Fallin D, Cohen A, Essioux L, Chumakov I, Blumenfeld M, Cohen D, Schork N J
Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio 44109, USA.
Genome Res. 2001 Jan;11(1):143-51. doi: 10.1101/gr.148401.
There is growing debate over the utility of multiple locus association analyses in the identification of genomic regions harboring sequence variants that influence common complex traits such as hypertension and diabetes. Much of this debate concerns the manner in which one can use the genotypic information from individuals gathered in simple sampling frameworks, such as the case/control designs, to actually assess the association between alleles in a particular genomic region and a trait. In this paper we describe methods for testing associations between estimated haplotype frequencies derived from multilocus genotype data and disease endpoints assuming a simple case/control sampling design. These proposed methods overcome the lack of phase information usually associated with samples of unrelated individuals and provide a comprehensive way of assessing the relationship between sequence or multiple-site variation and traits and diseases within populations. We applied the proposed methods in a study of the relationship between polymorphisms within the APOE gene region and Alzheimer's disease. Cases and controls for this study were collected from the United States and France. Our results confirm the known association between the APOE locus and Alzheimer's disease, even when the epsilon 4 polymorphism is not contained in the tested haplotypes. This suggests that, in certain situations, haplotype information and linkage disequilibrium-induced associations between polymorphic loci that neighbor loci harboring functional sequence variants can be exploited to identify disease-predisposing alleles in large, freely mixing populations via estimated haplotype frequency methods.
在识别含有影响常见复杂性状(如高血压和糖尿病)的序列变异的基因组区域时,多位点关联分析的效用引发了越来越多的争论。这场争论的大部分内容涉及如何利用在简单抽样框架(如病例/对照设计)中收集的个体基因型信息,来实际评估特定基因组区域中的等位基因与某一性状之间的关联。在本文中,我们描述了在假设简单病例/对照抽样设计的情况下,用于检验从多位点基因型数据推导的估计单倍型频率与疾病终点之间关联的方法。这些提出的方法克服了通常与无关个体样本相关的相位信息缺失问题,并提供了一种全面的方式来评估群体内序列或多位点变异与性状及疾病之间的关系。我们将提出的方法应用于一项关于载脂蛋白E(APOE)基因区域内多态性与阿尔茨海默病之间关系的研究。该研究的病例和对照来自美国和法国。我们的结果证实了APOE基因座与阿尔茨海默病之间已知的关联,即使测试的单倍型中不包含ε4多态性。这表明,在某些情况下,单倍型信息以及与携带功能序列变异的位点相邻的多态性位点之间由连锁不平衡引起的关联,可以通过估计单倍型频率方法,在大型自由混合群体中用于识别疾病易感等位基因。