Quantifying the phenome-wide disease burden of obesity using electronic health records and genomics

Obesity (Silver Spring). 2022 Dec;30(12):2477-2488. doi: 10.1002/oby.23561. Epub 2022 Nov 13.

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.

MeSH terms

  • Cost of Illness
  • Diabetes Mellitus, Type 2* / epidemiology
  • Diabetes Mellitus, Type 2* / genetics
  • Electronic Health Records
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study
  • Genomics
  • Humans
  • Obesity / epidemiology
  • Obesity / genetics
  • Phenomics*
  • Phenotype
  • Polymorphism, Single Nucleotide

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