|Home | About | Journals | Submit | Contact Us | Français|
Background: Many associations between common genetic polymorphisms and complex diseases have not been replicated. One of the few exceptions may be the association between NAT2 slow acetylation, GSTM1 null genotype and bladder cancer risk. However, current evidence is based on meta-analyses of relatively small studies (range 23-374 cases) with some evidence of publication bias and study heterogeneity. Associations between polymorphisms in other NAT and GST genes and bladder cancer risk have been inconsistent.
Methods: We evaluated polymorphisms in NAT2, GSTM1, NAT1, GSTT1, GSTM3 and GSTP1 in 1,150 patients with transitional cell carcinoma of the urinary bladder and 1,149 control subjects of Caucasian origin in Spain. We also carried out meta-analyses of NAT2, GSTM1 and bladder cancer which included more than twice the number of cases in previous reports.
Findings: In our study, the relative risks of bladder cancer for subjects with deletion of one or two (null genotype) copies of the GSTM1 gene were 1.2 (95% CI 0.8-1.7) and 1.9 (1.4-2.7), respectively (p-trend=3×10−8). Compared to NAT2 rapid/intermediate acetylators, NAT2 slow acetylators had an increased overall risk of bladder cancer (1.4 (95% CI 1.2-1.7)) that was stronger for cigarette smokers than for never smokers (p-interaction = 0.008). No significant associations were found with the other polymorphisms. Meta-analyses showed that the overall association for NAT2 was robust (p=5×10−8) and case-only meta-analyses provided support for a NAT2-smoking interaction (p-interaction=0.008). The overall association for GSTM1 also was robust (p=9×10−15) and was not modified by smoking status (p=0.86).
Interpretation: The GSTM1 null genotype increases the overall risk of bladder cancer, and the NAT2 slow acetylator genotype increases risk particularly among cigarette smokers. Although relative risks are modest, these polymorphisms could account for up to 30% of bladder cancer cases because of their high prevalence. These findings provide some of the most compelling evidence to date for the role of common polymorphisms in the etiology of cancer, and illustrate the need for large and rigorous investigations to establish effects.
Lack of replication for many associations between common genetic polymorphisms and complex diseases has raised skepticism in this field of research (1). One of the few exceptions may be the association between bladder cancer risk with polymorphisms in two carcinogen detoxification genes, NAT2 slow acetylation and GSTM1 null genotype. However, evidence for an association relies on pooled and meta-analyses of relatively small studies (range 23-374 cases, average size of about 100 cases per study) and concerns have been raised about publication bias and heterogeneity of results (2-9). Tobacco smoking is an important cause of bladder cancer (10) and previous analyses have suggested that the relative risk for smoking is stronger for NAT2 slow than rapid/intermediate acetylators (2;5;11). This interaction is biologically plausible since aromatic amines are thought to be the primary bladder carcinogen in tobacco smoke (12) and are detoxified by NAT2 (13). However, epidemiologic evidence for this interaction is even weaker than for the overall genotype association. Also, the GSTM1 genotype does not seem to modify the relative risk for smoking according to previous studies (8). Associations between bladder cancer risk and polymorphisms in other carcinogen detoxification genes such as NAT1 and other glutathione S-transfereases have been less frequently explored with inconsistent results across studies (14-33).
Here, we report results on the associations of polymorphisms in NAT and GST genes with bladder cancer risk and their interaction with cigarette smoking among subjects participating in the Spanish Bladder Cancer Study. This is the first study of bladder cancer that has adequate statistical power to rigorously evaluate the proposed associations between genetic variation in NAT2, GSTM1 and bladder cancer risk, as well as to study interactions with smoking habits. We also conduct meta-analyses of NAT2, GSTM1, smoking and bladder cancer that include more than twice the number of cases than in previous reports.
The Spanish Bladder Cancer Study is a hospital-based case-control study conducted in 18 hospitals from five different areas in Spain (i.e., Asturias, Barcelona metropolitan area, Vallès/Bages, Alicante, and Tenerife). Cases were patients newly diagnosed with histologically confirmed carcinoma of the urinary bladder in 1998-2001, aged 21-80 years. Diagnostic slides from each case were reviewed by a panel of expert study pathologists to confirm diagnosis and ensure uniformity of classification criteria, based on the 1998 World Health Organization/International Society of Urological Pathology system (34).
