Mapping cognitive and neuropsychiatric symptoms in idiopathic Parkinson’s Disease: A cross-sectional and longitudinal data analysis
Jonge, F.M.P. de
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Introduction: The purpose of this study was to map subtypes in Parkinson's disease with respect to motor, cognitive and neuropsychiatric symptoms, assess the possible relation between these symptoms, and assess their longitudinal disease trajectory. Methods: Data from 341 idiopathic Parkinson’s disease patients were used to perform a Hierarchical Cluster Analysis (HCA). We included measurements of motor, cognitive and neuropsychiatric symptoms. A Linear Discriminant Analysis (LDA) was performed to determine which constructs could best differentiate the clusters and a repeated measures ANOVA was used to assess the development of symptoms over a period of two years. Results: The HCA revealed six clusters: (A) a cluster with low motor symptoms and high REM sleep behavior disorder ( age M: 61.6); (B) a neuropsychiatrically and cognitively impaired cluster with rapidly worsening REM sleep behavior disorder (age M: 66.3); (C) a cluster with severe motor dysfunction and below average but stable cognition and neuropsychiatry (age M: 68.1); (D) a cluster with overall average functioning without RBD symptoms (age M: 65.9); (E) a young aged overall unimpaired cluster (age M: 58.0); and (F) an old-aged cluster with severe overall impairments (age M: 68.6). The LDA revealed that cognitive symptoms could best discriminate the clusters. Conclusion: We differentiated six cluster (A-E). The mean age in clusters A and E were relatively similar, as is the case for clusters B, C, D, and F. We found a distinction between these two cluster groups based on disease onset and severity of symptoms. The clusters were further distinguishable on specific cognitive, motor and neuropsychiatric symptoms. Future research should focus on determining whether the distinction we found is based on different underlying neuropathology or other factors, like medication effectiveness.