Background: A potential dual role of folate in colorectal cancer (CRC) is currently subject to debate. We investigate the associations between plasma folate, several relevant folate-related polymorphisms, and CRC risk within the large European Prospective Investigation into Cancer and Nutrition cohort.

Methods: In this nested case-control study, 1,367 incident CRC cases were matched to 2,325 controls for study center, age, and sex. Risk ratios (RR) were estimated with conditional logistic regression and adjusted for smoking, education, physical activity, and intake of alcohol and fiber.

Results: Overall analyses did not reveal associations of plasma folate with CRC. The RR (95% confidence interval; Ptrend) for the fifth versus the first quintile of folate status was 0.94 (0.74-1.20; 0.44). The polymorphisms MTHFR677C→T, MTHFR1298A→C, MTR2756A→G, MTRR66A→G, and MTHFD11958G→A were not associated with CRC risk. However, in individuals with the lowest plasma folate concentrations, the MTHFR 677TT genotype showed a statistically nonsignificant increased CRC risk [RR (95% CI; Ptrend) TT versus CC = 1.39 (0.87-2.21); 0.12], whereas those with the highest folate concentrations showed a nonsignificant decreased CRC risk [RR TT versus CC = 0.74 (0.39-1.37); 0.34]. The SLC19A180G→A showed a positive association with CRC risk [RR AA versus GG 1.30 (1.06-1.59); <0.01].

Conclusions: This large European prospective multicenter study did not show an association of CRC risk with plasma folate status nor with MTHFR polymorphisms.

Impact: Findings of the present study tend to weaken the evidence that folate plays an important role in CRC carcinogenesis. However, larger sample sizes are needed to adequately address potential gene-environment interactions. Cancer Epidemiol Biomarkers Prev; 19(5); 1328–40. ©2010 AACR.

It has been proposed that folate status may affect colorectal cancer (CRC) risk because of the role of folate in the synthesis of nucleic acid and in DNA methylation (1). Although not consistent, the majority of studies on folate intake, as summarized in two meta-analyses (2, 3), indicate a 20% to 40% CRC risk reduction in individuals with the highest folate intake compared with those with the lowest folate intake. The Nurses Health Study showed no relation between dietary folate and CRC risk, but a 75% CRC risk reduction was observed in women using multivitamin supplements with ≥400 μg folic acid for 15 years or longer compared with those taking them <15 years or never (4). However, a temporally increased CRC incidence has been reported to coincide with mandatory folic acid supplementation in the United States and Canada (5). In addition, explorative analyses of the first randomized controlled intervention trial of folic acid for the secondary prevention of colorectal polyps revealed that supplementation was associated with a 67% increased risk in advanced lesions during the last part of a follow-up period of 6 to 8 years (6). As a result of these contradictory findings, a potential dual role of folate has been hypothesized (1, 7, 8), that is, that folate deficiency in normal colorectal tissues may promote carcinogenesis, whereas folate deficiency could have an inhibitory effect on the progression of established neoplasms (1).

Folate metabolism involves multiple enzymes (9) that provide methyl groups to various reactions. The trifunctional enzyme methylenetetrahydrofolate dehydrogenase/methenyltetrahydrofolate cyclohydrolase/formyltetrahydrofolate synthetase (MTHFD1) catalyses the conversion from tetrahydrofolate to the corresponding 10-formyl, 5,10-methenyl, and 5,10-methylene forms, which are cofactors for de novo purine and pyrimidine and subsequent DNA synthesis (10).The reduced folate carrier 1 (SLC19A1) plays a role in cellular uptake of 5-methyltetrahydrofolate (11). Methionine synthase reductase (MTRR) is required for activation of methionine synthase (MTR; refs. 12-15), which requires 5-methyltetrahydrofolate as a methyl donor for the remethylation of homocysteine to methionine to provides methylgroups for, e.g., DNA methylation. Regeneration of 5-methyltetrahydrofolate from tetrahydrofolate is catalyzed by the enzyme methylenetetrahydrofolate reductase (MTHFR; Fig. 1; ref. 16). Among the one carbon–related single nucleotide polymorphisms (SNP) mentioned above, only MTHFR 677C→T has been shown to significantly and consistently affect life-long folate and homocysteine status, whereas data for the other SNPs are sparse and inconsistent (17-19). The 677C→T and 1298A→C polymorphisms in the methylenetetrahydrofolate (MTHFR) gene have been studied in greatest detail in relation to CRC risk. Two meta-analyses indicate inverse associations between 677TT and 1298CC genotypes, and CRC risk (20, 21). In contrast, the effects of genetic variants of MTR (22-24), MTRR (18, 19, 25), MTHFD1 (26, 27) and SLC19A1 (9, 28) on CRC risk have been less studied and show inconsistent associations. Furthermore, the TT variant of the MTHFR 677C→T SNP, compared with the CC or CT variants, is either a risk factor for CRC (25, 29-31) or colorectal adenomas (32, 33) at low folate concentrations and protective at high folate concentrations, whereas other studies did not show such a dual effect (22, 34-37). In addition to an interaction of MTHFR genotype with folate status, there is also some evidence for an interaction with alcohol consumption (29, 38).

Figure 1.

Key pathways of the folate metabolism. CH2THF, methylenetetrahydrofolate; CH3THF, methyltetrahydrofolate; Hcy, homocysteine; Met, methionine; MTHFD1, provision of one-carbon units for purine and pyrimidine synthesis; MTHFR, provision of 5-methylfolate for homocysteine remethylation; MTR, remethylation of homocysteine to methionine; MTRR, activation of MTR; SLC19A1, reduced folate carrier-1 (transport and binding of folate); THF, tetrahydrofolate.

Figure 1.

Key pathways of the folate metabolism. CH2THF, methylenetetrahydrofolate; CH3THF, methyltetrahydrofolate; Hcy, homocysteine; Met, methionine; MTHFD1, provision of one-carbon units for purine and pyrimidine synthesis; MTHFR, provision of 5-methylfolate for homocysteine remethylation; MTR, remethylation of homocysteine to methionine; MTRR, activation of MTR; SLC19A1, reduced folate carrier-1 (transport and binding of folate); THF, tetrahydrofolate.

Close modal

The associations between plasma folate and CRC risk has been investigated in several previous studies (30, 37, 39-42). However, the associations were inconsistent. Therefore, we investigated the association between plasma folate status and CRC in a very large-scale prospective cohort study within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. We also assessed the potential interaction between plasma folate status, SNPs related to one-carbon metabolism, and alcohol consumption.

Study population and collection of blood samples

The design and methods of the EPIC study have been previously described in detail (43). Briefly, the EPIC cohort recruited participants from 23 centers in 10 European countries (Denmark, France, Greece, Germany, Italy, the Netherlands, Norway, Spain, Sweden, and United Kingdom). Between 1992 and 1998, country-specific dietary questionnaires, standardized life-style and personal history questionnaires, and anthropometric data were collected from all the cohort members, and a blood sample was taken from 80% of the participants.

In each of the recruitment centers, both fasting or nonfasting blood samples of at least 30 mL were drawn from those participants who provided a blood sample and stored at 5°C to 10°C, protected from light, and transported to local laboratories for processing and aliquoting as previously described (43, 44). The only exceptions are the EPIC-Oxford and EPIC-Norway centers where blood samples were collected from a network of general practitioners (Oxford and Norway) and health conscious people (Oxford), and transported in the mail to a central laboratory in Norfolk (Oxford) and Tromsø (Norway), respectively. The whole blood samples were protected from light, but exposed to ambient temperatures for up to 48 hours. As it is possible that some B vitamins might be partly degraded by such handling (45), all EPIC-Oxford (55 cases and 107 controls) and EPIC-Norway (5 cases and 9 controls) samples were excluded from the present analyses.

