Comprehensive sieve analysis of breakthrough HIV-1 sequences in the RV144 vaccine efficacy trial.
Comprehensive sieve analysis of breakthrough HIV-1 sequences in the RV144 vaccine efficacy trial.
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DOI：
10.1371/journal.pcbi.1003973
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发表时间：
2015-02
影响因子：
4.3
通讯作者：
Gilbert PB
中科院分区：
文献类型：
--
作者：
Edlefsen PT;Rolland M;Hertz T;Tovanabutra S;Gartland AJ;deCamp AC;Magaret CA;Ahmed H;Gottardo R;Juraska M;McCoy C;Larsen BB;Sanders-Buell E;Carrico C;Menis S;Kijak GH;Bose M;RV144 Sequencing Team;Arroyo MA;O'Connell RJ;Nitayaphan S;Pitisuttithum P;Kaewkungwal J;Rerks-Ngarm S;Robb ML;Kirys T;Georgiev IS;Kwong PD;Scheffler K;Pond SL;Carlson JM;Michael NL;Schief WR;Mullins JI;Kim JH;Gilbert PB
RV 144临床试验显示了疫苗方案的部分功效，估计疫苗功效（VE）为31%，可保护低风险泰国志愿者免受HIV-1感染。疫苗诱导的免疫应答的影响可以通过HIV-1突破性感染（感染的疫苗和安慰剂接受者）的筛选分析来研究。对HIV-1突破性病毒的基因组进行V1/V2靶向比较，发现疫苗组和安慰剂组之间有两个不同的V2氨基酸位点。在这里，我们使用基于单个位点、k-mer和基因/蛋白质的一系列方法将V1/V2分析扩展到整个HIV-1基因组。我们确定了56个氨基酸位点或“签名”和119个k-mer，这些位点在疫苗组和安慰剂组之间存在差异。其中，19个位点和38个k-mer位于包含RV 144疫苗（Env-gp 120、Gag和Pro）的区域中。Env-gp 120中的9个特征位点显著富集已知的抗体相关位点（p = 0.0021）。特别地，第三可变环（V3）中的位点317与抗体识别的热点重叠，并且位点369和424与CD 4结合位点中和连接。所鉴定的特征位点与基因组中的其他位点显著共变（平均值= 32.1），比非特征位点（平均值= 0.9）多（p < 0.0001），表明特征位点的功能和/或结构相关性。由于特征位点并不优先限于疫苗免疫原，并且由于在多次检测校正后大多数相关性都不显著，因此我们预测很少有遗传差异与RV 144疫苗诱导的免疫压力密切相关。除了介绍RV 144试验中突破性感染的首次全基因组分析结果外，这项工作还描述了一套适用于分析不同病原体的一般疫苗效力试验中突破性感染基因组的统计方法和工具。我们对感染RV 144泰国试验的一些参与者的HIV病毒的基因组进行了分析，这是第一项显示疫苗预防HIV感染的有效性的研究。我们分析了受感染的疫苗接种者和受感染的安慰剂接种者的HIV基因组，并发现了它们之间的差异。这些差异与先前研究的与HIV感染生物学相关的遗传特征相吻合，包括参与病毒免疫识别的特征。这里提出的研究结果产生了关于泰国试验中所见的部分保护机制的可检验的假设，并可能最终导致改进的疫苗。本文还提出了一个工具包的方法计算分析，可应用于其他疫苗的有效性试验。
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. We present an analysis of the genomes of the HIV viruses that infected some participants of the RV144 Thai trial, which was the first study to show efficacy of a vaccine to prevent HIV infection. We analyzed the HIV genomes of infected vaccine recipients and infected placebo recipients, and found differences between them. These differences coincide with previously-studied genetic features that are relevant to the biology of HIV infection, including features involved in immune recognition of the virus. The findings presented here generate testable hypotheses about the mechanism of the partial protection seen in the Thai trial, and may ultimately lead to improved vaccines. The article also presents a toolkit of methods for computational analyses that can be applied to other vaccine efficacy trials.
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影响因子：
3.7
作者：
Gottardo R;Bailer RT;Korber BT;Gnanakaran S;Phillips J;Shen X;Tomaras GD;Turk E;Imholte G;Eckler L;Wenschuh H;Zerweck J;Greene K;Gao H;Berman PW;Francis D;Sinangil F;Lee C;Nitayaphan S;Rerks-Ngarm S;Kaewkungwal J;Pitisuttithum P;Tartaglia J;Robb ML;Michael NL;Kim JH;Zolla-Pazner S;Haynes BF;Mascola JR;Self S;Gilbert P;Montefiori DC
通讯作者：
Montefiori DC
DOI：
10.1073/pnas.89.22.10915
发表时间：
1992-11-15
影响因子：
11.1
作者：
HENIKOFF, S;HENIKOFF, JG
通讯作者：
HENIKOFF, JG
影响因子：
4.3
作者：
Gnanakaran S;Daniels MG;Bhattacharya T;Lapedes AS;Sethi A;Li M;Tang H;Greene K;Gao H;Haynes BF;Cohen MS;Shaw GM;Seaman MS;Kumar A;Gao F;Montefiori DC;Korber B
通讯作者：
Korber B
影响因子：
1.5
作者：
Gilbert, PB;Novitsky, V;Essex, M
通讯作者：
Essex, M
HIV-1 疫苗功效试验的免疫相关分析。
DOI：
10.1056/nejmoa1113425
发表时间：
2012-04-05
期刊：
The New England journal of medicine
影响因子：
--
作者：
Haynes BF;Gilbert PB;McElrath MJ;Zolla-Pazner S;Tomaras GD;Alam SM;Evans DT;Montefiori DC;Karnasuta C;Sutthent R;Liao HX;DeVico AL;Lewis GK;Williams C;Pinter A;Fong Y;Janes H;DeCamp A;Huang Y;Rao M;Billings E;Karasavvas N;Robb ML;Ngauy V;de Souza MS;Paris R;Ferrari G;Bailer RT;Soderberg KA;Andrews C;Berman PW;Frahm N;De Rosa SC;Alpert MD;Yates NL;Shen X;Koup RA;Pitisuttithum P;Kaewkungwal J;Nitayaphan S;Rerks-Ngarm S;Michael NL;Kim JH
通讯作者：
Kim JH