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

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)2948-2960
Number of pages13
JournalJournal of Neurology
Volume269
Issue number6
DOIs
Publication statusPublished - 2022 Jun

Bibliographical note

Funding Information:
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (Grant number: NRF-2019R1A2C2085462, PHL).

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.

All Science Journal Classification (ASJC) codes

  • Neurology
  • Clinical Neurology

Fingerprint

Dive into the research topics of 'White matter connectivity networks predict levodopa-induced dyskinesia in Parkinson’s disease'. Together they form a unique fingerprint.

Cite this