Background: Folate-associated one-carbon metabolism (FOCM) may play an important role in colorectal carcinogenesis. Variation in FOCM genes may explain some of the underlying risk of colorectal cancer.

Methods: This study utilized data from 1,805 population-based colorectal cancer cases and 2,878 matched sibling controls from the Colon Cancer Family Registry. We used a comprehensive haplotype tagging single nucleotide polymorphism (tagSNP) approach to select 395 tagSNPs in 15 genes involved in folate and vitamin B12 metabolism. Genotyping was done using the Illumina GoldenGate or Sequenom platforms. Risk factor and dietary data were collected using self-completed questionnaires. Microsatellite instability (MSI) status was determined using standard techniques, and tumor subsite was obtained from pathology reports. The association between SNPs and colorectal cancer was assessed using conditional logistic regression with sibships as the matching factor and assuming a log additive or codominant model.

Results: In the log additive model, two linked (r2 = 0.99) tagSNPs in the DHFR gene (rs1677693 and rs1643659) were associated with a significant decrease in colorectal cancer risk after correction for multiple testing (odds ratio, 0.87; 95% confidence interval, 0.71-0.94; P = 0.029; and odds ratio, 0.87; 95% confidence interval, 0.71-0.95; P = 0.034 for rs1677693 and rs1643659, respectively). These two linked (r2 = 0.99) tagSNPs and one tagSNP in the MTR gene (rs4659744) were significantly associated with reduced colorectal cancer risk only among individuals not using multivitamin supplements.

Conclusions: Overall, we found only moderate evidence that genetic variation in 15 folate pathway genes may affect colorectal cancer risk except in non–multivitamin users.

Impact: This study suggests that multivitamin supplement use may modify the association between folate pathway genes and colorectal cancer risk in a post-folic-acid-supplemented population. Cancer Epidemiol Biomarkers Prev; 19(7); 1812–21. ©2010 AACR.

This article is featured in Highlights of This Issue, p. 1663

Folates carry most of the one-carbon groups essential for hundreds of intracellular transmethylation reactions, including those involved in DNA methylation and DNA synthesis. A role for these reactions and the carcinogenic changes important in colorectal cancer has been defined, both in vitro and in vivo, in both humans and animals (1-3).

Folates are a family of molecules that have a common structure based on a pteridine ring conjugated to one or more glutamate side chains. This basic structure is modified by the binding of various single-carbon groups to the pteridine ring. Folate-associated one-carbon metabolism (FOCM) provides the one-carbon groups for numerous critical intracellular reactions, including methionine synthesis, the de novo synthesis of dTMP from dUMP, and de novo purine synthesis (2). Methionine synthesis is the first step in the synthesis of S-adenosylmethionine (SAM). SAM is the primary methyl donor for hundreds of intracellular methylation reactions, including the methylation of DNA. Aberrant DNA methylation, either global hypomethylation or hypermethylation of tumor suppressor genes, plays a key role in colorectal carcinogenesis (4). Global hypomethylation is associated with chromosomal instability and aneuploidy (5, 6), whereas hypermethylation is associated with loss of transcription, which can affect the activity of tumor suppressor genes (4). Low-folate conditions have also been associated with increased uracil in DNA (7, 8) and increased DNA damage (9).

Dietary folates have been associated with decreased colorectal neoplasia risk (1). However, their role in populations exposed to folic acid fortification of grain products is less clear (10, 11). Folic acid is the monoglutamated folate form, not found in nature, that is used in supplements and for fortifying cereal grain products in North America. In experimental preclinical studies the effect of folic acid supplementation on the risk of colon tumor formation depended upon the timing of its administration. Increased dietary folic acid decreased the number of intestinal tumors when given to APC min/ and APC min/MSH2/ mice before the onset of preneoplastic foci, but the number of tumors was increased significantly when given after the establishment of preneoplastic foci (12, 13). Some recent human studies also suggest that neoplasia risk may be increased in those taking high doses of folic acid from supplements (14-18) in the context of a folic acid–supplemented diet. In this regard Mason et al. documented a significant trend toward increasing colorectal cancer incidence in the United States and Canada coincident with the fortification of grain products with folic acid (19). The present study population was recruited after fortification of the U.S. and Canadian food supplies and so represents one of the first postfortification study cohorts in which to assess associations between folate-associated FOCM-associated genes and colorectal cancer risk.

Several studies have reported on the potential significance of polymorphic variation in FOCM-associated genes and colorectal cancer risk, but all of these studies have been restricted to a few variants in a limited number of genes (3, 20). We conducted a systematic investigation of genetic variation in 15 folate pathway genes involved in nucleotide synthesis, methionine metabolism, uptake and distribution of vitamin B12, and polyamine synthesis (Table 1), and colorectal cancer risk using a comprehensive tagSNP approach. Previous analyses in this population included variation in MTHFR (21), where we reported an association only for the C677T TT and A1298C CC genotypes in non–multivitamin supplement users, and four genes involved in folate uptake and distribution: the reduced folate carrier 1 (RFC1/SLC19A1), folate receptor 1 (FOLR1), γ-glutamyl hydrolase (GGH), and folylpolyglutamate synthase (FPGS). None of these genes were associated with colorectal cancer risk in any subgroup (22).

Table 1.

