Profiling people with Parkinson's disease at risk of cognitive decline: Insights from PPMI and ICICLE‐PD data

Abstract

Abstract Introduction A subset of people with Parkinson's disease (PD) develop dementia faster than others. We aimed to profile PD cognitive subtypes at risk of dementia based on their rate of cognitive decline. Method Latent class mixed models stratified subtypes in Parkinson's Progression Markers Initiative (PPMI) (N = 770) and ICICLE‐PD (N = 212) datasets based on their decline in the Montreal Cognitive Assessment over at least 4 years. Baseline demographic and cognitive data at diagnosis were compared between subtypes to determine their clinical profile. Results Four subtypes were identified: two with stable cognition, one with steady decline, and one with rapid decline. Performance on Judgement of Line Orientation, but not category fluency, was associated with a steady decline in the PPMI dataset, and deficits in category fluency, but not visuospatial function, were associated with a steady decline in the ICICLE‐PD dataset. Discussion People with PD susceptible to cognitive decline demonstrate unique clinical profiles at diagnosis, although this differed between cohorts. Highlights Four cognitive subtypes were revealed in two Parkinson's disease samples. Unique profiles of cognitive impairment were related to cognitive decline. Judgement of Line Orientation/category fluency predictive of steady decline. Global deficits related to rapid cognitive decline and increased dementia risk.

Keywords

• clinical neuropsychology
• cognitive impairment
• dementia
• latent class mixed model
• Parkinson's disease