HIV Incidence Assay via Deep Sequencing and Statistical Tests

通过深度测序和统计测试进行 HIV 发病率测定

• 批准号: 8318084
• 负责人: Ha Youn Lee
• 金额: $ 51.25万
• 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 2015-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8318084
• 关键词: AIDS prevention; AIDS/HIV problem; Acquired Immunodeficiency Syndrome; Acute; Address; Affect; Antibodies; Antibody Formation; Antigens; Area; Avidity; Base Sequence; Behavior; Biological Assay; Biological Markers; Blood; Blood specimen; CD4 Lymphocyte Count; Centers for Disease Control and Prevention (U.S.); Characteristics; Chronic; Clinic; Communities; Computer software; Data; Data Set; Development; Diagnosis; Disease; Enrollment; Epidemic; Evolution; Foundations; Genes; Guidelines; HIV; HIV Infections; HIV prevention trial; Hospitals; Incidence; Individual; Infection; Internet; Intervention; Intervention Trial; Kenya; Kinetics; Knowledge; Lead; Letters; Longitudinal Studies; Macaca; Manitoba; Measures; Modeling; Online Systems; Patients; Plasma; Population Heterogeneity; Prevention; Prevention Research; Preventive Intervention; Publications; Reporting; Research; Research Activity; SIV; Sampling; Scheme; Sequence Analysis; Serological; Staging; Statistical Methods; Testing; Time; Universities; Update; Vaccines; Viral; Viral load measurement; Virus; Washington; Work; base; cohort; design; innovation; meetings; microbicide; next generation; novel; sex; tool

DESCRIPTION (provided by applicant): Our recent studies developed acute sequence evolution model which has been applied to interpret sequence clones derived from 102 subjects with acute HIV subtype B infection, from 69 subjects with acute HIV subtype C infection, and from numerous SIV-infected macaques. Our model enabled an assessment of the sequence diversity in HIV infections originating from a single transmitted viral strain and the estimation on the period of infection, which has been a significant and beneficial contribution to HIV research community. We propose to expand our research activity of modeling intrahost HIV diversification toward the development of a novel assay identifying new, recent HIV infections. In the HIV/AIDS prevention field, it is critical to assess how many people have been recently infected in a given area in order to evaluate the feasibility of prevention and intervention trials. The diagnosis of HIV infection is currently possible from blood samples but reliable assays predicting how long an individual has been infected have not been developed. Various detuned antibody assays, or avidity-based assessments, have been used, assuming that antibody titer and avidity increases with time. However, serologic assays are problematic because (i) the rate of maturation of the antibody response varies between different individuals, (ii) some subjects with low CD4 counts or low virus loads may be inaccurately counted as having recent infection, and (iii) serologic assays can be negatively affected if the infecting virus clade differs from the clade of the antigen used in the assay (this is a particular problem in mixed-clade epidemics). This proposal aims to provide empirical and theoretical foundations for inventing a novel assay that distinguishes new, incident infections from chronic, asymptomatic infections. Major innovations of the proposal include (i) its comprehensive integration of next-generation ultradeep pyrosequencing data and biomathematical modeling and (ii) a novel statistical design estimating the number of founder viruses and the duration of infection. Our proposed study will focus on overcoming two primary barriers to the development of a sequencing based assay. First, the assay potentially mis-classifies early infections with multiple distinct founder strains as chronic infections. Second, it is questionable whether the assay can distinguish incident samples from chronic ones obtained at late stages of infections. We propose to collect a large scale of HIV sequence data from diverse population in different epidemic regions and different stages of infections. Ultradeep sequencing data in conjunction with novel statistical designs will lead us to invent a novel assay that is capable of identifying incident infections. The proposed work will advance HIV prevention research by providing a reliable assay based on the characteristics of intrahost HIV diversification.

描述（由申请人提供）：我们最近的研究开发了急性序列进化模型，该模型已用于解释来自102名急性HIV亚型B感染受试者、69名急性HIV亚型C感染受试者和许多SIV感染的猕猴的序列克隆。我们的模型能够评估源自单一传播病毒株的HIV感染的序列多样性和感染期的估计，这对HIV研究界做出了重大和有益的贡献。我们建议扩大我们的研究活动的建模宿主内HIV多样化的发展，一种新的检测方法，确定新的，最近的HIV感染。在艾滋病毒/艾滋病预防领域，必须评估某一地区最近有多少人受到感染，以便评价预防和干预试验的可行性。艾滋病毒感染的诊断目前可以通过血液样本进行，但尚未开发出预测个体感染时间的可靠检测方法。已使用各种失谐抗体测定或基于亲合力的评估，假设抗体滴度和亲合力随时间增加。然而，血清学测定是有问题的，因为（i）抗体应答的成熟速率在不同个体之间变化，（ii）具有低CD 4计数或低病毒载量的一些受试者可能被不准确地计数为具有近期感染，和（iii）如果感染病毒的进化枝不同于测定中使用的抗原的进化枝，（这在混合进化枝流行病中是一个特别的问题）。该提案旨在为发明一种新的检测方法提供经验和理论基础，该检测方法将新发、偶发感染与慢性、无症状感染区分开来。该提案的主要创新包括（i）下一代超深度焦磷酸测序数据和生物数学建模的全面整合，以及（ii）估计创始人病毒数量和感染持续时间的新型统计设计。我们提出的研究将集中在克服两个主要障碍，以发展一个基于测序的测定。首先，该检测可能将具有多种不同创始菌株的早期感染错误分类为慢性感染。第二，该检测方法是否能够区分感染后期获得的偶发样本和慢性样本是值得怀疑的。我们建议从不同流行地区和不同感染阶段的不同人群中收集大规模的HIV序列数据。超深度测序数据与新的统计设计相结合，将引导我们发明一种能够识别偶发感染的新检测方法。拟议的工作将通过提供基于宿主内艾滋病毒多样化特征的可靠测定来推进艾滋病毒预防研究。