Lack of association between EGF + 61A>G polymorphism and melanoma susceptibility in Caucasians: A HuGE review and meta-analysis

Emerging evidence showed that the common polymorphism (+ 61A>G, rs4444903) in the promoter region of epidermal growth factor (EGF) gene might be associated with melanoma susceptibility in humans. But individually published results are inconclusive. The aim of this Human Genome Epidemiology (HuGE) review and meta-analysis is to derive a more precise estimation of the association between EGF + 61A>G polymorphism and melanoma risk. The PubMed, Embase, Web of Science and CBM databases were searched for all articles published up to July 1st, 2012. Seven case–control studies were included with a total of 2367 melanoma cases and 4184 healthy controls. Meta-analysis results showed that there was no significant relationship between EGF + 61A>G polymorphism and the risk of melanoma (G vs A: odds ratio [OR] = 1.08, 95% confidence interval [CI]: 0.91–1.28, P = 0.386; GG + AG vs AA: OR = 1.05, 95%CI: 0.88–1.26, P = 0.580; GG vs AA + AG: OR = 1.10, 95%CI: 0.81–1.49, P = 0.552; GG vs AA: OR = 1.06, 95%CI: 0.80–1.41, P = 0.700; GG vs AG: OR = 1.12, 95%CI: 0.81–1.56, P = 0.494). Further subgroup analyses based on source of controls, country, detection samples, genotype methods, and Breslow thickness of tumor, we also found no significant association between EGF + 61A>G polymorphism and melanoma risk. In conclusion, this meta-analysis indicates that EGF + 61A>G polymorphism might not be a primary determinant in melanoma development and progression; EGF gene might be expected to interact with other genes in different signaling pathways to initiate and promote the carcinogenic process.     

Paraoxonase 1 polymorphisms L55M and Q192R were not risk factors for Parkinson's disease: a HuGE review and meta-analysis

Purpose

The Paraoxonase 1 (PON1) has been studied as a potential candidate gene for Parkinson's disease risk, but direct evidence from genetic association studies remains inconclusive. We performed a meta-analysis pooling data from all relevant studies in order to determine the effects of two PON 1 polymorphisms (L55M and Q192R) on Parkinson's disease.

Methods

We applied a random effects to combine odds ratio (OR) and 95% confidence intervals. Q statistic was used to evaluate the homogeneity, and Egger's test and Funnel plot were used to assess publication bias. In secondary analyses, we examined dominant and recessive models as well.

Results

Concerning the PON1 L55M polymorphism, we identified 9 eligible studies (a total of 2582 cases and 3997 controls). The random effects pooled OR was OR = 1.29, (0.90, 1.84). Concerning the Q192R polymorphism, we identified 7 eligible studies (a total of 2582 cases and 3997 controls). The random effects pooled OR was OR = 1.08(0.81, 1.43). Analysis with dominant and recessive genetic models yielded the same inferences as genotype-based comparisons for both of the two polymorphisms.

Conclusion

The results of this meta-analysis suggested that both PON1 L55M and Q192R were not responsible for PD.     

EGF + 61A > G polymorphism and gastrointestinal cancer risk: A HuGE review and meta-analysis

Emerging evidences from preclinical and clinical studies have shown that epidermal growth factor (EGF) has some effectiveness against endogenously arising carcinogenesis. Functional + 61A > G polymorphism (rs4444903 A > G) in the promoter region of the EGF gene was observed to modulate EGF levels, thus affecting the susceptibility to gastrointestinal cancer; but individually published studies showed inconclusive results. The aim of this Human Genome Epidemiology (HuGE) review and meta-analysis was to derive a more precise estimation of the association between EGF + 61A > G polymorphism and gastrointestinal cancer risk. A literature search of Pubmed, Embase, Web of Science and Chinese BioMedical databases from inception through July 2012 was conducted. Twelve studies were assessed with a total of 2868 gastrointestinal cancer cases and 4278 healthy controls. When all the eligible studies were pooled into the meta-analysis, the results showed that the G allele and GG genotype of EGF + 61A > G polymorphism might increase the risk of gastrointestinal cancer. In the stratified analysis by cancer types, the G allele and GG genotype of EGF + 61A > G polymorphism showed displayed significant correlations with increased risk of esophageal cancer. We also found significant correlations between the G carrier (GG + AG) and GG genotype of EGF + 61A > G polymorphism and colorectal cancer risk. However, EGF + 61A > G polymorphism did not appear to have an influence on gastric cancer susceptibility. Results from the current meta-analysis indicate that EGF + 61A > G polymorphism might increase the risk of esophageal and colorectal cancers. Nevertheless, further studies are needed to determine whether genetic associations between EGF + 61A > G polymorphism and susceptibility to gastric cancer are significant.     

