N -acetyltransferase 1 polymorphism and bladder cancer susceptibility: a meta-analysis of epidemiological studies

Abstract

Objective

This meta-analysis was conducted to summarize the association between an N-acetyltransferase 1 (NAT1) gene polymorphism and bladder cancer risk.

Methods

PubMed® and EMBASE databases were searched to identify studies that examined the effect of the NAT1*10 allele on the risk of bladder cancer.

Results

Eleven case–control studies, which included 3311 bladder cancer cases and 3906 control subjects, met the inclusion criteria. The pooled analyses based on all studies showed that there was no significant difference in the NAT1*10 allele between bladder cancer cases and controls (odds ratios [OR] 0.96; 95% confidence interval [CI] 0.81, 1.10). When stratifying for race, the results were similar among Caucasians (OR 0.96; 95% CI 0.81, 1.12) and Asians (OR 0.87; 95% CI 0.48, 1.56). No statistical association was found between the NAT1*10 allele and bladder cancer risk upon stratification for smoking status and study design.

Conclusions

This meta-analysis suggests that there was no association between the NAT1*10 allele and bladder cancer risk. Further research should focus on other potentially functional genetic polymorphisms.

Introduction

Bladder cancer is one of the most common urological malignancies in the world, with an estimated 386,300 new cases and 150,200 deaths worldwide in 2008. ¹ The highest incidence rates of bladder cancer are found in Europe, North America, and Northern Africa. ¹ In European countries, there were an estimated 140,000 new cases of bladder cancer and 50,000 deaths from bladder cancer in 2008. ² It is now commonly accepted that the cause of bladder cancer is a multifactorial interaction between environmental factors (e.g. exposure to certain chemicals, smoking and chronic urinary tract infections) and genetic susceptibility.^3–9

Arylamine N-acetyltransferase (NAT) has two isozymes, NAT1 and NAT2, which are encoded by the NAT1 and NAT2 genes, respectively. ¹⁰ Both of these genes are located on chromosome 8 and they have an open reading frame of 870 base pairs. ¹⁰ The NAT1 gene demonstrates genetic polymorphism in the 3′ untranslated region; known polymorphic alleles are NAT1*4 (wild-type), NAT1*10, NAT1*11 and NAT1*3. ¹¹ The NAT1*10 allele may increase enzyme activity.^12,13 When the NAT1 genotype was compared with the NAT1 phenotype in bladder and colon tissue samples, an approximately twofold higher level of NAT1 enzyme activity was observed in samples taken from individuals who inherited a variant polyadenylation signal (NAT1*10 allele). ¹³ This was the first observation that linked a genetic polymorphism in the NAT1 gene to a particular level of N-acetylation activity in humans. ¹³

Several epidemiological studies have been published from different countries reporting on the association between the NAT1*10 allele and bladder cancer risk,^10,14–24 but there has been no systematic, quantitative assessment of the published findings on this topic. Therefore, this current meta-analysis of the published epidemiological studies was undertaken to clarify the effect of the NAT1*10 allele on the susceptibility to bladder cancer.

Materials and methods

Literature Search Strategy

A systematic search of publications listed in electronic databases (PubMed® and EMBASE) between January 1950 and August 2012 was conducted using the following key words: (‘N-acetyltransferase’ OR ‘NAT’) AND (‘bladder’ OR ‘urinary’ OR ‘urocyst’ OR ‘urotheli*’) AND (‘adenocarcinoma*’ OR ‘carcinoma*’ OR ‘cancer*’ OR ‘tumour*’ OR ‘tumor*’ OR ‘neoplasm*’). Language restrictions were not applied. The list of articles was reviewed independently by two authors (K.W. and X.W.). The reference lists of the selected papers were screened manually for potentially relevant new articles. Furthermore, if more than one paper was published by an identical author using the same case series, the paper with the larger sample size was selected.

Study Selection

Criteria employed to select studies for this meta-analysis were as follows: (i) independent epidemiological studies (for humans only); (ii) a clear description of the NAT1 gene polymorphism in bladder cancer cases and control subjects. Exclusion criteria were: (i) not an original paper (e.g. review or letter); (ii) duplicate publications; (iii) no control subjects.

Data Extraction

Two investigators (K.W. and X.W.) independently extracted all the data from each study. Differences were resolved by a third investigator (Y.L.). The following data were extracted: first author’s last name; publication year; country; study design; predominant racial composition of the study population; number of cancer cases and control subjects with different NAT1 genotypes; smoking status (never, light and heavy smokers) as defined by the individual studies.

Statistical Analyses

Statistical analyses were conducted Stata® software (version 11.0; Stata Corp., College Station, TX, USA). A fixed- or random-effects model was used to calculate the pooled effect estimates depending on statistical heterogeneity. Statistical heterogeneity among the studies was tested with the Q (χ²-test) and I² statistics (a P-value < 0.1 was taken to indicate a statistically significant level of heterogeneity). The crude odds ratios (ORs) were pooled using the random-effects model (DerSimonian and Laird method) when statistical heterogeneity was found (P < 0.1).

