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pubmed-article:21037224pubmed:abstractTextAssociations between bladder cancer risk and NAT2 and GSTM1 polymorphisms have emerged as some of the most consistent findings in the genetic epidemiology of common metabolic polymorphisms and cancer, but their interaction with tobacco use, intensity and duration remain unclear. In a New England population-based case-control study of urothelial carcinoma, we collected mouthwash samples from 1088 of 1171 cases (92.9%) and 1282 of 1418 controls (91.2%) for genotype analysis of GSTM1, GSTT1 and NAT2 polymorphisms. Odds ratios and 95% confidence intervals of bladder cancer among New England Bladder Cancer Study subjects with one or two inactive GSTM1 alleles (i.e. the 'null' genotype) were 1.26 (0.85-1.88) and 1.54 (1.05-2.25), respectively (P-trend = 0.008), compared with those with two active copies. GSTT1 inactive alleles were not associated with risk. NAT2 slow acetylation status was not associated with risk among never (1.04; 0.71-1.51), former (0.95; 0.75-1.20) or current smokers (1.33; 0.91-1.95); however, a relationship emerged when smoking intensity was evaluated. Among slow acetylators who ever smoked at least 40 cigarettes/day, risk was elevated among ever (1.82; 1.14-2.91, P-interaction = 0.07) and current heavy smokers (3.16; 1.22-8.19, P-interaction = 0.03) compared with rapid acetylators in each category; but was not observed at lower intensities. In contrast, the effect of GSTM1-null genotype was not greater among smokers, regardless of intensity. Meta-analysis of the NAT2 associations with bladder cancer showed a highly significant relationship. Findings from this large USA population-based study provided evidence that the NAT2 slow acetylation genotype interacts with tobacco smoking as a function of exposure intensity.lld:pubmed
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pubmed-article:21037224pubmed:articleTitleGSTM1 null and NAT2 slow acetylation genotypes, smoking intensity and bladder cancer risk: results from the New England bladder cancer study and NAT2 meta-analysis.lld:pubmed
pubmed-article:21037224pubmed:affiliationDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20852, USA. moorele@mail.nih.govlld:pubmed
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