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. 2015;5(2):269-79.
doi: 10.3233/JPD-140523.

Parkinson's Disease Subtypes in the Oxford Parkinson Disease Centre (OPDC) Discovery Cohort

Michael Lawton  1 , Fahd Baig  2 , Michal Rolinski  2 , Claudio Ruffman  2 , Kannan Nithi  3 , Margaret T May  1 , Yoav Ben-Shlomo  1 , Michele T M Hu  2   3
Affiliations
Free PMC article

Parkinson's Disease Subtypes in the Oxford Parkinson Disease Centre (OPDC) Discovery Cohort

Michael Lawton et al. J Parkinsons Dis. 2015.
Free PMC article

Abstract

Background: Within Parkinson's there is a spectrum of clinical features at presentation which may represent sub-types of the disease. However there is no widely accepted consensus of how best to group patients.

Objective: Use a data-driven approach to unravel any heterogeneity in the Parkinson's phenotype in a well-characterised, population-based incidence cohort.

Methods: 769 consecutive patients, with mean disease duration of 1.3 years, were assessed using a broad range of motor, cognitive and non-motor metrics. Multiple imputation was carried out using the chained equations approach to deal with missing data. We used an exploratory and then a confirmatory factor analysis to determine suitable domains to include within our cluster analysis. K-means cluster analysis of the factor scores and all the variables not loading into a factor was used to determine phenotypic subgroups.

Results: Our factor analysis found three important factors that were characterised by: psychological well-being features; non-tremor motor features, such as posture and rigidity; and cognitive features. Our subsequent five cluster model identified groups characterised by (1) mild motor and non-motor disease (25.4%), (2) poor posture and cognition (23.3%), (3) severe tremor (20.8%), (4) poor psychological well-being, RBD and sleep (18.9%), and (5) severe motor and non-motor disease with poor psychological well-being (11.7%).

Conclusion: Our approach identified several Parkinson's phenotypic sub-groups driven by largely dopaminergic-resistant features (RBD, impaired cognition and posture, poor psychological well-being) that, in addition to dopaminergic-responsive motor features may be important for studying the aetiology, progression, and medication response of early Parkinson's.

Keywords: Cohort studies; Parkinson’s disease; cluster analysis; factor analysis.

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Figures

Fig.1
Fig.1
Flow chart of patient entry into study.
Fig.2
Fig.2
Within cluster means of the standardised variables for the 5 cluster solution. Positive is worse than average and negative better than average. For laterality positive is more bilateral than average and negative more unilateral than average.
See this image and copyright information in PMC

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