PhenoExplorer: An Interactive Web-based Platform for Exploring (Epi)Genome-Wide Associations Using a Swiss...

The recent advent of high-throughput sequencing technologies has allowed exploring the contribution of thousands of genomic, epigenomic, transcriptomic, or proteomic variants to complex phenotypic traits. Here, we sought to conduct large-scale (Epi)Genome-Wide Association Studies (GWAS/EWAS) to investigate the associations between genomic (Single Nucleotide Polymorphism; SNP) and epigenomic (Cytosine-Phospho-Guanine; CpG) markers, with multiple phenotypic traits in a population-based context. We used data from SKIPOGH, a family- and population-based cohort conducted in the cities of Lausanne, Geneva, and Bern (N=1100). We used 7,577,572 SNPs, 420,444 CpGs, and 825 phenotypes, including anthropometric, clinical, blood, urine, metabolite, and metal measures. GWAS analyses assessed the associations between SNPs and metabolites and metals (N=279), using regression models adjusted for age, sex, recruitment center, and familial structure, whereas EWAS analyses explored the relations between CpGs and 825 phenotypes, additionally adjusting for the seasonality of blood sampling and technical nuisance. Following the implementation of GWAS and EWAS analyses, we developed a web-based platform, PhenoExplorer, aimed at providing an open access to the obtained results. Of the 279 phenotypes included in GWAS, 103 displayed significant associations with 2804 SNPs (2091 unique SNPs) at Bonferroni threshold, whereas 109 of the 825 phenotypes included in EWAS analyses were associated with 4893 CpGs (2578 unique CpGs). All of the obtained GWAS and EWAS results were eventually made available using the in-house built web-based PhenoExplorer platform, with the purpose of providing an open-access to the tested associations. In conclusion, we provide a comprehensive outline of GWAS and EWAS associations performed in a Swiss population-based study. Further, we set up a web-based PhenoExplorer platform with the purpose of contributing to the overall understanding of the role of molecular variants in regulating complex phenotypes.