BIOMATHEMATICAL ANALYSIS OF VIRAL DYNAMICS AND EVOLUTION

病毒动力学和进化的生物数学分析

• 批准号: 8011069
• 负责人: DOUGLAS D RICHMAN
• 金额: $ 42.88万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-08-20 至 2011-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8011069
• 关键词: AIDS Dementia Complex; Anatomy; Antiviral Agents; Automobile Driving; Award; Biological; CCL3L1 gene; Caring; Cerebrospinal Fluid; Clinical; Clinical Data; Clinical Research; Collection; Complex; Data; Data Set; Databases; Development; Drug resistance; Evolution; Genetic Polymorphism; Genetic Variation; Genome; Genotype; HIV; HIV Infections; HIV-1; HLA Antigens; Haplotypes; Immune response; Immune system; Individual; Infection; Length; Link; Male Genital Organs; Modeling; Multiple Viral Drug Resistance; Mutation; Natural History; Neuraxis; Pathogenesis; Pattern; Phenotype; Plasma; Play; Regimen; Resolution; Role; Satellite Viruses; Source; Staging; Statistical Models; Therapeutic; Translational Research; Viral; Viral Load result; cost; design; fitness; genital secretion; genome-wide; insight; mathematical model; neurotropic; programs; resistance mutation; response; service utilization; transmission process; viral resistance

DESCRIPTION (provided by applicant): For HIV infection, biomathematical approaches have been instrumental in generating testable hypotheses regarding viral persistence and evolution, in providing insights into viral dynamics and pathogenesis, and in the analysis of viral sequences. This has led to the collection of increasingly detailed and complex data on viral and host genetic variation, which necessitates the development of more biologically realistic mathematical and statistical models of HIV dynamics and evolution. At UCSD we have developed a number of translational research programs to investigate the natural history and pathogenesis of HIV infection. The award of R01 AI047745, "Biomathematical analysis of viral dynamics and evolution," provided mathematical and statistical support to interpret the data and to aid in the design of new studies. We propose to continue to develop biomathematical models to help interpret viral and host genetic variation in the context of escape from therapy and the immune system, integrating these models into several clinical studies of HIV infection in a variety of settings relevant to the care of HIV infected individuals: 1. Full-length sequences of the HIV-1 genome will be obtained from individuals with recent HIV infection in order to describe the natural history of viral evolution during the early stages of infection at a genome-wide level. 2. High resolution human leukocyte antigen (HLA) haplotypes and various genetic polymorphisms involved in immune responses will be obtained from individuals with recent HIV infection. These data will be used to determine the role of host genetic variation in driving escape mutations and the natural history of HIV. 3. A large dataset of viral genotypes, phenotypes and clinical data from over 1000 subjects in the HIV Cost and Services Utilization study will be used to generate statistical models of the correlations between viral genotype, phenotype, viral load, and therapeutic regimen. These models will provide information on how HIV evolves resistance to multiple antiviral agents, and the impact of viral resistance mutations on viral fitness. 4. We will study viral dynamics and evolution in (a) the male genital tract and (b) cerebrospinal fluid. As genital secretions are the major source of transmitted HIV, information on the compartmentalization of HIV within the male genital tract will help us understand the biological determinants of HIV transmission. HIV in the central nervous system is associated with HIV dementia; we will investigate genetic changes in the virus associated with a neurotropic phenotype.

描述（由申请人提供）：对于 HIV 感染，生物数学方法有助于产生有关病毒持久性和进化的可检验假设，提供对病毒动力学和发病机制的见解，以及分析病毒序列。这导致关于病毒和宿主遗传变异的数据收集越来越详细和复杂，这就需要开发更符合生物学现实的艾滋病毒动力学和进化数学和统计模型。在加州大学圣地亚哥分校，我们开发了许多转化研究项目来研究艾滋病毒感染的自然史和发病机制。 R01 AI047745 奖“病毒动力学和进化的生物数学分析”为解释数据和帮助设计新研究提供了数学和统计支持。我们建议继续开发生物数学模型，以帮助解释在逃避治疗和免疫系统的情况下的病毒和宿主遗传变异，并将这些模型整合到与艾滋病毒感染者护理相关的各种环境中的艾滋病毒感染的几项临床研究中个体： 1. 将从最近感染 HIV 的个体获得 HIV-1 基因组的全长序列，以便在全基因组水平上描述感染早期阶段病毒进化的自然史。 2.将从最近感染HIV的个体中获得高分辨率人类白细胞抗原（HLA）单倍型和涉及免疫反应的各种遗传多态性。这些数据将用于确定宿主遗传变异在驱动逃逸突变和艾滋病毒自然史中的作用。 3. HIV 成本和服务利用研究中 1000 多名受试者的病毒基因型、表型和临床数据的大型数据集将用于生成病毒基因型、表型、病毒载量和治疗方案之间相关性的统计模型。这些模型将提供有关艾滋病毒如何进化出对多种抗病毒药物的耐药性以及病毒耐药性突变对病毒适应性的影响的信息。 4. 我们将研究 (a) 男性生殖道和 (b) 脑脊液中的病毒动力学和进化。由于生殖器分泌物是艾滋病毒传播的主要来源，有关男性生殖道内艾滋病毒划分的信息将有助于我们了解艾滋病毒传播的生物决定因素。中枢神经系统中的艾滋病毒与艾滋病毒痴呆有关；我们将研究与嗜神经表型相关的病毒基因变化。