Controls were selected from patients admitted to participating hospitals for diagnoses believed to be unrelated to the exposures of interest such as tobacco use. The distribution of reasons for hospital admission was: 37% hernias, 11% other abdominal surgery, 23% fractures, 7% other orthopedic conditions, 12% hydrocele, 4% circulatory conditions, 2% dermatological conditions, 1% ophthalmologic conditions, 3% other diseases. Controls were individually matched to the cases on age at interview within 5 year categories, gender, ethnicity and region. Information on known or potential bladder cancer risk factors for cases and controls was collected using computer-assisted personal interviews during the hospital admission. Eighty-four percent of eligible cases and 88 % of eligible controls agreed to participate in the study and were interviewed. Of the 1,219 cases and 1,271 controls interviewed, 1,188 (97.5 %) cases and 1,173 (92.3%) controls provided a blood or buccal cell sample for DNA extraction. Seven cases and 11 controls were excluded because of low amounts of DNA. To reduce heterogeneity, 16 cases with neoplasias of non-transitional histology, and 6 non-white subjects (5 cases and 1 control) were excluded from the analyses. Fifteen subjects (7 cases and 8 controls) with missing smoking status information and 7 subjects (3 cases and 4 controls) with DNA quality control problems were also excluded from the analyses. Thus, the final study population available for analysis included 1,150 cases and 1,149 controls, all of whom were Caucasians.
Subjects were categorized as never smokers if they smoked less than 100 cigarettes in their lifetime and ever smokers otherwise. Ever smokers were further classified as regular smokers if they smoked one cigarette per day for 6 months or longer and occasional smokers otherwise. Regular smokers were classified as current smokers if they smoked within a year of the reference date and former smokers otherwise. Smokers of black tobacco alone, black and blond tobacco, and unknown tobacco type had similarly elevated bladder cancer risks compared to never smokers (data not shown), and were grouped as known or likely black tobacco smokers. We obtained informed consent from potential participants in accordance with the National Cancer Institute and local Institutional Review Boards.
DNA for genotype assays was extracted from leukocytes using the Puregene® DNA Isolation Kit (Gentra Systems, Minneapolis, MN) for most cases (N=1,107) and controls (N=1,032) included in the analysis. DNA from additional 43 cases and 117 controls was extracted from mouthwash samples using phenol-chloroform. Genotype assays were performed at the core genotyping facility of the Division of Cancer Epidemiology and Genetics, National Cancer Institute using Applied Biosystems TaqMan® (Foster City, CA), Epoch Biosciences MGB Eclipse® (Bothel, WA), or Sequenom MASSArray® (San Diego, CA) assays. Description and methods for each specific assay can be found at http://snp500cancer.nci.nih.gov. Genotype assays were performed for NAT1 (Ex1-88A>T rs1057126, Ex1-81A>C rs15561, V149I rs4987076, R187Q rs4986782, R187* rs5030839, R33*, D251V, R64W), NAT2 (K268R rs1208, G286E rs1799931, R64Q rs1801279, Y94Y rs1041983, I114T rs1801280, L161L rs1799929, R197Q rs1799930), GSTM1 deletion (SNP500Cancer ID - GSTM1-02), GSTT1 deletion (SNP500Cancer ID - GSTT1-02), GSTP1 (I105V rs947894, A114V) and GSTM3 (V224I rs7483, IVS7 -30G>T rs1537234). All genotypes under study were in Hardy-Weinberg equilibrium among the control population. Duplicate quality control samples showed 100% agreement for all assays, except for four assays (range 98.2% to 99.6%).
Information from the NAT1 and NAT2 SNPs analyzed in this study was used to assign the most likely NAT1 and NAT2 alleles previously identified in human populations (35) (updated at www.louisville.edu/medschool/pharmacology/NAT.html). Individuals homozygous for rapid NAT2 acetylator alleles (NAT2*4, NAT2*11A, NAT2*12A, NAT2*12B, NAT2*12C, NAT2*13) were classified as rapid acetylator phenotype; individuals homozygous for slow acetylator alleles were classified as slow acetylator phenotype and heterozygous individuals (one rapid and one slow NAT2 allele) were classified as intermediate acetylator phenotype. Subjects with missing information for four rare NAT1 SNPs (R187*, R33*, D251V and R64W with > 99% homozygous wild-type subjects) were assumed to be *4/*4. Based on previous studies, the NAT1*10 allele was considered the “at risk” allele. The two GSTP1 (I105V and A114V) and GSTM3 (V224I and IVS7 -30G>T) genotypes evaluated were in strong linkage disequilibrium (D'=1.0, R2=0.10 and D'=1.0, R2=0.68, respectively). Subjects were classified according to the presence of three GSTP1 variants that have been found to encode functionally different GSTP1 proteins: GSTP1*A (105 Ile; 114Ala), GSTP1*B (105 Val; 114 Ala) and GSTP1*C (105 Val; 114 Val) (36).
