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Carcinogenesis Advance Access originally published online on August 21, 2006
Carcinogenesis 2007 28(2):328-341; doi:10.1093/carcin/bgl135
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Inherited variation in carcinogen-metabolizing enzymes and risk of colorectal polyps

Ellen L. Goode1,2,3,*, John D. Potter1,2, William R. Bamlet3, David N. Rider3 and Jeannette Bigler1

1 Cancer Prevention Program, Fred Hutchinson Cancer Research Center Seattle, WA, USA
2 Department of Epidemiology, University of Washington Seattle, WA, USA
3 Department of Health Sciences Research, Mayo Clinic College of Medicine Rochester, MN, USA

*To whom correspondence should be addressed at: Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA. Tel: +1 507 266 7997; Fax: +1 507 266 2478; Email: egoode{at}mayo.edu


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 Supplementary material
 References
 
Exposures such as cigarette smoke and meat contain a variety of procarcinogens, which are thought to play a role in elevation of risk for colorectal polyps and/or cancer. These procarcinogens (including heterocyclic amines and polycyclic aromatic hydrocarbons) are metabolized by a variety of polymorphic enzymes including N-acetyltransferases, sulfotransferases, cytochrome P450 enzymes and epoxide hydrolase. We hypothesized that genetic variation in the encoding genes NAT1, NAT2, SULT1A1, SULT1A2, CYP1A1 or EPHX1 is associated with risk of colorectal polyps and interacts with cigarette use or meat intake to modify risk of colorectal polyps. We examined the role of these genes in a clinic-based study of 651 Caucasian cases with hyperplastic polyps, adenomatous polyps or both types of polyps and 556 polyp-free controls. We found evidence for interaction between NAT acetylator status and SULT1A1 genotype in risk of hyperplastic polyps: individuals with SULT1A1 638AA genotype and NAT1 and NAT2 intermediate/fast phenotypes had 3.5-fold increased risk (95% CI 1.2–10.3) compared with individuals with SULT1A1 638GG genotype and NAT1 and NAT2 slow phenotypes. Data were also consistent with interactions between smoking and variation in SULT1A1, CYP1A1 and EPHX1 and between meat intake and variation in CYP1A1 and EPHX1. No interactions were statistically significant. Although results should be interpreted with caution considering sample size and the number of hypotheses examined, our study suggests future avenues of investigation in larger investigations of genetic and lifestyle factors in the pathway to colorectal cancer.

Abbreviations: AAs, aromatic amines; CYPs, cytochrome P450 enzymes; FAP, familial adenomatous polyposis; HAs, heterocyclic amines; LD, linkage disequilibrium; MAFs, minor allele frequencies; NSAIDs, non-steroidal anti-inflammatory drugs; PAHs, polycyclic aromatic hydrocarbons; SNPs, single nucleotide polymorphisms; SULTs, sulfotransferases


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 Supplementary material
 References
 
Risk of colorectal polyps and cancer is thought to be due to a complex interplay of environmental and genetic factors. Known environmental carcinogens include polycyclic aromatic hydrocarbons (PAHs), aromatic amines (AAs), heterocyclic amines (HAs) and nitrosamines (NAs). These compounds can be found in tobacco smoke, cooked meat, coal, petroleum products and motor vehicle exhaust. Exposure to these agents has been associated with an increased incidence of colorectal cancer in humans [for reviews see (1–4)]. In addition, evidence from rat models indicates that HAs cause APC mutations (5), and duration of smoking appears related to MSI status of colorectal cancers (6).

Tobacco smoking and meat intake are lifestyle factors responsible for a major portion of exposure to these carcinogens, particularly HAs, PAHs and NAs. Although early studies were inconsistent, substantial evidence has now accumulated showing cigarette smoking, particularly early-onset, long-duration smoking, as a risk factor for colorectal cancer and its precursors (7). High intake of meat, particularly red meat and, to a lesser extent, meat cooked at high temperatures, has been found to be a risk factor for colorectal cancer and its precursors in many studies (8–10), possibly due to benzo(a)pyrene content (11) or the formation of N-nitrosocompounds (12); some studies, however, show no association (13).