Genes involved in folate and vitamin B12 metabolism

GeneFunction
ADA Catalyzes the deamination of adenosine and 2′deoxyadenosine to their inosine derivatives. Linked to ACHY on chr. 20. Adenosine inhibits AHCY activity. 
ADH1C Metabolizes alcohol to acetaldehyde, a folate antagonist, in the colon. 
AHCY (SAHHCatalyzes the reversible hydrolysis of SAH, HCY, and adenosine. Linked to ADA on chr. 20. Activity is linked to the presence of ADA. 
AMD1 Catalyzes SAM decarboxylation to ornithine, the rate-limiting substrate for polyamine synthesis. 
CBS Catalyzes the transsulfuration of homocysteine to cysteine, the precursor for glutathione synthesis and an important mechanism for controlling intracellular homocysteine. 
DHFR Converts dihydrofolate into tetrahydrofolate, preventing the trapping of folates as dihydrofolates, which cannot be used in subsequent methyl group transfers. 
GIF Binds cobalamin (B12) for transport from the gut to the circulation. 
IFCR (CUBN) Transfers cobalamin (B12) from GIF to TC II (TCN2). 
MAT2A In nonliver tissues, MAT2A catalyzes the biosynthesis of SAM from methionine and ATP. 
MTHFD1 Catalyzes the transfer of methylene and formyl groups for the initial steps of purine synthesis. 
MTR With B12, catalyzes the transfer of a methyl group to HCY to form methionine, the first step in SAM synthesis. This reaction can trap folates as MTHF which cannot be recycled via the SHMT reaction or can oxidize B12 also preventing additional reactions (the “folate trap”). 
MTRR Catalyzes reduction of oxidized B12 releasing MTR and B12 for further reactions. 
SHMT1 Catalyzes the rate-limiting step in 5-10MTHF synthesis, itself the initial step of folate metabolism in cytoplasm. 5-10MTHF is the methyl group donor for pyrimidine and the substrate for the methyl groups involved in purine synthesis. 
TC II (TCN2The primary transport protein for cobalamin (vitamin B12) in plasma. 
TYMS (TSCatalyzes transfer of a methyl group from 5,10-MTHF to dUMP to form dTMP to maintain balanced nucleotide pools. 
GeneFunction
ADA Catalyzes the deamination of adenosine and 2′deoxyadenosine to their inosine derivatives. Linked to ACHY on chr. 20. Adenosine inhibits AHCY activity. 
ADH1C Metabolizes alcohol to acetaldehyde, a folate antagonist, in the colon. 
AHCY (SAHHCatalyzes the reversible hydrolysis of SAH, HCY, and adenosine. Linked to ADA on chr. 20. Activity is linked to the presence of ADA. 
AMD1 Catalyzes SAM decarboxylation to ornithine, the rate-limiting substrate for polyamine synthesis. 
CBS Catalyzes the transsulfuration of homocysteine to cysteine, the precursor for glutathione synthesis and an important mechanism for controlling intracellular homocysteine. 
DHFR Converts dihydrofolate into tetrahydrofolate, preventing the trapping of folates as dihydrofolates, which cannot be used in subsequent methyl group transfers. 
GIF Binds cobalamin (B12) for transport from the gut to the circulation. 
IFCR (CUBN) Transfers cobalamin (B12) from GIF to TC II (TCN2). 
MAT2A In nonliver tissues, MAT2A catalyzes the biosynthesis of SAM from methionine and ATP. 
MTHFD1 Catalyzes the transfer of methylene and formyl groups for the initial steps of purine synthesis. 
MTR With B12, catalyzes the transfer of a methyl group to HCY to form methionine, the first step in SAM synthesis. This reaction can trap folates as MTHF which cannot be recycled via the SHMT reaction or can oxidize B12 also preventing additional reactions (the “folate trap”). 
MTRR Catalyzes reduction of oxidized B12 releasing MTR and B12 for further reactions. 
SHMT1 Catalyzes the rate-limiting step in 5-10MTHF synthesis, itself the initial step of folate metabolism in cytoplasm. 5-10MTHF is the methyl group donor for pyrimidine and the substrate for the methyl groups involved in purine synthesis. 
TC II (TCN2The primary transport protein for cobalamin (vitamin B12) in plasma. 
TYMS (TSCatalyzes transfer of a methyl group from 5,10-MTHF to dUMP to form dTMP to maintain balanced nucleotide pools. 

Abbreviations: ADA, adenosine deaminase; ADH1C, alcohol dehydrogenase-1C; AHCY, adenosylhomocysteine hydrolase; AMD1, S-adenosylmethionine decarboxylase; CBS, cystathionine-β-synthase; GIF, Gastric intrinsic factor; IFCR (CUBN), intrinsic factor cobalamin receptor (also known as cubulin); MAT2A, methionine adenosyl-transferase isoform 2 (non-liver); MTHFD1, methylenetetrahydrofolate dehydrogenase/methynltetrahydrofolate-cyclohydrolase/formyltetrahydrofolate synthetase; MTRR, methionine synthase reductase; SHMT, serine hydroxymethyltransferase; TC II (also known as TCN2) Transcobalamin transporter 2; TYMS, thymidylate synthase.

Study population

The methods used for this study are described in detail in Levine et al. (21). A total of 1,806 cases and their sibling controls (n = 2,879) were enrolled in the six sites of the Colon Cancer Family Registry (C-CFR), a National Cancer Institute (NCI)-supported consortium initiated in 1997 (23). Details of subject recruitment can be found in Newcomb et al. (24). Briefly, cases were recruited in two phases, from 1998 to 2002 (phase 1) and from 2002 to 2007 (phase 2). Phase 2 subjects were enriched in cases more likely to have a family history of colorectal cancer. In this study we used only cases that were identified through population-based cancer registries as described by Newcomb et al. (24). Controls were the unaffected siblings of cases. All subjects signed an informed consent before providing data to the C-CFR.

SNP selection

TagSNPs were selected using Haploview Tagger (25) for the CEU population as described (21). The linkage disequilibrium (LD) blocks were determined using data from HapMap data release #16c.1, June 2005, on National Center for Biotechnology Information (NCBI) B34 assembly, dbSNP b124. For each gene, we extended the 5′- and 3′-untranslated regions to include the 5′- and 3′-most SNP within the LD block (approximately 10 kb upstream and 5 kb downstream). In regions of no or low LD, SNPs with minor allele frequency (MAF) >5% at a density of approximately 1 per kb were selected from either HapMap or dbSNP. Finally, nonsynonymous SNPs and expert-curated SNPs regardless of MAF were included. A total of 395 SNPs met our criteria of a MAF ≥0.05 and a P value for Hardy Weinberg equilibrium of ≥0.00013.

SNP genotyping

SNPs were genotyped on the Illumina 1536 GoldenGate platform (26). We implemented a series of quality control checks based on Illumina metrics, as described previously (21). We did additional genotyping using Sequenom's iPLEX Gold for 13 SNPs that were not successfully genotyped on the Illumina platform as described (21). PCR and extension primers for these SNPs are available upon request.

MSI testing

All available tumors were assayed for instability at as many as 10 microsatellite markers: BAT25, BAT26, BAT40, BAT34C4, D5S346, D17S250, D18S55, D10S197, ACTC, and MYCL as described (24). MSI data were available for 1,200 (66.4%) cases, including all phase 1 tumors in probands and their relatives with tumors that had clear results for at least four markers, and a sample of phase 2 tumors as described by Newcomb et al. (24). Instability at ≥30% of the tested loci was defined as MSI-H, instability at ≥10% but <30% of loci was defined as MSI-L, and those with instability at 0 loci were categorized as MSS. MSI-L and MSS cases were combined in the analysis.

Colon subsite

Colon subsite was obtained by reviewing pathology reports. Right colon was defined as occurring in the cecum through the splenic flexure, left colon included the descending colon through the sigmoid colon, and rectal tumors included the recto-sigmoid junction and the rectum.

Folate supplement use, multivitamin use, and family history of colorectal cancer

A standard risk factor questionnaire, described in Newcomb et al. (24), was administered to all participants at recruitment and available for approximately 98% of the study population. Family history of colorectal cancer was defined as any 1st-degree relative with colorectal cancer. Folate and multivitamin supplement use was defined as ever use at least twice a week for more than a month.

Dietary folate intake

Estimated dietary folate intake, available for 585 cases, 837 controls (about one third of the study population), was estimated from a validated food frequency questionnaire developed at the University of Hawaii (27) and available only for subjects recruited in Ontario, Hawaii, and the University of Southern California Consortium. All food frequency data were collected after folic acid fortification of the North American food supply in 1998 and analyzed, in separate analyses, assuming either prefortification or postfortification folate values as dietary folate equivalents. In the analysis of total dietary folate intake we assumed that both multivitamin and folic acid supplements contained 400 μg of folic acid per pill or tablet.

Statistical analysis

We used multivariable conditional logistic regression with sibship as the matching factor to estimate main effects assuming a log-additive model. As a secondary analysis we assessed all genotype effects in a codominant model and a 2-degree-of-freedom likelihood ratio test to estimate P values for each comparison. We controlled for age and sex in all analyses. Additional control for other variables did not change the results by >10%. For the log-additive model and within each gene, P values for all SNPs were adjusted for multiple testing taking into account correlated tagSNPs using a modified test of Conneely and Boehnke (Pact; ref. 28). We report both the observed likelihood ratio P value and Pact. For a test of a single gene, a α-level of 0.05 for Pact was used to determine statistical significance. To define significance across all the genes tested, a Bonferroni corrected P value of (α = 0.05/15 = 0.0033) may also be considered. For the 2-degree-of-freedom codominant model and all stratified analyses we used the Bonferroni significance level of 0.00013 (0.05/395 tagSNPs).

