Electrophysiological Signatures of Anxiety in Parkinson’s Disease (S51.008)

Abstract

<h3>Objective:</h3> 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). <h3>Background:</h3> 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. <h3>Design/Methods:</h3> 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. <h3>Results:</h3> 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. <h3>Conclusions:</h3> 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. <b>Disclosure:</b> Mrs. Yassine has nothing to disclose. Mrs. Almarouk has nothing to disclose. Ute Gschwandtner has nothing to disclose. 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. Mr. HASSAN has nothing to disclose. The institution of Dr. Fuhr has received research support from Roche. Mr. Verin has nothing to disclose.