Abstract
The Ala222Val single nucleotide polymorphism (SNP) in the gene for 5,10-methylenetetrahydrofolate reductase (MTHFR), a critical enzyme in one-carbon metabolism, has been associated with colorectal cancer risk. Many enzymes are involved in one-carbon metabolism, and SNPs in the corresponding genes may play a role in colorectal carcinogenesis. We examined 24 nonsynonymous SNPs in 13 genes involved in the one-carbon metabolism pathway in relation to the risk of colorectal cancer in a case-control study nested in the Nurses' Health Study and the Health Professionals Follow-up Study cohorts. Among 376 men and women with colorectal cancer and 849 controls, a reduced risk of colorectal cancer was observed for Val/Val versus Ala carriers of MTHFR Ala222Val [odds ratio (OR), 0.66; 95% confidence interval (CI), 0.43-1.00]. An increased risk was suggested for the variant carrier genotypes versus homozygous wild-type for betaine hydroxymethyltransferase Arg239Gln (OR, 1.40; 95% CI, 1.07-1.83) and two linked SNPs in methionine synthase reductase, Ser284Thr (OR, 1.85; 95% CI, 1.05-3.27) and Arg415Cys (OR, 2.03; 95% CI, 1.15-3.56). The other SNPs were not associated with colorectal cancer risk. Also, none of the SNPs were associated with risk in subgroups of dietary methyl status or were jointly associated with colorectal cancer risk in combination with another SNP, except possibly SNPs in methionine synthase and transcobalamin II. However, these analyses of gene-diet interactions were limited in statistical power. Our results corroborate previous findings for MTHFR Ala222Val and suggest that other genes involved in one-carbon metabolism, particularly those that affect DNA methylation, may be associated with colorectal cancer risk. (Cancer Epidemiol Biomarkers Prev 2006;15(12):2408–17)
Introduction
Folate intake and plasma folate levels have been inversely associated with the risk of colorectal cancer among men and women in most previous case-control and prospective cohort studies (1, 2). The main function of folate, a B vitamin found most abundantly in vegetables and fortified grain products (3), is to mediate the transfer of one-carbon units in various cellular reactions, including those that are necessary for thymidine, purine, and methionine synthesis (4). A sufficient pool of thymidine and purine nucleotides is required for adequate DNA synthesis and repair, whereas methionine, which is converted to S-adenosylmethionine, the methyl donor for various methylation reactions, is required for the maintenance of normal DNA methylation patterns. Abnormal DNA synthesis and methylation, due to insufficient folate intake, are thought to play a role in colorectal carcinogenesis (5).
High intakes of alcohol, a known folate antagonist (6), have also been associated with an increased risk of colorectal cancer (7, 8). The highest relative risks of colorectal cancer have been observed among individuals with methyl-poor diets, defined by high intakes of alcohol combined with low intakes of folate and methionine, compared to individuals with methyl-rich diets that are low in alcohol and high in folate and methionine (7, 9). Further support for the role of folate in colorectal carcinogenesis comes from evidence that a single nucleotide polymorphism (SNP) in the gene that encodes methylenetetrahydrofolate reductase (MTHFR), a critical enzyme in folate-mediated one-carbon metabolism, is associated with the risk of colorectal cancer (10, 11). MTHFR catalyzes the irreversible conversion of folate in the form of 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate, and in doing so, directs the folate pool towards methionine synthesis at the expense of nucleotide synthesis. The Val/Val genotype compared with Ala/Ala at codon 222 of MTHFR has been associated with decreased enzyme activity (12) and a decreased risk of colorectal cancer in most previous studies (11). Several studies have shown that Val/Val is associated with a reduced risk of colorectal cancer, particularly among individuals with a folate/methyl-sufficient diet, whereas those with a diet that is poor in methyl groups do not experience a similar reduced risk with the Val/Val genotype (13).
Many enzymes are involved in one-carbon metabolism (Fig. 1) and SNPs in these genes may play a role in colorectal carcinogenesis. In addition, other B vitamins, including vitamins B2, B6, and B12 act as cofactors in the one-carbon metabolism pathway. We examined the association between potentially functional SNPs in several genes in the one-carbon metabolism pathway and the risk of colorectal cancer in a case-control study nested in the Nurses' Health Study (NHS) and the Health Professionals Follow-up Study (HPFS) cohorts. We examined the main effect of each SNP, gene-nutrient interactions with dietary methyl status and B vitamin cofactors, as well as possible gene-gene joint associations.
The one-carbon metabolism pathway. For definitions of ATIC, BHMT, DNMT1, FOLH1, FTHFD, GART, MTHFD1, MTHFR, MTHFS, MTR, MTRR, SHMT, and TCN II, see Table 1. AMT, aminomethyltransferase; CBS, cystathionine-β-synthase; DHFR, dihydrofolate reductase; FTCD, formiminotransferase cyclodeaminase; MAT1A, methionine adenosyltransferase I; RFC, reduced folate carrier; SAHH, S-adenosylhomocysteine hydrolase; TYMS, thymidylate synthase. Enzymes (ovals), cofactors (circles), and carrier proteins (rectangles).
The one-carbon metabolism pathway. For definitions of ATIC, BHMT, DNMT1, FOLH1, FTHFD, GART, MTHFD1, MTHFR, MTHFS, MTR, MTRR, SHMT, and TCN II, see Table 1. AMT, aminomethyltransferase; CBS, cystathionine-β-synthase; DHFR, dihydrofolate reductase; FTCD, formiminotransferase cyclodeaminase; MAT1A, methionine adenosyltransferase I; RFC, reduced folate carrier; SAHH, S-adenosylhomocysteine hydrolase; TYMS, thymidylate synthase. Enzymes (ovals), cofactors (circles), and carrier proteins (rectangles).
Materials and Methods
Study Populations
SNPs in MTHFR and methionine synthase (MTR) have been previously examined for prevalent colorectal cancer in the HPFS, and for colorectal adenoma in the NHS and HPFS (10, 14, 15). The participants in the current study of incident colorectal cancer do not overlap with participants from these previous publications. The nested case-control studies of incident colorectal cancer among women in the NHS and among men in the HPFS have been described previously (16, 17). The NHS is an ongoing prospective study of 121,700 female registered nurses in the U.S. In 1976, women ages 30 to 55 provided questionnaire information on demographic, life-style, and reproductive factors. Dietary information was first obtained in 1980. Updated information on risk factors and disease diagnoses (confirmed by medical record review) has been collected biennially through mailed questionnaires (information on diet is collected quadrennially). Between 1989 and 1990, blood specimens were collected from 32,826 women in the NHS. Women with colorectal cancer and their controls were selected from among this subcohort of women with a blood sample and were eligible if they were free of inflammatory bowel disease and did not have a history of cancer (except non–melanoma skin cancer). Between 1989 and 2000, 197 women from this subcohort developed colorectal cancer. Four hundred and ninety-two women who were matched to cases on year of birth, date of blood collection, and fasting status were selected as controls.
The HPFS is an ongoing prospective study of 51,529 male dentists, optometrists, osteopaths, podiatrists, pharmacists, and veterinarians in the U.S. In 1986, men ages 40 to 75 years provided questionnaire information on demographic, life-style, medical history, and dietary factors. Updated information has been collected biennially through mailed questionnaires (information on diet is collected quadrennially). Self-reported disease diagnoses are confirmed by medical record review. Between 1993 and 1994, blood specimens were collected from 18,018 men in the HPFS. Men with colorectal cancer and their controls were eligible to be selected from among this subcohort of men who provided a blood sample if they did not have a history of cancer (except non–melanoma skin cancer). Between 1993 and 2002, 179 men developed colorectal cancer and each case was matched to two men without colorectal cancer on year of birth and date of blood collection. Subsequently, it was discovered that one control should not have been selected as he had a history of cancer, thus, there was a total of 357 controls.
SNP Selection
The genes in the one-carbon metabolism pathway that were included in our search for SNPs are shown in Fig. 1. We searched for SNPs in each of the genes using publicly available databases that had allele frequency information, including SNP500 Cancer (http://snp500cancer.nci.nih.gov/), the International HapMap Project (http://www.hapmap.org), and dbSNP (http://www.ncbi.nlm.nih.gov/SNP/). We identified and included SNPs that resulted in amino acid changes and were therefore potentially functional. We also included one SNP in the folate hydrolase gene that was not referenced in any of these databases but has been examined in association with serum folate and homocysteine levels (18). Our final selection included 26 SNPs in 15 genes with a rare allele frequency of 2% or greater. We were unable to design a TaqMan assay for a SNP in the gene for the reduced folate carrier (rs1051266), and another SNP in the gene for methionine adenosyltransferase I (rs1143693) was not polymorphic in our data, thus, our analysis included 24 SNPs in 13 genes (Table 1). The web tools, Polymorphism Phenotyping (PolyPhen; ref. 19) and Sorting Intolerant from Tolerant (SIFT; ref. 20), were used to predict the possible effect of each selected SNP on protein structure or function (Table 1).
