Abstract
Background
Animal studies suggest that lymphomagenesis can be induced by exposure to carcinogenic aromatic and heterocyclic amines found in diet, cigarette smoke, and the environment, but human epidemiologic investigations of these exogenous exposures have yielded conflicting results. As part of our evaluation of the role of aromatic and heterocyclic amines, which are metabolized by N-acetyltransferase (NAT) enzymes, in the etiology of non-Hodgkin lymphoma (NHL), we examined NHL risk in relation to genetic variation in NAT1 and NAT2 and exposure to cigarette smoke and dietary heterocyclic amines and mutagens.
Methods
We genotyped ten common single nucleotide polymorphisms (SNPs) in NAT1 and NAT2 among 1136 cases and 922 controls from a population-based case–control study in four geographic areas of the US. Relative risk of NHL for NAT1 and NAT2 genotypes, NAT2 acetylation phenotype, and exposure to cigarette smoke and dietary heterocyclic amines and mutagens was estimated using odds ratios (ORs) and 95% confidence intervals (CIs) derived from unconditional logistic regression models.
Results
We observed increased risk of NHL among individuals with the NAT1*10/*10 genotype compared with individuals with other NAT1 genotypes (OR=1.60, 95% CI 1.04–2.46, p=0.03). We also observed increased NHL risk in a dose-dependent model among NAT2 intermediate- and rapid-acetylators in comparison with slow-acetylators, although only the trend was statistically significant (intermediate: OR=1.18, 95% CI 0.97–1.44, p=0.1; rapid: OR=1.43, 95% CI 0.97–2.14, p=0.07; p for linear trend=0.03). Compared with nonsmokers, NHL risk estimates for current cigarette smoking were increased only among NAT2 intermediate/rapid-acetylators (OR=2.44, 95% CI 1.15–5.20, p=0.02).
Conclusions
Our data provide evidence that NAT1 and NAT2 genotypes are associated with NHL risk and support a contributory role for carcinogenic aromatic and/or heterocyclic amines in the multi-factorial etiology of NHL.
Keywords: lymphoma, non-Hodgkin; N-acetyltransferase 1; N-acetyltransferase 2; genetic variation; polymorphism, single nucleotide
Introduction
Non-Hodgkin lymphoma (NHL) comprises a group of closely-related yet heterogeneous diseases characterized by the malignant transformation of lymphoid cells [1]. Well-established risk factors for NHL include certain infections as well as treatments and diseases that cause severe immunosuppression [2]; however, the etiology of NHL remains largely unknown. Although animal studies have demonstrated that lymphomagenesis can be induced by exposure to various carcinogenic aromatic and heterocyclic amines found in diet from intake of well-done meats cooked at high-temperatures, cigarette smoke, and the environment [3-5], human epidemiologic investigations of NHL in relation to these exogenous exposures have yielded conflicting results [6-11]. Because aromatic and heterocyclic amines exhibit carcinogenic activity upon metabolism, it is plausible that genetic variation in aromatic and heterocyclic amine metabolism may modulate NHL risk.
N-acetyltransferase (NAT) enzymes are responsible for metabolizing aromatic and heterocyclic amines via N-acetylation, which generally leads to detoxification for monocyclic aromatic amines, or via O-acetylation, which leads to activation and the formation of DNA adducts linked to the induction of cancer [12,13]. Two distinct NAT enzymes, NAT1 and NAT2, have been identified, both of which are encoded by highly polymorphic genes located on chromosome 8 (8p23.1-p21.3 and 8p22, respectively) [14]. NAT1 and NAT2 appear to demonstrate some substrate specificity and varying levels of expression in different tissues [12,13]. Well-established sequence variation that corresponds to variation in acetylation capacity, and thus carcinogen metabolism, has been identified for NAT2 [13,15], but investigation of genetic variation in NAT1 and NAT2 in relation to NHL risk has been limited and inconsistent to date [16-19].
Differential susceptibility to NHL according to variation in acetylation capacity would provide important evidence supporting the role of carcinogenic aromatic and/or heterocyclic amines in the etiology of NHL. We therefore investigated NHL risk in relation to genetic variation in NAT1 and NAT2 and exposure to cigarette smoke and dietary heterocyclic amines and mutagens in a recently completed, population-based case–control study in the US.
Methods
Study population
The study population has been described previously in detail [20]. Briefly, cases included 1,321 patients with newly diagnosed NHL identified in four Surveillance, Epidemiology, and End Results (SEER) registries (state of Iowa and the metropolitan areas of Detroit, MI; Los Angeles, CA; and Seattle, WA) aged 20 to 74 between July 1998 and June 2000 without evidence of HIV infection. Population controls (N=1,057) were identified by random digit dialing (under age 65) and from Medicare eligibility files (65 years and older). Participation and response rates were 76% and 59%, respectively, in cases, and 52% and 44%, respectively, in controls. The study was conducted according to a protocol approved by Institutional Review Boards at the National Cancer Institute and each of the four SEER centers. Written informed consent was obtained from each participant prior to interview. All study participants were asked to provide a venous blood or mouthwash buccal cell sample that was shipped to the biological repository for processing and storage. We obtained blood samples from 773 cases and 668 controls, and buccal cell samples from 399 cases and 314 controls; 149 (11%) cases and 75 (7%) controls provided neither. Demographic characteristics (age, education, sex) for individuals who provided blood compared with buccal cells and compared with those who provided neither blood nor buccal cell samples were equivalent within each study site [21].
Histopathology
Each SEER registry provided NHL pathology and subtype information derived from abstracted reports by the local diagnosing pathologist. All cases were histologically confirmed and coded according to the International Classification of Diseases for Oncology, 2nd Edition (ICD-O-2) [22]. We evaluated the following histologic outcomes: (i) NHL overall (ICD-O-2: 9590-01, 9595, 9670-73, 9675-76, 9680-88, 9690-91, 9695-98, 9700, 9702-03, 9705-11, 9713-15, 9823, 9827), (ii) B-cell lymphomas (ICD-O-2: 9670-71, 9673, 9676, 9680-88, 9690-91, 9695-98, 9710-11, 9715, 9823), (iii) T-cell lymphomas (ICD-O-2: 9700, 9702-03, 9705-09, 9713-14, 9827), and four B-cell lymphoma subtypes: (iv) diffuse large B-cell (DLBCL) (ICD-O-2: 9680-84, 9688), (v) follicular (ICD-O-2: 9676, 9690-91, 9695-98), (vi) marginal zone (ICD-O-2: 9710-11, 9715), and (vii) small lymphocytic lymphoma (SLL) (ICD-O-2: 9670-71, 9823).
