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88461名成年人中与客观测量睡眠特征相关疾病的全表型分析及与主观睡眠特征的比较

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

作者信息

Wang Yimeng, Wen Qiaorui, Luo Siwen, Tang Lijuan, Zhan Siyan, Cao Jia, Wang Shengfeng, Chen Qing

机构信息

Key Lab of Medical Protection for Electromagnetic Radiation, Ministry of Education of China, Institute of Toxicology, College of Preventive Medicine, Third Military Medical University (Army Medical University), Chongqing 400038, China.

Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.

出版信息

Health Data Sci. 2025 Jun 3;5:0161. doi: 10.34133/hds.0161. eCollection 2025.

Abstract

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. 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. 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. 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.

摘要

睡眠特征已被认为与多种疾病相关,但大多数证据基于主观睡眠测量。我们研究了通过加速度计得出的客观睡眠特征与全身生理系统疾病之间的关联,以确定与客观睡眠特征相关的疾病谱是否与主观睡眠特征相关的疾病谱不同。在88461名佩戴加速度计的英国生物银行(UKB)成年人中,客观得出了睡眠的多个维度:(a)夜间睡眠时间和入睡时间,(b)睡眠节律(相对振幅和日间稳定性),以及(c)睡眠碎片化(睡眠效率和觉醒次数)。使用Cox模型估计随访期间与国际疾病分类第10版编码疾病的关联,并将结果与已发表的关于主观测量睡眠特征和疾病的文献搜索结果进行比较。使用美国国家健康与营养检查调查(NHANES)数据验证先前研究未报告的新发现关联。对于我们研究中荟萃分析报告的(与主观睡眠特征相关)为阴性(与客观睡眠特征相关)的关联,在UKB中对主观睡眠特征进行重新分析,并按客观测量分层。在平均6.8年的随访期间,172种疾病与睡眠特征相关。其中,42种疾病的患病风险至少增加了一倍,包括与年龄相关的身体虚弱(相对振幅最低四分位数与最高四分位数相比,风险比[HR]=3.36,95%置信区间[CI]:2.25,5.02)、坏疽(日间稳定性最低四分位数与最高四分位数相比,HR=2.61,95%CI:1.41,4.83)以及肝纤维化和肝硬化(入睡时间≥00:30与23:00至23:30相比,HR=2.57,95%CI:1.42,4.67)。共有92种疾病的负担中有超过20%可归因于睡眠,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种(48.3%)疾病关联是睡眠节律特异性的,不同于现有侧重于睡眠时间的主观测量文献。在UKB中的重新分析显示,自我报告为长睡眠者中存在客观短睡眠者的混杂情况,这在主观荟萃分析中导致了假阳性关联,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(包括慢性阻塞性肺疾病和糖尿病)的关联在NHANES中成功得到复制。中介分析表明,包括白细胞、嗜酸性粒细胞和C反应蛋白在内的炎症因子对所有这些新发现的睡眠 - 疾病关联有显著贡献。客观睡眠特征显示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,因为它可能有助于克服一些主观测量(如睡眠时间)的错误分类偏差导致的假阳性关联。对多种睡眠特征的综合控制可能对健康很重要,因为大量疾病负担归因于不同的睡眠特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2fd/12131323/140f79504472/hds.0161.fig.001.jpg

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