Genetically and environmentally predicted obesity in relation to cardiovascular disease: a nationwide cohort study

Background Evidence indicates that the adverse health effects of obesity differ between genetically and environ-mentally influenced obesity. We examined differences in the association between obesity and cardiovascular disease (CVD) between individuals with a genetically predicted low, medium, or high body mass index (BMI).Methods We used cohort data from Swedish twins born before 1959 who had BMI measured between the ages of 40-64 years (midlife) or at the age of 65 years or later (late-life), or both, and prospective CVD information from nationwide register linkage through 2016. A polygenic score for BMI (PGSBMI) was used to define genetically pre-dicted BMI. Individuals missing BMI or covariate data, or diagnosed with CVD at first BMI measure, were excluded, leaving an analysis sample of 17,988 individuals. We applied Cox proportional hazard models to examine the asso-ciation between BMI category and incident CVD, stratified by the PGSBMI. Co-twin control models were applied to adjust for genetic influences not captured by the PGSBMI.Findings Between 1984 and 2010, the 17,988 participants were enrolled in sub-studies of the Swedish Twin Registry. Midlife obesity was associated with a higher risk of CVD across all PGSBMI categories, but the association was stronger with genetically predicted lower BMI (hazard ratio from 1.55 to 2.08 for those with high and low PGSBMI, respectively). Within monozygotic twin pairs, the association did not differ by genetically predicted BMI, indicating genetic confounding not captured by the PGSBMI. Results were similar when obesity was measured in late-life, but suffered from low power.Interpretation Obesity was associated with CVD regardless of PGSBMI category, but obesity influenced by genetic predisposition (genetically predicted high BMI) was less harmful than obesity influenced by environmental factors (obesity despite genetically predicted low BMI). However, additional genetic factors, not captured by the PGSBMI, still influence the associations.Funding The Strategic Research Program in Epidemiology at Karolinska Institutet; Loo and Hans Osterman's Foundation; Foundation for Geriatric Diseases at Karolinska Institutet; the Swedish Research Council for Health, Working Life and Welfare; the Swedish Research Council; and the National Institutes of Health. Copyright (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).