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Keywords:

  • bladder cancer;
  • folate metabolism;
  • one-carbon metabolism;
  • GSTM1;
  • CTH;
  • genetic susceptibility

Abstract

  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. References

We have previously reported significant inverse associations between bladder cancer risk and dietary intake of vitamins B2, B6, B12, folate and protein in a hospital-based bladder cancer case-control study conducted in Spain (1,150 cases;1,149 controls). Because these dietary factors are involved in the one-carbon metabolism pathway, we evaluated associations between bladder cancer risk and 33 single nucleotide polymorphisms (SNPs) in 8 genes (CBS, CTH, MTHFR, MTR, MTRR, SHMT1, SLC19A1 and TYMS) and interactions with dietary variables involved in this pathway. Two SNPs in the CTH gene were significantly associated with bladder cancer risk. OR (95% CI) for heterozygous and the homozygous variants compared to homozygous wild-type individuals were: 1.37 (1.04–1.80) IVS3-66 A > C and 1.22 (1.02–1.45) IVS10-430 C > T. Because the CTH gene is important for glutathione synthesis, we examined interactions with the GSTM1 gene, which codes for glutathione S-transferase μu. Increased risk for individuals with the IVS10-430 CT or TT genotype was limited to those with the GSTM1 null genotype (p-interaction = 0.02). No other SNPs were associated with risk of bladder cancer. These findings suggest that common genetic variants in the one-carbon pathway may not play an important role in the etiology of bladder cancer. However, our results provide some evidence that variation in glutathione synthesis may contribute to risk, particularly among individuals who carry a deletion in GSTM1. Additional work is needed to comprehensively evaluate genomic variation in CTH and related genes in the trans-sulfuration pathway and bladder cancer risk. © 2007 Wiley-Liss, Inc.

Epidemiological studies have shown associations between low folate intake and increased cancer risk.1–5 Recently, we observed inverse associations for several B vitamins including folate, which are involved in one-carbon metabolism and bladder cancer risk.6 Although epidemiologic evidence strongly supports an association between low folate and higher risk of colon cancer, the association with bladder cancer has not been observed.7–11

Efficient functioning of the one-carbon metabolism pathway is dependent upon dietary intake of folate, B vitamins as co-factors, and methionine, an essential amino acid that is derived from protein intake. This pathway is also fundamental to many cellular processes including genomic DNA methylation and nucleotide synthesis and repair.12 Among several genetic polymorphisms in the folate metabolic pathway characterized thus far, 2 SNPs in the methylene tetrahydrofolate reductase (MTHFR) gene, A222V and E429A, have received the most attention and may be associated with decreased enzyme function.13–15 In relation to cancer, polymorphisms in other genes in this pathway have been studied less frequently.16–19 However, like MTHFR, variation in these genes can result in elevated levels of plasma homocysteine, presumably because of decreased enzyme activity.

The 6 previous publications on MTHFR polymorphic variants and bladder cancer risk have shown inconsistent findings.18, 20–24 Of these, 1 study (457 bladder cancer cases and 457 controls) also examined dietary folate intake and observed significant interactive effects among subjects that had both low folate and at least 1 variant MTHFR A222V allele.19 To further investigate the role of this pathway in bladder cancer, we determined the association between SNPs in several key genes involved in one-carbon metabolism with bladder cancer risk among 1,150 cases and 1,149 controls participating in the Spanish Bladder Cancer Study. Specifically, we analyzed 33 single nucleotide polymorphisms (SNPs) in 8 folate metabolism genes (CBS, CTH, MTHFR, MTR, MTRR, SHMT1, SLC19A1 TYMS). We also investigated interactions with intake of vitamins B2, B6, B12, folate and total protein because of their critical importance to this pathway.

Material and methods

  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. References

Study population

This study population has been previously described.25 Briefly, cases were patients participating in the Spanish Bladder Cancer Study (SBC) newly diagnosed, histologically confirmed carcinoma of the urinary bladder in 1998–2001, aged 21–80 years (mean (standard deviation) = 6610 years) of which 87% were males. Controls were selected from patients admitted to participating hospitals for diagnoses believed to be unrelated to the exposures of interest such as tobacco use. Controls were individually matched to the cases on age at interview within 5 year categories, sex, ethnicity and hospital region. The distribution of reasons for hospital admission was: 37% hernias, 11% other abdominal surgery, 23% fractures, 7% other orthopedic problems, 12% hydrocoele, 4% circulatory disorders, 2% dermatological disorders, 1% ophthalmologic disorders and 3% other diseases. Demographic and risk factor information was collected at 18 participating hospitals using computer-assisted personal interviews (CAPI). The final study population available for genetic analysis included 1,150 cases and 1,149 controls. We obtained informed consent from potential participants in accordance with the National Cancer Institute and local Institutional Review Boards. Food intake during the 5 year period pre-diagnosis for cases and before interview for controls was estimated using a comprehensive semi-quantitative food frequency questionnaire (FFQ) of 127 items previously validated in Spain.6 Nine hundred seventeen cases and 875 controls completed the FFQ. Among subjects completing the FFQ, 3 cases with unsatisfactory CAPI interview and 2 cases and 2 controls with missing information on smoking status, were excluded from the analyses. After exclusions, analyses with dietary information included a total of 880 cases and 815 controls. Nutrient density variables were calculated by dividing each continuous nutrient variable by the estimated number of kilocalories measured per day. Cut-off points for micronutrient quartiles were determined among controls. Subjects were not excluded based on extreme caloric intakes.

