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@ARTICLE{Ophey:1041316,
author = {Ophey, Anja and Vinod, Vaishali and Röttgen, Sinah and
Scharfenberg, Daniel and Fink, Gereon Rudolf and Sommerauer,
Michael and Kalbe, Elke and Maetzler, Walter and Hansen,
Clint},
title = {{A}ccelerometry-derived features of physical activity,
sleep and circadian rhythm relate to non-motor symptoms in
individuals with isolated {REM} sleep behavior disorder},
journal = {Journal of neurology},
volume = {272},
number = {3},
issn = {0367-004X},
address = {[Darmstadt]},
publisher = {Steinkopff},
reportid = {FZJ-2025-02215},
pages = {201},
year = {2025},
note = {Funding Open Access funding enabled and organized by
Projekt DEAL},
abstract = {Accelerometry enables passive, continuous, high-frequency
monitoring under free-living conditions. For individuals
with isolated REM sleep behavior disorder (iRBD), a
potential prodromal phase of Parkinson's disease (PD) and
dementia with Lewy bodies, accelerometry has been primarily
applied to aid diagnosis and to assess phenoconversion risk.
To extend this knowledge, we cross-sectionally combined
clinical assessments focusing on non-motor symptoms with
accelerometry-derived features of physical activity (PA),
sleep, and circadian rhythm of N = 68 individuals with iRBD
(age: 69.48 ± 6.01 years, self-reported RBD symptom
duration: 9.46 ± 6.21 years, 85 $\%$ male).
Accelerometry-assessed PA was associated with more stable
circadian rhythms. Additionally, higher PA and more stable
circadian rhythms were linked to a lower burden of overall
non-motor symptoms, depressive symptoms, and fatigue with
small to moderate effect sizes. Furthermore, including
accelerometry-derived features improved the prediction of
individual clinical scores, particularly for cognitive
performance. Our findings contribute to the growing body of
evidence highlighting the complex interplay between PA,
sleep, circadian rhythm, and non-motor symptoms in
α-synucleinopathies. Future research should focus on
longitudinal studies to monitor changes in clinical outcomes
and digital biomarkers over time to enhance our
understanding of symptom progression and corresponding
lifestyle changes in prodromal and manifest
α-synucleinopathies.Keywords: Actigraphy; Digital
biomarkers; Digital health technology; Prodromal
Parkinson’s disease; Wearables.},
cin = {INM-3},
ddc = {610},
cid = {I:(DE-Juel1)INM-3-20090406},
pnm = {5252 - Brain Dysfunction and Plasticity (POF4-525)},
pid = {G:(DE-HGF)POF4-5252},
typ = {PUB:(DE-HGF)16},
pubmed = {39934559},
UT = {WOS:001419949200007},
doi = {10.1007/s00415-025-12931-6},
url = {https://juser.fz-juelich.de/record/1041316},
}