Multivariate prediction of dementia in Parkinson’s disease

Thanaphong Phongpreecha, Brenna Cholerton, Ignacio F. Mata, Cyrus P. Zabetian, Kathleen L. Poston, Nima Aghaeepour, Lu Tian, Joseph F. Quinn, Kathryn A. Chung, Amie L. Hiller, Shu Ching Hu, Karen L. Edwards, Thomas J. Montine

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Cognitive impairment in Parkinson’s disease (PD) is pervasive with potentially devastating effects. Identification of those at risk for cognitive decline is vital to identify and implement appropriate interventions. Robust multivariate approaches, including fixed-effect, mixed-effect, and multitask learning models, were used to study associations between biological, clinical, and cognitive factors and for predicting cognitive status longitudinally in a well-characterized prevalent PD cohort (n = 827). Age, disease duration, sex, and GBA status were the primary biological factors associated with cognitive status and progression to dementia. Specific cognitive tests were better predictors of subsequent cognitive status for cognitively unimpaired and dementia groups. However, these models could not accurately predict future mild cognitive impairment (PD-MCI). Data collected from a large PD cohort thus revealed the primary biological and cognitive factors associated with dementia, and provide clinicians with data to aid in the identification of risk for dementia. Sex differences and their potential relationship to genetic status are also discussed.

Original languageEnglish (US)
Article number20
Journalnpj Parkinson's Disease
Volume6
Issue number1
DOIs
StatePublished - Dec 1 2020

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology
  • Cellular and Molecular Neuroscience

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