The role of hereditary polymorphisms of the arylamine N-acetyltransferase 1 (NAT1) gene in the etiology of urinary bladder cancer is controversial. NAT1 is expressed in the urothelium and may O-acetylate hydroxyl amines, particularly in subjects with low NAT2 activity. Thus, NAT1 polymorphisms may affect the individual bladder cancer risk by interacting with environmental factors (smoking and occupational risks) and by interacting with the NAT2 gene. We studied the frequencies of the NAT1 haplotypes *3, *4, *10, *11, *14, *15, *17, and *22 in 425 German bladder cancer patients and 343 controls by PCR-RFLP. NAT1*10 allelic frequency was lower in bladder cancer patients (15.1%) compared with controls (20.4%; P = 0.012). Genotypes that included NAT1*10 were significantly less frequent among the cases (odds ratio adjusted for age, gender, and smoking, 0.65; 95% confidence interval, 0.46–0.91; P = 0.013). Two subtypes of NAT1*11 were detected: *11A (−344T, −40T, 445A, 459A, 640G, and 1095A) and *11C (−344T, −40T, 459A, 640G, and 1095A). The allele frequency of NAT1*11 was 4.3% in the cases versus 3.9% in the controls. The rare low-active NAT1*14A was overrepresented in the cases (P = 0.026). With regard to the NAT2 genotype, our data showed: (a) a partial linkage of NAT1*10 to NAT2*4; (b) a clear underrepresentation of NAT1*10 genotypes among rapid NAT2 genotypes in the cases studied (odds ratio, 0.39; 95% confidence interval, 0.22–0.68; P = 0.001), and (c) a gene-gene-environment interaction. NAT2*slow/NAT1*4 genotype combinations with a history of occupational exposure were 5.96 (2.96–12.0) times more frequent in cancer cases than in controls without risk occupation (P < 0.0001). Hence, our data suggest that individuals provided with NAT2*4 and NAT1*10 are at a significantly lower risk for bladder cancer, particularly when exposed to environmental risk factors.

In humans, N-acetylation and O-acetylation of aromatic amines and some heterocyclic amines are mediated by two arylamine N-acetyltransferases, NAT13 and NAT2, both of which exhibit significant genetic polymorphisms. In early phenotype-based studies, the slow acetylator phenotype turned out to be at a higher risk for cancer of the urinary tract (1, 2, 3). Genotyping studies demonstrated that particularly slow acetylators, who were exposed to cigarette smoke or contamination at the workplace, were at increased risk for urinary bladder cancer (4, 5). As NAT1 but not NAT2 is expressed in the bladder (6), the question arose whether or not the local NAT1 activity contributes to the formation of highly reactive acetoxy esters (7) and whether polymorphic NAT1 genotypes (8) could modulate an individual’s risk to get bladder cancer. Some studies indicated that the NAT1*10 genotype was overrepresented among bladder cancer patients (9, 10) and was associated with increased activity. Moreover, it led to enhanced DNA adduct levels (11). However, until now, published results have been conflicting (12). Recently we were able to show that NAT1*10 does not alter enzyme activity toward ex vivo formation of p-amino benzoic acid, whereas there was a trend toward decreased acetylation rates of the rare NAT1*11 (13). There is evidence that the amino acid replacements Arg187Gln in NAT1*14 and Arg64Trp in NAT1*17 lead to a significant reduction of the enzyme activity, whereas NAT1*15 does not yield an active protein because of the formation of a premature stop codon by Arg187Stop (13, 14, 15). More than 20 human NAT1 haplotypes had been identified until recently (16). In addition to NAT1 alleles *3, *4, *10, *11A, *11B, *14, *15, and *17, we have analyzed allele *22 to cover all common haplotypes expected in Middle Europeans. The functional impact of the Asp251Val exchange in NAT1*22 is not yet clear. The aim of our study was to investigate the frequency of NAT1 and NAT2 genotypes in bladder cancer patients in a case-control study and to elucidate the NAT1/NAT2 as well as the gene-environmental interaction.

Subjects of Investigation.

