Quantitative sleep electroencephalogram and cognitive performance in Parkinson’s disease with and without rapid eye movement sleep behavior disorder

• Authors: Adeel A. Memon, University of Alabama at Birmingham; Corina Catiul, University of Alabama at Birmingham; Zachary Irwin, University of Alabama at Birmingham; Jennifer Pilkington, University of Alabama at Birmingham; Raima A. Memon, University of Alabama at Birmingham; Allen Joop, University of Alabama at Birmingham; Kimberly H. Wood, University of Alabama at Birmingham; Gary Cutter, University of Alabama at Birmingham; Svjetlana Miocinovic, Emory University; Amy W. Amara, University of Alabama at Birmingham
• Journal Title: Frontiers in Neurology
• Volume: Volume 14
• Publisher: Frontiers | 2023-09-07, Pages 1223974-None
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.3389/fneur.2023.1223974
• Subjects: Psychology, Cognitive; Health Sciences, Public Health
• Keywords: Parkinson's disease; quantitative sleep neurophysiology; non-rapid eye movement sleep; scalp slow wave; sleep spindles; phase-amplitude coupling; REM sleep behavior disorder; cognition

Abstract

Introduction Parkinson’s disease (PD) patients with REM sleep behavior disorder (RBD) are at greater risk for cognitive decline and RBD has been associated with alterations in sleep-related EEG oscillations. This study evaluates differences in sleep quantitative EEG (qEEG) and cognition in PD participants with (PD-RBD) and without RBD (PD-no-RBD). Methods In this cross-sectional study, polysomnography (PSG)-derived qEEG and a comprehensive level II neuropsychological assessment were compared between PD-RBD (n = 21) and PD-no-RBD (n = 31). Following artifact rejection, qEEG analysis was performed in the frontal and central leads. Measures included Scalp-slow wave (SW) density, spindle density, morphological properties of SW and sleep spindles, SW-spindle phase-amplitude coupling, and spectral power analysis in NREM and REM. The neurocognitive battery had at least two tests per domain, covering five cognitive domains as recommended by the Movement Disorders Society Task Force for PD-MCI diagnosis. Differences in qEEG features and cognitive performance were compared between the two groups. Stepwise linear regression was performed to evaluate predictors of cognitive performance. Multiple comparisons were corrected using the Benjamini-Hochberg method. Results Spindle density and SW-spindle co-occurrence percent were lower in participants with PD-RBD compared to PD-no-RBD. The PD-RBD group also demonstrated higher theta spectral power during REM. Sleep spindles and years of education, but not RBD, were predictors of cognitive performance. Conclusion PD participants with RBD have alterations in sleep-related qEEG compared to PD participants without RBD. Although PD-RBD participants had worse cognitive performance compared to PD-no-RBD, regression models suggest that lower sleep spindle density, rather than presence of RBD, predicts worse comprehensive cognitive score. Future studies should include longitudinal evaluation to determine whether sleep-related qEEG alterations are associated with more rapid cognitive decline in PD-RBD.