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; 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（由应用程序提供）：此提案是父级R01项目（AI095066）的续签应用。该应用基于我们在父母时期取得的开创性成就，在父母时期，我们成功地证明了HIV内HIV序列中的基因组信号是精确且可靠的标记物，可以将入射与慢性感染区分开。这些基因组生物标志物测量了密切相关菌株作为入射的特征的存在，其精度超过95％。我们通过实施尖端技术来设计高通量，下一代测序平台，进一步完善了事件测定法。目前，该测定法正在与杰出的中心合作进行600多个事件和长期规格进行积极测试。在介绍应用中，我们建议开发一种高度准确且低成本的基因组测定法，该测定同时确定HIV的发生率，并从横截面调查中的单个测量中传播耐药性突变（TDRM）。该提案的主要创新包括i）将高通量的下一代测序平台与生物信息学管道，统计测试和数学建模集成 新颖的统计方法是为了客观地确定近期感染（MDRI）的虚假新近度率（FRR）和平均持续时间 - 标准事件评估评估标准 - 和III）分发了易于访问的基于Web的软件，全球HIV社区可以与Indist and TDRM监视相互作用。我们的基因组评估将首先产生包膜基因段的下一代测序读数，以报告感染阶段。使用我们新的统计分层贝叶斯模型，我们将随着时间的推移分析基因组生物标志物动力学，以计算MDRI和FRR。然后，我们将监视与卫生和公共服务部推荐和替代治疗方案相关的82名通常发生的TDRM的列表。我们的单一评估方法应对日益增长的需求做出回应，以确切确定TDRM的全球存在的增加。该提出的测定的有效性将通过来自潜水员人群的大量HIV序列进行广泛测试，包括i）来自杰出中心（WIHS，CDC，CHAVI和CEPHIA）的良好同伙，ii）ii）我们自己的同伙在USC和Los Angeles gay and Les Anselbian Center（los and and les and cohort cohort cohort）cohorts and los and iii cohort（a los and les and les and co）临床艾滋病试验小组。该项目的最终产品基于Web的软件将系统地生产和组织重要的信息，以为个人和地理范围范围内的人口范围的事件和TDRM趋势提供最佳治疗方案。拟议的工作将通过提供有效的事件和TDRM监视测定法，可以直接用于横断面流行病监测来提高HIV预防工作。