On the occasion of their first surgery for urinary bladder cancer, 425 mostly incident Caucasian patients (277 males and 148 females; median age, 73; 25th–75th percentiles, 63–80 years) were recruited by the departments of urology at the Benjamin Franklin Medical Center, the Free University of Berlin, and the Krankenhaus Neukölln, Berlin. The control group consisted of 343 patients (220 males and 123 females; median age, 65; range, 56–73 years) from the same catchment area and were hospitalized because of a variety of nonmalignant diseases (4). Patients were selected during the time period 1994–1998; they gave their informed consent, and the study was approved by the Ethics Committee of the Charité University Medical Center. To avoid confounding by ethnicity, only subjects of German extraction were included, as defined by their names, and places of birth. Smoking behavior and occupation were recorded. The total cigarette consumption was expressed in PYs (1 PY = consumption of one pack of 20 cigarettes/day for 1 year). Bladder cancer risk occupations were defined on the basis of epidemiological studies (17, 18) and are given elsewhere (4).

Genotyping Procedure.

DNA was isolated from leukocytes by standard phenol/chloroform extraction. NAT1 genotypes were identified according to Henning et al.(19) with the addition of mutations C190T (as it occurs in NAT1*17), G445A (*11A), C559T (*15), G560A (*14A and *14B), and A752T, which occurs in NAT1 haplotype *22 (Fig. 1).

Apart from T1088A, which was discriminated by allele-specific PCR, all single nucleotide polymorphisms were determined by PCR-RFLP. For A-40T, G560A, and C1095A, mismatch primers were used, introducing restriction-enzyme cleavage sites in dependence on the respective mutation (Table 1). Primer pairs (TIB Molbiol, Berlin, Germany), restriction endonucleases (New England Biolabs, Schwalbach, Germany), and characteristic DNA fragment patterns are given in Table 2. Fragments were separated with 2–3.5% 3:1 NuSieve agarose gels (Biozym, Hessisch-Oldendorf, Germany).

NAT2 genotypes were analyzed essentially as described (20, 21). PCR analyses identified NAT2 mutations G191A, C282T, T341C, C481T, G590A, and A803G, which were finally addressed to alleles *4, *5A, *5B, *5C, *6A, *12A, and *14B, respectively.

Statistics.

The study was of case-control design, with group matching of cases to controls by age and gender. Expected genotype frequencies were calculated by the Hardy-Weinberg equation from the allele frequencies. Odds ratios appeared with 95% CIs and two-sided P, calculated by the χ2 test or Fisher’s exact test when a cell counted <5. Crude odds ratios were calculated from the ratio of specified versus wild-type genotypes in cases compared with the ratio in controls or other strata. Relative risks were computed by multiple logistic regression analysis, with adjustment for age, gender, and NAT genotypes and with smoking and occupational risk as confounding factors. All tests were analyzed using an SPSS 9.0 program.

NAT1 Haplotypes.

Nine haplotypes of NAT1 could be identified (Table 3): Most common was NAT1*4, with 75.3% in bladder cancer patients and 72.4% in controls. Strikingly, NAT1*10 was significantly less frequent in the cases than in the controls (15.1% versus 20.4%). The odds ratio of the allelic frequencies was 0.71 (95% CI, 0.54–0.93; P = 0.012).

NAT1*11 occurred in 4.3% of the cases and in 3.9% of the controls. However, in 1.2% of the cases and 0.4% of the controls, the G445A transition in *11 was lacking. This novel haplotype was assigned to NAT1*11C (GenBank accession no. AF308866). The *11A variant, defined by −344T, −40T, 445A, 459A, 640G, and 1095A, was found in 3.1% of the cases and 2.5% of the controls. An *11 allele with 1095C (*11B) was not observed. de Leon et al.(22) discussed sterical hindrances as the putative reason why G445A had not been detected in the initial sequencing of the NAT1*11(8). However, we have checked this mutation repeatedly by BbsI digest. Only the wild-type 445G resulted in the cleavage of the initial 878-bp fragment into three smaller fragments, and these results could be confirmed by DNA sequencing. The distinction between NAT1*11A and *11C haplotypes revealed no significant differences regarding bladder cancer risk.

Interestingly enough, the low-active NAT1 variant *14A occurred three times more frequently in the cases than in the controls (P = 0.026), although at rather low frequency. Other haplotypes were too rare for statistical analysis. Therefore, all additional analyses were focused on NAT1 alleles *4, *10, and *11.

NAT1 Genotypes.

All genotypes were in Hardy-Weinberg equilibrium; expected frequencies calculated from the allelic frequencies did not differ significantly from observed ones (Table 4). When taking into consideration only the genotypes which included NAT1*4 or NAT1*10, a significant lower frequency of NAT1*4/*10 and *10/*10 in comparison to NAT1*4/*4 was disclosed. The crude odds ratio was 0.64 (95% CI, 0.46–0.89; P = 0.007), the odds ratio adjusted for age, gender, and extent of smoking was 0.65 (95% CI, 0.46–0.91; P = 0.013). There was a 1.53-fold lower risk for carriers of one or two NAT1*10 alleles compared with the wild-type NAT1*4/*4. In females, there was a 2.7-fold reduction of risk (odds ratio, 0.37; 95% CI, 0.21–0.65; P < 0.001), whereas in males an underrepresentation of NAT1*10 that was not significant observed.

