A Comprehensive Genome-Wide and Phenome-Wide Examination of BMI and Obesity in a Northern Nevadan Cohort

Abstract

The aggregation of Electronic Health Records (EHR) and personalized genetics leads to powerful discoveries relevant to population health. Here we perform genome-wide association studies (GWAS) and accompanying phenome-wide association studies (PheWAS) to validate phenotype-genotype associations of BMI, and to a greater extent, severe Class 2 obesity, using comprehensive diagnostic and clinical data from the EHR database of our cohort. Three GWASs of 500,000 variants on the Illumina platform of 6,645 Healthy Nevada participants identified several published and novel variants that affect BMI and obesity. Each GWAS was followed with two independent PheWASs to examine associations between extensive phenotypes (incidence of diagnoses, condition, or disease), significant SNPs, BMI, and incidence of extreme obesity. The first GWAS examines associations with BMI in a cohort with no type 2 diabetics, focusing exclusively on BMI. The second GWAS examines associations with BMI in a cohort that includes type 2 diabetics. In the second GWAS, type 2 diabetes is a comorbidity, and thus becomes a covariate in the statistical model. The intersection of significant variants of these two studies is surprising. The third GWAS is a case vs. control study, with cases defined as extremely obese (Class 2 or 3 obesity), and controls defined as participants with BMI between 18.5 and 25. This last GWAS identifies strong associations with extreme obesity, including established variants in the FTO and NEGR1 genes, as well as loci not yet linked to obesity. The PheWASs validate published associations between BMI and extreme obesity and incidence of specific diagnoses and conditions, yet also highlight novel links. This study emphasizes the importance of our extensive longitudinal EHR database to validate known associations and identify putative novel links with BMI and obesity.

Exploring a Region on Chromosome 8p23.1 Displaying Positive Selection Signals in Brazilian Admixed Populations: Additional Insights Into Predisposition to Obesity and Related Disorders

“…(Secolin et al, 2019), we believe that the decrease in genetic variability present in exome data may render FCS less suitable for this type of analysis. Increasing fat and glucose storage could increase body fat, glucose storage, and obesity-related diseases in individuals who eat a fat and glucose-rich diet today; findings consistent with previous association studies (Pulit et al, 2019;Rask-Andersen et al, 2019;Schlauch et al, 2020). Indeed, we identified 89 variants with the potential to impact gene function that were found exclusively in the admixed Brazilian sample.…”

“…In Table 2 , we present the list of 17 genes that have been linked to diet patterns in large association studies and are located in the candidate region on ch 8p23.1. Seven of these large studies included Hispanic, Native-American, and Caribbean populations ( Comuzzie et al, 2012 ; Divers et al, 2017 ; Pulit et al, 2019 ; Rask-Andersen et al, 2019 ; Niarchou et al, 2020 ; Schlauch et al, 2020 ; Vujkovic et al, 2020 ), and three contained association signals in the ERI1 gene ( Pulit et al, 2019 ; Rask-Andersen et al, 2019 ; Schlauch et al, 2020 ), which is located within the region and was determined to possess the greatest degree of positive selection in admixed Brazilians in our previous work ( Secolin et al, 2019 ).…”

Digital Health for Supporting Precision Medicine in Pediatric Endocrine Disorders: Opportunities for Improved Patient Care

“…Precision medicine offers an opportunity for individuals to participate in population research through access to and use of their own genetic data and personal health characteristics, combined with websites such as the 23andme.com app (12)(13)(14). Bioinformatic data on growth disorders can take advantage of large cohorts and registries with genetic, biochemical and clinical information, and can use machine-learning to provide predictions of future risks (15)(16)(17).…”

The genetic case for cardiorespiratory fitness as a clinical vital sign and the routine prescription of physical activity in healthcare

“…Additional TWAS significant functional candidates with a high probability of the GWAS variant driving expression included SRRT (serrate, RNA receptor molecule) in the lung and heart (atrial appendage) tissue, RP11-62H7.2 in the heart (atrial appendage), FAM86B3P (family with sequence similarity 86 member B3) in the skeletal muscle, FAM85B (family with sequence similarity 85 member B) in the lung and coronary artery, and AF131215.2 in the artery (coronary and tibial) (PP4 range=0.74–0.92). SRRT and FAM86B3P are notably associated with heart rate response to exercise and recovery [ 59 ], electrocardiography (RR interval) [ 68 ], diabetes mellitus [ 66 ], and obesity [ 69 ].…”