Using biological networks to search for interacting loci in genome-wide association studies

被引：106

作者：

Emily, Mathieu ^{[1
,2
]}

Mailund, Thomas ^{[2
]}

Hein, Jotun ^{[3
]}

Schauser, Leif ^{[2
]}

Schierup, Mikkel Heide ^{[2
]}

机构：

[1] Univ Rennes 2, Univ Aarhus, Bioinformat Res Ctr, F-35043 Rennes, France

[2] Univ Aarhus, BiRC, Aarhus C, Denmark

[3] Univ Oxford, Dept Stat, Oxford OX1 3TG, England

来源：

EUROPEAN JOURNAL OF HUMAN GENETICS | 2009年 / 17卷 / 10期

关键词：

association studies; genome-wide scan; epistasis; biological network; ALZHEIMERS-DISEASE; PROTEIN; BETA; SCHIZOPHRENIA; EXPRESSION; EPISTASIS; DATABASE; CANCER; DOMAIN;

D O I：

10.1038/ejhg.2009.15

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

Genome-wide association studies have identified a large number of single-nucleotide polymorphisms (SNPs) that individually predispose to diseases. However, many genetic risk factors remain unaccounted for. Proteins coded by genes interact in the cell, and it is most likely that certain variants mainly affect the phenotype in combination with other variants, termed epistasis. An exhaustive search for epistatic effects is computationally demanding, as several billions of SNP pairs exist for typical genotyping chips. In this study, the experimental knowledge on biological networks is used to narrow the search for two-locus epistasis. We provide evidence that this approach is computationally feasible and statistically powerful. By applying this method to the Wellcome Trust Case-Control Consortium data sets, we report four significant cases of epistasis between unlinked loci, in susceptibility to Crohn's disease, bipolar disorder, hypertension and rheumatoid arthritis. European Journal of Human Genetics (2009) 17, 1231-1240; doi: 10.1038/ejhg.2009.15; published online 11 March 2009

引用

页码：1231 / 1240

页数：10

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