Genes and SNPs included in the analysis
Gene . | . | . | SNP . | . | . | . | |||||
---|---|---|---|---|---|---|---|---|---|---|---|
Name . | Symbol . | Chromosomal location . | Codon, amino acid change* . | Reference . | PolyPhen prediction† . | SIFT score‡ . | |||||
Aminoimidazole-4-carboxamide ribonucleotide transferase | ATIC | 2q35 | Thr116Ser | rs2372536 | Benign | 0.27 | |||||
Betaine-homocysteine methyltransferase | BHMT | 5q13.1-q15 | Arg239Gln | rs3733890 | Benign | 0.63 | |||||
DNA methyltransferase 1 | DNMT1 | 19p13.2 | Ile311Val | rs8111085 | Benign | 0.30 | |||||
Folate hydrolase | FOLH1 | 11p11.2 | Tyr75His | rs202676 | Benign | 0.15 | |||||
His475Tyr | —§ | — | — | ||||||||
10-formyltetrahydrofolate dehydrogenase | FTHFD | 3q21.2 | Leu254Pro | rs3796191 | Benign | 0.34∥ | |||||
Asp793Gly | rs1127717 | Possibly damaging | No prediction | ||||||||
Ile812Val | rs4646750 | Benign | 0.29∥ | ||||||||
Glycinade ribonucleotide transformylase | GART | 21q22.1 | Val421Ile | rs9984077 | Benign | Not found | |||||
Asp752Gly | rs8971 | Possibly damaging | 0.36 | ||||||||
Methylenetetrahydrofolate dehydrogenase 1 | MTHFD1 | 14q24 | Arg134Lys | rs1950902 | Benign | 1.00∥ | |||||
Arg653Gln | rs2236225 | Benign | 0.09 | ||||||||
Methylenetetrahydrofolate reductase | MTHFR | 1p36.3 | Ala222Val | rs1801133 | Possibly damaging | 0.06 | |||||
Glu429Ala | rs1801131 | Benign | 0.19 | ||||||||
Methylenetetrahydrofolate synthetase | MTHFS | 15q23 | Thr202Ala | rs8923 | Benign | 0.24∥ | |||||
Methionine synthase | MTR | 1q43 | Asp919Gly | rs1805087 | Possibly damaging | 0.35 | |||||
Methionine synthase reductase | MTRR | 5p15.3-p15.2 | Ile22Met | rs1801394 | Benign | 0.06 | |||||
Ser175Leu | rs1532268 | Benign | 0.85 | ||||||||
Ser284Thr | rs2303080 | Benign | 0.59 | ||||||||
Lys350Arg | rs162036 | Benign | 0.37 | ||||||||
Arg415Cys | rs2287780 | Possibly damaging | 0.04 | ||||||||
His595Tyr | rs10380 | Possibly damaging | 0.03 | ||||||||
Serine hydroxymethyltransferase | SHMT | 17p11.2 | Leu474Phe | rs1979277 | Benign | 0.04 | |||||
Transcobalamin II | TCN II | 22q12.2 | Pro259Arg | rs1801198 | Benign | 0.59 |
Gene . | . | . | SNP . | . | . | . | |||||
---|---|---|---|---|---|---|---|---|---|---|---|
Name . | Symbol . | Chromosomal location . | Codon, amino acid change* . | Reference . | PolyPhen prediction† . | SIFT score‡ . | |||||
Aminoimidazole-4-carboxamide ribonucleotide transferase | ATIC | 2q35 | Thr116Ser | rs2372536 | Benign | 0.27 | |||||
Betaine-homocysteine methyltransferase | BHMT | 5q13.1-q15 | Arg239Gln | rs3733890 | Benign | 0.63 | |||||
DNA methyltransferase 1 | DNMT1 | 19p13.2 | Ile311Val | rs8111085 | Benign | 0.30 | |||||
Folate hydrolase | FOLH1 | 11p11.2 | Tyr75His | rs202676 | Benign | 0.15 | |||||
His475Tyr | —§ | — | — | ||||||||
10-formyltetrahydrofolate dehydrogenase | FTHFD | 3q21.2 | Leu254Pro | rs3796191 | Benign | 0.34∥ | |||||
Asp793Gly | rs1127717 | Possibly damaging | No prediction | ||||||||
Ile812Val | rs4646750 | Benign | 0.29∥ | ||||||||
Glycinade ribonucleotide transformylase | GART | 21q22.1 | Val421Ile | rs9984077 | Benign | Not found | |||||
Asp752Gly | rs8971 | Possibly damaging | 0.36 | ||||||||
Methylenetetrahydrofolate dehydrogenase 1 | MTHFD1 | 14q24 | Arg134Lys | rs1950902 | Benign | 1.00∥ | |||||
Arg653Gln | rs2236225 | Benign | 0.09 | ||||||||
Methylenetetrahydrofolate reductase | MTHFR | 1p36.3 | Ala222Val | rs1801133 | Possibly damaging | 0.06 | |||||
Glu429Ala | rs1801131 | Benign | 0.19 | ||||||||
Methylenetetrahydrofolate synthetase | MTHFS | 15q23 | Thr202Ala | rs8923 | Benign | 0.24∥ | |||||
Methionine synthase | MTR | 1q43 | Asp919Gly | rs1805087 | Possibly damaging | 0.35 | |||||
Methionine synthase reductase | MTRR | 5p15.3-p15.2 | Ile22Met | rs1801394 | Benign | 0.06 | |||||
Ser175Leu | rs1532268 | Benign | 0.85 | ||||||||
Ser284Thr | rs2303080 | Benign | 0.59 | ||||||||
Lys350Arg | rs162036 | Benign | 0.37 | ||||||||
Arg415Cys | rs2287780 | Possibly damaging | 0.04 | ||||||||
His595Tyr | rs10380 | Possibly damaging | 0.03 | ||||||||
Serine hydroxymethyltransferase | SHMT | 17p11.2 | Leu474Phe | rs1979277 | Benign | 0.04 | |||||
Transcobalamin II | TCN II | 22q12.2 | Pro259Arg | rs1801198 | Benign | 0.59 |
SNPs are written in the format wild-type allele/codon number/variant allele.
PolyPhen predicts amino acid changes as benign, possibly damaging, or probably damaging.
Sorting Intolerant From Tolerant (SIFT) score indicates if amino acid changes are predicted to be damaging (<0.05) or tolerated (≥0.05).
This SNP was identified in Devlin et al. (18).
The SIFT score for these SNPs should be interpreted with caution as they were predicted with low confidence because the protein alignment did not have enough diversity.
DNA Extraction and Genotyping
DNA was extracted from 50 μL of buffy coat diluted with 150 μL of PBS using the QIAmp (Qiagen, Inc., Chatsworth, CA) 96-spin blood protocol according to the manufacturer's instructions. The TaqMan assay was used to genotype each of the 24 SNPs (21). Specific primer and probe sequences are available on request. A random 10% of quality control samples were inserted in each genotyping run and concordance for these samples for each of the 24 SNPs was 100%. Laboratory personnel were blinded to the case-control status of the specimens, and to the quality control samples. When genotype distributions were out of Hardy-Weinberg equilibrium, genotyping was repeated to exclude genotyping errors. The median genotyping success rate across all 24 SNPs was 95% (range, 93-98%).
Statistical Analyses
Characteristics of the study population were described using means for continuous variables and percentages for categorical variables. Genotype distributions were tested for departures from Hardy-Weinberg equilibrium using the χ2 test. For genes with multiple SNPs, D′ and r2 values were calculated to assess potential linkage disequilibrium between each of the SNPs within a gene. We used the ALLELE procedure of SAS Genetics (Cary, NC) (22).
The data for women and men were examined separately, as well as pooled, and conditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for the association between genotype and the risk of colorectal cancer for each of the 24 SNPs. Each SNP was examined according to the codominant model, with genotype analyzed as a three-level categorical variable with homozygous wild-type as the reference. Because some of the SNPs examined had sparse variant homozygous frequencies, we also used the dominant model in which variant carriers were compared with homozygous wild-type. We adjusted our analyses for commonly accepted colorectal cancer risk factors, including family history of colorectal cancer, pack-years of smoking, body mass index, physical activity level, aspirin use, red meat consumption, total energy intake, and postmenopausal hormone use (among women), from the questionnaire that preceded the time of diagnosis or selection as a control. We also adjusted for baseline dietary methyl status (described in detail below). Heterogeneity by sex was evaluated by including product terms for genotype and sex. The P values for departure from a multiplicative OR interaction model was based on the likelihood ratio test comparing models with and without the product terms. These analyses were conducted for colorectal cancer overall, and separately for cancers of the proximal colon, distal colon, and rectum. For genes with multiple SNPs, we examined haplotypes, with haplotypes estimated from unphased data using an expectation substitution approach (23). Conditional logistic regression was used to estimate the ORs and 95% CIs for each haplotype relative to the reference, which was the most common haplotype.
We also examined modification of associations between each SNP and colorectal cancer by methyl status of the diet, defined according to intakes of folate (including dietary and supplemental sources), methionine, and alcohol. Because of evidence suggesting that folate intakes during earlier time periods may be more important in reducing colon cancer risk compared with folate intakes closer to the time of diagnosis (24), which may possibly promote carcinogenesis (25), we used baseline intakes of total folate, methionine, and alcohol to define dietary methyl status. In addition, to account for changes in folate intakes during follow-up, which have increased for individuals in the U.S. following the implementation of the folate fortification program in 1996, we also examined dietary methyl status based on the cumulative average intake of folate based on energy-adjusted daily intakes in micrograms per day (μg/d) from the time of blood draw up to the time of diagnosis for cases or selection as a control. For consistency, methionine and alcohol intakes were calculated in the same way.
