Project 3: Identifying plasma biomarkers predicting time to HIV rebound after treatment interruption

项目 3：识别血浆生物标志物，预测治疗中断后 HIV 反弹的时间

• 批准号: 10223997
• 负责人: Satish Kumar Pillai
• 金额: $ 39.58万
• 依托单位: J. DAVID GLADSTONE INSTITUTES
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-08 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10223997
• 关键词: Aftercare; Aging; Antibody Response; Antigens; Antiviral Agents; Avidity; Bioinformatics; Biological Assay; Biological Markers; Biostatistics Core; Cells; Cerebrospinal Fluid; Chronic; Collection; Data; Development; Disease remission; Evaluation; Filtration; Flow Cytometry; Goals; HIV; HIV Antibodies; HIV Infections; HIV-1; Immune; Immunologic Factors; Immunologics; Immunoprecipitation; Individual; Inflammation; Interruption; Kinetics; Label; Luciferases; Machine Learning; Measurement; Measures; Mediating; MicroRNAs; Morbidity - disease rate; Nucleic Acids; Phase; Plasma; Protocols documentation; RNA; Recrudescences; Residual state; Resolution; Sampling; Small RNA; Specimen; Surface; System; Technology; Time; Viral; Viral Proteins; Viremia; Work; antibody detection; antiretroviral therapy; base; cell free DNA; chemokine; circulating microRNA; cohort; cost effective; cytokine; density; experience; experimental study; extracellular vesicles; interest; miRNA expression profiling; mortality; multidimensional data; multiplex assay; next generation sequencing; noninvasive diagnosis; predictive marker; prognostic significance; prognostic value; transcriptome sequencing; viral rebound; virology

PROJECT SUMMARY/ABSTRACT While the advent of antiretroviral therapy (ART) has dramatically reduced the morbidity and mortality associated with HIV infection, viral eradication is not achievable due to the persistence of latently-infected cells during treatment. ART must therefore be taken on a lifelong basis. Accumulating data suggest that HIV- infected individuals often experience persistent immune dysregulation, chronic inflammation, and accelerated aging even in the setting of ART-mediated viral suppression. These realities have created a pronounced interest in developing strategies to eradicate HIV in infected individuals. The development, evaluation and implementation of HIV curative strategies will depend critically on our capacity to determine when viral recrudescence in the near term is unlikely in an infected individual, justifying cessation of antiretroviral therapy (ART). The goal of this P01 project is to identify biomarkers that will enable us to predict the duration of the lag phase or “remission” period prior to HIV rebound following discontinuation of ART in HIV-infected individuals. In our study, a large number of virologic and immunologic parameters will be measured in a cohort of 125 well-characterized HIV-infected individuals undergoing analytical treatment interruption (ATI), to identify biomarkers that allow us to reliably predict the kinetics of viral rebound post-ART cessation. The experiments described in Project 3 of our P01 proposal will specifically examine the prognostic value of a broad spectrum of circulating factors in plasma and cerebrospinal fluid (CSF), leveraging cutting edge technologies and an unprecedented collection of longitudinal specimens from multiple ATI studies. In Aim 1, we will implement next-generation sequencing approaches to determine the relationship between circulating nucleic acids and viral rebound, focusing on microRNA profile, cell-free DNA, and residual low-level HIV viremia. In Aim 2, we will evaluate the prognostic significance of circulating extracellular vesicles, characterizing their abundance, cellular origin, and nucleic acid and viral protein cargo. Finally, in Aim 3, soluble antiviral immune factors will be evaluated as predictors of viral rebound, focusing on high-resolution analyses of anti-HIV antibody responses, cytokines and chemokines associated with HIV persistence. We will work closely with our Bioinformatics and Biostatistics Core to transform our high-dimensional data into robust predictors of HIV rebound following ART interruption, relying on sophisticated ensemble machine learning approaches. Ultimately, the identification of a reliable blood plasma-based predictor of viral rebound will represent an optimal scenario for the field, enabling rapid development, scaling and deployment of cost- effective, non-invasive diagnostic approaches to facilitate the search for an HIV cure.

项目摘要/摘要 而抗逆转录病毒疗法(Art)的出现大大降低了发病率和死亡率。 与艾滋病毒感染相关的是，由于潜伏感染细胞的持久性，无法根除病毒 在治疗过程中。因此，艺术必须终身学习。越来越多的数据表明，艾滋病毒- 感染者通常经历持续的免疫失调、慢性炎症和加速。 即使在ART介导的病毒抑制的背景下也会老化。这些现实创造了一个明显的 有兴趣制定策略，根除感染者中的艾滋病毒。 艾滋病毒治疗策略的制定、评估和实施将关键取决于我们的 有能力确定病毒在短期内不太可能在感染者身上复发，这是合理的 停止抗逆转录病毒治疗(ART)。这个P01项目的目标是识别将使 美国将预测停药后艾滋病毒反弹前滞后期或“缓解期”的持续时间 艾滋病病毒感染者的抗逆转录病毒治疗。在我们的研究中，大量的病毒学和免疫学参数将 在接受分析治疗的125名特征良好的艾滋病毒感染者中进行测量 中断(ATI)，以确定生物标志物，使我们能够可靠地预测ART后病毒反弹的动力学 停止。我们P01提案的项目3中描述的实验将专门检查预后 血浆和脑脊液中广谱循环因子利用切割的价值 EDGE技术和来自多个ATI研究的史无前例的纵向标本收集。 在目标1中，我们将实施下一代排序方法，以确定 循环核酸和病毒反弹，关注microRNA图谱、无细胞DNA和残留低水平 艾滋病病毒血症。在目标2中，我们将评估循环细胞外小泡的预后意义， 确定它们的丰度、细胞来源以及核酸和病毒蛋白的含量。最后，在目标3中， 可溶性抗病毒免疫因子将被评估为病毒反弹的预测因子，重点是高分辨率 抗HIV抗体应答、细胞因子和趋化因子与HIV持久性的分析。 我们将与我们的生物信息学和生物统计核心密切合作，将我们的高维数据转换为 依靠复杂的合奏机器，抗逆转录病毒治疗中断后艾滋病毒反弹的稳健预测 学习方法。最终，确定一个可靠的基于血浆的病毒反弹预测因子 将代表现场最佳方案，支持快速开发、扩展和部署成本- 有效的、非侵入性的诊断方法，以促进艾滋病毒治愈的研究。