Metabolic activation of the compounds found in tobacco smoke and meat is required for the formation of a carcinogenic or mutagenic compound (Figure 1). Phase I enzymes, including arylamine-N-acetyltransferases (NATs), sulfotransferases (SULTs), cytochrome P450 enzymes (CYPs) and microsomal epoxide hydrolase (mEH), can catalyze the activation of these compounds to electrophilic and nucleophilic intermediates leading to DNA adducts, apurinic sites and oxidative damage [for review see (14)]. NAT1 and NAT2 can activate N-hydroxylated HAs by O-acetylation or detoxify carcinogenic arylamines through N-acetylation (15). Members of the cytosolic SULT family catalyze sulfate conjugation of a variety of xenobiotics and endogenous small molecules leading to the bioactivation of dietary and environmental HAs and PAHs (16) as well as detoxification of many drugs and the metabolism of catecholestrogens (17). CYP1A1 is a major phase I enzyme in the activation of PAHs although it is not expressed in the liver in great quantities (18–20). It is regulated by the aryl hydrocarbon receptor which is activated by PAHs, halogenated hydrocarbons such as 2,3,7,8-tetrachlorodibenzo-p-dioxin, and dietary substances such as bioflavonoids (21). mEH hydrolyzes epoxides and has a broad substrate specificity including PAHs which may result in detoxified or more highly toxic compounds (22).


Figure 1
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  		Fig. 1 Involvement of select enzymes in carcinogen metabolism.

 
We hypothesized that variation in the genes encoding these carcinogen-metabolizing enzymes is associated with risk of colorectal polyps and interacts with tobacco and meat exposure. We selected putatively functional polymorphisms from reviews of the epidemiologic and pharmacogenetic literature. NAT1 and NAT2 polymorphisms may cause altered enzyme activities, resulting in considerable interindividual variation in acetylation (15,23). SULT1A1 enzymatic activity and thermal stability have been shown to be related to SULT1A1 genotype and possibly to altered expression (24). SULT1A2 has similar substrate specificities as SULT1A1, and studies with recombinant protein suggest that the enzyme encoded by the minor allele at SULT1A2 706A>C has a substantially higher Km than the major allele for the substrate 4-nitrophenol (25,26). We note, however, that because only SULT1A2 mRNA, but not protein, has been found in human tissues, the functional significance of SULT1A2 in vitro data is unclear (27,28). The 4889A>G (I462V) polymorphism in CYP1A1 is thought to encode an enzyme with enhanced activity (29–32). Non-synonymous polymorphisms in EPHX1(encoding mEH) have been associated with altered expression levels (33,34), although not consistently (22). Consideration of multiple polymorphisms in NAT1, NAT2, SULT1A1, SULT1A2, CYP1A1 and EPHX1 enables haplotype analysis allowing for linkage disequilibrium (LD) between typed polymorphisms and an untyped causal polymorphism. For NAT1 and NAT2, haplotype analysis may reduce misclassification when acetylation phenotype is incorrectly assigned based on assumed linkage phase (35,36).

We have shown previously that individuals with colorectal polyps may best be classified into three distinct groups (i: those with hyperplastic polyps only; ii: those with both adenomatous and hyperplastic polyps; and iii: those with adenomatous polyps only) because each group has unique risk-factor profiles, particularly with regard to carcinogenic exposures (37). In a clinic-based study of these three case groups and polyp-free controls, we now examine genotype, haplotype and imputed phenotype associations with polyp risk, taking into account the role of complex environmental sources of the relevant carcinogens. We note that some of the data presented here have been previously analyzed using a grouped phenotype with individuals having both adenomatous and hyperplastic polyps combined with individuals having adenomatous polyps only. First, we previously reported no evidence of association between NAT2 phenotype and polyp risk and no evidence of interaction with smoking (38). Second, we reported evidence for interaction between EPHX1 polymorphisms and exposure to smoking and cooked meat in relation to polyp risk (39). Our current aim is to extend these analyses with additional analytical methods, more precise case definitions, and data from additional genes in a comprehensive assessment of genetic variation in carcinogen metabolism and colorectal polyp risk.