There were no differences in the frequency of NAT1 alleles between patients younger or older than the median age. Evaluating gene-environment interactions, a stratification to the extent of smoking and to occupational exposure was performed. The frequencies of NAT1 genotypes were not different in nonsmokers or in the three groups of smokers. However, patients with NAT1*4/*10 or *10/*10 having no occupational risk were at a lower risk for bladder cancer as compared with controls with NAT1 wild-type *4/*4 (odds ratio, 0.60; 95% CI, 0.40–0.89; P = 0.012; Fig. 2).

NAT1*11 genotypes were similarly distributed among the cases and the controls (adjusted odds ratio, 0.88; 95% CI, 0.45–1.73; P = 0.71). Stratification to gender, age, smoking, or risk occupation also revealed no significant diversity (Fig. 3).

When NAT1 ex vivop-amino salicylic acid acetylation was measured, NAT1 alleles *14 and *15 were associated with a significant reduction of the enzyme activity (13). NAT1*17 and *22 are also assumed to provide low activity (14). In cancer patients, there was a slight overrepresentation of these rare slow NAT1 variants (4.7% versus 2.3%), which, however, did not reach statistical significance (crude odds ratio, 2.07; P = 0.081) and which was even smaller when the odds ratio was adjusted for age, gender, and smoking (odds ratio, 1.81; P = 0.18). The number, however, was too low to study the gene-gene interaction with NAT2.

Combination with NAT2.

As shown in an earlier publication (4), slow NAT2 acetylators were statistically significantly overrepresented when the odds ratio was adjusted for age, gender, smoking habits, and occupational exposure by logistic regression analysis. In this study, their relative risk was 1.36; a 95% CI of 0.99–1.86 and a P = 0.058 was of marginal statistical significance, with a crude odds ratio of 1.29 (95% CI, 0.96–1.73; P = 0.088). For smokers with more than 20 PYs and for subjects with exposure to occupational risks, relative risk adjusted for age and gender, 95% CI, and P were 1.70, 1.09–2.65, and 0.019 and 1.87, 1.02–3.43, and 0.042, respectively.

A cross table of NAT1*4 and *10 genotypes versusNAT2 genotypes disclosed a partial linkage of NAT1*10 with NAT2*4 (P < 0.001). The distribution of NAT1*10 among slow and rapid NAT2 acetylators differed drastically. Among slow NAT2 acetylators, an equal distribution of NAT1*4/*10 between the cases (26.2%) and the controls (26.7%) was found. In rapid NAT2 acetylators, 32.2% of the cases and 51.3% of the controls carried NAT1*4/*10. The odds ratio of NAT1*4/*10 compared with NAT1*4/*4 was as low as 0.39 (95% CI, 0.22–0.68; P = 0.001; Table 5).

A logistic regression analysis including age, gender, PYs, occupational risk, as well as presence of NAT1*10 and NAT2 acetylator status, revealed a relative risk for NAT1*10 carriers of 0.71 (95% CI, 0.51–0.99; P = 0.047) and of 1.29 (95% CI, 0.93–1.77; P = 0.12), for slow NAT2 acetylators, thus indicating the significant impact of NAT1*10 on urinary bladder cancer risk.

Testing for gene-gene-interactions, NAT1 genotypes (NAT1*4*/10* or NAT2*4/*4) combined with NAT2 (*4/slow or NAT2*4/*4) were clearly less frequent than NAT1*4/*4 combined with NAT2*slow/slow (crude odds ratio, 0.50; 95% CI, 0.33–0.76; P = 0.001). Adjustment for age and gender revealed an odds ratio of 0.43, a 95% CI of 0.28–0.67, and a P = 0.0001. Thus the bladder cancer risk for slow acetylators combined with NAT1*4 was increased 2.3 times compared with rapid acetylators with NAT1*10 genotypes.

In the next step we tested for gene-gene-environment interactions. Multiple logistic regression analysis revealed no additional impact of smoking, but in the group of patients with a history of occupational exposure to hazardous compounds, NAT2*slow/NAT1*4 were 5.96 (95% CI, 2.96–12.0) more frequent than in controls with risk occupation (P < 0.0001). With testing extremes (occupational exposure and smoking versus no environmental risk factors), an adjusted odds ratio of 4.15 (95% CI, 1.95–8.83; P = 0.0002) was calculated (Table 6).

