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Cancer Epidemiology Biomarkers & Prevention Vol. 14, 2509-2516, November 2005
© 2005 American Association for Cancer Research

Polymorphisms in the Reduced Folate Carrier, Thymidylate Synthase, or Methionine Synthase and Risk of Colon Cancer

Cornelia M. Ulrich1, Karen Curtin2, John D. Potter1, Jeannette Bigler1, Bette Caan3 and Martha L. Slattery2

1 Fred Hutchinson Cancer Research Center, Seattle, Washington; 2 University of Utah Health Sciences Center, Salt Lake City, Utah; and 3 Kaiser Permanente Medical Care Program, Division of Research, Oakland, California

Requests for reprints: Cornelia M. Ulrich, Cancer Prevention Program, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, M4-B402 Seattle, WA 98109-1024. Phone: 206-667-7617; Fax: 206-667-7850. E-mail: nulrich{at}fhcrc.org


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Folate metabolism supports the synthesis of nucleotides as well as the transfer of methyl groups. Polymorphisms in folate-metabolizing enzymes have been shown to affect risk of colorectal neoplasia and other malignancies. Using data from a population-based incident case-control study (1,600 cases and 1,962 controls), we investigated associations between genetic variants in the reduced folate carrier (RFC), thymidylate synthase (TS), methionine synthase (MTR), and 5,10-methylenetetrahydrofolate reductase (MTHFR) and colon cancer risk. The TS enhancer region (TSER) variant was associated with a reduced risk among men [2rpt/2rpt versus 3rpt/3rpt wild-type; odds ratio (OR), 0.7; 95% confidence interval, 0.6-0.98] but not women. When combined genotypes for both TS polymorphisms (TSER and 3'-untranslated region 1494delTTAAAG) were evaluated, ORs for variant genotypes were generally below 1.0, with statistically significantly reduced risks among women. Neither MTR D919G nor RFC 80G>A polymorphisms were associated with altered colon cancer risk. Because folate metabolism is characterized by interrelated reactions, we evaluated gene-gene interactions. Genotypes resulting in reduced MTHFR activity in conjunction with low TS expression were associated with a reduced risk of colon cancer. When dietary intakes were taken into account, individuals with at least one variant TSER allele (3rpt/2rpt or 2rpt/2rpt) were at reduced risk in the presence of a low folate intake. This study supports findings from adenoma studies indicating that purine synthesis may be a relevant biological mechanism linking folate metabolism to colon cancer risk. A pathway-based approach to data analysis is needed to help discern the independent and combined effects of dietary intakes and genetic variability in folate metabolism.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Folate is an essential micronutrient in humans, the primary function of which is as a carrier of single-carbon units. Folate-dependent reactions include the biosynthesis of thymidylate, purines, methionine, and glycine thus linking it to nucleotide synthesis as well as the provision of methyl groups (1). High dietary folate intakes, or biomarkers thereof, have been associated with a reduced risk of colon cancer or its precursors in most, although not all, studies (2-5). Several studies showing associations with genetic polymorphisms in folate-metabolizing enzymes lend support to a causal relationship between folate and colorectal carcinogenesis (6-10). Biological mechanisms linking folate to colorectal carcinogenesis include an altered provision of S-adenosylmethionine for methylation reactions, including DNA methylation, and changes in the availability of nucleotides, such as thymidylate, for DNA synthesis and repair (11, 12).

We have previously reported on associations between polymorphisms in 5,10-methylenetetrahydrofolate reductase (MTHFR) and risk of colon cancer (13). Here, we extend this work to common genetic variants in thymidylate synthase (TS), the reduced folate carrier (RFC), and methionine synthase (MTR) in relation to colon cancer risk. TS is a key enzyme in folate metabolism that catalyzes the conversion of dUMP to dTMP for the provision of thymidine, a rate-limiting nucleotide essential for DNA synthesis and repair (see Fig. 1). TS is also a primary target for major chemotherapeutic agents, including 5-fluorouracil. We investigated the role of a polymorphism in the 5'-untranslated region (5'-UTR) enhancer region (three or two repeats of a 28-bp sequence), resulting in reduced TS expression among those with fewer repeats (14) and a 6-bp insertion or deletion (1,494 bp in the 3'-UTR) that affects mRNA stability (15, 16).



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  		Figure 1. Simplified version of folate-mediated one-carbon metabolism, highlighting proteins with polymorphisms investigated in this study (figure modified from ref. 36). Key enzymes are denoted as ovals, substrates as rectangles. THF, tetrahydrofolate; DHF, dihydrofolate; DHFR, dihydrofolate reductase; SAM, S-adenosylmethionine; SAH, S-adenosylhomocysteine; dUMP, deoxyuridine monophosphate; dTMP, deoxythymidine monophosphate; X, a variety of substrates for methylation; RFC, reduced folate carrier; hFR, human folate receeptor; MTHFR, 5,10-methylanetetrahydrofolate reductase; GART, phosphoribosylglycinamide formyltransferase; AICARFT, 5-aminomidaole-4-carboximide ribunucleotide; 5-FU, 5-fluorouracil.

 
RFC is responsible for the active transport of 5-methyl-tetrahydrofolate from plasma to cytosol. A polymorphism in the RFC gene (80G>A, Arg27His) seems associated with a higher affinity for folate (17). Among 169 healthy individuals who were stratified by MTHFR 677C>T genotype, the variant A allele was consistently and linearly associated with higher plasma folate concentrations (17). Furthermore, concentrations of methotrexate 24 to 48 hours after administration were higher among children with acute leukemia homozygous for the variant A allele, providing additional support for differential carrier activity among those with variant genotypes (18).

