Polygenic risk score identifies associations between sleep duration and diseases determined from an electronic medical record biobank.
STUDY OBJECTIVES: We aimed to detect cross-sectional phenotype and polygenic risk score (PRS) associations between sleep duration and prevalent diseases using the Partners Biobank, a hospital-based cohort study linking electronic medical records (EMR) with genetic information.
METHODS: Disease prevalence was determined from EMR, and sleep duration was self-reported. A PRS for sleep duration was derived using 78 previously associated SNPs from genome-wide association studies (GWAS) for self-reported sleep duration. We tested for associations between (1) self-reported sleep duration and 22 prevalent diseases (n = 30 251), (2) the PRS and self-reported sleep duration (n = 6903), and (3) the PRS and the 22 prevalent diseases (n = 16 033). For observed PRS-disease associations, we tested causality using two-sample Mendelian randomization (MR).
RESULTS: In the age-, sex-, and race-adjusted model, U-shaped associations were observed for sleep duration and asthma, depression, hypertension, insomnia, obesity, obstructive sleep apnea, and type 2 diabetes, where both short and long sleepers had higher odds for these diseases than normal sleepers (p
CONCLUSIONS: By validating the PRS for sleep duration and identifying cross-phenotype associations, we lay the groundwork for future investigations on the intersection between sleep, genetics, clinical measures, and diseases using large EMR datasets.
|Year of Publication||
2019 Mar 01
|PubMed Central ID||
R01 DK105072 / DK / NIDDK NIH HHS / United States
R01 DK107859 / DK / NIDDK NIH HHS / United States
R35 HL135818 / HL / NHLBI NIH HHS / United States
R01 HL113338 / HL / NHLBI NIH HHS / United States