NAT2 and Bladder Cancer.

Low NAT2 activity is doubtless a risk factor for bladder cancer, particularly for those individuals who smoke or who are exposed to specific occupational hazards (23). A meta-analysis of studies totaling 2000 European cases and 2500 controls showed a slight, but statistically significant, overrepresentation of NAT2 slow acetylators (odds ratio, 1.4; 95% CI, 1.2–1.6; Ref. 24).

According to the current theory of the role of N-acetyltransferases in bladder cancer etiology, a decrease in arylamine N-acetylation rates in the liver enforces N-hydroxylation mediated by cytochrome P4501A2, which in turn leads to increased concentrations of hydroxyl amines in the urinary bladder (25). Local O-acetylation by the N-acetyltranferases, expressed in the urothelium (6) would subsequently produce aromatic acetoxy esters, which may disintegrate into highly reactive nitrenium ions (7, 8, 26). These intermediates can react nonspecifically with the urinary bladder epithelium by the formation of adducts (27).

Role of NAT1*10 in Bladder Cancer.

When the polymorphic character of NAT1 was disclosed (28), the question arose whether highly active NAT1 isoforms could modulate the risk of bladder cancer or could modify the consequence of slow NAT2-mediated acetylation. NAT1*10 was suspected of leading to higher enzymatic activity than NAT1*4 in the colon, the bladder (9), and the liver (29), thus possibly causing increased adduct rates in these tissues (11). We, therefore, based the present study on the working hypothesis that NAT1*10-mediated enzyme activity affects the individual’s risk for urinary bladder cancer.

As reviewed by Hirvonen (30), the results of other studies on the role of NAT1 are conflicting, thus making it difficult to understand the functional significance of different NAT1 alleles in certain types of cancer. In contrast to positive findings (10), some studies showed no evidence of an association of NAT1 genotypes with cancer of the bladder (12), colon (31, 32), or larynx (19). Moreover, phenotypic ex vivo experiments using p-amino salicylic acid as a substrate did not prove an increased acetylation activity in carriers of NAT1*10 compared with wild-type NAT1*4 carriers (13, 15).

Role of Other NAT1 Alleles.

NAT1*14, as well as *17 and *22 are associated with low enzyme activity in in vitro experiments (33), and NAT1*15 carriers lack enzyme activity at all. One-third of all NAT1*11 alleles among bladder cancer patients and 20% of controls lacked the G455A single nucleotide polymorphism, designated as the novel allele *11C. It is still unclear how NAT1*11C affects enzyme activity. G445A, absent in haplotypes *11A and *11B, codes for a replacement of Val/Ile at codon 149. In vitro experiments showed increased activity of the isolated 149 Ile variant (12), whereas ex vivo acetylation of p-amino benzoic acid was slightly decreased by NAT1*11 (13).

Linkage of NAT1 to NAT2.

The linkage disequilibrium of the NAT1*10 to the rapid NAT2*4 haplotype, which we observed in our sample, confirms the results of at least two other studies (19, 33). Because of the short distance of 170–360 kb on chromosome 8p21.3–23.1 (34), such a cosegregation of defined NAT1/NAT2 traits is not unlikely. The frequency of NAT1*10 alleles did not differ in the cases and in the controls with slow NAT2 genotypes (25.0% versus 27.6%), however, NAT1*10 alleles were considerably less frequent in the patient group with rapid NAT2 genotypes (33.8 versus 50.3%; P = 0.003). A disequilibrium of the distribution of NAT1*10 was also detected in a sample of 240 young healthy volunteers genotyped for NAT1 (26.4% in slow acetylators and 51.9% in rapid NAT2 genotypes; data not shown).

In a second step, we analyzed only samples with NAT1*4/*4, *4/*10, and *10/*10 (Table 5). Among rapid NAT2 acetylators, only 36.4% of the cases but 58.1% of the controls carried NAT1*4/*10 or *10/*10 (odds ratio, 0.41; 95% CI, 0.24–0.70; P = 0.001). This underrepresentation of NAT1*10/*10 and NAT1*4/*10 in rapidly acetylating patients suggests a linkage between NAT2*4 and NAT1*10 in bladder cancer etiology.

