Centre for Molecular, Environmental, Genetic, and Analytic (MEGA) Epidemiology, University of Melbourne, Melbourne, Australia.
Genet Epidemiol. 2010 May;34(4):309-18. doi: 10.1002/gepi.20462.
Haplotype-based association studies have been proposed as a powerful comprehensive approach to identify causal genetic variation underlying complex diseases. Data comparisons within families offer the additional advantage of dealing naturally with complex sources of noise, confounding and population stratification. Two problems encountered when investigating associations between haplotypes and a continuous trait using data from sibships are (i) the need to define within-sibship comparisons for sibships of size greater than two and (ii) the difficulty of resolving the joint distribution of haplotype pairs within sibships in the absence of parental genotypes. We therefore propose first a method of orthogonal transformation of both outcomes and exposures that allow the decomposition of between- and within-sibship regression effects when sibship size is greater than two. We conducted a simulation study, which confirmed analysis using all members of a sibship is statistically more powerful than methods based on cross-sectional analysis or using subsets of sib-pairs. Second, we propose a simple permutation approach to avoid errors of inference due to the within-sibship correlation of any errors in haplotype assignment. These methods were applied to investigate the association between mammographic density (MD), a continuously distributed and heritable risk factor for breast cancer, and single nucleotide polymorphisms (SNPs) and haplotypes from the VDR gene using data from a study of 430 twins and sisters. We found evidence of association between MD and a 4-SNP VDR haplotype. In conclusion, our proposed method retains the benefits of the between- and within-pair analysis for pairs of siblings and can be implemented in standard software.
基于单体型的关联研究被提议为一种强大的综合方法，用于识别复杂疾病潜在的因果遗传变异。在家庭内进行数据比较具有处理复杂噪声、混杂和群体分层等复杂来源的额外优势。在使用来自同胞对的数据研究单体型与连续性状之间的关联时，会遇到两个问题：（i）需要为大小大于 2 的同胞对定义同胞内比较，以及（ii）在没有父母基因型的情况下，难以解析同胞内单体型对的联合分布。因此，我们首先提出了一种对结果和暴露进行正交变换的方法，当同胞对大小大于 2 时，该方法允许分解同胞间和同胞内的回归效应。我们进行了一项模拟研究，证实了当使用同胞对的所有成员进行分析时，其统计效力比基于横断面分析或使用同胞对子集的方法更高。其次，我们提出了一种简单的置换方法，以避免由于单体型分配中的任何误差的同胞内相关性而导致的推断错误。这些方法被应用于使用来自一项 430 对双胞胎和姐妹的研究中的 VDR 基因的单核苷酸多态性（SNP）和单体型来研究乳腺密度（MD）与乳腺癌的连续分布和遗传风险因素之间的关联。我们发现 MD 与 VDR 基因的 4-SNP 单体型之间存在关联的证据。总之，我们提出的方法保留了对同胞对进行的同胞间和同胞内分析的优势，并且可以在标准软件中实现。
