Huang Yungui, Bartlett Christopher W, Segre Alberto M, O'Connell Jeffrey R, Mangin Lavonne, Vieland Veronica J
Center for Quantitative and Computational Biology, Columbus Children's Research Institute, 700 Children's Drive, Columbus, Ohio 43205, USA.
BMC Proc. 2007;1 Suppl 1(Suppl 1):S64. doi: 10.1186/1753-6561-1-s1-s64. Epub 2007 Dec 18.
When two genes interact to cause a clinically important phenotype, it would seem reasonable to expect that we could leverage genotypic information at one of the loci in order to improve our ability to detect the other. We were therefore interested in extending the posterior probability of linkage (PPL), a class of linkage statistics we have been developing over the past decade, in order to explicitly allow for gene x gene interaction. In this report we utilize a new implementation of the PPL incorporating liability classes (LCs), which provide a direct parameterization of gene x gene interaction by allowing the penetrances at the locus being evaluated to depend upon measured genotypes at a known locus. With knowledge of the generating model for the simulated rheumatoid arthritis (RA) data, we selected two loci for examination: Locus A, which in interaction with the HLA-DR antigen locus affects risk of the dichotomous RA phenotype; and Locus E, which in interaction with DR affects quantitative levels of the anti-CCP phenotype. The data comprised nuclear families of two parents and an affected sib pair (ASP). Our results confirm theoretical work suggesting that gene x gene interactions CANNOT be leveraged to improve linkage detection for dichotomous traits based on affecteds-only data structures. However, incorporation of DR-based LCs did lead to appreciably higher quantitative trait PPLs. This suggests that gene x gene interactions could be effectively used in quantitative trait analyses even when families have been ascertained as ASPs for a related dichotomous trait.
当两个基因相互作用导致临床上重要的表型时，似乎有理由期望我们能够利用其中一个位点的基因型信息来提高我们检测另一个位点的能力。因此，我们有兴趣扩展连锁后验概率（PPL），这是我们在过去十年中一直在开发的一类连锁统计量，以便明确考虑基因×基因相互作用。在本报告中，我们利用了一种结合了易患性类别（LCs）的PPL新实现方法，通过允许在被评估位点的外显率取决于已知位点的测量基因型，为基因×基因相互作用提供了直接的参数化。基于模拟类风湿性关节炎（RA）数据的生成模型，我们选择了两个位点进行检查：位点A，它与HLA - DR抗原位点相互作用影响二分法RA表型的风险；以及位点E，它与DR相互作用影响抗环瓜氨酸肽（anti - CCP）表型的定量水平。数据包括由两个亲本和一个患病同胞对（ASP）组成的核心家庭。我们的结果证实了理论研究结果，即基于仅患病个体的数据结构，基因×基因相互作用无法用于改善对二分性状的连锁检测。然而，纳入基于DR的LC确实导致定量性状的PPL明显更高。这表明即使家庭是作为相关二分性状的ASP确定的，基因×基因相互作用也可以有效地用于定量性状分析。