Laboratory Methods
DNA was extracted from blood clots or buffy coats (from 10 mL blood) at BBI Biotech Repository (Gaithersburg, MD) using Puregene Autopure DNA extraction kits (Gentra Systems, Minneapolis, MN). DNA was extracted from buccal cell samples by phenol chloroform extraction methods [23].
We selected for genotyping four single nucleotide polymorphisms (SNPs) in NAT1 and six SNPs in NAT2 (Table 1). Data from the NAT1 and NAT2 SNPs genotyped in this study were used to assign the most likely NAT1 and NAT2 alleles previously identified in human populations using consensus nomenclature (http://www.louisville.edu/medschool/pharmacology/NAT.html) [24]. All ten SNPs were genotyped in blood-based DNA samples first. Three SNPs (rs1041983, rs1799929, and rs1208) that were not informative for NAT2 phenotype assignment in our study population were not genotyped in buccal cell samples, which generally had less DNA than blood-based samples (Table 1). Genotyping was conducted at the National Cancer Institute Core Genotyping Facility (Advanced Technology Center, Gaithersburg, MD) using validated assays on the Taqman (Applied Biosystems, Foster City, CA) or MGB Eclipse (Epoch Biosciences, Bothell, WA) platforms. Sequence data and assay conditions are provided at http://snp500cancer.nci.nih.gov [25].
Table 1.
N-acetyltransferase 1 (NAT1) and 2 (NAT2) polymorphisms selected for genotyping.
| SNP rs # | Nucleotide change* | Amino acid change |
|---|---|---|
| NAT1 | ||
| rs4987076 | Ex1+591G>A | V149I |
| rs13249533 | Ex1-616G>A | R187Q |
| rs1057126 | Ex1-88T>A | - |
| rs15561 | Ex1-81C>A | - |
| NAT2 | ||
| rs1041983** | Ex2+288C>T | Y94Y |
| rs1801280 | Ex2+347T>C | I114T |
| rs1799929** | Ex2+487C>T | L161L |
| rs1799930 | Ex2-580G>A | R197Q |
| rs1208** | Ex2-367A>G | K268R |
| rs1799931 | Ex2-313G>A | G286E |
Genotyped in blood-based DNA samples only.
For the purposes of quality control (QC), 40 replicate samples from each of two blood donors and duplicate samples from 100 study participants processed in an identical fashion were interspersed for all genotyping assays and blinded from the laboratory. For each plate of 368 samples, genotype-specific QC samples were also included and comprised four homozygote wild-type, four heterozygote, four homozygote variant, and four DNA negative controls. Finally, each individual was identified using the AmpFLSTR® Identifiler® PCR Amplification Kit (Applied Biosystems, Foster City, CA). Of the 2,154 study participants who donated a biologic sample, 26 (3%) controls and 22 (2%) cases whose chromosomal sex based on the Identifiler® was discordant from that reported during the interview were excluded from this analysis. Participants with insufficient DNA for this analysis or whose DNA was not successfully extracted and quantified (14 (1%) cases and 34 (3%) controls) were also excluded, yielding a final population of 1136 cases and 922 controls for genotyping and analyses of NAT1 and NAT2 SNPs in relation to NHL. Because of incomplete genotyping for some SNPs due to insufficient DNA, the most likely NAT alleles could not be determined for 220 (19%) cases and 176 (19%) controls for NAT1, and 151 (13%) cases and 114 (12%) controls for NAT2, yielding a final population of 916 cases and 746 controls for analyses of NAT1 genotypes, and 985 cases and 808 controls for analyses of NAT2 genotypes and phenotypes. Demographic characteristics (age, education, sex) for cases and controls did not differ significantly for individuals with undetermined NAT alleles compared with those with known NAT alleles.
For nine of ten assays (excepting one NAT1 SNP, rs15561), genotyping was completed successfully in 95%-100% of the DNA samples and agreement for QC replicates and duplicates was >97%. Completion rate for rs15561 was 83% in blood-based DNA; however, quality control data were re-checked and the assay was deemed to be acceptable. The genotype frequencies among white, non-Hispanic controls were in Hardy–Weinberg equilibrium for all ten SNPs (Pearson chi-square statistic >0.05).
Exposure Assessment
The study population was divided into two groups, each receiving a different version of a computer-assisted personal interview (CAPI) and a different self-administered questionnaire. The present analysis of history of cigarette smoking and exposure to dietary heterocyclic amines and mutagens is thus based on the 484 cases and 419 controls who returned the self-administered dietary questionnaire.
Details have been published previously for the exposure assessment of history of cigarette smoking [9] and dietary exposure to heterocyclic amines [8]. Briefly, participants were classified as nonsmokers and used as the referent group for all analyses if they had never smoked regularly for at least 6 months. Former smokers were defined as those who stopped smoking at least 1 year prior to diagnosis (for cases) or interview (for controls). All smokers were asked to provide additional information about the age they began smoking, and duration and intensity (cigarettes/day) of smoking. Dietary exposure to three heterocyclic amines, including 2-amino-3,4,8-trimethylimidazo[4,5-f]quinoxaline (DiMeIQx), 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx), and 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP), was derived from information on the frequency of consumption, portion size, cooking method, and doneness level for hamburger, steak, pork chops, bacon, and sausage linked to a database on heterocyclic amines (http://charred.cancer.gov). This database was also used to create a continuous measure of the total mutagenic potential from meat consumption. All four variables were classified into quintiles according to the distribution among controls, and the first quintile was used as the referent group for all analyses.
Statistical Analysis
Variation in demographic characteristics for cases and controls was assessed using the Pearson chi-square statistic. To estimate the relative risk of NHL associated with NAT1 and NAT2 genotypes, history of cigarette smoking, and exposure to dietary heterocyclic amines and mutagens, we computed odds ratios (ORs) and 95% confidence intervals (CIs) derived from dichotomous multivariate unconditional logistic regression models. We also computed a p-value for the linear trend based on a three-level ordinal variable for each genotype (0=homozygote common, 1=heterozygote, 2=homozygote variant). Heterogeneity among NHL subtypes was assessed in polytomous multivariate unconditional logistic regression models using the Wald chi-square statistic.
For analyses of NAT1, NAT1*10 was designated as the at-risk allele based on previous research [15]. We thus computed ORs, 95% CIs, and a p-value for the linear trend comparing individuals with one or two copies of NAT1*10 with individuals with no copies of NAT1*10. For analyses of NAT2, we designated NAT2*4/*4 as the referent genotype, as has been done previously, because it corresponds to an absence of the nucleotide substitutions that define the other NAT2 genotypes [15]. The NAT2 genotype-phenotype relationship is well-established. NAT2 acetylation phenotype was assigned at the University of Louisville (by DWH) based on in vivo and in vitro data on allelic variation in catalytic activity [13]. For analysis of NAT2 phenotypes, individuals homozygous for NAT2 rapid- and slow-acetylator alleles were designated as rapid- and slow-acetylators, respectively; individuals possessing one rapid- and one slow-acetylator allele (heterozygotes) were designated as intermediate-acetylators [26].
