Covariance patterns between sleep health domains and distributed intrinsic functional connectivity

Yulin Wang, Sarah Genon, Debo Dong, Feng Zhou, Chenyu Li, Dahua Yu, Kai Yuan, Qinghua He, Jiang Qiu, Tingyong Feng, Hong Chen and Xu Lei ()
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Yulin Wang: Southwest University
Sarah Genon: Brain & Behaviour (INM-7), Research Centre Jülich
Debo Dong: Southwest University
Feng Zhou: Southwest University
Chenyu Li: Chongqing Traditional Chinese Medicine Hospital
Dahua Yu: Inner Mongolia University of Science and Technology
Kai Yuan: Xidian University
Qinghua He: Southwest University
Jiang Qiu: Southwest University
Tingyong Feng: Southwest University
Hong Chen: Southwest University
Xu Lei: Southwest University

Nature Communications, 2023, vol. 14, issue 1, 1-16

Abstract: Abstract Sleep health is both conceptually and operationally a composite concept containing multiple domains of sleep. In line with this, high dependence and interaction across different domains of sleep health encourage a transition in sleep health research from categorical to dimensional approaches that integrate neuroscience and sleep health. Here, we seek to identify the covariance patterns between multiple sleep health domains and distributed intrinsic functional connectivity by applying a multivariate approach (partial least squares). This multivariate analysis reveals a composite sleep health dimension co-varying with connectivity patterns involving the attentional and thalamic networks and which appear relevant at the neuromolecular level. These findings are further replicated and generalized to several unseen independent datasets. Critically, the identified sleep-health related connectome shows diagnostic potential for insomnia disorder. These results together delineate a potential brain connectome biomarker for sleep health with high potential for clinical translation.

Date: 2023
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DOI: 10.1038/s41467-023-42945-5

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