Red Meat Intake, Doneness, Polymorphisms in Genes that Encode Carcinogen-Metabolizing Enzymes, and Colorectal Cancer Risk

Colorectal cancer literature regarding the interaction between polymorphisms in carcinogen-metabolizing enzymes and red meat intake/doneness is inconsistent. A case-control study was conducted to evaluate the interaction between red meat consumption, doneness, and polymorphisms in carcinogen-metabolizing enzymes. Colorectal cancer cases diagnosed 1997 to 2000, ages 20 to 74 years, were identified through the population-based Ontario Cancer Registry and recruited by the Ontario Family Colorectal Cancer Registry. Controls were sex-matched and age group-matched random sample of Ontario population. Epidemiologic and food questionnaires were completed by 1,095 cases and 1,890 controls; blood was provided by 842 and 1,251, respectively. Multivariate logistic regression was used to obtain adjusted odds ratio (OR) estimates. Increased red meat intake was associated with increased colorectal cancer risk [OR (>5 versus <= 2 servings/wk), 1.67 (1.36-2.05)]. Colorectal cancer risk also increased significantly with well-done meat intake [OR (>2 servings/wk well-done versus <= 2 servings/wk rare-regular), 1.57 (1.27-1.93)]. We evaluated interactions between genetic variants in 15 enzymes involved in the metabolism of carcinogens in overcooked meat (cytochrome P450, glutathione S-transferase, UDP-glucuronosyltransferases, SULT, NAT, mEH, and AHR). CYP2C9 and NAT2 variants were associated with colorectal cancer risk. Red meat intake was associated with increased colorectal cancer risk regardless of genotypes; however, CYP1B1 combined variant and SULT1A1-638G>A variant significantly modified the association between red meat doneness intake and colorectal cancer risk. In conclusion, well-done red meat intake was associated with an increased risk of colorectal cancer regardless of carcinogen-metabolizing genotype, although our data suggest that persons with CYP1B1 and SULT1A1 variants had the highest colorectal cancer risk. (Cancer Epidemiol Biomarkers Prev 2008;17(11):3098-107)