Sleep · 2024
Electroencephalographic spectro-spatial covariance patterns related to phenoconversion in isolated rapid eye movement sleep behavior disorder and their longitudinal trajectories in α-synucleinopathies.
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Park Kyoungeun, Shin Jung Hwan, Byun Jung-Ick, Jeong El, Kim Han-Joon, Jung Ki-Young
Аннотация
STUDY OBJECTIVES: This study aimed to identify electroencephalographic (EEG) spectro-spatial covariance patterns associated with phenoconversion in isolated rapid eye movement sleep behavior disorder (iRBD) patients and explore their longitudinal trajectories within α-synucleinopathies.
METHODS: We assessed 47 participants, including 35 patients with iRBD and 12 healthy controls (HC), through baseline eye-closed resting EEGs. Patients with iRBD underwent follow-up EEG assessments and 18 patients with iRBD converted (12 to Parkinson's disease (PD), 6 to dementia with Lewy bodies [DLB]) during follow-up. We derived EEG spectro-spatial covariance patterns for PD-RBD and DLB-RBD from converters and HC. Correlations with motor and cognitive function, baseline distinctions among iRBD converters and nonconverters, and longitudinal trajectories were examined.
RESULTS: At baseline, converters exhibited higher PD-RBD and DLB-RBD beta2 pattern scores compared to nonconverters (each area under curve [AUC] = 0.7751). The delta and alpha spatial patterns effectively distinguished both PD and DLB converters from HC, with the alpha pattern showing high discriminative power (AUC = 0.9097 for PD-RBD, 0.9306 for DLB-RBD). Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III scores correlated positively with PD-RBD and DLB-RBD delta patterns (Spearman's rho = 0.688, p = 0.00014; rho = 0.539, p = 0.0055, respectively), with age and sex as cofactors. Distinct trajectories emerged during follow-up among PD converters, DLB converters, and iRBD nonconverters.
CONCLUSIONS: Unique EEG spectro-spatial patterns specific to PD-RBD and DLB-RBD offer potential as predictive markers for phenoconversion to α-synucleinopathies in iRBD.
METHODS: We assessed 47 participants, including 35 patients with iRBD and 12 healthy controls (HC), through baseline eye-closed resting EEGs. Patients with iRBD underwent follow-up EEG assessments and 18 patients with iRBD converted (12 to Parkinson's disease (PD), 6 to dementia with Lewy bodies [DLB]) during follow-up. We derived EEG spectro-spatial covariance patterns for PD-RBD and DLB-RBD from converters and HC. Correlations with motor and cognitive function, baseline distinctions among iRBD converters and nonconverters, and longitudinal trajectories were examined.
RESULTS: At baseline, converters exhibited higher PD-RBD and DLB-RBD beta2 pattern scores compared to nonconverters (each area under curve [AUC] = 0.7751). The delta and alpha spatial patterns effectively distinguished both PD and DLB converters from HC, with the alpha pattern showing high discriminative power (AUC = 0.9097 for PD-RBD, 0.9306 for DLB-RBD). Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part III scores correlated positively with PD-RBD and DLB-RBD delta patterns (Spearman's rho = 0.688, p = 0.00014; rho = 0.539, p = 0.0055, respectively), with age and sex as cofactors. Distinct trajectories emerged during follow-up among PD converters, DLB converters, and iRBD nonconverters.
CONCLUSIONS: Unique EEG spectro-spatial patterns specific to PD-RBD and DLB-RBD offer potential as predictive markers for phenoconversion to α-synucleinopathies in iRBD.