All logistic regression models were adjusted for sex, age (< 45, 45–64, 65 + years), race (white non-Hispanic, black, other), and study center, as these were study design variables. Additional adjustment for education (high school or less, some college, college graduate) and cigarette smoking (current/former/never, cigarettes per day, or duration) did not materially alter (>10%) the parameter estimates for NAT1 or NAT2; these variables were therefore excluded from the final model. Models for exposure to dietary heterocyclic amines and mutagens were also adjusted for physical activity (none, 30-270, 271-675, 676-1080, >1080 metabolic equivalent tasks per week), total caloric intake (kcal/day), alcohol consumption (<1, 1-15, >15-30, >30 g/day), and animal protein (g/day), based on previous analyses of these data [8]. Modification of the effect of NAT1 and NAT2 on risk of NHL by sex, race, cigarette smoking, and dietary exposures was evaluated under the multiplicative model using a Wald chi-square statistic by including an interaction term in the logistic regression models. The SAS System, version 9.1 (SAS Institute, Inc., Cary, NC), was used to conduct all statistical analyses. P-values are presented with one significant digit. Statistical tests were two-sided with an α-level of 0.05.
Results
Table 2 presents selected characteristics for the study population. Cases were younger and more likely to be white, non-Hispanic than controls. Cases and controls did not differ significantly with respect to sex, history of cigarette smoking, or exposure to dietary heterocyclic amines and mutagens. DLBCL and follicular lymphoma accounted for slightly more than half of the histologic subtypes for cases.
Table 2.
Selected characteristics of cases (N=1,136) and controls (N=922) with NAT1 and NAT2 SNP genotype data in the NCI-SEER multicenter case–control study of NHL.
| Cases | Controls | ||
|---|---|---|---|
| N(%) | N(%) | p-value* | |
| Sex | |||
| Male | 622(54.8%) | 487(52.8%) | 0.4 |
| Female | 514(45.2%) | 435(47.2%) | |
| Age (years) | |||
| < 45 | 200(17.6%) | 144(15.6%) | 0.0006 |
| 45–64 | 561(49.4%) | 398(43.2%) | |
| 65 + | 375(33.0%) | 380(41.2%) | |
| Race | |||
| White, non-Hispanic | 980(86.3%) | 743(80.6%) | < 0.0001 |
| Black | 78(6.9%) | 124(13.4%) | |
| Other | 78(6.9%) | 55(6.0%) | |
| Study center | |||
| Detroit | 232(20.4%) | 160(17.4%) | 0.1 |
| Iowa | 333(29.3%) | 257(27.9%) | |
| Los Angeles | 282(24.8%) | 238(25.8%) | |
| Seattle | 289(25.4%) | 267(29.0%) | |
| History of cigarette smoking | |||
| Nonsmoker | 208(18.3%) | 163(17.7%) | 0.1** |
| Current smoker | 80(7.0%) | 55(6.0%) | |
| Former smoker | 148(13.0%) | 147(15.9%) | |
| Missing | 700(61.6%) | 557(60.4%) | |
| Mutagenic potential | |||
| (revertant colonies/day) | |||
| Q1: 0.0–1700.0 | 79(7.0%) | 64(6.9%) | 0.2** |
| Q2: 1700.1–3416.1 | 68(6.0%) | 74(8.0%) | |
| Q3: 3416.2–6470.0 | 99(8.7%) | 68(7.4%) | |
| Q4: 6470.1–11,338.0 | 103(9.1%) | 73(7.9%) | |
| Q5: > 11,338.0 | 76(6.7%) | 69(7.5%) | |
| Missing | 711(62.6%) | 574(62.3%) | |
| DNA source | |||
| Blood | 751(66.1%) | 639(69.3%) | 0.1 |
| Buccal cells | 385(33.9%) | 283(30.7%) | |
| Case histopathology | |||
| DLBCL | 358(31.5%) | ||
| Follicular lymphoma | 269(23.7%) | ||
| SLL | 146(12.9%) | ||
| Marginal zone | 91(8.0%) | ||
| Mantle Cell | 41(3.6%) | ||
| Burkitt lymphoma | 18(1.6%) | ||
| All T-cell | 70(6.2%) | ||
| NOS | 143(12.6%) |
P-value for Pearson chi-square statistic.
P-values computed excluding those with missing data for history of cigarette smoking and diet.
The prevalence of the NAT1*10/*10 genotype among controls was 5.5%. We observed increased risk of NHL among individuals with two copies of NAT1*10 in comparison with individuals with no copies of NAT1*10 (*10/any: OR=1.07, 95% CI 0.87–1.33, p=0.5; *10/*10: OR=1.60, 95% CI 1.04–2.46, p=0.03; p for linear trend=0.07) (Table 3). Risk estimates were generally increased for all the NHL subtypes we evaluated, although higher risk estimates were observed for follicular lymphoma than for other subtypes (*10/*10: OR=2.06, 95% CI 1.12–3.79, p=0.02). Results from our analyses of other NAT1 genotypes and SNPs supported our designation of NAT1*10 as the at-risk allele. Analyses of other NAT1 genotypes in comparison with the NAT1*4/*4 genotype demonstrated increased risk of NHL for NAT1*10/*10 only (OR=1.61, 95% CI 1.04–2.48, p=0.03) (Table 4).
Table 3.
Association between NAT1*10 and risk of NHL and NHL subtypes.
