In Parkinson's disease, electroencephalographic abnormalities during wakefulness and non-rapid eye movement sleep (spindles) were found to be predictive biomarkers of dementia. Because rapid eye movement sleep is regulated by the cholinergic system, which shows early degeneration in Parkinson's disease with cognitive impairment, anomalies during this sleep stage might mirror dementia development. In this prospective study, we examined baseline electroencephalographic absolute spectral power across three states of consciousness (non-rapid eye movement sleep, rapid eye movement sleep, and wakefulness) in 68 non-demented patients with Parkinson's disease and 44 healthy controls. All participants underwent baseline polysomnographic recordings and a comprehensive neuropsychological assessment. Power spectral analyses were performed on standard frequency bands. Dominant occipital frequency during wakefulness and ratios of slow-to-fast frequencies during rapid eye movement sleep and wakefulness were also computed. At follow-up (an average 4.5 years after baseline), 18 patients with Parkinson's disease had developed dementia and 50 patients remained dementia-free. In rapid eye movement sleep, patients with Parkinson's disease who later developed dementia showed, at baseline, higher absolute power in delta and theta bands and a higher slowing ratio, especially in temporal, parietal, and occipital regions, compared to patients who remained dementia-free and controls. In non-rapid eye movement sleep, lower baseline sigma power in parietal cortical regions also predicted development of dementia. During wakefulness, patients with Parkinson's disease who later developed dementia showed lower dominant occipital frequency as well as higher delta and slowing ratio compared to patients who remained dementia-free and controls. At baseline, higher slowing ratios in temporo-occipital regions during rapid eye movement sleep were associated with poor performance on visuospatial tests in patients with Parkinson's disease. Using receiver operating characteristic curves, we found that best predictors of dementia in Parkinson's disease were rapid eye movement sleep slowing ratios in posterior regions, wakefulness slowing ratios in temporal areas, and lower dominant occipital frequency. These results suggest that electroencephalographic slowing during sleep is a new promising predictive biomarker for Parkinson's disease dementia, perhaps as a marker of cholinergic denervation.

Background/Aims: Mild cognitive impairment (MCI) is frequent in Parkinson’s disease (PD) and idiopathic REM sleep behavior disorder (iRBD). However, only a few studies have evaluated the validity of brief cognitive measures to detect MCI in PD or iRBD using standard diagnostic criteria for MCI. Our aim was to evaluate the validity of the Mini-Mental State Examination (MMSE) and the Mattis Dementia Rating Scale (DRS-2) to detect MCI in PD and iRBD. Methods: Forty PD patients and 34 iRBD patients were studied. Receiver operating characteristic curves were created for both tests to assess their effectiveness in identifying MCI in PD and iRBD. Results: In PD, a normality cutoff of 138 on the DRS-2 yielded the best balance between sensitivity (72%) and specificity (86%) with a correct classification of 80%. In iRBD, the optimal normality cutoff was 141 on the DRS-2, with a sensitivity of 90%, a specificity of 71% and a correct classification of 82%. No cutoff for the MMSE was found to have acceptable sensitivity or specificity. Conclusion: The DRS-2 has satisfactory validity to detect MCI in PD or iRBD. The MMSE proved to be invalid as a screening test for MCI in both populations.