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. 2007;16(4):769-74).
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. 2007;16(4):769-74).
Authors: Kerryn W Reding; Noel S Weiss; Chu Chen; Christopher I Li; Christopher S Carlson; Hui-Wen Wilkerson; Federico M Farin; Kenneth E Thummel; Janet R Daling; Kathleen E Malone Journal: Cancer Epidemiol Biomarkers Prev Date: 2009-04-21 Impact factor: 4.254
Authors: Lori C Sakoda; Christie R Blackston; Kan Xue; Jennifer A Doherty; Roberta M Ray; Ming Gang Lin; Helge Stalsberg; Dao Li Gao; Ziding Feng; David B Thomas; Chu Chen Journal: Breast Cancer Res Treat Date: 2007-07-12 Impact factor: 4.872
Authors: Kathleen M McCarty; Regina M Santella; Susan E Steck; Rebecca J Cleveland; Jiyoung Ahn; Christine B Ambrosone; Kari North; Sharon K Sagiv; Sybil M Eng; Susan L Teitelbaum; Alfred I Neugut; Marilie D Gammon Journal: Environ Health Perspect Date: 2008-12-10 Impact factor: 9.031