PUBLIC HIV DRUG RESISTANCE DATABASE

描述（由申请人提供）：全面、准确和可公开获得的HIV-1抗逆转录病毒（ARV）耐药性数据对于资源有限地区以人群为基础的获得性和传播性耐药性监测、指导资源充足地区的补救性ARV治疗以及确定总体ARV开发需求至关重要。然而，构成艾滋病毒-1大流行的病毒的可变性和艾滋病毒-1的高突变率使得难以量化传播和获得性耐药性，难以最佳地解释艾滋病毒-1基因型耐药性测试，也难以确定那些与未来抗逆转录病毒药物开发最相关的抗逆转录病毒耐药性变异。斯坦福大学HIV耐药数据库（HIVDB）是唯一公开提供HIV-1耐药知识基础的三个数据相关性的来源：(1)抗逆转录病毒治疗酶靶点（PR、RT和IN）的基因序列与获得HIV-1变异体的人的抗逆转录病毒治疗之间的相关性；(2)基因型与体外药敏的相关性；(3)基因型与抗逆转录病毒新治疗方案的病毒学反应的相关性。通过强调收集、注释、传播和分析三种主要类型的数据，HIVDB促进了荟萃分析，其中许多已发表的研究和临床试验的数据可以有效地综合。这一资助hiv - db的竞争性更新的具体目标是：(1)开发标准化的基因型方法，以监测传播和获得性耐药性的程度，并确定这些方法是否适用于所有HIV-1亚型；(2)通过收集、注释和传播基因型-治疗、基因型-表型和基因型-病毒学应答数据来扩展HIVDB，为基因型耐药试验的解释提供信息。结合这一目标，我们将改进在线框架，用于表示和描述与每种基因型抗性解释相关的证据基础；(3)鉴定并初步表征具有代表性的新型arv耐药变异，这可能有助于指导未来arv的开发。该提案的创新方面包括：(1)开发广泛可用和广泛使用的在线程序，以促进许多国家实验室的数据共享和一致的分析方法；(2)在HIV-1耐药突变研究中应用回归方法和相关网络分析的发展与实施；(3)利用模式生物数据库中的数据招募和管理方法，为HIVDB的延续和扩展创建一个可持续的模式。

DESCRIPTION (provided by applicant): Comprehensive, accurate, and publicly available HIV-1 antiretroviral (ARV) drug resistance data is essential for population-based monitoring of acquired and transmitted drug resistance in resource-limited regions, for guiding salvage ARV therapy in well-resourced regions, and for identifying overall ARV- development needs. However, the variability of viruses that comprise the HIV-1 pandemic and the high mutation rate of HIV-1 make it difficult to quantify transmitted and acquired drug resistance, to optimally interpret HIV-1 genotypic resistance tests, and to identify those ARV-resistant variants most relevant to the development of future ARVs. The Stanford HIV Drug Resistance Database (HIVDB) is the only publicly available source for three data correlations underlying HIV-1 drug resistance knowledge: (1) Correlations between the genetic sequences of the enzymatic targets of ARV therapy - PR, RT, and IN - with the ARV treatments of persons from whom sequenced HIV-1 variants are obtained; (2) Correlations between genotype and in vitro drug susceptibility; and (3) Correlations between genotype and the virological response to a new ARV treatment regimen. By emphasizing the collection, annotation, dissemination, and analysis of three main types of data, HIVDB facilitates meta-analyses in which data from many published studies and clinical trials can be effectively synthesized. The specific aims of this competing renewal for funding HIVDB are (1) To develop standardized genotypic methods to monitor the extent of transmitted and acquired drug resistance and to determine whether these methods can be applied across all HIV-1 subtypes; (2) To expand HIVDB by collecting, annotating, and disseminating the genotype-treatment, genotype-phenotype, and genotype-virological response data that inform genotypic resistance test interpretation. Coupled with this aim, we will improve the online framework for representing and describing the evidence basis associated with each genotypic resistance interpretation; and (3) To identify and preliminarily characterize representative and novel ARV-resistant variants that may help guide the development of future ARVs. Innovative aspects of this proposal include (1) the development of widely available and widely used online programs to facilitate data sharing and consistent analytic approaches across laboratories in many countries; (2) the development and implementation of regression methods and correlation network analyses to the study of HIV-1 drug resistance mutations; and (3) the use of data recruitment and curation methods adopted from model organism databases to create a sustainable model for the continuation and expansion of HIVDB.