title: Protein interaction networks reveal novel autism risk genes within GWAS statistical noise.
abstract: Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.1) directly interact more than random expectation and are involved in a limited number of interconnected biological processes, indicating that they are functionally related. The functionally coherent networks generated by this approach contain ASD-relevant disease biology, as demonstrated by an improved positive predictive value and sensitivity in retrieving known ASD candidate genes relative to the top associated genes from either GWAS, as well as a higher gene overlap between the two ASD datasets. Analysis of the intersection between the networks obtained from the two ASD GWAS and six unrelated disease datasets identified fourteen genes exclusively present in the ASD networks. These are mostly novel genes involved in abnormal nervous system phenotypes in animal models, and in fundamental biological processes previously implicated in ASD, such as axon guidance, cell adhesion or cytoskeleton organization. Overall, our results highlighted novel susceptibility genes previously hidden within GWAS statistical "noise" that warrant further analysis for causal variants.
authors.affiliation: Departamento de Promoção da Saúde e Doenças não Transmissíveis, Instituto Nacional de Saúde Doutor Ricardo Jorge, 1649-016 Lisboa, Portugal; Center for Biodiversity, Functional & Integrative Genomics, Faculty of Sciences, University of Lisbon, 1749-016 Lisboa, Portugal; Instituto Gulbenkian de Ciência, 2780-156 Oeiras, Portugal.
authors.forename: Catarina
authors.initials: C
authors.lastname: Correia
authors.affiliation: Unidade Neurodesenvolvimento e Autismo, Centro de Desenvolvimento, Hospital Pediátrico (HP) do Centro Hospitalar e Universitário de Coimbra (CHUC), 3000-602 Coimbra, Portugal; Centro de Investigação e Formação Clinica do HP-CHUC, 3000-602 Coimbra, Portugal; Faculdade de Medicina da Universidade de Coimbra, 3000-548 Coimbra, Portugal.
authors.forename: Guiomar
authors.initials: G
authors.lastname: Oliveira
authors.affiliation: Departamento de Promoção da Saúde e Doenças não Transmissíveis, Instituto Nacional de Saúde Doutor Ricardo Jorge, 1649-016 Lisboa, Portugal; Center for Biodiversity, Functional & Integrative Genomics, Faculty of Sciences, University of Lisbon, 1749-016 Lisboa, Portugal; Instituto Gulbenkian de Ciência, 2780-156 Oeiras, Portugal.
authors.forename: Astrid M
authors.initials: AM
authors.lastname: Vicente
mesh_terms: D001321:Autistic Disorder / Q000235:genetics*; D019295:Computational Biology / Q000379:methods*; D053263:Gene Regulatory Networks; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study; D006801:Humans; D015233:Models, Statistical; D060066:Protein Interaction Maps