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 Supplementary material
 References
 
Study population
This case–control study recruited participants between April 1991 and April 1994 as part of the Minnesota Cancer Prevention Research Unit, an NCI-funded program project that combined several units within the University of Minnesota and Digestive Healthcare (DH), a large multiclinic private gastroenterology practice (40). Briefly, patients aged 30–74 who were scheduled for a colonoscopy and found to have adenomatous and/or hyperplastic polyps or to be polyp-free were recruited into the study, and written informed consent was obtained. Patients were recruited prior to their procedure so as to blind patients and recruiters to the final polyp diagnosis. Based on the colonoscopy and pathology findings using standard diagnostic criteria (41), participants were assigned to four groups: (i) hyperplastic polyps only; (ii) hyperplastic and adenomatous polyps; (iii) adenomatous polyps only; and (iv) polyp-free controls. Patients for whom the colonoscopy did not reach the cecum, patients with previous ulcerative colitis, Crohn's disease, polyps or cancer (except non-melanoma skin cancer), and patients with known genetic syndromes, familial adenomatous polyposis (FAP) or hereditary non-polyposis colon cancer, were ineligible (40).

Information on lifestyle factors, diet, anthropometry, demographics, use of aspirin and non-steroidal anti-inflammatory drugs (NSAIDs), and medical information, including family history of cancer and polyps, was obtained by questionnaire. The dietary questionnaire used was an adaptation of the Willett food-frequency questionnaire, which has been studied previously for validity and repeatability (42). A variety of different meat, fish and chicken dishes were listed and possible responses ranged from ‘never or less than once per month’ to ‘six or more times a day’. The participation rate for all colonoscoped individuals was 68%. The study was approved by the Institutional Review Boards (IRBs) of the University of Minnesota and each colonoscopy site.

The current analysis was limited to 1207 Caucasian study participants (556 controls, 174 participants with hyperplastic polyps only, 109 participants with hyperplastic and adenomatous polyps, and 368 participants with adenomatous polyps only) with questionnaire data and genotypes available for all the polymorphisms presented here. The activities associated with the present study were approved by the IRB of the Fred Hutchinson Cancer Research Center.

Nomenclature
Nineteen studied polymorphisms, including eighteen single nucleotide polymorphisms (SNPs) and one deletion polymorphism, in six carcinogen-metabolizing genes (NAT1, NAT2, SULT1A1, SULT1A2, CYP1A1 and EPHX1) are described in Table I. As mentioned above, polymorphisms were chosen on the basis of putative function and previously reported associations. For consistency across polymorphisms, each polymorphism is represented in this text by its gene position and nucleotide change. Haplotypes for each gene and for NAT1–NAT2 and SULT1A1–SULT1A2 gene combinations are represented in this text as strings of ‘0’s and ‘1’s with ‘0’ indicating the major allele and ‘1’ indicating the minor allele for polymorphisms from 5' to 3'; multigene haplotypes include ‘–’ to separate genes. Haplotypes for some genes have also been traditionally assigned ‘allele’ or ‘allozyme’ designations. Supplementary Table S1 provides the cross-classification of haplotypes based on polymorphisms currently analyzed, their possible ‘allele’ or ‘allozyme’ designations, and putative functional effects.


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  		Table I Characteristics of polymorphisms in carcinogen-metabolizing genes among 556 Caucasian polyp-free controls

 
Genotyping
Assays used genomic DNA extracted from peripheral white blood cells with a Puregene kit (Gentra Systems, Minneapolis, MN). As outlined in Supplementary Table S2 and described previously (38,39,43), genotypes were determined using oligonucleotide ligation assays (NAT1 190C>T, 559C>T and 560G>A; NAT2 191G>A, 341T>C, 590G>A, 803A>G and 857G>A; CYP1A1 4887A>C and 4889A>G; EPHX1 337T>C), allele-specific amplification [NAT1 1065_1073del(TAA)3 and 1088T>A and 1095C>A], restriction fragment length polymorphism assays (SULT1A1 638G>A; CYP1A1 6235T>C; EPHX1 415T>C) and Taqman fluorescent 5' endonuclease assays (SULT1A2 56C>T and 706A>C). Eight percent of samples were duplicated for each polymorphism and were found to be 100% concordant. Additional details on genotyping are available upon request.

NAT phenotype imputation
NAT1 and NAT2 phenotypes were imputed in the traditional manner by predicting the most likely chromosomal phase, assigning fast acetylator status to certain ‘alleles’ or ‘allozymes’ based on function literature (see Supplementary Table S1), and assuming a codominant effect on acetylator phenotype leading to fast, intermediate and slow acetylator phenotypes. Classification and distribution of NAT1 and NAT2 genotypes, presumed ‘alleles’ or ‘allozymes’, and imputed phenotypes are provided in Supplementary Table S3.

