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Comprehensive sieve analysis of breakthrough HIV-1 sequences in the RV144 vaccine efficacy trial.

Authors :
Paul T Edlefsen
Morgane Rolland
Tomer Hertz
Sodsai Tovanabutra
Andrew J Gartland
Allan C deCamp
Craig A Magaret
Hasan Ahmed
Raphael Gottardo
Michal Juraska
Connor McCoy
Brendan B Larsen
Eric Sanders-Buell
Chris Carrico
Sergey Menis
Gustavo H Kijak
Meera Bose
RV144 Sequencing Team
Miguel A Arroyo
Robert J O'Connell
Sorachai Nitayaphan
Punnee Pitisuttithum
Jaranit Kaewkungwal
Supachai Rerks-Ngarm
Merlin L Robb
Tatsiana Kirys
Ivelin S Georgiev
Peter D Kwong
Konrad Scheffler
Sergei L Kosakovsky Pond
Jonathan M Carlson
Nelson L Michael
William R Schief
James I Mullins
Jerome H Kim
Peter B Gilbert
Source :
PLoS Computational Biology, Vol 11, Iss 2, p e1003973 (2015)
Publication Year :
2015
Publisher :
Public Library of Science (PLoS), 2015.

Abstract

The RV144 clinical trial showed the partial efficacy of a vaccine regimen with an estimated vaccine efficacy (VE) of 31% for protecting low-risk Thai volunteers against acquisition of HIV-1. The impact of vaccine-induced immune responses can be investigated through sieve analysis of HIV-1 breakthrough infections (infected vaccine and placebo recipients). A V1/V2-targeted comparison of the genomes of HIV-1 breakthrough viruses identified two V2 amino acid sites that differed between the vaccine and placebo groups. Here we extended the V1/V2 analysis to the entire HIV-1 genome using an array of methods based on individual sites, k-mers and genes/proteins. We identified 56 amino acid sites or "signatures" and 119 k-mers that differed between the vaccine and placebo groups. Of those, 19 sites and 38 k-mers were located in the regions comprising the RV144 vaccine (Env-gp120, Gag, and Pro). The nine signature sites in Env-gp120 were significantly enriched for known antibody-associated sites (p = 0.0021). In particular, site 317 in the third variable loop (V3) overlapped with a hotspot of antibody recognition, and sites 369 and 424 were linked to CD4 binding site neutralization. The identified signature sites significantly covaried with other sites across the genome (mean = 32.1) more than did non-signature sites (mean = 0.9) (p < 0.0001), suggesting functional and/or structural relevance of the signature sites. Since signature sites were not preferentially restricted to the vaccine immunogens and because most of the associations were insignificant following correction for multiple testing, we predict that few of the genetic differences are strongly linked to the RV144 vaccine-induced immune pressure. In addition to presenting results of the first complete-genome analysis of the breakthrough infections in the RV144 trial, this work describes a set of statistical methods and tools applicable to analysis of breakthrough infection genomes in general vaccine efficacy trials for diverse pathogens.

Subjects

Subjects :
Biology (General)
QH301-705.5

Details

Language :
English
ISSN :
1553734X and 15537358
Volume :
11
Issue :
2
Database :
Directory of Open Access Journals
Journal :
PLoS Computational Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.3c48e8cc0f7048819758a015ac56625a
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pcbi.1003973