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Genotype 1 Hepatitis C Virus Envelope Features That Determine Antiviral Response Assessed through Optimal Covariance Networks

The poor response to the combined antiviral therapy of pegylated alfa-interferon and ribavarin for hepatitis C virus (HCV) infection may be linked to mutations in the viral envelope gene E1E2 (env), which can result in escape from the immune response and higher efficacy of viral entry. Mutations tha...

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Autores principales: Murray, John M., Moenne-Loccoz, Rémy, Velay, Aurélie, Habersetzer, François, Doffoël, Michel, Gut, Jean-Pierre, Fofana, Isabel, Zeisel, Mirjam B., Stoll-Keller, Françoise, Baumert, Thomas F., Schvoerer, Evelyne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3688619/
https://www.ncbi.nlm.nih.gov/pubmed/23840641
http://dx.doi.org/10.1371/journal.pone.0067254
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author Murray, John M.
Moenne-Loccoz, Rémy
Velay, Aurélie
Habersetzer, François
Doffoël, Michel
Gut, Jean-Pierre
Fofana, Isabel
Zeisel, Mirjam B.
Stoll-Keller, Françoise
Baumert, Thomas F.
Schvoerer, Evelyne
author_facet Murray, John M.
Moenne-Loccoz, Rémy
Velay, Aurélie
Habersetzer, François
Doffoël, Michel
Gut, Jean-Pierre
Fofana, Isabel
Zeisel, Mirjam B.
Stoll-Keller, Françoise
Baumert, Thomas F.
Schvoerer, Evelyne
author_sort Murray, John M.
collection PubMed
description The poor response to the combined antiviral therapy of pegylated alfa-interferon and ribavarin for hepatitis C virus (HCV) infection may be linked to mutations in the viral envelope gene E1E2 (env), which can result in escape from the immune response and higher efficacy of viral entry. Mutations that result in failure of therapy most likely require compensatory mutations to achieve sufficient change in envelope structure and function. Compensatory mutations were investigated by determining positions in the E1E2 gene where amino acids (aa) covaried across groups of individuals. We assessed networks of covarying positions in E1E2 sequences that differentiated sustained virological response (SVR) from non-response (NR) in 43 genotype 1a (17 SVR), and 49 genotype 1b (25 SVR) chronically HCV-infected individuals. Binary integer programming over covariance networks was used to extract aa combinations that differed between response groups. Genotype 1a E1E2 sequences exhibited higher degrees of covariance and clustered into 3 main groups while 1b sequences exhibited no clustering. Between 5 and 9 aa pairs were required to separate SVR from NR in each genotype. aa in hypervariable region 1 were 6 times more likely than chance to occur in the optimal networks. The pair 531–626 (EI) appeared frequently in the optimal networks and was present in 6 of 9 NR in one of the 1a clusters. The most frequent pairs representing SVR were 431–481 (EE), 500–522 (QA) in 1a, and 407–434 (AQ) in 1b. Optimal networks based on covarying aa pairs in HCV envelope can indicate features that are associated with failure or success to antiviral therapy.
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spelling pubmed-36886192013-07-09 Genotype 1 Hepatitis C Virus Envelope Features That Determine Antiviral Response Assessed through Optimal Covariance Networks Murray, John M. Moenne-Loccoz, Rémy Velay, Aurélie Habersetzer, François Doffoël, Michel Gut, Jean-Pierre Fofana, Isabel Zeisel, Mirjam B. Stoll-Keller, Françoise Baumert, Thomas F. Schvoerer, Evelyne PLoS One Research Article The poor response to the combined antiviral therapy of pegylated alfa-interferon and ribavarin for hepatitis C virus (HCV) infection may be linked to mutations in the viral envelope gene E1E2 (env), which can result in escape from the immune response and higher efficacy of viral entry. Mutations that result in failure of therapy most likely require compensatory mutations to achieve sufficient change in envelope structure and function. Compensatory mutations were investigated by determining positions in the E1E2 gene where amino acids (aa) covaried across groups of individuals. We assessed networks of covarying positions in E1E2 sequences that differentiated sustained virological response (SVR) from non-response (NR) in 43 genotype 1a (17 SVR), and 49 genotype 1b (25 SVR) chronically HCV-infected individuals. Binary integer programming over covariance networks was used to extract aa combinations that differed between response groups. Genotype 1a E1E2 sequences exhibited higher degrees of covariance and clustered into 3 main groups while 1b sequences exhibited no clustering. Between 5 and 9 aa pairs were required to separate SVR from NR in each genotype. aa in hypervariable region 1 were 6 times more likely than chance to occur in the optimal networks. The pair 531–626 (EI) appeared frequently in the optimal networks and was present in 6 of 9 NR in one of the 1a clusters. The most frequent pairs representing SVR were 431–481 (EE), 500–522 (QA) in 1a, and 407–434 (AQ) in 1b. Optimal networks based on covarying aa pairs in HCV envelope can indicate features that are associated with failure or success to antiviral therapy. Public Library of Science 2013-06-20 /pmc/articles/PMC3688619/ /pubmed/23840641 http://dx.doi.org/10.1371/journal.pone.0067254 Text en © 2013 Murray 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Murray, John M.
Moenne-Loccoz, Rémy
Velay, Aurélie
Habersetzer, François
Doffoël, Michel
Gut, Jean-Pierre
Fofana, Isabel
Zeisel, Mirjam B.
Stoll-Keller, Françoise
Baumert, Thomas F.
Schvoerer, Evelyne
Genotype 1 Hepatitis C Virus Envelope Features That Determine Antiviral Response Assessed through Optimal Covariance Networks
title Genotype 1 Hepatitis C Virus Envelope Features That Determine Antiviral Response Assessed through Optimal Covariance Networks
title_full Genotype 1 Hepatitis C Virus Envelope Features That Determine Antiviral Response Assessed through Optimal Covariance Networks
title_fullStr Genotype 1 Hepatitis C Virus Envelope Features That Determine Antiviral Response Assessed through Optimal Covariance Networks
title_full_unstemmed Genotype 1 Hepatitis C Virus Envelope Features That Determine Antiviral Response Assessed through Optimal Covariance Networks
title_short Genotype 1 Hepatitis C Virus Envelope Features That Determine Antiviral Response Assessed through Optimal Covariance Networks
title_sort genotype 1 hepatitis c virus envelope features that determine antiviral response assessed through optimal covariance networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3688619/
https://www.ncbi.nlm.nih.gov/pubmed/23840641
http://dx.doi.org/10.1371/journal.pone.0067254
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