Statistical analysis
The extent of LD between two alleles was quantified as Lewontin's D' and r2 calculated with LDMAX (44) based on expectation-maximization (EM) algorithm estimation of haplotype frequencies (45). For two biallelic polymorphisms with alleles A or a and B or b, respectively, D represents the difference between observed and expected haplotype frequencies (D = PAB – PAPB). D' normalizes D such that it ranges from –1 to 1 and if D' > 0, D' = (PAB – PAPB)/min(PAb, PaB), and if D < 0, D' = (PAB – PAPB)/min(Pab, PAB) (46). If D' equals –1.0, no chromosomes are observed with both tested alleles and if D' equals +1.0, one of the tested alleles occurs only on the same chromosome as the other tested allele. r2, also known as {Delta}2, is more robust to variation in allele frequencies and is calculated as r2 = (PAB – PAPB)2/(PAPaPBPb) (46). r2 is equivalent to the Pearson product–moment correlation and ranges from 0 to <1 if the minor allele frequencies (MAFs) differ between polymorphisms (47,48). If MAFs are very low, D' may equal –1.0 even if LD is not present; r2 may more accurately reflect the extent of LD. {chi}2 testing assessed statistical significance of LD.

Maximum-likelihood multinomial logistic (polytomous) regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for risk of belonging to each of three distinct colorectal polyp groups: hyperplastic polyps only, phenotype including both hyperplastic and adenomatous polyps, and adenomatous polyps only. For consistency, the following characteristics were included in all regression models after assessment for confounding: age, sex, hormone therapy (women only; ever/never), body mass index, pack-years of smoking, regular use of NSAIDs (one or more per week) and total meat intake. Likelihood ratio tests assessed gene–environment interaction within case groups (comparison of models with and without interaction terms) and heterogeneity across case groups (comparison of models with constrained and unconstrained ORs).

Haplotype-based logistic regression analysis with HPlus v 2.0 (49,50) used EM algorithm likelihood formulation for haplotype frequency estimation (45) and estimating-equation techniques for standard error estimation (49). Haplotype-specific ORs and 95% CIs were calculated using weighted sums of each individual's haplotype probabilities and relevant covariates (50). The most common haplotype was used as referent group; ORs were not calculated for rare haplotypes (estimated n < 10). This approach is advantageous in that it simultaneously estimates haplotype frequencies and relative risks, provides haplotype-specific risk estimates, and permits inclusion of covariates and interaction terms (50).


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 Supplementary material
 References
 
We assessed whether 19 putatively functional variants in six carcinogen-metabolizing genes were associated with colo-rectal polyps (hyperplastic only; hyperplastic and adenomatous polyp types; adenomatous only) and whether associations varied by smoking status or meat intake. Demographic characteristics for study participants have been reported previously (37,38); distributions of risk factors did not differ in the slightly reduced dataset used here (individuals missing genotypes were excluded). Briefly, controls (n = 566) were more likely to be women, never smokers, NSAID users and post-menopausal hormone therapy users (women only) than any of the polyp case groups (hyperplastic polyps, n = 174; both hyperplastic and adenomatous polyps, n = 109; and adenomatous polyps, n = 368). LD was observed between NAT1 and NAT2 alleles, between SULT1A1 and SULT1A2 alleles, and between CYP1A1 alleles (Table I).

Risk of colorectal polyps
Risks of colorectal polyps associated with haplotypes and polymorphisms are shown in Table II and Supplementary Table S4, respectively. For all genotypes and phenotypes, no significant heterogeneity across polyp groups was seen.


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  		Table II Haplotypes of carcinogen-metabolizing genes and risk of colorectal polyps

 
No associations between polyp risk and NAT1 or NAT2 genotypes were observed (Supplementary Table S4). NAT1 haplotype analysis revealed elevated but non-significantly increased risk of hyperplastic polyps associated with the ‘000101’ haplotype [minor allele at 1065_1073del(TAA)3 and 1095C>A only] and risk of having both polyp types associated with the ‘001011’ haplotype (minor allele at 560G>A, 1088T>A and 1095C>A) compared with the ‘000000’ haplotype (Table II). NAT2 haplotype analysis comparing the most common ‘01010’ haplotype (minor allele at 341T>C and 803A>G) with the ‘01000’ haplotype (minor allele at 341T>C only) was consistent with non-significantly increased risk of hyperplastic polyps associated with the minor allele at 803A>G. Haplotype analysis including both genes (~170 kb) did not reveal a consistent association with polyp risk (Table II). However, increased risk for hyperplastic polyps was suggested for the ‘000001-00000’ haplotype (minor allele at NAT1 1095C>A only) compared with the most common ‘000000-01010’ haplotype (minor alleles at NAT2 341T>C and NAT2 803A>G) (OR 2.1; 95% CI 1.0–4.5) (Table II). Although NAT2 imputed phenotype analysis suggested increased risk with fast acetylator status and risk of having both polyp types, analysis of NAT1 imputed phenotypes and combined analysis of NAT1 and NAT2 imputed phenotypes did not reveal associations with any polyp group (Table III).


