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Multimodal biomarkers as predictors of cognitive decline in Parkinson’s Disease

T. Tropea, J. Berlyand, J. McBride, J. Doshi, C. Davatzikos, L. Shaw, S. Xie, J. Trojanowski, D. Weintraub, A. Chen-Plotkin (Philadelphia, PA, USA)

Meeting: 2017 International Congress

Abstract Number: 959

Keywords: Dementia, Parkinsonism

Session Information

Date: Wednesday, June 7, 2017

Session Title: Parkinson's Disease: Cognition

Session Time: 1:15pm-2:45pm

Location: Exhibit Hall C

Objective: To identify a set of multimodal biomarkers to predict cognitive decline in non-demented Parkinson’s disease patients.  

Background: People with Parkinson’s Disease are at high risk of developing cognitive impairment and dementia. Early identification of those at risk of developing dementia may help guide clinical decision making and inform research studies. Cross sectional studies have identified candidate biomarkers to inform predictive models of cognitive decline. Few longitudinal studies have evaluated the use of biomarkers to predict change in cognition over time, and even fewer investigate the use of biomarker panels encompassing multiple modalities. 

Methods: We performed a prospective cohort study of 100 patients with a diagnosis of Parkinson’s disease based on clinical examination. All participants were cognitively normal or had mild cognitive impairment (MCI) at baseline based on a consensus panel of physicians. Lumbar puncture, MRI and cognitive testing were performed at baseline and cognitive exams were performed at yearly intervals. We examined 17 biomarkers from clinical, genetic, biochemical, and MRI-based imaging modalities, investigating each marker’s contribution to prediction of cognitive decline individually, as well as developing a multimodal biomarker model to maximize predictive performance. The primary outcome was change in the Mattis Dementia Rating Scale-2 over time. The effect of APOE genotype on cognitive change over time was assessed for individual DRS subdomains. 

Results: The best fit linear mixed-effects model determined the presence of APOE E4 allele, hallucinations and SPARE-AD score to predict longitudinal decline in dementia rating scale, with APOE genotype exerting the greatest effect.  Indeed, in a Cox proportional hazards model, presence of the APOE E4 allele was associated with a 3.5 times higher risk of cognitive decline from normal to MCI or MCI to dementia (HR 3.53 95% CI 1.52-8.24, p<0.05) on an annual basis. This effect was not specific to any DRS subdomain.

Conclusions: These results confirm the importance of APOE genotype as a predictive biomarker in the development of cognitive impairment in Parkinson’s disease and highlight similarities between Alzheimer’s and Parkinson’s Disease pathogenesis.

This research has previously been presented the 18th Annual NINDS Udall Centers Meeting, 11/4/2016, Bethesda, MD. 

To cite this abstract in AMA style:

T. Tropea, J. Berlyand, J. McBride, J. Doshi, C. Davatzikos, L. Shaw, S. Xie, J. Trojanowski, D. Weintraub, A. Chen-Plotkin. Multimodal biomarkers as predictors of cognitive decline in Parkinson’s Disease [abstract]. Mov Disord. 2017; 32 (suppl 2). https://www.mdsabstracts.org/abstract/multimodal-biomarkers-as-predictors-of-cognitive-decline-in-parkinsons-disease/. Accessed June 14, 2025.
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