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可迅速将血浆HIV-1 RNA浓度推至检测限以下，但尽管进行了完全抑制治疗，潜伏感染的静息记忆CD 4 + T细胞仍可持续数年。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，尽管进行了高度抑制性的联合抗逆转录病毒治疗，但潜伏感染的细胞群体可能持续60年或更长时间。因此，这些长寿命的感染细胞被认为是用抗逆转录病毒药物治愈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：病毒也可以在滤泡树突细胞和组织巨噬细胞中持续很长时间。目前用于估计感染细胞半衰期的程序限于组织，如PBMC，其可以随时间定量取样。在这项研究中，我建议使用遗传趋异减少的数据（即，与患者体内创始病毒的距离），以推断潜伏感染细胞库的周转情况。将使用最大似然树获得遗传趋异的下降。为了量化这些下降，我将开发病毒动力学的数学模型，解释抗逆转录病毒治疗后病毒突变和不同感染细胞区室的衰变。将从预处理趋异数据中获得短寿命感染细胞中病毒多样化的参数，而将使用病毒载量数据对病毒进入潜伏库的输入进行建模。这些模型将根据已发表的数据和实验合作者从接受抗逆转录病毒治疗的受感染儿童和成人的HIV-1序列中获得的数据进行测试。将从这些模型中获得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中获得的估计值进行比较。这些模型可能会为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寿细胞区室中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.