MTR catalyzes the methylation of homocysteine to methionine with simultaneous conversion of 5-methyl-tetrahydrofolate to tetrahydrofolate (Fig. 1). A variant in the MTR gene (2756A>G, Asp919Gly; ref. 19) may affect plasma homocysteine concentrations. Some studies (20, 21) but not others (22-24) have found that homocysteine concentrations tend to decrease linearly across genotypes, with the AA genotype associated with the highest homocysteine concentrations. Studies on colorectal neoplasia have been inconsistent: the GG genotype has been associated with a somewhat reduced risk of colorectal cancer (22, 25) yet a possible increased risk of colorectal adenoma (26).

In this large population-based case-control study of colon cancer, we sought to evaluate the role of these polymorphisms in defining colon cancer risk, either alone or in interaction with specific nutrient intakes and other genotypes. Furthermore, as some of the associations of folate metabolism may differ by estrogen exposure (13), possibly because of mechanisms attributable to hypermethylation of the estrogen receptor (27), we evaluated interactions with postmenopausal hormone (PMH) use.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Participants were African American, Caucasian, or Hispanic subjects from the Kaiser Permanente Medical Care Program of Northern California, an eight-county area in Utah, and the metropolitan Twin Cities area of Minnesota. Eligibility criteria for cases included diagnosis with first-primary incident colon cancer (International Classification of Diseases for Oncology, 2nd edition codes 18.0, 18.2-18.9) between October 1, 1991 and September 30, 1994; between 30 and 79 years of age at time of diagnosis; and mentally competent to complete the interview. Proximal tumors were defined as cecum through transverse colon; tumors in the splenic flexure and descending and sigmoid colon were categorized as distal. Cases with adenocarcinoma or carcinoma of the rectosigmoid junction or rectum (defined as the first 15 cm from the anal opening) or with known familial adenomatous polyposis, ulcerative colitis, or Crohn's disease were not eligible. Of all cases identified, 65% of those contacted consented to participate in the study. Controls who had never had a previous colorectal tumor were randomly selected in proportion to the cases within the geographically defined areas from Kaiser Permanente Medical Care Program membership lists in California; driver's license lists, random digit dialing, or Centers for Medicare and Medicaid Services lists, formerly known as the Health Care Finance Administration, for Utah; and driver's license or state identification lists in Minnesota. Controls were frequency matched to cases by sex and 5-year age group. These methods have been described in detail (28). Of all controls selected, 64% participated.

Data Collection
Trained interviewers collected diet and lifestyle data in person using laptop computers. Study quality control methods have been described (29, 30). The reference period for the study was the calendar year ~2 years before date of diagnosis (cases) or date of selection (controls). Dietary intake data were ascertained using an adaptation of the validated Coronary Artery Risk Development in Young Adults diet history questionnaire (31). Participants were asked to determine which foods were eaten and the frequency with which foods were eaten. Nutrients were calculated using the Minnesota Nutrition Coordinating Center's nutrient database, version 19.

TS, MTR, and RFC genotyping
Of 4,403 cases and controls with valid study data, 3,680 (84%) had blood collected primarily during the in-person interview, or during a clinical visit (83% of cases and 85% of controls). Genomic DNA was extracted using methods described in refs. (14, 32). All samples were genotyped for two polymorphisms in the TS gene (TSER, 3'-UTR 1494delTTAAAG), MTR D919G, and RFC 80G>A. A total of 3,562 (97% of cases and 97% of controls with blood collected) had genotype information for both TSER and 3'-UTR 1494delTTAAAG. 5'-Nuclease assays that had been previously used to genotype other polymorphisms in the folate pathway (MTHFR 677C>T, MTHFR 1298A>C, and MTR D919G) have been described (13, 26).

Both TS polymorphisms were analyzed using fluorescent size discrimination. For the analysis of the TSER 28-bp repeat polymorphism, a fragment containing the repeats was amplified using the following primers: forward primer, 5'-6FAM-GTGGCTCCTGCGTTTCCCCC-3'; reverse primer, 5'-GGCTCCGAGCCGGCCACAGGCATGGCGCGG-3'(14). The PCR reactions contained 1x GeneAmp buffer (Applied Biosystems, Foster City, CA), 1.5 mmol/L MgCl2, 200 µmol/L deoxyribonucleotide triphosphates, 100 nmol/L each primer, 10% DMSO, 1 unit AmpliTaq DNA polymerase (Applied Biosystems), and 100 ng of genomic DNA. Cycling conditions were one cycle of 94°C for 2 minutes; 35 cycles of 94°C for 30 seconds, 63°C for 30 seconds, and 72°C for 30 seconds; and a final extension at 72°C for 5 minutes. The amplified fragments were analyzed on an ABI 3100 genetic analyzer. A fragment containing the 3'-UTR deletion was amplified using the following primers: forward primer, 5'-6FAM-CAAATCTGAGGGAGCTGAGT-3'; reverse primer, 5'-CAGATAAGTGGCAGTACAGA-3'. The PCR reactions contained 1x GeneAmp buffer, 2 mmol/L MgCl2, 150 µmol/L deoxynucleotide triphosphates, 300 nmol/L each primer, 1 unit AmpliTaq DNA polymerase, and 50 ng genomic DNA. Cycling conditions were one cycle of 94°C for 5 minutes; 30 cycles of 94°C for 30 seconds, 60°C for 45 seconds, and 72°C for 60 seconds; and a final extension at 72°C for 10 minutes. The amplified fragments were analyzed on an ABI 3100 genetic analyzer. For both TS polymorphisms, the correlation between fragment size and repeat number was confirmed by sequencing.