Table 2 shows the demographic characteristics of the study population. The study population was over 87% non-Hispanic white. The mean age of cases was 53.5 years (±10.9) and the mean age of controls was 54.0 years (±11.8). Fifty-one percent of cases and 44% of controls were male, and 81% of the cases were from sites in North America. Thirty percent of cases reported a family history of colorectal cancer. Multivitamin supplement use was reported for 52.8% of cases and 46.8% of controls, whereas 11% of cases and 9.5% of controls reported taking a folic acid supplement.

Table 2.

Selected characteristics of the study population

Cases (n = 1,806)Sibling controls (n = 2,879)
Person characteristic 
    Mean age ± SD, y 53.5 ± 10.9 54.0 ± 11.8 
    Sex, no. (%) 
        Male 927 (51.3) 1,278 (44.4) 
        Female 879 (48.7) 1,601 (55.6) 
    Race, no. (%) 
        Non-Hispanic white 1,580 (87.5) 2,512 (87.3) 
        Black 32 (1.8) 42 (1.5) 
        Asian 69 (3.8) 113 (3.9) 
        Other* 104 (5.8) 189 (6.6) 
        Unknown/Missing 21 (1.2) 23 (0.8) 
    Center, no. (%) 
        Ontario, Canada 308 (17.1) 515 (17.9) 
        USC Consortium, U.S. 384 (21.3) 519 (18.0) 
        Melbourne, Australia 344 (19.0) 611 (21.2) 
        Hawaii, U.S. 63 (3.5) 103 (3.6) 
        Mayo Foundation, U.S. 282 (15.6) 526 (18.3) 
        Seattle, U.S. 425 (23.5) 605 (21.0) 
Family history of colorectal cancer, no. (%) 
No 1st-degree relative 1,177 (65.2) — 
At least 1 1st-degree relative 546 (30.2)  
Unknown/Missing 83 (4.6)  
    Alcohol use (drinks/wk) 
        None 467 (25.9) 7829 (28.8) 
        1-7 (moderate) 857 (47.5) 1,353 (47.0) 
        ≥8 (heavy) 229 (12.7) 7362 (12.6) 
        Unknown/Missing 253 (14.0) 7335 (11.6) 
    Folate supplements 
        No 1,586 (87.8) 2,557 (88.8) 
        Yes 196 (10.9) 274 (9.5) 
        Unknown/Missing 24 (1.3) 48 (1.7) 
Multivitamins 
    No 820 (45.4) 1,497 (52.0) 
    Yes 971 (53.8) 1,346 (46.8) 
    Dietary folate (μg/d), mean ± SD 327.4 ± 118.7 334.1 ± 126.8 
    Total folate (DFE/d), mean ± SD§ 477 ± 265.6 525.4 ± 439.7 
    Dietary B12 (μg/d), mean ± SD 3.0 ± 1.2 2.9 ± 1.3 
        Total B12 (μg/d), mean ± SD 6.2 ± 6.4 7.4 ± 11.8 
        Dietary B6 (mg/d), mean ± SD 1.1 ± 0.4 1.1 ± 0.4 
        Total B6 (mg/d), mean ± SD 1.9 ± 2.0 2.3 ± 3.8 
Tumor characteristics 
    Site, no. (%) 
        Right colon 598 (33.1) — 
        Left colon 525 (29.1)  
        Rectum 593 (32.8)  
        Unknown/Missing 90 (5.0)  
    MSI, no. (%) 
        MSS 855 (47.3) — 
        MSI-L 151 (8.4)  
        MSI-H 179 (9.9)  
        Unknown/Missing 621 (34.4)  
Cases (n = 1,806)Sibling controls (n = 2,879)
Person characteristic 
    Mean age ± SD, y 53.5 ± 10.9 54.0 ± 11.8 
    Sex, no. (%) 
        Male 927 (51.3) 1,278 (44.4) 
        Female 879 (48.7) 1,601 (55.6) 
    Race, no. (%) 
        Non-Hispanic white 1,580 (87.5) 2,512 (87.3) 
        Black 32 (1.8) 42 (1.5) 
        Asian 69 (3.8) 113 (3.9) 
        Other* 104 (5.8) 189 (6.6) 
        Unknown/Missing 21 (1.2) 23 (0.8) 
    Center, no. (%) 
        Ontario, Canada 308 (17.1) 515 (17.9) 
        USC Consortium, U.S. 384 (21.3) 519 (18.0) 
        Melbourne, Australia 344 (19.0) 611 (21.2) 
        Hawaii, U.S. 63 (3.5) 103 (3.6) 
        Mayo Foundation, U.S. 282 (15.6) 526 (18.3) 
        Seattle, U.S. 425 (23.5) 605 (21.0) 
Family history of colorectal cancer, no. (%) 
No 1st-degree relative 1,177 (65.2) — 
At least 1 1st-degree relative 546 (30.2)  
Unknown/Missing 83 (4.6)  
    Alcohol use (drinks/wk) 
        None 467 (25.9) 7829 (28.8) 
        1-7 (moderate) 857 (47.5) 1,353 (47.0) 
        ≥8 (heavy) 229 (12.7) 7362 (12.6) 
        Unknown/Missing 253 (14.0) 7335 (11.6) 
    Folate supplements 
        No 1,586 (87.8) 2,557 (88.8) 
        Yes 196 (10.9) 274 (9.5) 
        Unknown/Missing 24 (1.3) 48 (1.7) 
Multivitamins 
    No 820 (45.4) 1,497 (52.0) 
    Yes 971 (53.8) 1,346 (46.8) 
    Dietary folate (μg/d), mean ± SD 327.4 ± 118.7 334.1 ± 126.8 
    Total folate (DFE/d), mean ± SD§ 477 ± 265.6 525.4 ± 439.7 
    Dietary B12 (μg/d), mean ± SD 3.0 ± 1.2 2.9 ± 1.3 
        Total B12 (μg/d), mean ± SD 6.2 ± 6.4 7.4 ± 11.8 
        Dietary B6 (mg/d), mean ± SD 1.1 ± 0.4 1.1 ± 0.4 
        Total B6 (mg/d), mean ± SD 1.9 ± 2.0 2.3 ± 3.8 
Tumor characteristics 
    Site, no. (%) 
        Right colon 598 (33.1) — 
        Left colon 525 (29.1)  
        Rectum 593 (32.8)  
        Unknown/Missing 90 (5.0)  
    MSI, no. (%) 
        MSS 855 (47.3) — 
        MSI-L 151 (8.4)  
        MSI-H 179 (9.9)  
        Unknown/Missing 621 (34.4)  

*Includes individuals who self-identified themselves as Hispanic, Native, Hawaiian/Pacific Islander, and Mixed Race.

Ever use of supplements at least 2×/week for more than a month.

Calorie adjusted, calculated from food frequency questionnaire as dietary folate equivalents using postfortification food composition tables (cases, n = 585; controls, n = 837).

§Calorie adjusted, sum of dietary and supplement use [as dietary folate equivalents (DFE)] from food frequency questionnaire (n cases = 585; n controls = 837).

