Associations of polygenic scores for sleep traits with cognitive function
TL;DR
A higher PGS for long sleep was associated with lower GCF at baseline and higher risk of poor GCF at baseline, and a higher PGS for BMI-adjusted OSA was associated with higher risk of poor GCF at baseline.
Abstract
Polygenic scores (PGSs) for sleep traits are potentially more stable, and less subject to confounding than measured sleep traits. Leveraging data from five observational cohorts, we aim to assess the associations between PGS for six common sleep traits, and global cognitive function (GCF) among middle-aged to older adults. In each cohort, GCF was defined as the first principal component (PC) of multiple cognitive measures and was projected from baseline (first selected visit) to measures from a subsequent follow up visit. Poor GCF was defined as having GCF < 1 standard deviation (SD) of the age-adjusted GCF distribution median. We estimated sleep PGS associations with baseline GCF, poor baseline GCF, GCF change between baseline and follow-up, and incident poor GCF at follow-up. Models adjusted for age, sex, study center, race/ethnicity, genetic PCs, and education. Results were meta-analyzed via fixed effects meta-analysis. Estimates are reported per 1 SD increase in PGS. A higher PGS for long sleep was associated with lower GCF at baseline (estimate = -0.02 SD, 95% CI: -0.03 to 0.00, p = 0.01) and higher risk of poor GCF at baseline (odds ratio, OR = 1.04, 95% CI: 1.00 to 1.09, p = 0.06). In addition, a higher PGS for BMI-adjusted OSA was associated with higher risk of poor GCF at baseline (OR = 1.11, 95% CI: 1.00 to 1.22, p = 0.04). Genetic predisposition to long sleep and OSA is associated with poorer cognitive function in a meta analysis of more than 20,000 middle-aged and older adults.