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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)

The final, peer-reviewed published version of this preprint can be found here:

Functional Magnetic Resonance Imaging Biomarkers Predicting Cognitive Progression in Parkinson Disease: Protocol for a Prospective Longitudinal Cohort Study

Hanna-Pladdy B, Gullapalli R, Chen H

Functional Magnetic Resonance Imaging Biomarkers Predicting Cognitive Progression in Parkinson Disease: Protocol for a Prospective Longitudinal Cohort Study

JMIR Res Protoc 2019;8(4):e12870

DOI: 10.2196/12870

PMID: 31033450

PMCID: 6660119

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Functional Magnetic Resonance Imaging Biomarkers Predicting Cognitive Progression in Parkinson Disease: Protocol for a Prospective Longitudinal Cohort Study

  • Brenda Hanna-Pladdy; 
  • Rao Gullapalli; 
  • Hegang Chen

Background:

Cardinal features of Parkinson disease (PD) are motor symptoms, but nonmotor 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 the 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 functional magnetic resonance imaging paradigm of object recognition memory; and (4) anatomical and regional brain activation changes (resting-state functional magnetic resonance imaging) across 4 years.

Results:

The project received funding from the National Institutes of Health in August 2017, and data collection began in February 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, and structural and functional magnetic resonance imaging 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.

International Registered Report:

DERR1-10.2196/12870


 Citation

Please cite as:

Hanna-Pladdy B, Gullapalli R, Chen H

Functional Magnetic Resonance Imaging Biomarkers Predicting Cognitive Progression in Parkinson Disease: Protocol for a Prospective Longitudinal Cohort Study

JMIR Res Protoc 2019;8(4):e12870

DOI: 10.2196/12870

PMID: 31033450

PMCID: 6660119

Per the author's request the PDF is not available.

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