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Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise

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 dise...

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Autores principales: Correia, Catarina, Oliveira, Guiomar, Vicente, Astrid M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4237351/
https://www.ncbi.nlm.nih.gov/pubmed/25409314
http://dx.doi.org/10.1371/journal.pone.0112399
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author Correia, Catarina
Oliveira, Guiomar
Vicente, Astrid M.
author_facet Correia, Catarina
Oliveira, Guiomar
Vicente, Astrid M.
author_sort Correia, Catarina
collection PubMed
description 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.
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spelling pubmed-42373512014-11-21 Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise Correia, Catarina Oliveira, Guiomar Vicente, Astrid M. PLoS One Research Article 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. Public Library of Science 2014-11-19 /pmc/articles/PMC4237351/ /pubmed/25409314 http://dx.doi.org/10.1371/journal.pone.0112399 Text en © 2014 Correia et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Correia, Catarina
Oliveira, Guiomar
Vicente, Astrid M.
Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise
title Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise
title_full Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise
title_fullStr Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise
title_full_unstemmed Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise
title_short Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise
title_sort protein interaction networks reveal novel autism risk genes within gwas statistical noise
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4237351/
https://www.ncbi.nlm.nih.gov/pubmed/25409314
http://dx.doi.org/10.1371/journal.pone.0112399
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