In all countries, except Denmark and Sweden, blood was separated into 0.5-mL fractions (serum, plasma, red cells, and buffy coat for DNA extraction). Each fraction was placed into plastic CBS straws, which were heat sealed and stored in liquid nitrogen (−196°C). One half of all aliquots were stored at the local study center and the other half in the central EPIC biorepository at the IARC (Lyon, France). In Denmark, blood fraction aliquots of 1.0 mL were stored locally at −150°C under nitrogen vapor. In Sweden, samples were stored in −80°C freezers.

This study was approved by the Ethical Review Board of the IARC and those of all EPIC centers. All EPIC participants have provided written consent for the use of their blood samples and all data.

Follow-up for cancer incidence

In EPIC, follow-up is based on population cancer registries (Denmark, Italy, the Netherlands, Norway, Spain, Sweden, and the United Kingdom) or through a combination of methods, including linkage with health insurance records, contact with cancer and pathology registries, and active contact of study subjects or next of kin (France, Germany, and Greece). Follow-up began at the date of enrollment and ended at the date of CRC diagnosis. Follow-up was closed between 1999 and 2004. Depending on study center, complete follow-up for the centers using record linkage with cancer registries, data were available until December 31, 1999 (Turin), June 30, 2000 (Bilthoven), December 31, 2000 (Asturias, Murcia), December 31, 2001 (Florence, Varese, Ragusa, Naples, Granada, Navarra, San Sebastian, Malmö, and United Kingdom), December 31, 2002 (Denmark and Umeå), and June 30, 2003 (Utrecht). For the centers using active follow-up, the last contact dates were June 30, 2002 (France), September 11, 2002 (Greece), December 6, 2003 (Heidelberg), and March 11, 2004 (Potsdam).

Indicators of data quality of all cancer registries in the study are considered to be of good quality (46). In France, Germany, and Greece, self-reported cancer cases through active follow-up were verified by physicians and pathology reports. In these countries, pathology reports are available for at least 95% of cases and are confirmed at least 95% of self-reported cancers for other cancer sites, indicating a well-functioning case identification system (47-50). In the present study, histologic confirmation of CRC was available for 93%, whereas 6% was diagnosed through clinical observation, cytology, or autopsy; information on 1% was missing. Current information about the efficacy of follow-up until 2007 shows that 1.57% of the total population is lost to follow-up, from which 0.18% was reluctant to continue to participate, 0.80% emigrated to another region or country, and the remaining 0.57% are lost to follow-up for unknown reasons (51), implying even lower rates for follow-up until 2004 in the present study.

Nested case-control study design and selection of study subjects

Case ascertainment and selection

For the present study, colon cancers were defined as tumors in the cecum, appendix, ascending colon, hepatic flexure, transverse colon, splenic flexure, and descending and sigmoid colon (C18.0-C18.7 as per the 10th Revision of the International Statistical Classification of Diseases, Injury and Causes of Death), as well as tumors that were overlapping or unspecified (C18.8 and C18.9). Cancers of the rectum were defined as tumors occurring at the recto-sigmoid junction (C19) or rectum (C20). CRC is defined as a combination of the colon and rectal cancer cases. The present study includes a total of 1,367 incident CRC cases (colon n = 850; rectal n = 517). The distribution of cases (colon/rectal) by country was as follows: 206/172 for Denmark, 100/84 for Sweden, 30/3 for France, 14/13 for Greece, 98/61 for Germany, 106/43 for Italy, 102/49 for the Netherlands, 80/43 for Spain, and 114/49 for United Kingdom. Ninety-six percent (n = 1,299) of cancer cases were classified as adenocarcinomas, whereas the remaining 4% of the tumors were classified as carcinomas or unspecified forms.

Control selection

For each identified cancer case, control cohort members with available blood samples were randomly selected from all cohort members with available blood samples who were alive and free of cancer (except nonmelanoma skin cancer) at the time of diagnosis of the index case. Controls were matched to cases by gender, age group (±2.5 y), and study center (to account of center-specific differences in questionnaire design, blood collection procedures, etc.). An exception were Danish cases (n = 378) and controls (n = 373) who were post hoc matched using the “greedy” algorithm, a macro (gmatch) provided by the Mayo Clinic College of Medicine (52, 53) to be run in SAS. Cases and controls were exactly matched for sex and study center, and with a maximum age difference of 5 years. The mean (range) difference in age between cases and controls within each caseset was −1.03 (−5.0 to 4.9) years.

Laboratory measurements

Plasma folate was determined by a Lactobacillus casei microbiological assay, adapted to a microtiter plate format and carried out by a robotic workstation (Micro-lab AT plus 2; Hamilton Bonaduz AG; ref. 54), and plasma total homocysteine (tHcy) was determined by a method based on methylchloroformate derivatization and gas chromatography-mass spectrometry (55). In total, 1.89% of the samples could not be analyzed due to, e.g., insufficient sample volumes. Within- and between-day coefficients of variation for folate and tHcy were 3% to 20% (54) and 6% to 22% (55), respectively.

The SNPs of genes related to one-carbon metabolism were determined by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (56). These included MTHFR (MTHFR 677C→T; rs#1801133 and MTHFR 1298A→C; rs#1801131), MTR (MTR 2756A→G; rs#1805087), MTR reductase (MTRR; MTRR 66A→G; rs#1801394), MTHFD1 (MTHFD1 1958G→A; rs#2236225), and reduced folate carrier-1 (SLC19A1 80G→A; rs#1051266).

Statistical methods

Differences between cases and controls in median baseline covariates and differences in median folate and tHcy concentrations for selected characteristics were assessed by Mann-Whitney U tests, whereas categorical variable differences were assessed by χ2 tests.

Relative risks (RR) and 95% confidence intervals (95% CI) for CRC in relation to plasma folate and tHcy were calculated by conditional logistic regression using the SAS LOGISTIC procedure (SAS statistical software, version 9.1, SAS Institute), stratified by the case-control set. In our study, the RR indicated the incidence rate ratio, which is reflected by the odds ratio calculated from conditional logistic regression (57). The RRs for CRC risk were examined by quintile categories with cutoff points based on the distribution of folate and homocysteine in all 2,325 controls combined. Because excluding the 4% (n = 61) of cases with other histologies than adenocarcinoma did not modify any associations, we included them in the statistical analyses. Potential confounders were investigated, including smoking status (never, former, current, and missing), alcohol consumption (continuous), dietary fiber (continuous), intake of red and processed meat (continuous), physical activity (inactive, moderately inactive, moderately active, and active), educational level (none, primary school completed, technical/professional school, secondary school, university degree, and not specified), and body mass index (kg/m2). Although none of these variables altered the risk estimates as obtained by the matched analyses, we present matched analyses that were further adjusted for these covariates to allow comparisons to previous publications. Likelihood ratio tests were used to assess linear trends in RRs across the categories using values for quintile categories as the quantitative score of exposure. All models were run separately and tested for effect modification for the anatomical site of cancer (colon versus rectal), European region [North (Denmark, Sweden) versus Central (France, United Kingdom, the Netherlands, and Germany) versus South (Italy, Spain, and Greece)], time from blood donation to cancer diagnosis [≤3.6 (median follow-up time) y versus >3.6 y)], age (≤60 y versus >60 y), sex, and alcohol intake (0-30 g/d versus ≥30 g/d). Effect modification was tested by adding the product term of folate and potential effect modifiers in the model. All statistical tests were two tailed and P < 0.05 was considered statistically significant.

The associations between the polymorphisms and CRC risk were studied with conditional logistic regression. The risk estimates were calculated with the wild-type as the reference category. A trend test with equally spaced integer weights for the genotypes were used to summarize the effect of each polymorphism. Effect modification of the SNP-CRC associations by folate concentrations and alcohol consumption were studied with conditional logistic regression, but by stratifying on country instead of the matched sets and with age and sex as covariates.

