Hutcheson H B, Lautenberger J A, Nelson G W, Pontius J U, Kessing B D, Winkler C A, Smith M W, Johnson R, Stephens R, Phair J, Goedert J J, Donfield S, O'Brien S J
Laboratory of Genomic Diversity, National Cancer Institute-Frederick, Frederick, MD 21702, USA.
Vaccine. 2008 Jun 6;26(24):2951-65. doi: 10.1016/j.vaccine.2007.12.054. Epub 2008 Feb 1.
The screening of common genetic polymorphisms among candidate genes for AIDS pathology in HIV exposed cohort populations has led to the description of 20 AIDS restriction genes (ARGs), variants that affect susceptibility to HIV infection or to AIDS progression. The combination of high-throughput genotyping platforms and the recent HapMap annotation of some 3 million human SNP variants has been developed for and applied to gene discovery in complex and multi-factorial diseases. Here, we explore novel computational approaches to ARG discovery which consider interacting analytical models, various genetic influences, and SNP-haplotype/LD structure in AIDS cohort populations to determine if these ARGs could have been discovered using an unbiased genome-wide association approach. The procedures were evaluated by tracking the performance of haplotypes and SNPs within ARG regions to detect genetic association in the same AIDS cohort populations in which the ARGs were originally discovered. The methodology captures the signals of multiple non-independent AIDS-genetic association tests of different disease stages and uses association signal strength (odds ratio or relative hazard), statistical significance (p-values), gene influence, internal replication, and haplotype structure together as a multi-facetted approach to identifying important genetic associations within a deluge of genotyping/test data. The complementary approaches perform rather well and predict the detection of a variety of undiscovered ARGs that affect different stages of HIV/AIDS pathogenesis using genome-wide association analyses.
在暴露于HIV的队列人群中,对艾滋病病理候选基因中的常见基因多态性进行筛查,已确定了20个艾滋病限制基因(ARG),这些基因变体影响对HIV感染或艾滋病进展的易感性。高通量基因分型平台与最近对约300万个人类SNP变体的HapMap注释相结合,已被开发并应用于复杂多因素疾病的基因发现。在此,我们探索发现ARG的新计算方法,该方法考虑相互作用的分析模型、各种遗传影响以及艾滋病队列人群中的SNP单倍型/连锁不平衡(LD)结构,以确定是否可以使用无偏全基因组关联方法发现这些ARG。通过追踪ARG区域内单倍型和SNP的表现来评估程序,以检测在最初发现ARG的同一艾滋病队列人群中的基因关联。该方法捕捉不同疾病阶段多个非独立艾滋病基因关联测试的信号,并将关联信号强度(比值比或相对风险)、统计学显著性(p值)、基因影响、内部重复以及单倍型结构作为一种多方面的方法,用于在大量基因分型/测试数据中识别重要的基因关联。这些互补方法表现相当出色,并预测使用全基因组关联分析可检测到影响HIV/AIDS发病机制不同阶段的多种未发现的ARG。