Public HIV Drug Resistance Database

公共艾滋病毒耐药数据库

• 批准号: 7416601
• 负责人: ROBERT William SHAFER
• 金额: $ 60.4万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-05-01 至 2011-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7416601
• 关键词: Acute; Anti-Retroviral Agents; Back; CD4 Lymphocyte Count; Chronic; Clinical; Collaborations; Communities; Data; Databases; Development; Disease regression; Drug Design; Drug resistance; Endopeptidases; Evolution; Genetic; Genotype; HIV; HIV drug resistance; HIV therapy; HIV-1; HIV-1 drug resistance; In Vitro; Infection; Knowledge; Link; London; Machine Learning; Maps; Medical Surveillance; Methods; Minor; Modeling; Molecular Target; Multi-Drug Resistance; Mutation; Outcome; Pathway interactions; Pattern; Peptide Hydrolases; Persons; Pharmaceutical Preparations; Phenotype; Phylogenetic Analysis; Pliability; Population Dynamics; Population Genetics; Predisposition; Prevalence; Protocols documentation; Publishing; Recombinants; Recording of previous events; Research; Research Personnel; Resistance; Treatment Protocols; Universities; Variant; Viral; Virus; Work; antiretroviral therapy; base; college; fitness; improved; in vivo; response; transmission process; trend

DESCRIPTION (provided by applicant): HIV drug resistance data are critical for HIV drug resistance surveillance, antiretroviral drug design, and the management of persons infected with drug-resistant HIV. Three fundamental types of correlations form the basis of drug resistance knowledge: (1) Correlations between genotypic data with the treatments of persons from whom sequenced HIV-1 isolates have been obtained (genotype-treatment); (2) Correlations between genotype and in vitro drug susceptibility (genotype-phenotype); and (3) Correlations between genotype and the clinical response to a new treatment regimen (genotype-outcome). Accordingly our three plans are as follows: (1) To use phylogenetically-based statistical analysis of correlations between mutations in the targets of HIV therapy (genotype) and antiretroviral treatment to distinguish between drug- and non-drug- related HIV-1 evolution, to identify temporal and geographic patterns in the prevalence of drug resistance, and to identify the spread of viruses with particular patterns of drug-resistance mutations. (2) To use patterns of mutations in the targets of antiretroviral therapy, antiretroviral treatment data, and in vitro drug susceptibility results to help prioritize the clinical development of experimental antiretroviral compounds. (3) To us correlations between genotype-phenotype and genotype-clinical outcome to identify the treatment regimens most likely to be effective in persons with acquired or transmitted drug resistance. In order to accomplish these aims, we will expand the online publicly available Stanford HIV RT and Protease Sequence Database to represent, store, and analyze the diverse forms of data underlying drug resistance knowledge. Standardized protocols for exchanging data with the broad community of researchers studying HIV-1 drug resistance will be refined and validated. Improved methods for representing published drug resistance data, performing temporal queries and knowledge discovery, and for analyzing genotypic resistance data in a phylogenetic context will be implemented. This proposal is also the start of a three-way collaboration between Stanford University, the University College of London (UCL), and Oxford University. UCL is on the forefront of research into the problem of transmitted drug resistance and Oxford University is on the forefront of research on virus evolution and population genetics.

描述(由申请人提供)：艾滋病毒耐药性数据对于艾滋病毒耐药性监测、抗逆转录病毒药物设计和耐药艾滋病毒感染者的管理至关重要。三种基本类型的相关性构成了耐药性知识的基础：(1)基因数据与获得艾滋病毒-1病毒分离株序列的人的治疗之间的相关性(基因-治疗)；(2)基因与体外药物敏感性之间的相关性(基因-表型)；以及(3)基因与新治疗方案的临床反应之间的相关性(基因-结果)。因此，我们的三个计划如下：(1)使用基于系统发育的统计分析艾滋病毒治疗目标(基因)和抗逆转录病毒治疗目标突变之间的相关性，以区分药物相关和非药物相关的艾滋病毒-1进化，识别耐药性流行的时间和地理模式，并确定具有特定耐药性突变模式的病毒的传播。(2)利用抗逆转录病毒治疗靶点的突变模式、抗逆转录病毒治疗数据和体外药敏结果来帮助确定实验性抗逆转录病毒化合物的临床开发的优先顺序。(3)研究基因-表型和基因-临床结局之间的相关性，以确定对获得性或传播性耐药患者最有可能有效的治疗方案。为了实现这些目标，我们将扩大在线公开可用的斯坦福艾滋病毒逆转录酶和蛋白酶序列数据库，以表示、存储和分析支持耐药性知识的各种形式的数据。与研究艾滋病毒-1耐药性的广大研究人员交换数据的标准化协议将得到完善和验证。将实施用于表示已公布的耐药性数据、执行时间查询和知识发现以及在系统发育背景下分析基因类型耐药性数据的改进方法。这项提议也是斯坦福大学、伦敦大学学院(UCL)和牛津大学之间三方合作的开始。伦敦大学学院在传播耐药性问题的研究方面走在了前列，牛津大学在病毒进化和种群遗传学研究方面走在了前列。