Odds ratios (OR), as measure of relative risk, and 95% confidence intervals (95%CI) were estimated using logistic regression models, adjusting for gender, age at interview, region, and smoking status defined as never, occasional, former and current smoker categories. These unconditional models provided estimates similar to conditional logistic regression models for individually matched pairs. Interactions between genotypes and smoking habits were also evaluated using semi-parametric maximum likelihood estimator (SPMLE) (37) to allow estimation of parameters under the assumption of genotype-smoking and genotype-gender independence in the source population. This assumption is supported by strong evidence from previous studies for independence of NAT2 and GSTM1 genotypes from cigarette smoking status (8;11;38) and gender (38) in the general population. Tests for multiplicative interaction were used to evaluate if the genotype ORs within categories of smoking habits were significantly different from each other, or if smoking ORs within genotype categories were significantly different from each other. We also tested for additive interactions since departures from the additive model may have biological implications under certain biological models (39). The synergy index was used as a measure of additive interaction and its confidence interval was calculated using previously published formulae (40).
We updated previous meta-analyses on NAT2, GSTM1 and bladder cancer following similar study selection criteria, i.e. case-control studies conducted in the general population (4;8;11). Relevant studies published through February 2005 were identified in a Medline search. Random-effects summary measures were calculated by weighting each study result by a factor of within- and between-study variance (41). Homogeneity of study results in different groups was assessed by the Q statistic and publication bias by Begg (42) and Egger's tests (43). A case-only design (44) was used in meta-analyses performed to assess the presence of a multiplicative interaction between NAT2 and GSTM1 genotypes and smoking status (ever/never) because it allowed us to include some studies without information on the cross-classification of genotype and smoking status among controls, it removed possible biases due to the inclusion of hospital controls with diseases related to tobacco use, and it is a powerful design to test for multiplicative interactions under the assumption of independence of NAT2 and GSTM1 from smoking status in the population. Statistical analyses were done with STATA (Version 8.2, Special Edition).
The study sponsors had no role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.
The study population was of Caucasian origin, predominantly male and with a high prevalence of smoking, mostly black tobacco (Table 1). In this population, NAT2 slow acetylator and GSTM1 null (−/−) genotypes significantly increased bladder cancer risk (Table 2). NAT2 slow acetylators had a 40% increase in bladder cancer risk compared to NAT2 rapid/intermediate acetylators (OR (95% CI) = 1.4 (1.2-1.7)); the risk for NAT2 rapid and intermediate acetylators was similar (Table 2). The relative risks of bladder cancer for subjects with deletion of one or two (null genotype) copies of the GSTM1 gene were 1.2 (95% CI 0.8-1.7) and 1.9 (1.4-2.7), respectively (p for trend test=3×10−8). Individuals with the null genotype had a 70% increased risk of bladder cancer, compared to subjects with one or two copies of the GSTM1 gene (95% CI = 1.4-2.0) (Table 2). The associations for NAT2 and GSTM1 genotypes were similar regardless of tumor grade or stage (footnote to Table 2), and there was no evidence that these associations differed by age or gender (data not shown).
The joint association for the combined NAT2 slow acetylator and GSTM1 null genotype, present in 28% of the control population, compared to NAT2 rapid/intermediate and GSTM1 present genotype (OR (95%CI) = 2.2 (1.7-2.9)) was consistent with a weak multiplicative interaction between these two genetic variants; however, the test for multiplicative interaction was not significant (p=0.15). None of the other genetic polymorphisms evaluated was significantly associated with an increased risk of bladder cancer (Table 2), and there was no evidence of multiplicative interactions between them (data not shown).