Laboratory techniques

Genotype assays were conducted at the Core Genotyping Facility (CGF) of the Division of Cancer Epidemiology and Genetics, National Cancer Institute. DNA for genotype assays was extracted from leukocytes (1,107 cases and 1,032 controls) and mouthwash samples (43 cases and 117 controls) as described previously.25 Initially we selected SNPs in 6 genes with expected minor allele frequency (MAF) ≥ 0.05 in Caucasians, with TaqMan® based assays available at the CGF. SNP selection favored those leading to non-synonymous amino acid changes, those previously evaluated in relation to bladder cancer risk, or those with evidence of functional significance. We later added SNPs from a large scale evaluation of candidate genes using the Illumina® Golden Gate Assay (San Diego, CA). The panel included 1,433 SNPs in selected candidate genes with assays previously sequenced and genotyped in the SNP500 Cancer project.26 Because of low DNA amounts available at the time of analysis, 64 of the 1,150 cases and 116 of the 1,149 controls in this manuscript were not included in the Illumina assays. Descriptions of SNPs can be found in Table I. Methods for genotype assays can be found at http://snp500cancer.nci.nih.gov. All genotypes included in this study were in Hardy-Weinberg Equilibrium among the controls (p < 0.05).

Table I. Genes and Single Nucleotide Polymorphisms Involved in the One-Carbon Metabolism Pathway Selected for the Spanish Bladder Cancer Case–Control Study of Gene-Environment Interactions
Name of gene (symbol)Function in the one-carbon metabolism pathwayChromosomal locationNucleic acid changeAmino acid changedbSNP IDMinor allele frequency in controls
Cystathione beta-synthase (CBS)Catalyzes the first step of trans sulfuration pathway of homocysteine to cystathionine. Deficiency of this enzyme is known to cause homocysteineuria, -emia.21q22.3Ex9+33 C > TY233Yrs2347060.33
   Ex13+41 C > TA360Ars18011810.36
   IVS15-134 G > A3′UTRrs65862820.17
   Ex18-391 A > G rs126130.08
Cystathionase (CTH)Encodes a cytoplasmic enzyme in the transfulfuration pathway that converts cystatione derived from methionine into cytosine. Glutathione synthesis in the liver is dependent upon cysteine. Mutations cause cystathioneuria.1p31.1−340 A > G rs6634650.41
  IVS3-66 A > C rs64134710.05
  IVS7-799 A > G rs4733340.30
  IVS7-583 G > T rs6636490.30
  IVS10-430 C > T rs5590620.22
  IVS10-303 A > G rs5150640.84
5,10 methylene tetrahydrofolate reductase (MTHFR)Catalyzes the conversion of 5,10 methylenetetrahydrofolate, a co-substrate for homocysteine remethylation to methionine. Can be mutated in cases of homocysteineuria.1p36.3Ex2-120 C > TP39Prs20664700.09
  Ex5+79 C > TA222Vrs18011330.39
  IVS7-76 T > G rs121215430.22
  Ex8-62 A > CE429Ars18011310.28
5-methyltetrahydrofolate-homocysteine methyltransferase reductase (MTR)Also known as cobalamin-dependent methionine synthase (MS). Catalyzes the final step in methionine biosynthesis. Mutations cause methylcobalamin deficiency complementation group G.1q43Ex26-20 A > GD919Grs18050870.17
  IVS26+157 T > G rs22755650.21
  IVS26+43 G > A rs22755660.42
5-methyltetrahydrofolate-homocysteine methyltransferase reductase (MTRR)Regenerates functional MTR (MS) via reductive methylation. Mutations cause disorders of folate cobalamin metabolism.5p15.2-3Ex2-64 A > GI49Mrs18013940.36
  Ex9-85 C > TR442Crs22877800.03
  Ex9+9 G > AL412Lrs22877790.03
  Ex14-42 G > AA664Ars18020590.36
  Ex14+14 C > TH622Yrs103800.10
  Ex15-526 G > A3′UTRrs93320.12
  Ex15-405 A > T3′UTRrs86590.34
Serine hydroxymethyltransferase 1 (SHMT1))Catalyzes the reversible conversion of serine and tetrahydrofolate to glycine and 5,10 methylenetetrahydrofolate. Provides 1-carbon units for synthesis of methionine thymidylate and purines in the cytoplasm.17p11.2Ex12+138 C > TL435Frs19792770.27
  Ex12+217 G > T3′UTRrs37830.36
  Ex12+236 T > C3′UTRrs19792760.30
Solute carrier family 19 (folate transporter member 1 (SLC19A1)Transport of folate compounds into mammalian cells. Maintains cellular concentrations of folate.21q22.3Ex4-114 T > CH27Rrs10512660.45
 Ex7-233 G > T3′UTRrs10512960.48
  Ex7-198 C > T3′UTRrs10512980.47
Thymidylate Synthetase (TYMS)Uses methylene THF as a cofactor to maintain dTMP pool critical for DNA replication and repair.18p11.32IVS7-68 T > C rs10593940.32
  Ex8+157 C > T3′UTRrs6995170.32
   Ex8+227 A > G3′UTRrs27900.20

