Accelerometry-derived features of physical activity, sleep and circadian rhythm relate to non-motor symptoms in individuals with isolated REM sleep behavior disorder

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.