Quantifying the phenome‐wide disease burden of obesity using electronic health records and genomics. Issue 12 (13th November 2022) - Robinson, Jamie R.; Carroll, Robert J.; Bastarache, Lisa; Chen, Qingxia; Pirruccello, James; Mou, Zongyang; Wei, Wei‐Qi; Connolly, John; Mentch, Frank; Crane, Paul K.; Hebbring, Scott J.; Crosslin, David R.; et al.
Abstract: Objective: High BMI is associated with many comorbidities and mortality. This study aimed to elucidate the overall clinical risk of obesity using a genome‐ and phenome‐wide approach. Methods: This study performed a phenome‐wide association study of BMI using a clinical cohort of 736, 726 adults. This was followed by genetic association studies using two separate cohorts: one consisting of 65, 174 adults in the Electronic Medical Records and Genomics (eMERGE) Network and another with 405, 432 participants in the UK Biobank. Results: Class 3 obesity was associated with 433 phenotypes, representing 59.3% of all billing codes in individuals with severe obesity. A genome‐wide polygenic risk score for BMI, accounting for 7.5% of variance in BMI, was associated with 296 clinical diseases, including strong associations with type 2 diabetes, sleep apnea, hypertension, and chronic liver disease. In all three cohorts, 199 phenotypes were associated with class 3 obesity and polygenic risk for obesity, including novel associations such as increased risk of renal failure, venous insufficiency, and gastroesophageal reflux. Conclusions: This combined genomic and phenomic systematic approach demonstrated that obesity has a strong genetic predisposition and is associated with a considerable burden of disease across all disease classes.