Conventional logistic regression analyses showed a significant multiplicative interaction between NAT2 slow acetylation and cigarette smoking status (ever/never) with an interaction OR (95%CI) of 1.8 (1.2-2.8), p=0.008 (Table 3). The evidence for a multiplicative interaction became somewhat weaker (interaction OR (95% CI) = 1.4 (1.0-1.9), p =0.08) when using SPMLE logistic regression which assumes genotype-smoking and genotype-gender independence conditional on age, in the source population. Estimates for the NAT2 slow acetylation association with bladder cancer were similar for occasional, current and former smokers (Table 3, SPMLE OR (95%CI) were 1.5 (0.8-2.8), 1.5 (1.2-1.9) and 1.4 (1.1-1.8), respectively). The data suggested that the association of NAT2 slow acetylation genotype with bladder cancer was stronger for known or likely black tobacco smokers than for blond tobacco smokers (Table 3, SPMLE OR (95%CI) = 1.5 (1.3-1.8) and 1.0 (0.6-1.7), respectively). However, this difference was not statistically significant (Table 3, SPMLE p interaction = 0.08). NAT2 slow acetylators were at a higher risk than rapid/intermediate acetylators compared to never smokers for all levels of smoking intensity (average cigarettes per day) (Figure 1). At the same time, the magnitude of the association between NAT2 slow acetylation and bladder cancer risk among regular smokers was similar across different levels of smoking intensity (Table 3), duration and pack-years (data not shown).
Neither conventional nor SPMLE logistic regression showed a significant multiplicative interaction (OR (95%CI) was 0.7 (0.4-1.1), p=0.09, and 0.8 (0.5-1.1), p=0.15, respectively) for the association of GSTM1 null and smoking status (ever/never) on bladder cancer risk. This indicated that the relative risk of bladder cancer for GSTM1 null compared to present genotypes does not vary by smoking status. Multiplicative interactions were also not found for other smoking characteristics such as smoking cessation (current vs. former smokers), smoking intensity or duration. Given that an additive interaction can exist in the absence of a multiplicative interaction, and that departures from the additive model might have biological implications under certain assumptions, we then tested for an additive interaction. Both conventional and SPMLE logistic regressions showed significant departures from the additive model (i.e. additive interactions) with a synergy index (95% CI) of 1.3 (1.0-1.6), p=0.04 and 1.4 (1.1-1.7), p=0.001, respectively.
We updated a previously published meta-analysis of 22 studies of NAT2 and bladder cancer (4) to include data from our study and 8 additional studies (17-19;27;28;45-47) including a total of 5,096 cases and 6,519 controls (Figure 2A). The summary relative risk for NAT2 slow acetylators compared to rapid/intermediate acetylators was 1.4 (1.2-1.6), p=5×10−8, with no evidence for publication bias according to Begg's (p=0.94) and Egger's tests (p=0.91). There was some evidence for study heterogeneity (Q statistic p=0.04) which was not present when small studies (14 studies with less than 100 cases each) were excluded (summary OR (95%CI) = 1.4 (1.2-1.5), Q statistic p=0.31). Summary estimates for Caucasians (56% prevalence of NAT2 slow acetylators in controls) and Asians (11% prevalence of NAT2 slow acetylators in controls) were similar (p=0.87) (Figure 2A). The summary relative risk for studies of Caucasians conducted in the US was lower than for studies conducted in Europe, which accounted for most (82%) Caucasian cases; however this difference was not statistically significant (p=0.17) (Figure 2A).
We also updated a case-only meta-analysis of NAT2 and smoking interaction on bladder cancer risk (11) to include results from our study and 5 additional studies published after the meta-analysis (17;19;46;47) (Figure 2B). This analysis included a total of 4,305 cases and showed evidence for an interaction with a summary estimate of 1.2 (95%CI 1.1-1.5, p=0.008) for all populations combined. The point estimate for interaction was higher in Caucasian than Asian populations (1.3 versus 0.9, respectively), as well as in European compared to US Caucasian populations (1.4 versus 1.0, respectively); however, these differences were not statistically significant (p=0.32 and 0.08, respectively) (Figure 2B).
A meta-analysis of 17 studies of GSTM1 (8) was also updated to include our study, 10 additional studies (17;21;22;24;26;29;30;48-50) and an update from a previously published study (45) yielding a total of 5,108 cases and 6,483 controls (Figure 3A). The summary odds ratio for GSTM1 null versus present genotype for all populations combined was 1.5 (95% CI 1.3-1.6), p=9×10−15, with no evidence for publication bias according to Begg's (p=0.25) and Egger's tests (p=0.56). Summary estimates were similar and statistically significant in Caucasians (51% of GSTM1 null genotype in controls) and Asians (53% of GSTM1 null genotype in controls), as well as in US and European Caucasians (Figure 3A).
