Dataset Information

U-shaped association between sleep duration and biological aging: Evidence from the UK Biobank study.

ABSTRACT: Previous research on sleep and aging largely has failed to illustrate the optimal dose-response curve of this relationship. We aimed to analyze the associations between sleep duration and measures of predicted age. In total, 241,713 participants from the UK Biobank were included. Habitual sleep duration was collected from the baseline questionnaire. Four indicators, homeostatic dysregulation (HD), phenoAge (PA), Klemera-Doubal method (KDM), and allostatic load (AL), were chosen to assess predicted age. Multivariate linear regression models were utilized. The association of sleep duration and predicted age followed a U-shape (All p for nonlinear <0.05). Compared with individuals who sleep for 7 h/day, the multivariable-adjusted beta of ≤5 and ≥9 h/day were 0.05 (95% CI 0.03, 0.07) and 0.03 (95% CI 0.02, 0.05) for HD, 0.08 (95% CI 0.01, 0.14) and 0.36 (95% CI 0.31, 0.41) for PA, and 0.21 (95% CI 0.12, 0.30) and 0.30 (95% CI 0.23, 0.37) for KDM. Significant independent and joint effects of sleep and cystatin C (CysC) and gamma glutamyltransferase (GGT) on predicted age metrics were future found. Similar results were observed when conducting stratification analyses. Short and long sleep duration were associated with accelerated predicted age metrics mediated by CysC and GGT.

SUBMITTER: Wang X

PROVIDER: S-EPMC11258478 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature

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U-shaped association between sleep duration and biological aging: Evidence from the UK Biobank study.

Wang Xuanyang X Yan Xuemin X Li Mengdi M Cheng Licheng L Qi Xiang X Zhang Jia J Pan Sijia S Xu Xiaoqing X Wei Wei W Li Ying Y

Aging cell 20240331 7

Previous research on sleep and aging largely has failed to illustrate the optimal dose-response curve of this relationship. We aimed to analyze the associations between sleep duration and measures of predicted age. In total, 241,713 participants from the UK Biobank were included. Habitual sleep duration was collected from the baseline questionnaire. Four indicators, homeostatic dysregulation (HD), phenoAge (PA), Klemera-Doubal method (KDM), and allostatic load (AL), were chosen to assess predict ...[more]

PMID: 38556842

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Project description:BackgroundPsychological and trauma-related factors are associated with many diseases and mortality. However, a comprehensive assessment of the association between psycho-trauma exposures and aging acceleration is currently lacking.MethodsUsing data from 332,359 UK Biobank participants, we calculated biological aging acceleration, indexed by the presence of leukocyte telomere length (LTL) deviation (i.e., the difference between genetically determined and observed LTL > 0). The acceleration of facial aging (i.e., looking older than the chronological age) was assessed using a self-report question. Then, we estimated the associations of each psycho-trauma factor with biological and facial aging acceleration, using logistic regression models adjusted for multiple important covariates. Furthermore, restricted to 99,180 participants with complete psychological and trauma-related data, we identified clusters of individuals with distinct psycho-trauma patterns using the latent class analysis method and assessed their associations with aging acceleration using similar models.ResultsWe observed most of the studied psycho-trauma factors were associated with biological and facial aging acceleration. Compared to the "Absence of trauma and psychopathology" cluster, the "adverse childhood experiences (ACEs) with psychopathology" cluster showed strong associations with those aging measurements (odds ratio [OR] = 1.13 [1.05 - 1.23] for biological and 1.52 [1.18 - 1.95] for facial aging acceleration), while no such association was observed for the "ACEs without psychopathology" cluster (1.04 [0.99 - 1.09] and 1.02 [0.84 - 1.24].ConclusionsOur study demonstrated significant associations of psycho-trauma factors with both biological and facial aging acceleration. The differential aging consequences observed among ACEs exposed individuals with and without psychopathology prompt interventions aimed to improve individuals' psychological resilience to prevent aging acceleration.