The 80G>A polymorphism in RFC was detected by allelic discrimination using the 5' nuclease assay on a 7900HT sequence detection system (ABI). The 5'-nuclease genotyping assay was validated by genotyping 100 individuals by both 5'-nuclease assay and RFLP. There were no discrepancies between the two assays. Genotyping of the 80G>A polymorphism was done in 20-µL reactions containing 1x Taqman PCR core reagents (ABI), 3 mmol/L MgCl2, 200 nmol/L each PCR primer (forward primer, 5'-AGCCCAGCGGTGGAGAAG-3' and reverse primer, 5'-AGCCGTAGAAGCAAAGGTAGCA-3'), 150 nmol/L MGB probe 5'-VIC-TCCTGGCGGCGCC-3' (Applied Biosystems; G allele), 100 nmol/L MGB probe 5'-6-FAM-TGGCGGCACCTCG-3' (A allele), 0.5 unit AmpliTaq Gold, 0.2 unit AmpErase UNG, and 5 ng genomic DNA. The amplification cycles were 50°C for 5 minutes, 95°C for 10 minutes, and 40 cycles of 95°C for 15 seconds and 60°C for 1 minute. Positive controls for all the genotypes as well as four negative controls were included in each plate. For quality control of all the polymorphisms, genotyping for 94 randomly selected samples was repeated. There were no discrepancies.

Statistical Methods
Logistic regression models were used to estimate associations in various ways. We stratified the data by sex and estimated the risk of colon cancer given a certain TS, MTR, or RFC genotype and examined risk estimates further stratified by other population characteristics (e.g., tumor site and age). The combined effects of TSER and 3'-UTR 1494delTTAAAG were calculated using individuals who were homozygous for the common allele at both loci as the reference group. We assessed the joint interaction between genotype and level of nutrient intake by using those with low nutrient intake and homozygous for the most common (wild type) allele for TSER, 3'-UTR, MTR, or RFC as a common reference point. We also assessed gene-gene interactions in the folate pathway using the homozygous genotype for the most common allele as the reference. Similarly, the interaction between genotype and recent estrogen status in postmenopausal women was assessed using as the reference group no PMH use and wild-type TS, MTR, or RFC genotype.

Maximum likelihood estimates of population TS haplotype frequencies from unphased genotype data were obtained from an expectation maximization algorithm, assuming Hardy-Weinberg equilibrium, according to Excoffier and Slatkin (33) using SAS/Genetics software, 2002 (SAS/Genetics, Cary, NC).

Odds ratios (OR) and 95% confidence intervals (95% CI) were calculated from unconditional logistic regression models. In these models, age at diagnosis or selection, body mass index reported for the reference period (kg/m2), long-term vigorous leisure time physical activity, total energy intake, dietary fiber, dietary calcium, and number of cigarettes smoked per day on a regular basis were included as covariates to adjust for potential confounding. Haplotype-specific relative risks were assessed according to methods described in Stram et al. (34) using logistic regression software (SAS, release 8.2).

Separate analyses were done for men and women to determine whether differences existed by sex, as most of the literature has focused on either men or women. Assessment of interactions among genotypes, diet, and the risk of colon cancer were based on departure from additive risks using the relative risk due to interaction formulation of Hosmer and Lemeshow extended to more than two allelic combinations and/or environmental exposures (35). Interaction using a multiplicative scale was also examined. Interactions between genotypes and PMH use in postmenopausal women were assessed using a Wald {chi}2 test of the difference between slopes from the (assumed linear) change in ORs, keeping the wild-type TS genotype constant across the varying genotypes for the respective other TS polymorphism.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Selected characteristics of the study population and MTHFR genotype frequencies by case or control status are presented in Table 1. The study participants were predominantly self-identified as non-Hispanic Caucasian (92%), with the remainder Hispanic (4%) and African American (4%). All genotypes were in Hardy-Weinberg equilibrium (assessed separately for cases and controls), and allele frequencies were consistent with previous reports (36). The TS polymorphisms were in linkage disequilibrium (D' = 0.46 among non-Hispanic Caucasians).


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  		Table 1. Characteristics of the study population (n = 3,562)

 
Table 2 describes the main associations seen with the polymorphisms, stratified by gender. Among men, TSER variant genotypes were associated with a significantly decreased risk (3rpt/2rpt: OR, 0.8; 95% CI, 0.6-0.98; 2rpt/2rpt: OR, 0.7; 95% CI, 0.6-0.98). No such risk reduction was observed among women. When combined genotypes (or diplotypes) for both TS polymorphisms were considered, almost all of the ORs for variant genotypes among both men and women were below 1.0, with statistically significantly reduced risks for women. Risk estimates for TS haplotypes, including variant alleles, compared with wild-type haplotype were not significantly different from 1.0 (data not shown).


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  		Table 2. Association between TS, MTR, and RFC genotypes and colon cancer

 
Neither the MTR D919G nor RFC 80G>A polymorphism was associated with altered colon cancer risk among men or women (Table 2).

