatchou, Laeticia Grace Ndjolo, Alexis Kuiate, Jules-Roger |
author_facet | Ndzi, Elvis Ndukong Nkenfou, Celine Nguefeu Pefura, Eric Walter Yone Mekue, Linda Chapdeleine Mouafo Guiedem, Elise Nguefeu, Carine Nkenfou Ngoufack, Marie Nicole Elong, Elise Yatchou, Laeticia Grace Ndjolo, Alexis Kuiate, Jules-Roger |
author_sort | Ndzi, Elvis Ndukong |
collection | PubMed |
description | Diagnosis of tuberculosis still faces a lot of challenges and is one of the priorities in the field of tuberculosis management. Deciphering the complex tuberculosis pathogenicity network could provide biomarkers for diagnosis. We discussed the distribution of HLA-B17, -DQB and -DRB together with QuantiFERON test results in tuberculosis infection. A case control study was done during which a total of 337 subjects were enrolled comprising 227 active tuberculosis (ATB), 46 latent tuberculosis infection (LTBI) and 64 healthy controls (HC). Sequence-specific primer polymerase chain reaction and immune epitope database were used to genotype samples and determine the epitope binding ability of the over-represented alleles respectively. QuantiFERON test was done according to manufacturer's instructions. The peptides HLA-B*5801 and HLA-DRB1*12 and the peptides HLA-B*5802 and HLA-DQB1*03 were found to be associated with latent tuberculosis while the haplotypes DRB1*10-DQB1*02 and DRB1*13-DQB1*06 were found to be associated with active tuberculosis (All p-values≤0.05). The association of HLA-B*5801 and HLA-B*5802 with latent tuberculosis was linked to their ability to bind or not mycobacterial antigens. DRB1*10-DQB1*02 haplotype was found to be over-represented in LTBI compared to ATB (p-value = 0.0015) while DRB1*13-DQB1*06 was found to be under-represented in LTBI compared to ATB (p-value = 0.0335). The DRB1*10-DQB1*02 haplotype was only found in the LTBI when compared with the ATB group. The present study suggests the following algorithm to discriminate LTBI from ATB: QuantiFERON+ and DRB1*10-DQB1*02 haplotype + may indicate LTBI; QuantiFERON+ and DRB1*10-DQB1*02 haplotype - may indicate ATB. |
format | Online Article Text |
id | pubmed-6806400 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-68064002019-11-05 Tuberculosis diagnosis: algorithm that May discriminate latent from active tuberculosis Ndzi, Elvis Ndukong Nkenfou, Celine Nguefeu Pefura, Eric Walter Yone Mekue, Linda Chapdeleine Mouafo Guiedem, Elise Nguefeu, Carine Nkenfou Ngoufack, Marie Nicole Elong, Elise Yatchou, Laeticia Grace Ndjolo, Alexis Kuiate, Jules-Roger Heliyon Article Diagnosis of tuberculosis still faces a lot of challenges and is one of the priorities in the field of tuberculosis management. Deciphering the complex tuberculosis pathogenicity network could provide biomarkers for diagnosis. We discussed the distribution of HLA-B17, -DQB and -DRB together with QuantiFERON test results in tuberculosis infection. A case control study was done during which a total of 337 subjects were enrolled comprising 227 active tuberculosis (ATB), 46 latent tuberculosis infection (LTBI) and 64 healthy controls (HC). Sequence-specific primer polymerase chain reaction and immune epitope database were used to genotype samples and determine the epitope binding ability of the over-represented alleles respectively. QuantiFERON test was done according to manufacturer's instructions. The peptides HLA-B*5801 and HLA-DRB1*12 and the peptides HLA-B*5802 and HLA-DQB1*03 were found to be associated with latent tuberculosis while the haplotypes DRB1*10-DQB1*02 and DRB1*13-DQB1*06 were found to be associated with active tuberculosis (All p-values≤0.05). The association of HLA-B*5801 and HLA-B*5802 with latent tuberculosis was linked to their ability to bind or not mycobacterial antigens. DRB1*10-DQB1*02 haplotype was found to be over-represented in LTBI compared to ATB (p-value = 0.0015) while DRB1*13-DQB1*06 was found to be under-represented in LTBI compared to ATB (p-value = 0.0335). The DRB1*10-DQB1*02 haplotype was only found in the LTBI when compared with the ATB group. The present study suggests the following algorithm to discriminate LTBI from ATB: QuantiFERON+ and DRB1*10-DQB1*02 haplotype + may indicate LTBI; QuantiFERON+ and DRB1*10-DQB1*02 haplotype - may indicate ATB. Elsevier 2019-10-18 /pmc/articles/PMC6806400/ /pubmed/31692671 http://dx.doi.org/10.1016/j.heliyon.2019.e02559 Text en © 2019 Published by Elsevier Ltd. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Ndzi, Elvis Ndukong Nkenfou, Celine Nguefeu Pefura, Eric Walter Yone Mekue, Linda Chapdeleine Mouafo Guiedem, Elise Nguefeu, Carine Nkenfou Ngoufack, Marie Nicole Elong, Elise Yatchou, Laeticia Grace Ndjolo, Alexis Kuiate, Jules-Roger Tuberculosis diagnosis: algorithm that May discriminate latent from active tuberculosis |
title | Tuberculosis diagnosis: algorithm that May discriminate latent from active tuberculosis |
title_full | Tuberculosis diagnosis: algorithm that May discriminate latent from active tuberculosis |
title_fullStr | Tuberculosis diagnosis: algorithm that May discriminate latent from active tuberculosis |
title_full_unstemmed | Tuberculosis diagnosis: algorithm that May discriminate latent from active tuberculosis |
title_short | Tuberculosis diagnosis: algorithm that May discriminate latent from active tuberculosis |
title_sort | tuberculosis diagnosis: algorithm that may discriminate latent from active tuberculosis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806400/ https://www.ncbi.nlm.nih.gov/pubmed/31692671 http://dx.doi.org/10.1016/j.heliyon.2019.e02559 |
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