Abstract Details

Title Electrophysiological Signatures of Anxiety in Parkinson’s Disease

Topic Movement Disorders

Presentation(s) S51 - Movement Disorders: Tremor, Parkinsonism, and Non-motor Symptoms (4:54 PM-5:06 PM)

Poster/Presentation
Number 008

Objective

To assess the pattern of disturbances in the functional brain networks of Parkinson’s disease patients with anxiety (PD-A) compared to those without anxiety (PD-NA) and healthy controls (HC).

Background Anxiety is a common non motor symptom in PD occurring in up to 60% of the patients and affecting their quality of life. Despite their high prevalence, anxiety symptoms are often undiagnosed and untreated in PD. To date, functional and structural neuroimaging studies have contributed to our understanding of the motor and cognitive symptomatology of PD. Yet, the underlying pathophysiology of the anxiety symptoms in PD remains largely unknown and studies on their neural correlates are missing.

Design/Methods

The present study comprised 68 non-demented PD patients and 25 healthy controls. PD patients were divided into two subgroups based on their Beck Anxiety Inventory (BAI) scale (cut-off=13): PD patients with anxiety (N=18) and without anxiety (N=50). Using their resting state high density electroencephalography (EEG) recordings at baseline, we assessed the frequency-dependent functional connectivity patterns that characterize the PD-A patients compared to both PD-NA patients and HC and we validated their relevance after 3 years.

Results We revealed different frequency-dependent pattern of connectivity that can characterize the PD-A group compared to PD-NA and HC: patterns with high functional connectivity were observed in delta, theta and gamma bands involving mainly fronto-temporal connections, whereas fronto-parietal patterns with low functional connectivity were pertinent in alpha and beta bands. Their corresponding network signature metric were strongly correlated with the anxiety scale of all the participants at baseline and after 3 years showing a predictive power of the revealed networks.

Conclusions

Our findings suggest that PD-related anxiety can be characterized by a signature of different frequency-dependent pattern of disturbances in the functional brain networks. Resting state EEG could be a very promising biomarker for early detection of anxiety in PD.

Authors/Disclosures
Marc Verin (CHU Hopital Pontchaillou) PRESENTER	Mr. Verin has nothing to disclose.
	No disclosure on file
	No disclosure on file
	No disclosure on file
Manon Auffret, PhD, PharmD, DAAN	Dr. Auffret has received personal compensation for serving as an employee of France Développement Electronique. Dr. Auffret has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Aguettant. The institution of 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 Aguettant. The institution of Dr. Auffret has received research support from Oxylis Medical. Dr. Auffret has received publishing royalties from a publication relating to health care. Dr. Auffret has received publishing royalties from a publication relating to health care. Dr. Auffret has received publishing royalties from a publication relating to health care. Dr. Auffret has received publishing royalties from a publication relating to health care.
	No disclosure on file
Peter Fuhr, MD, FAAN	The institution of Dr. Fuhr has received research support from Roche.

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