Rosenberg Noah A, Nordborg Magnus
Department of Human Genetics, Bioinformatics Program and the Life Sciences Institute, University of Michigan, Michigan 48109-2218, USA.
Genetics. 2006 Jul;173(3):1665-78. doi: 10.1534/genetics.105.055335. Epub 2006 Apr 2.
In linkage disequilibrium mapping of genetic variants causally associated with phenotypes, spurious associations can potentially be generated by any of a variety of types of population structure. However, mathematical theory of the production of spurious associations has largely been restricted to population structure models that involve the sampling of individuals from a collection of discrete subpopulations. Here, we introduce a general model of spurious association in structured populations, appropriate whether the population structure involves discrete groups, admixture among such groups, or continuous variation across space. Under the assumptions of the model, we find that a single common principle--applicable to both the discrete and admixed settings as well as to spatial populations--gives a necessary and sufficient condition for the occurrence of spurious associations. Using a mathematical connection between the discrete and admixed cases, we show that in admixed populations, spurious associations are less severe than in corresponding mixtures of discrete subpopulations, especially when the variance of admixture across individuals is small. This observation, together with the results of simulations that examine the relative influences of various model parameters, has important implications for the design and analysis of genetic association studies in structured populations.
在对与表型有因果关联的遗传变异进行连锁不平衡定位时,各种类型的群体结构都有可能产生虚假关联。然而,虚假关联产生的数学理论在很大程度上局限于涉及从离散亚群体集合中抽样个体的群体结构模型。在此,我们引入了一个结构化群体中虚假关联的通用模型,无论群体结构是涉及离散群体、此类群体间的混合,还是空间上的连续变异,该模型都适用。在该模型的假设下,我们发现一个单一的通用原则——适用于离散和混合情形以及空间群体——给出了虚假关联发生的充要条件。利用离散和混合情形之间的数学联系,我们表明在混合群体中,虚假关联比在离散亚群体的相应混合中要轻,尤其是当个体间混合方差较小时。这一观察结果,连同检验各种模型参数相对影响的模拟结果,对结构化群体中遗传关联研究的设计和分析具有重要意义。