Bayesian Hierarchical Modeling of the HIV Evolutionary Response to Therapy

• 成果类型: Article
• 署名作者: Jensen, Shane T.; Park, Jared; Braunstein, Alexander F.; McAuliffe, Jon
• 署名单位: University of Pennsylvania; University of California System; University of California Berkeley
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2013.830449
• 发表日期: 2013
• 页码: 1230-1242
• 关键词: immunodeficiency-virus type-1; sequence evolution; dna-sequences; recombination; deaminases; resistance; samples; rna

摘要

A major challenge for the treatment of human immunodeficiency virus (HIV) infection is the development of therapy-resistant strains. We present a statistical model that quantifies the evolution of HIV populations when exposed to particular therapies. A hierarchical Bayesian approach is used to estimate differences in rates of nucleotide changes between treatment- and control-group sequences. Each group's rates are allowed to vary spatially along the HIV genome. We employ a coalescent structure to address the sequence diversity within the treatment and control HIV populations. We evaluate the model in simulations and estimate HIV evolution in two different applications: a conventional drug therapy and an antisense gene therapy. In both studies, we detect evidence of evolutionary escape response in the HIV population. Supplementary materials for this article are available online.