Dietary methyl status was modeled as a three-level categorical variable (low, intermediate, and high). Low methyl status was defined as energy-adjusted intakes below the sex-specific median level among controls for total folate (338.0 μg/d for women, 444.5 μg/d for men) and methionine (1.82 g/d for women, 2.01 g/d for men), combined with alcohol intakes of 5 g/d or more for women and 15 g/d or more for men. Conversely, high methyl status was defined by energy-adjusted intakes of total folate and methionine at or above the sex-specific median levels combined with low alcohol intakes (<5 g/d for women, <15 g/d for men). The dietary methyl status of individuals not classified as low or high based on these definitions was considered as intermediate. We examined whether the associations for each SNP and colorectal cancer risk were modified by dietary methyl status by including a product term between genotype (using the dominant model) and dietary methyl status, and conducting the likelihood ratio test comparing models with and without the product terms. We also tested whether each SNP was associated with colorectal cancer risk among any subgroup defined by dietary methyl status. This test was based on the likelihood ratio test comparing the genetic null model, which included only the main effect of dietary methyl status, with the model including dietary methyl status, genotype, and the interaction term between genotype and dietary methyl status. The P value for this test, which we refer to as the global P value, indicates the significance of the fit of the model after the addition of the genotype main effect and the interaction term. A significant global P value may reflect any significant main effect of the SNP that we observe, but may also indicate that a SNP for which no main effect is observed is in fact associated with colorectal cancer risk within levels of dietary methyl status.
The analyses of interactions with other B vitamins were also conducted using the likelihood ratio test. Energy-adjusted intakes of vitamins B2, B6 and B12 were based on dietary and supplemental sources and were modeled as high versus low for the interaction analyses, where high intakes were defined as above the median level and low intakes were at or below the median. The median intakes for men and women, respectively, were 2.5 mg/d and 2.2 mg/d for vitamin B2, 2.9 mg/d and 2.5 mg/d for vitamin B6 and 9.9 μg/d and 8.0 μg/d for vitamin B12.
Finally, we examined whether a SNP was associated with the risk of colorectal cancer jointly with another SNP by examining all two-way gene-gene combinations. The global P value for this test was calculated using the likelihood ratio test comparing the null model, with no genetic effects, to the model containing the main effect of each SNP and the product term between the two SNPs (26). This test differs from a test for significance of the interaction term, and was conducted to test whether either SNP within a pair-wise gene-gene model was associated with disease (26), regardless of whether a main effect was observed. All statistical tests were two-sided.
Results
Each of the 24 SNPs was genotyped among 376 men and women with colorectal cancer and 849 controls. The mean age of the cases and their matched controls was 67.8 years; the women were younger than the men (Table 2). A family history of colorectal cancer was more common among cases than controls, whereas regular aspirin use, multivitamin use, and having never smoked was more frequent among controls than cases (Table 2). Among men, cases tended to consume more red meat than controls, and among women, controls were more likely to currently use postmenopausal hormones (Table 2). Among the cases with colorectal site information (n = 333), 43.8% were proximal colon cancers, 31.8% were distal colon cancers, and 24.3% were rectal cancers; this distribution did not appreciably differ between men and women (Table 2).
Characteristics of the study population
. | Men . | . | Women . | . | ||
---|---|---|---|---|---|---|
. | Cases (n = 179) . | Controls (n = 357) . | Cases (n = 197) . | Controls (n = 492) . | ||
Mean age at diagnosis or selection (y) | 71.1 | 71.1 | 65.5 | 65.2 | ||
Family history of colorectal cancer (%) | 21.8 | 15.1 | 23.4 | 17.3 | ||
Never smokers (%) | 41.3 | 47.3 | 43.2 | 47.6 | ||
Regular aspirin use (%) | 20.1 | 25.8 | 31.0 | 35.2 | ||
Current use of postmenopausal hormones (%) | — | — | 33.5 | 44.9 | ||
Multivitamin use (%) | 53.6 | 57.4 | 45.2 | 49.4 | ||
Mean body mass index (kg/m2) | 26.1 | 25.6 | 26.1 | 26.0 | ||
Mean physical activity level (MET-h/wk) | 31.2 | 33.2 | 16.4 | 17.8 | ||
Red meat intake, ≥1 serving/d (%) | 36.3 | 31.9 | 19.3 | 20.1 | ||
Mean total folate intake* (μg/d) | 495.2 | 532.7 | 408.0 | 427.9 | ||
Mean methionine intake* (g/d) | 2.0 | 2.0 | 1.7 | 1.8 | ||
Mean alcohol intake* (g/d) | 11.5 | 11.6 | 7.6 | 6.4 | ||
Mean vitamin B2 intake* (mg/d) | 5.1 | 5.8 | 3.7 | 4.2 | ||
Mean vitamin B6 intake* (mg/d) | 6.4 | 8.7 | 6.1 | 7.6 | ||
Mean vitamin B12 intake* (μg/d) | 13.2 | 13.6 | 10.3 | 10.5 | ||
Cases with nonmissing colorectal site (n) | 156 | 177 | ||||
Proximal colon cancers (%) | 44.2 | 43.5 | ||||
Distal colon cancers (%) | 30.1 | 33.3 | ||||
Rectal cancers (%) | 25.6 | 23.2 |
. | Men . | . | Women . | . | ||
---|---|---|---|---|---|---|
. | Cases (n = 179) . | Controls (n = 357) . | Cases (n = 197) . | Controls (n = 492) . | ||
Mean age at diagnosis or selection (y) | 71.1 | 71.1 | 65.5 | 65.2 | ||
Family history of colorectal cancer (%) | 21.8 | 15.1 | 23.4 | 17.3 | ||
Never smokers (%) | 41.3 | 47.3 | 43.2 | 47.6 | ||
Regular aspirin use (%) | 20.1 | 25.8 | 31.0 | 35.2 | ||
Current use of postmenopausal hormones (%) | — | — | 33.5 | 44.9 | ||
Multivitamin use (%) | 53.6 | 57.4 | 45.2 | 49.4 | ||
Mean body mass index (kg/m2) | 26.1 | 25.6 | 26.1 | 26.0 | ||
Mean physical activity level (MET-h/wk) | 31.2 | 33.2 | 16.4 | 17.8 | ||
Red meat intake, ≥1 serving/d (%) | 36.3 | 31.9 | 19.3 | 20.1 | ||
Mean total folate intake* (μg/d) | 495.2 | 532.7 | 408.0 | 427.9 | ||
Mean methionine intake* (g/d) | 2.0 | 2.0 | 1.7 | 1.8 | ||
Mean alcohol intake* (g/d) | 11.5 | 11.6 | 7.6 | 6.4 | ||
Mean vitamin B2 intake* (mg/d) | 5.1 | 5.8 | 3.7 | 4.2 | ||
Mean vitamin B6 intake* (mg/d) | 6.4 | 8.7 | 6.1 | 7.6 | ||
Mean vitamin B12 intake* (μg/d) | 13.2 | 13.6 | 10.3 | 10.5 | ||
Cases with nonmissing colorectal site (n) | 156 | 177 | ||||
Proximal colon cancers (%) | 44.2 | 43.5 | ||||
Distal colon cancers (%) | 30.1 | 33.3 | ||||
Rectal cancers (%) | 25.6 | 23.2 |
Baseline intakes.
Departures from Hardy-Weinberg equilibrium among controls were suggested for FOLH1 His475Tyr (P = 0.03) and MTRR Lys350Arg (P = 0.04) in the NHS, and FTHFD Leu254Pro (P = 0.03), MTHFD1 Arg134Lys (P = 0.02), MTHFR Ala222Val (P = 0.02), MTRR Ser175Leu (P = 0.02), and SHMT Leu474Phe (P = 0.02) in the HPFS. These P values were not extreme given the number of statistical tests conducted, and the genotype distributions for these SNPs, as well as all other SNPs, did not differ between men and women. When men and women were combined, all SNPs were in Hardy-Weinberg equilibrium among controls except MTHFR Ala222Val (P = 0.01) and MTRR Ser175Leu (P = 0.02). For SNPs that have been previously examined, genotype distributions in our study population were consistent with what has been observed in other populations of predominantly Caucasian origin. Minor allele frequencies ranged from 2% to 44% across all SNPs except MTRR Ile22Met and MTHFD1 Arg653Gln. The frequency of the Met allele of MTRR Ile22Met (55%) and the Gln allele of MTHFD1 Arg653Gln (52%) indicated that these alleles were not the minor allele in our study population. The Ala222Val and Glu429Ala SNPs in MTHFR were in linkage disequilibrium (D′ = 1.00, r2 = 0.24). In addition, there was evidence of linkage disequilibrium between the two SNPs in each of the genes FOLH1 (D′ = 0.88), GART (D′ = 1.00), and MTHFD1 (D′ = 0.40), as well as between Leu254Pro and Asp793Gly (D′ = 1.00), and Asp793Gly and Ile812Val (D′ = 1.00) in FTHFD, however, the corresponding correlations for each of these pair-wise combinations were low (r2 < 0.10). Similarly, there was evidence of linkage disequilibrium between each of the six SNPs in the MTRR gene (D′ = 0.20-1.00), although each pair-wise combination was not highly correlated (r2 < 0.15), except for Ser284Thr and Arg415Cys (r2 = 0.97), and Lys350Arg and His595Tyr (r2 = 0.84).