Calorie adjusted, calculated from food frequency questionnaire.

Calorie adjusted, sum of dietary and supplement use from food frequency questionnaire.

The results of the single SNP analysis, log additive model, are shown in Fig. 1 and Supplementary Table S1. Only two tagSNPs were associated significantly with colorectal cancer risk after correction for multiple testing. Table 3 shows the associations for the 10 tagSNPs with nominally significant associations with risk of colorectal cancer. The two significant tagSNPs, DHFR rs1677693 and rs1643659, were strongly linked (r2 = 0.99) and associated with a decrease in colorectal cancer risk [per minor allele odds ratio (OR), 0.87; 95% confidence interval (95% CI), 0.71-0.94; Pact = 0.029; and OR, 0.87; 95% CI, 0.71-0.95; Pact = 0.034 for rs1677693 and rs1643659, respectively].

Figure 1.

Single SNP analysis of the total study population. Odds ratios were estimated assuming a log additive model for all SNPs. Each gene is a different color. +, per minor allele OR >1.0; −, OR <1.0. P values were corrected for multiple comparisons by the method of Connelly and Boehnke (18). We show a Bonferroni adjustment to account for the inclusion of 15 genes in the analysis.

Figure 1.

Single SNP analysis of the total study population. Odds ratios were estimated assuming a log additive model for all SNPs. Each gene is a different color. +, per minor allele OR >1.0; −, OR <1.0. P values were corrected for multiple comparisons by the method of Connelly and Boehnke (18). We show a Bonferroni adjustment to account for the inclusion of 15 genes in the analysis.

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Table 3.

Colorectal cancer tagSNP associations with nominally significant P values

SNPGeneCasesControlsSibshipsOR*L95U95LRT PPact§
rs1677693 DHFR 1,805 2,878 1,750 0.818 0.710 0.942 0.0041 0.0293 
rs1643659 DHFR 1,805 2,876 1,749 0.821 0.713 0.945 0.0048 0.0336 
rs3788050 CBS 1,796 2,864 1,742 0.814 0.686 0.965 0.0205 0.3137 
rs4659744 MTR 1,805 2,878 1,749 0.867 0.769 0.977 0.0225 0.1409 
rs12563688 MTR 1,804 2,877 1,748 0.871 0.773 0.982 0.0287 0.1718 
rs1650723 DHFR 1,803 2,875 1,747 0.836 0.705 0.991 0.0361 0.2040 
rs12060264 MTR 1,799 2,862 1,743 0.877 0.778 0.989 0.0381 0.2148 
rs10737812 MTR 1,806 2,879 1,750 1.137 1.008 1.282 0.0393 0.2112 
rs2281649 CUBN 1,806 2,879 1,750 1.176 1.006 1.375 0.0440 0.9591 
rs719037 CBS 1,804 2,877 1,749 0.882 0.779 0.997 0.0444 0.5264 
SNPGeneCasesControlsSibshipsOR*L95U95LRT PPact§
rs1677693 DHFR 1,805 2,878 1,750 0.818 0.710 0.942 0.0041 0.0293 
rs1643659 DHFR 1,805 2,876 1,749 0.821 0.713 0.945 0.0048 0.0336 
rs3788050 CBS 1,796 2,864 1,742 0.814 0.686 0.965 0.0205 0.3137 
rs4659744 MTR 1,805 2,878 1,749 0.867 0.769 0.977 0.0225 0.1409 
rs12563688 MTR 1,804 2,877 1,748 0.871 0.773 0.982 0.0287 0.1718 
rs1650723 DHFR 1,803 2,875 1,747 0.836 0.705 0.991 0.0361 0.2040 
rs12060264 MTR 1,799 2,862 1,743 0.877 0.778 0.989 0.0381 0.2148 
rs10737812 MTR 1,806 2,879 1,750 1.137 1.008 1.282 0.0393 0.2112 
rs2281649 CUBN 1,806 2,879 1,750 1.176 1.006 1.375 0.0440 0.9591 
rs719037 CBS 1,804 2,877 1,749 0.882 0.779 0.997 0.0444 0.5264 

*ORs and 95% confidence limits computed using conditional logistic regression with sibship as the matching factor and controlling for age and sex.

Lower 95% confidence limit.

Upper 95% confidence limit.

§Adjusted for multiple testing taking into account correlated tagSNPs using a modified test of Conneely and Boehnke (Pact; ref. 28).

We assessed possible heterogeneity of effects by MSI status, tumor subsite (proximal, distal, rectal), folate and multivitamin supplement use (yes or no), dietary folate intake (continuous), time to interview (≤2 years or >2 years), ascertainment site (Australia or North America), and family history of colorectal cancer (yes or no). There was no significant heterogeneity except with multivitamin use (Table 4). The two DHFR tagSNPs (rs1677693 and rs1643659) and one tagSNP in MTR (rs4659744) were significantly associated with risk only in individuals not using multivitamin supplements. In individuals who did not use multivitamin supplements the per allele OR for both rs1677693 and rs1643659 was 0.69 (95% CI, 0.58-0.82; P = 0.00002 and 0.00003, respectively). For individuals using multivitamin supplements these ORs were 0.91 (95% CI, 0.78-1.07) for both tagSNPs. The P values for heterogeneity between the two strata were 0.000899 and 0.000986, respectively. For MTR rs4659744 the OR in non–multivitamin supplement users was 0.76 (95% CI, 0.67-0.88; P = 0.00011) and 0.97 (95% CI, 0.85-1.11) in supplement users (P for heterogeneity = 0.000265). There was also significant heterogeneity between non-multivitamin and multivitamin supplement users for four tagSNPs in MAT2A (rs1446669,rs699664, rs10179195, rs6739015) and one tagSNP in MTRR (rs716537). In each case the per allele OR was nonsignificantly decreased in nonusers and slightly increased in users of multivitamin supplements (Table 4).

Table 4.

Interactions between folate-associated genotypes by multivitamin supplement use

GeneSNPNo multivitamin supplement use*Multivitamin supplement useP interaction
SibshipsOR (95% CI)PSibshipsOR (95% CI)P
DHFR rs1677693 565 0.69 (0.58-0.82) 0.000021 637 0.91 (0.78-1.07) 0.299 0.000899 
DHFR rs1643659 564 0.69 (0.58-0.82) 0.000026 637 0.91 (0.78-1.07) 0.223 0.000986 
MTR rs4659744 565 0.76 (0.67-0.88) 0.000108 637 0.97 (0.85-1.11) 0.624 0.000265 
MTRR rs16537 565 0.79 (0.68-0.91) 0.0017 637 1.04 (0.91-1.20) 0.547 0.000057 
MAT2A rs1446669 564 0.81 (0.69-0.95) 0.0084 634 1.13 (0.98-1.32) 0.103 0.000033 
MAT2A rs6739015 562 0.83 (0.72-0.96) 0.0137 633 1.09 (0.95-1.25) 0.238 0.000030 
MAT2A rs10179195 565 0.84 (0.73-0.97) 0.0142 637 1.07 (0.94-1.22) 0.338 0.000063 
MAT2A rs699664 564 0.80 (0.68-0.93) 0.0041 635 1.06 (0.92-1.23) 0.428 0.000107 
GeneSNPNo multivitamin supplement use*Multivitamin supplement useP interaction
SibshipsOR (95% CI)PSibshipsOR (95% CI)P
DHFR rs1677693 565 0.69 (0.58-0.82) 0.000021 637 0.91 (0.78-1.07) 0.299 0.000899 
DHFR rs1643659 564 0.69 (0.58-0.82) 0.000026 637 0.91 (0.78-1.07) 0.223 0.000986 
MTR rs4659744 565 0.76 (0.67-0.88) 0.000108 637 0.97 (0.85-1.11) 0.624 0.000265 
MTRR rs16537 565 0.79 (0.68-0.91) 0.0017 637 1.04 (0.91-1.20) 0.547 0.000057 
MAT2A rs1446669 564 0.81 (0.69-0.95) 0.0084 634 1.13 (0.98-1.32) 0.103 0.000033 
MAT2A rs6739015 562 0.83 (0.72-0.96) 0.0137 633 1.09 (0.95-1.25) 0.238 0.000030 
MAT2A rs10179195 565 0.84 (0.73-0.97) 0.0142 637 1.07 (0.94-1.22) 0.338 0.000063 
MAT2A rs699664 564 0.80 (0.68-0.93) 0.0041 635 1.06 (0.92-1.23) 0.428 0.000107 

