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Title: N-acetyltransferase 2 polymorphisms, tobacco smoking, and breast cancer risk in the breast and prostate cancer cohort consortium.
Authors: Cox DG,  Dostal L,  Hunter DJ,  Le Marchand L,  Hoover R,  Ziegler RG,  Thun MJ,  Breast and Prostate Cancer Cohort Consortium,  Diver WR,  Stevens VL,  Amiano P,  Boutron-Rualt MC,  Campa D,  van Duijnhoven FJ,  Gram IT,  Kaaks R,  Khaw KT,  Riboli E,  Sund M,  Trichopoulos D,  Tumino R,  Vogel U,  Kraft P,  Buring JE,  Hankinson SE,  Lee IM,  Zhang SM,  Lindstrom S,  Berg CD,  Chanock S,  Isaacs C,  McCarty C,  Haiman CA,  Henderson BE
Journal: Am J Epidemiol
Date: 2011 Dec 1
Branches: EBP
PubMed ID: 22074863
PMC ID: PMC3390163
Abstract: Common polymorphisms in the N-acetyltransferase 2 gene (NAT2) modify the association between cigarette smoking and bladder cancer and have been hypothesized to determine whether active cigarette smoking increases breast cancer risk. The authors sought to replicate the latter hypothesis in a prospective analysis of 6,900 breast cancer cases and 9,903 matched controls drawn from 6 cohorts (1989-2006) in the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium. Standardized methods were used to genotype the 3 most common polymorphisms that define NAT2 acetylation phenotype (rs1799930, rs1799931, and rs1801280). In unconditional logistic regression analyses, breast cancer risk was higher in women with more than 20 pack-years of active cigarette smoking than in never smokers (odds ratio (OR) = 1.28, 95% confidence interval (CI): 1.17, 1.39), after controlling for established risk factors other than alcohol consumption and physical inactivity. However, associations were similar for the slow (OR = 1.25, 95% CI: 1.11, 1.39) and rapid/intermediate (OR = 1.24, 95% CI: 1.08, 1.42) acetylation phenotypes, with no evidence of interaction (P = 0.87). These results provide some support for the hypothesis that long-term cigarette smoking may be causally associated with breast cancer risk but underscore the need for caution when interpreting sparse data on gene-environment interactions.