Zhang Shengkui, Zhang Manrui, Yuan Yuxin, Li Zilin, Li Xihao, Li Xiaoyu
Department of Sociology, Tsinghua University, Beijing, China.
School of Mathematics and Statistics and KLAS, Northeast Normal University, Changchun, China.
Nat Commun. 2025 Jul 31;16(1):7026. doi: 10.1038/s41467-025-62338-0.
A multidimensional sleep health framework improves screening and treatment efficacy by simultaneously addressing multiple sleep domains. However, limited studies have used objective measures to evaluate the co-occurrence of diverse unhealthy sleep characteristics and their pleiotropic health effects. To represent real-world sleep patterns, we introduce the Unfavorable Sleep Profile (USP), an integrated multidimensional sleep health metric developed using accelerometer data in the UK Biobank (N = 85,233; aged 43-79 years). USP captures five domains: sleep timing, efficiency, duration, rhythmicity, and regularity. Phenome-wide association study found that USP was significantly associated with 76 out of 526 incident health outcomes over 7.9 years of follow-up. We identified several upstream environmental risk factors associated with USP, including low socioeconomic status. Whole-genome sequence analyses identified common variants in MEIS1 and rare coding variants in TTC1 associated with USP. We validated the USP framework in an independent cohort, the Multi-Ethnic Study of Atherosclerosis. Our findings underscore the importance of multidimensional sleep health assessment in predicting and potentially mitigating a wide array of health disorders and advance genetic insights into sleep health.
一个多维睡眠健康框架通过同时解决多个睡眠领域的问题来提高筛查和治疗效果。然而，使用客观测量方法来评估多种不健康睡眠特征的共现及其多效性健康影响的研究有限。为了呈现现实世界中的睡眠模式，我们引入了不良睡眠概况（USP），这是一种利用英国生物银行（N = 85,233；年龄在43 - 79岁之间）的加速度计数据开发的综合多维睡眠健康指标。USP涵盖五个领域：睡眠时间、效率、时长、节律性和规律性。全表型关联研究发现，在7.9年的随访中，USP与526种新发健康结局中的76种显著相关。我们确定了几个与USP相关的上游环境风险因素，包括社会经济地位低下。全基因组序列分析确定了与USP相关的MEIS1中的常见变异和TTC1中的罕见编码变异。我们在一个独立队列——动脉粥样硬化多族裔研究中验证了USP框架。我们的研究结果强调了多维睡眠健康评估在预测和潜在缓解多种健康障碍方面的重要性，并推进了对睡眠健康的遗传学认识。
