engleski

Genetic network as post-GWAS analysis approach for correlated complex phenotypes: example on infectious diseases

Background: Due to the rigorous genome-wide significance threshold in GWA studies, causative common low-risk polymorphisms for complex phenotypes may be missed. We propose building a genetic network as post-GWAS approach to provide an insight into the role of host genetics in infectious disease pathogenesis from the 10, 001 Dalmatians biobank. Materials and methods: We included 1, 998 participants representing isolated island populations and 1, 012 participants from mainland population. GWAS with meta-analyses was performed for 11 infection-related phenotypes. Genotypic correlations between each phenotype-associated SNPs from GWAS were used for network construction and enrichment analysis. We also searched for the overlap between correlated infectious phenotypes to find shared core genes and pathways. Results: Three genes reached a genome-wide significance threshold – HAPLN1 for meningitis in all cohorts, while IPMK for tuberculosis and TTC39B for hepatitis in island cohorts. Genetic network additionally revealed genes DCN and CORIN to be marginally significant for tuberculosis, DMD for hepatitis and GALNT18 for systemic infections. Pathway analysis also revealed enrichment in genes outside of the immune system that may have plausible functions in various infection-related outcomes. Conclusions: Network analysis can be a favourable post-GWAS approach, especially to elucidate shared genes among correlated complex phenotypes. Some variants in infectious diseases may be wide-spread, while others could be a result of genetic drift and isolation and possibly even local co-adaptation. Funding: Medical Research Council UK, Croatian Science Foundation grants 8875 and 8445, FP7 project PREPARE (602525). We gratefully acknowledge contribution from the Institute for Anthropological Research in Zagreb, Croatia.

host susceptibility, GWAS, genetic network, infections

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