Literature DB >> 24211060

CYP2D6 phenotypes and Parkinson's disease risk: a meta-analysis.

Yu Lu1, Qiliu Peng1, Zhiyu Zeng2, Jian Wang1, Yan Deng1, Li Xie1, Cuiju Mo1, Jie Zeng3, Xue Qin4, Shan Li5.   

Abstract

BACKGROUND: CYP2D6 polymorphisms have been reported to be associated with Parkinson's disease (PD) susceptibility, but the results of these previous studies were inconsistent.
OBJECTIVES: To explore whether PD patients with CYP2D6 gene variation have different risk to PD to those with normal function of CYP2D6.
METHODS: Systematic review with meta-analysis of case-controlled studies on the association between CYP2D6 and PD risk was conducted. Studies published up to August 1, 2013 were identified by searching electronic databases PubMed and Embase. Odds ratios (ORs) together with their corresponding 95% confidence intervals (CIs) were used to estimated the association between CYP2D6 polymorphisms and PD risk in different phenotype models. Meta-regression, subgroup analysis, sensitivity analysis and publication bias were also performed.
RESULTS: A total of 3521 PD Patients and 4476 controls from 29 case-control studies were identified. Overall, a borderline significant influence of the CYP2D6 polymorphisms on PD risk was observed (OR: 1.07, 95%CI: 0.99-1.16, p=0.106). Significant association was found when comparisons were performed in different phenotypes in PM versus EM (OR=1.33, 95% CI=1.01-1.74, p=0.044) and PM versus IM+EM (OR=1.32, 95% CI=1.11-1.56, p=0.002). In subgroup analysis stratified by country, significant association was demonstrated in British but not in other white subjects. No significant association was detected in subgroup analysis according to the age of onset and the source of patients.
CONCLUSION: The present meta-analysis demonstrated that the poor metabolizer phenotype of CYP2D6 confers a significant genetic susceptibility to PD in Caucasians, especially in British white subjects.
© 2013.

Entities:  

Keywords:  CYP2D6; Meta-analysis; Metabolizer; Parkinson's disease; Phenotypes; Polymorphisms

Mesh:

Substances:

Year:  2013        PMID: 24211060     DOI: 10.1016/j.jns.2013.10.030

Source DB:  PubMed          Journal:  J Neurol Sci        ISSN: 0022-510X            Impact factor:   3.181


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