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  		Table III Imputed phenotypes and risk of colorectal polyps

 
SULT1A1 and SULT1A2 haplotype analysis considering both genes (~10 kb) did not reveal associations with any polyp group (Table II), although we observed an OR for adenomatous polyps of 4.7 (95% CI 1.6–13.6) for the rare ‘1-00’ haplotype compared with the ‘0-00’ haplotype. Analysis of minor alleles at SULT1A1 638G>A and SULT1A2 706A>C (r2 = 0.85) revealed modestly, but statistically non-significantly increased risks for hyperplastic polyps (Supplementary Table S4). An interaction between NAT1 and NAT2 phenotype and SULT1A1 genotypes was suggested in relation to risk of hyperplastic polyps (Table IV); individuals with SULT1A1 638AA genotype and NAT1 intermediate/fast phenotype had 2-fold increased risk (95% CI 0.9–4.8) compared with individuals with SULT1A1 638GG genotype and NAT1 slow phenotype; individuals with SULT1A1 638AA genotype and NAT2 intermediate/fast phenotype were at a 2.2-fold increased risk of hyperplastic polyps (95% CI 1.0–4.7) compared with individuals with SULT1A1 638GG genotype and NAT2 slow phenotype. Combining NAT1 and NAT2 phenotype, individuals with SULT1A1 638AA genotype and NAT1 and NAT2 intermediate/fast phenotypes had 3.5-fold increased risk (95% CI 1.2–10.3) compared with individuals with SULT1A1 638GG genotype and NAT1 and NAT2 slow phenotypes. We note that results with SULT1A2 706A>C were similar (as expected due to LD) but that no SULT–NAT interaction terms were statistically significant.


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  		Table IV Multigene combinations and risk of colorectal polyps

 
CYP1A1 haplotype analysis did not reveal statistically significant associations with any polyp group (Table II). A modestly increased risk of both polyp types was observed with the ‘001’ haplotype (6235T>C only) compared with ‘000’ haplotype (OR 1.3; 95% CI 0.7–2.5) (Table II) consistent with a 4.6-fold increased risk for having both polyp types seen in genotype analysis comparing 6235CC with TT (95% CI 1.0–21.8) (Supplementary Table S4); however, this analysis is based on a small number of individuals. No other CYP1A1 genotype associations were suggested.

EPHX1 haplotype analysis suggested a modestly increased risk of both polyp types with the ‘10’ haplotype (minor allele at 337T>C only) compared with the ‘00’ haplotype (OR 1.4; 95% CI 0.9–2.2; Table II), consistent with genotype analysis at 337T>C and both polyps types (Supplementary Table S4): TC versus TT OR 1.6 95% CI 1.0–2.5, CC versus TT OR 1.8 95% CI 0.8–4.0 (39). Because of the plausibility of interaction between EPHX1 and CYP1A1 genotypes (51), we assessed evidence of effect modification in risk of colorectal polyps and found no evidence for interaction (Table IV).

Interactions with smoking and risk of colorectal polyps
Because of the involvement of these genes in metabolism of carcinogens in tobacco smoke, we assessed whether genetic variation interacted with smoking status in risk of colorectal polyps. The current analysis is consistent with previously reported associations between smoking status and increased risk of hyperplastic polyps [current versus never (OR 4.1; 95% CI 2.2–7.6) and having both polyp types (OR 6.1; 95% CI 2.8–13.5)], and lack of association with risk of adenomas only (OR 1.3; 95% CI 0.8–2.3) (37). For all genotypes and phenotypes, no statistically significant heterogeneity across polyp groups was seen, and no statistically significant interactions with smoking status were detected.

