0800 Independent Contributions of Aperiodic and Periodic EEG Features as Prognostic Biomarkers for Phenoconversion to α-Synucleinopathies in iRBD

Abstract Introduction Isolated REM sleep behavior disorder (iRBD) is considered a prodromal stage of α-synucleinopathies such as Parkinson’s disease (PD) and dementia with Lewy bodies (DLB). Identifying early biomarkers to predict phenoconversion is essential. Previous electroencephalographic (EEG) studies have mainly relied on conventional power spectrum analysis where periodic and aperiodic components are not separated. This study aimed to assess whether independently distinguished aperiodic and periodic components can differentiate iRBD converters (iRBD-CV) from non-converters (iRBD-NC). Methods We analyzed baseline eye-closed resting EEG from 134 participants (108 iRBD-NC, 26 iRBD-CV: 18 PD-CV, and 8 DLB-CV). Original spectra were computed for the delta (1–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–50 Hz). Aperiodic components (offset and slope: 2–50 Hz; low-frequency slope: 2–30 Hz; high-frequency slope: 30–50 Hz) were estimated and subtracted to obtain periodic spectra. Correlation analyses assessed associations between EEG features and clinical variables. Results DLB-CV was significantly older than the other groups (66.47±6.32 vs. 67.50±6.42 vs. 75.62±7.39 years, p=0.008) and had fewer years of education (12.92±4.08 vs. 11.89±3.88 vs. 8.25±4.17 years, p=0.013). MMSE and MoCA scores were lower in DLB-CV. PD-CV showed higher theta and alpha in the original spectrum. After removing the aperiodic component, only DLB-CV showed increased periodic theta, whereas significance did not remain in PD-CV. In DLB-CV, the posterior regions showed an increased offset, steeper low-frequency slope, and a reduction in periodic dominant occipital frequency (DOF). Spearman correlation analysis, performed within iRBD-CV, revealed that periodic theta was correlated with MMSE (r=-0.421, p=0.032). Offset correlated with MMSE (r=-0.534, p=0.005) and UPDRS-III (r=0.605, p=0.010). Periodic DOF and low-frequency slope were associated with both MMSE (r=0.455, p=0.019; r=-0.697, p < 0.001) and MoCA (r=0.400, p=0.043; r=-0.609, p < 0.001). Conclusion This study demonstrated that both aperiodic and periodic components of iRBD may serve as independent biomarkers for predicting phenoconversion to α-synucleinopathies. EEG slowing was more clearly captured within the periodic spectrum. The low-frequency slope of aperiodic component may serve as a biomarker reflecting cognitive function, whereas the offset appears to reflect motor function. Support (if any)