Folate metabolism involves circulation of folate metabolites through multiple cycles, as well as feedback mechanisms between these cycles (Fig. 1). Therefore, we evaluated gene-gene interactions between the polymorphisms investigated here, as well as those we have reported on previously (8, 13). ORs different from 1.0 were seen largely for stratifications of TS, RFC, or MTR by MTHFR 677C>T or 1298A>C genotypes, and these are presented in Table 3. Among men, reduced risks associated with variant TS genotypes (e.g., the presence of TSER 2rpt/2rpt or TS 3'-UTR deletion) were most pronounced for those with MTHFR TT genotypes. The MTHFR 1298CC genotype was associated with a decreased risk among women; however, this risk reduction seemed independent of TS genotypes. There was no evidence for interactions between MTR D919G or RFC 80G>A and MTHFR genotypes.


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  		Table 3. Association between polymorphisms in the folate pathway and colon cancer

 
We also investigated whether risk estimates associated with polymorphisms in these folate-metabolizing enzymes differed by dietary intakes of folate, methionine, alcohol, or vitamins B6, B2, or B12. Consistent with our previous report on colorectal adenoma (37) among men, the TSER variant conferred a reduced risk in the presence of low folate intake (lowest tertile < 318 µg/d; TS 2rpt/2rpt or 2rpt/3rpt: OR, 0.7; 95% CI, 0.5-0.9 compared with wild-type 3rpt/3rpt). A similar risk reduction with the TSER variant genotypes was observed among men with low methionine intakes (<2.0 g/d): TS 2rpt/2rpt or 2rpt/3rpt (OR, 0.6; 95% CI, 0.4-0.9) compared with wild-type 3rpt/3rpt. However, none of these patterns was observed among women for the TS genotypes nor for TS haplotypes in either sex. There were no clear patterns or associations following stratification by vitamin B6 or B12 intake. No meaningful differences in risk were observed for MTR genotypes when stratified by nutrient intakes.

Among women in the lowest tertile of folate intake (≤273 µg/d), the RFC variant genotypes were associated with a decreased risk (wild-type GG: OR, 1.0; GA or AA: OR, 0.7; 95% CI, 0.5-1.0). Among women, we observed a significant gene-nutrient interaction in that only those with the GG genotype benefited from a diet higher in folate, whereas no difference in risk with variable folate intake was seen among those with the combined GA or AA genotypes (Pinteraction = 0.04, multiplicative scale; P = 0.01, additive scale). This pattern was not seen among men.

Because of the observed differences in risk patterns among men and women and our past findings regarding an interaction between postmenopausal hormone use (PMH use) and MTHFR genotype, we investigated whether risk estimates of TS, MTR, or RFC genotypes differed by PMH use. Among PMH users, the variant TS genotypes were associated with substantially reduced risk of colon cancer, whereas much weaker associations were observed among non-PMH users (Table 4). No such interactions were observed for MTR or RFC (data not shown).


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  		Table 4. Association among combined TS genotype, postmenopausal hormone (PMH) use, and colon cancer in postmenopausal women

 

   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Within this large population-based study of colon cancer, we investigated polymorphisms in three folate-metabolizing enzymes (TS, MTR, and MTHFR), as well as the relevant carrier protein (RFC), thus addressing genetic variability in multiple key proteins in this biological pathway. There is strong evidence for the functional effect of MTHFR 677C>T and TSER variant genotypes (14, 38-41), with some, yet less well defined, evidence for the in vivo functional relevance of MTR, RFC, and the TS 3'-UTR variant (16-18, 20-23, 42). Our evaluations of colon cancer risk confirm this assessment, in that there were no significant alterations in risk for MTR, RFC, and TS polymorphisms, with the exception of a risk reduction associated with the TSER variants among men. The ORs for TSER are comparable with those from a previous report by Chen et al. (43) among male physicians (OR, 0.9; 95% CI, 0.6-1.3 for the 2rpt/3rpt genotype and OR, 0.6; 95% CI, 0.4-0.98 for the 2rpt/2rpt genotype). A statistically significant trend towards reduced risk with the variant TSER alleles was observed both here and in that population (43). These results indicate that the variant TSER 2rpt/2rpt genotype reduces risk of colon or colorectal cancer among men to a degree comparable with that of the MTHFR 677TT genotype (44). As risk reductions for TSER variants were only seen among women who are on postmenopausal hormones but not among women overall, estrogen status may play a role.

Further complexity is added as a result of the presence of a second functionally relevant polymorphism in TS (15, 16). We evaluated the combined effects of these genotypes as well as haplotypes to discern possible risk patterns. The combined TS wild type/wild type genotype constitutes only 8.3% of our population. When compared with this wild type/wild type reference group of putatively highest TS expression and TS mRNA stability, the variant TSER genotypes were associated with statistically significantly reduced risk among women (OR, 0.6; 95% CI, 0.4-0.9) yet not among men. Our sample sizes for these sex-specific associations were limited, and results should be followed up in large study populations that have the ability to investigate combined genotypes as well as sex-specific ORs. The presence of two common functional variants within TS suggests that it is essential to take both of these into account simultaneously.

The MTR polymorphism is less common (allele frequency = 0.20) and has been investigated in three epidemiologic studies, including a large Norwegian cohort (7, 25, 45). Similar to our findings, Le Marchand et al. (45) and Chen et al. (7) did not report any associations between this variant and colon cancer risk, whereas Ulvik et al. (25) observed a significantly reduced risk among those with a GG genotype compared with wild-type AA (OR, 0.65; 95% CI, 0.47-0.90). We observed reduced risks among men (OR, 0.7), but the 95% CI included 1.0. As only about 5% of the population have the homozygous variant genotype, very large studies are needed to quantify the strength of this association.

