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In Search of Covariates of HIV-1 Subtype B Spread in the United States—A Cautionary Tale of Large-Scale Bayesian Phylogeography

Infections with HIV-1 group M subtype B viruses account for the majority of the HIV epidemic in the Western world. Phylogeographic studies have placed the introduction of subtype B in the United States in New York around 1970, where it grew into a major source of spread. Currently, it is estimated t...

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Autores principales: Hong, Samuel L., Dellicour, Simon, Vrancken, Bram, Suchard, Marc A., Pyne, Michael T., Hillyard, David R., Lemey, Philippe, Baele, Guy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7077180/
https://www.ncbi.nlm.nih.gov/pubmed/32033422
http://dx.doi.org/10.3390/v12020182
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author Hong, Samuel L.
Dellicour, Simon
Vrancken, Bram
Suchard, Marc A.
Pyne, Michael T.
Hillyard, David R.
Lemey, Philippe
Baele, Guy
author_facet Hong, Samuel L.
Dellicour, Simon
Vrancken, Bram
Suchard, Marc A.
Pyne, Michael T.
Hillyard, David R.
Lemey, Philippe
Baele, Guy
author_sort Hong, Samuel L.
collection PubMed
description Infections with HIV-1 group M subtype B viruses account for the majority of the HIV epidemic in the Western world. Phylogeographic studies have placed the introduction of subtype B in the United States in New York around 1970, where it grew into a major source of spread. Currently, it is estimated that over one million people are living with HIV in the US and that most are infected with subtype B variants. Here, we aim to identify the drivers of HIV-1 subtype B dispersal in the United States by analyzing a collection of 23,588 pol sequences, collected for drug resistance testing from 45 states during 2004–2011. To this end, we introduce a workflow to reduce this large collection of data to more computationally-manageable sample sizes and apply the BEAST framework to test which covariates associate with the spread of HIV-1 across state borders. Our results show that we are able to consistently identify certain predictors of spread under reasonable run times across datasets of up to 10,000 sequences. However, the general lack of phylogenetic structure and the high uncertainty associated with HIV trees make it difficult to interpret the epidemiological relevance of the drivers of spread we are able to identify. While the workflow we present here could be applied to other virus datasets of a similar scale, the characteristic star-like shape of HIV-1 phylogenies poses a serious obstacle to reconstructing a detailed evolutionary and spatial history for HIV-1 subtype B in the US.
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spelling pubmed-70771802020-03-20 In Search of Covariates of HIV-1 Subtype B Spread in the United States—A Cautionary Tale of Large-Scale Bayesian Phylogeography Hong, Samuel L. Dellicour, Simon Vrancken, Bram Suchard, Marc A. Pyne, Michael T. Hillyard, David R. Lemey, Philippe Baele, Guy Viruses Article Infections with HIV-1 group M subtype B viruses account for the majority of the HIV epidemic in the Western world. Phylogeographic studies have placed the introduction of subtype B in the United States in New York around 1970, where it grew into a major source of spread. Currently, it is estimated that over one million people are living with HIV in the US and that most are infected with subtype B variants. Here, we aim to identify the drivers of HIV-1 subtype B dispersal in the United States by analyzing a collection of 23,588 pol sequences, collected for drug resistance testing from 45 states during 2004–2011. To this end, we introduce a workflow to reduce this large collection of data to more computationally-manageable sample sizes and apply the BEAST framework to test which covariates associate with the spread of HIV-1 across state borders. Our results show that we are able to consistently identify certain predictors of spread under reasonable run times across datasets of up to 10,000 sequences. However, the general lack of phylogenetic structure and the high uncertainty associated with HIV trees make it difficult to interpret the epidemiological relevance of the drivers of spread we are able to identify. While the workflow we present here could be applied to other virus datasets of a similar scale, the characteristic star-like shape of HIV-1 phylogenies poses a serious obstacle to reconstructing a detailed evolutionary and spatial history for HIV-1 subtype B in the US. MDPI 2020-02-05 /pmc/articles/PMC7077180/ /pubmed/32033422 http://dx.doi.org/10.3390/v12020182 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Hong, Samuel L.
Dellicour, Simon
Vrancken, Bram
Suchard, Marc A.
Pyne, Michael T.
Hillyard, David R.
Lemey, Philippe
Baele, Guy
In Search of Covariates of HIV-1 Subtype B Spread in the United States—A Cautionary Tale of Large-Scale Bayesian Phylogeography
title In Search of Covariates of HIV-1 Subtype B Spread in the United States—A Cautionary Tale of Large-Scale Bayesian Phylogeography
title_full In Search of Covariates of HIV-1 Subtype B Spread in the United States—A Cautionary Tale of Large-Scale Bayesian Phylogeography
title_fullStr In Search of Covariates of HIV-1 Subtype B Spread in the United States—A Cautionary Tale of Large-Scale Bayesian Phylogeography
title_full_unstemmed In Search of Covariates of HIV-1 Subtype B Spread in the United States—A Cautionary Tale of Large-Scale Bayesian Phylogeography
title_short In Search of Covariates of HIV-1 Subtype B Spread in the United States—A Cautionary Tale of Large-Scale Bayesian Phylogeography
title_sort in search of covariates of hiv-1 subtype b spread in the united states—a cautionary tale of large-scale bayesian phylogeography
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7077180/
https://www.ncbi.nlm.nih.gov/pubmed/32033422
http://dx.doi.org/10.3390/v12020182
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