Association of 42 SNPs with genetic risk for cervical cancer: an extensive meta-analysis

BMC Med Genet. 2015 Apr 15:16:25. doi: 10.1186/s12881-015-0168-z.

Abstract

Background: A large number of single nucleotide polymorphisms (SNPs) associated with cervical cancer have been identified through candidate gene association studies and genome-wide association studies (GWAs). However, some studies have yielded different results for the same SNP. To obtain a more comprehensive understanding, we performed a meta-analysis on previously published case-control studies involving the SNPs associated with cervical cancer.

Methods: Electronic searches of PubMed and Embase were conducted for all publications about the association between gene polymorphisms and cervical cancer. One-hundred and sixty-seven association studies were included in our research. For each SNP, three models (the allele, dominant and recessive effect models) were adopted in the meta-analysis. For each model, the effect summary odds ratio (OR) and 95% CI were calculated. Heterogeneity between studies was evaluated by Cochran's Q test. If the p value of Q test was less than 0.01, a random effect model was used; otherwise, a fixed effect model was used.

Results: The results of our meta-analysis showed that: (1) There were 8, 2 and 8 SNPs that were significantly associated with cervical cancer (P < 0.01) in the allele, dominant and recessive effect models, respectively. (2) rs1048943 (CYP1A1 A4889G) showed the strongest association with cervical cancer in the allele effect model (1.83[1.57, 2.13]); in addition, rs1048943 (CYP1A1 A4889G) had a very strong association in the dominant and recessive effect model. (3) 15, 11 and 10 SNPs had high heterogeneity (P < 0.01) in the three models, respectively. (4) There was no published bias for most of the SNPs according to Egger's test (P < 0.01) and Funnel plot analysis. For some SNPs, their association with cervical cancer was only tested in a few studies and, therefore, might have been subjected to published bias. More studies on these loci are required.

Conclusion: Our meta-analysis provides a comprehensive evaluation of cervical cancer association studies.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alleles
  • Female
  • Genetic Predisposition to Disease / genetics*
  • Humans
  • Models, Statistical
  • Phenotype
  • Polymorphism, Single Nucleotide*
  • Uterine Cervical Neoplasms / genetics*