In an American study (10), the distribution of NAT1*10 among slow and rapid NAT2 acetylators in 191 white controls was similar to the distribution in our study (21.2% versus 48.3%), whereas in the 205 bladder cancer patients, NAT1*10 carriers were overrepresented among the slow NAT2 genotypes (34.7% versus 50.5%).

The theory of the implication of NAT1/NAT2 combinations in the etiology of cancer is supported by studies of colon cancer patients. Rapid acetylation seems to augment the risk of colon cancer (35), particularly in individuals who have NAT2*4 and NAT1*10 and who consume considerable amounts of red meat (36).

In our study, carriers of NAT2*4 and NAT1*10 were protected from bladder cancer, thus contradicting initial observations (9, 10). Particularly subjects with occupational hazards were at increased risk (adjusted odds ratio, 5.96; P < 0.0001). The data suggest that earlier findings on the association of slow NAT2 acetylators with bladder cancer risk should be reconsidered with respect to the role of NAT1*10. It is possible that our results are also partly attributable to our consideration of haplotypes other than *3, *4, *10, and *11, as determined by Taylor et al.(10), although it is not very likely that additional undiscovered alleles may exist. In fact, carriers of low-active NAT1 variants such as *14, *15, *17, and *22 were slightly (although not significantly) overrepresented among bladder cancer patients.

In summary, our data suggest that individuals provided with NAT2*4 and NAT1*10 are at a significantly lower risk for bladder cancer, particularly when exposed to environmental risk factors. However, the etiology of bladder cancer remains difficult to understand with respect to polymorphisms of xenobiotic metabolizing enzymes (37).

Fig. 1.

Common NAT1 polymorphisms investigated in this case-control study and resulting amino acid changes.

Fig. 1.

Common NAT1 polymorphisms investigated in this case-control study and resulting amino acid changes.

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Fig. 2.

Association of NAT1*10-consisting NAT1-genotypes to urinary bladder cancer in different subgroups stratified to gender, median age, cigarette consumption, and occupational risk (odds ratios given with 95% CIs). Number of individuals given for cases/controls.

Fig. 2.

Association of NAT1*10-consisting NAT1-genotypes to urinary bladder cancer in different subgroups stratified to gender, median age, cigarette consumption, and occupational risk (odds ratios given with 95% CIs). Number of individuals given for cases/controls.

Close modal
Fig. 3.

Association of NAT1*11-consisting NAT1-genotypes to urinary bladder cancer in different subgroups stratified to gender, median age, cigarette consumption, and occupational risk (odds ratios given with 95% CIs). Number of individuals given for cases/controls.

Fig. 3.

Association of NAT1*11-consisting NAT1-genotypes to urinary bladder cancer in different subgroups stratified to gender, median age, cigarette consumption, and occupational risk (odds ratios given with 95% CIs). Number of individuals given for cases/controls.

Close modal

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1

Supported by Grant 01 GG 9845/5 from the German Federal Ministry of Education, Science, Research, and Technology.

3

The abbreviations used are: NAT1, arylamine N-acetyltransferase 1; NAT2, arylamine N-acetyltransferase 2; PY, pack year; CI, confidence interval.

Table 1

Oligonucleotide primers used for amplification of the entire NAT1 gene and of smaller fragments, enabling reliable detection of point mutations

NameaBinding positionsFragment length (bp)Sequence
N1-1F −415–−394 1540 5′-GAA ATT GAG TGG GTC AGG TAC C 
N1-5R 1125–1106  5′-TTC CAA GAT AAC CAC AGG CC 
N1-IR −7–−39 409 (with N1-1F) 5′-CTA AGC AAG GAA AAC AAA ACG AAA GCA AAT AAT 
N1-5F 691–710 435 5′-GTT CAC TGT TTG GTG GGC TT 
N1-IIR 1125–1096  5′-TTC CAA GAT AAC CAC AGG CCA TCT TTA GAA 
N1-6R 1108–1088 418 (with N1-5F) 5′-GCC ATC TTT AAA ATA CAT TTA 
N1-7R 1108–1088  5′-GCC ATC TTT AAA ATA CAT TTT 
N1-4F 344–364 247 5′-ATG GCA GGA ACT ACA TTG TCG 
N1-IIIR 561–590  5′-CGA GGC TTA AGA GTA AAG GAG TAG ATG TC
N1-8F −16–4 878 5′-TCC TTG CTT AGG GGA TCA TG 
N1-8R 861–840  5′-AAA TCT ATC ACC ATG TTT GGG C 
NameaBinding positionsFragment length (bp)Sequence
N1-1F −415–−394 1540 5′-GAA ATT GAG TGG GTC AGG TAC C 
N1-5R 1125–1106  5′-TTC CAA GAT AAC CAC AGG CC 
N1-IR −7–−39 409 (with N1-1F) 5′-CTA AGC AAG GAA AAC AAA ACG AAA GCA AAT AAT 
N1-5F 691–710 435 5′-GTT CAC TGT TTG GTG GGC TT 
N1-IIR 1125–1096  5′-TTC CAA GAT AAC CAC AGG CCA TCT TTA GAA 
N1-6R 1108–1088 418 (with N1-5F) 5′-GCC ATC TTT AAA ATA CAT TTA 
N1-7R 1108–1088  5′-GCC ATC TTT AAA ATA CAT TTT 
N1-4F 344–364 247 5′-ATG GCA GGA ACT ACA TTG TCG 
N1-IIIR 561–590  5′-CGA GGC TTA AGA GTA AAG GAG TAG ATG TC
N1-8F −16–4 878 5′-TCC TTG CTT AGG GGA TCA TG 
N1-8R 861–840  5′-AAA TCT ATC ACC ATG TTT GGG C 
a