*Multivitamin supplement users were defined as those reporting ever use of supplements regularly (at least 2×/week for more than a month).

OR's and 95% confidence limits computed using conditional logistic regression with sibship as the matching factor and controlling for age and sex.

The Bonferroni-adjusted P value based on an analysis of 395 tagSNPs is 0.00013.

In this large family-based case-control study of colorectal cancer risk we found that common variants in DHFR and MTR may be associated with a decrease in colorectal cancer risk in nonusers of multivitamin supplements, whereas there was no association in multivitamin users. No other significant associations were observed for common variants in these 15 FOCM-associated genes involved in nucleotide synthesis, methylation, vitamin B12 transport, or polyamine synthesis. There was significant heterogeneity by multivitamin use for four tagSNPs in MAT2A and one tagSNP in MTRR, although neither association was statistically significant.

Dihydrofolate reductase (DHFR) reduces dihydrofolate to tetrahydrofolate. Failure of this reaction can trap folate moieties in an oxidized form that cannot be used for further one-carbon transfers. Inhibition of the DHFR reaction has been exploited for chemotherapy by the drug methotrexate (MTX), and increased DHFR activity is a common cause for resistance to MTX (29). Reduction by DHFR is also involved in the utilization of folic acid, the fully oxidized folate form used for folate supplementation (30).

Variation in DHFR seems to affect folate metabolism. Homozygosity for a 19 bp deletion polymorphism in the 1st intron of the DHFR gene has been associated with increased DHFR mRNA (31, 32), a 14% decrease in plasma homocysteine (33), increased RBC and plasma folate in women (34), increased circulating folic acid in those with high folic acid intake (>500 μg/day), and decreased RBC folate in those consuming <250 μg/day (35). A study that assessed the association between this polymorphism and colorectal cancer risk reported no association for either CpG island methylator positive (CIMP) or negative tumors (36). Other promoter region (37) or 3′ untranslated region SNPs (38) have been identified in DHFR but no SNPs in the coding region of the gene have been reported (33).

The vitamin B12–dependent enzyme methionine synthase (MTR) catalyzes the transfer of a methyl group from 5-methyltetrahydrofolate (5-MTHF) to homocysteine to make methionine and tetrahydrofolate. Interference with this process traps folates as 5-MTHF, which cannot be recycled for further one-carbon transfer reactions (39). The de novo synthesis of methionine is the first step in the synthesis of the universal methyl donor SAM, suggesting a possible mechanism by which genetic variation in the MTR gene may influence colorectal cancer risk. In this population one intronic tagSNP in MTR (rs4659744) was associated with decreased colorectal cancer risk in non–multivitamin supplement users. The association between one nonsynonymous SNP in the MTR gene (A2756G, D919G, rs1805087) and colorectal cancer risk has been studied by several groups (40-46). The reported associations were inconsistent although a recent meta-analysisreported a small but significant decrease in colorectal cancer risk for the GG genotype in European populations (47). The D919G genotype (not linked to rs4659744) was not associated with risk in this population.

TagSNPs in two other genes, MTRR and MAT2A, were also modified significantly by multivitamin use, although the individual associations were not statistically significant in either multivitamin use group. MTRR reduces oxidized MTR and B12 after transfer of the methyl group from the B12 cofactor to homocysteine, whereas the MAT2A enzyme transfers the methyl group from methionine to SAM in an ATP-dependent reaction. The MTRR SNPs rs2303080 and rs2287780 were significantly associated with colorectal cancer risk in a recent study of 24 nonsynonymous SNPs in 13 folate pathway genes (42) but were not associated with risk overall or in any subgroup in our study.

Martinez et al. reported that the association between the MTHFR C677T TT genotype and adenoma recurrence was limited to non–multivitamin supplement users with risk increased in that largely postfortification population (48). In the current study population, on the other hand, the MTHFR-677 TT genotype was associated with a significantly decreased colorectal cancer risk in individuals not using a multivitamin supplement but an OR of approximately 1.0 in those using a multivitamin supplement, results that are similar to those reported here for the other folate pathway gene variants (21).

Numerous other studies of the MTHFR C677T and A1298C polymorphisms and other FOCM-associated genes have assessed interactions between genotypes and indices of folate, alcohol, or other B vitamins, although most of these studies were undertaken in populations not exposed to fortification of foods with folic acid (36, 41-46, 49-64). All but five of these studies (36, 46, 52, 57, 63) support the existence of such interactions. For the MTHFR C677T genotype the majority of studies reported that the TT genotype is more protective in those with a diet high in folate or other methyl-group nutrients or low in alcohol (42-44, 49, 50, 53-55, 60, 64, 65), although other studies have reported no such trends or trends in the opposite direction (45, 51, 59). Although none of these studies looked specifically at multivitamin supplement use, such supplement use is the major source of folates for those in the highest category (66).

Clearly, we do not know for certain which nutrients or what combination of nutrients in multivitamins may modify the association between these FOCM-associated genetic variants and colorectal cancer risk. However, folic acid, B6, and B12 are likely to play the dominant roles. Additionally, in this study we used a tagSNP approach to assess genetic effects so it is not possible to predict how the variations tagged by these SNPs might interact with methyl-group nutrient status. It is notable, however, that >80% of our study population was recruited after fortification of the North American food supply with folic acid, the synthetic folate used in fortified foods and supplements.

In our population, those not taking multivitamin supplements may have had folate levels more similar to those taking multivitamin supplements than to the non–multivitamin supplement users in prefortification populations. The significant increase in plasma and RBC folate in both supplement users and nonusers after fortification is well documented (67-69). Thus, for genotype effects that are more relevant at higher folate levels we would expect to see associations in non–multivitamin supplement users in this population.