Statistical analysis

Hardy-Weinberg equilibrium was tested by the goodness of fit χ2 test. Pairwise linkage disequilibrium (LD) between SNPs was estimated based on D′ and r2 values using Haploview (http://www.broad.mit.edu/mpg/haploview/index.php). Of the 33 SNPs genotyped, 4 pairs were highly correlated (r2 > 0.95). To reduce redundancy, only data from 1 SNP per pair is shown. For each of the individual polymorphisms we estimated odds ratios (OR) and 95% confidence intervals (95% CI) using logistic regression models adjusting for sex, age at interview in 5 year categories, region, smoking status (never, ever) and energy intake (continuous). Tests for trend were conducted using logistic regression. Interactions were tested comparing regression models with and without interaction terms using a likelihood ratio test (LRT). Haplotype frequencies for genes with more than 1 SNP were estimated using HaploStats, adjusting for age, sex and region (version 1.2.1; http://mayoresearch.mayo.edu/mayo/research/biostat/schaid.cfm). A global score test was implemented in HaploStats as proposed by Shaid et al.27 The false discovery rate (FDR) procedure was used to identify associations unlikely to be due to chance.28 All analyses were conducted in STATA 8.0 unless otherwise specified (STATA Corporation, College Station, TX).

Results

  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. References

A description of study subjects is presented in Table II. We obtained DNA from 97% of the cases and 92% of the controls that were interviewed (leaving 31 cases and 98 controls interviewed without DNA for analysis). Subjects without genotyping data were similar with respect to age and known bladder cancer risk factors to those genotyped (data not shown). Previously we observed an inverse association with bladder cancer for several micronutrients that are also necessary co-factors in the one-carbon metabolism pathway.6 Odds ratios and 95% confidence intervals [OR(95% CI)] comparing subjects in the 25–75% percentile and the bottom quartile to those in the top quartile of intake in a multivariate model adjusted by age, sex, region, cigarette smoking (ever, never) and energy intake are also shown in Table II. Significant inverse trends were observed with intake of vitamins B2 (p-trend = 0.001) and B6 (p-trend < 0.001). For this study, we also calculated risks associated with total protein intake as a source of methionine, an essential amino acid that is metabolized to S-adenosylmethionine (SAM), the universal methyl donor.29 Significant inverse associations were observed comparing individuals in the 25–75% percentile and the lowest quartile, to those in the top quartile as a reference (p-trend = 0.002).

Table II. Characeristics of Cases and Controls in the Spanish Bladder Cancer Study
VariablesCases N = 1,150 (66 yr ±10)1Control N =1,149 (65 yr ±10)1OR95% CIp-trend
N%N%
  • Odds Ratio (95% confidence interval).

  • 1

    Mean age at interview (±SD).

  • 2

    Nutrient density; μg/1000 kcal/day.

