Association between two CHRNA3 variants and susceptibility of lung cancer: a meta-analysis

Abstract

Genome-wide association studies (GWAS) have identified two CHRNA3 polymorphisms (rs578776 and rs938682) associated with lung cancer risk. Furthermore, these polymorphisms were investigated and genotyped by PCR analysis. All eligible case-control studies published up to Mar 1st 2015 were identified by searching Pubmed and Embase database. Negative association between rs578776-T allele and risk of lung cancer was obtained without obvious heterogeneity (OR: 0.83, 95% CI: 0.79-0.86; p = 0.898 for Q test). Rs938682-C allele carriers had a 12% to 28% decreased risk. Genotype model analysis showed results of dominant model for rs578776 (OR with 95% CI: 0.839(0.718-0.981)), dominant model for rs938682 (OR with 95% CI: 0.778(0.663-0.912)) and homozygous model for rs938682 (OR with 95% CI: 0.767(0.708-0.831)) were statistically significant. Subgroup analysis indicated rs578776-T variant had protective effect in Smokers, Caucasians, two histology subgroups, and two match subgroups. Meanwhile, rs938682-C allele was associated with decreased risk in Smokers, Caucasians, Lung cancer, and two match subgroups. Meta-regression suggested ethnicity might be the major source of heterogeneity in allele model and homozygous model for rs938682. Moreover, smoking status might contribute to part of heterogeneity under allele model. In summary, this meta-analysis suggested both rs578776 and rs938682 were significantly associated with the susceptibility of lung cancer.

Figure 1. The PRISMA processing map.

10 articles were finally included in the meta-analysis.

Figure 2. Forest plots of the association between each mutant allele and susceptibility of lung cancer.

For each SNP, the mutant allele could decrease (rs578776 and rs938682) the risk of lung cancer without high heterogeneity (Fig. 2A, OR: 0.83, 95% CI: 0.79–0.86, I² = 0.0% for rs578776; Fig. 2C, OR: 0.80, 95% CI: 0.72–0.88, I² = 47.9% for rs938682). Funnel plot for publication bias of two SNPs (rs578776, rs938682). Figure 2B,D showed all researches seemed no obvious asymmetry and had no significant publication bias. P values of Egger’s test for these two SNP were 0.334 and 0.167 respectively.

Figure 3. Meta-regression analysis.

Impact of ethnicity on the rs938682-C allele heterogeneity was shown in Fig. 3A. 100% between-study variance could be explained by ethnicity. Impact of ethnicity on the rs938682-CC genotype heterogeneity was shown in Fig. 3B. 59.67% variance could be explained by ethnicity. Impact of smoking status on the rs938682-C allele smoking subgroups was shown in Fig. 3C. 45.41% variance could be explained by the smoking status.