Estimating the timing of mother-to-child transmission of the human immunodeficiency virus type 1 using a viral molecular evolution model
Mother-to-child transmission (MTCT) is responsible for most pediatric HIV-1 infections worldwide. It can occur during pregnancy, labor, or breastfeeding. Numerous studies have used coalescent and molecular clock methods to understand the epidemic history of HIV-1, but the timing of vertical transmis...
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creator | Chaillon, Antoine Samleerat, Tanawan Zoveda, Faustine Ballesteros, Sébastien Moreau, Alain Ngo-Giang-Huong, Nicole Jourdain, Gonzague Gianella, Sara Lallemant, Marc Depaulis, Frantz Barin, Francis |
description | Mother-to-child transmission (MTCT) is responsible for most pediatric HIV-1 infections worldwide. It can occur during pregnancy, labor, or breastfeeding. Numerous studies have used coalescent and molecular clock methods to understand the epidemic history of HIV-1, but the timing of vertical transmission has not been studied using these methods. Taking advantage of the constant accumulation of HIV genetic variation over time and using longitudinally sampled viral sequences, we used a coalescent approach to investigate the timing of MTCT.
Six-hundred and twenty-two clonal env sequences from the RNA and DNA viral population were longitudinally sampled from nine HIV-1 infected mother-and-child pairs [range: 277-1034 days]. For each transmission pair, timing of MTCT was determined using a coalescent-based model within a Bayesian statistical framework. Results were compared with available estimates of MTCT timing obtained with the classic biomedical approach based on serial HIV DNA detection by PCR assays.
Four children were infected during pregnancy, whereas the remaining five children were infected at time of delivery. For eight out of nine pairs, results were consistent with the transmission periods assessed by standard PCR-based assay. The discordance in the remaining case was likely confused by co-infection, with simultaneous introduction of multiple maternal viral variants at the time of delivery.
The study provided the opportunity to validate the Bayesian coalescent approach that determines the timing of MTCT of HIV-1. It illustrates the power of population genetics approaches to reliably estimate the timing of transmission events and deepens our knowledge about the dynamics of viral evolution in HIV-infected children, accounting for the complexity of multiple transmission events. |
doi_str_mv | 10.1371/journal.pone.0090421 |
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Six-hundred and twenty-two clonal env sequences from the RNA and DNA viral population were longitudinally sampled from nine HIV-1 infected mother-and-child pairs [range: 277-1034 days]. For each transmission pair, timing of MTCT was determined using a coalescent-based model within a Bayesian statistical framework. Results were compared with available estimates of MTCT timing obtained with the classic biomedical approach based on serial HIV DNA detection by PCR assays.
Four children were infected during pregnancy, whereas the remaining five children were infected at time of delivery. For eight out of nine pairs, results were consistent with the transmission periods assessed by standard PCR-based assay. The discordance in the remaining case was likely confused by co-infection, with simultaneous introduction of multiple maternal viral variants at the time of delivery.
The study provided the opportunity to validate the Bayesian coalescent approach that determines the timing of MTCT of HIV-1. It illustrates the power of population genetics approaches to reliably estimate the timing of transmission events and deepens our knowledge about the dynamics of viral evolution in HIV-infected children, accounting for the complexity of multiple transmission events.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0090421</identifier><identifier>PMID: 24717647</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Acquired immune deficiency syndrome ; AIDS ; Antiretroviral drugs ; Babies ; Bayes Theorem ; Bayesian analysis ; Biology and Life Sciences ; Biomedical materials ; Breast feeding ; Child ; Children ; Deoxyribonucleic acid ; Directed Molecular Evolution ; Discordance ; Disease prevention ; Disease transmission ; DNA ; DNA polymerase ; Epidemics ; Epidemiology ; Evolution ; Female ; Gene sequencing ; Genetic aspects ; Genetic diversity ; Genetics ; HIV ; HIV infection in children ; HIV-1 - genetics ; HIV-1 - physiology ; Human immunodeficiency virus ; Humans ; Immunology ; Infections ; Infectious Disease Transmission, Vertical ; Infectious diseases ; Markov Chains ; Mathematical models ; Medicine and health sciences ; Models, Biological ; Molecular evolution ; Monte Carlo Method ; Mothers ; Nucleotide sequence ; Phylogenetics ; Phylogeny ; Polymerase chain reaction ; Population (statistical) ; Population genetics ; Pregnancy ; Prevention ; Public health ; Ribonucleic acid ; RNA ; Sequence Analysis, DNA ; Time Factors ; Viruses</subject><ispartof>PloS one, 2014-04, Vol.9 (4), p.e90421-e90421</ispartof><rights>COPYRIGHT 2014 Public Library of Science</rights><rights>2014 Chaillon et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2014 Chaillon et al 2014 Chaillon