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. 2013 Sep 15;8(26):2468-77.
doi: 10.3969/j.issn.1673-5374.2013.26.008.

Correlation between X-ray cross-complementing group 1 polymorphisms and the onset risk of glioma: A meta-analysis

Affiliations

Correlation between X-ray cross-complementing group 1 polymorphisms and the onset risk of glioma: A meta-analysis

Xinquan Gu et al. Neural Regen Res. .

Abstract

Objective: To evaluate the association of X-ray cross-complementing group 1 (XRCC1) Arg399Gln, Arg194Trp and Arg280His polymorphisms with the risk of glioma.

Data sources: A systematic literature search of papers published from January 2000 to August 2012 in PubMed, Embase, China National Knowledge Infrastructure database, and Wanfang database was performed. The key words used were "glioma", "polymorphism", and "XRCC1 or X-ray repair cross-complementing group 1". References cited in the retrieved articles were screened manually to identify additional eligible studies.

Study selection: STUDIES WERE IDENTIFIED ACCORDING TO THE FOLLOWING INCLUSION CRITERIA: case-control design was based on unrelated individuals; and genotype frequency was available to estimate an odds ratio (OR) and 95% confidence interval (CI). Meta-analysis was performed for the selected studies after strict screening. Dominant and recessive genetic models were used and the relationship between homozygous mutant genotype frequencies and mutant gene frequency and glioma incidence was investigated. We chose the fixed or random effect model according to the heterogeneity to calculate OR and 95%CI, and sensitivity analyses were conducted. Publication bias was examined using the inverted funnel plot and the Egger's test using Stata 12.0 software.

Main outcome measures: Association of XRCC1 Arg399Gln, Arg194Trp, and Arg280His polymorphisms with the risk of glioma, and subgroup analyses were performed according to different ethnicities of the subjects.

Results: Twelve articles were included in the meta-analysis. Eleven of the articles were concerned with the Arg399Gln polymorphism and glioma onset risk. Significantly increased glioma risks were found only in the dominant model (Gln/Gln + Gln/Arg versus Arg/Arg: OR = 1.26, 95%CI = 1.03-1.54, P = 0.02). In the subgroup analysis by ethnicity, significantly increased risk was found in Asian subjects in the recessive (OR = 1.46, 95%CI = 1.04-2.45, P = 0.03) and dominant models (OR = 1.40, 95%CI = 1.10-1.78, P = 0.007), and homozygote contrast (OR = 1.69, 95%CI = 1.17-2.45, P = 0.005), but not in Caucasian subjects. For association of the Arg194Trp (eight studies) and Arg280His (four studies) polymorphisms with glioma risk, the meta-analysis did not reveal a significant effect in the allele contrast, the recessive genetic model, the dominant genetic model, or homozygote contrast.

Conclusion: The XRCC1 Arg399Gln polymorphism may be a biomarker of glioma susceptibility, especially in Asian populations. The Arg194Trp and Arg280His polymorphisms were not associated with overall glioma risk.

Keywords: X-ray cross-complementing group 1; gene mutation; gene polymorphism; glioma; grants-supported paper; meta-analysis; neural regeneration; neuroregeneration; onset risk; susceptibility.

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Conflict of interest statement

Conflicts of interest: None declared.

Figures

Figure 1
Figure 1
Flow diagram showing the selection process for the articles used in this study.
Figure 2
Figure 2
Forest plot of overall glioma risk associated with the XRCC1 Arg399Gln polymorphism (Gln/Gln + Gln/Arg versus Arg/Arg) for different ethnicities. M-H: Mantel-Haenszel.
Figure 3
Figure 3
Forest plot of overall glioma risk associated with the XRCC1 Arg194Trp polymorphism (Trp/Trp + Trp/Arg versus Arg/Arg) for different ethnicities. M-H: Mantel-Haenszel.
Figure 4
Figure 4
Forest plot of overall glioma risk associated with the XRCC1 Arg280His polymorphism (His/His + Arg/His versus Arg/Arg) for different ethnicities. M-H: Mantel-Haenszel.
Figure 5
Figure 5
Publication bias for XRCC1 Arg399Gln under the dominant model (Gln/Gln + Gln/Arg versus Arg/Arg) detected by Begg's Funnel plot analysis. SE: Standard error of mean.

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