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Updated: Jan 11, 2026

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
Published on: July 24, 2019
Global network and local vulnerabilities underlie brain atrophy across Parkinson's disease stages
Andrew Vo1, Christina Tremblay2, Shady Rahayel2
1Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Canada H3A 2B4.
Abstract:
Parkinson's disease is associated with extensive structural brain changes. Recent work has proposed that the spatial pattern of disease pathology is shaped by both network spread and local vulnerability. However, few studies have assessed these biological frameworks in large patient samples across disease stages. Analysing the largest imaging cohort in Parkinson's disease to date (n = 3096 patients), we investigated the roles of network architecture and local brain features by relating regional abnormality maps to normative profiles of connectivity, intrinsic networks, cytoarchitectonics, neurotransmitter receptor densities and gene expression. We found widespread cortical and subcortical atrophy in Parkinson's disease to be associated with advancing disease stage, longer time since diagnosis and poorer global cognition. Structural brain connectivity best explained cortical atrophy patterns in Parkinson's disease and across disease stages. These patterns were robust among individual patients. The precuneus, lateral temporal cortex and amygdala were identified as likely network-based epicentres, with high convergence across disease stages. Individual epicentres varied significantly among patients, yet they consistently localized to the default mode and limbic networks. Furthermore, we showed that regional overexpression of genes implicated in synaptic structure and signalling conferred increased susceptibility to brain atrophy in Parkinson's disease. In summary, this study demonstrates in a well-powered sample that structural brain abnormalities in Parkinson's disease across disease stages and within individual patients are influenced by both network spread and local vulnerability.
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