Matching factors
 Sex
  Female14612.714712.8   
  Male1,00487.31,00287.2  0.94
 Level of education
  Less than primary52546.353947.7   
  Incomplete high school45239.943738.7   
  High school or higher15613.815413.6  0.45
 Region
  Barcelona20918.223220.2   
  Vallès/bages18015.718215.8   
  Elche857.4827.1   
  Tenerife21118.319116.6   
  Asturias46540.446240.2  0.33
Risk factors
 Cigarette smoking
  Never15913.833829.41.00  
  Occasional504.3887.71.34(0.81–2.23) 
  Former47441.245839.92.84(2.04–3.96) 
  Current46740.626523.16.75(4.73–9.62)<0.001
 Pack years
  <199710.617325.01.60(1.61, 2.21) 
  19–3622724.717725.53.89(2.91, 5.19) 
  36–5832635.517224.85.70(4.30, 7.56) 
  >5826829.217324.94.68(3.51, 6.23)<0.001
 Vitamin B2 (quartile)2
  >75% (>1.11)19722.420024.51.00  
  25–75% (>0.77 to ≤1.11)41046.641350.71.10(0.85,1.42) 
  <25% (≤0.77)27331.020224.81.48(1.11, 1.98)0.001
 Vitamin B6 (quartile)2
  >75% (>1.18)17620.020425.01.00  
  25–75% (>0.85 to ≤1.18)43349.240850.11.32(1.02, 1.71) 
  <25% (≤0.85)27130.820324.91.72(1.27, 2.31)<0.001
 Vitamin B12 (quartile)2
  >75% (>5.66)18821.420324.91.00  
  25–75% (>2.78 to ≤5.66)42548.340850.11.17(0.92, 1.50) 
  <25% (≤2.78)26730.320425.01.44(1.09, 1.90)0.07
 Folate (quartile)2
  >75% (>207.61)20323.120324.91.00  
  25–75% (>138.59 to ≤207.61)38944.240850.11.03(0.80, 1.32) 
  <25% (≤138.59)28832.720425.01.52(1.14, 2.03)0.08
 Protein (quartile)2
  >75% (>53.36)17119.420324.91.00  
  25–75% (>40.51 to ≤53.36)45952.240850.11.32(1.04, 1.73) 
  <25% (≤40.51)25028.420425.01.48(1.08, 1.94)0.002

Associations between polymorphisms in 1-C metabolism and trans-sulfuration pathway genes and bladder cancer risk are shown in Table III. Results for CTH IVS7-799 A > G, SHMT1 Ex12+217 G > T, SLC19A1 Ex7-198 C > T and TYMS IVS7-68 T > C are not shown because each SNP was highly correlated with another SNP in that gene (r2 > 0.95). MAFs among controls were similar to those previously reported in Caucasian populations in the SNP 500 database (http://snp500cancer.nci.nih.gov) (Table I). Compared to homozygous wild-type individuals, data suggested an increased risk for subjects with 1 or more variant alleles for the CTH IVS3-66 A > C (OR = 1.37; 95% CI:1.04–1.80, p = 0.03) and IVS10-430 C > T polymorphisms (OR = 1.21 (95% CI:1.02–1.45, p = 0.03) (Table III) although, the false discovery rate (FDR) values for these 2 significant findings were both 0.43.

Table III. Association Between Polymorphisms in 1-Carbon Metabolism Genes and Bladder Cancer Risk
GeneSNP2CasesControlsOR195% CIp-trend
N%N%
  • 1

    Adjusted for age, sex, region, and smoking status (ever/never).

  • 2

    Results combined if minor allele frequency is controls ≤ 5 %.

