Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits

被引：1052

作者：

Yang, Jian ^{[1
,2
]}

Ferreira, Teresa ^{[3
]}

Morris, Andrew P. ^{[3
]}

Medland, Sarah E. ^{[1
]}

Madden, Pamela A. F. ^{[4
]}

Heath, Andrew C. ^{[4
]}

Martin, Nicholas G. ^{[1
]}

Montgomery, Grant W. ^{[1
]}

Weedon, Michael N. ^{[5
]}

Loos, Ruth J. ^{[6
]}

Frayling, Timothy M. ^{[5
]}

McCarthy, Mark I. ^{[3
,7
]}

Hirschhorn, Joel N. ^{[8
,9
,10
,11
,12
]}

Goddard, Michael E. ^{[13
,14
]}

Visscher, Peter M. ^{[1
,2
,15
]}

机构：

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

[2] Univ Queensland, Diamantina Inst, Princess Alexandra Hosp, Brisbane, Qld, Australia

[3] Univ Oxford, Wellcome Trust Ctr Human Genet, Oxford, England

[4] Washington Univ, Dept Psychiat, St Louis, MO USA

[5] Univ Exeter, Peninsula Coll Med & Dent, Exeter, Devon, England

[6] Addenbrookes Hosp, MRC, Epidemiol Unit, Inst Metab Sci, Cambridge, England

[7] Oxford Ctr Diabet Endocrinol & Metab, Oxford, England

[8] Childrens Hosp, Program Genom, Boston, MA 02115 USA

[9] Childrens Hosp, Div Genet, Boston, MA 02115 USA

[10] Childrens Hosp, Div Endocrinol, Boston, MA 02115 USA

[11] Broad Inst, Cambridge, MA USA

[12] Harvard Univ, Sch Med, Dept Genet, Boston, MA USA

[13] Univ Melbourne, Dept Food & Agr Syst, Parkville, Vic 3052, Australia

[14] Dept Primary Ind, Biosci Res Div, Bundoora, Vic, Australia

[15] Univ Queensland, Queensland Brain Inst, Brisbane, Qld, Australia

来源：

NATURE GENETICS | 2012年 / 44卷 / 04期

基金：

美国国家卫生研究院; 英国医学研究理事会; 英国惠康基金; 澳大利亚研究理事会;

关键词：

GENOME-WIDE ASSOCIATION; BODY-MASS INDEX; COMMON SNPS; SUSCEPTIBILITY LOCI; GENETIC-VARIATION; HUMAN HEIGHT; HERITABILITY; DISEASE; RISK; MAP;

D O I：

10.1038/ng.2213

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium.

引用

页码：369 / U170

页数：10

共 4 条

[1] Conditional analysis of multiple quantitative traits based on marginal GWAS summary statistics
Deng, Yangqing
Pan, Wei
GENETIC EPIDEMIOLOGY, 2017, 41 (05) : 427 - 436
[2] Methods for meta-analysis of multiple traits using GWAS summary statistics
Ray, Debashree
Boehnke, Michael
GENETIC EPIDEMIOLOGY, 2018, 42 (02) : 134 - 145
[3] Primo: integration of multiple GWAS and omics QTL summary statistics for elucidation of molecular mechanisms of trait-associated SNPs and detection of pleiotropy in complex traits
Gleason, Kevin J.
Yang, Fan
Pierce, Brandon L.
He, Xin
Chen, Lin S.
GENOME BIOLOGY, 2020, 21 (01)
[4] Fast set-based association analysis using summary data from GWAS identifies novel gene loci for human complex traits
Bakshi, Andrew
Zhu, Zhihong
Vinkhuyzen, Anna A. E.
Hill, W. David
Mcrae, Allan F.
Visscher, Peter M.
Yang, Jian
SCIENTIFIC REPORTS, 2016, 6

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