An updated case-only meta-analysis of studies that evaluated the GSTM1-smoking interaction (8) to include our study and 7 additional studies (17;21;22;29;30;48;50) (17 studies of 4,059 cases), confirmed the absence of a multiplicative interaction with a summary OR (95%CI) of 1.0 (0.9-1.2), p=0.86 (Figure 3B). Q statistics showed no evidence for study heterogeneity and Begg's and Egger's tests did not show evidence for publication bias among any of the population subgroups evaluated. Summary estimates for the interaction were very similar for all population subgroups (Figure 3B).
This report provides compelling evidence for an increased bladder cancer risk associated with the GSTM1 null and NAT2 slow acetylation genotypes. The association of the latter was particularly important among cigarette smokers. Although the relative risks for polymorphisms in NAT2 and GSTM1 genes are modest, they could account for a large percentage of bladder cancer cases because of their high prevalence in the population. Based on our data, we estimated that these polymorphisms are responsible for 31% (95% CI 20%-46%) of bladder cancer cases. In addition, we provide strong evidence against a substantial overall association for polymorphisms in other NAT and GST genes, with the possible exception of small to moderate associations for NAT1 *10/*10 and GSTP1 114Val/Val genotypes.
A new meta-analysis of studies of NAT2 slow acetylation and bladder cancer risk shows that this association is robust (p=5×10−8) and similar for Caucasian and Asian populations. The fact that the association for Asian populations was not stistically significant might be explained by a substantially lower statistical power to detect associations in Asian studies due to a lower prevalence of NAT2 slow acetylators (11% for Asians versus 56% for Caucasians) along with a smaller number of cases available for the meta-analysis. We also show that NAT2 slow acetylators are especially susceptible to the adverse effects of cigarette smoking on bladder cancer risk. This gene-environment interaction has strong biological plausibility since NAT2 slow acetylators have a decreased capacity to detoxify aromatic monoamines by N-acetylation (13), tobacco smoking is a primary source of exposure to aromatic amines in the general population, and aromatic amines are suspected of being the primary bladder carcinogen in tobacco smoke (12). Although our data suggest that NAT2 slow acetylation might not increase bladder cancer risk among never smokers, although it does not rule out a small increase in risk in this group of subjects.
Because the content of aromatic amines is higher in black than in blond tobacco (51), it is conceivable the effect of NAT2 slow acetylation may be stronger for smokers of black tobacco. Out data are consistent with this hypothesis, although differences were not statistically significant. The magnitude of the association between NAT2 slow acetylation and bladder cancer risk is similar for different levels of smoking intensity in our study population. Our meta-analysis of the interaction between smoking status and NAT2 slow acetylation genotype suggested a stronger interaction with ever/never smoking in European than in US studies. This could be due to a smaller number of studies conducted in the US than in Europe, or the lower aromatic amine content in blond tobacco generally smoked in the US compared to black tobacco commonly smoked in parts of Europe. Interestingly, a report from a population in the US recently reported an interaction between NAT2 slow acetylation genotype and smoking only for heavy smokers (47).
Distinction of subjects with one and two copies of the GSTM1 gene, an issue that has not been adequately addressed in prior studies of bladder cancer, suggests the presence of a gene-dosage effect with relative risks of 1.2 (95% CI 0.8-1.7) and 1.9 (1.4-2.7) for subjects with one or no copies of GSTM1, respectively, compared to subjects with two copies (ptrend=3×10−8). Meta-analyses of the association between the deletion of two copies of the GSTM1 gene (null genotype) compared to subjects with one or two copies (present genotype), as presented in previous studies that could not distinguish between these two groups of subjects, indicated that this association is robust (p=9×10−15), and similar in magnitude and significant across different population subgroups.
The relative risk for GSTM1 null genotype and bladder cancer is similar for smokers and never smokers in our study population and meta-analysis within population subgroups, suggesting that the GSTM1 activity protects equally against tobacco-related and non-tobacco related bladder cancers. This finding indicates that GSTM1 may reduce the risk of bladder cancer through mechanisms that are not specific to the detoxification of polycyclic aromatic hydrocarbons (PAHs) in tobacco smoke. Other mechanisms of action for GSTM1 could be protection from oxidative damage through metabolism of reactive oxygen species (52). Our data did not confirm previously suggested differences in risk for NAT2 slow acetylation and GSTM1 null genotypes by tumor grade or stage at presentation (26;53-56). Our findings are consistent with a potential interaction between NAT2 slow acetylation and GSTM1 null genotypes; however, additional evidence is needed to confirm this interaction (17;28).