For MTHFR Ala222Val, a nonsignificant reduced risk of colorectal cancer among individuals with the Val/Val genotype compared with Ala/Ala was observed (Table 3; adjusted OR, 0.65; 95% CI, 0.42-1.01). The unadjusted results did not differ greatly. This association was similar among men (OR, 0.64; 95% CI, 0.32-1.27) and women (OR, 0.70; 95% CI, 0.38-1.29). The OR for Val/Val versus Ala/Ala was weaker for rectal cancers (OR, 1.08; 95% CI, 0.38-3.04) compared with colon cancers [the OR (95% CI) was 0.67 (0.31-1.43) for proximal colon cancer and 0.33 (0.13-0.84) for distal colon cancer]. When analyzed using the dominant model, an association between MTHFR Ala222Val was not apparent (Table 3), however, when using the recessive model, the OR (95% CI) for Val/Val versus Ala carriers was 0.66 (0.43-1.00).
Adjusted ORs (95% CIs) for the association between SNPs in one-carbon metabolism genes and the risk of colorectal cancer in men and women
Gene . | SNP . | . | Genotype* . | . | . | . | P for interaction by sex . | |||
---|---|---|---|---|---|---|---|---|---|---|
. | . | . | wt/wt . | wt/var . | var/var . | var carrier . | . | |||
ATIC | Thr116Ser | Cases/controls† | 151/357 | 175/368 | 39/94 | 214/462 | ||||
OR (95% CI) | 1.00 (ref) | 1.10 (0.84-1.44) | 0.98 (0.64-1.52) | 1.07 (0.83-1.39) | 0.63 | |||||
BHMT | Arg239Gln | Cases/controls† | 166/431 | 158/319 | 35/57 | 193/376 | ||||
OR (95% CI) | 1.00 (ref) | 1.34 (1.01-1.77) | 1.73 (1.07-2.80) | 1.40 (1.07-1.83) | 0.38 | |||||
DNMT1 | Ile311Val | Cases/controls† | 301/690 | 41/98 | 1/7 | 42/105 | ||||
OR (95% CI) | 1.00 (ref) | 0.97 (0.63-1.47) | 0.26 (0.03-2.32) | 0.92 (0.61-1.40) | 0.89 | |||||
FOLH1 | Tyr75His | Cases/controls† | 228/517 | 115/255 | 15/39 | 130/294 | ||||
OR (95% CI) | 1.00 (ref) | 1.04 (0.78-1.38) | 0.90 (0.48-1.68) | 1.02 (0.78-1.33) | 0.10 | |||||
His475Tyr | Cases/controls† | 320/721 | 31/67 | 0/3 | 31/70 | |||||
OR (95% CI) | 1.00 (ref) | 1.01 (0.63-1.63) | —‡ | 0.97 (0.60-1.55) | 0.30 | |||||
FTHFD | Leu254Pro | Cases/controls† | 326/728 | 23/61 | 1/2 | 24/63 | ||||
OR (95% CI) | 1.00 (ref) | 0.96 (0.57-1.63) | 1.27 (0.11-14.78) | 0.98 (0.58-1.63) | 0.49 | |||||
Asp793Gly | Cases/controls† | 232/504 | 106/266 | 20/31 | 126/297 | |||||
OR (95% CI) | 1.00 (ref) | 0.81 (0.60-1.08) | 1.57 (0.85-2.89) | 0.88 (0.67-1.16) | 0.11 | |||||
Ile812Val | Cases/controls† | 318/716 | 47/100 | 1/3 | 48/103 | |||||
OR (95% CI) | 1.00 (ref) | 1.09 (0.73-1.63) | 0.86 (0.07-10.93) | 1.09 (0.73-1.61) | 0.77 | |||||
GART | Val421Ile | Cases/controls† | 226/479 | 118/302 | 20/42 | 138/344 | ||||
OR (95% CI) | 1.00 (ref) | 0.88 (0.67-1.15) | 1.09 (0.61-1.94) | 0.90 (0.70-1.17) | 0.27 | |||||
Asp752Gly | Cases/controls† | 213/459 | 128/285 | 17/60 | 145/345 | |||||
OR (95% CI) | 1.00 (ref) | 1.05 (0.79-1.39) | 0.58 (0.32-1.05) | 0.95 (0.73-1.24) | 0.61 | |||||
MTHFD1 | Arg134Lys | Cases/controls† | 247/544 | 91/227 | 8/20 | 99/247 | ||||
OR (95% CI) | 1.00 (ref) | 0.86 (0.64-1.15) | 0.91 (0.38-2.17) | 0.86 (0.64-1.15) | 0.34 | |||||
Arg653Gln | Cases/controls† | 74/190 | 162/375 | 122/225 | 284/600 | |||||
OR (95% CI) | 1.00 (ref) | 1.20 (0.85-1.69) | 1.37 (0.95-1.99) | 1.27 (0.92-1.75) | 0.95 | |||||
MTHFR | Ala222Val | Cases/controls† | 166/355 | 145/327 | 38/112 | 183/439 | ||||
OR (95% CI) | 1.00 (ref) | 0.98 (0.73-1.30) | 0.65 (0.42-1.01) | 0.89 (0.68-1.17) | 0.22 | |||||
Glu429Ala | Cases/controls† | 154/389 | 166/332 | 33/85 | 199/417 | |||||
OR (95% CI) | 1.00 (ref) | 1.21 (0.90-1.61) | 0.98 (0.61-1.59) | 1.16 (0.88-1.54) | 0.04 | |||||
MTHFS | Thr202Ala | Cases/controls† | 299/688 | 63/125 | 1/4 | 64/129 | ||||
OR (95% CI) | 1.00 (ref) | 1.22 (0.85-1.74) | 0.43 (0.04-4.58) | 1.19 (0.83-1.69) | 0.67 | |||||
MTR | Asp919Gly | Cases/controls† | 222/529 | 121/239 | 20/36 | 141/275 | ||||
OR (95% CI) | 1.00 (ref) | 1.26 (0.95-1.68) | 1.13 (0.61-2.08) | 1.24 (0.95-1.63) | 0.96 | |||||
MTRR | Ile22Met | Cases/controls† | 82/163 | 159/399 | 116/245 | 275/644 | ||||
OR (95% CI) | 1.00 (ref) | 0.88 (0.63-1.24) | 0.98 (0.68-1.41) | 0.92 (0.67-1.26) | 0.88 | |||||
Ser175Leu | Cases/controls† | 146/330 | 173/351 | 41/131 | 214/482 | |||||
OR (95% CI) | 1.00 (ref) | 1.27 (0.96-1.69) | 0.71 (0.46-1.09) | 1.11 (0.85-1.46) | 0.52 | |||||
Ser284Thr | Cases/controls† | 335/782 | 23/38 | 0/0 | 23/38 | |||||
OR (95% CI) | 1.00 (ref) | 1.85 (1.05-3.27) | —‡ | 1.85 (1.05-3.27) | 0.39 | |||||
Lys350Arg | Cases/controls† | 277/642 | 70/150 | 8/14 | 78/164 | |||||
OR (95% CI) | 1.00 (ref) | 1.08 (0.77-1.50) | 1.35 (0.53-3.44) | 1.10 (0.80-1.52) | 0.94 | |||||
Arg415Cys | Cases/controls† | 339/796 | 24/37 | 0/0 | 24/37 | |||||
OR (95% CI) | 1.00 (ref) | 2.03 (1.15-3.56) | —‡ | 2.03 (1.15-3.56) | 0.52 | |||||
His595Tyr | Cases/controls† | 288/658 | 59/132 | 9/8 | 68/140 | |||||
OR (95% CI) | 1.00 (ref) | 0.97 (0.68-1.38) | 2.41 (0.88-6.61) | 1.06 (0.76-1.49) | 0.51 | |||||
SHMT | Leu474Phe | Cases/controls† | 172/370 | 141/358 | 37/75 | 178/433 | ||||
OR (95% CI) | 1.00 (ref) | 0.84 (0.64-1.12) | 1.07 (0.67-1.73) | 0.88 (0.68-1.15) | 0.84 | |||||
TCN II | Pro259Arg | Cases/controls† | 119/249 | 168/392 | 62/155 | 230/547 | ||||
OR (95% CI) | 1.00 (ref) | 0.86 (0.64-1.17) | 0.85 (0.57-1.26) | 0.86 (0.65-1.14) | 0.08 |
Gene . | SNP . | . | Genotype* . | . | . | . | P for interaction by sex . | |||
---|---|---|---|---|---|---|---|---|---|---|
. | . | . | wt/wt . | wt/var . | var/var . | var carrier . | . | |||
ATIC | Thr116Ser | Cases/controls† | 151/357 | 175/368 | 39/94 | 214/462 | ||||
OR (95% CI) | 1.00 (ref) | 1.10 (0.84-1.44) | 0.98 (0.64-1.52) | 1.07 (0.83-1.39) | 0.63 | |||||
BHMT | Arg239Gln | Cases/controls† | 166/431 | 158/319 | 35/57 | 193/376 | ||||
OR (95% CI) | 1.00 (ref) | 1.34 (1.01-1.77) | 1.73 (1.07-2.80) | 1.40 (1.07-1.83) | 0.38 | |||||
DNMT1 | Ile311Val | Cases/controls† | 301/690 | 41/98 | 1/7 | 42/105 | ||||
OR (95% CI) | 1.00 (ref) | 0.97 (0.63-1.47) | 0.26 (0.03-2.32) | 0.92 (0.61-1.40) | 0.89 | |||||
FOLH1 | Tyr75His | Cases/controls† | 228/517 | 115/255 | 15/39 | 130/294 | ||||
