Dana Pourzinal, Rachael A Lawson, Alison J Yarnall, Caroline H Williams-Gray, Roger A Barker, Jihyun Yang, Katie L McMahon, John D O'Sullivan, Gerard J Byrne, Nadeeka N Dissanayaka
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Baseline demographic and cognitive data at diagnosis were compared between subtypes to determine their clinical profile.</p><p><strong>Results: </strong>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.</p><p><strong>Discussion: </strong>People with PD susceptible to cognitive decline demonstrate unique clinical profiles at diagnosis, although this differed between cohorts.</p><p><strong>Highlights: </strong>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.</p>","PeriodicalId":53226,"journal":{"name":"Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring","volume":"16 3","pages":"e12625"},"PeriodicalIF":4.0000,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11299072/pdf/","citationCount":"0","resultStr":"{\"title\":\"Profiling people with Parkinson's disease at risk of cognitive decline: Insights from PPMI and ICICLE-PD data.\",\"authors\":\"Dana Pourzinal, Rachael A Lawson, Alison J Yarnall, Caroline H Williams-Gray, Roger A Barker, Jihyun Yang, Katie L McMahon, John D O'Sullivan, Gerard J Byrne, Nadeeka N Dissanayaka\",\"doi\":\"10.1002/dad2.12625\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>A subset of people with Parkinson's disease (PD) develop dementia faster than others. 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Profiling people with Parkinson's disease at risk of cognitive decline: Insights from PPMI and ICICLE-PD data.
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.
期刊介绍：
Alzheimer''s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM) is an open access, peer-reviewed, journal from the Alzheimer''s Association® that will publish new research that reports the discovery, development and validation of instruments, technologies, algorithms, and innovative processes. Papers will cover a range of topics interested in the early and accurate detection of individuals with memory complaints and/or among asymptomatic individuals at elevated risk for various forms of memory disorders. The expectation for published papers will be to translate fundamental knowledge about the neurobiology of the disease into practical reports that describe both the conceptual and methodological aspects of the submitted scientific inquiry. Published topics will explore the development of biomarkers, surrogate markers, and conceptual/methodological challenges. Publication priority will be given to papers that 1) describe putative surrogate markers that accurately track disease progression, 2) biomarkers that fulfill international regulatory requirements, 3) reports from large, well-characterized population-based cohorts that comprise the heterogeneity and diversity of asymptomatic individuals and 4) algorithmic development that considers multi-marker arrays (e.g., integrated-omics, genetics, biofluids, imaging, etc.) and advanced computational analytics and technologies.
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