{"title":"Divergent biological pathways linking short and long sleep durations to mental and physical health","authors":"Yuzhu Li, Weikang Gong, Barbara J. Sahakian, Shuyi Huang, Wei Zhang, Yujie Zhao, Liang Ma, Sharon Naismith, Jintai Yu, Tianye Jia, Wei Cheng, Jianfeng Feng","doi":"10.1038/s44220-025-00395-6","DOIUrl":null,"url":null,"abstract":"Short and long sleep durations are associated with multiple physical, psychiatric and neurodegenerative diseases, yet their potentially shared and distinct biological mechanisms remain unclear. Here, using data from UK Biobank participants aged 38–73 years, we have characterized the in-depth genetic architecture of short (≤7 h) and long (≥7 h) sleep groups, along with their associations with behaviors, neuroimaging and blood biomarkers. The two sleep groups exhibited independent genetic architectures and distinct immunometabolic and proteomic profiles. Notably, long sleep showed more significant associations with cardiovascular-related biomarkers (for example, cholesterol), brain structures (for example, hippocampus) and plasma proteins (for example, GDF15), whereas short sleep demonstrated greater genetic overlap with psychiatric conditions, particularly depression. Mendelian randomization further supported this dissociation by showing that long sleep duration is probably a consequence of multiple brain disorders and cardiovascular diseases, whereas short sleep duration has a potential causal effect on various brain and physical illnesses. Our findings advance our understanding of the relationship between sleep and health conditions by revealing distinct biological origins and genetic mechanisms underlying short and long sleep duration. Using data from the UK Biobank, the authors investigate the differences between short and long sleep duration regarding genetics, biomarkers and phenotypic implications.","PeriodicalId":74247,"journal":{"name":"Nature mental health","volume":"3 4","pages":"429-443"},"PeriodicalIF":8.7000,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44220-025-00395-6.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature mental health","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s44220-025-00395-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Short and long sleep durations are associated with multiple physical, psychiatric and neurodegenerative diseases, yet their potentially shared and distinct biological mechanisms remain unclear. Here, using data from UK Biobank participants aged 38–73 years, we have characterized the in-depth genetic architecture of short (≤7 h) and long (≥7 h) sleep groups, along with their associations with behaviors, neuroimaging and blood biomarkers. The two sleep groups exhibited independent genetic architectures and distinct immunometabolic and proteomic profiles. Notably, long sleep showed more significant associations with cardiovascular-related biomarkers (for example, cholesterol), brain structures (for example, hippocampus) and plasma proteins (for example, GDF15), whereas short sleep demonstrated greater genetic overlap with psychiatric conditions, particularly depression. Mendelian randomization further supported this dissociation by showing that long sleep duration is probably a consequence of multiple brain disorders and cardiovascular diseases, whereas short sleep duration has a potential causal effect on various brain and physical illnesses. Our findings advance our understanding of the relationship between sleep and health conditions by revealing distinct biological origins and genetic mechanisms underlying short and long sleep duration. Using data from the UK Biobank, the authors investigate the differences between short and long sleep duration regarding genetics, biomarkers and phenotypic implications.