Characteristics of cases and controls

The present study investigates 1,367 cancer cases and 2,325 matched controls. The sex distribution and mean age at recruitment were comparable among cases and controls. The median (range) follow up time between blood donation and CRC diagnosis was 3.6 (0.0-10.3) years. Median folate concentrations in cases were slightly lower compared with their matched controls (Pdifference = 0.08), whereas no differences in tHcy concentrations were observed between cases and controls (Table 1).

Table 1.

Characteristics of cohort members

CasesControlsPdifference
No. of individuals 1,367 2,325  
Sex, female, n (%) 700 (51) 1,215 (53) 0.54 
Mean age (y; min-max)    
    At recruitment 58.9 (30.1-76.9) 58.7 (30.0-76.6) 0.37 
    At blood donation 59.1 (36.8-77.0) 58.9 (36.6-76.6) 0.42 
    At diagnosis 62.8 (37.7-81.2) N.a.  
    Lag time 3.6 (0.01-10.3) N.a.  
Smoking status, n (%)   0.02 
    Never 561 (41) 1,026 (43)  
    Former 451 (33) 775 (33)  
    Smoker 346 (25) 511 (22)  
Mean/median (P5-P95)    
    Folate (nmol/L) 13.6/10.9 (5.1-32.1) 14.2/11.3 (4.9-34.0) 0.08 
    tHcy (μmol/L) 10.2/9.5 (6.2-16.2) 10.3/9.6 (6.3-16.4) 0.33 
CasesControlsPdifference
No. of individuals 1,367 2,325  
Sex, female, n (%) 700 (51) 1,215 (53) 0.54 
Mean age (y; min-max)    
    At recruitment 58.9 (30.1-76.9) 58.7 (30.0-76.6) 0.37 
    At blood donation 59.1 (36.8-77.0) 58.9 (36.6-76.6) 0.42 
    At diagnosis 62.8 (37.7-81.2) N.a.  
    Lag time 3.6 (0.01-10.3) N.a.  
Smoking status, n (%)   0.02 
    Never 561 (41) 1,026 (43)  
    Former 451 (33) 775 (33)  
    Smoker 346 (25) 511 (22)  
Mean/median (P5-P95)    
    Folate (nmol/L) 13.6/10.9 (5.1-32.1) 14.2/11.3 (4.9-34.0) 0.08 
    tHcy (μmol/L) 10.2/9.5 (6.2-16.2) 10.3/9.6 (6.3-16.4) 0.33 

NOTE: Differences in plasma concentrations were assessed by Mann-Whitney U tests, whereas categorical variable differences were assessed by χ2 tests.

Abbreviation: N.a., not applicable

Data integrity

Table 2 shows folate and tHcy concentrations among the 2,325 control cohort members by sex; age; smoking status; European region; alcohol intake; and the SNPs MTHFR 677C→T, MTHFR 1298A→C, MTR 2756A→G, MTRR 66A→G, MTHFD1 1958G→A, and SLC19A1 80G→A. Folate concentrations were lower in males, individuals younger than 60 years, smokers, those living in Sweden and Denmark, and in those with the homozygote variant of the MTHFR 677C→T polymorphism. tHcy concentrations were higher in males, individuals older than 60 years, smokers, and in those with the homozygote variant of the MTHFR 677C→T and the homozygote wild-type of the MTHFR 1298A→C polymorphisms (Pall differences < 0.01; Table 2). Plasma folate and tHcy concentrations correlated strongly within each European region after adjustment for age, sex, and study center, with Spearman correlation coefficients of −0.43 in Northern, −0.35 in Central, and −0.32 in Southern European countries (Pall correlations < 0.0001).

Table 2.

Folate and homocysteine concentrations [mean/median (P5-P95)] by selected characteristics in control cohort members (n = 2,320)

