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Genome-wide association, genetic network and pathway analyses identify novel human genes for susceptibility to common infectious diseases

Background: Due to variety of factors, we are still faced with major limitations in understanding the infectious disease pathogenesis and therefore lack proper tools to effectively treat some of them. Host genetics profile is often suggested to be responsible for observed variations in disease occurrence and treatment outcomes. Therefore, the aim of this study was to use hypothesis-free approach, genome-wide association study with network analysis, in order to provide an insight into the role of host genetics in the complex infectious disease pathogenesis, based on the resource of isolated human populations from the 10, 001 Dalmatians biobank. Material/methods: We included 1, 029 participants from the island of Vis and 969 from the island of Korčula. A total of 11 infection-related phenotypic outcomes were extracted from medical history and used as binary outcome variables. First, a genome-wide association study (GWAS) was performed for each phenotype. Using genotypic correlations between each phenotype-associated SNPs with p-value < 0.01 in GWAS, we constructed weighted genetic networks and further examined association of identified SNP modules with all infection- related phenotypes. Significantly associated modules for each infection-related phenotype were investigated by functional enrichment analyses. Moreover, since for each phenotype- associated GWAS results there was a significant correlation with several other phenotypes, we searched for an overlap between SNPs of those additionally associated phenotypes in order to find common core genes and pathways important for correlated infection-related phenotypes. Also, meta-analyses of GWAS results were performed. Results: Despite rather small number of cases, we found that two genes reached a genome-wide significance threshold after meta-analyses – inositol polyphosphate multikinase gene (IPMK) as a significant predictor for tuberculosis (rs7899961 ; P=9.15x10-8, OR=1.04, 95% CI [1.02- 1.05]) and tetratricopeptide repeat domain 39B gene (TTC39B) for hepatitis (rs1323597 ; P=4.72x10-8, OR=1.06, 95% CI [1.04-1.08]). Network analyses revealed enrichment in genes involved in the immune response as expected (e.g. MHC class II for overlap between hepatitis, gastrointestinal and viral infections ; interferon type I for overlap between pneumonia, respiratory and bacterial infections). Moreover, we identified several significantly associated pathways and genes outside of the immune system that have plausible functions in various infectious diseases, as shown in several in vitro and animal studies (e.g. serine C- palmitoyltransferase, plexin/semaphorin, keratin, olfactory receptor). Conclusions: These results suggest that the existing biobanks can provide an interesting target for infectious diseases investigations. Also, as infectious diseases represent complex phenotypes, with usually common low-risk genetic variants in the host, network analyses showed to be a favourable post-GWAS approach to further identify genes below rigid genome-wide significance threshold. Despite biological roles that seem to correspond to the imposed infectious diseases pathogenesis, much better understanding of the role of the genes and pathways identified in this study is needed before translation of this knowledge towards clinical use.

host susceptibility, GWAS, genetic network

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