F, forward primer; R, reverse primer; roman numerals, designed primers; mismatch base is indicated in italic bold.

Table 2

Restriction endonucleases used for recognition of NAT1 mutations

Single nucleotide polymorphismRestriction enzymeAmplification with primersFragment length
Wild type Mutation
C-344T MaeII N1-1F /N1-IR 71 338 
  or TaiI  409 
A-40T SspI N1-1F /N1-IR 409 
   376 33 
C190T Tsp590I N1-8F /N1-8R 358 139 129 110 73 43 26 
   224 139 134 129 110 73 43 26 
G445A BbsI N1-8F /N1-8R 455 310 113 
   568 310 
G459A BslI N1-1F /N1-5R 406 324 278 230 160 141 1 
   554 406 278 160 141 1 
C559T DdeI N1-4F/N1-IIIR 159 88 
   127 88 32 
G560A Alw26I N1-4F/N1-IIIR 211 36 
   247 
T640G AlwNI N1-1F /N1-5R 817 723 
   817 482 241 
A752T Bg/II N1-8F /N1-8R 767 111 
   878 
C1095A BbsI N1-5F /N1-IIR 396 39 
   435 
Single nucleotide polymorphismRestriction enzymeAmplification with primersFragment length
Wild type Mutation
C-344T MaeII N1-1F /N1-IR 71 338 
  or TaiI  409 
A-40T SspI N1-1F /N1-IR 409 
   376 33 
C190T Tsp590I N1-8F /N1-8R 358 139 129 110 73 43 26 
   224 139 134 129 110 73 43 26 
G445A BbsI N1-8F /N1-8R 455 310 113 
   568 310 
G459A BslI N1-1F /N1-5R 406 324 278 230 160 141 1 
   554 406 278 160 141 1 
C559T DdeI N1-4F/N1-IIIR 159 88 
   127 88 32 
G560A Alw26I N1-4F/N1-IIIR 211 36 
   247 
T640G AlwNI N1-1F /N1-5R 817 723 
   817 482 241 
A752T Bg/II N1-8F /N1-8R 767 111 
   878 
C1095A BbsI N1-5F /N1-IIR 396 39 
   435 
Table 3

NAT1 mutations determined in 425 urinary bladder cancer patients compared to 343 controls and designation to NAT1 haplotypes

AlleleNucleotide at position (nt)CasesControlsORaP
−344−4019044545955956064075210881095%b%b
*3 A 3.1 3.1 1.04 NSc 
*4 75.3 72.4 1.00  
*10 A A 15.1 20.4 0.71 0.012 
*11A T T A A G A 3.1 2.5 1.19 NS 
*11C T T A G A 1.2 0.4 2.59 NS 
*14A A A A 1.9 0.6 3.11 0.034 
*15 T 0.2 0.0   
*17 T 0.2 0.1 1.55 NS 
*22 T 0.0 0.4   
AlleleNucleotide at position (nt)CasesControlsORaP
−344−4019044545955956064075210881095%b%b
*3 A 3.1 3.1 1.04 NSc 
*4 75.3 72.4 1.00  
*10 A A 15.1 20.4 0.71 0.012 
*11A T T A A G A 3.1 2.5 1.19 NS 
*11C T T A G A 1.2 0.4 2.59 NS 
*14A A A A 1.9 0.6 3.11 0.034 
*15 T 0.2 0.0   
*17 T 0.2 0.1 1.55 NS 
*22 T 0.0 0.4   
a

OR, odds ratio. ORs refer to wild-type allele NAT1*4.

b

Percent of alleles (i.e., 850 in cases and 686 in controls).

c

NS, not significant.

