title: Meta-analysis of heterogeneous data sources for genome-scale identification of risk genes in complex phenotypes.
abstract: Meta-analyses of large-scale association studies typically proceed solely within one data type and do not exploit the potential complementarities in other sources of molecular evidence. Here, we present an approach to combine heterogeneous data from genome-wide association (GWA) studies, protein-protein interaction screens, disease similarity, linkage studies, and gene expression experiments into a multi-layered evidence network which is used to prioritize the entire protein-coding part of the genome identifying a shortlist of candidate genes. We report specifically results on bipolar disorder, a genetically complex disease where GWA studies have only been moderately successful. We validate one such candidate experimentally, YWHAH, by genotyping five variations in 640 patients and 1,377 controls. We found a significant allelic association for the rs1049583 polymorphism in YWHAH (adjusted P = 5.6e-3) with an odds ratio of 1.28 [1.12-1.48], which replicates a previous case-control study. In addition, we demonstrate our approach's general applicability by use of type 2 diabetes data sets. The method presented augments moderately powered GWA data, and represents a validated, flexible, and publicly available framework for identifying risk genes in highly polygenic diseases. The method is made available as a web service at www.cbs.dtu.dk/services/metaranker.
authors.affiliation: Center for Biological Sequence Analysis, Technical University of Denmark, Lyngby, Denmark.
authors.forename: Tune H
authors.initials: TH
authors.lastname: Pers
authors.forename: Niclas Tue
authors.initials: NT
authors.lastname: Hansen
authors.forename: Kasper
authors.initials: K
authors.lastname: Lage
authors.forename: Pernille
authors.initials: P
authors.lastname: Koefoed
authors.forename: Piotr
authors.initials: P
authors.lastname: Dworzynski
authors.forename: Martin Lee
authors.initials: ML
authors.lastname: Miller
authors.forename: Tracey J
authors.initials: TJ
authors.lastname: Flint
authors.forename: Erling
authors.initials: E
authors.lastname: Mellerup
authors.forename: Henrik
authors.initials: H
authors.lastname: Dam
authors.forename: Ole A
authors.initials: OA
authors.lastname: Andreassen
authors.forename: Srdjan
authors.initials: S
authors.lastname: Djurovic
authors.forename: Ingrid
authors.initials: I
authors.lastname: Melle
authors.forename: Anders D
authors.initials: AD
authors.lastname: Børglum
authors.forename: Thomas
authors.initials: T
authors.lastname: Werge
authors.forename: Shaun
authors.initials: S
authors.lastname: Purcell
authors.forename: Manuel A
authors.initials: MA
authors.lastname: Ferreira
authors.forename: Irene
authors.initials: I
authors.lastname: Kouskoumvekaki
authors.forename: Christopher T
authors.initials: CT
authors.lastname: Workman
authors.forename: Torben
authors.initials: T
authors.lastname: Hansen
authors.forename: Ole
authors.initials: O
authors.lastname: Mors
authors.forename: Søren
authors.initials: S
authors.lastname: Brunak
mesh_terms: D001714:Bipolar Disorder / Q000235:genetics; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics; D056726:Genetic Association Studies; D055106:Genome-Wide Association Study / Q000706:statistics & numerical data*; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D020641:Polymorphism, Single Nucleotide; D025941:Protein Interaction Mapping / Q000706:statistics & numerical data