Project 003 - VICI

项目003 - VICI

• 批准号: 10459876
• 负责人: VICTOR GERARD DEGRUTTOLA
• 金额: $ 33.18万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10459876
• 关键词: Address; Algorithms; Automobile Driving; Biological; Blood; Cells; Characteristics; Classification; Clinical; Complex; Data; Data Set; Development; Dimensions; Enrollment; Environment; Environmental Risk Factor; Epigenetic Process; Future; Gene Expression; Generations; Genes; Genome; Gifts; Goals; HIV; Heterogeneity; Human body; Immune; Immunologics; Integration Host Factors; Knowledge; Linear Models; Measures; Mediating; Mediation; Medicine; Methods; Modeling; Movement; Network-based; Organ; Participant; Pathway interactions; Pattern; Persons; Phenotype; Reproducibility; Research; Research Personnel; Research Project Grants; Resources; Satellite Viruses; Statistical Methods; Structure; System; Talents; Technology; Testing; Tissue Sample; Tissues; Validation; Viral; Viremia; Virion; analytical method; antiretroviral therapy; base; biological systems; cohort; data integration; demographics; diverse data; gene regulatory network; high dimensionality; innovation; insight; integration site; migration; multidimensional data; network models; new technology; novel; programs; trait

PROJECT 3. Viral, Immunologic and Cellular data Integration (VICI) Research Project - ABSTRACT For 40 years, research has advanced HIV medicine to the point where persons with HIV (PWH) can live normal and healthy lives if they have access to antiretroviral therapy (ART). Nevertheless, HIV cannot be readily cured. Curing HIV requires further advances in approaches to investigating biological systems at multiple scales, from interactions among genes within a cell to migration of HIV between tissues. Innovative methods are needed to characterize HIV dynamics more fully in settings where ART is and is not stopped. These methods are urgently needed to address the challenges that arise in proof-of-concept studies with a small number of participants. The VICI Research Project (RP) proposes development and validation of methods for analyzing large and complex datasets generated by the other RPs (VENI and VIDI) from 20 well-characterize participants enrolled in the innovative Last Gift cohort. As reproducible scientific results depend as much on development of novel analytical methods to address the challenges posed by these datasets as on their generation, we propose to devote considerable resources and talent to the proposed VICI RP. Throughout this VICI RP, we describe development, statistical validation, and application of models that integrate high-dimensional, single-cell and single-genome data with clinical and other low-dimensional covariates. Proposed methods use a ‘systems’ approach that incorporates connections among complex and distinct entities (e.g., gene expression, integration site, epigenetic marks, tissue types) or elucidates relationships among predictors to integrate the totality of the data. Aims 1 and 2 focus on novel statistical methods to (1) combine novel network methods with the discrete trait analyses (described in the VENI RP) to infer viral migration networks and its predictors, and (2) identify cell phenotypes based on classes of gene regulatory networks identified through a novel form of recursive partitioning. These methods will be directly applied to analyze HIV activation and repopulation of tissues. Aim 3 uses mediation analysis⸺including novel tests for heterogeneity in mediation effects⸺to assess mechanisms that drive HIV persistence in the body. These complementary aims share the same overarching goal of providing a system-based framework that facilitates analysis of large, complex, and high dimensional datasets. To illustrate the study framework and guide reviewers, we describe the application of the proposed innovative methods on the study-defined reservoir states of HIV leaving, coming, and staying HOME on and off ART.

项目 3. 病毒、免疫学和细胞数据集成 (VICI) 研究项目 - 摘要 40 年来，研究不断推进艾滋病毒治疗，使艾滋病毒感染者 (PWH) 能够正常生活 如果他们能够接受抗逆转录病毒治疗 (ART)，就能过上健康的生活 然而，艾滋病毒并不能轻易治愈。 治愈艾滋病毒需要在多尺度研究生物系统的方法上取得进一步进展，从 细胞内基因之间的相互作用对于艾滋病毒在组织之间的迁移需要创新的方法。 在 ART 已停止或未停止的环境中更全面地描述 HIV 动态。 迫切需要这些方法来解决概念验证研究中出现的挑战 VICI 研究项目 (RP) 提出了方法的开发和验证。 分析其他 RP（VENI 和 VIDI）从 20 个特征良好的数据集生成的大型复杂数据集 加入创新的“最后的礼物”队列，因为可重复的科学结果同样取决于。 开发新的分析方法来解决这些数据集带来的挑战 一代，我们建议为拟议的 VICI RP 投入大量资源和人才。 在整个 VICI RP 中，我们描述了模型的开发、统计集成验证和应用 具有临床和其他低维协变量的高维、单细胞和单基因组数据。 提出的方法使用“系统”方法，该方法结合了复杂且不同实体之间的联系 （例如，基因表达、整合位点、表观遗传标记、组织类型）或阐明之间的关系 预测器来整合数据的整体。 目标 1 和 2 侧重于新颖的统计方法，以 (1) 将新颖的网络方法与离散特征相结合 分析（在 VENI RP 中描述）以推断病毒迁移网络及其预测因子，以及 (2) 识别细胞 基于通过新型递归形式识别的基因调控网络类别的表型 这些方法将直接应用于分析 HIV 激活和组织再生。 目标 3 使用中介分析⸺包括中介效应异质性的新颖测试⸺来评估 驱动艾滋病毒在体内持续存在的机制。 这些互补的目标具有相同的总体目标，即提供一个基于系统的框架， 促进大型、复杂和高维数据集的分析 说明研究框架和指南。 审稿人，我们描述了所提出的创新方法在研究定义的储层状态上的应用 艾滋病毒离开、到来以及留在家中和不接受 ART 的情况。