Mutation Profile Analysis of HIV Genetic Heterogeneity

描述（由申请人提供）：临床试验表明， 联合治疗减少HIV病毒量（病毒载量）的能力 在血浆中。具有讽刺意味的是，这种疗法的使用可能会促进肿瘤细胞的增殖。 病毒耐药基因型，使患者几乎没有选择， 后续治疗。基于基因型的替代策略， HIV基因变异与某些表型之间关系 治疗反应，如病毒药物敏感性正在研究， 指导治疗选择。这种关系很难研究，部分原因是 它的高维度，艾滋病毒的准物种性质，以及 其他关系往往嵌入其中，如果忽视，可能导致 不正确的解释和处理。例如，由于已知的病毒 负荷（或其他协变量）对观察到的HIV基因型的影响， 对于病毒载量影响所考虑的表型，其关系 HIV遗传异质性可能会受到病毒载量的混淆 表型间的异质性。要检验的主要假设是， 除了HIV遗传学之外，还可以在 表型群体及其对遗传关联的贡献， 估算新的方法被提出来从其他基因推断HIV基因。 与表型相关的异质性来源，基于非参数 （无分布）方法，使用复合（序列对）测量 遗传距离与其他方法相比，所提出的方法 更稳健，因为经验，而不是分析建模的分布 进行比较和协变量调整。这些方法将根据 配置文件分析类型的设置，其中一系列相关的假设， 考察利益关系的构建。具体目标是： (1)构建了一个度量理论框架来模拟准物种 使用无分布方法与协变量相关的异质性， （2）制定免费分发的方法， 确定改变艾滋病毒遗传学之间关系的协变量， 并调整这种关系 （3）扩大目标1和2的方法， HIV遗传学基因区域和时间趋势的多变量分析 与表型相关的异质性，存在协变量， 取决于这些连续体;（4）表征艾滋病毒遗传异质性 与表型相关的方法， 将遗传距离分为区域、时间和地点效应; 评估目标1 - 3中制定的方法对 表型种群的遗传组成;（6） 将目标1 - 4中的方法计算机化为可通过互联网访问的免费软件; 和（7）使用 将它们的意义转化为遗传背景的范例。

DESCRIPTION (provided by applicant): Clinical trials have demonstrated the ability of combination therapy to curtail the amount of HIV virus (viral load) in plasma. Ironically, the use of such therapy may promote proliferation of viral drug resistant genotypes, leaving patients with few options for subsequent treatment. Alternative, genotypic-based strategies that make use of the relationship between HIV genetic alterations with some phenotypic treatment response like viral drug susceptibility are being researched to guide treatment choice. This relationship is difficult to study, due in part to its high-dimension, the quasi-species nature of HIV, and the presence of other relationships often imbedded in it, which if neglected, may lead to incorrect interpretations and treatment. For example, because of a known viral load (or other covariate) effect on observed HIV genotypes and the potential for viral load to affect the phenotype under consideration, its relationship with HIV genetic heterogeneity is likely to be confounded by viral load heterogeneity among phenotypes. The primary hypothesis to be examined is that sources of heterogeneity other than HIV genetic can be identified between phenotypic groups and their contributions to genetic associations can be estimated. New methods are proposed for extrapolating HIV genetic from other heterogeneity sources associated with phenotype, based on a non-parametric (distribution-free) approach that uses a composite (sequence pair) measure of genetic distance. In comparison to other approaches, the proposed methods are more robust, since empirical, rather than analytically modeled distributions are compared and covariate-adjusted. The methods will be developed based on a profile analysis-type setting in which a series of related hypotheses for examining the relationship of interest are constructed. The specific aims are: (1) to construct a measure-theoretic framework for modeling quasi-species heterogeneity associated with covariates using distribution-free approaches, including distance-based; (2) to develop distribution-free approaches for identifying covariates that alter the relationship between HIV genetic heterogeneity and phenotype and to adjust this relationship for such covariates; (3) to extend the approaches in Aims 1 and 2 to address multivariate analysis of gene regions and temporal trends in HIV genetic heterogeneity associated with phenotype, in the presence of covariates that depend upon these continuums; (4) to characterize HIV genetic heterogeneity associated with phenotype by developing methods that translate composite genetic distance measures into region, time and location effects; (5) to assess the sensitivity of the methods developed in Aims 1-3 to the type of phenotypic populations with respect to their genetic compositions; (6) to computerize the methods in Aims 1-4 into a free, internet-accessible software; and (7) to communicate statistical tests to clinicians/virologists using paradigms that translate their meaning into genetic settings.