Functional polymorphisms in the interleukin-12 gene contribute to cancer risk: Evidence from a meta-analysis of 18 case–control studies

Background

Emerging evidence from preclinical and clinical studies has shown that interleukin-12 (IL-12) has some effectiveness against endogenously arising carcinogenesis. Several potentially functional polymorphisms of IL-12 gene have been implicated in cancer risk, but individually published studies showed inconclusive results. The aim of this study was to investigate the association between IL-12 polymorphisms and cancer risk.

Methods

The MEDLINE, EMBASE, Web of science and CBM databases were searched for all articles published up to June 10, 2012 that addressed IL-12 polymorphisms and cancer risk. Statistical analyses were performed using RevMan 5.1.6 and STATA 12.0 softwares.

Results

Eighteen studies were included with a total of 6463 cancer cases and 7412 healthy controls. We found that the 3'UTR A > C (rs3212227) polymorphism of IL-12B gene was associated with significantly increased overall risk of cancers using random effects model (C vs A: odds ratio [OR] = 1.14, 95% confidence interval [CI]: 1.02-1.27; AC + CC vs AA: OR = 1.20, 95%CI: 1.01-1.43). However, the 3'UTR G > A (rs568408), IVS2 T > A (rs582054) and 5'UTR T > G (rs2243115) polymorphisms of IL-12A gene did not appear to have an influence on cancer susceptibility. Further subgroup analyses showed that the 3'UTR A > C (rs3212227) polymorphism was associated with increased cancer risks in the subgroups of Asians, cervical and nasopharyngeal cancers.

Conclusions

Results from the current meta-analysis indicates that the 3'UTR A > C (rs3212227) polymorphism of IL-12B gene might be a potential biomarker for cancer risk among Asians, especially for cervical and nasopharyngeal cancers.     

Identification of susceptibility modules for coronary artery disease using a genome wide integrated network analysis

Although recent genome-wide association studies (GWAS) have identified a handful of variants with best significance for coronary artery disease (CAD), it remains a challenge to summarize the underlying biological information from the abundant genotyping data. Here, we propose an integrated network analysis that effectively combines GWAS genotyping dataset, protein–protein interaction (PPI) database, literature and pathway annotation information. This three-step approach was illustrated for a comprehensive network analysis of CAD as the following. First, a network was constructed from PPI database and CAD seed genes mined from the available literatures. Then, susceptibility network modules were captured from the results of gene-based association tests. Finally, susceptibility modules were annotated with potential mechanisms for CAD via the KEGG pathway database. Our network analysis identified four susceptibility modules for CAD including a complex module that consisted of 15 functional inter-connected sub-modules, AGPAT3–AGPAT4–PPAP2B module, ITGA11–ITGB1 module and EMCN–SELL module. MAPK10 and COL4A2 among the top-scored focal adhesion pathway related module were the most significant genes (MAPK10: OR = 32.5, P = 3.5 × 10^− 11; COL4A2: OR = 2.7, P = 2.8 × 10^− 10). The significance of the two genes were further validated by other two gene-based association tests (MAPK10: P = 0.009 and 0.007; COL4A2: P = 0.001 and 0.023) and another independent GWAS dataset (MAPK10: P = 0.001; COL4A2: P = 0.0004). Furthermore, 34 out of 44 previously reported CAD susceptibility genes were captured by our CAD PPI network and 17 of them were also significant genes. The susceptibility modules identified in our study might provide novel clues for the clarification of CAD pathogenesis in the future.