Table 4

Frequency distribution of NAT1 genotypes among 425 urinary bladder cancer patients and 343 controls

Expected frequencies are calculated from the allelic frequencies (Table 1) by the Hardy-Weinberg law.
Bladder cancerControls
NAT1 genotypeObservedObserved
 n n Expected % 
*3/*3 0.2 0.3 0.1 
*3/*4 18 4.2 14 4.1 4.4 
*3/*10 0.7 1.5 1.2 
*3/*11A 0.2 0.0 0.2 
*3/*11C 0.2 0.0 0.0 
*3/*14A 0.2 0.0 0.0 
*4/*4 241 56.7 175 51.0 52.5 
*4/*10 98 23.1 108 31.5 29.6 
*4/*11A 22 5.2 16 4.7 3.6 
*4/*11C 1.9 0.6 0.6 
*4/*14A 11 2.6 0.9 0.8 
*4/*17 0.2 0.3 0.2 
*4/*22 0.0 0.9 0.6 
*10/*10 1.9 12 3.5 4.2 
*10/*11A 0.7 0.3 1.0 
*10/*11C 0.2 0.3 0.2 
*10/*14A 0.9 0.3 0.2 
*10/*15 0.5 0.0 0.0 
*10/*17 0.2 0.0 0.1 
 ND     0.4 
 Total 425 100.0 343 100.0 100.0 
Expected frequencies are calculated from the allelic frequencies (Table 1) by the Hardy-Weinberg law.
Bladder cancerControls
NAT1 genotypeObservedObserved
 n n Expected % 
*3/*3 0.2 0.3 0.1 
*3/*4 18 4.2 14 4.1 4.4 
*3/*10 0.7 1.5 1.2 
*3/*11A 0.2 0.0 0.2 
*3/*11C 0.2 0.0 0.0 
*3/*14A 0.2 0.0 0.0 
*4/*4 241 56.7 175 51.0 52.5 
*4/*10 98 23.1 108 31.5 29.6 
*4/*11A 22 5.2 16 4.7 3.6 
*4/*11C 1.9 0.6 0.6 
*4/*14A 11 2.6 0.9 0.8 
*4/*17 0.2 0.3 0.2 
*4/*22 0.0 0.9 0.6 
*10/*10 1.9 12 3.5 4.2 
*10/*11A 0.7 0.3 1.0 
*10/*11C 0.2 0.3 0.2 
*10/*14A 0.9 0.3 0.2 
*10/*15 0.5 0.0 0.0 
*10/*17 0.2 0.0 0.1 
 ND     0.4 
 Total 425 100.0 343 100.0 100.0 

a ND, not detected.

Table 5

Distribution of NAT1*4 and *10 genotypes among slow and rapid NAT2 acetylator genotypes

NAT2 genotypeNAT1 genotypeCases %Controls %Odds ratioa95% CIP
All NAT1*4/*4 69.5 59.2 1.00   
n = 347 cases NAT1*4/*10 28.2 36.7 0.66 0.47–0.94 0.02 
n = 289 controls NAT1*10/*10 2.3 4.2 0.53 0.20–1.40 0.20 
Slow NAT1*4/*4 72.5 70.9 1.00   
n = 229 cases NAT1*4/*10 26.2 26.7 1.04 0.65–1.66 0.86 
n = 172 controls NAT1*10/*10 1.3 2.3 0.75 0.15–3.87 0.73 
Rapid NAT1*4/*4 63.6 41.9 1.00   
n = 118 cases NAT1*4/*10 32.2 51.3 0.39 0.22–0.68 0.001 
n = 117 controls NAT1*10/*10 4.2 6.8 0.42 0.12–1.46 0.17 
NAT2 genotypeNAT1 genotypeCases %Controls %Odds ratioa95% CIP
All NAT1*4/*4 69.5 59.2 1.00   
n = 347 cases NAT1*4/*10 28.2 36.7 0.66 0.47–0.94 0.02 
n = 289 controls NAT1*10/*10 2.3 4.2 0.53 0.20–1.40 0.20 
Slow NAT1*4/*4 72.5 70.9 1.00   
n = 229 cases NAT1*4/*10 26.2 26.7 1.04 0.65–1.66 0.86 
n = 172 controls NAT1*10/*10 1.3 2.3 0.75 0.15–3.87 0.73 
Rapid NAT1*4/*4 63.6 41.9 1.00   
n = 118 cases NAT1*4/*10 32.2 51.3 0.39 0.22–0.68 0.001 
n = 117 controls NAT1*10/*10 4.2 6.8 0.42 0.12–1.46 0.17 
a

Adjusted for age, gender, and extent of smoking.

