Dataset Information

Longitudinal evolution of non-motor symptoms in early Parkinson's disease: a 3-year prospective cohort study.

ABSTRACT: The progression of global non-motor symptoms (NMS) in Chinese patients with Parkinson's disease (PD) has not been explored. We aimed to examine the longitudinal evolution of overall NMS in a 3-year prospective Chinese cohort with early-stage PD. We included 224 patients with early PD who underwent annual evaluation of motor and non-motor symptoms. NMS was assessed using the non-motor symptoms scale (NMSS). We observed an increased number of NMS in the majority of the NMSS domains except mood/apathy and sexual dysfunctions. Significant deterioration was observed in the sleep/fatigue, perceptual problems/hallucinations, attention/memory, gastrointestinal, urinary, and miscellaneous domains during the follow-up (P < 0.05). Notably, the number and the score of sexual dysfunctions decreased with the progression of the disease. All NMSS domains showed a small effect size from baseline to 1-, 2-, and 3-year follow-ups (effect size < 0.5). The generalized estimating equations model indicated that the total number of NMS was significantly associated with age and the Unified Parkinson's Disease Rating Scale (UPDRS) III score (P < 0.05). Multiple logistic regression indicated that a high number of NMS at baseline was associated with a 3-point, a 6-point, and a 9-point increase in the UPDRS III score from baseline to 1-year (odds ratio [OR] 1.074, P = 0.017), 2-year (OR 1.113, P = 0.001), and 3-year (OR 1.117, P < 0.001), respectively. Our study indicated that overall NMS evolution in early PD is mild and multidimensional; a high NMS burden in early PD predicts the faster motor progression of PD. Our study is helpful for understanding the longitudinal evolution of NMS in PD.

SUBMITTER: Ou R

PROVIDER: S-EPMC8282608 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Dopamine transporter (DAT) imaging is an in vivo tool to assess presynaptic dopaminergic function in the clinical practices of Parkinson's disease (PD). Current clinical practices focused on qualitatively visual interpretation of DAT imaging, whereas quantitative analyses are potentially more helpful when monitoring the progression of PD. Previous cross-sectional studies indicated certain motor and non-motor features were associated with striatal DAT binding, whereas limited data were reported in terms of the longitudinal correlation between clinical features of PD with striatal DAT binding. The purpose of our study is to clarify current and longitudinal correlations between striatal DAT binding and clinical measures. A total of 352 untreated PD individuals and 167 healthy controls with complete baseline clinical measures and neuroimaging data were identified from the Parkinson's Progression and Markers Initiative (PPMI) database. Patients with PD underwent DAT imaging at the screening visit and following months 12, 24, and 48. Multiple linear regression models and linear mixed-effect models were respectively conducted to investigate the cross-sectional and longitudinal correlation between clinical characteristics and DAT binding. Associations between changes in clinical characteristics and changes in DAT binding were further evaluated and the Spearman rank correlation coefficients were reported. In the cross-sectional analysis, baseline striatal DAT binding was significantly associated with the Hoehn and Yahr scale, the Movement Disorder Society-Sponsored Revision of the Unified Parkinson Disease Rating Scale (MDS-UPDRS) scores, the rigidity scores, and the axial scores in PD individuals (false discovery rate [FDR]-adjusted p = 0.0017 for all above). Patients who developed freezing of gait had lower striatal DAT binding (FDR-adjusted p = 0.0161). Healthy controls who had higher tremor scores and suffered more severe olfactory dysfunction had lower striatal DAT binding (FDR-adjusted p = 0.0257 for all above). Longitudinal analysis indicated that baseline severity of rapid-eye-movement sleep behavior disorder was significantly associated with longitudinal striatal DAT binding in patients with PD (FDR-adjusted p = 0.0120). Furthermore, changes in MDS-UPDRS scores and the State-Trait Anxiety Inventory (STAI) scores demonstrated significant correlations with changes in striatal DAT binding over 4 years (p = 0.005 and p = 0.032, respectively). Our findings clarified quantitative associations between certain motor and non-motor features with current and future striatal dopamine binding, suggesting the feasibility of using DAT images as a progression predictive marker for PD. Further studies are needed to investigate correlations between different regional dopamine binding with specific clinical features.

Project description:BackgroundIdentifying individuals with high-risk Parkinson's disease (PD) at earlier stages is an urgent priority to delay disease onset and progression. In the present study, we aimed to develop and validate clinical risk models using non-motor predictors to distinguish between early PD and healthy individuals. In addition, we constructed prognostic models for predicting the progression of non-motor symptoms [cognitive impairment, Rapid-eye-movement sleep Behavior Disorder (RBD), and depression] in de novo PD patients at 5 years of follow-up.MethodsWe retrieved the data from the Parkinson's Progression Markers Initiative (PPMI) database. After a backward variable selection approach to identify predictors, logistic regression analyses were applied for diagnosis model construction, and cox proportional-hazards models were used to predict non-motor symptom progression. The predictive models were internally validated by correcting measures of predictive performance for "optimism" or overfitting with the bootstrap resampling approach.ResultsFor constructing diagnostic models, the final model reached a high accuracy with an area under the curve (AUC) of 0.93 (95% CI: 0.91-0.96), which included eight variables (age, gender, family history, University of Pennsylvania Smell Inventory Test score, Montreal Cognitive Assessment score, RBD Screening Questionnaire score, levels of cerebrospinal fluid α-synuclein, and SNCA rs356181 polymorphism). For the construction of prognostic models, our results showed that the AUC of the three prognostic models improved slightly with increasing follow-up time. The overall AUCs fluctuated around 0.70. The model validation established good discrimination and calibration for predicting PD onset and progression of non-motor symptoms.ConclusionThe findings of our study facilitate predicting the individual risk at an early stage based on the predictors derived from these models. These predictive models provide relatively reliable information to prevent PD onset and progression. However, future validation analysis is still needed to clarify these findings and provide more insight into the predictive models over more extended periods of disease progression in more diverse samples.

Dataset Information

Longitudinal evolution of non-motor symptoms in early Parkinson's disease: a 3-year prospective cohort study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets