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Details

Autor(en) / Beteiligte
Titel
A Systematic Approach to Analysing Gene-Gene Interactions: Polymorphisms at the Microsomal Epoxide Hydrolase EPHX and Glutathione S-transferase GSTM1, GSTT1, and GSTP1 Loci and Breast Cancer Risk
Ist Teil von
  • Cancer epidemiology, biomarkers & prevention, 2007-04, Vol.16 (4), p.769-774
Ort / Verlag
Philadelphia, PA: American Association for Cancer Research
Erscheinungsjahr
2007
Link zum Volltext
Quelle
MEDLINE
Beschreibungen/Notizen
  • Objective: We undertook a case-control study in an Australian Caucasian population-based sample of 1,246 cases and 664 controls to assess the roles of detoxification gene polymorphisms EPHX T>C Tyr 113 His, GSTT1 deletion, GSTM1 deletion, and GSTP1 A>G Ile 105 Val on risk of breast cancer. Methods: We systematically addressed the main effects and possible gene-gene interactions using unconditional logistic regression to estimate odds ratios (OR) adjusted for potential confounders and using standard model building approaches based on likelihood theory. Results: There was a decreased risk associated with the EPHX CC genotype [OR, 0.60; 95% confidence interval (95% CI), 0.43-0.84; P = 0.003], marginally significant evidence of increased risk with GSTM1 null genotype (OR, 1.21; 95% CI, 1.00-1.47; P = 0.05), but no association with GSTT1 null genotype (OR, 1.12; 95% CI, 0.86-1.45; P = 0.4) or GSTP1 (OR, 0.95; 95% CI, 0.82-1.10; P = 0.5) genotype. The full model with all interactions gave a significantly better fit than a main-effects-only model ( P < 0.001), providing evidence for gene-gene interactions. The most parsimonious model included main effects for EPHX, GSTT1 , and GSTM1 ; a two-way interaction between EPHX and GSTM1 ; and a three-way interaction between EPHX, GSTM1 , and GSTT1 . Predicted risks were greatest for women carrying deletions of both GSTT1 and GSTM1 , with either the EPHX TC genotype (OR, 2.02; 95% CI, 1.19-3.45; P = 0.009) or EPHX CC genotype (OR, 3.54; 95% CI, 1.29-9.72; P = 0.14). Conclusion: Detoxification gene polymorphisms may interact with each other to result in small groups of individuals at modestly increased risk. We caution against overinterpretation and suggest that pooling of similarly large studies is needed to clarify the possible role of such complex gene-gene interactions on breast cancer risk. (Cancer Epidemiol Biomarkers Prev 2007;16(4):769–74)

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