Integrating Multi-Ancestry Polygenic Risk Scores and Wearable Data to Detect Depression and Gene-Environment Interactions in Youth

Background: Depression (DEP) has an estimated heritability of ~37%. Polygenic risk scores (PRS), which aggregate common genetic variant effects, account for up to 8.4% variance in case versus control status. Understanding the relationships between sleep, activity, and DEP symptoms, and whether these relationships differ depending on genetic predisposition is crucial for early identification, particularly during adolescence when DEP rates tend to increase.

Method: 2,768 adolescents (African [AFR], American Admixed [AMR], and European [EUR] ancestry) from the Adolescent Brain Cognitive Development study were examined. DEP-PRS was calculated using PRS-CSx. Average and variance sleep and activity measures were derived from Fitbit wearable data. Mixed effects models examined main and interaction effects of DEPPRS and each Fitbit measure with DEP severity.

Results: DEP-PRS, mean resting heart rate, mean sedentary minutes, and sleep minutes variance were positively associated with DEP severity; mean intense active minutes, total steps, and sleep minutes were negatively associated. DEP-PRS showed interactions with sleep minutes variance, mean total steps, and mean intense active minutes, with stronger associations between these variables in individuals at higher genetic risk. In individuals at higher genetic risk with different ancestries, the association between mean sleep minutes and DEP severity was positive for AFR, negative for AMR, and non-significant for EUR.

Conclusion: The relationship between sleep, activity, and DEP severity appears to depend on genetic predisposition Further research with optimized PRS, research-grade wearables, and longitudinal design is needed.