et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-d20e7d0290efb3a97867dfb1ef88d8df1f68ec0af14bdf0714d08944ace2d7a03</citedby><cites>FETCH-LOGICAL-c692t-d20e7d0290efb3a97867dfb1ef88d8df1f68ec0af14bdf0714d08944ace2d7a03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3981669/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3981669/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2095,2914,23846,27903,27904,53769,53771,79346,79347</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24717647$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Vartanian, Jean-Pierre</contributor><creatorcontrib>Chaillon, Antoine</creatorcontrib><creatorcontrib>Samleerat, Tanawan</creatorcontrib><creatorcontrib>Zoveda, Faustine</creatorcontrib><creatorcontrib>Ballesteros, Sébastien</creatorcontrib><creatorcontrib>Moreau, Alain</creatorcontrib><creatorcontrib>Ngo-Giang-Huong, Nicole</creatorcontrib><creatorcontrib>Jourdain, Gonzague</creatorcontrib><creatorcontrib>Gianella, Sara</creatorcontrib><creatorcontrib>Lallemant, Marc</creatorcontrib><creatorcontrib>Depaulis, Frantz</creatorcontrib><creatorcontrib>Barin, Francis</creatorcontrib><title>Estimating the timing of mother-to-child transmission of the human immunodeficiency virus type 1 using a viral molecular evolution model</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Mother-to-child transmission (MTCT) is responsible for most pediatric HIV-1 infections worldwide. It can occur during pregnancy, labor, or breastfeeding. Numerous studies have used coalescent and molecular clock methods to understand the epidemic history of HIV-1, but the timing of vertical transmission has not been studied using these methods. Taking advantage of the constant accumulation of HIV genetic variation over time and using longitudinally sampled viral sequences, we used a coalescent approach to investigate the timing of MTCT.
Six-hundred and twenty-two clonal env sequences from the RNA and DNA viral population were longitudinally sampled from nine HIV-1 infected mother-and-child pairs [range: 277-1034 days]. For each transmission pair, timing of MTCT was determined using a coalescent-based model within a Bayesian statistical framework. Results were compared with available estimates of MTCT timing obtained with the classic biomedical approach based on serial HIV DNA detection by PCR assays.
Four children were infected during pregnancy, whereas the remaining five children were infected at time of delivery. For eight out of nine pairs, results were consistent with the transmission periods assessed by standard PCR-based assay. The discordance in the remaining case was likely confused by co-infection, with simultaneous introduction of multiple maternal viral variants at the time of delivery.
The study provided the opportunity to validate the Bayesian coalescent approach that determines the timing of MTCT of HIV-1. It illustrates the power of population genetics approaches to reliably estimate the timing of transmission events and deepens our knowledge about the dynamics of viral evolution in HIV-infected children, accounting for the complexity of multiple transmission events.</description><subject>Acquired immune deficiency syndrome</subject><subject>AIDS</subject><subject>Antiretroviral drugs</subject><subject>Babies</subject><subject>Bayes Theorem</subject><subject>Bayesian analysis</subject><subject>Biology and Life Sciences</subject><subject>Biomedical materials</subject><subject>Breast feeding</subject><subject>Child</subject><subject>Children</subject><subject>Deoxyribonucleic acid</subject><subject>Directed Molecular Evolution</subject><subject>Discordance</subject><subject>Disease prevention</subject><subject>Disease transmission</subject><subject>DNA</subject><subject>DNA polymerase</subject><subject>Epidemics</subject><subject>Epidemiology</subject><subject>Evolution</subject><subject>Female</subject><subject>Gene sequencing</subject><subject>Genetic aspects</subject><subject>Genetic diversity</subject><subject>Genetics</subject><subject>HIV</subject><subject>HIV infection in children</subject><subject>HIV-1 - genetics</subject><subject>HIV-1 - physiology</subject><subject>Human immunodeficiency virus</subject><subject>Humans</subject><subject>Immunology</subject><subject>Infections</subject><subject>Infectious Disease Transmission, Vertical</subject><subject>Infectious diseases</subject><subject>Markov Chains</subject><subject>Mathematical models</subject><subject>Medicine and health sciences</subject><subject>Models, Biological</subject><subject>Molecular evolution</subject><subject>Monte Carlo Method</subject><subject>Mothers</subject><subject>Nucleotide sequence</subject><subject>Phylogenetics</subject><subject>Phylogeny</subject><subject>Polymerase chain reaction</subject><subject>Population (statistical)</subject><subject>Population genetics</subject><subject>Pregnancy</subject><subject>Prevention</subject><subject>Public health</subject><subject>Ribonucleic acid</subject><subject>RNA</subject><subject>Sequence Analysis, DNA</subject><subject>Time 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the timing of mother-to-child transmission of the human immunodeficiency virus type 1 using a viral molecular evolution model</title><author>Chaillon, Antoine ; Samleerat, Tanawan ; Zoveda, Faustine ; Ballesteros, Sébastien ; Moreau, Alain ; Ngo-Giang-Huong, Nicole ; Jourdain, Gonzague ; Gianella, Sara ; Lallemant, Marc ; Depaulis, Frantz ; Barin, Francis</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-d20e7d0290efb3a97867dfb1ef88d8df1f68ec0af14bdf0714d08944ace2d7a03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Acquired immune deficiency syndrome</topic><topic>AIDS</topic><topic>Antiretroviral drugs</topic><topic>Babies</topic><topic>Bayes Theorem</topic><topic>Bayesian analysis</topic><topic>Biology and Life Sciences</topic><topic>Biomedical materials</topic><topic>Breast feeding</topic><topic>Child</topic><topic>Children</topic><topic>Deoxyribonucleic acid</topic><topic>Directed Molecular Evolution</topic><topic>Discordance</topic><topic>Disease prevention</topic><topic>Disease transmission</topic><topic>DNA</topic><topic>DNA polymerase</topic><topic>Epidemics</topic><topic>Epidemiology</topic><topic>Evolution</topic><topic>Female</topic><topic>Gene sequencing</topic><topic>Genetic aspects</topic><topic>Genetic diversity</topic><topic>Genetics</topic><topic>HIV</topic><topic>HIV infection in children</topic><topic>HIV-1 - genetics</topic><topic>HIV-1 - physiology</topic><topic>Human immunodeficiency virus</topic><topic>Humans</topic><topic>Immunology</topic><topic>Infections</topic><topic>Infectious Disease Transmission, Vertical</topic><topic>Infectious diseases</topic><topic>Markov Chains</topic><topic>Mathematical models</topic><topic>Medicine and health sciences</topic><topic>Models, Biological</topic><topic>Molecular evolution</topic><topic>Monte Carlo Method</topic><topic>Mothers</topic><topic>Nucleotide 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Marc</au><au>Depaulis, Frantz</au><au>Barin, Francis</au><au>Vartanian, Jean-Pierre</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimating the timing of mother-to-child transmission of the human immunodeficiency virus type 1 using a viral molecular evolution model</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2014-04-01</date><risdate>2014</risdate><volume>9</volume><issue>4</issue><spage>e90421</spage><epage>e90421</epage><pages>e90421-e90421</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Mother-to-child transmission (MTCT) is responsible for most pediatric HIV-1 infections worldwide. It can occur during pregnancy, labor, or breastfeeding. Numerous studies have used coalescent and molecular clock methods to understand the epidemic history of HIV-1, but the timing of vertical transmission has not been studied using these methods. Taking advantage of the constant accumulation of HIV genetic variation over time and using longitudinally sampled viral sequences, we used a coalescent approach to investigate the timing of MTCT.
Six-hundred and twenty-two clonal env sequences from the RNA and DNA viral population were longitudinally sampled from nine HIV-1 infected mother-and-child pairs [range: 277-1034 days]. For each transmission pair, timing of MTCT was determined using a coalescent-based model within a Bayesian statistical framework. Results were compared with available estimates of MTCT timing obtained with the classic biomedical approach based on serial HIV DNA detection by PCR assays.
Four children were infected during pregnancy, whereas the remaining five children were infected at time of delivery. For eight out of nine pairs, results were consistent with the transmission periods assessed by standard PCR-based assay. The discordance in the remaining case was likely confused by co-infection, with simultaneous introduction of multiple maternal viral variants at the time of delivery.
The study provided the opportunity to validate the Bayesian coalescent approach that determines the timing of MTCT of HIV-1. It illustrates the power of population genetics approaches to reliably estimate the timing of transmission events and deepens our knowledge about the dynamics of viral evolution in HIV-infected children, accounting for the complexity of multiple transmission events.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>24717647</pmid><doi>10.1371/journal.pone.0090421</doi><oa>free_for_read</oa></addata></record> |
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source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Public Library of Science (PLoS); PubMed Central; Free Full-Text Journals in Chemistry |
subjects | Acquired immune deficiency syndrome AIDS Antiretroviral drugs Babies Bayes Theorem Bayesian analysis Biology and Life Sciences Biomedical materials Breast feeding Child Children Deoxyribonucleic acid Directed Molecular Evolution Discordance Disease prevention Disease transmission DNA DNA polymerase Epidemics Epidemiology Evolution Female Gene sequencing Genetic aspects Genetic diversity Genetics HIV HIV infection in children HIV-1 - genetics HIV-1 - physiology Human immunodeficiency virus Humans Immunology Infections Infectious Disease Transmission, Vertical Infectious diseases Markov Chains Mathematical models Medicine and health sciences Models, Biological Molecular evolution Monte Carlo Method Mothers Nucleotide sequence Phylogenetics Phylogeny Polymerase chain reaction Population (statistical) Population genetics Pregnancy Prevention Public health Ribonucleic acid RNA Sequence Analysis, DNA Time Factors Viruses |
title | Estimating the timing of mother-to-child transmission of the human immunodeficiency virus type 1 using a viral molecular evolution model |
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