Oncotarget

Meta-Analysis:

Relationship between mitochondrial DNA A10398G polymorphism and Parkinson’s disease: a meta-analysis

Feifei Hua, Xiaona Zhang, Binghui Hou, Li Xue and Anmu Xie _

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Oncotarget. 2017; 8:78023-78030. https://doi.org/10.18632/oncotarget.20920

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Abstract

Feifei Hua1, Xiaona Zhang1, Binghui Hou1, Li Xue2 and Anmu Xie1

1Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China

2Department of Rehabilitation, The Affiliated Hospital of Qingdao University, Qingdao, China

Correspondence to:

Anmu Xie, email: [email protected]

Keywords: Parkinson’s disease, mitochondrial DNA, gene polymorphism, meta-analysis

Received: July 21, 2017     Accepted: August 29, 2017     Published: September 15, 2017

ABSTRACT

Many studies have researched the mitochondrial DNA (mtDNA) A10398G in Parkinson’s disease (PD) to determine the association between mtDNA A10398G and PD, but the results of their research were not consistent. Therefore, we performed a meta-analysis to demonstrate the connection between mtDNA A10398G and the susceptibility of PD. We searched PubMed, Web of Science, Springer Link, EMBASE and EBSCO databases up to identify relevant studies. Through strict inclusion and exclusion criteria, at last, 9 studies (total 3381 cases and 2810 controls) were included in our meta-analysis. We used the STATA 12.0 statistics software to calculate the pooled odds ratios (ORs) and 95% confidence intervals (CIs) to evaluate the genetic association between mtDNA A10398G and the risk of PD. We performed subgroup analysis to clarify the possible roles of the mtDNA A10398G polymorphism in the aetiology of PD in different ethnicities. Our meta-analysis indicates that although there was no significant association between mtDNA A10398G and PD in the Asian population (G vs. A: OR = 1.090, 95% CI = 0.939–1.284, P = 0.242), in the Caucasian population the G allele of mtDNA A10398G mutations may be a potential protective factor of PD (G vs. A: OR = 0.699, 95% CI = 0.546–0.895, P = 0.005). Further well-designed studies with larger samples are needed to validate these results.


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