21The aggregation of Election Health Records (EHR) and personalized genetics leads to powerful 22 discoveries relevant to population health. Here we perform genome-wide association studies (GWAS) 23 and accompanying phenome-wide association studies (PheWAS) to validate phenotype-genotype 24 associations of BMI, and to a greater extent, severe Class 2 obesity, using comprehensive diagnostic 25 and clinical data from the EHR database of our cohort. Three GWASs of 500,000 variants on the 26 Illumina platform of 6,645 Healthy Nevada participants identified several published and novel variants 27 that affect BMI and obesity. Each GWAS was followed with two independent PheWASs to examine 28 associations between extensive phenotypes (incidence of diagnoses, condition, or disease), significant 29 SNPs, BMI, and incidence of extreme obesity. The first GWAS excludes DM2-diagnosed individuals 30 and focuses on associations with BMI exclusively. The second GWAS examines the interplay between 31 Type 2 Diabetes (DM2) and BMI. The intersection of significant variants of these two studies is 32 surprising. The third complementary case-control GWAS, with cases defined as extremely obese (Class 33 2 or 3 obesity), identifies strong associations with extreme obesity, including established variants in the 34 FTO and NEGR1 genes, as well as loci not yet linked to obesity. The PheWASs validate published 35 associations between BMI and extreme obesity and incidence of specific diagnoses and conditions, yet 36 also highlight novel links. This study emphasizes the importance of our extensive longitudinal EHR 37 database to validate known associations and identify putative novel links with BMI and obesity. 38 39 2014; Qureshi et al. 2017; Huđek et al. 2018; Gonzalez-Herrera et al. 2018), none, to the best of our 63 knowledge, have included comprehensive GWASs on the quantitative BMI metric and on extreme 64 obesity case-control simultaneously, as well as investigated phenotypic associations with BMI, obesity, 65 and significant loci identified by the GWAS. 66 67 Our study begins with the Healthy Nevada Project (HNP), a project centered around a Northern Nevada 68 cohort formed in 2016 and 2017 by Renown Health and the Desert Research Institute in Reno, NV to 69 4investigate factors that may contribute to health outcomes in Northern Nevada. Its first phase provided 70 10,000 individuals in Northern Nevada with genotyping using the 23andMe platform at no cost. 71Renown Health is the only tertiary care health system in the area, and 75% of these 10,000 individuals 72 are cross-referenced in its extensive electronic health records (EHR) database. The Renown EHR 73 database contains 86,610 BMI measurements for these 10,000 individuals over twelve years, along 74 with comprehensive disease diagnoses, (e.g. diabetes or eating disorders) and other general conditions 75 such as pregnancy, allowing for precise individual phenotypic classifications and thereby leading to 76 more robust and meaningful phenotype-genotype associations. 77
78The focus ...