Network-assisted investigation of combined causal signals from genome-wide association studies in schizophrenia.
PLoS Comput Biol
; 8(7): e1002587, 2012.
Article
em En
| MEDLINE
| ID: mdl-22792057
ABSTRACT
With the recent success of genome-wide association studies (GWAS), a wealth of association data has been accomplished for more than 200 complex diseases/traits, proposing a strong demand for data integration and interpretation. A combinatory analysis of multiple GWAS datasets, or an integrative analysis of GWAS data and other high-throughput data, has been particularly promising. In this study, we proposed an integrative analysis framework of multiple GWAS datasets by overlaying association signals onto the protein-protein interaction network, and demonstrated it using schizophrenia datasets. Building on a dense module search algorithm, we first searched for significantly enriched subnetworks for schizophrenia in each single GWAS dataset and then implemented a discovery-evaluation strategy to identify module genes with consistent association signals. We validated the module genes in an independent dataset, and also examined them through meta-analysis of the related SNPs using multiple GWAS datasets. As a result, we identified 205 module genes with a joint effect significantly associated with schizophrenia; these module genes included a number of well-studied candidate genes such as DISC1, GNA12, GNA13, GNAI1, GPR17, and GRIN2B. Further functional analysis suggested these genes are involved in neuronal related processes. Additionally, meta-analysis found that 18 SNPs in 9 module genes had P(meta)<1 × 10â»4, including the gene HLA-DQA1 located in the MHC region on chromosome 6, which was reported in previous studies using the largest cohort of schizophrenia patients to date. These results demonstrated our bi-directional network-based strategy is efficient for identifying disease-associated genes with modest signals in GWAS datasets. This approach can be applied to any other complex diseases/traits where multiple GWAS datasets are available.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Esquizofrenia
/
Estudo de Associação Genômica Ampla
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
/
Systematic_reviews
Limite:
Humans
Idioma:
En
Ano de publicação:
2012
Tipo de documento:
Article