Phenome-wide Analysis of Diseases in Relation to Objectively Measured Sleep Traits and Comparison with Subjective Sleep Traits in 88,461 Adults.

Health data science Pub Date : 2025-06-03 eCollection Date: 2025-01-01 DOI:10.34133/hds.0161
Yimeng Wang, Qiaorui Wen, Siwen Luo, Lijuan Tang, Siyan Zhan, Jia Cao, Shengfeng Wang, Qing Chen
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Abstract

Background: Sleep traits have been suggested to correlate with various diseases, but most evidence is based on subjective sleep measurement. We investigated the associations of accelerometer-derived objective sleep traits with diseases throughout physiological systems to ascertain whether the disease spectrum related to objective sleep traits differs from that related to subjective sleep traits. Methods: In 88,461 UK Biobank (UKB) adults wearing accelerometers, multiple dimensions of sleep were objectively derived: (a) nocturnal sleep duration and onset timing, (b) sleep rhythm (relative amplitude and interdaily stability), and (c) sleep fragmentation (sleep efficiency and waking numbers). Associations with International Classification of Diseases, 10th Revision-decoded diseases during follow-up were estimated using the Cox model, and the results were compared with those of a published literature search of subjectively measured sleep traits and diseases. National Health and Nutrition Examination Survey (NHANES) data were used to validate the newly identified associations unreported by previous studies. For the meta-analysis-reported associations (with subjective sleep traits) that were negative (with objective sleep traits) in our study, reanalysis was done in UKB with subjective sleep traits, stratified by objective measurements. Results: During the average 6.8-year follow-up, 172 diseases were associated with sleep traits. Among them, 42 showed at least doubled disease risk, including age-related physical debility (lowest versus highest quartile of relative amplitude, hazard ratio [HR] = 3.36, 95% confidence interval [CI]: 2.25, 5.02), gangrene (lowest versus highest quartile of interdaily stability, HR = 2.61, 95% CI: 1.41, 4.83), and fibrosis and cirrhosis of the liver (sleep onset timing ≥0030 versus 2300 to 2330, HR = 2.57, 95% CI: 1.42, 4.67). A total of 92 diseases had >20% burden attributable to sleep, such as Parkinson's disease (37.05%, 95% CI: 21.02%, 49.83%), type 2 diabetes (36.12%, 95% CI: 29.00%, 42.52%), and acute kidney failure (21.85%, 95% CI: 13.47%, 29.42%). Notably, 83 (48.3%) disease associations were sleep rhythm specific, distinct from existing subjective-measure literature that focused on sleep duration. Reanalysis in UKB showed a contamination of objectively short sleepers in self-report long sleepers, which induced false-positive associations in subjective meta-analyses, including for ischemic heart disease and depressive disorder. Newly identified associations of sleep rhythm with 4 diseases including chronic obstructive pulmonary disease and diabetes were successfully replicated in NHANES. A mediation analysis showed that inflammatory factors including leukocytes, eosinophils, and C-reactive protein contributed significantly to all these newly identified sleep-disease associations. Conclusions: Objective sleep traits showed a disease spectrum similar to but not identical to that of subjective sleep traits. Objective measurement can be a useful complement to sleep-disease studies as it may help overcome false-positive associations caused by misclassification bias of some subjective measurement such as sleep duration. Comprehensive control of multiple sleep traits may be important for health as substantial disease burden was attributed to different sleep traits.

88,461名成人客观测量睡眠特征相关疾病的全现象分析及与主观睡眠特征的比较
背景:睡眠特征被认为与多种疾病相关,但大多数证据都是基于主观的睡眠测量。我们研究了加速计衍生的客观睡眠特征与整个生理系统疾病的关联,以确定与客观睡眠特征相关的疾病谱系是否与与主观睡眠特征相关的疾病谱系不同。方法:在英国生物银行(UKB)的88,461名佩戴加速度计的成年人中,客观地得出了睡眠的多个维度:(a)夜间睡眠持续时间和发作时间,(b)睡眠节奏(相对振幅和每日间稳定性),(c)睡眠碎片化(睡眠效率和清醒次数)。使用Cox模型估计随访期间与《国际疾病分类》第10版解码疾病的关联,并将结果与已发表的主观测量睡眠特征和疾病的文献检索结果进行比较。国家健康和营养检查调查(NHANES)的数据被用来验证新发现的未被以前的研究报告的关联。对于在我们的研究中报告的(与主观睡眠特征)负相关(与客观睡眠特征)的荟萃分析,在UKB中进行了主观睡眠特征的重新分析,并通过客观测量进行分层。结果:在平均6.8年的随访中,172种疾病与睡眠特征有关。其中,42例表现出至少两倍的疾病风险,包括与年龄相关的身体衰弱(相对振幅最低与最高四分位数,风险比[HR] = 3.36, 95%可信区间[CI]: 2.25, 5.02),坏疽(每日间稳定性最低与最高四分位数,HR = 2.61, 95% CI: 1.41, 4.83),以及肝纤维化和肝硬化(睡眠开始时间≥0030 vs 2300 - 2330, HR = 2.57, 95% CI: 1.42, 4.67)。共有92种疾病可归因于睡眠的负担为bb0 - 20%,如帕金森病(37.05%,95% CI: 21.02%, 49.83%)、2型糖尿病(36.12%,95% CI: 29.00%, 42.52%)和急性肾衰竭(21.85%,95% CI: 13.47%, 29.42%)。值得注意的是,83例(48.3%)疾病关联是睡眠节律特异性的,与现有的专注于睡眠持续时间的主观测量文献不同。对UKB的再分析显示,客观上短睡眠者与自我报告的长睡眠者之间存在污染,这在主观荟萃分析中引起了假阳性关联,包括缺血性心脏病和抑郁症。新发现的睡眠节律与4种疾病的关联,包括慢性阻塞性肺疾病和糖尿病,在NHANES中成功复制。一项中介分析显示,包括白细胞、嗜酸性粒细胞和c反应蛋白在内的炎症因子在所有这些新发现的睡眠疾病关联中起着重要作用。结论:客观睡眠特征表现出与主观睡眠特征相似但不完全相同的疾病谱。客观测量可以作为睡眠疾病研究的有益补充,因为它可以帮助克服一些主观测量(如睡眠时间)的错误分类偏差所引起的假阳性关联。综合控制多种睡眠特征可能对健康很重要,因为大量的疾病负担归因于不同的睡眠特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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