Presynaptic dopamine depletion predicts levodopa-induced dyskinesia in de novo Parkinson disease

Jin Yong Hong, Jungsu S. Oh, Injoo Lee, Mun Kyung Sunwoo, Jee Hyun Ham, Ji E. Lee, Young H. Sohn, Jae Seung Kim, Phil Hyu Lee

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74 Citations (Scopus)


Objective: To investigate whether the magnitude of presynaptic dopamine depletion is a risk factor for the development of levodopa-induced dyskinesia (LID) in Parkinson disease (PD) by quantitatively analyzing 18F-FP- CIT PET data. Methods: This retrospective cohort study enrolled a total of 127 drug-naive de novo patients with PD who completed 18F-FP-CIT PET scanning at their initial evaluation. The patients visited our outpatient clinic every 3-6 months and had been followed for a minimum of 2 years since beginning dopaminergic medication. The predictive power of the quantitatively analyzed 18F-FP-CIT uptake of striatal subregions and other clinical factors for the development of LID was evaluated using Cox proportional hazard models. Results: During a mean follow-up period of 3.4 years, 35 patients with PD (27.6%) developed LID. Patients with LID showed less dopamine transporter (DAT) activity in the putamen than did those without LID. Multivariate Cox proportional hazard models revealed that the DAT uptakes of the anterior putamen (hazard ratio [HR] 0.530; p = 0.032), posterior putamen (HR 0.302; p = 0.024), and whole putamen (HR 0.386; p = 0.022) were significant predictors of the development of LID, whereas DAT activities in the caudate and ventral striatum were not significantly correlated with the development of LID. In addition, younger age at onset of PD and higher dose of levodopa were also significant predictors of the development of LID. Conclusions: The present results provide convincing evidence that presynaptic dopaminergic denervation in PD plays a crucial role in the development of LID.

Original languageEnglish
Pages (from-to)1597-1604
Number of pages8
Issue number18
Publication statusPublished - 2014 May 6

All Science Journal Classification (ASJC) codes

  • Clinical Neurology


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