Project description:BackgroundAlzheimer's disease (AD) is the most frequently occurring type of dementia. Concurrently, inadequate sleep has been recognized as a public health epidemic. Notably, genetic and environmental factors are now considered contributors to AD progression.ObjectiveTo assess the association between sleep duration, genetic susceptibility, and AD.Methods and resultsBased on 483,507 participants from the UK Biobank (UKB) with an average follow-up of 11.3 years, there was a non-linear relationship between AD incidence and sleep duration (P for non-linear < 0.001) by restricted cubic splines (RCS). Sleep duration was categorized into short sleep duration (< 6 h/night), normal sleep duration (6-9 h/night), and long sleep duration (> 9 h/night). No statistically significant interaction was identified between sleep duration and the AD-GRS (Alzheimer's disease genetic risk score, P for interaction = 0.45) using Cox proportional risk model. Compared with the participants who had a low AD-GRS and normal sleep duration, there was associated with a higher risk of AD in participants with a low AD-GRS and long sleep duration (HR = 3.4806; 95% CI 2.0011-6.054, p < 0.001), participants with an intermediate AD-GRS and long sleep duration (HR = 2.0485; 95% CI 1.3491-3.1105, p < 0.001), participants with a high AD-GRS and normal sleep duration (HR = 1.9272; 95% CI 1.5361-2.4176, p < 0.001), and participants with a high AD-GRS and long sleep duration (HR = 5.4548; 95% CI 3.1367-9.4863, p < 0.001).In addition, there was no causal association between AD and sleep duration using Two Sample Mendelian randomization (MR).ConclusionIn the UKB population, though there was no causal association between AD and sleep duration analyzed using Two Sample MR, long sleep duration (> 9 h/night) was significantly associated with a higher risk of AD, regardless of high, intermediate or low AD-GRS. Prolonged sleep duration may be one of the clinical predictors of a higher risk of AD.

Project description:BackgroundEmerging evidence supports a link between circadian disruption as measured by higher night-to-night variation in sleep duration and increased risk of cardiovascular disease (CVD). It remains unclear whether this association varies by CVD types or may be modified by average sleep duration and genetic risk for CVD.MethodsOur prospective analysis included 86,219 UK Biobank participants who were free from CVD when completing 7 days of accelerometer measurement in 2013-2016. Sleep irregularity was evaluated by the standard deviation (SD) of accelerometer-measured sleep duration over 7 days. Incident major CVD events, defined as fatal or nonfatal myocardial infarction (MI) and stroke, were identified through linkage to Hospital Episode Statistics data until May 31, 2022. Multivariable-adjusted Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% CIs for associations of sleep duration SD with risk for major CVD events overall and for MI and stroke separately.ResultsWe documented 2,310 incident cases of major CVD events (MI: 1,183, stroke: 1,175) over 636,258 person-years of follow-up. After adjusting for sociodemographic factors and family history of CVD, the HR (95% CI) associated with a 1-hour increase in sleep duration SD was 1.19 (1.10, 1.27) for CVD (p-trend<0.0001), 1.23 (1.11, 1.35) for MI (p-trend<0.0001), and 1.17 (1.05, 1.29) for stroke (p-trend=0.003). Additional adjustment for lifestyle factors, co-morbidities and sleep-related factors modestly attenuated these associations. Higher sleep irregularity was associated with higher CVD risk irrespective of genetic risk (p-interaction=0.43), but this association was stronger among individuals with longer average sleep duration >8 hours (p-interaction=0.006).ConclusionsHigher night-to-night variation in accelerometer-measured sleep duration was associated with consistently higher risks for major CVD events. The association did not seem to be modified by genetic risk for CVD and was more pronounced in long sleepers.

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U-shaped association between sleep duration and biological aging: Evidence from the UK Biobank study.

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U-shaped association between sleep duration and biological aging: Evidence from the UK Biobank study.

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