For the multivitamin supplement users the interaction between genotype and colorectal cancer risk may be more complex. First, genotype effects may become less important when mucosal folate levels are maximized, consistent with the ORs close to 1.0 that we observed in multivitamin supplement users. Second, unmetabolized folic acid levels become measurable in the circulation at folic acid levels >400 μg/day, due to saturation of the DHFR enzyme (30, 70, 71). Such high folic acid intakes may be more prevalent in multivitamin users eating folic acid–fortified foods (72). The effect of this on cancer risk is unknown. One in vivo study (73) reported that increased unmetabolized folic acid was associated with a decrease in natural killer cell activity, suggesting a possible decrease in tumor surveillance. Additionally, sustained exposure to high levels of folic acid was associated with a significant decrease in folate uptake in human colon cancer cells in vitro (74). Whether circulating folic acid levels among multivitamin users in fortified populations are high enough to have this effect in vivo is not known, but the possibility should be studied further as it suggests a paradoxical decrease in tissue folate stores among those with the highest folic acid intakes. Decreased folate uptake in those with higher folic acid intakes may nullify any protective effect of genotype. Alternatively, the lack of any effect of genotype on colorectal cancer risk in multivitamin users may be due to a higher progression risk in multivitamin users with preclinical lesions at the time fortification was instituted in 1998. Such an effect would be consistent with the increased neoplasia risk observed in recent studies of post-folic-acid-fortified populations (14-18), the dual effect of folic acid supplementation observed in animal studies (12, 13), and the coincident rise in colorectal cancer incidence in the United States and Canada around the time of fortification (19). In this regard it may be of interest that the prevalence of multivitamin use was significantly higher in cases than in controls in this study population (Table 2; P < 0.01), suggesting increased colorectal cancer risk in supplement users. It is possible that this increase in colorectal cancer risk among supplement users ameliorated any protective effects attributable to genotype. Whether multivitamin use is a colorectal cancer risk factor in postfortification populations requires further study.

The strengths of our study include the large number of subjects, the comprehensive approach to tagSNP selection, and the use of a family-based design which limits the possibility of population stratification. This study has several limitations. In the main analysis we had limited statistical power for SNPs with a MAF of ≤5% (60% power to detect an OR of 1.4). For SNPs with an MAF of 10% we had 80% power to detect an OR of 1.35. We did not have data on all potentially relevant FOCM pathway genes and may have missed some relevant tagSNPs. However, gene coverage ranged from 71% of all identified SNPs for CBS to 98% for SHMT1. The mean coverage was 89%. Although we did take multiple testing into account some possibility of a false-positive result remains given the large number of parameters estimated. Similarly the stringent Bonferroni correction may have resulted in some false negatives in stratified analyses. Our study sample was selected to enrich the subject pool for those at higher colorectal cancer risk and recruited largely from populations with mandatory supplementation of foods with folic acid, potentially limiting the generalizability of our results.

In conclusion, in these data from a large population-based study we found significant associations between tagSNPs in DHFR and colorectal cancer risk in a study of 395 tagSNPs in 15 folate-pathway genes. Our data suggest that two linked tagSNPs in DHFR and one in MTR may mark genotypes that decrease colorectal cancer risk in non–multivitamin supplement users in this folate-fortified population. Future studies of similarly fortified populations are required to replicate these results.

D. Conti is a consultant for Pfizer Inc. and P. Limburg is a consultant for Genomic Health Inc.

We thank Margreet Luchtenborg, Maj Earle, Barbara Saltzman, Darin Taverna, Chris Edlund, Matt Westlake, Paul Mosquin, Darshana Daftary, Douglas Snazel, Allyson Templeton, Terry Teitsch, Helen Chen, Maggie Angelakos, and Paul Mosquin for their support in data collection and management, and all the individuals who participated in the Colon CFR.

Grant Support: National Cancer Institute, National Institutes of Health under RFA # CA-95-011 and through cooperative agreements with the Australasian Colorectal Cancer Family Registry (U01 CA097735), the USC Familial Colorectal Neoplasia Collaborative Group (U01 CA074799), the Mayo Clinic Cooperative Family Registry for Colon Cancer Studies (U01 CA074800), the Ontario Registry for Studies of Familial Colorectal Cancer (U01 CA074783), the Seattle Colorectal Cancer Family Registry (U01 CA074794), and the University of Hawaii Colorectal Cancer Family Registry (U01 CA074806) as well as NCI R01 CA112237 (R.W. Haile), NCI T32 CA009142 (J.N. Poynter) and NCI PO1 CA41108 CA-23074 and CA 956060 (M.E. Martinez). P.T. Campbell and J.C. Figueiredo were supported in part by National Cancer Institute of Canada post-PhD Fellowships (#18735 and #17602).

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.