| NAT1*any(except *10)/*any(except *10) | NAT1*10/*any(except *10) | NAT1*10/*10 | NAT1*10/any(except *10) | NAT1*10/*10 | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| N(%) | OR(95% CI)* | N(%) | OR(95% CI)* | p | N(%) | OR(95% CI)* | p | p for linear trend | N(%) | OR(95% CI)* | p | |
| Controls | 454(60.9) | 251(33.6) | 41(5.5) | 292(39.1) | ||||||||
| All NHL | 547(59.7) | 1.00 (reference) | 303(33.1) | 1.07 (0.87, 1.33) | 0.5 | 66(7.2) | 1.60 (1.04, 2.46) | 0.03 | 0.07 | 369(40.3) | 1.14 (0.92, 1.40) | 0.2 |
| By NHL subtype | ||||||||||||
| DLBCL | 167(57.4) | 1.00 (reference) | 106(36.4) | 1.25 (0.93, 1.68) | 0.1 | 18(6.2) | 1.49 (0.81, 2.74) | 0.2 | 0.08 | 124(42.6) | 1.28 (0.96, 1.70) | 0.09 |
| Follicular lymphoma | 138(63.9) | 1.00 (reference) | 59(27.3) | 0.87 (0.62, 1.24) | 0.5 | 19(8.8) | 2.06 (1.12, 3.79) | 0.02 | 0.3 | 78(36.1) | 1.01 (0.73, 1.40) | 0.9 |
| SLL | 71(59.7) | 1.00 (reference) | 43(36.1) | 1.21 (0.79, 1.84) | 0.4 | 5(4.2) | 0.96 (0.36, 2.57) | 0.9 | 0.6 | 48(40.3) | 1.18 (0.79, 1.77) | 0.4 |
| Marginal zone | 41(57.7) | 1.00 (reference) | 25(35.2) | 1.08 (0.64, 1.84) | 0.8 | 5(7.0) | 1.51 (0.55, 4.17) | 0.4 | 0.5 | 30(42.3) | 1.13 (0.68, 1.88) | 0.6 |
| All T-cell | 33(61.1) | 1.00 (reference) | 16(29.6) | 0.93 (0.49, 1.76) | 0.8 | 5(9.3) | 1.84 (0.64, 5.27) | 0.3 | 0.6 | 21(38.9) | 1.04 (0.58, 1.89) | 0.9 |
OR (95% CI) adjusted for age, sex, race, and study center.
Table 4.
Association between NAT1 genotypes and risk of NHL.
| Controls | Cases | ||||
|---|---|---|---|---|---|
| NAT1 genotype | N(%) | N(%) | OR | (95% CI)* | p |
| NAT1*4/*4 | 386(51.3) | 463(50.3) | 1.00 | (reference) | |
| NAT1*10/*10 | 42(5.6) | 68(7.4) | 1.61 | (1.04, 2.48) | 0.03 |
| NAT1*4/*10 | 206(27.4) | 254(27.6) | 1.11 | (0.87, 1.40) | 0.4 |
| NAT1*4/*11A or*3/*11B | 20(2.7) | 27(2.9) | 1.04 | (0.57, 1.90) | 0.9 |
| NAT1*4/*3 | 31(4.1) | 26(2.8) | 0.70 | (0.40, 1.21) | 0.2 |
| Other** | 67(8.9) | 83(9.0) | 1.10 | (0.77, 1.57) | 0.6 |
OR (95% CI) adjusted for age, sex, race, and study center.
Other NAT1 genotypes (<2% prevalence among controls): NAT1*10/*11A, NAT1*10/*14A, NAT1*11A/*14A, NAT1*14A/*14A, NAT1*3/*10, NAT1*3/*11A, NAT1*3/*14A, NAT1*4/*14A, NAT1*10/*14B.
In our analyses by NAT2 phenotype, we observed increased risk of NHL in a dose-dependent model among intermediate- and rapid-acetylators in comparison with slow-acetylators, although only the trend was statistically significant (intermediate: OR=1.18, 95% CI 0.97–1.44, p=0.1; rapid: OR=1.44, 95% CI 0.97–2.14, p=0.07; p for linear trend=0.03) (Table 5). Risk estimates were generally increased for all the NHL subtypes we evaluated, although the increased risk was most pronounced for follicular lymphoma (intermediate/rapid-acetylators: OR=1.50, 95% CI 1.11–2.02, p=0.008) and for marginal zone lymphoma (intermediate/rapid-acetylators: OR=1.56, 95% CI 0.98–2.49, p=0.06). Further analysis of NAT2 genotypes supported our finding of increased risk among rapid-acetylators; the NHL risk estimates for the NAT2 genotypes corresponding to the intermediate- and slow-acetylator phenotypes in comparison with those corresponding to the rapid-acetylator phenotype were consistently less than 1.0 (Table 6).
Table 5.
Association between NAT2 phenotypes and risk of NHL and NHL subtypes.
| Slow* | Intermediate* | Rapid* | Intermediate/Rapid | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| N(%) | OR(95% CI)** | N(%) | OR(95% CI)** | p | N(%) | OR(95% CI)** | p | p for linear trend | N(%) | OR(95% CI)** | p | |
| Controls | 452(55.9) | 306(37.9) | 50(6.2) | 356(44.1) | ||||||||
| All NHL | 523(53.1) | 1.00 (reference) | 390(39.6) | 1.18 (0.97, 1.44) | 0.1 | 72(7.3) | 1.44 (0.97, 2.14) | 0.07 | 0.03 | 462(46.9) | 1.21 (1.00, 1.47) | 0.05 |
| By NHL subtype | ||||||||||||
| DLBCL | 173(55.4) | 1.00 (reference) | 114(36.5) | 1.05 (0.79, 1.39) | 0.7 | 25(8.0) | 1.52 (0.89, 2.58) | 0.1 | 0.2 | 139(44.6) | 1.11 (0.85, 1.45) | 0.5 |
| Follicular lymphoma | 113(48.5) | 1.00 (reference) | 104(44.6) | 1.50 (1.10, 2.04) | 0.01 | 16(6.9) | 1.52 (0.82, 2.82) | 0.2 | 0.01 | 120(51.5) | 1.50 (1.11, 2.02) | 0.008 |
| SLL | 73(56.6) | 1.00 (reference) | 46(35.7) | 1.02 (0.68, 1.52) | 0.9 | 10(7.8) | 1.58 (0.75, 3.31) | 0.2 | 0.4 | 56(43.4) | 1.08 (0.74, 1.59) | 0.7 |
| Marginal zone | 37(45.1) | 1.00 (reference) | 44(53.7) | 1.76 (1.10, 2.82) | 0.02 | 1(1.2) | 0.24 (0.03, 1.83) | 0.2 | 0.4 | 45(54.9) | 1.56 (0.98, 2.49) | 0.06 |
| All T-cell | 36(63.2) | 1.00 (reference) | 18(31.6) | 0.78 (0.43, 1.42) | 0.4 | 3(5.3) | 0.86 (0.25, 2.99) | 0.8 | 0.5 | 21(36.8) | 0.79 (0.45, 1.41) | 0.4 |
NAT2 phenotypes: Slow (NAT2*5B/*6A, NAT2*5/*5, NAT2*5/*6, NAT2*5B/*5B, NAT2*5B/*7B, NAT2*6/*6, NAT2*6A/*6A, NAT2*5/*7, NAT2*5A/*5B, NAT2*5A/*5C, NAT2*5A/*6A, NAT2*5A/*7B, NAT2*5B/*5C, NAT2*5C/*6A, NAT2*5C/*7B, NAT2*6/*7, NAT2*6A/*7B, NAT2*7/*7, NAT2*7B/*7B); Intermediate (NAT2*4/*5, NAT2*4/*5B, NAT2*4/*6, NAT2*4/*6A, NAT2*4/*5A, NAT2*4/*5C, NAT2*4/*7, NAT2*4/*7B, NAT2*5B/*12A, NAT2*5B/*13, NAT2*5C/*12A, NAT2*6A/*12A, NAT2*6A/*13, NAT2*7B/*12A, NAT2*7B/*13); Rapid (NAT2*4/*4, NAT2*12A/*13, NAT2*4/*12A, NAT2*4/*13).
