Accepted for/Published in: JMIR Research Protocols
Date Submitted: Nov 20, 2018
Open Peer Review Period: Dec 3, 2018 - Dec 17, 2018
Date Accepted: Mar 3, 2019
(closed for review but you can still tweet)
Functional MRI Biomarkers Predicting Cognitive Progression in Parkinson’s Disease: Protocol for a Prospective Longitudinal Cohort Study
ABSTRACT
Background:
Cardinal features of Parkinson’s disease (PD) are motor symptoms, but non-motor features such as mild cognitive impairment (MCI) are common early in the disease process. MCI can progress and convert to dementia in advanced stages creating significant disability and reduced quality of life. The primary pathological substrate for cognitive decline in PD is unclear, and there are no reliable biomarkers predicting risk of conversion to dementia. A subgroup of PD patients with visual hallucinations may display more rapid conversion to dementia suggesting that regional markers of visuoperceptual dysfunction may be sensitive to pathologic density in posterior cortical regions.
Objective:
The purpose of this project is to characterize PD-MCI and evaluate the utility of genetic and neuroimaging biomarkers in predicting cognitive outcomes with a prospective longitudinal study. We will evaluate whether accelerated cognitive progression may be reflected in biomarkers of early posterior cortical changes reflective of α-synuclein deposition.
Methods:
We will evaluate a cohort of early-stage PD patients with the following methods to predict cognitive progression: (1) Serial neuropsychological evaluations including detailed visuoperceptual functioning across 4 years. (2) Genetic analysis of SNCA (α-synuclein), MAPT (microtubule associated tau) and APOE (apolipoprotein E). (3) An event-related fMRI paradigm of object recognition memory. (4) Anatomical and regional brain activation changes (rs-fMRI) across 4 years.
Results:
The project received NIH funding in August of 2017 and data collection began February of 2018. Enrollment is ongoing, and subjects will be evaluated annually for 4 years extended across a 5 year project including data analysis and image processing.
Conclusions:
Cognitive, genetic, structural and functional MRI will characterize neural network changes predictive of cognitive progression in PD across 4 years. Identification of biomarkers with sensitivity for early prediction and estimation of risk for conversion to dementia in PD will pave the way for effective intervention with neuroprotective therapies during the critical stage when treatment can have the greatest impact.
Citation
Per the author's request the PDF is not available.
Copyright
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