Genome-Wide Association Analysis of Imputed Rare Variants: Application to Seven Common Complex Diseases

被引:23
作者
Maegi, Reedik [2 ]
Asimit, Jennifer L. [3 ]
Day-Williams, Aaron G. [3 ]
Zeggini, Eleftheria [3 ]
Morris, Andrew P. [1 ]
机构
[1] Univ Oxford, Genet & Genom Epidemiol Unit, Wellcome Trust Ctr Human Genet, Oxford OX3 7BN, England
[2] Univ Tartu, Estonian Genome Ctr, EE-50090 Tartu, Estonia
[3] Wellcome Trust Sanger Inst, Hinxton, Cambs, England
基金
英国惠康基金;
关键词
genome-wide association study; rare variants; imputation; DIABETES SUSCEPTIBILITY; LOCI; IMPUTATION; SEQUENCE; GENES; RISK; HERITABILITY; STRATEGIES; COVERAGE; SAMPLES;
D O I
10.1002/gepi.21675
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Genome-wide association studies have been successful in identifying loci contributing effects to a range of complex human traits. The majority of reproducible associations within these loci are with common variants, each of modest effect, which together explain only a small proportion of heritability. It has been suggested that much of the unexplained genetic component of complex traits can thus be attributed to rare variation. However, genome-wide association study genotyping chips have been designed primarily to capture common variation, and thus are underpowered to detect the effects of rare variants. Nevertheless, we demonstrate here, by simulation, that imputation from an existing scaffold of genome-wide genotype data up to high-density reference panels has the potential to identify rare variant associations with complex traits, without the need for costly re-sequencing experiments. By application of this approach to genome-wide association studies of seven common complex diseases, imputed up to publicly available reference panels, we identify genome-wide significant evidence of rare variant association in PRDM10 with coronary artery disease and multiple genes in the major histocompatibility complex (MHC) with type 1 diabetes. The results of our analyses highlight that genome-wide association studies have the potential to offer an exciting opportunity for gene discovery through association with rare variants, conceivably leading to substantial advancements in our understanding of the genetic architecture underlying complex human traits. Genet. Epidemiol. 36:785-796, 2012. (C) 2012 Wiley Periodicals, Inc
引用
收藏
页码:785 / 796
页数:12
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