Modeling HIV Escape from Neutralizing Antibody Respones

描述(由申请人提供)：艾滋病毒可以在体内快速逃避中和抗体反应。虽然逃避有助于病毒在感染患者体内的持续，但逃避中和意味着抗体反应对病毒施加了显著的选择性压力。因此，疫苗增强的体液反应在预防感染方面可能是有效的，因为感染病毒的小群体不能快速进化。一种有效的疫苗还将能够诱导显著的异源中和反应。虽然艾滋病毒通常对艾滋病毒阳性患者血清的中和反应具有抵抗力，但一些人安装了广泛反应的中和反应最近高通量分析方法的出现，加上对艾滋病毒-1包膜基因全长克隆测序的能力，使定量分析自体和异源中和反应及其与病毒遗传变异的关系成为可能。我们建议量化HIV-1包膜中的点突变和插入/缺失在病毒逃逸中的作用，这是基于来自原发HIV感染者的数据。中和抗体反应将使用快速、高重复性的重组病毒/报告基因分析来测量，包膜的遗传变异将使用基于群体和克隆测序的方法来测量。对这些数据的分析提出了一些统计挑战。我们将开发统计模型，以(A)获得对自体中和抗体反应的动态和病毒逃逸模式的定量描述，以及(B)量化患者血清之间和异源中和病毒之间的差异，并将这种差异与宿主和病毒(例如病毒基因型)因素联系起来。这些模型将考虑艾滋病毒数据的分层性质，将使用基于样条法的方法来捕捉非线性效应，并将纳入用于审查和测量误差的子模型。

DESCRIPTION (provided by applicant): HIV can rapidly escape neutralizing antibody responses in vivo. Although escape facilitates viral persistence within the infected patient, escape from neutralization implies that the antibody response is exerting significant selective pressure on the virus. Consequently, a vaccine-boosted humoral response may be effective in preventing infection, as the small population of infecting viruses cannot evolve quickly. An effective vaccine will also be able to induce significant heterologous neutralization responses. Although HIV is generally resistant to neutralization by sera from HIV-positive patients, some individuals mount broadly reactive neutralization responses The recent availability of high-throughput assays to quantify neutralizing antibody responses coupled with the ability to sequence full-length clones of the HIV-1 envelope gene permits a quantitative analysis of autologous and heterologous neutralization responses, and their relationship to viral genetic variation. We propose to quantify the roles of point mutations and insertions/deletions in the HIV-1 envelope in viral escape based on data from individuals with primary HIV infection. Neutralizing antibody responses will be measured using a rapid, highly reproducible recombinant virus/reporter assay, and genetic variation in envelope will be measured using both population-based and clonal sequencing. Analysis of these data presents a number of statistical challenges. We will develop statistical models to (a) obtain a quantative description of the dynamics of autologous neutralizing antibody responses and the patterns of viral escape and (b) to quantify variation between patients' sera and between viruses in heterologous neutralization, and relate this variation to host and viral (e.g. viral genotype) factors. These models will take the hierarchical nature of HIV data into account, will use spline-based methods to capture nonlinear effects, and will incorporate submodels for censoring and measurement error.