OR (95% CI) adjusted for age, sex, race, and study center.
Table 6.
Association between NAT2 genotypes and risk of NHL.
| Controls | Cases | ||||
|---|---|---|---|---|---|
| N(%) | N(%) | OR (95% CI)* | p | Acetylator phenotype | |
| NAT2*5B/*6A | 129(16.0) | 137(13.9) | 0.64 (0.40, 1.01) | 0.06 | Slow |
| NAT2*5/*5 | 27(3.3) | 55(5.6) | 1.16 (0.63, 2.13) | 0.6 | Slow |
| NAT2*5/*6 | 59(7.3) | 77(7.8) | 0.77 (0.45, 1.30) | 0.3 | Slow |
| NAT2*5B/*5B | 94(11.6) | 94(9.6) | 0.59 (0.36, 0.97) | 0.04 | Slow |
| NAT2*5B/*7B | 22(2.7) | 22(2.2) | 0.59 (0.29, 1.20) | 0.1 | Slow |
| NAT2*6/*6 | 19(2.4) | 26(2.6) | 0.88 (0.43, 1.81) | 0.7 | Slow |
| NAT2*6A/*6A | 46(5.7) | 52(5.3) | 0.66 (0.38, 1.17) | 0.2 | Slow |
| Other NAT2 slow-acetylator genotypes** | 56(6.9) | 59(6.0) | 0.67 (0.39, 1.15) | 0.1 | Slow |
| NAT2*4/*5 | 45(5.6) | 57(5.8) | 0.88 (0.50, 1.55) | 0.7 | Intermediate |
| NAT2*4/*5B | 88(10.9) | 151(15.3) | 1.04 (0.65, 1.68) | 0.9 | Intermediate |
| NAT2*4/*6 | 42(5.2) | 33(3.4) | 0.49 (0.27, 0.90) | 0.02 | Intermediate |
| NAT2*4/*6A | 92(11.4) | 92(9.3) | 0.61 (0.37, 0.99) | 0.04 | Intermediate |
| Other NAT2 intermediate-acetylator genotypes** | 39(4.8) | 57(5.8) | 1.13 (0.64, 2.01) | 0.7 | Intermediate |
| NAT2*4/*4 | 45(5.6) | 66(6.7) | 1.00 (reference) | Rapid | |
| Other NAT2 rapid-acetylator genotypes** | 5(0.6) | 6(0.6) | 0.97 (0.27, 3.49) | 1.0 | Rapid |
OR (95% CI) adjusted for age, sex, race, and study center.
Other NAT2 slow-acetylator genotypes (<2% prevalence among controls): NAT2*5/*7, NAT2*5A/*5B, NAT2*5A/*5C, NAT2*5A/*6A, NAT2*5A/*7B, NAT2*5B/*5C, NAT2*5C/*6A, NAT2*5C/*7B, NAT2*6/*7, NAT2*6A/*7B, NAT2*7/*7, NAT2*7B/*7B.
Other NAT2 intermediate-acetylator genotypes (<2% prevalence among controls): NAT2*4/*5A, NAT2*4/*5C, NAT2*4/*7, NAT2*4/*7B, NAT2*5B/*12A, NAT2*5B/*13, NAT2*5C/*12A, NAT2*6A/*12A, NAT2*6A/*13, NAT2*7B/*12A, NAT2*7B/*13.
Other NAT2 rapid-acetylator genotypes (<2% prevalence among controls): NAT2*12A/*13, NAT2*4/*12A, NAT2*4/*13.
In our study population, NAT1*10 was over-represented among NAT2 rapid-acetylators (frequency of NAT1*10/*10 was 3%, 7%, and 20% in NAT2 slow-, intermediate-, and rapid-acetylators, respectively (Pearson chi-square < 0.0001)). However, inclusion of both NAT1 and NAT2 in the same model did not materially alter (>10%) the NHL risk estimates for NAT*10/*10 or NAT2 rapid-acetylators, nor was there interaction between NAT1 and NAT2 (data not shown).
Although analyses stratified by sex revealed that risk estimates for NAT1 genotypes and NAT2 phenotypes were slightly higher for men than for women, these differences were not statistically significant under the multiplicative model (data not shown). NAT1 genotype and NAT2 phenotype frequencies differed between non-Hispanic whites and blacks, however the NHL risk estimates were not statistically significantly different under the multiplicative model (Online Supplemental Table).
Risk of NHL associated with history of cigarette smoking differed significantly by NAT2 phenotype (interaction p-value=0.05), but not by NAT1 genotype (interaction p-value=0.9) under the multiplicative model (Table 7). Among NAT2 intermediate-/rapid-acetylators, risk estimates for NHL were 2.4-fold for current smokers compared with nonsmokers (OR=2.44 (95% CI 1.15-5.20, p=0.02), whereas risk of NHL was not related to current cigarette smoking among NAT2 slow-acetylators (OR=0.87, 95% CI 0.50, 1.53, p=0.6). Risk of NHL associated with exposure to dietary heterocyclic amines and mutagens did not differ significantly by NAT1 genotype or by NAT2 phenotype under the multiplicative model (data not shown).
Table 7.
Association between history of cigarette smoking and risk of NHL by NAT1*10 and NAT2 phenotype.
| NAT1*any(except *10)/*any(except *10) | NAT1*10/any(except *10) | NAT1*10/*10 | |||||||
|
|
|
|||||||
| Controls N(%) | Cases N(%) | OR (95% CI)* | P | Controls N(%) | Cases N(%) | OR(95% CI)* | p | |
|
| ||||||||
| Nonsmokers | 85(18.7) | 102(18.6) | 1.00 (reference) | 43(14.7) | 62(16.8) | 1.00 (reference) | ||
| Current smokers | 30(6.6) | 42(7.7) | 1.12 (0.64, 1.95) | 0.7 | 14(4.8) | 28(7.6) | 1.32 (0.62, 2.84) | 0.5 |
| Former smokers | 78(17.2) | 74(13.5) | 0.86 (0.55, 1.33) | 0.5 | 36(12.3) | 46(12.5) | 0.85 (0.47, 1.56) | 0.6 |
| Missing | 261(57.5) | 329(60.1) | 1.11 (0.79, 1.57) | 0.6 | 199(68.2) | 233(63.1) | 0.95 (0.60, 1.49) | 0.8 |
|
| ||||||||
| NAT2 Slow | Intermediate/Rapid | |||||||
|
|
|
|||||||
| Controls N(%) | Cases N(%) | OR (95% CI)* | p | Controls N(%) | Cases N(%) | OR(95% CI)* | p | |
|
| ||||||||
| Nonsmokers | 82(18.1) | 93(17.8) | 1.00 (reference) | 60(16.9) | 88(19.0) | 1.00 (reference) | ||
| Current smokers | 34(7.5) | 36(6.9) | 0.87 (0.50, 1.53) | 0.6 | 11(3.1) | 38(8.2) | 2.44 (1.15, 5.20) | 0.02 |
| Former smokers | 70(15.5) | 75(14.3) | 0.99 (0.63, 1.55) | 0.9 | 56(15.7) | 57(12.3) | 0.70 (0.42, 1.15) | 0.2 |
| Missing | 266(15.5) | 319(61.0) | 1.06 (0.74, 1.50) | 0.8 | 229(64.3) | 279(60.4) | 1.03 (0.70, 1.52) | 0.9 |
OR (95% CI) adjusted for age, sex, race, and study center.
