Open AccessAdaptive and pathological connectivity responses in Parkinson’s disease brain networks
Author(s) -
An Vo,
Katharina A. Schindlbeck,
Nha Nguyen,
Andrea Rommal,
Phoebe Spetsieris,
Chris C. Tang,
Yoon Young Choi,
Martin Niethammer,
Vijay Dhawan,
David Eidelberg
Publication year - 2022
Publication title -
cerebral cortex
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.694
H-Index - 250
eISSN - 1460-2199
pISSN - 1047-3211
DOI - 10.1093/cercor/bhac110
Subject(s) - assortativity , neuroscience , parkinson's disease , disease , dopaminergic , neuroimaging , medicine , biology , dopamine , computer science , complex network , pathology , world wide web
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.