title: Hope for GWAS: relevant risk genes uncovered from GWAS statistical noise.
abstract: Hundreds of genetic variants have been associated to common diseases through genome-wide association studies (GWAS), yet there are limits to current approaches in detecting true small effect risk variants against a background of false positive findings. Here we addressed the missing heritability problem, aiming to test whether there are indeed risk variants within GWAS statistical noise and to develop a systematic strategy to retrieve these hidden variants. Employing an integrative approach, which combines protein-protein interactions with association data from GWAS for 6 common diseases, we found that associated-genes at less stringent significance levels (p < 0.1) with any of these diseases are functionally connected beyond noise expectation. This functional coherence was used to identify disease-relevant subnetworks, which were shown to be enriched in known genes, outperforming the selection of top GWAS genes. As a proof of principle, we applied this approach to breast cancer, supporting well-known breast cancer genes, while pinpointing novel susceptibility genes for experimental validation. This study reinforces the idea that GWAS are under-analyzed and that missing heritability is rather hidden. It extends the use of protein networks to reveal this missing heritability, thus leveraging the large investment in GWAS that produced so far little tangible gain.
authors.affiliation: Instituto Nacional de Saúde Doutor Ricardo Jorge, Av. Padre Cruz, Lisboa 1649-016, Portugal. ccorreia@igc.gulbenkian.pt.
authors.forename: Catarina
authors.initials: C
authors.lastname: Correia
authors.affiliation: Instituto Gulbenkian de Ciência, Oeiras 2780-156, Portugal. ydiekmann@igc.gulbenkian.pt.
authors.forename: Yoan
authors.initials: Y
authors.lastname: Diekmann
authors.affiliation: Instituto Nacional de Saúde Doutor Ricardo Jorge, Av. Padre Cruz, Lisboa 1649-016, Portugal. astrid.vicente@insa.min-saude.pt.
authors.forename: Astrid M
authors.initials: AM
authors.lastname: Vicente
authors.affiliation: Instituto Gulbenkian de Ciência, Oeiras 2780-156, Portugal. jleal@igc.gulbenkian.pt.
authors.forename: José B
authors.initials: JB
authors.lastname: Pereira-Leal
mesh_terms: D001943:Breast Neoplasms / Q000235:genetics / Q000473:pathology; D005260:Female; D020022:Genetic Predisposition to Disease / Q000235:genetics; D055106:Genome-Wide Association Study; D006801:Humans; D015233:Models, Statistical; D020641:Polymorphism, Single Nucleotide; D060066:Protein Interaction Maps / Q000235:genetics