{Reference Type}: Journal Article
{Title}: Predictors associated with the rate of progression of nigrostriatal degeneration in Parkinson's disease.
{Author}: Yoo HS;Kim HK;Lee HS;Yoon SH;Na HK;Kang SW;Lee JH;Ryu YH;Lyoo CH;
{Journal}: J Neurol
{Volume}: 271
{Issue}: 8
{Year}: 2024 Aug 5
{Factor}: 6.682
{DOI}: 10.1007/s00415-024-12477-z
{Abstract}: BACKGROUND: Parkinson's disease (PD) manifests as a wide variety of clinical phenotypes and its progression varies greatly. However, the factors associated with different disease progression remain largely unknown.
METHODS: In this retrospective cohort study, we enrolled 113 patients who underwent 18F-FP-CIT PET scan twice. Given the negative exponential progression pattern of dopamine loss in PD, we applied the natural logarithm to the specific binding ratio (SBR) of two consecutive 18F-FP-CIT PET scans and conducted linear mixed model to calculate individual slope to define the progression rate of nigrostriatal degeneration. We investigated the clinical and dopamine transporter (DAT) availability patterns associated with the progression rate of dopamine depletion in each striatal sub-region.
RESULTS: More symmetric parkinsonism, the presence of dyslipidemia, lower K-MMSE total score, and lower anteroposterior gradient of the mean putaminal SBR were associated with faster progression rate of dopamine depletion in the caudate nucleus. More symmetric parkinsonism and lower anteroposterior gradient of the mean putaminal SBR were associated with faster depletion of dopamine in the anterior putamen. Older age at onset, more symmetric parkinsonism, the presence of dyslipidemia, and lower anteroposterior gradient of the mean putaminal SBR were associated with faster progression rate of dopamine depletion in the posterior putamen. Lower striatal mean SBR predicted the development of LID, while lower mean SBR in the caudate nuclei predicted the development of dementia.
CONCLUSIONS: Our results suggest that the evaluation of baseline clinical features and patterns of DAT availability can predict the progression of PD and its prognosis.