Motor subtype changes in early Parkinson's disease

Highlights

• There exist multiple distinct motor subtypes of Parkinson's disease.

• The majority of Parkinson's disease patients have a tremor-dominant phenotype.

• Parkinson's disease subtypes vary with disease duration.

Abstract

Introduction

Distinct motor subtypes of Parkinson's disease (PD) have been described through both clinical observation and through data-driven approaches. However, the extent to which motor subtypes change during disease progression remains unknown. Our objective was to determine motor subtypes of PD using an unsupervised clustering methodology and evaluate subtype changes with disease duration.

Methods

The Parkinson's Progression Markers Initiative database of 423 newly diagnosed PD patients was utilized to retrospectively identify unique motor subtypes through a data-driven, hierarchical correlational clustering approach. For each patient, we assigned a subtype to each motor assessment at each follow-up visit (time points) and by using published criteria. We examined changes in PD subtype with disease duration using both qualitative and quantitative methods.

Results

Five distinct motor subtypes were identified based on the motor assessment items and these included: Tremor Dominant (TD), Axial Dominant, Appendicular Dominant, Rigidity Dominant, and Postural and Instability Gait Disorder Dominant. About half of the patients had consistent subtypes at all time points. Most patients met criteria for TD subtype soon after diagnosis. For patients with inconsistent subtypes, there was an overall trend to shift away from a TD phenotype with disease duration, as shown by chi-squared test, p < 0.001, and linear regression analysis, p < 0.05.

Conclusion

These results strongly suggest that classification of motor subtypes in PD can shift with increasing disease duration. Shifting subtypes is a factor that should be accounted for in clinical practice or in clinical trials.

Introduction

It is widely accepted that Parkinson's disease (PD) is a clinically heterogeneous disease with several different motor phenotypes [1], [2]. Accurately characterizing the heterogeneity that occurs in PD is important for assessing prognosis, enrolling in clinical trials, and for screening for possible co-morbidities [3]. Properly subtyping patients is also a critical step for determining inclusion in both preclinical [4], [5] and clinical studies, particularly those involving individualized treatment plans based on motor symptoms [6], [7], [8].

PD subtype categories were originally based on clinical observation of motor symptoms [1], [9]. Commonly recognized subtypes of PD include a tremor dominant (TD) group and a postural instability and gait disorder/difficulty/dominant (PIGD) group [2]. Some clinicians and researchers also recognize an ill-defined intermediate or indeterminate type (IT) classification for patients that do not fit the TD or PIGD phenotype. Recently, studies have proposed additional subtypes based on data-driven cluster analysis approaches using other clinical characteristics including age of onset, speed of disease progression, cognitive measures, and behavioral measures [10], [11], [12], [13], [14]. Aside from establishing subtypes, several studies have attempted to clarify whether subtypes are fixed or whether they represent different stages of disease progression [15], [16].

In this study, our goal was to use a data-driven approach to discover distinct motor subtypes in PD, and to apply these subtypes to longitudinal motor assessment data to look for shift in category over time. To accomplish this task, we used hierarchical correlational clustering on motor assessment data from 423 early PD patients included in the Parkinson's Progression Markers Initiative (PPMI) database (www.ppmi-info.org/data).