Discussion
In this large, population-based case–control study, we report increased risk of NHL among individuals with the NAT1*10/*10 genotype, present in 5.5% of controls, compared with other NAT1 genotypes. Risk of NHL was also higher among individuals with NAT2 rapid-acetylator genotypes, present in 6.2% of controls, compared with those with slow-acetylator genotypes. Risk of NHL associated with current cigarette smoking was observed only among NAT2 intermediate- and rapid-acetylators. The observed relationship between variation in acetylation capacity and differential susceptibility to NHL indirectly supports the role of carcinogenic aromatic and/or heterocyclic amines in the etiology of NHL.
Sources of exposure to aromatic or heterocyclic amines include cigarette smoke, dietary intake of well-done meats cooked at high-temperatures, hair dyes, and occupations within industries using aniline. Aromatic and heterocyclic amines such as these are bioactivated in a two-step process that includes oxidation by cytochrome P450 enzymes and subsequent O-acetylation by NAT1 and/or NAT2 [15,27]. The resulting acetoxy-ester intermediates are capable of forming DNA adducts [12,13,15,28] and have been linked to the induction of various cancers in rodents, including lymphomas [3,5,29]. Human epidemiologic investigations of NHL in relation to aromatic or heterocyclic amine exposures, however, have yielded conflicting results [6-11]. We present here the first evidence that the potential relation between NHL risk and these exogenous exposures may be modified by common genetic variation in acetylation capacity. We observed increased risk of NHL associated with current cigarette smoking among NAT2 intermediate-/rapid-acetylators, which supports a role for diarylamines or heterocyclic amines that are present at higher concentrations in cigarette smoke than in well-done meats in the etiology of NHL. Future investigations to replicate and extend these results are necessary, however, particularly because our analysis was limited by the study design such that data on history of cigarette smoking and exposure to dietary heterocyclic amines and mutagens were only available for half our study population.
There is a well-established correlation between NAT2 genotype and acetylation phenotype [13,15]. NAT2 rapid-acetylators demonstrate increased O-acetylation activity, thereby increasing the bioactivation of aromatic and heterocyclic amines and potential formation of DNA adducts. The genotype-phenotype relationship for NAT1 is less clear [13]: NAT1*10 has been linked to increased O-acetylation activity in some studies [30], but not in others [31,32].
Three previous smaller epidemiologic investigations found no association between NAT1 or NAT2 genotypes and NHL risk [16,18,19]; a fourth epidemiologic investigation, which used caffeine as a metabolic probe to determine acetylation status, also found no significant relationship between acetylation status and overall malignant lymphoma but did suggest an association between the NAT2 slow-acetylator phenotype and low-grade lymphoma [17]. The NAT1 and NAT2 genotype frequencies in our controls were similar to the control populations in previous studies. If genetic variations in NAT1 and NAT2 do, in fact, modulate NHL risk, conflicting study results could arise due to variations among different study populations in the levels of exposure to NAT1/NAT2 substrates [15]. Previous studies might have also had genotype misclassification as only recently have methods allowed sufficient distinction of the NAT1*10 allele from other NAT1 alleles (e.g., NAT1*14A); prior methods only detected the wildtype NAT2*4 allele and a small number of variant NAT2 alleles [15]. The accuracy of our genotyping data for individual SNPs and our method for assignment of NAT1 and NAT2 alleles therefore minimized such misclassification. Although our study population is the largest published to date, replication of our results is warranted in other large epidemiologic studies that distinguish between individuals with one versus two copies of the NAT1*10 allele and between individuals with NAT2 intermediate- versus rapid-acetylator phenotype, which was important in our data.
The distribution and levels of NAT expression in humans are tissue specific: NAT1 is present in most tissues throughout the body, whereas NAT2 is expressed predominantly in the liver and gastrointestinal tracts [33]. Correspondingly, the effect of exposure to aromatic and heterocyclic amines on cancer risk appears to be organ specific [15]. For example, NAT2 slow-acetylators are at increased risk for bladder cancer [34], whereas rapid-acetylators are at increased risk for colorectal cancer [35]. Moderate linkage disequilibrium exists between the NAT1 and NAT2 loci, and thus the genotypes are not independent of one another; however, the SNPs we genotyped were not in strong linkage disequilibrium [36]. In our study population, NAT1*10 was over-represented among NAT2 rapid-acetylators, which is consistent with previous reports [15,37]. Inclusion of both NAT1 and NAT2 in the same model did not materially alter (>10%) the NHL risk estimates for NAT1*10/*10 or NAT2 rapid-acetylators, suggesting that our overall findings for NAT1 and NAT2 are not confounded by one another.
Although a population-based study design, several study limitations should also be taken into account in the interpretation of our findings. Loss of information from eligible subjects due to death or refusal to participate could have biased our results, although survival bias was minimized by the use of rapid case reporting systems in all four study centers. It is also unlikely that participation bias would completely explain our findings because our results were similar when we restricted our analysis to the study center with the highest participation rates (Iowa), and because it is unlikely that genotype frequencies vary by willingness to participate [21]. In addition, the observed frequencies of the NAT1*10/*10 genotype (5.5% among controls) and of homozygous NAT2 rapid-acetylators (6% among controls) were similar to that expected in a predominantly Caucasian population in the US [38]. Finally, information bias resulting from exposure misclassification is likely to have been non-differential, thus biasing our risk estimates toward the null.
In summary, our data provide evidence of differential susceptibility to NHL in relation to genetic variation in acetylation capacity, thereby suggesting a contributory role for carcinogenic aromatic and/or heterocyclic amines in the multi-factorial etiology of NHL. If our results are replicated in additional studies, future large-scale epidemiologic investigations of carcinogenic aromatic and heterocyclic amines that take into account variation in acetylation capacity are warranted.
