Sahar Yassine1, Sourour Almarouk2, Ute Gschwandtner3, Manon Auffret4, Mahmoud HASSAN5, Peter Fuhr3, Marc Verin6
1Université Rennes 1, 2Lebanese University, 3Hospitals of the University of Basel, 4Behavior & Basal Ganglia - CHU Rennes/ Universite de Rennes 1, 5Reykjavik University, 6CHU Hopital Pontchaillou
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.