Differential equation analyses of latent HIV reservoirs

描述（由申请人提供）：尽管联合抗逆转录病毒药物治疗迅速将血浆HIV-1 RNA浓度降低到检测极限以下，但潜伏感染的静息记忆CD4+ t细胞可以持续数年，尽管完全抑制治疗。这些细胞的固有半衰期估计为6个月或更长。最近的研究表明，尽管抗逆转录病毒联合治疗具有高度抑制性，潜伏感染细胞群仍可持续60年或更长时间。因此，这些长寿的受感染细胞被认为是用抗逆转录病毒药物治疗HIV-1患者的主要障碍。然而，它们可能不是感染性病毒的唯一储存库：病毒也可能在滤泡树突状细胞和组织巨噬细胞上持续很长时间。目前估计感染细胞半衰期的方法仅限于组织，如PBMC，可以随时间定量取样。在这项研究中，我建议使用抗逆转录病毒治疗后发生的遗传差异（即与患者体内创始病毒的距离）减少的数据来推断潜伏感染细胞库的周转。利用最大似然树可以得到遗传差异的下降。为了量化这些下降，我将开发病毒动力学的数学模型，以解释病毒突变和抗逆转录病毒治疗后不同感染细胞区室的衰变。病毒在短寿命感染细胞中多样化的参数将从预处理发散数据中获得，而病毒进入潜伏库的输入将使用病毒载量数据进行建模。这些模型将根据已发表的数据和从接受抗逆转录病毒治疗的受感染儿童和成人的HIV-1序列实验合作者获得的数据进行测试。将把从这些模型得到的估计值与从抗逆转录病毒治疗后潜伏感染细胞密度衰减得到的估计值进行比较。这些模型可能会对为什么治疗不能从体内根除病毒提供新的见解，并可能为临床医生提供针对长期存在的细胞区室中的病毒的策略的新思路。

DESCRIPTION (provided by applicant): Although combination antiretroviral drug therapies rapidly push plasma HIV-1 RNA concentrations below limits of detection, latently infected resting memory CD4+ T-cells can persist for years despite fully suppressive therapy. The intrinsic half-life of these cells has been estimated to be six months or longer. Recent studies suggest that populations of latently infected cell populations may persist for 60 years or more despite highly suppressive combination antiretroviral therapy. These long-lived infected cells, therefore, are thought to be the major impediment to curing patients of HIV-1 with antiretroviral drugs. However, they may not be the only reservoir for infectious virus: virus may also persist for long periods of time on follicular dendritic cells and in tissue macrophages. Current procedures for estimating infected cell half-lives are limited to tissues, such as PBMC, which can be sampled quantitatively over time. In this study I propose to use data on the decrease in genetic divergence (i.e., distance from the founder virus in patient) that occurs following antiretroviral therapy to draw inferences concerning the turnover of latently infected cell reservoirs. Declines in genetic divergence will be obtained using maximum likelihood trees. To quantify these declines I will develop mathematical models for viral dynamics that account for viral mutation and the decay of different infected cell compartments following antiretroviral therapy. Parameters for the diversification of virus in short-lived infected cells will be obtained from pre-treatment divergence data, while the input of virus into the latent reservoir will be modeled using viral load data. These models will be tested from published data and data obtained from experimental collaborators on HIV-1 sequences from infected children and adults who have gone on antiretroviral therapy. The estimates obtained from these models will be compared to estimates obtained from the decay in the density of latently infected cells following antiretroviral therapy. These models may give new insights into why therapies do not eradicate virus from the body and may give clinicians new ideas for strategies for targeting viruses in long-lived cellular compartments.