Objective: To identify motor symptom subtypes in idiopathic Parkinson’s disease (PD) using a Bayesian analytic approach to latent profile analysis.

Background: Several subtypes of Parkinson’s disease (PD) have been proposed to account for the considerable heterogeneity in symptom presentation. However, current analytic approaches assume that motor symptom scores are perfect measures of a given symptom, and that there are no correlations between motor symptom scores within each subtype:  given that all individuals share a diagnosis, there are likely to be facets of the disease common to all that cannot be explained by subtype membership, leading to correlations within subtypes. A Bayesian statistical framework deals with measurement error, allows correlations within subtypes (does not assume local independence), and is suitable for smaller samples.

Methods: 249 individuals with idiopathic PD completed the revised Unified Parkinson’s Disease Rating Scale. Using Bayesian estimation, a factor analysis (with informative priors for cross-loadings) was conducted. A mixture-model of these (error-free) factors was then estimated, using informative priors to relax the assumption of local independence within subtypes. This allows for subtyping based not only on differences in symptom severity, but also on differences in the relationships between symptoms.

Results: Significant cross-loadings and subtype-specific symptom correlations support the need for a Bayesian approach. The 3-class solution showed the best fit and clear separation of individuals. A group with significantly increased postural, rigid, and akinetic severity was identified. A group with reduced overall symptom severity and greatly reduced rest tremor severity was also identified. The third class was an intermediary, sharing a mixture of the other two classes’ symptoms.

Conclusions: Previous studies have proposed postural instability and gait difficulty, and akinetic-rigid subtypes. However, these results indicate that both are part of the same subtype, and that assessing postural or akinetic symptoms in isolation would not accurately capture an individual’s motor subtype. This may be largely responsible for inconsistent subtyping results to date.

This robust approach to subtyping in PD reveals three novel classes of motor symptoms in PD, and demonstrates a framework for exploring heterogeneity in PD. Longitudinal studies are required to explore the prognostic value of subtypes.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/motor-heterogeneity-in-parkinsons-disease-a-bayesian-perspective/