For gene-gene interactions, only combinations with the MTHFR polymorphisms showed interesting patterns. This is not surprising, because MTHFR is a key regulatory enzyme in folate-mediated one-carbon metabolism, the activity of which determines the distribution of folate metabolites toward nucleotide synthesis or methylation reactions. There is strong evidence that the MTHFR 677C>T variant alters the balance of metabolites within the pathway (39, 46). In combined analyses of TS and MTHFR polymorphisms, we observed that men carrying at least one variant TS allele (either TSER 2rpt or TS 1494del) in addition to the MTHFR 677TT genotype were at relatively lowest risk compared with all other groups (both OR, 0.6; 95% CI, 0.4-0.9). This confirms our previous observation in colorectal adenoma, where individuals with low TS expression and low MTHFR activity genotypes also experienced the lowest adenoma risk (OR, 0.56; ref. 10). If this statistical interaction reflects biological mechanisms, then we may hypothesize that the observed pattern suggests that a greater diversion of folate metabolites (specifically 5,10-methylene-tetrahydrofolate) toward purine synthesis is protective for the development of colorectal neoplasia. Recent findings by Quinlivan et al. suggest that folate depletion adversely affects purine synthesis in humans and a greater relative rate of adenine synthesis among individuals with the MTHFR TT genotype (46). Depurination is the most common type of DNA damage with ~10,000 depurinations/cell/d (47, 48). Although efficiently repaired, apurinic sites are present in DNA. We recognize that one other study did not observe this risk pattern, but their sample size was limited to 270 cases, with consequent restricted power for studying gene-gene interactions (43).

Our investigations of gene-diet interactions confirmed, to some extent, associations we have previously observed with respect to TSER, and folate intake that reduced TS expression (TSER 2rpt/2rpt) is associated with a reduced risk in the presence of a low folate intake (10). However, this pattern was seen only among men and also has not been observed in the Health Professionals study (43). Again, if that pattern reflects a biological mechanism, it would point toward purine synthesis as a key link between one-carbon metabolism and colorectal neoplasia. We were unable to confirm previously observed gene-diet interactions for MTR in colorectal adenoma (26) and did not see a clear pattern for RFC-diet interactions. However, the RFC is the transporter for naturally occurring folates (in the form of 5-methyl-tetrahydrofolate) but plays a smaller role in the transport of folic acid (49). Thus, in populations, such as the one described here, where folate intake from supplements in the form of folic acid comprises a substantial proportion of the overall folate intake, genetic variability in the RFC may not be as relevant for the overall supply of folate metabolites. Unfortunately, no quantitative information on supplement use was available for this population.

Lastly, we observed differences in risk patterns dependent on the past use of postmenopausal hormones. Interactions between folate metabolism and PMH use are not implausible, as there are links between homocysteine concentrations and PMH use (50-53), and methylation of the estrogen receptor is an early event in colorectal carcinogenesis, which may less frequently occur in the presence of PMH (27, 54). We have previously reported on a significant difference in risk patterns of PMH-associated risks by MTHFR genotypes (13). However, these interactions need to be confirmed by others, because sample sizes were in parts insufficient to yield stable estimates.

Although this study is quite comprehensive with respect to investigations of genetic variability in one-carbon metabolism and risk of colon cancer, there are three important limitations. First, our investigations did not include other genetic polymorphisms in folate-metabolizing enzymes that may be of possible relevance, such as methionine-synthase reductase (MTRR) or serine-hydroxymethyltransferase (SHMT). Thus far, MTRR does not seem related to colon cancer risk (45), and the functional relevance of the cSHMT polymorphisms is unclear. The study presented here focused on candidate polymorphisms in key enzymes with substantial evidence for functional effect; we hope to expand our investigations to other relevant candidate polymorphisms as they are reported.

Second, there is now strong evidence that a subset of colorectal cancer cases arises as part of a CpG island methylator phenotype (55, 56). Information on CpG island methylator phenotype status should be taken into account in future studies investigating links between genetic variability in folate metabolism and risk of colorectal cancer.

A final limitation is our current inability to integrate knowledge of biochemical relationships within the pathway into the statistical analysis. Although an approach that uses stratification for gene-nutrient or gene-gene interactions is valuable, in that it allows for an empirical investigation of the associations, it is also limited in that statistical power for higher-order interactions is lacking, even within this large study population. Because folate metabolism consists of several interconnected cycles (see Fig. 1), such interactions are to be expected. Our approach toward solving this problem is to use, in the future, results from a mathematical model of one-carbon biochemistry for investigations of multiple genetic variants on selected biomarkers. Although this model is still under development, preliminary results show that it replicates the biochemical relationships in the folate cycle and methionine cycle with reasonable accuracy (57, 58). Furthermore, our group and others are developing methods to address this key problem for molecular epidemiologic studies (59). Thus, we hope that in the future, we will be able to achieve closer integration of the biochemistry and statistical analysis. Because there is strong evidence that disturbances in this biochemical pathway can modify risk of several types of malignancies (60-63), birth outcomes (64-66), and possibly cardiovascular disease (67) and autism (68), a more thorough understanding of the interplay of multiple genetic polymorphisms under specific dietary conditions and their combined effect on biomarkers and disease end points will be highly relevant.


   Acknowledgments
 
We thank Sandra Edwards and Leslie Palmer at the University of Utah for data collection efforts of this study, Clayton Hibbert and Linda Massey for word processing assistance, and Juanita Leija for genotyping assays.


