Adaptive and pathological connectivity responses in Parkinson's disease brain networks. (25th March 2022)

• Record Type: Journal Article
• Authors: Vo, An; Schindlbeck, Katharina A; Nguyen, Nha; Rommal, Andrea; Spetsieris, Phoebe G; Tang, Chris C; Choi, Yoon Young; Niethammer, Martin; Dhawan, Vijay; Eidelberg, David
• Is Part Of: Cerebral cortex. Volume 33:Number 4(2023)
• Page Start: 917
• Page End: 932
• Publication Date: 2022-03-25
• Subjects: brain networks -- FDG PET -- graph theory -- metabolic connectivity -- Parkinson's disease; Cerebral cortex -- Periodicals; Brain -- Periodicals; 612.825
• DOI: 10.1093/cercor/bhac110
• Languages: English
• ISSNs: 1047-3211

Abstract

Abstract: Functional imaging has been used extensively to identify and validate disease-specific networks as biomarkers in neurodegenerative disorders. It is not known, however, whether the connectivity patterns in these networks differ with disease progression compared to the beneficial adaptations that may also occur over time. To distinguish the 2 responses, we focused on assortativity, the tendency for network connections to link nodes with similar properties. High assortativity is associated with unstable, inefficient flow through the network. Low assortativity, by contrast, involves more diverse connections that are also more robust and efficient. We found that in Parkinson's disease (PD), network assortativity increased over time. Assoratitivty was high in clinically aggressive genetic variants but was low for genes associated with slow progression. Dopaminergic treatment increased assortativity despite improving motor symptoms, but subthalamic gene therapy, which remodels PD networks, reduced this measure compared to sham surgery. Stereotyped changes in connectivity patterns underlie disease progression and treatment responses in PD networks.