Network-assisted analysis of GWAS data identifies a functionally-relevant gene module for childhood-onset asthma

The number of genetic factors associated with asthma remains limited. To identify new genes with an undetected individual effect but collectively influencing asthma risk, we conducted a network-assisted analysis that integrates outcomes of genome-wide association studies (GWAS) and protein-protein i...

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Veröffentlicht in:Scientific reports 2017-04, Vol.7 (1), p.938-10, Article 938
Hauptverfasser: Liu, Y., Brossard, M., Sarnowski, C., Vaysse, A., Moffatt, M., Margaritte-Jeannin, P., Llinares-López, F., Dizier, M. H., Lathrop, M., Cookson, W., Bouzigon, E., Demenais, F.
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Sprache:eng
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Zusammenfassung:The number of genetic factors associated with asthma remains limited. To identify new genes with an undetected individual effect but collectively influencing asthma risk, we conducted a network-assisted analysis that integrates outcomes of genome-wide association studies (GWAS) and protein-protein interaction networks. We used two GWAS datasets, each consisting of the results of a meta-analysis of nine childhood-onset asthma GWASs (5,924 and 6,043 subjects, respectively). We developed a novel method to compute gene-level P -values (fastCGP), and proposed a parallel dense-module search and cross-selection strategy to identify an asthma-associated gene module. We identified a module of 91 genes with a significant joint effect on childhood-onset asthma ( P  
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-017-01058-y