Estimating Missing Heritability for Disease from Genome-wide Association Studies

被引：755

作者：

Lee, Sang Hong ^{[1
]}

Wray, Naomi R. ^{[1
]}

Goddard, Michael E. ^{[2
,3
]}

Visscher, Peter M. ^{[1
]}

机构：

[1] Queensland Inst Med Res, Herston, Qld 4006, Australia

[2] Dept Primary Ind, Biosci Res Div, Melbourne, Vic 3086, Australia

[3] Univ Melbourne, Dept Agr & Food Syst, Melbourne, Vic 3010, Australia

来源：

AMERICAN JOURNAL OF HUMAN GENETICS | 2011年 / 88卷 / 03期

基金：

英国惠康基金; 英国医学研究理事会; 澳大利亚研究理事会;

关键词：

COMMON SNPS EXPLAIN; LARGE PROPORTION; INFORMATION; LIABILITY; VARIANCE;

D O I：

10.1016/j.ajhg.2011.02.002

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

Genome-wide association studies are designed to discover SNPs that are associated with a complex trait. Employing strict significance thresholds when testing individual SNPs avoids false positives at the expense of increasing false negatives. Recently, we developed a method for quantitative traits that estimates the variation accounted for when fitting all SNPs simultaneously. Here we develop this method further for case-control studies. We use a linear mixed model for analysis of binary traits and transform the estimates to a liability scale by adjusting both for scale and for ascertainment of the case samples. We show by theory and simulation that the method is unbiased. We apply the method to data from the Wellcome Trust Case Control Consortium and show that a substantial proportion of variation in liability for Crohn disease, bipolar disorder, and type I diabetes is tagged by common SNPs.

引用

页码：294 / 305

页数：12

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