1
Giovannucci
E
. 
Epidemiologic studies of folate and colorectal neoplasia: a review
.
J Nutr
2002
;
132
:
2350
5S
.
2
Kim
YI
. 
Role of folate in colon cancer development and progression
.
J Nutr
2003
;
133
:
3731
9S
.
3
Ulrich
CM
. 
Nutrigenetics in cancer research-folate metabolism and colorectal cancer
.
J Nutr
2005
;
135
:
2698
702
.
4
Jones
PA
,
Baylin
SB
. 
The epigenomics of cancer
.
Cell
2007
;
128
:
683
92
.
5
Ehrlich
M
. 
DNA methylation in cancer: too much, but also too little
.
Oncogene
2002
;
21
:
5400
13
.
6
Pogribny
IP
,
Beland
FA
. 
DNA hypomethylation in the origin and pathogenesis of human diseases
.
Cell Mol Life Sci
2009
;
66
:
2249
61
.
7
Blount
BC
,
Mack
MM
,
Wehr
CM
, et al
. 
Folate deficiency causes uracil misincorporation into human DNA and chromosome breakage: implications for cancer and neuronal damage
.
Proc Natl Acad Sci U S A
1997
;
94
:
3290
5
.
8
Duthie
SJ
,
Narayanan
S
,
Sharp
L
,
Little
J
,
Basten
G
,
Powers
H
. 
Folate, DNA stability and colo-rectal neoplasia
.
Proc Nutr Soc
2004
;
63
:
571
8
.
9
Beetstra
S
,
Thomas
P
,
Salisbury
C
,
Turner
J
,
Fenech
M
. 
Folic acid deficiency increases chromosomal instability, chromosome 21 aneuploidy and sensitivity to radiation-induced micronuclei
.
Mutat Res
2005
;
578
:
317
26
.
10
Kim
YI
. 
Will mandatory folic acid fortification prevent or promote cancer?
Am J Clin Nutr
2004
;
80
:
1123
8
.
11
Ulrich
CM
,
Potter
JD
. 
Folate supplementation: too much of a good thing?
Cancer Epidemiol Biomarkers Prev
2006
;
15
:
189
93
.
12
Song
J
,
Medline
A
,
Mason
JB
,
Gallinger
S
,
Kim
YI
. 
Effects of dietary folate on intestinal tumorigenesis in the apcMin mouse
.
Cancer Res
2000
;
60
:
5434
40
.
13
Song
J
,
Sohn
KJ
,
Medline
A
,
Ash
C
,
Gallinger
S
,
Kim
YI
. 
Chemopreventive effects of dietary folate on intestinal polyps in Apc+/−Msh2−/− mice
.
Cancer Res
2000
;
60
:
3191
9
.
14
Charles
D
,
Ness
AR
,
Campbell
D
,
Davey Smith
G
,
Hall
MH
. 
Taking folate in pregnancy and risk of maternal breast cancer
.
BMJ
2004
;
329
:
1375
6
.
15
Cole
BF
,
Baron
JA
,
Sandler
RS
, et al
. 
Folic acid for the prevention of colorectal adenomas: a randomized clinical trial
.
JAMA
2007
;
297
:
2351
9
.
16
Figueiredo
JC
,
Grau
MV
,
Haile
RW
, et al
. 
Folic acid and risk of prostate cancer: results from a randomized clinical trial
.
J Natl Cancer Inst
2009
;
101
:
432
5
.
17
Hirsch
S
,
Sanchez
H
,
Albala
C
, et al
. 
Colon cancer in Chile before and after the start of the flour fortification program with folic acid
.
Eur J Gastroenterol Hepatol
2009
;
21
:
436
9
.
18
Stolzenberg-Solomon
RZ
,
Chang
SC
,
Leitzmann
MF
, et al
. 
Folate intake, alcohol use, and postmenopausal breast cancer risk in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial
.
Am J Clin Nutr
2006
;
83
:
895
904
.
19
Mason
JB
,
Dickstein
A
,
Jacques
PF
, et al
. 
A temporal association between folic acid fortification and an increase in colorectal cancer rates may be illuminating important biological principles: a hypothesis
.
Cancer Epidemiol Biomarkers Prev
2007
;
16
:
1325
9
.
20
Xu
X
,
Liu
AY
,
Ulrich
CM
,
Chen
J
.
Folate and cancer: epidemiological perspecitve
.
New York
:
Taylor and Francis
; 
2009
.
21
Levine
AJ
,
Figueiredo
JC
,
Lee
W
, et al
. 
Genetic variability in the MTHFR gene and colorectal cancer risk using the colorectal cancer family registry
.
Cancer Epidemiol Biomarkers Prev
2010
;
19
:
89
100
.
22
Figueiredo
JC
,
Levine
AJ
,
Lee
WH
, et al
. 
Genes involved with folate uptake and distribution and their association with colorectal cancer risk
.
Cancer Causes Control
2010
;
21
:
597
608
.
24
Newcomb
PA
,
Baron
J
,
Cotterchio
M
, et al
. 
Colon Cancer Family Registry: an international resource for studies of the genetic epidemiology of colon cancer
.
Cancer Epidemiol Biomarkers Prev
2007
;
16
:
2331
43
.
25
Barrett
JC
,
Fry
B
,
Maller
J
,
Daly
MJ
. 
Haploview: analysis and visualization of LD and haplotype maps
.
Bioinformatics
2005
;
21
:
263
5
.
26
Shen
R
,
Fan
JB
,
Campbell
D
, et al
. 
High-throughput SNP genotyping on universal bead arrays
.
Mutat Res
2005
;
573
:
70
82
.
27
Stram
DO
,
Hankin
JH
,
Wilkens
LR
, et al
. 
Calibration of the dietary questionnaire for a multiethnic cohort in Hawaii and Los Angeles
.
Am J Epidemiol
2000
;
151
:
358
70
.
28
Conneely
KN
,
Boehnke
M
. 
So many correlated tests, so little time! Rapid adjustement of P values for multiple correlated tests
.
Am J Hum Genet
2007
;
81
:
1158
68
.
29
Banerjee
D
,
Mayer-Kuckuk
P
,
Capiaux
G
,
Budak-Alpdogan
T
,
Gorlick
R
,
Bertino
JR
. 
Novel aspects of resistance to drugs targeted to dihydrofolate reductase and thymidylate synthase
.
Biochim Biophys Acta
2002
;
1587
:
164
73
.
30
Bailey
SW
,
Ayling
JE
. 
The extremely slow and variable activity of dihydrofolate reductase in human liver and its implications for high folic acid intake
.
Proc Natl Acad Sci U S A
2009
;
106
:
15424
9
.
31
Parle-McDermott
A
,
Pangilinan
F
,
Mills
JL
, et al
. 
The 19-bp deletion polymorphism in intron-1 of dihydrofolate reductase (DHFR) may decrease rather than increase risk for spina bifida in the Irish population
.
Am J Med Genet A
2007
;
143A
:
1174
80
.
32
Xu
X
,
Gammon
MD
,
Wetmur
JG
, et al
. 
A functional 19-base pair deletion polymorphism of dihydrofolate reductase (DHFR) and risk of breast cancer in multivitamin users
.
Am J Clin Nutr
2007
;
85
:
1098
102
.
33
Gellekink
H
,
Blom
HJ
,
van der Linden
IJ
,
den Heijer
M
. 
Molecular genetic analysis of the human dihydrofolate reductase gene: relation with plasma total homocysteine, serum and red blood cell folate levels
.
Eur J Hum Genet
2007
;
15
:
103
9
.
34
Stanislawska-Sachadyn
A
,
Brown
KS
,
Mitchell
LE
, et al
. 
An insertion/deletion polymorphism of the dihydrofolate reductase (DHFR) gene is associated with serum and red blood cell folate concentrations in women
.
Hum Genet
2008
;
123
:
289
95
.
35
Kalmbach
RD
,
Choumenkovitch
SF
,
Troen
AP
,
Jacques
PF
,
D'Agostino
R
,
Selhub
J
. 
A 19-base pair deletion polymorphism in dihydrofolate reductase is associated with increased unmetabolized folic acid in plasma and decreased red blood cell folate
.
J Nutr
2008
;
138
:
2323
7
.
36
Curtin
K
,
Slattery
ML
,
Ulrich
CM
, et al
. 
Genetic polymorphisms in one-carbon metabolism: associations with CpG island methylator phenotype (CIMP) in colon cancer and the modifying effects of diet
.
Carcinogenesis
2007
;
28
:
1672
9
.
37
Dulucq
S
,
St-Onge
G
,
Gagne
V
, et al
. 
DNA variants in the dihydrofolate reductase gene and outcome in childhood ALL
.
Blood
2008
;
111
:
3692
700
.
38
Goto
Y
,
Yue
L
,
Yokoi
A
, et al
. 
A novel single-nucleotide polymorphism in the 3′-untranslated region of the human dihydrofolate reductase gene with enhanced expression
.
Clin Cancer Res
2001
;
7
:
1952
6
.
39
Lucock
M
. 
Folic acid: nutritional biochemistry, molecular biology, and role in disease processes