   Footnotes
 
Grant support: NIH grants R01 CA48998 and R01 CA59045.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Note: C.M. Ulrich and K. Curtin contributed equally to this work.

Received 4/14/05; revised 8/10/05; accepted 9/ 8/05.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

  1. Wagner C. Biochemical role of folate in cellular metabolism. Folate in health and disease. New York: Marcel Dekker; 1995.
  2. World Cancer Research Fund. Diet, nutrition, and the prevention of cancer: a global perspective. Washington (DC): World Cancer Research Fund/American Institute for Cancer Research; 1997.
  3. Giovannucci E. Epidemiologic studies of folate and colorectal neoplasia: a review. J Nutr 2002;132:2350–5S.
  4. Marugame T, Tsuji E, Kiyohara C, et al. Relation of plasma folate and methylenetetrahydrofolate reductase C677T polymorphism to colorectal adenomas [comment]. Int J Epidemiol 2003;32:64–6.[Abstract/Free Full Text]
  5. Pufulete M, Al-Ghnaniem R, Leather AJ, et al. Folate status, genomic DNA hypomethylation, and risk of colorectal adenoma and cancer: a case control study. Gastroenterology 2003;124:1240–8.[CrossRef][Medline]
  6. Ma J, Stampfer MJ, Giovannucci E, et al. Methylenetetrahydrofolate reductase polymorphism, dietary interactions, and risk of colorectal cancer. Cancer Res 1997;57:1098–102.[Abstract/Free Full Text]
  7. Chen J, Giovannucci E, Hankinson SE, et al. A prospective study of methylenetetrahydrofolate reductase and methionine synthase gene polymorphisms, and risk of colorectal adenoma. Carcinogenesis 1998;19:2129–32.[Abstract/Free Full Text]
  8. Slattery ML, Potter JD, Samowitz W, Schaffer D, Leppert M. Methylenetetrahydrofolate reductase, diet, and risk of colon cancer. Cancer Epidemiol Biomarkers Prev 1999;8:513–8.[Abstract/Free Full Text]
  9. Ulrich CM, Kampman E, Bigler J, et al. Colorectal adenomas and the C677T MTHFR polymorphism: evidence for gene-environment interaction? Cancer Epidemiol Biomarkers Prev 1999;8:659–68.[Abstract/Free Full Text]
  10. Ulrich CM, Bigler J, Bostick R, Fosdick L, Potter JD. Thymidylate synthase promoter polymorphism, interaction with folate intake, and risk of colorectal adenomas. Cancer Res 2002;62:3361–4.[Abstract/Free Full Text]
  11. Choi SW, Mason JB. Folate and carcinogenesis: an integrated scheme. J Nutr 2000;130:129–32.[Abstract/Free Full Text]
  12. Duthie SJ. Folic acid deficiency and cancer: mechanisms of DNA instability. Br Med Bull 1999;55:578–92.[Abstract/Free Full Text]
  13. Curtin K, Bigler J, Slattery ML, Caan B, Potter JD, Ulrich CM. MTHFR C677T and A1298C polymorphisms: diet, estrogen, and risk of colon cancer. Cancer Epidemiol Biomarkers Prev 2004;13:285–92.[Abstract/Free Full Text]
  14. Horie N, Aiba H, Oguro K, Hojo H, Takeishi K. Functional analysis and DNA polymorphism of the tandemly repeated sequences in the 5'-terminal regulatory region of the human gene for thymidylate synthase. Cell Struct Funct 1995;20:191–7.[Medline]
  15. Ulrich C, Bigler J, Velicer C, Greene E, Farin F, Potter J. Searching expressed sequence tag databases: discovery and confirmation of a common polymorphism in the thymidylate synthase gene. Cancer Epidemiol Biomarkers Prev 2000;9:1381–5.[Abstract/Free Full Text]
  16. Mandola MV, Stoehlmacher J, Zhang W, et al. A 6 bp polymorphism in the thymidylate synthase gene causes message instability and is associated with decreased intratumoral TS mRNA levels. Pharmacogenetics 2004;14:319–27.[CrossRef][Medline]
  17. Chango A, Emery-Fillon N, de Courcy GP, et al. A polymorphism (80G->A) in the reduced folate carrier gene and its associations with folate status and homocysteinemia. Mol Genet Metab 2000;70:310–5.[CrossRef][Medline]
  18. Laverdiere C, Chiasson S, Costea I, Moghrabi A, Krajinovic M. Polymorphism G80A in the reduced folate carrier gene and its relationship to methotrexate plasma levels and outcome of childhood acute lymphoblastic leukemia. Blood 2002;100:3832–4.[Abstract/Free Full Text]
  19. Leclerc D, Wilson A, Dumas R, et al. Cloning and mapping of a cDNA for methionine synthase reductase, a flavoprotein defective in patients with homocystinuria. Proc Natl Acad Sci U S A 1998;95:3059–64.[Abstract/Free Full Text]
  20. Chen J, Stampfer MJ, Ma J, et al. Influence of a methionine synthase (D919G) polymorphism on plasma homocysteine and folate levels and relation to risk of myocardial infarction. Atherosclerosis 2001;154:667–72.[CrossRef][Medline]
  21. Harmon D, Shields D, Woodside J, et al. Methionine synthase D919G polymorphism is a significant but modest determinant of circulating homocysteine concentrations. Genet Epidemiol 1999;17:298–309.[CrossRef][Medline]