Supplementary Material
Acknowledgments
We are indebted to our SEER collaborators for the recruitment and conduct of the study's field effort and collection of biological specimens. We gratefully acknowledge Sunita Yadavalli and staff at the NCI Core Genotyping Facility for specimen handling and laboratory analysis of genotyping data. We also gratefully acknowledge the assistance of Peter Hui (Information Management Services, Inc., Silver Spring, MD) for programming support.
Financial support: This research was supported by the Intramural Research Program of the NIH, National Cancer Institute, with Public Health Service (PHS) contracts N01-PC-65064, N01-PC-67008, N01-PC-67009, N01-PC-67010, and N02-PC-71105.
List of abbreviations
- DLBCL
diffuse large B-cell lymphoma
- ICD-O-2
International Classification of Diseases for Oncology, 2nd edition
- NAT
N-acetyltransferase
- NHL
non-Hodgkin lymphoma
- QC
quality control
- SNP
single nucleotide polymorphism
- SLL
small lymphocytic lymphoma
- SEER
Surveillance, Epidemiology, and End Results
- US
United States
References
- 1.Jaffe ES, Harris NL, Stein H, Vardiman JW, editors. Pathology and Genetics of Tumours of Haematopoietic and Lymphoid Tissues. Lyon: IARC Press; 2001. World Health Organization Classification of Tumours. [Google Scholar]
- 2.Hartge P, Bracci PM, Wang SS, Devesa SS, Holly EA. Non-Hodgkin lymphoma. In: Schottenfeld D, Fraumeni JF Jr, editors. Cancer Epidemiology and Prevention. Oxford: Oxford Press; 2005. [Google Scholar]
- 3.Sorensen I, Mortensen A, Kristiansen E, van Kreijl C, Adamson R, Thorgeirsson S. Short-term carcinogenicity testing of 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) and 2-amino-3-methylimidazo[4,5-f]quinoline (IQ) in E(mu)-pim-1 transgenic mice. Carcinogenesis. 1996;17:2221–2227. doi: 10.1093/carcin/17.10.2221. [DOI] [PubMed] [Google Scholar]
- 4.National Toxicology Program. Bioassay of 2,4-diaminotoluene for possible carcinogenicity. Natl Cancer Inst Carcinog Tech Rep Ser. 1979;162:1–139. [PubMed] [Google Scholar]
- 5.Esumi H, Ohgaki H, Kohzen E, Takayama S, Sugimura T. Induction of lymphoma in CDF1 mice by the food mutagen, 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine. Jpn J Cancer Res. 1989;80:1176–1178. doi: 10.1111/j.1349-7006.1989.tb01651.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Chiu BC, Cerhan JR, Folsom AR, Sellers TA, Kushi LH, Wallace RB, et al. Diet and risk of non-Hodgkin lymphoma in older women. JAMA. 1996;275:1315–1321. doi: 10.1001/jama.1996.03530410029029. [DOI] [PubMed] [Google Scholar]
- 7.De Stefani E, Fierro L, Barrios E, Ronco A. Tobacco, alcohol, diet and risk of non-Hodgkin's lymphoma: a case-control study in Uruguay. Leuk Res. 1998;22:445–452. doi: 10.1016/s0145-2126(97)00194-x. [DOI] [PubMed] [Google Scholar]
- 8.Cross AJ, Ward MH, Schenk M, Kulldorff M, Cozen W, Davis S, et al. Meat and meat-mutagen intake and risk of non-Hodgkin lymphoma: results from a NCI-SEER case-control study. Carcinogenesis. 2006;27:293–297. doi: 10.1093/carcin/bgi212. [DOI] [PubMed] [Google Scholar]
- 9.Morton LM, Hartge P, Holford TR, Holly EA, Chiu BCH, Vineis P, et al. Cigarette smoking and risk of non-Hodgkin lymphoma: a pooled analysis from the InterLymph consortium. Cancer Epidemiol Biomarkers Prev. 2005;14:925–933. doi: 10.1158/1055-9965.EPI-04-0693. [DOI] [PubMed] [Google Scholar]
- 10.Purdue MP, Bassani DG, Klar NS, Sloan M, Kreiger N The Canadian Cancer Registries Epidemiology Research Group. Dietary factors and risk of non-Hodgkin lymphoma by histologic subtype: a case-control analysis. Cancer Epidemiol Biomarkers Prev. 2004;13:1665–1676. [PubMed] [Google Scholar]
- 11.Zhang S, Hunter DJ, Rosner BA, Colditz GA, Fuchs CS, Speizer FE, et al. Dietary fat and protein in relation to risk of non-Hodgkin's lymphoma among women. J Natl Cancer Inst. 1999;91:1751–1758. doi: 10.1093/jnci/91.20.1751. [DOI] [PubMed] [Google Scholar]
- 12.Hein DW, Doll M, Rustan T, Gray K, Feng Y, Ferguson R, et al. Metabolic activation and deactivation of arylamine carcinogens by recombinant human NAT1 and polymorphic NAT2 acetyltransferases. Carcinogenesis. 1993;14:1633–1638. doi: 10.1093/carcin/14.8.1633. [DOI] [PubMed] [Google Scholar]
- 13.Hein DW. Molecular genetics and function of NAT1 and NAT2: role in aromatic amine metabolism and carcinogenesis. Mutat Res. 2002;506-507:65–77. doi: 10.1016/s0027-5107(02)00153-7. [DOI] [PubMed] [Google Scholar]
- 14.Blum M, Grant D, McBride W, Heim M, Meyer U. Human arylamine N-acetyltransferase genes: isolation, chromosomal localization, and functional expression. DNA Cell Biol. 1990;9:193–203. doi: 10.1089/dna.1990.9.193. [DOI] [PubMed] [Google Scholar]
- 15.Hein DW, Doll MA, Fretland AJ, Leff MA, Webb SJ, Xiao GH, et al. Molecular genetics and epidemiology of the NAT1 and NAT2 acetylation polymorphisms. Cancer Epidemiol Biomarkers Prev. 2000;9:29–42. [PubMed] [Google Scholar]
- 16.Chiu BCH, Kolar C, Gapstur SM, Lawson T, Anderson JR, Weisenburger DD. Association of NAT and GST polymorphisms with non-Hodgkin's lymphoma: a population-based case-control study. Br J Haematol. 2005;128:610–615. doi: 10.1111/j.1365-2141.2004.05358.x. [DOI] [PubMed] [Google Scholar]
- 17.William BM, Abdel-Tawab A, Hassan E, Mohamed O. Acetylator phenotyping in patients with malignant lymphomas, using caffeine as the metabolic probe. Pol J Pharmacol. 2004;56:445–449. [PubMed] [Google Scholar]