CBSY233Y       
 CC50845.050044.41.00  
 CT51445.549644.01.01(0.84–1.20) 
 TT1079.513111.60.82(0.61–1.10)0.34
 A360A       
 CC43638.645640.61.00  
 CT54748.452146.41.12(0.93–1.34) 
 TT14713.014512.91.05(0.80–1.38)0.45
 IVS15-134G > A       
 GG74668.869567.31.00  
 AG/AA33931.233732.70.93(0.77–1.12)0.45
 Ex18-391A > G       
 GG91183.986783.91.00  
 AG/AA17516.116616.11.03(0.81–1.30)0.84
CTH−340A > G       
 AA39336.236335.11.00  
 AG50546.548346.80.95(0.78–1.16) 
 GG18717.218718.10.93(0.72–1.21)0.56
 IVS3-66A > C       
 AA94386.892689.61.00  
 AC/CC14313.210710.41.37(1.04–1.80)0.03
 IVS7-583G > T       
 GG52548.450649.01.00  
 GT46042.442741.31.02(0.85–1.23) 
 TT1009.21009.70.96(0.70–1.31)0.95
 IVS10-430C > T       
 CC61056.262260.21.00  
 CT/TT47543.841139.81.21(1.02–1.45)0.03
 IVS10-303A > G       
 AA46743.045143.71.00  
 AG48444.645844.31.00(0.83–1.21) 
 GG13512.412412.01.04(0.78–1.38)0.82
MTHFRP39P       
 CC90783.785983.41.00  
 CT/TT17616.317116.60.95(0.75–1.21)0.70
 A222V       
 CC41840.240238.31.00  
 CT47845.948646.30.99(0.81–1.20) 
 TT14513.916115.30.90(0.68–1.18)0.49
 IVS7-76T > G       
 GG65460.263061.01.00  
 GT/TT43239.840339.01.01(0.84−1.21)0.92
 E429A       
 AA53750.355751.71.00  
 AC45742.842939.81.08(0.90–1.29) 
 CC746.9928.50.80(0.57–1.12)0.68
MTRD919G       
 AA75169.468367.91.00  
 AG/GG33130.632332.10.99(0.81–1.19)0.89
 IVS26+157T > G       
 GG69263.765363.21.00  
 GT/TT39436.338036.81.02(0.85–1.23)0.82
 IVS26+43G > A       
 AA36833.935934.81.00  
 AG53048.848947.31.02(0.84–1.24) 
 GG18817.318517.90.98(0.75–1.26)0.92
MTRRI49M       
 GG29126.727427.01.00  
 AG53148.851050.20.98(0.79–1.21) 
 AA26724.523222.81.14(0.89–1.46)0.33
 R442C       
 CC102923.797723.61.00  
 CT/TT561.3561.40.97(0.66–1.44)0.89
 L412L       
 GG102894.797794.61.00  
 AG/AA575.3565.40.99(0.67–1.46)0.95
 H622Y       
 CC85678.984581.81.00  
 CT/TT22921.118818.21.17(0.94–1.46)0.16
 A664A       
 GG45541.942040.71.00  
 AG48544.748146.60.89(0.74–1.08) 
 AA14513.413212.81.00(0.76–1.33)0.65
 Ex15-526G > A       
 GG80273.880377.71.00  
 AG/AA28426.223022.31.22(1.00–1.50)0.06
 Ex15-405A > T       
 AA45942.344142.81.00  
 AT49445.647946.51.00(0.83–1.20) 
 TT13112.111110.81.20(0.89–1.61)0.37
SHMT1L435F       
 CC59054.053853.21.00  
 CT42639.040039.60.97(0.80–1.16) 
 TT767.0737.20.98(0.69–1.40)0.77
 Ex12+236T > C, 3′UTR       
 CC54950.348948.31.00  
 CT44240.543242.70.91(0.76–1.10) 
 TT1009.2919.01.00(0.72–1.37)0.59
SLC19A1H27R       
 GG30127.831330.31.00  
 AG52048.050048.41.07(0.87–1.32) 
 AA26324.321921.21.25(0.98–1.60)0.08
 Ex7-233G > T, 3′UTR       
 TT27525.528728.61.00  
 GT53349.447847.71.14(0.92–1.41) 
 GG27025.023823.71.18(0.92–1.51)0.18
TYMSEx8+157C > T, 3′UTR       
 CC50246.348647.01.00  
 CT47643.943442.01.05(0.87–1.26) 
 TT1069.811310.90.89(0.66–1.20)0.74
 Ex8+227A > G, 3′UTR       
 AA70264.865863.91.00  
 AG/GG38235.237236.10.97(0.80–1.16)0.72

Haplotypes were estimated in genes for which we had information on more than 1 SNP. Significant results were only observed for the CTH gene. Five SNPs in this gene formed a LD block with 8 common haplotypes with frequency >0.5% in the control population (Table IV). The 2 SNPs associated with risk were found in 2 haplotypes with frequencies of 4.3% (A-C-G-T-A) and 0.8 % (G-C-G-T-A) in the control population. Both haplotypes were associated with increase in risk compared to the wild-type (referent) haplotype. However, data suggested a stronger and significant association for the haplotype which also included a variant SNP in the CTH promoter region (−360 A > G; OR = 2.39; 95% CI: 1.13–5.04, p = 0.02). A global test to determine whether the distribution of CTH haplotypes differed significantly between cases and controls was of borderline significance (p = 0.07).

Table IV. Association Between Haplotypes of Cystathionase Gene and Bladder Cancer Risk in the Spanish Bladder Cancer Study
HaplotypeControls (%)Cases (%)OR195% CIp-value2
  • SNPs: -340 A > G, IVS3-66 A > C, IVS7-583G > T, IVS10-430 C > T, IVS10-303 A > G

  • 1

    Adjusted for sex, age, center and smoking status.

  • 2

    Global p = 0.07.

