Neurophysiological Biomarkers of Parkinson's Disease.

Publisher: IOS Press Country of Publication: Netherlands NLM ID: 101567362 Publication Model: Print Cited Medium: Internet ISSN: 1877-718X (Electronic) Linking ISSN: 18777171 NLM ISO Abbreviation: J Parkinsons Dis Subsets: MEDLINE

Original Publication: Amsterdam : IOS Press

Beta Rhythm*/physiology ; Biomarkers* ; Electroencephalography Phase Synchronization*/physiology; Electroencephalography/*standards ; Outcome Assessment, Health Care/*standards ; Parkinson Disease/*diagnosis; Aged ; Dopamine Plasma Membrane Transport Proteins ; Electroencephalography/methods ; Female ; Humans ; Machine Learning ; Male ; Middle Aged ; Parkinson Disease/drug therapy ; Parkinson Disease/physiopathology ; Positron-Emission Tomography

Background: There is a need for reliable and robust Parkinson's disease biomarkers that reflect severity and are sensitive to disease modifying investigational therapeutics.
Objective: To demonstrate the utility of EEG as a reliable, quantitative biomarker with potential as a pharmacodynamic endpoint for use in clinical assessments of neuroprotective therapeutics for Parkison's disease.
Methods: A multi modal study was performed including aquisition of resting state EEG data and dopamine transporter PET imaging from Parkinson's disease patients off medication and compared against age-matched controls.
Results: Qualitative and test/retest analysis of the EEG data demonstrated the reliability of the methods. Source localization using low resolution brain electromagnetic tomography identified significant differences in Parkinson's patients versus control subjects in the anterior cingulate and temporal lobe, areas with established association to Parkinson's disease pathology. Changes in cortico-cortical and cortico-thalamic coupling were observed as excessive EEG beta coherence in Parkinson's disease patients, and correlated with UPDRS scores and dopamine transporter activity, supporting the potential for cortical EEG coherence to serve as a reliable measure of disease severity. Using machine learning approaches, an EEG discriminant function analysis classifier was identified that parallels the loss of dopamine synapses as measured by dopamine transporter PET.
Conclusion: Our results support the utility of EEG in characterizing alterations in neurophysiological oscillatory activity associated with Parkinson's disease and highlight potential as a reliable method for monitoring disease progression and as a pharmacodynamic endpoint for Parkinson's disease modification therapy.

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R44 AG050326 United States AG NIA NIH HHS; R44 AG054256 United States AG NIA NIH HHS

Keywords: Biomarkers; EEG; Parkinson’s disease; dopamine transporter PET; neurophysiology

0 (Biomarkers)
0 (Dopamine Plasma Membrane Transport Proteins)

Date Created: 20200303 Date Completed: 20210726 Latest Revision: 20230202

20230202

PMC7242849

10.3233/JPD-191844

32116262