Analysis of NAT1 genotypes, haplotypes and phenotypes did not reveal evidence of interaction with smoking status (never/former/current) (Table V) or pack-years smoked (data not shown). The number of currently smoking fast acetylators was very small. Our current NAT2 analysis of three case groups is consistent with previously reported analysis of two case groups (those with both polyp types included with the adenoma-only group) (38). Results suggest that NAT2 acetylator status is most relevant for risk of each polyp group (hyperplastic only, both hyperplastic and adenomatous, adenomatous only) among current smokers (Table V). Combined analysis of NAT1 and NAT2 imputed phenotypes and smoking status suggested that current smokers with imputed intermediate or fast acetylator phenotypes at both enzymes were at increased risk for adenomatous polyps only (OR 2.4; 95% CI 1.1–5.4). Haplotype analysis across NAT1 and NAT2 was inconclusive.


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  		Table V Smoking status, selected genotypes, haplotypes, and phenotypes and risk of colorectal polyps

 
An interaction between SULT1A1 and smoking status was suggested, such that among current smokers only SULT1A1 638G>A genotype was associated with risk of hyperplastic polyps and of both types of polyps (Table V). Results were similar when considering pack-years of smoking and for SULT1A2 706A>C as expected owing to LD. Combined SULT1A1–SULT1A2 haplotype analyses were consistent with this result, suggesting that haplotype was associated with risk of hyperplastic polyps and of both types of polyps only among current smokers. The ‘1-01’ haplotype (minor alleles at SULT1A1 638G>A and SULT1A2 706A>C) was associated with 1.8-fold (95% CI 1.0–2.9) increased risk for hyperplastic polyps and with 2.5-fold (95% CI 1.2–5.2) increased risk for having both types of polyps among current smokers (Table V).

Though based on small numbers, risk associated with the ‘001’ CYP1A1 haplotype (*2A, minor allele at 6235T>C only) versus ‘000’ CYP1A1 haplotype (*1A) appeared increased among never/former smokers compared with current smokers for cases with both polyp types [never/former smokers (OR 1.7; 95% CI 0.9–3.5) and current smokers (OR 0.7; 95% CI 0.2–3.0)] and for cases with adenomatous polyps only [never/former smokers (OR 1.2; 95% CI 0.8–2.0) and current smokers (OR 0.6; 95% CI 0.2–2.1)] (Table V).

Analysis of EPHX1 haplotypes showed that, among current smokers only, the ‘11’ haplotype (minor alleles at 337T>C and 415A>G) was associated with a 6.1-fold (95% CI 1.0–35.3) increased risk of both types of polyps and with a statistically non-significant 1.9-fold (95% CI 0.6–6.4) increased risk of adenomatous polyps only. As reported previously (39), consistent results were seen with pack-years of smoking. Increased risks for both polyp types were also suggested for the ‘10’ haplotype, consistent with 337T>C driving the result; however, the number of participants is too small to be conclusive.

Interactions with meat intake and risk of colorectal polyps
We also hypothesized that intake of fried, broiled or baked meat may interact with inherited variation in carcinogen-metabolizing genes in influencing colorectal polyp risk. Results consistent with previous reports were seen for weekly frequency of eating fried, broiled, baked meat and risk of having hyperplastic polyps [5/week or more versus <5/week (OR 1.4; 95% CI 0.7–2.6)], both hyperplastic and adenomatous polyps (OR 1.7; 95% CI 1.0–3.0), and adenomas only (OR 1.4; 95% CI 0.9–2.3) (37). For all genotypes and phenotypes, no statistically significant heterogeneity across polyp groups was seen, and no statistically significant interactions with frequency of fried, broiled, baked meat, doneness or red meat intake were detected.

Analysis of NAT1 or NAT2 genotypes, haplotypes and phenotypes did not reveal evidence of interaction with meat intake (fried, broiled, baked meat ≤4 serving per week; 5 or more serving per week) (Table VI) or with meat doneness or intake of red meat (data not shown).


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  		Table VI Meat intake, selected genotypes, haplotypes, and phenotypes and risk of colorectal polyps

 
An interaction between SULT1A1 and meat intake was suggested, such that among individuals consuming five or more servings per week of fried, broiled or baked meat, SULT1A1 638G>A AA genotype was associated with risk of both types of polyps (Table VI). However, the number of minor allele homozygotes was small. Results were similar for SULT1A2 706A>C as expected owing to LD between these minor alleles. Combined SULT1A1–SULT1A2 haplotype analyses suggested differences in ‘0-01’ haplotype (minor allele at SULT1A2 706A>C) risk estimates across the two meat intake groups for both polyp types and for adenomatous polyps only; however, trends were based on small numbers and not consistent with genotype results.