OR (95% CI) | 1.00 (ref) | 1.04 (0.78-1.38) | 0.90 (0.48-1.68) | 1.02 (0.78-1.33) | 0.10 | |||||
His475Tyr | Cases/controls† | 320/721 | 31/67 | 0/3 | 31/70 | |||||
OR (95% CI) | 1.00 (ref) | 1.01 (0.63-1.63) | —‡ | 0.97 (0.60-1.55) | 0.30 | |||||
FTHFD | Leu254Pro | Cases/controls† | 326/728 | 23/61 | 1/2 | 24/63 | ||||
OR (95% CI) | 1.00 (ref) | 0.96 (0.57-1.63) | 1.27 (0.11-14.78) | 0.98 (0.58-1.63) | 0.49 | |||||
Asp793Gly | Cases/controls† | 232/504 | 106/266 | 20/31 | 126/297 | |||||
OR (95% CI) | 1.00 (ref) | 0.81 (0.60-1.08) | 1.57 (0.85-2.89) | 0.88 (0.67-1.16) | 0.11 | |||||
Ile812Val | Cases/controls† | 318/716 | 47/100 | 1/3 | 48/103 | |||||
OR (95% CI) | 1.00 (ref) | 1.09 (0.73-1.63) | 0.86 (0.07-10.93) | 1.09 (0.73-1.61) | 0.77 | |||||
GART | Val421Ile | Cases/controls† | 226/479 | 118/302 | 20/42 | 138/344 | ||||
OR (95% CI) | 1.00 (ref) | 0.88 (0.67-1.15) | 1.09 (0.61-1.94) | 0.90 (0.70-1.17) | 0.27 | |||||
Asp752Gly | Cases/controls† | 213/459 | 128/285 | 17/60 | 145/345 | |||||
OR (95% CI) | 1.00 (ref) | 1.05 (0.79-1.39) | 0.58 (0.32-1.05) | 0.95 (0.73-1.24) | 0.61 | |||||
MTHFD1 | Arg134Lys | Cases/controls† | 247/544 | 91/227 | 8/20 | 99/247 | ||||
OR (95% CI) | 1.00 (ref) | 0.86 (0.64-1.15) | 0.91 (0.38-2.17) | 0.86 (0.64-1.15) | 0.34 | |||||
Arg653Gln | Cases/controls† | 74/190 | 162/375 | 122/225 | 284/600 | |||||
OR (95% CI) | 1.00 (ref) | 1.20 (0.85-1.69) | 1.37 (0.95-1.99) | 1.27 (0.92-1.75) | 0.95 | |||||
MTHFR | Ala222Val | Cases/controls† | 166/355 | 145/327 | 38/112 | 183/439 | ||||
OR (95% CI) | 1.00 (ref) | 0.98 (0.73-1.30) | 0.65 (0.42-1.01) | 0.89 (0.68-1.17) | 0.22 | |||||
Glu429Ala | Cases/controls† | 154/389 | 166/332 | 33/85 | 199/417 | |||||
OR (95% CI) | 1.00 (ref) | 1.21 (0.90-1.61) | 0.98 (0.61-1.59) | 1.16 (0.88-1.54) | 0.04 | |||||
MTHFS | Thr202Ala | Cases/controls† | 299/688 | 63/125 | 1/4 | 64/129 | ||||
OR (95% CI) | 1.00 (ref) | 1.22 (0.85-1.74) | 0.43 (0.04-4.58) | 1.19 (0.83-1.69) | 0.67 | |||||
MTR | Asp919Gly | Cases/controls† | 222/529 | 121/239 | 20/36 | 141/275 | ||||
OR (95% CI) | 1.00 (ref) | 1.26 (0.95-1.68) | 1.13 (0.61-2.08) | 1.24 (0.95-1.63) | 0.96 | |||||
MTRR | Ile22Met | Cases/controls† | 82/163 | 159/399 | 116/245 | 275/644 | ||||
OR (95% CI) | 1.00 (ref) | 0.88 (0.63-1.24) | 0.98 (0.68-1.41) | 0.92 (0.67-1.26) | 0.88 | |||||
Ser175Leu | Cases/controls† | 146/330 | 173/351 | 41/131 | 214/482 | |||||
OR (95% CI) | 1.00 (ref) | 1.27 (0.96-1.69) | 0.71 (0.46-1.09) | 1.11 (0.85-1.46) | 0.52 | |||||
Ser284Thr | Cases/controls† | 335/782 | 23/38 | 0/0 | 23/38 | |||||
OR (95% CI) | 1.00 (ref) | 1.85 (1.05-3.27) | —‡ | 1.85 (1.05-3.27) | 0.39 | |||||
Lys350Arg | Cases/controls† | 277/642 | 70/150 | 8/14 | 78/164 | |||||
OR (95% CI) | 1.00 (ref) | 1.08 (0.77-1.50) | 1.35 (0.53-3.44) | 1.10 (0.80-1.52) | 0.94 | |||||
Arg415Cys | Cases/controls† | 339/796 | 24/37 | 0/0 | 24/37 | |||||
OR (95% CI) | 1.00 (ref) | 2.03 (1.15-3.56) | —‡ | 2.03 (1.15-3.56) | 0.52 | |||||
His595Tyr | Cases/controls† | 288/658 | 59/132 | 9/8 | 68/140 | |||||
OR (95% CI) | 1.00 (ref) | 0.97 (0.68-1.38) | 2.41 (0.88-6.61) | 1.06 (0.76-1.49) | 0.51 | |||||
SHMT | Leu474Phe | Cases/controls† | 172/370 | 141/358 | 37/75 | 178/433 | ||||
OR (95% CI) | 1.00 (ref) | 0.84 (0.64-1.12) | 1.07 (0.67-1.73) | 0.88 (0.68-1.15) | 0.84 | |||||
TCN II | Pro259Arg | Cases/controls† | 119/249 | 168/392 | 62/155 | 230/547 | ||||
OR (95% CI) | 1.00 (ref) | 0.86 (0.64-1.17) | 0.85 (0.57-1.26) | 0.86 (0.65-1.14) | 0.08 |
NOTE: ORs adjusted for family history of colorectal cancer, pack-years of smoking, postmenopausal hormone use (in women), body mass index, physical activity level, aspirin use, red meat intake, dietary methyl status, and total energy intake.
wt, wild-type; var, variant.
Total number of cases and controls vary due to genotyping failures; there was a total of 376 women and men with colorectal cancer and 849 controls that were genotyped for each of the 24 SNPs.
Unable to estimate OR because there were zero cases and/or controls that were homozygous variant.
Table 3 shows the covariate-adjusted associations for each SNP and colorectal cancer risk. These results were not very different from the unadjusted results (data not shown). In general, we did not observe a strong main effect for the SNPs in the one-carbon metabolism genes included in this study (Table 3). An increased risk associated with the variant allele of BHMT Arg239Gln was suggested; the OR (95% CI) was 1.73 (1.07-2.80) for Gln/Gln versus Arg/Arg and 1.34 (1.01-1.77) for Arg/Gln versus Arg/Arg. This association comparing Gln carriers versus Arg/Arg was slightly weaker for proximal colon cancers (OR, 1.16; 95% CI, 0.75-1.80) compared with cancers of the distal colon (OR, 1.73; 95% CI, 0.97-3.11) and rectum (OR, 1.81; 95% CI, 0.93-3.55). Carriage of variants of two SNPs in the MTRR gene was also associated with an increased colorectal cancer risk (Table 3). For MTRR Ser284Thr, the OR (95% CI) was 1.85 (1.05-3.27) for Ser/Thr versus Ser/Ser and for Arg415Cys, the OR (95% CI) was 2.03 (1.15-3.56) for Arg/Cys versus Arg/Arg. We did not observe statistically significant multiplicative interactions between each SNP and sex, except for MTHFR Glu429Ala (P = 0.04). The adjusted OR (95% CI) for Ala carriers versus Glu/Glu was 1.55 (1.05-2.29) among women and 0.85 (0.56-1.30) among men. Other SNPs for which a difference in men and women was suggested although not statistically significant included FOLH1 His475Tyr [adjusted OR (95% CI) was 1.31 (0.92-1.85) for women and 0.82 (0.54-1.25) for men], FTHFD Ile812Val [adjusted OR (95% CI) was 1.10 (0.77-1.57) for women and 0.64 (0.42-0.99) for men] and TCN II Pro259Arg [adjusted OR (95% CI) was 0.70 (0.49-1.00) for women and 1.11 (0.70-1.75) for men]. The associations for each of the SNPs and colorectal cancer risk generally did not differ appreciably by colorectal site (results not shown). In addition, none of the specific haplotypes were significantly associated with the risk of colorectal cancer (results not shown).