- 18.Kerridge I, Lincz L, Scorgie F, Hickey D, Granter N, Spencer A. Association between xenobiotic gene polymorphisms and non-Hodgkin's lymphoma risk. Br J Haematol. 2002;118:477–481. doi: 10.1046/j.1365-2141.2002.03606.x. [DOI] [PubMed] [Google Scholar]
- 19.Lemos MC, Cabrita FJ, Silva HA, Vivan M, Placido F, Regateiro FJ. Genetic polymorphism of CYP2D6, GSTM1 and NAT2 and susceptibility to haematological neoplasias. Carcinogenesis. 1999;20:1225–1229. doi: 10.1093/carcin/20.7.1225. [DOI] [PubMed] [Google Scholar]
- 20.Chatterjee N, Hartge P, Cerhan JR, Cozen W, Davis S, Ishibe N, et al. Risk of non-Hodgkin's lymphoma and family history of lymphatic, hematologic, and other cancers. Cancer Epidemiol Biomarkers Prev. 2004;13:1415–1421. [PubMed] [Google Scholar]
- 21.Bhatti P, Sigurdson AJ, Wang SS, Chen J, Rothman N, Hartge P, et al. Genetic cariation and willingness to participate in epidemiologic research: data from three studies. Cancer Epidemiol Biomarkers Prev. 2005;14:2449–2453. doi: 10.1158/1055-9965.EPI-05-0463. [DOI] [PubMed] [Google Scholar]
- 22.Harris NL, Jaffe ES, Stein H, Banks PM, Chan JK, Cleary ML, et al. A revised European-American classification of lymphoid neoplasms: a proposal from the International Lymphoma Study Group. Blood. 1994;84:1361–1392. [PubMed] [Google Scholar]
- 23.Garcia-Closas M, Egan KM, Abruzzo J, Newcomb PA, Titus-Ernstoff L, Franklin T, et al. Collection of genomic DNA from adults in epidemiological studies by buccal cytobrush and mouthwash. Cancer Epidemiol Biomarkers Prev. 2001;10:687–696. [PubMed] [Google Scholar]
- 24.Hein DW, Grant DM, Sim E. Update on consensus arylamine N-acetyltransferase gene nomenclature. Pharmacogenetics. 2000;10:291–292. doi: 10.1097/00008571-200006000-00002. [DOI] [PubMed] [Google Scholar]
- 25.Packer BR, Yeager M, Staats B, Welch R, Crenshaw A, Kiley M, et al. SNP500Cancer: a public resource for sequence validation and assay development for genetic variation in candidate genes. Nucl Acids Res. 2004;32:D528–D532. doi: 10.1093/nar/gkh005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Hein DW. N-acetyltransferase 2 genetic polymorphism: Effects of carcinogen and haplotype on urinary bladder cancer risk. Oncogene. doi: 10.1038/sj.onc.1209374. (In press) [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Jagerstad M, Skog K. Genotoxicity of heat-processed foods. Mutat Res. 2005;574:156–172. doi: 10.1016/j.mrfmmm.2005.01.030. [DOI] [PubMed] [Google Scholar]
- 28.Hein DW, Rustan T, Ferguson R, Doll M, Gray K. Metabolic activation of aromatic and heterocyclic N-hydroxyarylamines by wild-type and mutant recombinant human NAT1 and NAT2 acetyltransferases. Arch Toxicol. 1994;68:129–133. doi: 10.1007/s002040050045. [DOI] [PubMed] [Google Scholar]
- 29.Kroese ED. Use of E mu-PIM-1 transgenic mice short-term in vivo carcinogenicity testing: lymphoma induction by benzo[a]pyrene, but not by TPA. Carcinogenesis. 1997;18:975–980. doi: 10.1093/carcin/18.5.975. [DOI] [PubMed] [Google Scholar]
- 30.Bell DA, Badawi A, Lang N, Ilett K, Kadlubar F, Hirvonen A. Polymorphism in the N-acetyltransferase 1 (NAT1) polyadenylation signal: association of NAT1*10 allele with higher N-acetylation activity in bladder and colon tissue. Cancer Res. 1995;55:5226–5229. [PubMed] [Google Scholar]
- 31.Butcher NJ, Ilett KF, Minchin RF. Functional polymorphism of the human arylamine N-acetyltransferase type 1 gene caused by C190T and G560A mutations. Pharmacogenetics. 1998;8:67–72. doi: 10.1097/00008571-199802000-00009. [DOI] [PubMed] [Google Scholar]
- 32.Hughes NC, Janezic S, McQueen K, Jewett M, Castranio T, Bell DA, et al. Identification and characterization of variant alleles of human acetyltransferase NAT1 with defective function using p-aminosalicylate as an in-vivo and in-vitro probe. Pharmacogenetics. 1998;8:55–66. doi: 10.1097/00008571-199802000-00008. [DOI] [PubMed] [Google Scholar]
- 33.Pompeo F, Brooke E, Kawamura A, Mushtaq A, Sim E. The pharmacogenetics of NAT: structural aspects. Pharmacogenomics. 2002;3:19–30. doi: 10.1517/14622416.3.1.19. [DOI] [PubMed] [Google Scholar]
- 34.Garcia-Closas M, Malats N, Silverman D, Dosemeci M, Kogevinas M, Hein DW, et al. NAT2 slow acetylation, GSTM1 null genotype, and risk of bladder cancer: results from the Spanish Bladder Cancer Study and meta-analyses. Lancet. 2005;366:649–659. doi: 10.1016/S0140-6736(05)67137-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Landi S, Gemignani F, Moreno V, Gioia-Patricola L, Chabrier A, Guino E, et al. A comprehensive analysis of phase I and phase II metabolism gene polymorphisms and risk of colorectal cancer. Pharmacogenetics and Genomics. 2005;15:535–546. doi: 10.1097/01.fpc.0000165904.48994.3d. [DOI] [PubMed] [Google Scholar]
- 36.Barrett J, Fry B, Maller J, Daly M. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21:263–265. doi: 10.1093/bioinformatics/bth457. [DOI] [PubMed] [Google Scholar]
- 37.Gago-Dominguez M, Bell DA, Watson MA, Yuan JM, Castelao JE, Hein DW, et al. Permanent hair dyes and bladder cancer: risk modification by cytochrome P4501A2 and N-acetyltransferases 1 and 2. Carcinogenesis. 2003;24:483–489. doi: 10.1093/carcin/24.3.483. [DOI] [PubMed] [Google Scholar]
- 38.Zheng W, Deitz AC, Campbell DR, Wen WQ, Cerhan JR, Sellers TA, et al. N-Acetyltransferase 1 genetic polymorphism, cigarette smoking, well-done meat intake, and breast cancer risk. Cancer Epidemiol Biomarkers Prev. 1999;8:233–239. [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.