A-A-G-C-A25.124.51.00(reference) 
A-A-T-C-G28.628.91.040.871.230.68
A-C-G-T-A4.35.11.250.891.760.19
G-A-G-C-A18.215.90.900.731.100.30
G-A-G-C-G3.73.91.110.791.570.54
G-A-G-T-A17.117.41.060.881.290.53
G-A-T-C-G1.61.40.910.501.670.77
G-C-G-T-A0.81.72.391.135.040.02

The CTH gene encodes the protein cystathionine gamma-lyase, an enzyme that irreversibly converts cystathionine derived from methionine to cysteine via the trans-sulfuration pathway (Fig. 1).16, 17, 29–31 Because cysteine is a substrate for glutathione synthesis in the liver by glutamate–cysteine ligase,28 and the GSTM1 null genotype was previously shown to be associated with bladder cancer risk in this and other populations,25, 32 we examined interactions between CTH and the GSTM1 gene (Table V). Increased risk for the IVS10-430 variant was limited to subjects with the GSTM1 null genotype only (OR = 1.97; 95% CI: 1.53–2.54; p-interaction = 0.02).

thumbnail image

Figure 1. Metabolic pathway for glutathione synthesis in liver cells showing upstream trans-sulfuration and subsequent glutathione synthesis.

Download figure to PowerPoint

Table V. Gene–Gene Interaction Between GSTM1 and CTH IVS-66 A > C and IVS10−430 C > T Genotypes and Bladder Cancer Risk in the Spanish Bladder Cancer Study
CTHGSTM1 present (+/+ and +/−)GSTM1 null (−/−)p2
Cases(%)Controls(%)OR195% CICases(%)Controls(%)OR195% CI
  • 1

    Adjusted for sex, age, center and smoking status.

  • 2

    P-value for interaction.

IVS3 -66 A > C
 AA34387.145090.41.00Reference59286.746889.31.63(1.35–1.98) 
 AC/CC5112.9489.61.37(0.89–2.10)9113.35610.72.28(1.58–3.32)0.95
IVS10-430 C > T
 CC24060.929459.01.00Reference36553.532161.31.37(1.08–1.73) 
 CT/TT15439.120441.00.94(0.71–1.24)31746.520338.71.97(1.53–2.54)0.02

None of the genotype or haplotype associations were significantly modified by sex or age. Exploratory analyses were conducted to determine whether consideration of dietary variables (vitamin B2, B6, B12, folate and protein) or cigarette smoking (ever, never) would be helpful in revealing biologically meaningful genotype associations. Most interactions observed were not statistically significant. Those that were significant implied cross-over effects or demonstrated inconsistent trends that would most likely be explained by chance.

Discussion

  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. References

In this study, we examined associations between bladder cancer risk and 33 SNPs in 8 genes and interactions with dietary factors involved the one-carbon metabolism pathway. While data from this study indicated that dietary intake of vitamins B2, B6, B12, folate and total protein were inversely associated with bladder cancer risk, genetic variation in one-carbon metabolism genes did not substantially modify bladder cancer risk. To our knowledge this is the largest and most detailed evaluation of genetic variation within this pathway and bladder cancer risk conducted to date. This study, like 3 previous smaller studies did not show evidence of an association between the 2 functional SNPs in MTHFR (A222V and E429A) or the MTR D919G polymorphisms with bladder cancer risk. Unlike the study by Lin et al.,18 we did not observe interactive effects between dietary folate and the MTHFR A222V polymorphism, possibly because of differences in dietary folate intake between the populations. In the study by Lin et al.,18 total dietary folate levels including folic acid from supplements was much higher than that observed among participants in the current study (median among cases = 416.9 μg/1,000 kcal/day; median among controls = 857.6 μg/1,000 kcal/day). An alternate possibility is that the above findings could be false positive associations and that genetic variation may only be associated with cancer risk in instances of severe dietary depletion, an issue that requires further attention.

The results of this study provided some evidence that 2 CTH gene variants may be associated with increased bladder cancer risk. Several functional variants of this gene have been observed among patients with cystathioninuria, a condition in which patients develop high levels of cystathionine in the urine when it is not further metabolized by the CTH enzyme16; however, the current study would have been underpowered to include such rare polymorphic variants in the analysis. Like MTHFR, 1 common non-synonymous SNP in Exon 12, codon 1364 G > T (S403I) was recently associated with elevated levels of plasma homocysteine, suggesting that normal recycling of homocysteine may also be altered. The CTH gene product, cystathionine gamma-lyase is normally required for the conversion of methionine into cysteine.16, 17 Cysteine, available through dietary sources or the trans-sulfuration pathway, is the limiting substrate necessary for glutathione synthesis in the liver. We analyzed these data for interactions between CTH and the GSTM1 genotype and observed that increased risk associated with the IVS10-430 variant was limited to subjects with the GSTM1 null genotype (p-interaction = 0.02). It is possible that variation in CTH, may be associated with bladder cancer risk because of its role in glutathione synthesis via the trans-sulfuration pathway, rather than one-carbon metabolism. Several large pooled and meta-analyses of bladder cancer and have shown GSTM1 null to be associated with an increased bladder cancer risk, independent of smoking status.25, 32 In this study, we also observed that the association between the CTH variants evaluated and bladder cancer was independent of smoking status.

