Pedunculopontine nucleus microstructure predicts postural and gait symptoms in Parkinson's disease
Research output: Contribution to journal › Article
Colleges, School and Institutes
- Behavioural Brain Sciences Centre
Background: There is an urgent need to identify individuals at risk of postural instability and gait difficulties, and the resulting propensity for falls, in Parkinson's disease.
Objectives: Given known relationships between posture and gait and degeneration of the cholinergic pedunculopontine nucleus, we investigated whether metrics of pedunculopontine nucleus microstructural integrity hold independent utility for predicting future postural instability and gait difficulties and whether they could be combined with other candidate biomarkers to improve prognostication of these symptoms.
Methods: We used stereotactic mapping of the pedunculopontine nucleus and diffusion tensor imaging to extract baseline pedunculopontine nucleus diffusivity metrics in 147 participants with Parkinson's disease and 65 controls enrolled in the Parkinson's Progression Markers Initiative. We also recorded known candidate markers of posture and gait changes: loss of caudate dopamine and CSF β-amyloid 1-42 levels at baseline; as well as longitudinal progression motor symptoms over 72-months.
Results: Survival analyses revealed that reduced dopamine in the caudate and increased axial diffusivity in the pedunculopontine nucleus incurred independent risk of postural instability and gait difficulties. Binary logistic regression and receiver operating characteristics analysis in 117 participants with complete follow-up data at 60 months revealed that only pedunculopontine nucleus microstructure provided more accurate discriminative ability for predicting future postural instability and gait difficulties than clinical and demographic variables alone.
Conclusion: Dopaminergic and cholinergic loss incur independent risk for future postural instability and gait difficulties, and pedunculopontine nucleus microstructure can be used to prognosticate these symptoms from early Parkinson's disease stages.
|Early online date||13 May 2020|
|Publication status||E-pub ahead of print - 13 May 2020|