nFolate (nmol/L)tHcy (μmol/L)
Sex Male 1,108 13.4/11.0 (4.7-31.6) 10.9/10.1 (6.7-17.3) 
Female 1,212 14.9/11.7 (5.3-37.0) 9.8/9.1 (6.0-15.2) 
Pdifference* <0.01 <0.01 
Age <60 y 1,277 13.3/11.1 (4.8-30.0) 9.7/8.9 (6.1-15.5) 
≥60 y 1,043 15.2/11.7 (5.2-38.6) 11.0/10.4 (6.8-17.2) 
Pdifference*  <0.01 <0.01 
Smoking status Never 1,024 15.2/12.3 (5.5-36.6) 9.9/9.4 (6.2-15.5) 
Former 774 14.6/11.6 (5.4-34.6) 10.3/9.8 (6.4-15.8) 
Current 509 11.5/9.3 (3.9-27.8) 11.1/9.8 (6.3-19.7) 
Unknown 13 13.6/12.2 (8.9-23.1) 9.3/9.6 (6.4-13.6) 
Ptrend  <0.01 <0.01 
European region North§ 736 12.0/9.6 (4.0-27.9) 10.4/9.6 (6.3-17.1) 
Central 997 15.8/12.5 (5.7-38.1) 10.4/9.8 (6.5-16.1) 
South 587 14.2/12.4 (5.2-29.2) 10.0/8.9 (5.9-15.8) 
Pdifference  <0.01 0.11 
Alcohol intake (g/d) Abstainers intake 166 15.1/12.7 (4.5-36.8) 9.9/8.9 (5.9-16.1) 
1-30 1,783 14.2/11.3 (4.9-34.0) 10.3/9.6 (6.3-16.3) 
≥30 371 13.7/11.3 (5.2-32.7) 10.8/9.6 (6.4-17.0) 
Pdifference*  0.33 0.03 
MTHFR 677 CC 1,131 14.4/11.5 (5.2-33.4) 10.1/9.5 (6.3-15.6) 
CT 933 13.9/11.3 (4.9-32.8) 10.2/9.5 (6.4-15.7) 
TT 254 13.2/9.8 (4.2-37.2) 11.9/10.4 (6.5-22.9) 
Ptrend  0.01 <0.01 
MTHFR 1298 AA 1,002 13.6/10.9 (4.8-34.5) 10.5/9.7 (6.4-17.1) 
AC 950 14.2/11.5 (5.1-32.6) 10.3/9.6 (6.3-15.7) 
CC 236 14.9/11.2 (5.1-34.5) 10.1/9.3 (6.4-16.4) 
Ptrend  0.08 0.01 
MTR 2756 AA 1,395 14.2/11.5 (5.0-34.6) 10.4/9.7 (6.3-16.5) 
AG 710 13.6/10.8 (4.9-31.6) 10.4/9.5 (6.3-16.6) 
GG 82 13.5/10.3 (4.7-30.6) 9.9/9.2 (6.4-14.2) 
Ptrend  0.24 0.48 
MTRR 66 AA 404 14.5/11.3 (4.8-36.6) 10.0/9.3 (6.4-16.4) 
AG 1,025 13.6/11.1 (4.9-30.6) 10.3/9.6 (6.3-15.8) 
GG 603 13.9/11.3 (5.0-32.3) 10.5/9.7 (6.3-17.0) 
Ptrend  0.92 0.06 
MTHFD1 1958 GG 679 13.7/11.3 (4.7-31.0) 10.4/9.6 (6.3-16.9) 
GA 1,061 14.4/11.1 (5.0-35.6) 10.3/9.6 (6.3-15.9) 
AA 448 13.4/11.1 (5.0-30.1) 10.6/9.8 (6.6-16.6) 
Ptrend  0.41 0.71 
SLC19A1 80 GG 743 13.8/11.3 (5.1-32.0) 10.4/9.5 (6.3-16.4) 
GA 1,066 14.4/11.3 (4.8-35.5) 10.4/9.8 (6.4-16.3) 
AA 378 13.1/10.8 (4.8-28.7) 10.2/9.5 (6.1-17.7) 
Ptrend  0.23 0.12 
nFolate (nmol/L)tHcy (μmol/L)
Sex Male 1,108 13.4/11.0 (4.7-31.6) 10.9/10.1 (6.7-17.3) 
Female 1,212 14.9/11.7 (5.3-37.0) 9.8/9.1 (6.0-15.2) 
Pdifference* <0.01 <0.01 
Age <60 y 1,277 13.3/11.1 (4.8-30.0) 9.7/8.9 (6.1-15.5) 
≥60 y 1,043 15.2/11.7 (5.2-38.6) 11.0/10.4 (6.8-17.2) 
Pdifference*  <0.01 <0.01 
Smoking status Never 1,024 15.2/12.3 (5.5-36.6) 9.9/9.4 (6.2-15.5) 
Former 774 14.6/11.6 (5.4-34.6) 10.3/9.8 (6.4-15.8) 
Current 509 11.5/9.3 (3.9-27.8) 11.1/9.8 (6.3-19.7) 
Unknown 13 13.6/12.2 (8.9-23.1) 9.3/9.6 (6.4-13.6) 
Ptrend  <0.01 <0.01 
European region North§ 736 12.0/9.6 (4.0-27.9) 10.4/9.6 (6.3-17.1) 
Central 997 15.8/12.5 (5.7-38.1) 10.4/9.8 (6.5-16.1) 
South 587 14.2/12.4 (5.2-29.2) 10.0/8.9 (5.9-15.8) 
Pdifference  <0.01 0.11 
Alcohol intake (g/d) Abstainers intake 166 15.1/12.7 (4.5-36.8) 9.9/8.9 (5.9-16.1) 
1-30 1,783 14.2/11.3 (4.9-34.0) 10.3/9.6 (6.3-16.3) 
≥30 371 13.7/11.3 (5.2-32.7) 10.8/9.6 (6.4-17.0) 
Pdifference*  0.33 0.03 
MTHFR 677 CC 1,131 14.4/11.5 (5.2-33.4) 10.1/9.5 (6.3-15.6) 
CT 933 13.9/11.3 (4.9-32.8) 10.2/9.5 (6.4-15.7) 
TT 254 13.2/9.8 (4.2-37.2) 11.9/10.4 (6.5-22.9) 
Ptrend  0.01 <0.01 
MTHFR 1298 AA 1,002 13.6/10.9 (4.8-34.5) 10.5/9.7 (6.4-17.1) 
AC 950 14.2/11.5 (5.1-32.6) 10.3/9.6 (6.3-15.7) 
CC 236 14.9/11.2 (5.1-34.5) 10.1/9.3 (6.4-16.4) 
Ptrend  0.08 0.01 
MTR 2756 AA 1,395 14.2/11.5 (5.0-34.6) 10.4/9.7 (6.3-16.5) 
AG 710 13.6/10.8 (4.9-31.6) 10.4/9.5 (6.3-16.6) 
GG 82 13.5/10.3 (4.7-30.6) 9.9/9.2 (6.4-14.2) 
Ptrend  0.24 0.48 
MTRR 66 AA 404 14.5/11.3 (4.8-36.6) 10.0/9.3 (6.4-16.4) 
AG 1,025 13.6/11.1 (4.9-30.6) 10.3/9.6 (6.3-15.8) 
GG 603 13.9/11.3 (5.0-32.3) 10.5/9.7 (6.3-17.0) 
Ptrend  0.92 0.06 
MTHFD1 1958 GG 679 13.7/11.3 (4.7-31.0) 10.4/9.6 (6.3-16.9) 
GA 1,061 14.4/11.1 (5.0-35.6) 10.3/9.6 (6.3-15.9) 
AA 448 13.4/11.1 (5.0-30.1) 10.6/9.8 (6.6-16.6) 
Ptrend  0.41 0.71 
SLC19A1 80 GG 743 13.8/11.3 (5.1-32.0) 10.4/9.5 (6.3-16.4) 
GA 1,066 14.4/11.3 (4.8-35.5) 10.4/9.8 (6.4-16.3) 
AA 378 13.1/10.8 (4.8-28.7) 10.2/9.5 (6.1-17.7) 
Ptrend  0.23 0.12 

*Pdifference (two sided) calculated by Mann-Whitney U test; abstainers were excluded from statistical analyses on alcohol consumption.

Pdifference (two sided) calculated by Kruskal-Wallis test; category unknown was excluded from statistical analyses smoking status.

Category unknown not included in the test for trend.

§North: Sweden and Denmark; Central: France, United Kingdom, the Netherlands, and Germany; South: Italy, Spain, and Greece.

Ptrend (two sided) calculated by regression models.

Associations of folate with CRC

Overall analyses do not show an association of plasma folate with CRC risk, nor after stratifying according to age, sex, alcohol intake, and time between blood donation and cancer diagnoses (Table 3). Cancer risk for tumors in the colon or the rectum was similar compared with overall CRC risk (data not shown). However, individuals living in Northern European countries showed an inverse association between plasma folate and rectal cancer risk, with an RR (95% CI; Ptrend) of the highest versus the lowest folate concentrations of 0.56 (0.29-1.09; 0.04; data not shown). tHcy concentrations were not associated with cancer risk in the colorectum, colon, or rectum for any of the subgroup analyses (data not shown).

Table 3.

