Modeling Sleep Genetics Uncovers Distinct Disease Risks in Night vs. Day Workers

Abstract Shift work has adverse health consequences, but the genetic basis of this vulnerability remains underexplored. Using Genomic structural equation modelling, we derived six latent sleep factors reflecting core RU-SATED domains from large-scale GWAS data. Polygenic scores for sleep regularity and daytime alertness showed strong genetic correlations with metabolic and behavioral traits and were causally linked to depression, well-being, and insulin regulation in Mendelian randomization. A phenome-wide association study in UK Biobank comparing night shift workers with controls (N = 46,211) revealed associations with type 2 diabetes, hypertension, and chronic obstructive pulmonary disease, and other outcomes, which were independently replicated in the All of Us cohort (N = 131,729). Finally, genetic predisposition for reduced daytime alertness nearly doubled the odds of T2D in night shift workers compared to day workers, with genetic predisposition to irregular sleep showing similar effects on T2D and COPD. These risks were further amplified in smokers and obese individuals.