One Patient, One Destiny: A Cluster Analysis of PPMI Data
Khashayar Dashtipour1, Mehrbod Vakhshoori2, Alberto Espay3, Jacob Jones4, Karen Frei1, Farzin Pedouim1
1Neurology, Loma Linda University Medical Center, 2Loma Linda University Medical Center, 3University of Cincinnati, 4Department of Psychology, California State University San Bernardino
Objective:

We tested whether Parkinson’s disease (PD) patients with similar and distinctive baseline characteristics maintain or separate clinical outcomes independent of comorbidity, genetics, and demographics.

Background:

PD patients can exhibit diverse motor and non-motor symptoms. Prior attempts to classify patients based on phenotype subtypes have not consistently predicted outcomes, highlighting the unpredictability of disease progression. There remains a gap in research exploring outcome variability beyond phenotypic characteristics, and no study to date has confirmed this hypothesis.

Design/Methods:

Utilizing data from the Parkinson's Progression Markers Initiative (PPMI), we analyzed a cohort of 209 PD patients over a five-year follow-up period. Patients were grouped based on baseline characteristics including age (<50, 50-80, >80 years), sex, race (White, African-American, Hispanic, others), BMI (<18.5, 18.5-25, 25-30, >30 kg/m²), genetic mutation status (positive/negative), medical history (cardiovascular disease (CVD) and endocrine disease), presence of jaw and limb tremors, and alpha-synuclein seeding status (positive/negative). Outcomes were assessed for motor and nonmotor features such as gait abnormalities, dyskinesia, motor fluctuations, dystonia, cognitive impairment, hallucinations, and others, as well as levodopa equivalent daily dose (LEDD) progression. Cluster analysis identified baseline and outcome clusters, visualizing patient flow over time with Sankey plots.

Results:

The analysis identified 120 unique baseline clusters and 169 distinct outcome clusters. The largest baseline PD cluster (n=14) consisted of white males aged 50-80, with no tremor, positive for cardiovascular and endocrine comorbidities, positive alpha-synuclein seeding status, no genetic mutations, and a BMI of 25-30 kg/m2. After five years, these patients dispersed into 14 unique outcome clusters. Conversely, the largest outcome cluster (n=13) (normal/negative for predefined variables, except LEDD progression) originated from 12 different baseline clusters.

Conclusions:

This analysis suggests the presence of an individualized clinical trajectory even among those with similar baseline features. This underscores the importance of a personalized, patient-centered approach to management and research in PD.

10.1212/WNL.0000000000210417
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