Evidence map›Paper›PMID 24717647›Full record

ArticlePloS one2014

Estimating the timing of mother-to-child transmission of the human immunodeficiency virus type 1 using a viral molecular evolution model.

Antoine Chaillon, Tanawan Samleerat, Faustine Zoveda, Sébastien Ballesteros, Alain Moreau, Nicole Ngo-Giang-Huong, Gonzague Jourdain, Sara Gianella, Marc Lallemant, Frantz Depaulis and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.9field-weighted citation impact, top 29% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 12 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 5 institutions in 3 countries.

Antoine ChaillonUniversité François-Rabelais, Institut National de la Santé et de la Recherche Médicale - Unité 966 et Laboratoire de Virologie, Centre Hopsitalier Universitaire Bretonneau, Tours, France; University of California San Diego, Department of Pathology, San Diego, California, United States of America.
Tanawan SamleeratUniversité François-Rabelais, Institut National de la Santé et de la Recherche Médicale - Unité 966 et Laboratoire de Virologie, Centre Hopsitalier Universitaire Bretonneau, Tours, France; Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand.
Faustine ZovedaLaboratoire Ecologie et Evolution, Centre National de la Recherche Scientifique - Unité Mixte de Recherche 7625- Ecole Normale Supérieure, Paris, France.
Sébastien BallesterosLaboratoire Ecologie et Evolution, Centre National de la Recherche Scientifique - Unité Mixte de Recherche 7625- Ecole Normale Supérieure, Paris, France.
Alain MoreauUniversité François-Rabelais, Institut National de la Santé et de la Recherche Médicale - Unité 966 et Laboratoire de Virologie, Centre Hopsitalier Universitaire Bretonneau, Tours, France.
Nicole Ngo-Giang-HuongInstitut de Recherche pour le Développement, Chiang Mai, Thailand; Harvard School of Public Health, Department of Immunology and Infectious Diseases, Boston, Massachusetts, United States of America.
Gonzague JourdainInstitut de Recherche pour le Développement, Chiang Mai, Thailand; Harvard School of Public Health, Department of Immunology and Infectious Diseases, Boston, Massachusetts, United States of America.
Sara GianellaUniversity of California San Diego, Department of Pathology, San Diego, California, United States of America.
Marc LallemantInstitut de Recherche pour le Développement, Chiang Mai, Thailand; Harvard School of Public Health, Department of Immunology and Infectious Diseases, Boston, Massachusetts, United States of America.
Frantz DepaulisLaboratoire Ecologie et Evolution, Centre National de la Recherche Scientifique - Unité Mixte de Recherche 7625- Ecole Normale Supérieure, Paris, France.
Francis BarinUniversité François-Rabelais, Institut National de la Santé et de la Recherche Médicale - Unité 966 et Laboratoire de Virologie, Centre Hopsitalier Universitaire Bretonneau, Tours, France.
Ecologie & Evolution · FRHarvard University · USInserm · FRUniversity of California, San Diego · USChiang Mai University · TH

Funding

SHORT ZDV COURSE TO PREVENT PERINATAL HIV IN THAILANDR01HD033326 · NICHD · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI LALLEMANT, MARC J · 1996 to 2000
$368k
NICHD NIH HHS 5 R01 HD 33326NICHD NIH HHS R01 HD033326
6 · The paper itself

Abstract

backgroundMother-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. MATERIALS AND

methodsSix-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.

resultsFour 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.

conclusionsThe 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.

Indexed as

Directed Molecular EvolutionInfectious Disease Transmission, VerticalModels, BiologicalBayes TheoremChildFemaleHIV-1HumansMarkov ChainsMonte Carlo MethodPhylogenyPregnancySequence Analysis, DNATime Factors

Identifiers

PMID24717647
PMCPMC3981669
OpenAlexW1966795361

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.