Dietary methyl status was associated with the risk of colorectal cancer. Compared with a high methyl diet, the OR (95% CI) was 1.17 (0.83-1.64) for an intermediate methyl diet and 1.76 (1.08-2.87) for a low methyl diet (P test for trend = 0.03, P test for heterogeneity by sex = 0.92). Our analysis of modifications of ORs by dietary methyl status analyzed as a three-level variable was similar to our findings when high and intermediate methyl status was grouped, therefore, we only present results for the grouped methyl status variable. We observed no evidence of multiplicative interaction between each SNP and dietary methyl status (P test for interaction >0.11; Table 4). Also, no SNP was associated with colorectal cancer risk within levels of dietary methyl status except BHMT Arg239Gln SNP (global P = 0.03; Table 4), which was consistent with the main effect that we observed for this SNP. When dietary methyl status was based on the cumulative average intakes during follow-up (results not shown), the only difference observed was for SHMT in which a marginally significant multiplicative interaction was suggested (P = 0.04). We also examined potential effect modification by high intakes of alcohol (≥15 g/d for women, ≥30 g/d for men) as another measure of methyl status, given that alcohol is a folate antagonist. The results were similar to that from our analysis of dietary methyl status (P test for interaction >0.13; data not shown).
Adjusted OR (95% CI) for the association between SNPs in one-carbon metabolism genes and colorectal cancer risk in men and women according to dietary methyl status
Gene . | SNP . | Homozygous wild-type . | . | Variant carrier . | . | Pglobal* . | Pinteraction† . | ||
---|---|---|---|---|---|---|---|---|---|
. | . | High methyl diet‡ . | Low methyl diet . | High methyl diet . | Low methyl diet . | . | . | ||
ATIC | Thr116Ser | 1.00 (ref) | 1.61 (0.88-2.95) | 1.08 (0.82-1.43) | 1.59 (0.93-2.73) | 0.85 | 0.83 | ||
BHMT | Arg239Gln | 1.00 (ref) | 1.93 (1.06-3.53) | 1.48 (1.11-1.97) | 1.80 (1.04-3.13) | 0.03 | 0.27 | ||
DNMT | Ile311Val | 1.00 (ref) | 1.23 (0.79-1.93) | 0.82 (0.52-1.28) | 2.83 (0.86-9.39) | 0.29 | 0.13 | ||
FOLH | Tyr75His | 1.00 (ref) | 1.52 (0.91-2.53) | 1.00 (0.75-1.34) | 1.72 (0.90-3.29) | 0.95 | 0.77 | ||
His475Tyr | 1.00 (ref) | 1.54 (1.01-2.37) | 1.02 (0.61-1.69) | 1.05 (0.30-3.66) | 0.84 | 0.57 | |||
FTHFD | Leu254Pro | 1.00 (ref) | 1.38 (0.90-2.10) | 0.92 (0.53-1.60) | 2.46 (0.59-10.21) | 0.71 | 0.41 | ||
Asp793Gly | 1.00 (ref) | 1.96 (1.18-3.25) | 0.95 (0.71-1.28) | 0.94 (0.48-1.81) | 0.17 | 0.11 | |||
Ile812Val | 1.00 (ref) | 1.53 (1.00-2.33) | 1.10 (0.72-1.67) | 1.56 (0.58-4.18) | 0.91 | 0.90 | |||
GART | Val421Ile | 1.00 (ref) | 1.39 (0.82-2.35) | 0.89 (0.67-1.18) | 1.39 (0.76-2.52) | 0.71 | 0.77 | ||
Asp752Gly | 1.00 (ref) | 1.68 (1.02-2.77) | 0.96 (0.73-1.28) | 1.44 (0.75-2.77) | 0.89 | 0.77 | |||
MTHFD1 | Arg134Lys | 1.00 (ref) | 1.18 (0.72-1.93) | 0.80 (0.59-1.09) | 1.75 (0.87-3.53) | 0.23 | 0.17 | ||
Arg653Gln | 1.00 (ref) | 1.86 (0.89-3.90) | 1.35 (0.95-1.92) | 1.69 (0.99-2.91) | 0.23 | 0.38 | |||
MTHFR | Ala222Val | 1.00 (ref) | 1.73 (0.95-3.16) | 0.92 (0.69-1.23) | 1.12 (0.62-2.01) | 0.47 | 0.42 | ||
Glu429Ala | 1.00 (ref) | 1.71 (0.90-3.26) | 1.18 (0.88-1.59) | 1.80 (1.05-3.09) | 0.53 | 0.78 | |||
MTHFS | Thr202Ala | 1.00 (ref) | 1.35 (0.88-2.08) | 1.12 (0.77-1.62) | 3.67 (1.16-11.56) | 0.21 | 0.15 | ||
MTR | Asp919Gly | 1.00 (ref) | 1.29 (0.77-2.14) | 1.19 (0.89-1.59) | 2.08 (1.09-3.97) | 0.25 | 0.48 | ||
MTRR | Ile22Met | 1.00 (ref) | 1.09 (0.44-2.72) | 0.89 (0.64-1.23) | 1.36 (0.81-2.30) | 0.70 | 0.51 | ||
Ser175Leu | 1.00 (ref) | 1.60 (0.85-2.99) | 1.13 (0.85-1.50) | 1.63 (0.95-2.81) | 0.71 | 0.81 | |||
Ser284Thr | 1.00 (ref) | 1.62 (1.06-2.47) | 1.82 (1.01-3.27) | 3.19 (0.43-23.78) | 0.12 | 0.94 | |||
Lys350Arg | 1.00 (ref) | 1.57 (1.00-2.45) | 1.13 (0.80-1.59) | 1.41 (0.56-3.55) | 0.77 | 0.67 | |||
Arg415Cys | 1.00 (ref) | 1.59 (1.05-2.41) | 2.01 (1.12-3.61) | 3.43 (0.46-25.57) | 0.06 | 0.95 | |||
His595Tyr | 1.00 (ref) | 1.60 (1.03-2.47) | 1.13 (0.79-1.61) | 0.96 (0.34-2.71) | 0.53 | 0.28 | |||
SHMT | Leu474Phe | 1.00 (ref) | 1.41 (0.82-2.45) | 0.88 (0.67-1.17) | 1.33 (0.74-2.40) | 0.67 | 0.87 | ||
TCN II | Pro259Arg | 1.00 (ref) | 1.86 (0.92-3.74) | 0.90 (0.67-1.23) | 1.11 (0.64-1.92) | 0.37 | 0.35 |
Gene . | SNP . | Homozygous wild-type . | . | Variant carrier . | . | Pglobal* . | Pinteraction† . | ||
---|---|---|---|---|---|---|---|---|---|
. | . | High methyl diet‡ . | Low methyl diet . | High methyl diet . | Low methyl diet . | . | . | ||
ATIC | Thr116Ser | 1.00 (ref) | 1.61 (0.88-2.95) | 1.08 (0.82-1.43) | 1.59 (0.93-2.73) | 0.85 | 0.83 | ||
BHMT | Arg239Gln | 1.00 (ref) | 1.93 (1.06-3.53) | 1.48 (1.11-1.97) | 1.80 (1.04-3.13) | 0.03 | 0.27 | ||
DNMT | Ile311Val | 1.00 (ref) | 1.23 (0.79-1.93) | 0.82 (0.52-1.28) | 2.83 (0.86-9.39) | 0.29 | 0.13 | ||
FOLH | Tyr75His | 1.00 (ref) | 1.52 (0.91-2.53) | 1.00 (0.75-1.34) | 1.72 (0.90-3.29) | 0.95 | 0.77 | ||
His475Tyr | 1.00 (ref) | 1.54 (1.01-2.37) | 1.02 (0.61-1.69) | 1.05 (0.30-3.66) | 0.84 | 0.57 | |||
FTHFD | Leu254Pro | 1.00 (ref) | 1.38 (0.90-2.10) | 0.92 (0.53-1.60) | 2.46 (0.59-10.21) | 0.71 | 0.41 | ||
Asp793Gly | 1.00 (ref) | 1.96 (1.18-3.25) | 0.95 (0.71-1.28) | 0.94 (0.48-1.81) | 0.17 | 0.11 | |||
Ile812Val | 1.00 (ref) | 1.53 (1.00-2.33) | 1.10 (0.72-1.67) | 1.56 (0.58-4.18) | 0.91 | 0.90 | |||
GART | Val421Ile | 1.00 (ref) | 1.39 (0.82-2.35) | 0.89 (0.67-1.18) | 1.39 (0.76-2.52) | 0.71 | 0.77 | ||
Asp752Gly | 1.00 (ref) | 1.68 (1.02-2.77) | 0.96 (0.73-1.28) | 1.44 (0.75-2.77) | 0.89 | 0.77 | |||
MTHFD1 | Arg134Lys | 1.00 (ref) | 1.18 (0.72-1.93) | 0.80 (0.59-1.09) | 1.75 (0.87-3.53) | 0.23 | 0.17 | ||
Arg653Gln | 1.00 (ref) | 1.86 (0.89-3.90) | 1.35 (0.95-1.92) | 1.69 (0.99-2.91) | 0.23 | 0.38 | |||
MTHFR | Ala222Val | 1.00 (ref) | 1.73 (0.95-3.16) | 0.92 (0.69-1.23) | 1.12 (0.62-2.01) | 0.47 | 0.42 | ||
Glu429Ala | 1.00 (ref) | 1.71 (0.90-3.26) | 1.18 (0.88-1.59) | 1.80 (1.05-3.09) | 0.53 | 0.78 | |||
MTHFS | Thr202Ala | 1.00 (ref) | 1.35 (0.88-2.08) | 1.12 (0.77-1.62) | 3.67 (1.16-11.56) | 0.21 | 0.15 | ||
MTR | Asp919Gly | 1.00 (ref) | 1.29 (0.77-2.14) | 1.19 (0.89-1.59) | 2.08 (1.09-3.97) | 0.25 | 0.48 | ||
MTRR | Ile22Met | 1.00 (ref) | 1.09 (0.44-2.72) | 0.89 (0.64-1.23) | 1.36 (0.81-2.30) | 0.70 | 0.51 | ||
Ser175Leu | 1.00 (ref) | 1.60 (0.85-2.99) | 1.13 (0.85-1.50) | 1.63 (0.95-2.81) | 0.71 | 0.81 | |||
Ser284Thr | 1.00 (ref) | 1.62 (1.06-2.47) | 1.82 (1.01-3.27) | 3.19 (0.43-23.78) | 0.12 | 0.94 | |||
Lys350Arg | 1.00 (ref) | 1.57 (1.00-2.45) | 1.13 (0.80-1.59) | 1.41 (0.56-3.55) | 0.77 | 0.67 | |||
Arg415Cys | 1.00 (ref) | 1.59 (1.05-2.41) | 2.01 (1.12-3.61) | 3.43 (0.46-25.57) | 0.06 | 0.95 | |||
His595Tyr | 1.00 (ref) | 1.60 (1.03-2.47) | 1.13 (0.79-1.61) | 0.96 (0.34-2.71) | 0.53 | 0.28 | |||
SHMT | Leu474Phe | 1.00 (ref) | 1.41 (0.82-2.45) | 0.88 (0.67-1.17) | 1.33 (0.74-2.40) | 0.67 | 0.87 | ||
TCN II | Pro259Arg | 1.00 (ref) | 1.86 (0.92-3.74) | 0.90 (0.67-1.23) | 1.11 (0.64-1.92) | 0.37 | 0.35 |
NOTE: ORs adjusted for family history of colorectal cancer, pack-years of smoking, postmenopausal hormone use (in women), body mass index, physical activity level, aspirin use, red meat intake, dietary methyl status, and total energy intake.
