Alteration of brain structural connectivity in progression of Parkinson's disease: A connectome-wide network analysis.

Neuroimage Clin

Department of Neurobiology, Neurology and Geriatrics, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Disease, Beijing, China. Electronic address:

Published: September 2021

AI Article Synopsis

  • Researchers are studying brain connectivity changes in idiopathic rapid eye movement sleep behavior disorder (iRBD) to understand its progression to Parkinson's disease (PD).
  • The study involved 151 participants (iRBD, PD, and healthy controls) who underwent diffusion MRI scans to analyze brain structural networks.
  • Findings revealed significant changes in brain connectivity in certain regions as PD progresses, and machine learning improved the classification of these patterns, potentially aiding in early prediction of PD.

Article Abstract

Pinpointing the brain dysconnectivity in idiopathic rapid eye movement sleep behaviour disorder (iRBD) can facilitate preventing the conversion of Parkinson's disease (PD) from prodromal phase. Recent neuroimage investigations reported disruptive brain white matter connectivity in both iRBD and PD, respectively. However, the intrinsic process of the human brain structural network evolving from iRBD to PD still remains largely unknown. To address this issue, 151 participants including iRBD, PD and age-matched normal controls were recruited to receive diffusion MRI scans and neuropsychological examinations. The connectome-wide association analysis was performed to detect reorganization of brain structural network along with PD progression. Eight brain seed regions in both cortical and subcortical areas demonstrated significant structural pattern changes along with the progression of PD. Applying machine learning on the key connectivity related to these seed regions demonstrated better classification accuracy compared to conventional network-based statistic. Our study shows that connectome-wide association analysis reveals the underlying structural connectivity patterns related to the progression of PD, and provide a promising distinct capability to predict prodromal PD patients.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8209844PMC
http://dx.doi.org/10.1016/j.nicl.2021.102715DOI Listing

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