Associations between bladder cancer risk and polymorphisms in genes coding for the NAT1 enzyme involved in the activation of aromatic amines by O-acetylation (13), and other GST enzymes that play an important role in the detoxification of PAHs and other carcinogens (57), have been less explored. Previous studies have provided inconsistent evidence for an association between bladder cancer risk and NAT1*10 alone or in combination with NAT2 slow acetylation (14-19;47), GSTT1 null alone or in combination with GSTM1 null genotype (17;20-31;50), and GSTP1 105 Val/Val genotype (17;21;32;33). Data from our study does not support a substantial association between GSTT1 and GSTM3 genotypes and bladder cancer risk. We find no significant increases in bladder cancer risk associated with polymorphisms in NAT1 or GSTP1 genes; however, our estimates do not exclude a small to moderate association for the NAT1*10/*10 compared to the NAT1*4/*4 genotype, or for genotypes with the GSTP1 114Val allele compared to the 114Ala/Ala genotype.
Analyses using conventional logistic regression suggested a modification of the association between bladder cancer with NAT2, GSTM1 and NAT1 genotypes by gender. However, the modifications by gender are explained by unexpected differences in the genotype distribution for male and female controls.
Our study has several strengths of note: high participation rates, large sample size, high quality exposure and genotype information and use of state-of-the art statistical methods. Specifically, we made an effort to improve the precision in genotype estimation by genotyping the seven SNPs in NAT2 that likely account for virtually all genetic variation in Caucasian populations,(58) and developed assays that sucesfully distinguished individuals with one or two copies of the GSTM1 and GSTT1 genes. We also used the SPMLE method (37) to increase power and reduce bias in the estimation of interactions, because of the strong evidence from previous studies for independence of NAT2 and GSTM1 genotypes from cigarette smoking status (8;11;38) and gender (38) in the general population. In order to minimize selection bias, we carefully selected controls from patients admitted for a variety of diagnoses that were thought to be unrelated to exposures of interest including tobacco use. Genotype frequencies among the control population were similar to those previously published. We found no significant overall differences in genotype frequencies across control diagnoses that could have biased our results.
Although this is the largest study on the role of genetic polymorphisms and bladder cancer risk published to date and had adequate statistical power to detect small genotype associations, the power to detect small to moderate interactions was limited. Meta-analyses including previous studies improved our ability to make inferences on interactions, when there were an adequate number of previous studies with homogeneous results. A consortium of bladder cancer studies is currently being formed to facilitate the pooling of comparable data on environmental and genetic risk factors across studies that will help overcome the limited power of individual studies to evaluate complex interrelationships.
Overall, these findings are among the most consistent for common genetic polymorphisms and risk of any tumor site in the literature, and provide compelling evidence for the role of common polymorphisms in cancer risk. This report also illustrates that large and rigorous investigations are required to establish or dismiss effects of common polymorphisms on complex diseases.
We thank Robert C. Saal from Westat, Rockville, MD, and Leslie Carroll and Jane Wang from IMS, Silver Spring, MD, for their support in study and data management; Dr. Maria Sala from IMIM, Barcelona, Spain, for her work in data collection; physicians, nurses, interviewers and study participants for their efforts during field work; and Drs. Pam Marcus and Larry Engels from NCI for providing datasets to perform meta-analyses. This work was supported by NCI-Westat contract no. N02-CP-11015, FIS/Spain 00/0745 and G03/174, and CA34627.
Contributions of authors
M. García-Closas, N. Malats, D. Silverman, M. Dosemeci, M. Kogevinas, F. X. Real and N. Rothman participated in the study design, patient enrollment and gene selection. G. Castaño-Vinyals, M. Torà, F. Fernández, C. Samanic, A. Tardón, C. Serra, A. Carrato, R. García-Closas participated in the study design and patient enrollment. D. W. Hein, M. Yeager, R. Welch and S. Chanock participated in gene selection and genotyping. J. Lloreta participated in the pathology review. N. Chatterjee and S. Wacholder participated in the statistical analyses. M. García-Closas performed the statistical analyses and drafted the paper with input from all investigators.
Conflict of interest statement
None of the authors in this manuscript have conflicts of interest. Montserrat García-Closas had full access to all the data in the study and had final responsibility for the decision to submit for publication.