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The associations between common SNPs of EFEMP1 gene and glioma risk in Chinese population

Authors Hu J, Dong D, Lu DD

Received 9 June 2017

Accepted for publication 14 September 2017

Published 6 November 2017 Volume 2017:10 Pages 5297—5302


Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Narasimha Reddy Parine

Peer reviewer comments 2

Editor who approved publication: Dr Yao Dai

Jun Hu,1 Dong Dong,2 Dandan Lu3

1Research Centre of Biomedical Technology Co., Ltd., Jiangsu Vocational College of Medicine, Yancheng, Jiangsu, 2Department of Pharmacy, Women and Infants Hospital of Zhengzhou, Zhengzhou, Henan, 3Department of Dermatology, The Third Hospital of Jinan, Jinan, Shandong, China

Background: Although the associations between common single nucleotide polymorphisms (SNPs) of EFEMP1 gene and glioma risk have been investigated in Chinese population-based case–control studies, investigation results for several SNPs are inconsistent. In addition, the single-center study has a poor statistical power due to finite sample size. Therefore, a meta-analysis was conducted to comprehensively determine the associations.
Methods: All eligible case–control studies were obtained by searching PubMed, EMBASE, Web of Science, and Chinese National Knowledge Infrastructure. Pooled odds ratio (OR) with 95% confidence interval (CI) was used to assess the strength of the associations in fixed- or random-effects model.
Results: EFEMP1 rs1346787 polymorphism was significantly associated with glioma risk in Chinese population under all genetic models (GG vs AA, OR =2.22, 95% CI =1.46–3.36; AG vs AA, OR =1.54, 95% CI =1.27–1.87; (GG+AG) vs AA, OR =1.60, 95% CI =1.34–1.93; GG vs (AG+AA), OR =1.86, 95% CI =1.24–2.78; G vs A, OR =1.54, 95% CI =1.32–1.79). However, the significant association of EFEMP1 rs1346786 with glioma risk in Chinese population was observed only under heterozygous model of AG vs AA (OR =1.34, 95% CI =1.10–1.62), dominant model of (GG+AG) vs AA (OR =1.36, 95% CI =1.13–1.63), and allelic model of G vs A (OR =1.28, 95% CI =1.10–1.50).
Conclusion: Our study demonstrated that EFEMP1 polymorphisms, especially rs1346787 and rs1346786, might predict glioma risk in Chinese population. However, high-quality case–control studies with larger sample sizes are warranted to confirm the above-mentioned findings.

Keywords: polymorphism, glioma, risk, meta-analysis

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