Project 003 - VICI

项目3.病毒、免疫学和细胞数据集成（维西）研究项目-摘要 40年来，研究已经将艾滋病毒医学发展到艾滋病毒感染者（PWH）可以正常生活的程度 如果他们能够获得抗逆转录病毒治疗，他们就能过上健康的生活。然而，艾滋病毒并不容易治愈。 治愈艾滋病毒需要在多尺度研究生物系统的方法方面取得进一步进展， 从细胞内基因间的相互作用到HIV在组织间的迁移。需要创新方法， 更充分地描述艾滋病毒在抗逆转录病毒治疗停止和未停止的情况下的动态。 迫切需要这些方法来解决在概念验证研究中出现的挑战， 参与者人数。维西研究项目（RP）建议开发和验证以下方法： 分析由其他RP（VENI和VIDI）从20个良好表征的 参与者加入了创新的“最后的礼物”队列。因为可重复的科学结果同样依赖于 开发新的分析方法，以应对这些数据集带来的挑战， 因此，我们建议为拟议的维西RP投入大量资源和人才。 在整个维西RP中，我们描述了集成模型的开发，统计验证和应用。 高维、单细胞和单基因组数据，以及临床和其他低维协变量。 所提出的方法使用“系统”方法，将复杂和不同实体之间的联系结合起来 (e.g.,基因表达、整合位点、表观遗传标记、组织类型）或阐明 预测器来整合数据的整体。 目标1和2集中在新的统计方法，以（1）将新的网络方法与离散特性相结合 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）鉴定细胞 表型基于通过一种新的递归形式识别的基因调控网络类 分区这些方法将直接应用于分析组织的HIV活化和再增殖。 目标3使用中介分析方法，包括中介效应异质性的新检验方法， 导致HIV在体内持续存在的机制。 这些相辅相成的目标有一个共同的总体目标，即提供一个基于系统的框架， 便于分析大型、复杂和高维数据集。说明研究框架和指南 评论家，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 艾滋病病毒离开，来到，和留在家里和关闭艺术。

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.