Methyl status was defined by energy-adjusted intakes. High methyl status—in women, ≥338.0 μg/d of total folate, ≥1.82 g/d of methionine, and <5 g/d of alcohol; and in men, ≥444.5 μg/d of total folate, ≥2.01 g/d of methionine, and <15 g/d of alcohol. Low methyl status—in women, <338.0 μg/d of total folate, <1.82 g/d of methionine, and ≥5 g/d of alcohol; and in men, <444.5 μg/d of total folate, <2.01 g/d of methionine, and ≥15 g/d of alcohol.
Pglobal is the global P value for the test of whether a SNP was associated with colorectal cancer risk within any subgroup defined by dietary methyl status.
Pinteraction is the P value for the test for multiplicative interaction between genotype and dietary methyl status.
Reference category is wt/wt genotype and intermediate/high dietary methyl status.
Because this analysis of interaction with dietary methyl status was based on grouping the variant carriers, and the main effect of MTHFR Ala222Val has been observed to behave in a recessive manner, we also conducted this analysis with MTHFR Ala222Val categorized as Val/Val versus Ala carriers, and observed no evidence of statistically significant multiplicative interaction (P for interaction = 0.78). Compared with Ala carriers with a high/intermediate methyl diet, the OR (95% CI) was 1.48 (0.95-2.29) for Ala carriers with a low methyl diet, 0.66 (0.43-1.04) for Val/Val individuals with a high/intermediate methyl diet, and 0.82 (0.27-2.52) for Val/Val individuals with a low methyl diet. Results were generally similar when dietary methyl status was based on the cumulative average intakes (results not shown). Also, similar findings were observed when we examined high alcohol intakes of ≥15 g/d for women and ≥30 g/d for men (P test for interaction = 0.37). Compared with Ala carriers with low alcohol intakes, the OR (95% CI) was 1.18 (0.77-1.81) for Ala carriers with high alcohol intakes, 0.60 (0.38-0.96) for Val/Val individuals with low alcohol intakes, and 1.23 (0.45-3.42) for Val/Val individuals with high alcohol intakes.
Vitamin B12 is transported by TCN II and is a cofactor to MTR, the function of which is related to MTRR and BHMT, thus, we examined whether total vitamin B12 intake (including dietary and supplemental sources) modified the associations for BHMT Arg239Gln, MTR Asp919Gly, TCN II Pro259Arg, and the six MTRR SNPs. For each of the nine SNPs, we did not observe statistically significant interactions between high versus low vitamin B12 intakes and genotype with P value for multiplicative interaction ranging from 0.06 for MTR Asp919Gly to 0.98 for MTRR Lys350Arg. The marginally significant interaction for MTR Asp919Gly suggested that compared to individuals with a high vitamin B12 intake and Asp/Asp genotype, the OR (95% CI) was 1.05 (0.75-1.47) for low vitamin B12 intakes and Asp/Asp genotype, 0.90 (0.59-1.37) for high vitamin B12 intakes and Gly carrier genotypes, and 1.59 (1.10-2.30) for low vitamin B12 intakes and Gly carrier genotypes.
Because vitamin B6 is a cofactor to SHMT and is involved in the conversion of homocysteine to cysteine, we examined whether total vitamin B6 modified associations for SHMT Leu474Phe as well as SNPs in genes related to homocysteine including BHMT Arg239Gln, MTR Asp919Gly, TCN II Pro259Arg, and the six MTRR SNPs. A statistically significant interaction was observed for high versus low vitamin B6 intakes and MTR Asp919Gly (P = 0.005). Compared to individuals with a high vitamin B6 intake and Asp/Asp genotype, the OR (95% CI) was 0.94 (0.67-1.32) for low vitamin B6 intakes and Asp/Asp genotype, 0.80 (0.52-1.21) for high vitamin B6 intakes and Gly carrier genotypes, and 1.64 (1.11-2.41) for low vitamin B6 intakes and Gly carrier genotypes. For vitamin B2, which is a cofactor to MTHFR, high versus low intakes did not modify associations for MTHFR Ala222Val or Glu429Ala (data not shown).
We conducted 276 tests for each pair-wise gene-gene combination, and at an α-level of 0.05, we observed statistically significant evidence of a joint effect between two SNPs for 20 of these tests, although most of the global P values were not extreme and were >0.01. Furthermore, most pair-wise combinations included BHMT Arg239Gln, MTRR Ser284Thr, or MTRR Arg415Cys and thus reflected the main effects that we observed for these three SNPs. Two pair-wise combinations, ATIC Thr116Ser and TCN II Pro259Arg (global P = 0.04) and MTR Asp919Gly and TCN II Pro259Arg (global P = 0.0008), did not include one of BHMT Arg239Gln, MTRR Ser284Thr, or MTRR Arg415Cys. Compared with individuals homozygous wild-type for both ATIC Thr116Ser and TCN II Pro259Arg, the OR (95% CI) was 1.39 (0.86-2.24) for a combination of ATIC Thr/Thr and TCN II Arg carrier, 1.69 (1.03-2.77) for ATIC Ser carrier and TCN II Pro/Pro, and 1.03 (0.65-1.61) for variant carriers of both ATIC Thr116Ser and TCN II Pro259Arg. Only the global P value for the joint association between MTR Asp919Gly and TCN II Pro259Arg (P = 0.0008) approached statistical significance based on a Bonferroni multiple comparisons corrected α-level of 0.0002. Compared with individuals homozygous wild-type for both MTR Asp919Gly and TCN II Pro259Arg, the OR (95% CI) was 0.55 (0.38-0.79) for MTR Asp/Asp combined with TCN II Arg carriers, 0.61 (0.37-1.01) for MTR Gly carriers combined with TCN II Pro/Pro, and 1.00 (0.68-1.47) for variant carriers of both MTR Asp919Gly and TCN II Pro259Arg.
Discussion
We analyzed 24 nonsynonymous SNPs in 13 genes that encode for enzymes involved in the one-carbon metabolism pathway. Our analyses were exploratory in nature as many of these SNPs, aside from MTHFR Ala222Val, have not been previously examined in relation to the risk of colorectal cancer or other health outcomes. Moreover, the functions of most of these SNPs have not been assessed, although the SNPs included here were selected because they were nonsynonymous and therefore more likely to alter protein function. In general, we did not find evidence of a strong main effect of any of the SNPs. There was some suggestion that the variant alleles of BHMT Arg239Gln, MTRR Ser284Thr, and MTRR Arg415Cys were associated with an increased risk of colorectal cancer. For MTHFR Ala222Val, Val/Val compared with Ala carrier genotypes was associated with a reduced risk of colorectal cancer. The observed associations did not greatly differ between men and women for most SNPs. Also, differences were not great according to colorectal site, although the association with MTHFR Ala222Val was weaker for rectal versus colon cancers. We did not observe that any of the SNPs were associated with colorectal cancer risk in subgroups of dietary methyl status or were modified by dietary methyl status. Similarly, there was little evidence that any SNP was jointly associated with colorectal cancer risk in combination with another SNP, except for the MTR Asp919Gly and TCN II Pro259Arg gene-gene combination.