Adjusted RRs (95% CI) for CRC by quintiles of plasma folate concentrations

N case/controlQ1Q2: 7.6-9.9Q3: 9.9-13.0Q4: 13.0-18.3Q5: >18.3PtrendPinteraction
Matched analyses Overall 1,367/2,318 0.97 (0.78-1.20) 1.06 (0.86-1.31) 0.87 (0.69-1.09) 0.91 (0.73-1.14) 0.29  
Matched plus covariate-adjusted analyses Overall 1,327/2,239 1.02 (0.82-1.27) 1.08 (0.87-1.35) 0.92 (0.72-1.16) 0.94 (0.74-1.20) 0.44  
    Sex Males 644/1,060 0.99 (0.72-1.37) 1.07 (0.77-1.47) 0.83 (0.58-1.18) 0.86 (0.60-1.23) 0.26  
Females 683/1,179 1.06 (0.78-1.44) 1.10 (0.81-1.50) 1.00 (0.73-1.39) 1.00 (0.72-1.39) 0.90 0.50 
    Age* ≤60 y 706/1,185 0.97 (0.72-1.31) 0.97 (0.72-1.30) 0.76 (0.55-1.03) 0.91 (0.65-1.27) 0.22  
>60 y 621/1,054 1.02 (0.74-1.40) 1.09 (0.78-1.52) 1.01 (0.72-1.43) 0.94 (0.67-1.32) 0.72 0.96 
    European Region North 540/695 1.09 (0.79-1.51) 0.88 (0.61-1.26) 0.76 (0.51-1.13) 0.73 (0.48-1.13) 0.06  
Central 495/971 1.05 (0.70-1.58) 1.34 (0.91-1.99) 1.09 (0.72-1.63) 1.34 (0.90-1.99) 0.18  
South 292/573 1.04 (0.65-1.68) 1.21 (0.76-1.93) 1.02 (0.63-1.67) 0.85 (0.51-1.41) 0.56 0.17 
    Alcohol intake* Abstainer 88/155 0.87 (0.31-2.45) 2.66 (0.93-7.61) 0.93 (0.33-2.64) 0.84 (0.29-2.42) 0.65  
1-30 g/d 963/1,719 0.92 (0.71-1.18) 0.95 (0.74-1.23) 0.81 (0.61-1.05) 0.89 (0.68-1.17) 0.26  
≥30 g/d 276/365 1.18 (0.70-1.99) 0.92 (0.54-1.56) 1.07 (0.61-1.87) 1.09 (0.61-1.96) 0.96 0.82 
    Median follow-up <3.6 y 651/1,145 1.16 (0.84-1.59) 1.17 (0.85-1.61) 1.05 (0.75-1.46) 0.96 (0.68-1.35) 0.70  
≥3.6 y 676/1,094 0.88 (0.65-1.21) 1.01 (0.73-1.40) 0.83 (0.59-1.17) 0.97 (0.69-1.37) 0.80 0.73 
N case/controlQ1Q2: 7.6-9.9Q3: 9.9-13.0Q4: 13.0-18.3Q5: >18.3PtrendPinteraction
Matched analyses Overall 1,367/2,318 0.97 (0.78-1.20) 1.06 (0.86-1.31) 0.87 (0.69-1.09) 0.91 (0.73-1.14) 0.29  
Matched plus covariate-adjusted analyses Overall 1,327/2,239 1.02 (0.82-1.27) 1.08 (0.87-1.35) 0.92 (0.72-1.16) 0.94 (0.74-1.20) 0.44  
    Sex Males 644/1,060 0.99 (0.72-1.37) 1.07 (0.77-1.47) 0.83 (0.58-1.18) 0.86 (0.60-1.23) 0.26  
Females 683/1,179 1.06 (0.78-1.44) 1.10 (0.81-1.50) 1.00 (0.73-1.39) 1.00 (0.72-1.39) 0.90 0.50 
    Age* ≤60 y 706/1,185 0.97 (0.72-1.31) 0.97 (0.72-1.30) 0.76 (0.55-1.03) 0.91 (0.65-1.27) 0.22  
>60 y 621/1,054 1.02 (0.74-1.40) 1.09 (0.78-1.52) 1.01 (0.72-1.43) 0.94 (0.67-1.32) 0.72 0.96 
    European Region North 540/695 1.09 (0.79-1.51) 0.88 (0.61-1.26) 0.76 (0.51-1.13) 0.73 (0.48-1.13) 0.06  
Central 495/971 1.05 (0.70-1.58) 1.34 (0.91-1.99) 1.09 (0.72-1.63) 1.34 (0.90-1.99) 0.18  
South 292/573 1.04 (0.65-1.68) 1.21 (0.76-1.93) 1.02 (0.63-1.67) 0.85 (0.51-1.41) 0.56 0.17 
    Alcohol intake* Abstainer 88/155 0.87 (0.31-2.45) 2.66 (0.93-7.61) 0.93 (0.33-2.64) 0.84 (0.29-2.42) 0.65  
1-30 g/d 963/1,719 0.92 (0.71-1.18) 0.95 (0.74-1.23) 0.81 (0.61-1.05) 0.89 (0.68-1.17) 0.26  
≥30 g/d 276/365 1.18 (0.70-1.99) 0.92 (0.54-1.56) 1.07 (0.61-1.87) 1.09 (0.61-1.96) 0.96 0.82 
    Median follow-up <3.6 y 651/1,145 1.16 (0.84-1.59) 1.17 (0.85-1.61) 1.05 (0.75-1.46) 0.96 (0.68-1.35) 0.70  
≥3.6 y 676/1,094 0.88 (0.65-1.21) 1.01 (0.73-1.40) 0.83 (0.59-1.17) 0.97 (0.69-1.37) 0.80 0.73 

NOTE: Lower quintile is reference category. All analyses are matched for age, sex, study center, and date of blood collection. The matched + covariate adjusted analyses are further adjusted for smoking status, education level, physical activity, fiber intake, intake of red and processed meat, alcohol consumption, and body mass index.

*Subgroup analyses by age and alcohol consumption are matched for sex and study center, and further adjusted for age, date of blood collection, smoking status, education level, physical activity, fiber intake, intake of red and processed meat, alcohol consumption, and body mass index.

We further explored whether the association between CRC risk and plasma folate in those with low and high alcohol consumption differed among males and females. Among individuals drinking <30 g alcohol/day, the RR (95% CI; Ptrend) for the fifth versus the first quintile of folate status for males was 0.79 (0.52-1.23; 0.19) and 0.96 (0.67-1.37; 0.73) for females. Among those drinking >30 g alcohol/day, the RR (95% CI; Ptrend) for the fifth versus the first quintile of folate status for males was 0.91 (0.47-1.75; 0.87) and 2.59 (0.53-12.75; 0.47) for females. The association between folate and CRC risk within different categories of alcohol intake did not differ by gender (Pinteraction <30 g alcohol/d = 0.56; Pinteraction ≥30 g alcohol/d = 0.15) and within each gender not by alcohol intake (Pinteraction males = 0.96; Pinteraction females = 0.15).

The folate related SNPs and their associations with CRC risk

All the SNPs were in Hardy-Weinberg equilibrium (χ2 test P > 0.05 for all SNPs) and the genotype distributions did not differ among cases and their matched controls (Table 4). We observed a borderline significant inverse association between the MTR 2756A→G polymorphism and CRC risk (Ptrend = 0.06). Compared with the SLC19A1 GG homozygotes, both the GA and AA genotypes were associated with significantly increased CRC risk (Ptrend < 0.01). Neither the MTHFR, MTRR, nor the MTHFD1 polymorphisms were associated with altered CRC cancer risk (Table 4). In addition, we investigated the associations between CRC risk and MTHFR 677C→T in 1298AA individuals, and MTHFR 1298A→C association in 677CC individuals to take potential effects of linkage disequilibrium between these two SNPs into account. These restrictions did not alter the associations between the MTHFR SNPs and CRC risk as shown in Table 4.

Table 4.

Associations [RR (95% CI)] of SNPs with CRC risk

SNPN case/controlOdds ratio (95% CI)
MTHFR 677 CC 567/1,019 
CT 608/1,076 1.02 (0.88-1.18) 
TT* 154/271 1.02 (0.81-1.28) 
Ptrend  0.79 
MTHFR 1298 AA 605/1,099 
AC 574/1,007 1.05 (0.91-1.21) 
CC* 151/259 1.09 (0.87-1.37) 
Ptrend  0.45 
MTR 2756 AA 890/1,498 
AG 385/774 0.83 (0.72-0.97) 
GG 54/92 0.98 (0.69-1.39) 
Ptrend  0.06 
MTRR 66 AA 264/435 
AG 597/1,111 0.88 (0.73-1.06) 
GG* 377/661 0.92 (0.76-1.13) 
Ptrend  0.54 
MTHFDI1958 GG 414/721 
GA 626/1,117 0.98 (0.84-1.15) 
AA* 269/489 0.98 (0.80-1.19) 
Ptrend  0.86 
SLC19A1 80 GG 390/792 
GA 660/1,126 1.21 (1.03-1.41) 
AA* 258/408 1.30 (1.06-1.59) 
Ptrend  <0.01 
SNPN case/controlOdds ratio (95% CI)
MTHFR 677 CC 567/1,019 
CT 608/1,076 1.02 (0.88-1.18) 
TT* 154/271 1.02 (0.81-1.28) 
Ptrend  0.79 
MTHFR 1298 AA 605/1,099 
AC 574/1,007 1.05 (0.91-1.21) 
CC* 151/259 1.09 (0.87-1.37) 
Ptrend  0.45 
MTR 2756 AA 890/1,498 
AG 385/774 0.83 (0.72-0.97) 
GG 54/92 0.98 (0.69-1.39) 
Ptrend  0.06 
MTRR 66 AA 264/435 
AG 597/1,111 0.88 (0.73-1.06) 
GG* 377/661 0.92 (0.76-1.13) 
Ptrend  0.54 
MTHFDI1958 GG 414/721 
GA 626/1,117 0.98 (0.84-1.15) 
AA* 269/489 0.98 (0.80-1.19) 
Ptrend  0.86 
SLC19A1 80 GG 390/792 
GA 660/1,126 1.21 (1.03-1.41) 
AA* 258/408 1.30 (1.06-1.59) 
Ptrend  <0.01 

*Prevalence in control cohort members significantly different among European regions (Pall < 0.01).