.
Mol Genet Metab
2000
;
71
:
121
38
.
40
de Vogel
S
,
Wouters
KA
,
Gottschalk
RW
, et al
. 
Genetic variants of methyl metabolizing enzymes and epigenetic regulators: associations with promoter CpG island hypermethylation in colorectal cancer
.
Cancer Epidemiol Biomarkers Prev
2009
;
18
:
3086
96
.
41
Guerreiro
CS
,
Carmona
B
,
Goncalves
S
, et al
. 
Risk of colorectal cancer associated with the C677T polymorphism in 5,10-methylenetetrahydrofolate reductase in Portuguese patients depends on the intake of methyl-donor nutrients
.
Am J Clin Nutr
2008
;
88
:
1413
8
.
42
Koushik
A
,
Kraft
P
,
Fuchs
CS
, et al
. 
Nonsynonymous polymorphisms in genes in the one-carbon metabolism pathway and associations with colorectal cancer
.
Cancer Epidemiol Biomarkers Prev
2006
;
15
:
2408
17
.
43
Le Marchand
L
,
Wilkens
LR
,
Kolonel
LN
,
Henderson
BE
. 
The MTHFR C677T polymorphism and colorectal cancer: the multiethnic cohort study
.
Cancer Epidemiol Biomarkers Prev
2005
;
14
:
1198
203
.
44
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
.
45
Matsuo
K
,
Ito
H
,
Wakai
K
, et al
. 
One-carbon metabolism related gene polymorphisms interact with alcohol drinking to influence the risk of colorectal cancer in Japan
.
Carcinogenesis
2005
;
26
:
2164
71
.
46
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
.
47
Yu
K
,
Zhang
J
,
Dou
C
, et al
. 
Methionine synthase A2756G polymorphism and cancer risk: a meta-analysis
.
Eur J Hum Genet
2010
;
18
:
370
8
.
48
Martinez
ME
,
Thompson
P
,
Jacobs
ET
, et al
. 
Dietary factors and biomarkers involved in the methylenetetrahydrofolate reductase genotype-colorectal adenoma pathway
.
Gastroenterology
2006
;
131
:
1706
16
.
49
Chang
SC
,
Lin
PC
,
Lin
JK
,
Yang
SH
,
Wang
HS
,
Li
AF
. 
Role of MTHFR polymorphisms and folate levels in different phenotypes of sporadic colorectal cancers
.
Int J Colorectal Dis
2007
;
22
:
483
9
.
50
Chen
J
,
Giovannucci
E
,
Kelsey
K
, et al
. 
A methylenetetrahydrofolate reductase polymorphism and the risk of colorectal cancer
.
Cancer Res
1996
;
56
:
4862
4
.
51
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
.
52
Jiang
Q
,
Chen
K
,
Ma
X
, et al
. 
Diets, polymorphisms of methylenetetrahydrofolate reductase, and the susceptibility of colon cancer and rectal cancer
.
Cancer Detect Prev
2005
;
29
:
146
54
.
53
Keku
T
,
Millikan
R
,
Worley
K
, et al
. 
5,10-Methylenetetrahydrofolate reductase codon 677 and 1298 polymorphisms and colon cancer in African Americans and whites
.
Cancer Epidemiol Biomarkers Prev
2002
;
11
:
1611
21
.
54
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
.
55
Ma
J
,
Stampfer
MJ
,
Giovannucci
E
, et al
. 
Methylenetetrahydrofolate reductase polymorphism, dietary interactions, and risk of colorectal cancer
.
Cancer Res
1997
;
57
:
1098
102
.
56
Matsuo
K
,
Hamajima
N
,
Hirai
T
, et al
. 
Methionine synthase reductase gene A66G polymorphism is associated with risk of colorectal cancer
.
Asian Pac J Cancer Prev
2002
;
3
:
353
9
.
57
Murtaugh
MA
,
Curtin
K
,
Sweeney
C
, et al
. 
Dietary intake of folate and co-factors in folate metabolism, MTHFR polymorphisms, and reduced rectal cancer
.
Cancer Causes Control
2007
;
18
:
153
63
.
58
Otani
T
,
Iwasaki
M
,
Hanaoka
T
, et al
. 
Folate, vitamin B6, vitamin B12, and vitamin B2 intake, genetic polymorphisms of related enzymes, and risk of colorectal cancer in a hospital-based case-control study in Japan
.
Nutr Cancer
2005
;
53
:
42
50
.
59
Sharp
L
,
Little
J
,
Brockton
NT
, et al
. 
Polymorphisms in the methylenetetrahydrofolate reductase (MTHFR) gene, intakes of folate and related B vitamins and colorectal cancer: a case-control study in a population with relatively low folate intake
.
Br J Nutr
2008
;
99
:
379
89
.
60
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
.
61
Steck
SE
,
Keku
T
,
Butler
LM
, et al
. 
Polymorphisms in methionine synthase, methionine synthase reductase and serine hydroxymethyltransferase, folate and alcohol intake, and colon cancer risk
.
J Nutrigenet Nutrigenomics
2008
;
1
:
196
204
.
62
Ulrich
CM
,
Curtin
K
,
Potter
JD
,
Bigler
J
,
Caan
B
,
Slattery
ML
. 
Polymorphisms in the reduced folate carrier, thymidylate synthase, or methionine synthase and risk of colon cancer
.
Cancer Epidemiol Biomarkers Prev
2005
;
14
:
2509
16
.
63
Van Guelpen
B
,
Hultdin
J
,
Johansson
I
, et al
. 
Low folate levels may protect against colorectal cancer
.
Gut
2006
;
55
:
1461
6
.
64
Yin
G
,
Kono
S
,
Toyomura
K
, et al
. 
Methylenetetrahydrofolate reductase C677T and A1298C polymorphisms and colorectal cancer: the Fukuoka Colorectal Cancer Study
.
Cancer Sci
2004
;
95
:
908
13
.
65
Wang
J
,
Gajalakshmi
V
,
Jiang
J
, et al
. 
Associations between 5,10-methylenetetrahydrofolate reductase codon 677 and 1298 genetic polymorphisms and environmental factors with reference to susceptibility to colorectal cancer: a case-control study in an Indian population
.
Int J Cancer
2006
;
118
:
991
7
.
66
Yeung
L
,
Yang
Q
,
Berry
RJ
. 
Contributions of total daily intake of folic acid to serum folate concentrations
.
JAMA
2008
;
300
:
2486
7
.
67
Dietrich
M
,
Brown
CJ
,
Block
G
. 
The effect of folate fortification of cereal-grain products on blood folate status, dietary folate intake, and dietary folate sources among adult non-supplement users in the United States
.
J Am Coll Nutr
2005
;
24
:
266
74
.
68
Ganji
V
,
Kafai
MR
. 
Trends in serum folate, RBC folate, and circulating total homocysteine concentrations in the United States: analysis of data from National Health and Nutrition Examination Surveys, 1988–1994, 1999–2000, and 2001–2002
.
J Nutr
2006
;
136
:
153
8
.
69
Jacques
PF
,
Selhub
J
,
Bostom
AG
,
Wilson
PW
,
Rosenberg
IH
. 
The effect of folic acid fortification on plasma folate and total homocysteine concentrations
.
N Engl J Med
1999
;
340
:
1449
54
.
70
Kelly
P
,
McPartlin
J
,
Goggins
M
,
Weir
DG
,
Scott
JM
. 
Unmetabolized folic acid in serum: acute studies in subjects consuming fortified food and supplements
.
Am J Clin Nutr
1997
;
65
:
1790
5
.
71
Sweeney
MR
,
Staines
A
,
Daly
L
, et al
. 
Persistent circulating unmetabolised folic acid in a setting of liberal voluntary folic acid fortification. Implications for further mandatory fortification?
BMC Public Health
2009
;
9
:
295
.
72
Kalmbach
RD
,
Choumenkovitch
SF
,
Troen
AM
,
D'Agostino
R
,
Jacques
PF
,
Selhub
J
. 
Circulating folic acid in plasma: relation to folic acid fortification
.
Am J Clin Nutr
2008
;
88
:
763
8
.
73
Troen
AM
,
Mitchell
B
,
Sorensen
B
, et al
. 
Unmetabolized folic acid in plasma is associated with reduced natural killer cell cytotoxicity among postmenopausal women
.
J Nutr
2006
;
136
:
189
94
.
74
Ashokkumar
B
,
Mohammed
ZM
,
Vaziri
ND
,
Said
HM
. 
Effect of folate oversupplementation on folate uptake by human intestinal and renal epithelial cells
.
Am J Clin Nutr
2007
;
86
:
159
66
.

Supplementary data