Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.
US Military HIV Research Program, Silver Spring, Maryland, United States of America.
PLoS Comput Biol. 2015 Feb 3;11(2):e1003973. doi: 10.1371/journal.pcbi.1003973. eCollection 2015 Feb.
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.
RV144 临床试验显示,一种疫苗方案具有一定的效果,可估计对低风险泰国志愿者预防 HIV-1 感染的疫苗效力(VE)为 31%。疫苗诱导的免疫反应的影响可以通过筛分析 HIV-1 突破感染(接种疫苗和安慰剂的受感染者)来研究。通过对 HIV-1 突破病毒的基因组进行 V1/V2 靶向比较,确定了疫苗组和安慰剂组之间存在两个 V2 氨基酸位点的差异。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“特征”和 119 个 k-mer,它们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 RV144 疫苗的区域(Env-gp120、Gag 和 Pro)。Env-gp120 中的 9 个特征位点在已知的抗体相关位点上显著富集(p = 0.0021)。特别是,第三可变环(V3)中的 317 位点与抗体识别的热点重叠,而 369 和 424 位点与 CD4 结合位点中和有关。鉴定的特征位点与基因组中其他位点的显著共变(平均值为 32.1)高于非特征位点(平均值为 0.9)(p < 0.0001),表明特征位点具有功能和/或结构相关性。由于特征位点没有优先限制在疫苗免疫原上,并且大多数关联在进行多次测试校正后并不显著,因此我们预测很少有遗传差异与 RV144 疫苗诱导的免疫压力有很强的联系。除了介绍 RV144 试验中突破感染的全基因组分析的第一个结果外,这项工作还描述了一套统计方法和工具,适用于分析针对不同病原体的一般疫苗功效试验中的突破感染基因组。
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