We further stratified the analyses by European region. The homozygote rare variant genotypes of the MTHFR 677C→T and SLC19A1 80G→A polymorphisms were more prevalent in Southern European countries (15% for MTHFR 677TT and 22% for SLC19A1 80AA) compared with Northern European countries (8% for MTHFR 677TT and 17% for SLC19A1 80AA; P < 0.01). In contrast, the homozygote rare variant genotypes of the MTRR 66A→G polymorphism was more prevalent in Northern European countries (34%) compared with Southern European countries (25%; P < 0.01), whereas the AA genotype of the MTHFD1 1958G→A SNP was most prevalent in Central European countries (24%) compared with Northern (19%) and Southern (20%) countries (P < 0.01). In spite of this genetic variation among European regions, stratification did not reveal significantly different associations between the SNPs and CRC by European regions (data not shown).

Interactions between SNPs, plasma folate, and alcohol consumption in CRC risk

We studied each polymorphism separately in combination with quintiles of folate status (Table 5). Although not statistically significant, we observed that the rare MTHFR 677TT genotype conferred an increased CRC risk in individuals with the lowest folate concentrations [RR (95% CI) TT versus CC = 1.39 (0.87-2.21)], whereas the TT genotype was associated with a decreased CRC risk in individuals with the highest folate concentrations [RR (95% CI) TT versus CC = 0.74 (0.39-1.37)]. Overall, the association between MTHFR 677C→T was not significantly modified by folate status (Pinteraction = 0.11). The associations between the other SNPs and CRC were not modified by folate status (Table 5).

Table 5.

RRs (95% CI) for CRC in folate related SNPs by quintiles of plasma folate status

SNPQuintiles of folate statusOR (95% CI)
12345
N case/controlOR (95% CI)N case/controlOR (95% CI)N case/controlOR (95% CI)N case/controlOR (95% CI)N case/control
MTHFR 677 CC 103/182 101/177 116/196 99/190 105/188 
CT 137/201 1.25 (0.90-1.75) 122/200 1.11 (0.79-1.56) 125/203 1.02 (0.74-1.42) 98/207 0.92 (0.65-1.30) 96/191 0.92 (0.65-1.30) 
TT 46/64 1.39 (0.87-2.21) 37/66 1.06 (0.65-1.73) 26/44 0.96 (0.55-1.67) 25/41 1.16 (0.66-2.03) 17/39 0.74 (0.39-1.37) 
Ptrend  0.12  0.70  0.96  0.89  0.34 
MTHFR 1298 AA 148/221 121/210 118/200 97/204 92/167 
AC 105/183 0.87 (0.63-1.20) 110/182 1.08 (0.77-1.51)6 123/194 1.10 (0.79-1.53) 98/193 1.06 (0.75-1.50) 103/198 0.96 (0.67-1.36) 
CC 33/42 1.25 (0.75-2.08) 29/51 0.92 (0.54-1.55) 27/49 0.98 (0.58-1.67) 27/41 1.28 (0.74-2.24) 23/53 0.81 (0.47-1.42) 
Ptrend  0.83  0.97  0.82  0.42  0.50 
SLC19A1 AA 84/148 81/149 76/149 67/159 62/138 
AG 143/217 1.20 (0.85-1.70) 132/215 1.06 (0.74-1.52) 126/218 1.18 (0.83-1.70) 114/198 1.44 (0.99-2.09) 120/218 1.27 (0.87-1.85) 
GG 59/81 1.27 (0.82-1.97) 46/79 1.00 (0.62-1.59) 66/76 1.68 (1.08-2.61) 41/81 1.26 (0.78-2.03) 36/61 1.43 (0.85-2.39) 
Ptrend  0.25  0.95  0.03  0.21  0.14 
MTRR 66 AA 72/77 46/86 53/83 38/71 47/87 
AG 121/214 0.61 (0.41-0.91) 111/201 0.98 (0.63-1.52) 132/213 0.90 (0.59-1.36) 104/211 0.96 (0.60-1.53) 96/186 0.93 (0.60-1.45) 
GG 69/124 0.57 (0.37-0.90) 70/120 0.98 (0.60-1.0) 71/122 0.91 (0.57-1.44) 70/120 1.10 (0.67-1.82) 63/117 0.96 (0.60-1.54) 
Ptrend  0.02  0.95  0.70  0.62  0.89 
MTR 2756 AA 186/264 184/279 183/282 149/286 147/284 
AG 86/162 0.78 (0.56-1.09) 69/149 0.71 (0.50-1.01) 69/141 0.74 (0.52-1.05) 66/139 0.87 (0.60-1.24) 63/119 1.02 (0.71-1.47) 
GG 14/20 1.05 (0.51-2.16) 7/16 0.66 (0.26-1.66) 15/18 1.22 (0.59-2.50) 7/13 0.94 (0.36-2.44) 8/15 1.09 (0.45-2.67) 
Ptrend  0.34  0.05  0.40  0.49  0.85 
MTHFDi GG 96/134 75/137 90/134 70/147 64/127 
GA 129/225 0.88 (0.68-1.15) 133/210 0.74 (0.55-1.00) 129/212 0.89 (0.68-1.17) 107/200 0.90 (0.66-1.22) 105/214 1.03 (0.76-1.39) 
AA 61/88 1.02 (1.00-1.04) 52/96 1.01 (0.99-1.04) 49/97 1.00 (0.98-1.03) 45/91 1.02 (0.99-1.04) 49/76 1.01 (0.98-1.03) 
Ptrend  0.94  0.72  0.13  0.99  0.36 
SNPQuintiles of folate statusOR (95% CI)
12345
N case/controlOR (95% CI)N case/controlOR (95% CI)N case/controlOR (95% CI)N case/controlOR (95% CI)N case/control
MTHFR 677 CC 103/182 101/177 116/196 99/190 105/188 
CT 137/201 1.25 (0.90-1.75) 122/200 1.11 (0.79-1.56) 125/203 1.02 (0.74-1.42) 98/207 0.92 (0.65-1.30) 96/191 0.92 (0.65-1.30) 
TT 46/64 1.39 (0.87-2.21) 37/66 1.06 (0.65-1.73) 26/44 0.96 (0.55-1.67) 25/41 1.16 (0.66-2.03) 17/39 0.74 (0.39-1.37) 
Ptrend  0.12  0.70  0.96  0.89  0.34 
MTHFR 1298 AA 148/221 121/210 118/200 97/204 92/167 
AC 105/183 0.87 (0.63-1.20) 110/182 1.08 (0.77-1.51)6 123/194 1.10 (0.79-1.53) 98/193 1.06 (0.75-1.50) 103/198 0.96 (0.67-1.36) 
CC 33/42 1.25 (0.75-2.08) 29/51 0.92 (0.54-1.55) 27/49 0.98 (0.58-1.67) 27/41 1.28 (0.74-2.24) 23/53 0.81 (0.47-1.42) 
Ptrend  0.83  0.97  0.82  0.42  0.50 
SLC19A1 AA 84/148 81/149 76/149 67/159 62/138 
AG 143/217 1.20 (0.85-1.70) 132/215 1.06 (0.74-1.52) 126/218 1.18 (0.83-1.70) 114/198 1.44 (0.99-2.09) 120/218 1.27 (0.87-1.85) 
GG 59/81 1.27 (0.82-1.97) 46/79 1.00 (0.62-1.59) 66/76 1.68 (1.08-2.61) 41/81 1.26 (0.78-2.03) 36/61 1.43 (0.85-2.39) 
Ptrend  0.25  0.95  0.03  0.21  0.14 
MTRR 66 AA 72/77 46/86 53/83 38/71 47/87 
AG 121/214 0.61 (0.41-0.91) 111/201 0.98 (0.63-1.52) 132/213 0.90 (0.59-1.36) 104/211 0.96 (0.60-1.53) 96/186 0.93 (0.60-1.45) 
GG 69/124 0.57 (0.37-0.90) 70/120 0.98 (0.60-1.0) 71/122 0.91 (0.57-1.44) 70/120 1.10 (0.67-1.82) 63/117 0.96 (0.60-1.54) 
Ptrend  0.02  0.95  0.70  0.62  0.89 
MTR 2756 AA 186/264 184/279 183/282 149/286 147/284 
AG 86/162 0.78 (0.56-1.09) 69/149 0.71 (0.50-1.01) 69/141 0.74 (0.52-1.05) 66/139 0.87 (0.60-1.24) 63/119 1.02 (0.71-1.47) 
GG 14/20 1.05 (0.51-2.16) 7/16 0.66 (0.26-1.66) 15/18 1.22 (0.59-2.50) 7/13 0.94 (0.36-2.44) 8/15 1.09 (0.45-2.67) 
Ptrend  0.34  0.05  0.40  0.49  0.85 
MTHFDi GG 96/134 75/137 90/134 70/147 64/127 
GA 129/225 0.88 (0.68-1.15) 133/210 0.74 (0.55-1.00) 129/212 0.89 (0.68-1.17) 107/200 0.90 (0.66-1.22) 105/214 1.03 (0.76-1.39) 
AA 61/88 1.02 (1.00-1.04) 52/96 1.01 (0.99-1.04) 49/97 1.00 (0.98-1.03) 45/91 1.02 (0.99-1.04) 49/76 1.01 (0.98-1.03) 
Ptrend  0.94  0.72  0.13  0.99  0.36 

