Sequence Kernel Association Tests for the Combined Effect of Rare and Common Variants

被引:335
|
作者
Ionita-Laza, Iuliana [1 ]
Lee, Seunggeun [2 ]
Makarov, Vlad [1 ]
Buxbaum, Joseph D. [3 ,4 ,5 ,6 ]
Lin, Xihong [2 ]
机构
[1] Columbia Univ, Dept Biostat, New York, NY 10032 USA
[2] Harvard Univ, Dept Biostat, Boston, MA 02115 USA
[3] Icahn Sch Med Mt Sinai, Seaver Autism Ctr, New York, NY 10029 USA
[4] Icahn Sch Med Mt Sinai, Dept Psychiat Neurosci & Genet, New York, NY 10029 USA
[5] Icahn Sch Med Mt Sinai, Dept Genom Sci, New York, NY 10029 USA
[6] Icahn Sch Med Mt Sinai, Friedman Brain Inst, New York, NY 10029 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
DISEASE ASSOCIATION; GENETIC-VARIANTS; GENOME; FRAMEWORK; SET; PROPORTION; RISK; SNPS;
D O I
10.1016/j.ajhg.2013.04.015
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
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.
引用
收藏
页码:841 / 853
页数:13
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