The strengths of our study include high participation rates and large sample size. Our study also had adequate statistical power to detect relatively small genotype associations; however, the power to detect interactions was limited. Although we included a majority of functional and non-synonymous SNPs in this analysis, we did not conduct a dense survey of tagged SNPs intended to capture haplotype diversity. It is possible that additional genetic variation not captured by the analyzed genotypes may be related to bladder cancer.

In conclusion, our results do not support a substantial role for the evaluated genetic variation in one-carbon metabolism genes and bladder cancer, despite the strong inverse associations with several micronutrients crucial to this pathway.6 This study did provide evidence that genetic variation in the CTH gene, perhaps through a role in the trans-sulfuration pathway and subsequent glutathione synthesis, could increase bladder cancer risk, especially among individuals that have low GSTM1 activity. Pooling data from ongoing bladder cancer studies and more comprehensive analysis of genetic variation are ongoing and will be required to confirm these findings.

References

  1. Top of page
  2. Abstract
  3. Material and methods
  4. Results
  5. Discussion
  6. References
  • 1
    Mason JB, Choi SW. Folate carcinogenesis: developing a unifying hypothesis. Adv Enzyme Regul 2000; 40: 12741.
  • 2
    Larsson SC, Hakansson N, Giovannucci E, Wolk A. Folate intake and pancreatic cancer incidence: a prospective study of Swedish women and men. J Natl Cancer Inst 2006; 98: 40713.
  • 3
    Stevens VL, Rodriguez C, Pavluck AL, McCullough ML, Thun MJ, Calle EE. Folate nutrition and prostate cancer incidence in a large cohort of US men. Am J Epidemiol 2006; 163: 98996.
  • 4
    Schabath MB, Spitz MR, Lerner SP, Pillow PC, Hernandez LM, Delchos GL, Grossman HB, Wu X. Nutr Cancer 2006; 53: 14451.
  • 5
    Sharp L, Little J. Polymorphisms in genes involved in folate metabolism and colorectal neoplasia: a HuGE review. Am J Epidemiol 2004; 159: 42343.
  • 6
    Garcia-Closas R, Garcia-Closas M, Kogevinas M, Malats N, Silverman D, Serra C, Tardon A, Carrato A, Castano-Vinyals G, Dosemeci M, Moore L, Rothman N, Sinha R. Food, nutrient and heterocyclic amine intake and the risk of bladder cancer (submitted).
  • 7
    Silverman DT, Devesa SS, Moore LE, Rothman N. Bladder cancer. In: SchottenfeldD, FraumeniJF,Jr, eds. Cancer epidemiology and prevention, 3rd edn. New York, NY: Oxford University Press, 2006. 11011127.
  • 8
    World Cancer Research Fund and American Institute for Cancer Research Food, nutrition, and the prevention of cancer. A global perspective. Washington DC: American Institute for Cancer Research, 1997.
  • 9
    Steinmaus CM, Nunez S, Smith AH. Diet and bladder cancer: a meta-analysis of six dietary variables. Am J Epidemiol 2000; 151: 693702.
  • 10
    Zeegers MP, Goldbohm RA, van den Brandt PA. Consumption of vegetables and fruits and urothelial cancer incidence: a prospective study. Cancer Epidemiol Biomarkers Prev 2001; 10: 11218.
  • 11
    Michaud DS, Pietinen P, Taylor PR, Virtanen M, Virtamo J, Albanes D. Intakes of fruits and vegetables carotenoids and vitamins A, E, and C in relation to the risk of bladder cancer in the ATBC cohort study. Br J Cancer 2002; 87: 9605.
  • 12
    Choi SW, Friso S. Interactions between folate and aging for carcinogenesis. Clin Chem Lab Med 2005; 43: 11517.
  • 13
    van der Put NM, Gabreels F, Stevens EM, Smeitink JA, Trijbels FJ, Eskes TK, van den Heuvel LP, Blom HJ. A second common mutation in the methyleletetrahydrofolate reductase gene: an additional risk factor for neural-tube defects? Am J Hum Genet 1998; 62: 104451.
  • 14
    Parle-McDermott A, Mills JL, Molloy AM, Carroll N, Kirke PN, Cox C, Conley MR, Pangilinan FJ, Brody LC, Scott JM. The MTHFR 1298 and 677 TT genotypes have opposite associations with red cell folate levels. Mol Genet Metab 2006; 88: 2904.
