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Modeling Drug Resistance Emergence and Transmission in HIV-1 in the UK
A deeper understanding of HIV-1 transmission and drug resistance mechanisms can lead to improvements in current treatment policies. However, the rates at which HIV-1 drug resistance mutations (DRMs) are acquired and which transmitted DRMs persist are multi-factorial and vary considerably between dif...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10304371/ https://www.ncbi.nlm.nih.gov/pubmed/37376544 http://dx.doi.org/10.3390/v15061244 |
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author | Zhukova, Anna Dunn, David Gascuel, Olivier |
author_facet | Zhukova, Anna Dunn, David Gascuel, Olivier |
author_sort | Zhukova, Anna |
collection | PubMed |
description | A deeper understanding of HIV-1 transmission and drug resistance mechanisms can lead to improvements in current treatment policies. However, the rates at which HIV-1 drug resistance mutations (DRMs) are acquired and which transmitted DRMs persist are multi-factorial and vary considerably between different mutations. We develop a method for the estimation of drug resistance acquisition and transmission patterns. The method uses maximum likelihood ancestral character reconstruction informed by treatment roll-out dates and allows for the analysis of very large datasets. We apply our method to transmission trees reconstructed on the data obtained from the UK HIV Drug Resistance Database to make predictions for known DRMs. Our results show important differences between DRMs, in particular between polymorphic and non-polymorphic DRMs and between the B and C subtypes. Our estimates of reversion times, based on a very large number of sequences, are compatible but more accurate than those already available in the literature, with narrower confidence intervals. We consistently find that large resistance clusters are associated with polymorphic DRMs and DRMs with long loss times, which require special surveillance. As in other high-income countries (e.g., Switzerland), the prevalence of sequences with DRMs is decreasing, but among these, the fraction of transmitted resistance is clearly increasing compared to the fraction of acquired resistance mutations. All this indicates that efforts to monitor these mutations and the emergence of resistance clusters in the population must be maintained in the long term. |
format | Online Article Text |
id | pubmed-10304371 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103043712023-06-29 Modeling Drug Resistance Emergence and Transmission in HIV-1 in the UK Zhukova, Anna Dunn, David Gascuel, Olivier Viruses Article A deeper understanding of HIV-1 transmission and drug resistance mechanisms can lead to improvements in current treatment policies. However, the rates at which HIV-1 drug resistance mutations (DRMs) are acquired and which transmitted DRMs persist are multi-factorial and vary considerably between different mutations. We develop a method for the estimation of drug resistance acquisition and transmission patterns. The method uses maximum likelihood ancestral character reconstruction informed by treatment roll-out dates and allows for the analysis of very large datasets. We apply our method to transmission trees reconstructed on the data obtained from the UK HIV Drug Resistance Database to make predictions for known DRMs. Our results show important differences between DRMs, in particular between polymorphic and non-polymorphic DRMs and between the B and C subtypes. Our estimates of reversion times, based on a very large number of sequences, are compatible but more accurate than those already available in the literature, with narrower confidence intervals. We consistently find that large resistance clusters are associated with polymorphic DRMs and DRMs with long loss times, which require special surveillance. As in other high-income countries (e.g., Switzerland), the prevalence of sequences with DRMs is decreasing, but among these, the fraction of transmitted resistance is clearly increasing compared to the fraction of acquired resistance mutations. All this indicates that efforts to monitor these mutations and the emergence of resistance clusters in the population must be maintained in the long term. MDPI 2023-05-25 /pmc/articles/PMC10304371/ /pubmed/37376544 http://dx.doi.org/10.3390/v15061244 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhukova, Anna Dunn, David Gascuel, Olivier Modeling Drug Resistance Emergence and Transmission in HIV-1 in the UK |
title | Modeling Drug Resistance Emergence and Transmission in HIV-1 in the UK |
title_full | Modeling Drug Resistance Emergence and Transmission in HIV-1 in the UK |
title_fullStr | Modeling Drug Resistance Emergence and Transmission in HIV-1 in the UK |
title_full_unstemmed | Modeling Drug Resistance Emergence and Transmission in HIV-1 in the UK |
title_short | Modeling Drug Resistance Emergence and Transmission in HIV-1 in the UK |
title_sort | modeling drug resistance emergence and transmission in hiv-1 in the uk |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10304371/ https://www.ncbi.nlm.nih.gov/pubmed/37376544 http://dx.doi.org/10.3390/v15061244 |
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