Our findings support previous studies of the MTHFR Ala222Val SNP and colorectal cancer risk, which has been examined in 23 case-control (27-45) and nested case-control studies (10, 46-48). In addition, our finding that the inverse association was stronger for colon cancers versus rectal cancers was consistent with some (47, 48), although not all previous studies (38, 40, 46). Although relative risk estimates from previous studies have been varied, the findings have generally supported a reduced risk of colorectal cancer associated with the Val allele. A meta-analysis of 16 of these previous studies indicated a statistically significant 18% reduced risk of colorectal cancer for Val/Val versus Ala/Ala (11).
In some previous studies (10, 27, 31, 42, 43, 46-48), the reduced risk associated with the Val allele was stronger among individuals with methyl-sufficient diets, whereas individuals with methyl-deficient diets did not experience a similar reduced risk. This reduced risk due to the Val form of MTHFR, which is specific to individuals with a methyl-sufficient diet, has been suggested to be due to an enhanced pool of nucleotides for DNA synthesis and repair resulting from the reduced enzyme activity and accumulation of 5,10-methylenetetrahydroflate (10). We did not observe a significant difference in association for Val/Val versus Ala/Ala by dietary methyl status. This finding probably reflects the relatively high dietary methyl status of individuals in the NHS and HPFS. Mean folate intakes among both men and women exceeded the recommended intake value of 400 μg/d. Furthermore, folate intakes increased for the individuals included in this study due to the folate fortification program in the U.S. As well, alcohol intakes were generally low, particularly among women (less than three drinks per week). When we examined this interaction according to more extreme alcohol intakes, a reduced risk of colorectal cancer for Val/Val versus Ala/Ala was observed among individuals with low alcohol intakes but not with high alcohol intakes, however, this interaction was not statistically significant.
Chance may account for our results for the MTRR SNPs Ser284Thr and Arg415Cys, which were in strong linkage disequilibrium in our study, and for BHMT Arg239Gln. However, it is possible that the observed associations reflect the influence of these genes on DNA methylation. Both BHMT and MTRR are involved in maintaining cellular levels of methionine; BHMT catalyzes the re-methylation of homocysteine to methionine, predominantly in the liver and kidney (49), whereas MTRR activates MTR, which also catalyzes the re-methylation of homocysteine to methionine in various tissues. Possible functions of the MTRR Ser284Thr and Arg415Cys SNPs and associations with disease have not been previously reported. Statistically nonsignificant reduced risks of cardiovascular disease (50, 51) and spina bifida (52) associated with Gln/Gln versus Arg/Arg at BHMT codon 239 have been suggested among three previous studies. However, another study observed no association with spina bifida (53), and Arg239Gln has not been associated with altered BHMT activity (51) or homocysteine levels (50). Although the evidence for an association between BHMT Arg239Gln and homocysteine-related diseases is weak, the suggested reduced risks of cardiovascular disease and spina bifida is in contrast to the increased risk of colorectal cancer due to the Gln allele that we observed. This possible difference in the direction of associations may reflect the different mechanisms involved in the development of these different outcomes.
Other SNPs, including MTHFR Glu429Ala (31, 32, 34, 35, 37, 41, 42, 45, 47, 54), MTR Asp919Gly (31, 37, 38, 43, 55, 56), and MTRR Ile22Met (31, 34, 45), which have been inconsistently associated with colorectal cancer risk among a limited number of previous studies were not associated with risk in our study. There was some indication that the variant allele of MTHFR Glu429Ala may be associated with an increased risk of colorectal cancer among women but not men in our study. Results from the few previous studies of MTHFR Glu429Ala and colorectal cancer risk have been inconsistent, with a statistically significant reduced risk associated with Ala/Ala versus Glu/Glu having been observed in just one study (32). The point estimates from other studies have suggested reduced (34, 39, 45, 47, 54), null (31, 42), and increased (35, 37, 41) risks of colorectal cancer for Ala/Ala versus Glu/Glu. In a meta-analysis of eight previous studies, Ala/Ala versus Glu/Glu was associated with a nonsignificant 17% reduction in colorectal cancer risk, however, statistically significant heterogeneity between studies was observed (11). The inconsistent results for MTHFR Glu429Ala suggest that this SNP is not strongly associated with the risk of colorectal cancer or may be modified by dietary factors. We also observed no associations with FOLH His475Tyr, MTHFD1 Arg653Gln, and SHMT Leu474Phe, which is consistent with the results from a previous study of these SNPs and colorectal cancer risk in men (57).
Chance may also account for the observed joint association between MTR Asp919Gly and TCN II Pro259Arg. Alternatively, this joint association may correspond to the relationship of both SNPs to vitamin B12. Vitamin B12 is a cofactor in the re-methylation of homocysteine to methionine catalyzed by MTR (13), and is transported in the plasma for cellular uptake by TCN II (58). Although TCN II Pro259Arg has not been examined in association with colorectal cancer, previous studies have suggested that the variant allele of TCN II Pro259Arg may reduce the binding of TCN II to vitamin B12 and alter the cellular uptake of vitamin B12 (59, 60). MTR Asp919Gly has been inconsistently associated with colorectal cancer risk (31, 37, 38, 43, 55, 56), with two studies reporting a statistically significant reduced risk for Gly/Gly versus Asp/Asp (38, 55). Other studies have suggested nonsignificant reduced, null, and increased risks. Our results suggest that Gly carriers versus Asp/Asp at MTR codon 919 is associated with a reduced colorectal cancer risk among individuals that are homozygous wild-type for TCN II Pro259Arg, who presumably have efficient vitamin B12 binding and transport, whereas Gly carriers versus Asp/Asp may possibly increase risk among TCN II Pro259Arg variant carriers, who may have less efficient vitamin B12 transport. This finding is consistent with the marginally significant interaction we observed for MTR Asp919Gly and vitamin B12 intakes which suggested that Gly carriers versus Asp/Asp may increase colorectal cancer risk among individuals with low vitamin B12 intakes.
For this analysis, we pooled men and women from two similar studies, the NHS and HPFS, which are both large prospective cohort studies of female and male health professionals that have used similar methods for participant recruitment, blood collection, diet assessment, and follow-up. Cases and their matched controls were selected from the same underlying population, thus, the potential for selection bias was not great. In addition, 97% of the study population was of Caucasian ancestry, suggesting that the potential for bias due to population stratification was minimal.
We may have missed a possible association with a SNP or an interaction with dietary methyl status because of the relatively high methyl status of individuals in our study. Ideally, we would have been able to account for changes in folate intake due to the folate fortification program by examining each SNP pre- and post-fortification, however, most of the cases occurred prior to fortification, thus the sample size was limited for such an analysis. Statistical power was also limited in our analyses by colorectal site and of modification by dietary methyl status. We did not consider models in which disease risk depends on combinations of alleles at three or more SNPs. There are 2,024 three-SNP combinations alone, thus, given our limited sample size, we have little power to reliably detect these more complex combinations while properly adjusting for the model search and selection process. Alternatively, the number of potential models could be limited using prior biological knowledge. A better understanding of the relationship between one-carbon metabolism and colorectal cancer risk may be achieved by using a pathway approach that incorporates data on the biochemical interrelationships within the one-carbon metabolism pathway. When these biochemical data are available (61), along with functional information for the SNPs included here, we will be able to apply this information to our data.
We acknowledge that we conducted a large number of statistical tests to examine these 24 SNPs, most of which have never been examined in association with the risk of colorectal cancer previously. However, we hypothesized that these SNPs would potentially be associated with colorectal cancer risk as they were nonsynonymous and could therefore potentially have a function, although the PolyPhen and SIFT predictions suggested that the majority of the amino acid substitutions would be benign. Nonetheless, we did not observe any strong associations, thus, our findings for these previously unexamined SNPs can generally be interpreted as hypothesis-generating.
In summary, our findings corroborate previous studies of the MTHFR Ala222Val SNP and indicate a reduced risk of colorectal cancer associated with the Val/Val genotype among this population with a methyl-sufficient diet. Our results suggest that the BHMT Arg239Gln, MTRR Ser284Thr, and MTRR Arg415Cys SNPs may also be associated with colorectal cancer risk and that MTR Asp919Gly and TCN II Pro259Arg may be jointly associated with colorectal cancer risk. Interestingly, MTHFR, BHMT, MTRR, MTR, and TCN II are all related to methionine synthesis, suggesting an important role of DNA methylation in colorectal cancer risk (62). Replication of these findings in other study populations is warranted in order to confirm whether these SNPs do in fact play a role in colorectal carcinogenesis.
Grant support: NIH grants U54-CA100971, P01-CA087969, and P01-CA055075, and The National Colorectal Cancer Research Alliance of the Entertainment Industry Foundation. A. Koushik was supported by a fellowship from the Canadian Institutes of Health Research.
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.
Acknowledgments
We are grateful to the men and women of the Nurses' Health Study and the Health Professionals Follow-up Study for their participation, and to Hardeep Ranu, Patrice Soule, and Craig Labadie for technical assistance.