  • 15
    Frosst P, Blom HJ, Milos R, Goyette P, Sheppard CA, Matthews RG, Boers GJ, den Heijer M, Kluijtmans LA, van den Heuvel LP, Rozen R. A candidate genetic risk factor for vascular disease: a common mutation in methylenetetrahydrofolate reductase. Nat Genet 1995; 10: 11113.
  • 16
    Wang J, Hegele RA. Genomic basis of cystathioninuria (MIM 219500) revealed by multiple mutations in cystathionine γ-lyase (CTH). Hum Genet 2003; 112: 4048.
  • 17
    Wang J, Huff AM, Spence JD, Hegele RA. Single nucleotide polymorphism in CTH associated with variation in plasma homocysteine concentration. Clin Genet 2004; 65: 4836.
  • 18
    Lin J, Spitz MR, Wang Y, Schabath MB, Gorlov IP, Hernandez LM, Pillow PC, Grossman HB, Wu X. Polymorphisms of folate metabolic genes and susceptibility to bladder cancer: a case-control study. Carcinogenesis 2004; 25: 163947.
  • 19
    Kim YI. 5,10 Methylenetetrahydrofolate reductase polymorphisms and pharmacogenetics: a new role of single nucleotide polymorphisms in the folate metabolic pathway in human health and disease. Nutr Rev 2005; 63: 398407.
  • 20
    Heijmans BT, Boer JM, Suchiman HED, Cornelisse CJ, Westendorp RGJ, Kromhout D, Feskens EJM, Slagboom PE. A common variant of the methylenetetrahydrofolate reductase (1p36) is associated with increased risk of cancer. Cancer Res 2003; 63: 124953.
  • 21
    Moore LE, Wiencke JK, Bates MN, Zheng S, Rey OA, Smith AH. Investigation of genetic polymorphisms and smoking in a bladder cancer case-control study in Argentina. Cancer Lett 2004; 211: 197207.
  • 22
    Kimura F, Florl AR, Steinhoff C, Golka K, Willers R, Seifert H, Schulz WA. Polymorphic methyl group metabolism genes in patients with transitional cell carcinoma of the urinary bladder. Mutat Res 2001; 458: 4954.
  • 23
    Sanyal S, Festa F, Sakano S, Zhang Z, Steineck G, Norming U, Wijkstrom H, Larsson P, Kumar R, Hemminki K. Polymorphsims in DNA repair and metabolic genes in bladder cancer. Carcinogenesis 2004; 25: 72934.
  • 24
    Karagas MR, Parks S, Nelson HH, Andrew AS, Mott L, Schned A, Kelsey KT. Methylenetetrahydrofolate reductase (MTHFR) variants and bladder cancer: a population based case-control study. Int J Hyg Environ Health 2005; 208: 3217.
  • 25
    Garcia-Closas M, Malats N, Silverman D, Dosemeci M, Kogevinas M, Hein DW, Tardon A, Serra C, Carrato A, Garcia-Closas R, Lloreta J, Castano-Vinyals G, et al. NAT2 slow acetylation and GSTM1 null genotypes increase bladder cancer risk: results from the Spanish Bladder Cancer Study and meta-analyses. Lancet 2005; 366: 64959.
  • 26
    Garcia-Closas M, Rothman N, Malats N, Real FX, Welch R, Yeager M, Silverman D, Kogevinas M, Dosemeci M, Tardon A, Serra C, Carrato A, et al. Large-scale evaluation of candidate genes for urinary bladder cancer susceptibility using Illumina® in the Spanish Bladder Cancer Study. 97th AACR Annual Meeting. Proc Am Assoc Cancer Res 2006; 47: Abstract 2328.
  • 27
    Schaid DJ, Rowland CM, Tines DE, Jacobson RM, Poland GA. Score tests for associations between traits and haplotypes when linkage phase between traits is ambiguous. Am J Hum Genet 2002; 70: 42534.
  • 28
    Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc 1995; 57: 289300.
  • 29
    Brosnan JT, Brosnan ME. The sulfur-containing amino acids: an overview. J Nutr 2006; 136 ( Suppl): 1636S1640S.
  • 30
    Stipanuk MH, Dominy JE, Lee JI, Coloso RM. Mammalian cysteine metabolism: new insights into regulation of cysteine metabolism. JNutr 2006; 136 ( Suppl): 1652S1659S.
  • 31
    Vitvitsky V, Mosharov E, Tritt M, Ataullakhanov F, Banerjee R. Redox regulation of homocysteine-dependent glutathione synthesis. Redox Rep 2003; 8: 5763.
  • 32
    Engel LS, Taioli E, Pfeiffer R, Garcia-Closas M, Marcus PM, Lan Q, Boffetta P, Vineis P, Autrup H, Bell DA, Branch RA, Brockmoller J, et al. Pooled analysis and meta-analysis of glutathione S-transferase M1 and bladder cancer: a HuGE review. Am J Epidemiol 2002; 156: 95109.