NOTE: All analyses are stratified on country and sex and adjusted for age. PinteractionMTHFR677*folate = 0.11; MTHFR1298*folate = 0.81; SLC19A1*folate = 0.67; MTRR66*folate = 0.12; MTR2756*folate = 0,26; MTHFDI*folate = 0.59.

Table 6 shows that individuals with the MTHFR 677TT genotype who consumed ≥30 g of alcohol/day had a slight increased CRC risk (Ptrend 0.09) compared with those drinking less alcohol/day (Ptrend 0.46; Pinteraction = 0.11). These associations were not modified by medians of folate status (Pinteraction = 0.38). Examination of combinations of other SNPs under investigation, alcohol intake, and folate status did not modify the associations between those SNPs and CRC risk (Pinteractions > 0.31; data not shown).

Table 6.

RRs (95% CI) for CRC with MTHFR 677C→T in subgroups of alcohol consumption and folate status

Alcohol consumptionPinteractionPinteraction
1-29 g/d≥30 g/d
Plasma folate MTHFR 677 N ca/co OR (95% CI) N ca/co OR (95% CI) MTHFR 677 alcohol MTHFR 677 alcohol folate 
Overall CC 431/797 101/159   
CT 431/839 0.95 (0.80-1.12) 127/148 1.41 (1.00-2.00)   
TT 107/211 0.92 (0.71-1.20) 36/45 1.38 (0.82-2.32)   
Ptrend  0.46  0.09 0.11  
<11.3 nmol/L CC 301/549 68/107   
CT 318/591 0.99 (0.81-1.20) 92/110 1.33 (0.87-2.03)   
TT 84/164 0.93 (0.69-1.26) 27/34 1.42 (0.76-2.62)   
Ptrend  0.71  0.15 0.35  
>11.3 nmol/L CC 130/248 33/52   
CT 113/248 0.86 (0.63-1.17) 35/38 1.30 (0.67-2.51)   
TT 23/47 0.90 (0.52-1.56) 9/11 1.36 (0.49-3.74)  
Ptrend  0.42  0.41 0.28 0.38 
Alcohol consumptionPinteractionPinteraction
1-29 g/d≥30 g/d
Plasma folate MTHFR 677 N ca/co OR (95% CI) N ca/co OR (95% CI) MTHFR 677 alcohol MTHFR 677 alcohol folate 
Overall CC 431/797 101/159   
CT 431/839 0.95 (0.80-1.12) 127/148 1.41 (1.00-2.00)   
TT 107/211 0.92 (0.71-1.20) 36/45 1.38 (0.82-2.32)   
Ptrend  0.46  0.09 0.11  
<11.3 nmol/L CC 301/549 68/107   
CT 318/591 0.99 (0.81-1.20) 92/110 1.33 (0.87-2.03)   
TT 84/164 0.93 (0.69-1.26) 27/34 1.42 (0.76-2.62)   
Ptrend  0.71  0.15 0.35  
>11.3 nmol/L CC 130/248 33/52   
CT 113/248 0.86 (0.63-1.17) 35/38 1.30 (0.67-2.51)   
TT 23/47 0.90 (0.52-1.56) 9/11 1.36 (0.49-3.74)  
Ptrend  0.42  0.41 0.28 0.38 

In this large EPIC study, we investigated the associations of plasma folate status and genetic variability in five folate-related genes with CRC risk. Overall analysis did not reveal significant associations between plasma folate concentrations or the MTHFR genotypes and CRC risk. However, CRC risk increased with the number of T alleles of the MTHFR 677C→T polymorphism in individuals with low folate status and decreased in individuals with high folate status. Such an association has been reported by others (25, 29-31), but associations in our study did not reach statistical significance. For the first time, a positive association of the variant genotypes of the SLC19A1 80G→A SNP with CRC risk is observed.

The present study is the largest prospective investigation with data on plasma folate and CRC risk published thus far and its large sample size allowed us to perform subgroup analyses. Extensive information on life-style factors has been collected for each cohort member, which allowed the adjustment for potential confounders and the assessment of possible effect modification. Another important strength of this study is the collection of blood samples before cancer diagnosis. All study centers collected and stored blood samples according to a standardized protocol (43) and all biochemical analyses were done in one laboratory, thereby optimizing sample treatment and avoiding between-laboratory method variability. The observed associations between folate status and age, sex, smoking status, and the folate-related polymorphisms in the present study are in line with previous findings (17, 58, 59), confirming the integrity of biochemical data in this large multicenter study.

Studies on plasma folate and CRC risk are inconclusive, showing either an inverse association (40, 42), a positive association (37), or no association in the present and other (30, 39, 41) studies. It is unknown whether any of the Japanese (39), European (37, 41), and American (30, 40, 42) studies collected data under policies of voluntary folic acid fortification. Therefore, it is unclear whether folic acid fortification may explain contrasting study findings; however, relatively small sample sizes, ethnicity, and different ranges of plasma folate concentrations may do so. Conceivably, an association between CRC risk and plasma folate status may be more pronounced in a population that includes a higher proportion of individuals with low folate status. Different dietary habits and a large variation in folate status (30, 37, 39, 40) in this large multicountry study is therefore one of its strengths. In the present study, 9% of all cohort members were folate deficient, as defined by folate concentrations <6.0 nmol/L. In Sweden and Denmark, the prevalence was 15%, compared with 5% and 8% in Central and Southern Europe, respectively. Moreover, mean plasma folate concentrations were lower in Northern European countries compared with other European regions. The lower folate concentrations, and consequently higher prevalence of folate deficiency in Northern Europe, may explain the inverse association for rectal cancer. In contrast, although overall folate status was reported to be low, a Swedish study observed low plasma folate concentrations to be associated with a decreased CRC risk in a smaller subgroup with a follow up time of >4.2 years (37).

Regarding dietary intake of folate and CRC, the majority of studies reported an inverse association between folate and CRC risk (2, 3, 60), which was predominantly present for dietary folate and not for total folate intake (3), suggesting that the use of folic acid supplements may attenuate the inverse association with CRC risk. It is unclear whether this is the case in the present study because data on supplement use, and specifically use of B vitamins, in the EPIC cohort are sparse. However, in a subsample of the EPIC population, single 24-hour recalls revealed a clear North-South gradient in supplement use, with higher consumption in Northern European countries than in Southern European countries and higher consumption for women than for men (61). Although many countries apply mandatory folic acid fortification of flour (62), no such policies have been implemented in Western European countries and national voluntary fortification policies vary considerably throughout the European Union (63).

