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Hope for GWAS: Relevant Risk Genes Uncovered from GWAS Statistical Noise

dc.contributor.authorCorreia, C.
dc.contributor.authorDiekmann, Y.
dc.contributor.authorVicente, A.M.
dc.contributor.authorPereira-Leal, J.B.
dc.date.accessioned2014-11-07T14:19:57Z
dc.date.available2014-11-07T14:19:57Z
dc.date.issued2014-09
dc.description.abstractHundreds 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.por
dc.identifier.citationInt J Mol Sci. 2014 Sep 29;15(10):17601-21. doi: 10.3390/ijms151017601.por
dc.identifier.doidoi:10.3390/ijms151017601
dc.identifier.issn1422-0067
dc.identifier.urihttp://hdl.handle.net/10400.18/2446
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherMolecular Diversity Preservation International (MDPI)por
dc.relation.publisherversionhttp://www.mdpi.com/1422-0067/15/10/17601por
dc.subjectGenome-wide Association Studies (GWAS)por
dc.subjectMissing Heritabilitypor
dc.subjectProtein-proteinpor
dc.subjectInteraction Networkspor
dc.subjectFunctional Coherencepor
dc.titleHope for GWAS: Relevant Risk Genes Uncovered from GWAS Statistical Noisepor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage17621por
oaire.citation.startPage17601por
oaire.citation.titleInternational Journal of Molecular Sciencespor
oaire.citation.volume15(10)por
rcaap.rightsopenAccesspor
rcaap.typearticlepor

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