The association of sleep health with epigenetic aging in early adolescence: exploratory insights from the Health Outcomes and Measures of the Environment study
Source: PubMed Central Open Access, NCBI / U.S. National Library of Medicine
Abstract Study Objectives Sleep during adolescence may influence biological aging, yet few studies have examined this association using objective sleep measures. We examined the associations between accelerometry-based sleep characteristics and epigenetic age (EA), epigenetic age acceleration (EAA), and the pace of biological aging. sec3 Study Methods For this preliminary analysis, we used data from the Health Outcomes and Measures of the Environment Study (Cincinnati, OH). At age 12 years (2016–2019), we used accelerometers to assess total sleep time, sleep efficiency, the number of awakenings, and sleep fragmentation. Using DNA methylation data at the same age, we estimated EA and EAA using the skinbloodHorvath, Hannum, and Wu clocks, and the pace of biological aging using DunedinPACE. We used multivariable linear regression to estimate covariate-adjusted associations between sleep and epigenetic aging. We also evaluated sex modification by including product interaction terms and examined sex-stratified models. sec4a Results Among 138 adolescents (59 per cent female; mean age 12.29 ± 0.64 years), general trends suggested that poorer sleep quality was associated with higher EA and EAA. However, all effect estimates were imprecise, and confidence intervals (CIs) included the null. Notably, we found that sex modified these relationships: higher sleep fragmentation was associated with elevated EAA among males (Hannum= 0.885, 95% CI: 0.132, 1.638; interaction= .005), but not fem
Abstract
Abstract Study Objectives Sleep during adolescence may influence biological aging, yet few studies have examined this association using objective sleep measures. We examined the associations between accelerometry-based sleep characteristics and epigenetic age (EA), epigenetic age acceleration (EAA), and the pace of biological aging. sec3 Study Methods For this preliminary analysis, we used data from the Health Outcomes and Measures of the Environment Study (Cincinnati, OH). At age 12 years (2016–2019), we used accelerometers to assess total sleep time, sleep efficiency, the number of awakenings, and sleep fragmentation. Using DNA methylation data at the same age, we estimated EA and EAA using the skinbloodHorvath, Hannum, and Wu clocks, and the pace of biological aging using DunedinPACE. We used multivariable linear regression to estimate covariate-adjusted associations between sleep and epigenetic aging. We also evaluated sex modification by including product interaction terms and examined sex-stratified models. sec4a Results Among 138 adolescents (59 per cent female; mean age 12.29 ± 0.64 years), general trends suggested that poorer sleep quality was associated with higher EA and EAA. However, all effect estimates were imprecise, and confidence intervals (CIs) included the null. Notably, we found that sex modified these relationships: higher sleep fragmentation was associated with elevated EAA among males (Hannum= 0.885, 95% CI: 0.132, 1.638; interaction= .005), but not females (= –0.325, 95% CI: –0.866, 0.217). These associations were consistent across first-generation clocks. sec5a Conclusions Overall, we did not find consistent evidence of associations between sleep characteristics and epigenetic aging in this preliminary analysis. However, sex-stratified analyses suggested that poorer sleep quality may be associated with greater EAA among males. sec6a Graphical Abstract Graphical Abstract For graphical abstract description, please refer to the textual abstract. http://www.w3.org/1999/xlink float portrait zpag090ga1.webp float ga1 portrait graphical