A single genomic assay for HIV incidence and transmitted drug resistance mutation screening

HIV 发病率和传播耐药突变筛查的单一基因组测定

• 批准号: 9889868
• 负责人: Ha Youn Lee
• 金额: $ 52.82万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-10 至 2021-06-17
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9889868
• 关键词: AIDS clinical trial group; AIDS prevention; AIDS/HIV problem; Achievement; Alternative Therapies; Bayesian Modeling; Biological Assay; Centers for Disease Control and Prevention (U.S.); Characteristics; Chronic; Clinic; Clinical; Collaborations; Communities; Computer software; Cross-Sectional Studies; Data; Drug resistance; Epidemic; Evaluation; Evolution; Failure; Gays; Genes; Genomics; Geographic Locations; Geography; Goals; HIV; HIV Infections; HIV prevention trial; HIV resistance; Incidence; Individual; Infection; Internet; Intervention; Lesbian; Los Angeles; Mathematics; Measures; Methods; Monitor; Mutation Detection; Online Systems; Output; Parents; Performance; Phase; Population; Population Heterogeneity; Prevalence; Preventive Intervention; Regimen; Reporting; Research; Scheme; Specimen; Statistical Methods; Surveys; Techniques; Technology; Testing; Time; United States Dept. of Health and Human Services; Vaccines; Viral; Virus; Work; base; bioinformatics pipeline; chronic infection; cohort; cost; data hub; design; drug resistant virus; genomic biomarker; genomic signature; innovation; mathematical model; microbicide; mutation screening; mutational status; next generation sequencing; novel; optimal treatments; pol genes; population survey; public health relevance; resistance mutation; sequencing platform; tool; trend; virology; web-accessible

 DESCRIPTION (provided by applicant): This proposal is a renewal application of the parent R01 project (AI095066). This application builds upon our pioneering accomplishments made during the parent period wherein we successfully demonstrated that genomic signatures within the intrahost HIV sequence population are precise and robust markers to distinguish incident from chronic infections. These genomic biomarkers, measuring the presence of closely related strains as a signature of incidence, showed over 95% accuracy. We further refined the incidence assay by implementing cutting-edge technology to design a high-throughput, next-generation sequencing platform. This assay is currently being actively tested on over 600 incident and chronic specimens in collaboration with preeminent centers with well-established cohorts. In the present application, we propose to develop a highly accurate and low cost genomic assay which concurrently determines HIV incidence and profiles transmitted drug resistance mutations (TDRMs) from a single measure in cross-sectional surveys. Major innovations of the proposal include i) integrating a high-throughput next-generation sequencing platform with a bioinformatics pipeline, statistical tests and mathematical modeling, ii) designing novel statistical methods to objectively determine the False Recency Rate (FRR) and mean duration of recent infection (MDRI) - the standard incidence assay evaluation criteria - and iii) distributing easily accessible web-based software with which the global HIV community can interact for incidence and TDRM surveillance. Our genomic assay will first produce next-generation sequencing reads of envelope gene segments to report the stage of infection. Using our new statistical hierarchical Bayesian models, we will analyze the genomic biomarker dynamics over time to calculate the MDRI and FRR. We will then monitor the presence of 82 WHO-listed commonly occurring TDRMs associated with the Department of Health and Human Services' recommended and alternative therapy regimens. Our single assay approach responds to the growing need to precisely identify TDRMs as their global presence increases. The validity of the proposed assay will be extensively tested with a large volume of HIV sequences from diverse populations, including i) well-established cohorts from preeminent centers (WIHS, CDC, CHAVI, and CEPHIA), ii) our own cohorts at the Rand Schrader Clinic at USC and Los Angeles Gay and Lesbian center, and iii) the virologic failure cohort (A5202) from the Clinical AIDS Trial Group. This project's end-product, web-based software, will systematically produce and organize vital information to inform optimal therapy regimens for individuals and geographically trace population-wide incidence and TDRM trends. The proposed work will advance HIV prevention efforts by providing a working incidence and TDRM surveillance assay ready for direct use in cross-sectional epidemic monitoring.

 描述（申请人提供）：本建议书是父R 01项目（AI 095066）的延续申请。该应用建立在我们在母代期间取得的开创性成就的基础上，其中我们成功地证明了宿主内HIV序列群体内的基因组签名是区分慢性感染事件的精确和稳健的标记。这些基因组生物标志物测量密切相关菌株的存在作为发病率的标志，显示出超过95%的准确性。我们通过实施尖端技术来设计高通量的下一代测序平台，进一步完善了发病率测定。目前，该检测试剂盒正在与具有完善队列的卓越中心合作，对600多份事件和慢性标本进行积极测试。在本申请中，我们提出开发一种高度准确且低成本的基因组测定法，其在横断面调查中从单一测量同时确定HIV发病率和概况传播的耐药突变（TDRM）。该提案的主要创新包括i）将高通量下一代测序平台与生物信息学管道，统计测试和数学建模相结合，ii）设计 新的统计方法，以客观地确定假近率（FRR）和近期感染的平均持续时间（MDRI）-标准的发病率检测评估标准-和iii）分发易于访问的基于网络的软件，全球艾滋病毒社区可以与发病率和TDRM监测互动。我们的基因组检测将首先产生包膜基因片段的下一代测序读数，以报告感染的阶段。使用我们新的统计分层贝叶斯模型，我们将分析基因组生物标志物随时间的动态变化，以计算MDRI和FRR。然后，我们将监测与卫生与公众服务部推荐和替代治疗方案相关的82种WHO列出的常见TDRM的存在。我们的单一检测方法响应了随着TDRM全球存在的增加而日益增长的精确识别TDRM的需求。将使用来自不同人群的大量HIV序列对拟定检测试剂盒的有效性进行广泛测试，包括i）来自卓越中心（WIHS、CDC、CHAVI和CEPHIA）的成熟队列，ii）我们在南加州大学兰德施拉德诊所和洛杉矶同性恋中心的队列，以及iii）来自临床艾滋病试验组的病毒学失败队列（A5202）。该项目的最终产品，基于网络的软件，将系统地产生和组织重要信息，为个人提供最佳治疗方案，并在地理上追踪整个人口的发病率和TDRM趋势。拟议的工作将通过提供可直接用于横断面流行病监测的工作发病率和TDRM监测测定来推进艾滋病毒预防工作。