Abstract

The neuronal ceroid lipofuscinoses (NCLs) are a group of recessively inherited neurodegenerative diseases characterizsed by lysosomal storage of fluorescent materials. CLN3 disease, or juvenile Batten disease, is the most common NCL that is caused by mutations in the Ceroid Lipofuscinosis, Neuronal 3 (CLN3) gene. Sleep disturbances are among the most common symptoms associated with CLN3 disease that deteriorate the patients' life quality, yet this is understudied and has not been delineated in animal models of the disease. The current study utilised PiezoSleep, a non-invasive, automated piezoelectric motion sensing system, to classify sleep and wakefulness in a Cln3Δex1–6/Δex1-6 (Cln3KO) mouse model and age- and sex-matched wild-type (WT) controls. The sleep–wake classification by PiezoSleep was found to be about 90% accurate when validated against simultaneous polysomnographic recordings including electroencephalography (EEG) and electromyography (EMG) in a small cohort of WT and Cln3KO mice. Our large cohort PiezoSleep study revealed sleep abnormalities during the light period in male Cln3KO mice compared with WT male mice, and more subtle differences in Cln3KO female mice in the dark period compared with WT female mice. Our characterisation of sleep in the Cln3KO mouse model aligns with sleep abnormalities seen in CLN3 disease patients and serves as a basis to continue examining sleep disturbances commonly reported for CLN3 disease and other NCLs. As the first animal model study capturing sleep disturbances in CLN3 disease, our work will facilitate future studies into the potential mechanism behind sleep disturbances associated with the disease and the potential treatment strategies.

Original languageEnglish
JournalJournal of Sleep Research
DOIs
StateAccepted/In press - 2025

Bibliographical note

Publisher Copyright:
© 2025 European Sleep Research Society.

Keywords

  • neuronal ceroid lipofuscinosis
  • non-invasive sleep scoring
  • piezoelectric

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Behavioral Neuroscience

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