Introduction: Motor reserve refers to the individual capacity to cope with nigrostriatal dopamine depletion in Parkinson's disease (PD). This study aimed to explore the white matter structural network associated with motor reserve in patients with newly diagnosed PD. Methods: A total of 238 patients with early-stage drug-naïve PD who underwent 18F-FP-CIT PET and brain MRI scans at initial assessment were enrolled. We estimated individual motor reserve based on the Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) scores and dopamine transporter availability in the posterior putamen using a residual model. Then, we performed threshold-free network-based statistics (TFNBS) analysis to identify the structural brain network associated with the estimated motor reserve. We also assessed the effect of the network connectivity strength on the longitudinal increase in levodopa-equivalent dose (LED). Results: The mean age at PD symptom onset was 69.10 ± 9.03 years and the mean UPDRS-III score at the time of PD diagnosis was 22.44 ± 9.72. TFNBS analysis identified a motor reserve-associated structural network whose nodes were mainly in the frontal region and cerebellum. Higher network strength (i.e., greater motor reserve) was associated with a slower longitudinal increase in LED during a 3-year follow-up period. Conclusion: The structural brain network is associated with motor reserve in patients with PD. Connectivity strength within the identified network indicates the individual's capacity to tolerate PD-related pathologies, which is maintained with disease progression and affects the long-term motor prognosis of PD.
|Number of pages||7|
|Journal||Parkinsonism and Related Disorders|
|Publication status||Published - 2022 Sept|
Bibliographical noteFunding Information:
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Basic Research Lab (BRL) Program ( NRF-2020R1A4A1018714 ) and the Ministry of Education ( NRF-2021R1I1A1A01059678 ). This research was also supported by a Faculty research grant from Yonsei University College of Medicine ( 6-2020-0205 ).
© 2022 Elsevier Ltd
All Science Journal Classification (ASJC) codes
- Geriatrics and Gerontology
- Clinical Neurology