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Modelling the impact of protein-kinase R allelic variant on HIV biomarkers trajectories by means of latent class mixed models

This paper is based on a retrospective longitudinal study on people living with HIV under antiretroviral treatment (ART) where allelic variants (either heterozygous CT genotype or homozygous CC genotype) have been evaluated at position −168 of the promoter region of the protein kinase R (−168/PKR)....

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Autores principales: Brombin, Chiara, Bagaglio, Sabrina, Cugnata, Federica, Castagna, Antonella, Uberti-Foppa, Caterina, Salpietro, Stefania, Di Serio, Clelia, Morsica, Giulia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9633692/
https://www.ncbi.nlm.nih.gov/pubmed/36329104
http://dx.doi.org/10.1038/s41598-022-23289-4
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author Brombin, Chiara
Bagaglio, Sabrina
Cugnata, Federica
Castagna, Antonella
Uberti-Foppa, Caterina
Salpietro, Stefania
Di Serio, Clelia
Morsica, Giulia
author_facet Brombin, Chiara
Bagaglio, Sabrina
Cugnata, Federica
Castagna, Antonella
Uberti-Foppa, Caterina
Salpietro, Stefania
Di Serio, Clelia
Morsica, Giulia
author_sort Brombin, Chiara
collection PubMed
description This paper is based on a retrospective longitudinal study on people living with HIV under antiretroviral treatment (ART) where allelic variants (either heterozygous CT genotype or homozygous CC genotype) have been evaluated at position −168 of the promoter region of the protein kinase R (−168/PKR). In general, antiviral effects of interferon are partially mediated by a RNA-dependent protein kinase (PKR) that, once activated, inhibits protein synthesis. Indeed, activation of PKR response can inhibit HIV replication. To explore the role of allelic variants in shaping dynamics of commonly monitored HIV biomarkers, CD4 cells, CD8 cells and HIV-load were modelled within a latent class mixed model (LCMM) to account for participants’ heterogeneity over time. The estimated models identified two sub-groups from CD4 and HIV-load dynamics, revealing better outcomes for subgroups of participants with the heterozygous CT genotype. Heterozygous CT subjects in one of the two identified subgroups exhibited higher increase of CD4 cells and more marked decrease of HIV-load, over time, with respect to the homozygous CC subjects assigned to the same group.
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spelling pubmed-96336922022-11-05 Modelling the impact of protein-kinase R allelic variant on HIV biomarkers trajectories by means of latent class mixed models Brombin, Chiara Bagaglio, Sabrina Cugnata, Federica Castagna, Antonella Uberti-Foppa, Caterina Salpietro, Stefania Di Serio, Clelia Morsica, Giulia Sci Rep Article This paper is based on a retrospective longitudinal study on people living with HIV under antiretroviral treatment (ART) where allelic variants (either heterozygous CT genotype or homozygous CC genotype) have been evaluated at position −168 of the promoter region of the protein kinase R (−168/PKR). In general, antiviral effects of interferon are partially mediated by a RNA-dependent protein kinase (PKR) that, once activated, inhibits protein synthesis. Indeed, activation of PKR response can inhibit HIV replication. To explore the role of allelic variants in shaping dynamics of commonly monitored HIV biomarkers, CD4 cells, CD8 cells and HIV-load were modelled within a latent class mixed model (LCMM) to account for participants’ heterogeneity over time. The estimated models identified two sub-groups from CD4 and HIV-load dynamics, revealing better outcomes for subgroups of participants with the heterozygous CT genotype. Heterozygous CT subjects in one of the two identified subgroups exhibited higher increase of CD4 cells and more marked decrease of HIV-load, over time, with respect to the homozygous CC subjects assigned to the same group. Nature Publishing Group UK 2022-11-03 /pmc/articles/PMC9633692/ /pubmed/36329104 http://dx.doi.org/10.1038/s41598-022-23289-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Brombin, Chiara
Bagaglio, Sabrina
Cugnata, Federica
Castagna, Antonella
Uberti-Foppa, Caterina
Salpietro, Stefania
Di Serio, Clelia
Morsica, Giulia
Modelling the impact of protein-kinase R allelic variant on HIV biomarkers trajectories by means of latent class mixed models
title Modelling the impact of protein-kinase R allelic variant on HIV biomarkers trajectories by means of latent class mixed models
title_full Modelling the impact of protein-kinase R allelic variant on HIV biomarkers trajectories by means of latent class mixed models
title_fullStr Modelling the impact of protein-kinase R allelic variant on HIV biomarkers trajectories by means of latent class mixed models
title_full_unstemmed Modelling the impact of protein-kinase R allelic variant on HIV biomarkers trajectories by means of latent class mixed models
title_short Modelling the impact of protein-kinase R allelic variant on HIV biomarkers trajectories by means of latent class mixed models
title_sort modelling the impact of protein-kinase r allelic variant on hiv biomarkers trajectories by means of latent class mixed models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9633692/
https://www.ncbi.nlm.nih.gov/pubmed/36329104
http://dx.doi.org/10.1038/s41598-022-23289-4
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