Sleep patterns and DNA methylation age acceleration in middle-aged and older Chinese adults - Tingyue Diao; Kang Liu; Lue Zhou; Qiuhong Wang; Junrui Lyu; Ziwei Zhu; Fuchao Chen; Wengang Qin; Handong Yang; Chaolong Wang; Xiaomin Zhang; Tangchun Wu (Clinical Epigenetics)
Abstract Background Sleep is a biological necessity and fundamental to health. However, the associations of sleep patterns (integrating sleep determinants) with DNA methylation age acceleration (DNAm AA) remain unknown. We aimed to investigate the associations of sleep patterns with DNAm AA. Methods This cross-sectional and prospective cohort study used data from the Dongfeng-Tongji cohort collected from 2013 to December 31, 2018. Sleep patterns were reflected by sleep scores (range 0–4, with higher scores indicating healthier sleep patterns) characterized by bedtime, sleep duration, sleep quality, and midday napping. DNAm AA was estimated by PhenoAge acceleration (PhenoAgeAccel), GrimAge acceleration (GrimAgeAccel), DunedinPACE, and DNAm mortality risk score (DNAm MS). Linear regression models were used to estimate β and 95% confidence intervals (CIs) for the cross-sectional associations between sleep patterns and DNAm AA. Mediation models were applied to assess the mediating role of DNAm AA in the associations between sleep patterns and all-cause mortality in a prospective cohort. Results Among 3566 participants (mean age 65.5 years), 426 participants died during a mean 5.4-year follow-up. A higher sleep score was associated with lower DNAm AA in a dose–response manner. Each 1-point increase in sleep score was associated with significantly lower PhenoAgeAccel (β = − 0.208; 95% CI − 0.369 to − 0.047), GrimAgeAccel (β = − 0.107; 95% CI − 0.207 to − 0.007), DunedinPACE (β = − 0.008; 95% CI − 0.012 to − 0.004), and DNAm MS (β = − 0.019; 95% CI − 0.030 to − 0.008). Chronological age modified the associations between higher sleep scores and lower PhenoAgeAccel (p for interaction = 0.031) and DunedinPACE (p for interaction = 0.027), with stronger associations observed in older adults. Moreover, a slower DunedinPACE mediated 6.2% (95% CI 0.8% to 11.5%) of the association between a higher sleep score and a lower all-cause mortality risk. Conclusion In this cohort study, individuals with a higher sleep score had a slower DNAm AA, particularly in older adults. A slower DunedinPACE partially explained the association between higher sleep scores and lower all-cause mortality risk. These findings suggest that adopting healthy sleep patterns may promote healthy aging and further benefit premature mortality prevention, highlighting the value of sleep patterns as a potential tool for clinical management in aging.