Table 6

Gene-gene interaction and gene-gene-environment interaction of NAT1 and NAT2 genotypes

Environmental risk (no. of cases/controls)aNAT2 genotypeNAT1 genotypebCases %Controls %Odds ratioc95% CIP
 Slow All 63.2 56.7 1.35 1.00–1.84 0.051 
(425/337) Rapid All 36.8 43.3 1.00d   
 Slow NAT1*4 47.3 41.2 2.09 1.36–3.22 0.001 
(425/337) Rapid NAT1*10 12.5 21.7 1.00d   
Smoking Slow NAT1*4 50.5 40.9 2.06 1.26–3.36 0.004 
(297/254) Rapid NAT1*10 13.1 21.7 1.00d   
Nonsmoking Slow NAT1*4 37.2 42.7 2.37 0.92–6.06 0.07 
(121/82) Rapid NAT1*10 10.7 22.0 1.00d   
Smoking vs. nonsmoking     1.81 1.22–2.69 0.003 
Occupational exposure Slow NAT1*4 46.8 36.5 2.42 0.99–5.56 0.054 
(156/63) Rapid NAT1*10 10.9 19.9 1.00d   
No occupational exposure Slow NAT1*4 46.5 42.5 1.90 1.14–3.17 0.014 
(260/252) Rapid NAT1*10 13.5 23.0 1.00d   
Occupational exposure vs. no occupational exposure     5.96 2.96–12.0 <0.0001 
Occupational exposure + smoking Slow NAT1*4 50.8 33.3 2.58 0.93–7.09 0.067 
(126/51) Rapid NAT1*10 11.9 19.6 1.00d   
No occupational exposure + nonsmoking Slow NAT1*4 39.6 41.9 2.14 0.78–5.86 0.14 
(91/62) Rapid NAT1*10 12.1 24.2 1.00d   
Occupational exposure + smoking vs. no occupational exposure + nonsmoking     4.15 1.95–8.83 0.0002 
Environmental risk (no. of cases/controls)aNAT2 genotypeNAT1 genotypebCases %Controls %Odds ratioc95% CIP
 Slow All 63.2 56.7 1.35 1.00–1.84 0.051 
(425/337) Rapid All 36.8 43.3 1.00d   
 Slow NAT1*4 47.3 41.2 2.09 1.36–3.22 0.001 
(425/337) Rapid NAT1*10 12.5 21.7 1.00d   
Smoking Slow NAT1*4 50.5 40.9 2.06 1.26–3.36 0.004 
(297/254) Rapid NAT1*10 13.1 21.7 1.00d   
Nonsmoking Slow NAT1*4 37.2 42.7 2.37 0.92–6.06 0.07 
(121/82) Rapid NAT1*10 10.7 22.0 1.00d   
Smoking vs. nonsmoking     1.81 1.22–2.69 0.003 
Occupational exposure Slow NAT1*4 46.8 36.5 2.42 0.99–5.56 0.054 
(156/63) Rapid NAT1*10 10.9 19.9 1.00d   
No occupational exposure Slow NAT1*4 46.5 42.5 1.90 1.14–3.17 0.014 
(260/252) Rapid NAT1*10 13.5 23.0 1.00d   
Occupational exposure vs. no occupational exposure     5.96 2.96–12.0 <0.0001 
Occupational exposure + smoking Slow NAT1*4 50.8 33.3 2.58 0.93–7.09 0.067 
(126/51) Rapid NAT1*10 11.9 19.6 1.00d   
No occupational exposure + nonsmoking Slow NAT1*4 39.6 41.9 2.14 0.78–5.86 0.14 
(91/62) Rapid NAT1*10 12.1 24.2 1.00d   
Occupational exposure + smoking vs. no occupational exposure + nonsmoking     4.15 1.95–8.83 0.0002 
a

History of occupational exposure or smoking was lacking in some subjects.

b

NAT1*4 genotypes summarize all genotypes, but *10, NAT1*10 comprises hetero- and homozygotes.

c

Adjusted for age and gender.

d

Reference.

We are grateful for the skillful technical assistance of Hannelove Maszynski, Petra Pietsch, and Petra Lohse.

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