Modeling the genomic architecture of adiposity and anthropometrics across the lifespan

Abstract

Obesity-related conditions are among the leading causes of preventable death and are increasing in prevalence worldwide. Body size and composition are complex traits that are challenging to characterize due to environmental and genetic influences, longitudinal variation, heterogeneity between sexes, and differing health risks based on adipose distribution. We constructed a 4-factor genomic structural equation model using 18 measures and unveiled shared and distinct genetic architectures underlying birth size, abdominal size, adipose distribution, and adiposity. Multivariate genome-wide associations revealed the adiposity factor was enriched specifically in neural tissues and pathways, while adipose distribution was enriched across widespread physiological systems. In addition, polygenic scores for the adiposity factor predicted many adverse health outcomes, while body size and composition predicted a more limited subset. Finally, we characterized the factors genetic correlations with obesity-related traits and examined the druggable genome through constructing a bipartite drug-gene network to identify viable therapeutic targets.