Though based on small numbers, risk associated with the ‘100’ CYP1A1 haplotype (*4, minor allele at 4887A>C only) versus ‘000’ haplotype (*1A) appeared increased among individuals consuming four or fewer servings per week of fried, broiled or baked meat for adenomatous cases (OR 2.4; 95% CI 0.9–6.8) and decreased among individuals who eat five or more servings per week (OR 0.4; 95% CI 0.1–1.5) (Table VI). No other trends toward interaction between CYP1A1 and meat intake were suggested.

Consistent with previous analyses which found risk of adenomatous polyps with or without hyperplastic polyps associated with EPHX1 genotypes to vary by intake of meat (39), EPHX1 337T>C analysis yielded higher risk estimates among individuals consuming five or more servings per week of fried, broiled or baked meat for adenomatous polyps [CC versus TT (OR 2.2; 95% CI 0.9–5.4)] and for both polyp types [CC versus TT (OR 3.8; 95% CI 1.1–12.7)] compared with individuals with TT genotype consuming fewer servings per week. EPHX1 haplotype analyses were inconclusive (Table VI).


   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
Supplementary material
 References
 
In a clinic-based study of individuals with and without colorectal polyps, we assessed evidence of association between six carcinogen-metabolizing genes (NAT1, NAT2, SULT1A1, SULT1A2, CYP1A1 or EPHX1) and risk of adenomatous polyps, hyperplastic polyps and a phenotype including both polyp types. We studied 19 polymorphisms chosen on the basis of putative function, and we combined polymorphism data within genes and gene regions as haplotypes and imputed phenotypes where possible. We found evidence for interaction between NAT acetylator status and SULT1A1 genotype in modifying risk of hyperplastic polyps. Because of the suspected role of smoking and meat in colorectal carcinogenesis and the known role of the selected genes in metabolism of carcinogenic compounds found in these exposures, we also explored relevant interactions. We observed a suggestion of interaction between smoking and SULT1A1, CYP1A1 and EPHX1, and between meat intake and CYP1A1 and EPHX1. No interactions were statistically significant. Strengths of our approach include a focus on homogeneous polyp phenotypes, the consideration of multiple genes and exposures, and the use of comprehensive analytical tools. However, our results should be interpreted with caution considering the modest sample size (651 cases combined, 556 controls) and the number of hypotheses examined.

Previous studies of NAT1 have been inconsistent finding no association with adenomas (52,53) or cancer (54), or suggesting increased risk of colon cancer associated with the fast acetylator phenotype (55), possibly in the presence of meat intake (56). Slow NAT1 phenotypes have been recently associated with increased FAP severity (57). Our analysis did not reveal a major role for NAT1 in polyp risk.

Recent population genetics analyses found evidence for a selective advantage of the NAT2 *5B allele (341T>C minor allele only, slow acetylator), which has been implicated in cancer susceptibility and adverse drug reactions (36). The role of NAT2 in colorectal carcinogenesis has been frequently studied, finding increased colorectal cancer risk among fast NAT2 phenotypes (58,59) or no association (52,60–65). A meta-analysis of 42 studies found modestly elevated colon cancer risk among fast acetylators (66). Some reports suggest increased colon cancer risk among smoking slow acetylators (67); increased colon cancer risk among fast acetylators exposed to environmental tobacco smoke (56) or higher intakes of meat (56,68). However, some studies of interactions do not find evidence of effect modification (61). Colorectal adenoma studies have also been inconsistent, finding evidence for increased risk among smoking fast acetylators (69), smoking slow acetylators (53) or slow acetylators with higher meat intake (70). Fast NAT2 phenotypes have also been recently associated with increased FAP severity (57). Our data indicate that NAT2 genotypes, phenotypes and haplotypes do not play a large role in the polyp risk, although fast acetylation may lead to increased polyp risk in the presence of certain SULT1A1 genotypes.

