Long-Range Temporal Correlations in Electroencephalography for Parkinson's Disease Progression

Background: Patients with Parkinson's disease (PD) present progressive deterioration in both motor and non-motor manifestations. However, the absence of clinical biomarkers for disease progression hinders clinicians from tailoring treatment strategies effectively. Objectives: To identify electroencephalography (EEG) biomarker that can track disease progression in PD. Methods: A total of 116 patients with PD were initially enrolled, whereas 63 completed 2-year follow-up evaluation. Fifty-eight age- and sex-matched healthy individuals were recruited as the control group. All participants underwent EEG and clinical assessments. Long-range temporal correlations (LRTC) of EEG data were analyzed using the detrended fluctuation analysis. Results: Patients with PD exhibited higher LRTC in left parietal θ oscillations (P = 0.0175) and lower LRTC in centro-parietal γ oscillations (P = 0.0258) compared to controls. LRTC in parietal γ oscillations inversely correlated with changes in Unified Parkinson's Disease Rating Scale (UPDRS) part III scores over 2 years (Spearman ρ = −0.34, P = 0.0082). Increased LRTC in left parietal θ oscillations were associated with rapid motor progression (P = 0.0107), defined as an annual increase in UPDRS part III score ≥3. In cognitive assessments, LRTC in parieto-occipital α oscillations exhibited a positive correlation with changes in Mini-Mental State Examination and Montreal Cognitive Assessment scores over 2 years (Spearman ρ = 0.27–0.38, P = 0.0037–0.0452). Conclusions: LRTC patterns in EEG potentially predict rapid progression of both motor and non-motor manifestations in PD patients, enhancing clinical assessment and understanding of the disease.