scholarly journals Lack of Association Between GBA Mutations and Motor Complications in European and American Parkinson’s Disease Cohorts

2021 ◽  
pp. 1-10
Author(s):  
Jodi Maple-Grødem ◽  
Kimberly C. Paul ◽  
Ingvild Dalen ◽  
Kathie J. Ngo ◽  
Darice Wong ◽  
...  

Background: Motor complications are a consequence of the chronic dopaminergic treatment of Parkinson’s disease (PD) and include levodopa-induced dyskinesia (LIDs) and motor fluctuations (MF). Currently, evidence is lacking whether patients with GBA-associated PD differ in their risk of developing motor complications compared to the general PD population. Objective: To evaluate the association of GBA carrier status with the development of LIDS and MFs from early PD. Methods: Motor complications were recorded prospectively in 884 patients with PD from four longitudinal cohorts using part IV of the UPDRS or MDS-UPDRS. Subjects were followed for up to 11 years and the associations of GBA mutations with the development of motor complications were assessed using parametric accelerated failure time models. Results: In 439 patients from Europe, GBA mutations were detected in 53 (12.1%) patients and a total of 168 cases of LIDs and 258 cases of MF were observed. GBA carrier status was not associated with the time to develop LIDs (HR 0.78, 95%CI 0.47 to 1.26, p = 0.30) or MF (HR 1.19, 95%CI 0.84 to 1.70, p = 0.33). In the American cohorts, GBA mutations were detected in 36 (8.1%) patients and GBA carrier status was also not associated with the progression to LIDs (HR 1.08, 95%CI 0.55 to 2.14, p = 0.82) or MF (HR 1.22, 95%CI 0.74 to 2.04, p = 0.43). Conclusion: This study does not provide evidence that GBA-carrier status is associated with a higher risk of developing motor complications. Publication of studies with null results is vital to develop an accurate summary of the clinical features that impact patients with GBA-associated PD.

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Moumita Chatterjee ◽  
Sugata Sen Roy

AbstractIn this article, we model alternately occurring recurrent events and study the effects of covariates on each of the survival times. This is done through the accelerated failure time models, where we use lagged event times to capture the dependence over both the cycles and the two events. However, since the errors of the two regression models are likely to be correlated, we assume a bivariate error distribution. Since most event time distributions do not readily extend to bivariate forms, we take recourse to copula functions to build up the bivariate distributions from the marginals. The model parameters are then estimated using the maximum likelihood method and the properties of the estimators studied. A data on respiratory disease is used to illustrate the technique. A simulation study is also conducted to check for consistency.


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