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<p>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 (<i>N</i> = 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 <i>MEIS1</i> and rare coding variants in <i>TTC1</i> 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.</p>

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Health risks and genetic architecture of objectively measured multidimensional sleep health

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月31日

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  • Shengkui Zhang,
  • Manrui Zhang,
  • Yuxin Yuan,
  • Zilin Li,
  • Xihao Li,
  • Xiaoyu Li

摘要

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.