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Abstract Details

Resting-State Electroencephalography Reveals Three Subphenotypes of Parkinson’s Disease
Movement Disorders
P6 - Poster Session 6 (5:30 PM-6:30 PM)
5-002

Parkinson’s disease is a complex brain disorder characterised mainly by motor signs, with clinical evidence of cognitive and behavioural deficits in up to 40% of cases in early stage. Clinical and biological manifestations are very heterogeneous among individuals with PD and subgrouping was mainly performed using clinical parameters. However, these subgroups do not take into account underlying disease physiopathology, and were shown not entirely predictive of disease prognosis.

To identify different Parkinson’s disease (PD) sub-phenotypes and their electrophysiological profile based on resting-state electroencephalography (RS-EEG).

Resting-state electroencephalography (EEG) is a powerful tool to identify abnormal patterns of motor and cognitive deficits in PD. These disruptions have previously been identified across multiple frequency bands using cortical spectral power and functional connectivity from longitudinal high-density EEG recordings (baseline, 3 years follow-up and 5 years follow-up). In this study, using data-driven methods (similarity network fusion and source-space spectral analysis), we have performed a clustering analysis to identify disease sub-phenotypes and to determine whether different patterns of disruption are predictive of disease outcome.

We showed that PD patients (N = 44) can be subgrouped into three phenotypes with distinct electrophysiological profiles. These clusters are characterised by different levels of disruptions in the somatomotor network (delta and beta band), the frontotemporal network (alpha2 band) and the default mode network (alpha1 band), which consistently correlate with clinical profiles and disease courses. We showed that these clusters are statistically robust, and can predict the clinical trajectory and disease outcome.

Our findings show that novel phenotyping using electric brain signal analysis can distinguish PD subtypes based exclusively on different patterns of brain oscillations. These patterns can reflect underlying disease neurobiology. Innovative profiling in PD has clear potential in patient’s stratification and can also support new therapeutic strategies that are brain-based and designed to modulate brain activity disruption.

Authors/Disclosures
Marc Verin (CHU Hopital Pontchaillou)
PRESENTER
Mr. Verin has nothing to disclose.
Sahar Yassine Mrs. Yassine has nothing to disclose.
Ute Gschwandtner Ute Gschwandtner has nothing to disclose.
Manon Auffret, PhD, PharmD (Behavior & Basal Ganglia - CHU Rennes/ Universite de Rennes 1) Dr. Auffret has received personal compensation for serving as an employee of France Développement Electronique. The institution of Dr. Auffret has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Britannia. Dr. Auffret has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Britannia. Dr. Auffret has received personal compensation in the range of $5,000-$9,999 for serving on a Speakers Bureau for Britannia. Dr. Auffret has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Aguettant. The institution of Dr. Auffret has received research support from Association France Parkinson. The institution of Dr. Auffret has received research support from Homeperf. The institution of Dr. Auffret has received research support from LVL. The institution of Dr. Auffret has received research support from University of Rennes 1. The institution of Dr. Auffret has received research support from Aguettant. The institution of Dr. Auffret has received research support from Linde. The institution of Dr. Auffret has received research support from Plateforme Nationale pour la recherche sur la fin de vie. Dr. Auffret has received publishing royalties from a publication relating to health care.
Joan Duprez, PhD (University of Rennes 1) Dr. Duprez has nothing to disclose.
Peter Fuhr, MD, FAAN The institution of Dr. Fuhr has received research support from Roche.
Mahmoud Hassan, PhD (Reykjavik University) Mr. HASSAN has nothing to disclose.