Subgroup analyses were performed on the basis of race, study design and smoking status. Publication bias was assessed by visual inspection of the funnel plots, the Begg's rank correlation method and the Egger's weighted regression method.^25,26 A P < 0.05 was considered statistically significant, and all statistical tests were two sided.

Results

The initial review of the electronic databases identified 380 papers. Of these, 346 were excluded, leaving 34 studies for detailed review. Full text assessment resulted in the inclusion of 11 case–control studies in this current meta-analysis, which included 3311 bladder cancer cases and 3906 control subjects (Table 1).^{10,14,16,18–24} The paper by McGrath et al. ²⁰ was considered as two separate studies because it presents findings for the Nurses’ Health Study and Health Professionals’ Follow-up Study populations separately. Of the 11 studies, nine were hospital-based case–control (HCC) studies and two were nested case–control (NCC) studies. Ten studies reported on Caucasian populations and one reported on an Asian population. Studies were carried out in the USA, Italy, Poland, Germany, Spain, Denmark and China.

Table 1.

Major characteristics of the 11 studies selected for a meta-analysis of the relationship between polymorphisms in the arylamine N-acetyltransferase 1 gene (NAT1*10 allele) and susceptibility to bladder cancer.

Author	Year	Study design	Study period	Country	Race	Genotyping method	N cases	N controls	OR	95% CI
Covolo et al. 21	2008	HCC	1997–2000	Italy	Caucasian	PCR–RFLP	197	211	0.65	0.21, 1.99
McGrath et al. 20 NHS	2006	NCC	1976–1990	USA	Caucasian	PCR	78	234	0.76	0.40, 1.42
McGrath et al. 20 HPFS	2006	NCC	1986–1995	USA	Caucasian	PCR	139	293	1.06	0.68, 1.66
Gu et al. 18	2005	HCC	1999–2003	USA	Caucasian	PCR–RFLP	507	513	0.95	0.73, 1.25
García-Closas et al. 19	2005	HCC	1998–2001	Spain	Caucasian	PCR	1150	1149	1.20	0.80, 1.80
Hung et al. 23	2004	HCC	1997–2000	Italy	Caucasian	PCR–RFLP	201	214	0.83	0.55, 1.26
Jaskula-Sztul et al. 14	2001	HCC	DNR	Poland	Caucasian	PCR–RFLP	56	320	1.20	0.70, 2.00
Cascorbi et al. 22	2001	HCC	1994–1998	Germany	Caucasian	PCR–RFLP	425	343	0.53	0.20, 1.40
Hsieh et al. 10	1999	HCC	DNR	China	Asian	PCR–RFLP	74	184	0.87	0.48, 1.56
Taylor et al. 24	1998	HCC	DNR	USA	Caucasian	PCR–RFLP	230	203	1.67	1.13, 2.46
Okkels et al. 16	1997	HCC	1993–1995	Denmark	Caucasian	PCR–RFLP	254	242	1.01	0.45, 2.24

OR, odds ratio; CI, confidence interval; HCC, hospital-based case–control; PCR, polymerase chain reaction; RFLP, restriction fragment length polymorphism; NHS, Nurses’ Health Study; NCC, nested case–control; HPFS, Health Professionals’ Follow-up Study; DNR, data not reported.

The pooled analyses (based on all studies) showed that there was no significant difference in the NAT1*10 allele between bladder cancer cases and control subjects (OR 0.96; 95% confidence interval [CI] 0.81, 1.10) (Table 2) (Figure 1).^{10,14,16,18–24} No statistically significant heterogeneity was observed for the overall test with the I² statistic (I²= 0%; P = 0.475) (Table 2). Furthermore, Begg's rank correlation method and Egger's weighted regression method found no evidence of publication bias in the studies (Begg's test, P = 0.10; Egger's test, P = 0.27).

Figure 1.

Overall results of a meta-analysis of the relationship between polymorphisms in the arylamine N-acetyltransferase 1 gene (NAT1*10 allele) and susceptibility to bladder cancer.^{10,14,16,18–24} ID, identification; OR, odds ratio; CI, confidence interval.

Table 2.

Results of the meta-analysis of the relationship between polymorphisms in the arylamine N-acetyltransferase 1 gene (NAT1*10 allele) and susceptibility to bladder cancer in subgroups stratified according to race, study design and smoking status.^{10,14,16,18–24}

Stratification	No. of studies	OR (95% CI)	Test for heterogeneity a
			P-value	I 2 , %
Race	11	0.96 (0.81,1.10)	NS	0.0
Caucasian	10	0.96 (0.81,1.12)	NS	5.4
Asian	1	0.87 (0.48,1.56)	NA	NA
Study design	11	0.96 (0.81,1.10)	NS	0.0
HCC	9	0.96 (0.79,1.14)	NS	9.8
NCC	2	0.96 (0.56,1.27)	NS	0.0
Smoking status	4	0.96 (0.81,1.10)	NS	0.0
Never	4	1 (reference)	NA	NA
Light	4	1.32 (0.83, 1.80)	NS	0.0
Heavy	4	0.83 (0.26, 1.40)	NS	47.8

a

Statistical test for heterogeneity: NS, not statistically significant, P ≥0.1 for heterogeneity (I² method).