  22. Ma J, Stampfer MJ, Christensen B, et al. A polymorphism of the methionine synthase gene: association with plasma folate, vitamin B12, homocyst(e)ine, and colorectal cancer risk. Cancer Epidemiol Biomarkers Prev 1999;8:825–9.[Abstract/Free Full Text]
  23. van der Put NM, van der Molen EF, Kluijtmans LA, et al. Sequence analysis of the coding region of human methionine synthase: relevance to hyperhomocysteinaemia in neural-tube defects and vascular disease. QJM 1997;90:511–7.[Abstract/Free Full Text]
  24. Jacques PF, Bostom AG, Selhub J, et al. Effects of polymorphisms of methionine synthase and methionine synthase reductase on total plasma homocysteine in the NHLBI Family Heart Study. Atherosclerosis 2003;166:49–55.[CrossRef][Medline]
  25. Ulvik A, Vollset SE, Hansen S, Gislefoss R, Jellum E, Ueland PM. Colorectal cancer and the methylenetetrahydrofolate reductase 677C -> T and methionine synthase 2756A -> G polymorphisms: a study of 2,168 case-control pairs from the JANUS Cohort. Cancer Epidemiol Biomarkers Prev 2004;13:2175–80.[Abstract/Free Full Text]
  26. Goode EL, Potter JD, Bigler J, Ulrich CM. Methionine synthase D919G polymorphism, folate metabolism, and colorectal adenoma risk. Cancer Epidemiol Biomarkers Prev 2004;13:157–62.[Abstract/Free Full Text]
  27. Issa JP, Ottaviano YL, Celano P, Hamilton SR, Davidson NE, Baylin SB. Methylation of the oestrogen receptor CpG island links ageing and neoplasia in human colon. Nat Gen 1994;7:536–40.[CrossRef][Medline]
  28. Slattery ML, Edwards SL, Caan BJ, Kerber RA, Potter JD. Response rates among control subjects in case-control studies. Ann Epidemiol 1995;5:245–9.[CrossRef][Medline]
  29. Slattery ML, Caan BJ, Duncan D, Berry TD, Coates A, Kerber R. A computerized diet history questionnaire for epidemiologic studies. J Am Diet Assoc 1994;94:761–6.[CrossRef][Medline]
  30. Edwards S, Slattery ML, Mori M, et al. Objective system for interviewer performance evaluation for use in epidemiologic studies. Am J Epidemiol 1994;140:1020–8.[Abstract/Free Full Text]
  31. Liu K, Slattery M, Jacobs D, Jr., et al. A study of the reliability and comparative validity of the cardia dietary history. Ethn Dis 1994;4:15–27.[Medline]
  32. Kampman E, Slattery ML, Bigler J, et al. Meat consumption, genetic susceptibility, and colon cancer risk: a United States multicenter case-control study. Cancer Epidemiol Biomarkers Prev 1999;8:15–24.[Abstract/Free Full Text]
  33. Excoffier L, Slatkin M. Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population. Mol Biol Evol 1995;12:921–7.[Abstract]
  34. Stram DO, Haiman CA, Hirschhorn JN, et al. Choosing haplotype-tagging SNPS based on unphased genotype data using a preliminary sample of unrelated subjects with an example from the Multiethnic Cohort Study. Hum Hered 2003;55:27–36.[CrossRef][Medline]
  35. Hosmer DW, Lemeshow S. Confidence interval estimation of interaction. Epidemiology 1992;3:452–6.[Medline]
  36. Ulrich CM, Robien K, Sparks R. Pharmacogenetics and folate metabolism - a promising direction. Pharmacogenomics 2002;3:299–313.[CrossRef][Medline]
  37. Ulrich CM, Potter JD. Thymidylate synthase polymorphism and survival of colorectal cancer patients treated with 5-fluorouracil [comment]. Br J Cancer 2002;86:22.
  38. Frosst P, Blom HJ, Milos R, et al. A candidate genetic risk factor for vascular disease: a common mutation in methylenetetrahydrofolate reductase [letter]. Nat Gen 1995;10:111–3.[CrossRef][Medline]
  39. Bagley PJ, Selhub J. A common mutation in the methylenetetrahydrofolate reductase gene is associated with an accumulation of formylated tetrahydrofolates in red blood cells. Proc Natl Acad Sci U S A 1998;95:13217–20.[Abstract/Free Full Text]
  40. Pullarkat ST, Stoehlmacher J, Ghaderi V, et al. Thymidylate synthase gene polymorphism determines response and toxicity of 5-FU chemotherapy. Pharmacogenomics J 2001;1:65–70.[Medline]
  41. Trinh BN, Ong C-N, Coetzee GA, Yu MC, Laird PW. Thymidylate synthase: a novel genetic determinant of plasma homocysteine and folate levels. Hum Genet 2002;111:299–302.[CrossRef][Medline]
  42. Whetstine JR, Gifford AJ, Witt T, et al. Single nucleotide polymorphisms in the human reduced folate carrier: characterization of a high-frequency G/A variant at position 80 and transport properties of the His(27) and Arg(27) carriers. Clin Cancer Res 2001;7:3416–22.[Abstract/Free Full Text]
  43. Chen J, Hunter DJ, Stampfer MJ, et al. Polymorphism in the thymidylate synthase promoter enhancer region modifies the risk and survival of colorectal cancer. Cancer Epidemiol Biomarkers Prev 2003;12:958–62.[Abstract/Free Full Text]
