Rare-Variant Extensions of the Transmission Disequilibrium Test: Application to Autism Exome Sequence Data
Rare-Variant Extensions of the Transmission Disequilibrium Test: Application to Autism Exome Sequence Data
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DOI：
10.1016/j.ajhg.2013.11.021
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发表时间：
2014-01-02
影响因子：
9.8
通讯作者：
Leal, Suzanne M.
中科院分区：
文献类型：
--
作者：
He, Zongxiao;O'Roak, Brian J.;Leal, Suzanne M.
许多基于群体的罕见变异（RV）关联检验方法已经被开发出来用于分析序列数据，这些方法是对一个区域内的变异进行汇总。分析基于群体的数据的一个缺点是难以充分控制群体亚结构和混合情况，并且可能会出现虚假关联。对于罕见变异来说，这个问题可能很严重，因为不同群体之间罕见变异的频谱可能差异很大。一种解决方案是通过使用传递不平衡检验（TDT）来分析亲子三联体数据，该检验对群体亚结构和混合情况具有稳健性。我们将TDT扩展，使用四种常用方法来检验罕见变异关联。我们证明，对于所有的罕见变异 - TDT方法，使用恰当的分析策略时，即使存在高水平的群体亚结构或混合情况，I型错误也能得到很好的控制。对于三联体数据，与基于群体的数据不同，罕见变异等位基因计数关联方法会导致I型错误膨胀。然而，通过单倍型置换凭经验获取p值可以恰当地控制I型错误。我们对罕见变异 - TDT方法的功效进行了评估，并与多种遗传和疾病模型的病例 - 对照数据分析进行了比较。我们还使用罕见变异 - TDT分析了来自199个西蒙斯单纯性集合自闭症三联体的外显子组数据，并观察到与ABCA7中的变异存在关联。鉴于在罕见变异关联研究中充分控制群体亚结构和混合情况的问题以及基于序列的三联体研究数量的不断增加，罕见变异 - TDT对于阐明罕见变异在复杂性状病因学中的作用是非常有益的。
Many population-based rare-variant (RV) association tests, which aggregate variants across a region, have been developed to analyze sequence data. A drawback of analyzing population-based data is that it is difficult to adequately control for population substructure and admixture, and spurious associations can occur. For RVs, this problem can be substantial, because the spectrum of rare variation can differ greatly between populations. A solution is to analyze parent-child trio data, by using the transmission disequilibrium test (TDT), which is robust to population substructure and admixture. We extended the TDT to test for RV associations using four commonly used methods. We demonstrate that for all RV-TDT methods, using proper analysis strategies, type I error is well-controlled even when there are high levels of population substructure or admixture. For trio data, unlike for population-based data, RV allele-counting association methods will lead to inflated type I errors. However type I errors can be properly controlled by obtaining p values empirically through haplotype permutation. The power of the RV-TDT methods was evaluated and compared to the analysis of case-control data with a number of genetic and disease models. The RV-TDT was also used to analyze exome data from 199 Simons Simplex Collection autism trios and an association was observed with variants in ABCA7. Given the problem of adequately controlling for population substructure and admixture in RV association studies and the growing number of sequence-based trio studies, the RV-TDT is extremely beneficial to elucidate the involvement of RVs in the etiology of complex traits.