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iGWAS: Integrative Genome-Wide Association Studies of Genetic and Genomic Data for Disease Susceptibility Using Mediation Analysis.
Huang, Yen-Tsung; Liang, Liming; Moffatt, Miriam F; Cookson, William O C M; Lin, Xihong.
Afiliação
  • Huang YT; Departments of Epidemiology and Biostatistics, Brown University, Providence, Rhode Island, United States of America.
  • Liang L; Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America.
  • Moffatt MF; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
  • Cookson WO; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
  • Lin X; Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, Massachusetts, United States of America.
Genet Epidemiol ; 39(5): 347-56, 2015 Jul.
Article em En | MEDLINE | ID: mdl-25997986
ABSTRACT
Genome-wide association studies (GWAS) have been a standard practice in identifying single nucleotide polymorphisms (SNPs) for disease susceptibility. We propose a new approach, termed integrative GWAS (iGWAS) that exploits the information of gene expressions to investigate the mechanisms of the association of SNPs with a disease phenotype, and to incorporate the family-based design for genetic association studies. Specifically, the relations among SNPs, gene expression, and disease are modeled within the mediation analysis framework, which allows us to disentangle the genetic effect on a disease phenotype into two parts an effect mediated through a gene expression (mediation effect, ME) and an effect through other biological mechanisms or environment-mediated mechanisms (alternative effect, AE). We develop omnibus tests for the ME and AE that are robust to underlying true disease models. Numerical studies show that the iGWAS approach is able to facilitate discovering genetic association mechanisms, and outperforms the SNP-only method for testing genetic associations. We conduct a family-based iGWAS of childhood asthma that integrates genetic and genomic data. The iGWAS approach identifies six novel susceptibility genes (MANEA, MRPL53, LYCAT, ST8SIA4, NDFIP1, and PTCH1) using the omnibus test with false discovery rate less than 1%, whereas no gene using SNP-only analyses survives with the same cut-off. The iGWAS analyses further characterize that genetic effects of these genes are mostly mediated through their gene expressions. In summary, the iGWAS approach provides a new analytic framework to investigate the mechanism of genetic etiology, and identifies novel susceptibility genes of childhood asthma that were biologically meaningful.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Asma / Algoritmos / Predisposição Genética para Doença / Polimorfismo de Nucleotídeo Único / Locos de Características Quantitativas / Estudo de Associação Genômica Ampla / Modelos Genéticos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Child / Humans Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Asma / Algoritmos / Predisposição Genética para Doença / Polimorfismo de Nucleotídeo Único / Locos de Características Quantitativas / Estudo de Associação Genômica Ampla / Modelos Genéticos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Child / Humans Idioma: En Ano de publicação: 2015 Tipo de documento: Article