OR, odds ratio; CI, confidence interval; NA, not applicable; HCC, hospital-based case–control; NCC, nested case–control.

When stratifying for race, results were similar among the Caucasian populations (OR 0.96; 95% CI = 0.81, 1.12) and an Asian population (OR 0.87; 95% CI 0.48, 1.56) (Table 2). No statistically significant heterogeneity was observed with the I² statistic among Caucasians (P = 0.39) (Table 2). Stratifying this meta-analysis by study design found no statistical association in the NCC studies (OR 0.96; 95% CI 0.56, 1.27) or HCC studies (OR 0.96; 95% CI 0.79, 1.14) (Table 2). No statistically significant heterogeneity was observed with the I² statistic in the NCC (P = 0.41) or HCC studies (P = 0.35) (Table 2).

Considering that smoking is a risk factor for bladder cancer and that the NAT1 gene is involved in the metabolism of various carcinogens present in smoke, ²⁷ further analyses of a gene-dosage effect according to smoking status (never, light and heavy smokers) of participants were performed. Only four studies provided raw data for the NAT1*10 allele, smoking status and bladder cancer risk.^10,18,23,24 Smoking did not modify the association between the NAT1*10 allele and bladder cancer risk in light (OR 1.32; 95% CI 0.83, 1.80) or heavy smokers (OR 0.83; 95% CI 0.26, 1.40) (Table 2). No statistically significant heterogeneity was observed with the I² statistic in light (P = 0.75) or heavy smokers (P = 0.13) (Table 2).

Discussion

As a powerful statistical method, meta-analysis can help to summarize the effect size of the results from numerous independent epidemiological studies, and thus provide more reliable outcomes. This current meta-analysis of 11 case–control studies, which included 3311 bladder cancer cases and 3906 control subjects, found no association between the NAT1*10 allele and bladder cancer risk. There was also no association between the NAT1*10 allele and bladder cancer risk when stratifying for race, smoking status and study design.

It has been concluded that current cigarette smokers have an approximately three-fold higher risk of urinary tract cancer than nonsmokers. ²⁷ In Europe, approximately half of urinary tract cancer cases among males, and one-third of cases among females, might be attributable to cigarette smoking. ²⁷ Considering that smoking is a risk factor for bladder cancer and that the NAT1 gene is involved in the metabolism of various carcinogens present in smoke, ²⁷ further analyses of a gene-dosage effect according to smoking status (never, light and heavy smokers) of subjects were performed. Smoking did not modify the association between the NAT1*10 allele and bladder cancer risk in light or in heavy smokers. The apparent discrepancy between these findings could be explained as follows: (i) it has now become clear that gene–gene interactions and gene–environmental interactions are ubiquitous and fundamental mechanisms for the development of bladder cancer, but no gene–gene interactions were detected in this study; (ii) it was not possible to obtain information on the main confounders (environmental factors such as diet, occupational exposure to certain carcinogenic chemicals, drinking chlorinated water, arsenic exposure and exposure to hair dyes) from most of the studies; (iii) the definitions of the categories of never, light and heavy smokers were quite different between the studies, which may have contributed to a degree of heterogeneity that was not detected by the I² statistic in the pooled analysis. Therefore, this result regarding the impact of smoking status on the association between the NAT1*10 allele and bladder cancer risk should be interpreted with some caution.

This current meta-analysis has several limitations. First, in terms of the quality of the studies that were included in this meta-analysis, all were undertaken before the ‘Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE Statement’ report was published in 2009, which provides guidance on how to report transparently the findings of genetic association studies. ²⁸ A number of studies included in the current meta-analysis did not meet all of the requirements of the STREGA recommendations. Secondly, it was not possible to perform an adjustment estimate because of the lack of individual patient data. Thirdly, because many environmental factors may affect bladder cancer susceptibility, all of the findings from this current meta-analysis might be due to the context of the genetic background and interactions with multiple environmental factors. Fourthly, the database for this current meta-analysis included limited numbers of studies on ethnic populations; only one study reported on an Asian population, reflecting the current lack of epidemiological studies in non-Caucasian populations. Finally, meta-analysis is just a statistical test that is subject to many methodological restrictions.

To our knowledge, this is the first meta-analysis to provide a quantitative summary of the evidence of the role of the NAT1*10 allele in bladder cancer risk, and the findings suggest that there is no association between the NAT1*10 allele and bladder cancer risk. Further research should focus on other potentially functional genetic polymorphisms.