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White matter connectivity networks predict levodopa-induced dyskinesia in Parkinson's disease

 Jin Ho Jung  ;  Yae Ji Kim  ;  Seok Jong Chung  ;  Han Soo Yoo  ;  Yang Hyun Lee  ;  Kyoungwon Baik  ;  Seong Ho Jeong  ;  Young Gun Lee  ;  Hye Sun Lee  ;  Byoung Seok Ye  ;  Young H Sohn  ;  Yong Jeong  ;  Phil Hyu Lee 
 JOURNAL OF NEUROLOGY, Vol.269(6) : 2948-2960, 2022-06 
Journal Title
Issue Date
Antiparkinson Agents / adverse effects ; Dyskinesia, Drug-Induced* / diagnostic imaging ; Dyskinesia, Drug-Induced* / etiology ; Humans ; Levodopa / adverse effects ; Parkinson Disease* / drug therapy ; White Matter* / diagnostic imaging
Degree-based statistics ; Levodopa-induced dyskinesia ; Network-based statistics ; Parkinson’s disease ; White matter connectivity
Background: Although levodopa-induced dyskinesia-relevant white matter change has been evaluated, it is uncertain whether these changes may reflect the underlying predisposing conditions leading to the development of levodopa-induced dyskinesia.

Objective: To elucidate the role of white matter connectivity networks in the development of levodopa-induced dyskinesia in drug-naïve Parkinson's disease.

Methods: We recruited 30 patients who developed levodopa-induced dyskinesia within 5 years from MRI acquisition (vulnerable-group), 47 patients who had not developed levodopa-induced dyskinesia within 5 years (resistant-group), and 28 controls. We performed comparative analyses of whole-brain white matter integrity and connectivity using tract-based spatial and network- and degree-based statistics. We evaluated the predictability of levodopa-induced dyskinesia development and relationship with its latency, using the average connectivity strength as a predictor in Cox- and linear-regression, respectively.

Results: Mean-diffusivity was lower mainly at the left frontal region in the vulnerable-group compared to the resistant-group. Network-based statistics identified a subnetwork consisting of the bilateral fronto-striato-pallido-thalamic and lateral parietal regions (subnetwork A) and degree-based statistics identified four subnetworks (hub-subnetwork) consisting of edges centered on the left superior frontal gyrus, left putamen, left insular, or left precentral gyrus, where the vulnerable-group had stronger connectivity compared to the resistant-group. Stronger connectivity within the subnetwork A and hub-subnetwork centered on the left superior frontal gyrus was a predictor of levodopa-induced dyskinesia development independent of known risk factors and had an inverse relationship with its latency.

Conclusions: Our data suggest that white matter connectivity subnetworks within corticostriatal regions play a pivotal role in the development of levodopa-induced dyskinesia.
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1. College of Medicine (의과대학) > Dept. of Neurology (신경과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Yonsei Biomedical Research Center (연세의생명연구원) > 1. Journal Papers
Yonsei Authors
Baik, Kyoungwon(백경원) ORCID logo https://orcid.org/0000-0001-7215-375X
Sohn, Young Ho(손영호) ORCID logo https://orcid.org/0000-0001-6533-2610
Ye, Byoung Seok(예병석) ORCID logo https://orcid.org/0000-0003-0187-8440
Yoo, Han Soo(유한수) ORCID logo https://orcid.org/0000-0001-7846-6271
Lee, Yang Hyun(이양현)
Lee, Young-Gun(이영건)
Lee, Phil Hyu(이필휴) ORCID logo https://orcid.org/0000-0001-9931-8462
Lee, Hye Sun(이혜선) ORCID logo https://orcid.org/0000-0001-6328-6948
Chung, Seok Jong(정석종) ORCID logo https://orcid.org/0000-0001-6086-3199
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