Sequence Kernel Association Tests for the Combined Effect of Rare and Common Variants
Sequence Kernel Association Tests for the Combined Effect of Rare and Common Variants
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DOI：
10.1016/j.ajhg.2013.04.015
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发表时间：
2013-06-06
影响因子：
9.8
通讯作者：
Lin, Xihong
中科院分区：
文献类型：
--
作者：
Ionita-Laza, Iuliana;Lee, Seunggeun;Lin, Xihong
测序技术的最新发展使得发现罕见和常见的遗传变异成为可能。全基因组关联研究 (GWAS) 可以测试常见变异的影响，而基于序列的关联研究可以评估罕见和常见变异对疾病风险的累积影响。为此目的，已经提出了许多分组关联测试，包括负担测试和方差分量测试。尽管此类测试并未将常见变异排除在评估之外，但它们主要侧重于通过增加稀有变异效应并降低常见变异效应来测试稀有变异的影响，因此，当一个地区的罕见和常见遗传变异都影响性状易感性时，它们可能会失去实质性功效。越来越多的证据表明，给定位点的风险变异等位基因谱可能包括新颖、罕见、低频和常见的遗传变异。在这里，我们引入了几种序列核关联测试来评估罕见和常见变异的累积效应。所提出的测试计算效率高，并且适用于二元和连续特征。此外，如果可用，它们可以轻松地将同一个体的 GWAS 和全外显子组测序数据结合起来，并且也适用于 GWAS 位点的深度重测序数据。我们在综合场景下模拟的数据上评估这些测试，并表明与最常用的测试（包括负担和方差分量测试）相比，它们可以实现功效的大幅提高。接下来我们将展示在克罗恩病和自闭症谱系障碍测序研究中的应用。提议的测试已纳入软件包 SKAT 中。
Recent developments in sequencing technologies have made it possible to uncover both rare and common genetic variants. Genome-wide association studies (GWASs) can test for the effect of common variants, whereas sequence-based association studies can evaluate the cumulative effect of both rare and common variants on disease risk. Many groupwise association tests, including burden tests and variance-component tests, have been proposed for this purpose. Although such tests do not exclude common variants from their evaluation, they focus mostly on testing the effect of rare variants by upweighting rare-variant effects and downweighting common-variant effects and can therefore lose substantial power when both rare and common genetic variants in a region influence trait susceptibility. There is increasing evidence that the allelic spectrum of risk variants at a given locus might include novel, rare, low-frequency, and common genetic variants. Here, we introduce several sequence kernel association tests to evaluate the cumulative effect of rare and common variants. The proposed tests are computationally efficient and are applicable to both binary and continuous traits. Furthermore, they can readily combine GWAS and whole-exome-sequencing data on the same individuals, when available, and are also applicable to deep-resequencing data of GWAS loci. We evaluate these tests on data simulated under comprehensive scenarios and show that compared with the most commonly used tests, including the burden and variance-component tests, they can achieve substantial increases in power. We next show applications to sequencing studies for Crohn disease and autism spectrum disorders. The proposed tests have been incorporated into the software package SKAT.