| Title: |
Hyperarousal features in the sleep architecture of individuals with and without insomnia |
| Authors: |
Di Marco, Tobias; Scammell, Thomas E; Sadeghi, Kolia; Datta, Alexandre N; Little, David; Tjiptarto, Nurkurniati; Djonlagic, Ina; Olivieri, Antonio; Zammit, Gary; Krystal, Andrew; Pathmanathan, Jay; Donoghue, Jacob; Hubbard, Jeffrey; Dauvilliers, Yves |
| Source: |
Journal of Sleep Research, vol 34, iss 1 |
| Publisher Information: |
eScholarship, University of California |
| Publication Year: |
2025 |
| Collection: |
University of California: eScholarship |
| Subject Terms: |
32 Biomedical and Clinical Sciences (for-2020); 3201 Cardiovascular Medicine and Haematology (for-2020); Sleep Research (rcdc); Basic Behavioral and Social Science (rcdc); Clinical Research (rcdc); Clinical Trials and Supportive Activities (rcdc); Neurosciences (rcdc); Behavioral and Social Science (rcdc); Humans (mesh); Sleep Initiation and Maintenance Disorders (mesh); Polysomnography (mesh); Male (mesh); Female (mesh); Electroencephalography (mesh); Adult (mesh); Arousal (mesh); Retrospective Studies (mesh); Middle Aged (mesh); Sleep Stages (mesh); Wakefulness (mesh); Sleep (mesh); Machine Learning (mesh); hyperarousal; insomnia; sleep; sleep architecture |
| Description: |
Sleep architecture encodes relevant information on the structure of sleep and has been used to assess hyperarousal in insomnia. This study investigated whether polysomnography-derived sleep architecture displays signs of hyperarousal in individuals with insomnia compared with individuals without insomnia. Data from Phase 3 clinical trials, private clinics and a cohort study were analysed. A comprehensive set of sleep architecture features previously associated with hyperarousal were retrospectively analysed focusing on sleep-wake transition probabilities, electroencephalographic spectra and sleep spindles, and enriched with a novel machine learning algorithm called the Wake Electroencephalographic Similarity Index. This analysis included 1710 individuals with insomnia and 1455 individuals without insomnia. Results indicate that individuals with insomnia had a higher likelihood of waking from all sleep stages, and showed increased relative alpha during Wake and N1 sleep and increased theta power during Wake when compared with individuals without insomnia. Relative delta power was decreased and Wake Electroencephalographic Similarity Index scores were elevated across all sleep stages except N3, suggesting more wake-like activity during these stages in individuals with insomnia. Additionally, sleep spindle density was decreased, and spindle dispersion was increased in individuals with insomnia. These findings suggest that insomnia is characterized by a dysfunction in sleep quality with a continuous hyperarousal, evidenced by changes in sleep-wake architecture. |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
unknown |
| Relation: |
qt74p7n0d2; https://escholarship.org/uc/item/74p7n0d2; https://escholarship.org/content/qt74p7n0d2/qt74p7n0d2.pdf |
| DOI: |
10.1111/jsr.14256 |
| Availability: |
https://escholarship.org/uc/item/74p7n0d2; https://escholarship.org/content/qt74p7n0d2/qt74p7n0d2.pdf; https://doi.org/10.1111/jsr.14256 |
| Rights: |
CC-BY |
| Accession Number: |
edsbas.DF254E12 |
| Database: |
BASE |