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Updated: Feb 26, 2026

Human Circadian Phenotyping and Diurnal Performance Testing in the Real World
Published on: April 7, 2020
A Developmentally Informed Study of Sleep and Circadian Polygenic Scores in Adolescence
Katie J S Lewis1,2, Joanna Martin1,2, Jon Heron3
1Wolfson Centre for Young People's Mental Health, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom.
Importance:
Genome-wide association studies (GWAS) of sleep and circadian phenotypes have identified common genetic variants associated with these phenotypes in adults, but the relevance of these findings for younger age groups is unclear. It is important to determine whether genetic variants identified in these studies also index sleep phenotypes in adolescence, a time where sleep problems often emerge and have high heritability.
Objective:
To examine whether polygenic scores, calculated using results from adult sleep/circadian GWAS, index corresponding sleep phenotypes in adolescents.
Design, Setting, And Participants:
Data were from 3903 adolescents (1820 males, 2083 females) with genetic and sleep questionnaire data available at 15 years of age who were participants in the Avon Longitudinal Study of Parents and Children (ALSPAC), an ongoing, longitudinal, population-based birth cohort study. Data were analyzed for the current study from August 19, 2024, to March 28, 2025.
Exposures:
Polygenic scores were derived using summary statistics from large adult GWAS of sleep duration, insomnia, daytime sleepiness, napping, and chronotype.
Main Outcomes And Measures:
The following self-reported sleep phenotypes were assessed via questionnaire: sleep duration, sleep onset latency, chronotype, insomnia symptoms, and napping. Associations between polygenic scores with corresponding phenotypes in adolescence were analyzed using logistic or linear regression. Secondary analyses examined whether associations differed by sex or school nights vs weekends.
Results:
Polygenic scores were associated with corresponding sleep phenotypes in adolescence for sleep duration (B = 0.04 [95% CI, 0.02-0.07] hours; P = .002), insomnia symptoms (odds ratio [OR], 1.16 [95% CI, 1.09-1.25]; P = 1.18 × 10-5), napping (OR, 1.37 [95% CI, 1.26-1.49]; P = 8.11 × 10-13), chronotype (B = -0.13 [95% CI, -0.16 to -0.10] hours; P = 6.91 × 10-16), and daytime sleepiness (OR, 1.08 [95% CI, 1.01-1.15]; P = .02). Associations did not substantially differ by sex or by school nights/weekends, except for napping, the effect estimate for weekends was smaller than on school days.
Conclusions And Relevance:
Results of this study suggest overlap in the genetic etiology of sleep and circadian phenotypes in adolescence and adulthood. This has importance for studies using genomic designs for causal inference about sleep and understanding of the extent to which genetic influences vary across the lifespan. Future research, including larger GWAS across developmental periods, is required to further understand genetic influences on sleep across the lifespan, as well as environmental influences on adolescent sleep disturbances.
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