Risch N, Teng J
Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA.
Genome Res. 1998 Dec;8(12):1273-88. doi: 10.1101/gr.8.12.1273.
We consider statistics for analyzing a variety of family-based and nonfamily-based designs for detecting linkage disequilibrium of a marker with a disease susceptibility locus. These designs include sibships with parents, sibships without parents, and use of unrelated controls. We also provide formulas for and evaluate the relative power of different study designs using these statistics. In this first paper in the series, we derive statistical tests based on data derived from DNA pooling experiments and describe their characteristics. Although designs based on affected and unaffected sibs without parents are usually robust to population stratification, they suffer a loss of power compared with designs using parents or unrelateds as controls. Although increasing the number of unaffected sibs improves power, the increase is generally not substantial. Designs including sibships with multiple affected sibs are typically the most powerful, with any of these control groups, when the disease allele frequency is low. When the allele frequency is high, however, designs with unaffected sibs as controls do not retain this advantage. In designs with parents, having an affected parent has little impact on the power, except for rare dominant alleles, where the power is increased compared with families with no affected parents. Finally, we also demonstrate that for sibships with parents, only the parents require individual genotyping to derive the TDT statistic, whereas all the offspring can be pooled. This can potentially lead to considerable savings in genotyping, especially for multiplex sibships. The formulas and tables we derive should provide some guidance to investigators designing nuclear family-based linkage disequilibrium studies for complex diseases.
我们考虑用于分析各种基于家系和非基于家系的设计的统计方法,以检测标记与疾病易感基因座之间的连锁不平衡。这些设计包括有父母的同胞对、无父母的同胞对以及使用无关对照。我们还给出了使用这些统计方法的不同研究设计的相对效能的公式并进行了评估。在本系列的第一篇论文中,我们基于DNA池实验得到的数据推导了统计检验方法并描述了它们的特征。尽管基于无父母的患病和未患病同胞对的设计通常对群体分层具有稳健性,但与使用父母或无关个体作为对照的设计相比,它们的效能有所损失。尽管增加未患病同胞对的数量可提高效能,但这种提高通常并不显著。当疾病等位基因频率较低时,包含多个患病同胞对的设计通常是最有效的,无论使用哪种对照组。然而,当等位基因频率较高时,以未患病同胞对作为对照的设计并不具有这一优势。在有父母的设计中,有患病父母对效能影响不大,除了罕见的显性等位基因,在这种情况下与没有患病父母家庭相比效能会增加。最后,我们还证明,对于有父母的同胞对,只需对父母进行个体基因分型即可得出传递不平衡检验(TDT)统计量,而所有后代可以进行DNA池化。这可能会在基因分型方面节省大量成本,尤其是对于多个同胞对的家庭而言。我们推导的公式和表格应为设计基于核心家系的复杂疾病连锁不平衡研究的研究者提供一些指导。