Abstract
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
Introduction
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).
Genes involved in folate and vitamin B12 metabolism
Gene . | Function . |
---|---|
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 (SAHH) | Catalyzes 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 (TCN2) | The primary transport protein for cobalamin (vitamin B12) in plasma. |
TYMS (TS) | Catalyzes transfer of a methyl group from 5,10-MTHF to dUMP to form dTMP to maintain balanced nucleotide pools. |
Gene . | Function . |
---|---|
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 (SAHH) | Catalyzes 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 (TCN2) | The primary transport protein for cobalamin (vitamin B12) in plasma. |
TYMS (TS) | Catalyzes 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.
Materials and Methods
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).
Results
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.
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].
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.
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.
Colorectal cancer tagSNP associations with nominally significant P values
SNP . | Gene . | Cases . | Controls . | Sibships . | OR* . | L95† . | U95‡ . | LRT P . | Pact§ . |
---|---|---|---|---|---|---|---|---|---|
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 |
SNP . | Gene . | Cases . | Controls . | Sibships . | OR* . | L95† . | U95‡ . | LRT P . | Pact§ . |
---|---|---|---|---|---|---|---|---|---|
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).
Interactions between folate-associated genotypes by multivitamin supplement use
Gene . | SNP . | No multivitamin supplement use* . | Multivitamin supplement use . | P interaction . | ||||
---|---|---|---|---|---|---|---|---|
Sibships . | OR (95% CI)† . | P‡ . | Sibships . | OR (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 |
Gene . | SNP . | No multivitamin supplement use* . | Multivitamin supplement use . | P interaction . | ||||
---|---|---|---|---|---|---|---|---|
Sibships . | OR (95% CI)† . | P‡ . | Sibships . | OR (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.
Discussion
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.
Disclosure of Potential Conflicts of Interest
D. Conti is a consultant for Pfizer Inc. and P. Limburg is a consultant for Genomic Health Inc.
Acknowledgments
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.