Dataset Information

Variation in Recent Onset Parkinson's Disease: Implications for Prodromal Detection.

ABSTRACT:

Background

The detection of prodromal Parkinson's disease (PD) is desirable to test drugs with neuroprotective potential, but will be affected by known disease variations.

Objective

To assess the prevalence of four key non-motor prodromal PD markers, and evaluate the sensitivity of case detection when non-motor screening tools for prodromal PD are implemented in an early clinical PD cohort.

Methods

Hyposmia (University of Pennsylvania smell identification test ≤15th centile or Sniffin' Sticks at or ≤10th centile corrected for age and sex), rapid-eye movement sleep behaviour disorder (RBD questionnaire >4), constipation (<1 daily spontaneous bowel motion) and depression (Leeds >6) were recorded in recent onset PD cases, and proposed non-motor screening criteria applied.

Results

In 1,719 PD cases, mean age 68.6 years (SD 8.1), 65.5% male, mean disease duration 1.3 years (SD 0.9), 72.2% were hyposmic, 43.3% had RBD, 22.1% depression, and 21.5% constipation. 11.6% of cases had no key non-motor features, 38.8% one, 32.1% two, 15.5% three, and 2.0% all four. Increasing numbers of non-motor features were associated with younger age (p = 0.019), higher motor scores (p < 0.001), more postural instability gait difficulty (PIGD) (p < 0.001), greater cognitive impairment (p < 0.001) and higher total non-motor burden (p < 0.001). Cases with hyposmia alone were younger (p < 0.001), had less severe cognitive (p = 0.006) and other non-motor features (p < 0.001). All screening criteria selected younger patients (p = 0.001, p < 0.001), three of four greater overall non-motor burden (p = 0.005, p < 0.001), and inclusion of RBD more cognitive impairment (p = 0.003, p = 0.001) and PIGD (p = 0.004, p = 0.001).

Conclusions

Varying sensitivity levels, and age and phenotype selectivity, are found when different non-motor screening methods to detect prodromal PD are applied to an early clinical PD cohort.

SUBMITTER: Swallow DM

PROVIDER: S-EPMC4927926 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description: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.