Previous SULT studies have been inconsistent. An increased risk for colorectal cancer was seen for individuals with SULT1A1 638G>A GA and AA genotypes in one study (71); however, no association with colorectal cancer risk was seen for SULT1A1 638G>A and SULT1A2 706A>C in other studies (60,72–74). One colorectal adenoma study found an increased risk with the A allele at SULT1A1 638G>A and suggested an additive interaction with duration of smoking (53) and no evidence of interaction with meat intake (70) consistent with another study (75). Our study suggests that SULT1A1 may modify risk of polyps associated with smoking. Clearly, however, larger studies are needed to more accurately estimate risk associated with factors in combination.

Although several CYP1A1 studies have found increased colorectal cancer risk among carriers of minor alleles (60,76,77), a meta-analysis did not find any association with colorectal cancer risk (66). Genotypes at CYP1A1 4889A>G and 6235T>C were not associated with colorectal cancer in one large study (78), although interaction with NAT2 phenotype and GSTM1 allele was suggested, and carriers of a rare CYP1A1 allele who currently smoked were at greatest risk (78). Additional analysis suggested that rare CYP1A1 alleles and intake of white meat drippings were associated with decreased colorectal cancer risk (79). CYP1A1 AC genotype at 4887A>C compared with AA genotype was associated with reduced colorectal cancer risk in another study (55), and carriers of the G allele at 4889A>G were at modestly increased risk, especially among smokers and particular genotypes of NQO1 (80). Here, we did not observe polyp associations with CYP1A1 4887A>C or 4889A>G, but found some evidence of interaction with smoking for the 6235T>C genotype and with meat intake and 4887A>C genotype.

Previous reports on EPHX1 and adenomas found evidence for interaction with smoking but not meat intake (81,82). Other reports on EPHX1 and colorectal cancer risk found evidence of an inverse association with minor alleles (60) or did not find evidence of a main effect (55,83,84) or interaction with meat intake (83,85). Our findings of interaction with smoking, as previously reported (39), and seen here in haplotype analysis of three polyp phenotype groups are consistent with other polyp studies.

Limitations of the current study preclude definitive determination of the complex relationships between the variables and phenotypes studied. This is a case–control study of modest size, and thus, there are issues of bias and confounding to consider. Further, because neither adenomas nor hyperplastic polyps are reportable conditions, there is the problem of who is referred to be colonoscoped. As we have also noted previously, colonoscopy-negative controls provide a comparison group with similar socioeconomic backgrounds who have passed through similar filters in the referral system (38). We have evidence that, for smoking and other relevant risk factors, similar estimates of risk are derived from comparisons with both the colonoscopy-negative control group and a second community control group chosen from the community (40). This suggests an absence of major biases in the self-reported measures described here. The biologic measures included are not subject to reporting biases: all genotypes were performed blind to case–control status. The estimates derived from simple age- and sex-adjusted models and multivariate-adjusted models were quite similar, and there were no known plausible unmeasured confounders. We did not consider diplotype effects and the haplotype analysis used here assumes multiplicativity; however, advantages of the approach used include allowance for phase uncertainty (we did not assign most likely phase), incorporation of covariates and calculation of haplotype-specific risks (86–88). A factor limiting the generalizability of our results is that only Caucasians were analyzed because of the need for genetic homogeneity in LD-based analysis and the small number of non-Caucasians originally recruited (<3%).

The current analysis highlights additional avenues for future research on inborn and lifestyle factors as they relate to colorectal carcinogenesis. Clearly, however, the number of hypotheses examined in this report (genetic variation, exposures and phenotypes) urges caution in interpretation of even modestly suggestive results or trends. Larger sample size, pooled analyses with other studies and the use of approaches to optimally balance Type I and Type II error through modeling joint effects of multiple factors (89) or controlling the false discovery rate (90) are needed for subsequent analysis of homogeneous polyp groups.


   Supplementary material
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Supplementary material
References
 
Supplementary material is available online at http://www.carcin.oxfordjournals.org/


   Acknowledgments
 
The authors would like to thank Dr Roberd Bostick and Ms Lisa Fosdick for contributions to study design and data collection; Justin Sibert, Angela Bush and Xiaoyen Li for assistance with genotyping; Drs Sue S. Li and Richard J. Laws for assistance with HPlus; and Ms Laura Huennekens for graphic design. This work was funded in part by the Fred Hutchinson Cancer Research Center, the Mayo Foundation, and NIH grants R25-CA094880 and T32-CA09661.

Conflict of Interest Statement: None declared.


   References
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Supplementary material
 References
 

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