  44. Houlston RS, Tomlinson IP. Polymorphisms and colorectal tumor risk. Gastroenterology 2001;121:282–301.[CrossRef][Medline]
  45. Le Marchand L, Donlon T, Hankin JH, Kolonel LN, Wilkens LR, Seifried A. B-vitamin intake, metabolic genes, and colorectal cancer risk (United States). Cancer Causes Control 2002;13:239–48.[CrossRef][Medline]
  46. Quinlivan EP, Davis SR, Shelnutt KP, et al. Methylenetetrahydrofolate reductase 677C>T polymorphism and folate status affect one-carbon incorporation into human DNA deoxynucleosides. J Nutr 2005;135:389–96.[Abstract/Free Full Text]
  47. Lindahl T, Nyberg B. Rate of depurination of native deoxyribonucleic acid. Biochemistry 1972;11:3610–8.[CrossRef][Medline]
  48. Nakamura J, Swenberg JA. Endogenous apurinic/apyrimidinic sites in genomic DNA of mammalian tissues. Cancer Res 1999;59:2522–6.[Abstract/Free Full Text]
  49. Antony AC. The biological chemistry of folate receptors. Blood 1992;79:2807–20.[Free Full Text]
  50. van Baal WM, Smolders RG, van der Mooren MJ, Teerlink T, Kenemans P. Hormone replacement therapy and plasma homocysteine levels. Obstet Gynecol 1999;94:485–91.[CrossRef][Medline]
  51. Smolders RG, Vogelvang TE, Mijatovic V, et al. A 2-year, randomized, comparative, placebo-controlled study on the effects of raloxifene on lipoprotein(a) and homocysteine. Maturitas 2002;41:105–14.[Medline]
  52. Somekawa Y, Kobayashi K, Tomura S, Aso T, Hamaguchi H. Effects of hormone replacement therapy and methylenetetrahydrofolate reductase polymorphism on plasma folate and homocysteine levels in postmenopausal Japanese women. Fertil Steril 2002;77:481–6.[CrossRef][Medline]
  53. Mijatovic V, van der Mooren MJ. Homocysteine in postmenopausal women and the importance of hormone replacement therapy. Clin Chem Lab Med 2001;39:764–7.[CrossRef][Medline]
  54. Baylin SB, Herman JG, Graff JR, Vertino PM, Issa JP. Alterations in DNA methylation: a fundamental aspect of neoplasia. Adv Cancer Res 1998;72:141–96.[Medline]
  55. Issa JP. Opinion: CpG island methylator phenotype in cancer. Nat Rev Cancer 2004;4:988–93.[CrossRef][Medline]
  56. Laird PW. Cancer epigenetics. Hum Mol Genet 2005;14 Spec No 1:R65–76.[Abstract/Free Full Text]
  57. Reed MC, Nijhout HF, Sparks R, Ulrich CM. A mathematical model of the methionine cycle. J Theor Biol 2004;226:33–43.[CrossRef][Medline]
  58. Nijhout HF, Reed MC, Budu P, Ulrich CM. A mathematical model of the folate cycle: new insights into folate homeostasis. J Biol Chem 2004;279:55008–16.[Abstract/Free Full Text]
  59. Thomas DC. The need for a systematic approach to complex pathways in molecular epidemiology. Cancer Epidemiol Biomarkers Prev 2005;14:557–9.[Free Full Text]
  60. Skibola CF, Forrest MS, Coppede F, et al. Polymorphisms and haplotypes in folate-metabolizing genes and risk of non-Hodgkin lymphoma. Blood 2004;104:2155–62.[Abstract/Free Full Text]
  61. Skibola CF, Smith MT, Hubbard A, et al. Polymorphisms in the thymidylate synthase and serine hydroxymethyltransferase genes and risk of adult acute lymphocytic leukemia. Blood 2002;99:3786–91.[Abstract/Free Full Text]
  62. Skibola CF, Smith MT, Kane E, et al. Polymorphisms in the methylenetetrahydrofolate reductase gene are associated with susceptibility to acute leukemia in adults. Proc Natl Acad Sci U S A 1999;96:12810–5.[Abstract/Free Full Text]
  63. Wiemels JL, Smith RN, Taylor GM, et al. Methylenetetrahydrofolate reductase (MTHFR) polymorphisms and risk of molecularly defined subtypes of childhood acute leukemia. Proc Natl Acad Sci U S A 2001;98:4004–9.[Abstract/Free Full Text]
  64. Nurk E, Tell GS, Refsum H, Ueland PM, Vollset SE. Associations between maternal methylenetetrahydrofolate reductase polymorphisms and adverse outcomes of pregnancy: the Hordaland Homocysteine Study. Am J Med 2004;117:26–31.[CrossRef][Medline]
  65. O'Leary VB, Parle-McDermott A, Molloy AM, et al. MTRR and MTHFR polymorphism: link to Down syndrome? Am J Med Genet 2002;107:151–5.[CrossRef][Medline]
  66. Schwahn B, Rozen R. Polymorphisms in the methylenetetrahydrofolate reductase gene: clinical consequences. Am J Pharmacogenomics 2001;1:189–201.[CrossRef][Medline]
  67. De Bree A, Verschuren WM, Kromhout D, Kluijtmans LA, Blom HJ. Homocysteine determinants and the evidence to what extent homocysteine determines the risk of coronary heart disease. Pharmacol Rev 2002;54:599–618.[Abstract/Free Full Text]
  68. James SJ, Cutler P, Melnyk S, et al. Metabolic biomarkers of increased oxidative stress and impaired methylation capacity in children with autism. Am J Clin Nutr 2004;80:1611–7.[Abstract/Free Full Text]



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