The discrepant results of studies on the association of folate intake and plasma folate with CRC risk may be explained by the fact that plasma folate does not necessarily reflect folate intake due to disturbances in folate bioavailability, or measurement errors that are inevitable when using food frequency questionnaires. In some studies with a short follow-up period, preclinical cancer might have been present in controls when their blood sample was taken, which could have influenced the plasma folate concentrations. However, exclusion of cases and their matched controls diagnosed within 1 to 3.6 years from blood donation did not materially alter the associations in the present study.

In addition to some small prospective studies that observed inverse associations between plasma folate and CRC risk (30, 40, 42), several small randomized placebo-controlled intervention studies on surrogate end points of CRC, as summarized by Kim (1), suggest that folic acid supplementation may have beneficial effects on DNA stability, DNA repair, and DNA methylation, which are considered important in carcinogenesis. However, these trials have a short intervention period and do not, therefore, provide strong evidence for a role of folate in colorectal carcinogenesis. Nevertheless, these observations are not in agreement with the observations of a temporal increased CRC incidence concurrent with mandatory folic acid supplementation in the United States and Canada (5), and results from the Aspirin/Folate Polyp Prevention Study suggested increased risk of advanced lesions after folic acid supplementation (6). The apparent contradictory findings from epidemiologic (2, 3, 23, 37, 39-42) and intervention studies (1, 6, 64) may reflect differences in study designs, as well as a dual role of folate whereby the timing of low and high folate status in relation to the progress of colorectal carcinogenesis is thought to be of crucial importance. The present study is not designed to resolve this hypothesized dual effect of folate status.

The present study investigated SNPs that occurred in genes related to folate absorption, transport, and use (65). Two meta-analyses observed a CRC risk reduction of 7% to 17% in individuals with the MTHFR 677TT genotype compared with individuals with the 677CC genotype in worldwide populations (20, 21). However, stratification for geographic regions revealed moderate significant risk reductions in U.S. and Asian studies, but a null-finding for European studies (20), which agrees with the present study but not with a large Norwegian study (24). In addition, previous studies have shown that the MTHFR 677TT genotype might be a risk factor for CRC (25, 29-31) and adenoma (32, 33) at low folate status and protective at high folate status, which is confirmed to some extend by results from the present study. The variant genotype of the MTR 2756A→G polymorphism is rare (17) and less studied, but there is some evidence that the homozygote genotype is also associated with decreased CRC risk (23, 24), although this was not confirmed in the present and other studies (23, 25). Results from studies on MTRR 66A→G (18, 19, 25), MTHFD1 1958G→A (26, 27), and the SLC19A1 80G→A (9, 28) polymorphisms are sparse and inconclusive. We did not observe an association of MTRR 66A→G and MTHFD1 1958G→A SNPs with CRC risk. The positive association between the SLC19A1 80G→A polymorphism is a novel finding that requires confirmation in future studies.

In line with alcohol as a risk factor for CRC (66) and an antagonistic effect of alcohol on folate status (67), many studies on folate intake (66, 68) and some on plasma folate (30, 40, 41) have shown an increased CRC risk in individuals with low folate status and high alcohol consumption compared with those with high folate status and low alcohol consumption (30, 40, 41). This was not observed in the present and another study (39). Small subgroups, ethnicity, and different measures and ranges of folate status and alcohol intake may explain contrasting findings. It has been suggested that the alcohol effect is mediated by impaired one-carbon metabolism because previous studies showed an interaction between plasma folate status, MTHFR polymorphisms, and alcohol intake for CRC risk (22, 34-36). Furthermore, individuals with the MTHFR 677TT genotype showed a decreased risk when combined with high folate and low alcohol intake, and increased risk in individuals with low folate and high alcohol intake (25, 30, 31). Although the present study observed a borderline significant increased CRC risk in individuals with the CT and TT genotype in individuals who consumed ≥30 g alcohol/day compared with those consuming less alcohol, stratification by folate status attenuated these results. However, a large sample size is critical to investigate gene-environment interactions with moderate RRs and sample size requirement may even exceed the number of cases and controls included in the present study

In conclusion, the overall results of the current study did not reveal significant associations between the MTHFR 677C→T polymorphism and plasma folate with CRC risk, which is in contrast to results from meta-analyses (2, 3, 20, 21). However, a much longer follow-up period and repeated measures of plasma folate are required to elucidate potential time-dependent associations between folate and CRC risk. In addition, larger sample sizes are needed to adequately investigate gene-environment interactions.

No potential conflicts of interest were disclosed.

We thank B. Hemon and C. Casagrande (IARC-WHO) for their assistance in database preparation, and Tove Følid, Halvard Bergesen, and Gry Kvalheim (Section for Pharmacology, University of Bergen) for their laboratory assistance in the folate and homocysteine analyses.

Grant Support: European Commission: Public Health and Consumer Protection Directorate 1993 to 2004; Research Directorate-General 2005; Ligue contre le Cancer (France); Société 3M (France); Mutuelle Générale de l'Education Nationale; Institut National de la Santé et de la Recherche Médicale (INSERM); German Cancer Aid; German Cancer Research Center; German Federal Ministry of Education and Research; Danish Cancer Society; Health Research Fund (FIS) of the Spanish Ministry of Health (RCESP-C03/09; RTICCC (C03/10); the participating regional governments and institutions of Spain; Cancer Research UK; Medical Research Council, UK; the Stroke Association, UK; British Heart Foundation; Department of Health, UK; Food Standards Agency, UK; the Wellcome Trust, UK; Greek Ministry of Health and Social Solidarity; Hellenic Health Foundation and Stavros Niarchos Foundation; Italian Association for Research on Cancer; Compagnia San Paolo, Italy; Dutch Ministry of Public Health, Welfare and Sports; Dutch Ministry of Health; Dutch Prevention Funds; LK Research Funds; Dutch ZON (Zorg Onderzoek Nederland); World Cancer Research Fund (WCRF); Swedish Cancer Society; Swedish Scientific Council; Regional Government of Skane, Sweden; Norwegian Cancer Society; and the Foundation to promote research into functional vitamin B12-deficiency, Norway.

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

1
Kim
YI
. 
Folate and colorectal cancer: an evidence-based critical review
.
Mol Nutr Food Res
2007
;
51
:
267
92
.
2
Bollheimer
LC
,
Buettner
R
,
Kullmann
A
,
Kullmann
F
. 
Folate and its preventive potential in colorectal carcinogenesis. How strong is the biological and epidemiological evidence?
Crit Rev Oncol Hematol
2005
;
55
:
13
36
.
3
Sanjoaquin
MA
,
Allen
N
,
Couto
E
,
Roddam
AW
,
Key
TJ
. 
Folate intake and colorectal cancer risk: a meta-analytical approach
.
Int J Cancer
2005
;
113
:
825
8
.
4
Giovannucci
E
,
Stampfer
MJ
,
Colditz
GA
, et al
. 
Multivitamin use, folate, and colon cancer in women in the Nurses' Health Study
.
Ann Intern Med
1998
;
129
:
517
24
.
5
Mason
JB
,
Dickstein
A
,
Jacques
PF
, et al
. 
A temporal association between folic acid fortification and an increase in colorectal cancer rates may be illuminating important biological principles: a hypothesis
.
Cancer Epidemiol Biomarkers Prev
2007
;
16
:
1325
9
.
6
Cole
BF
,
Baron
JA
,
Sandler
RS
, et al
. 
Folic acid for the prevention of colorectal adenomas: a randomized clinical trial
.
JAMA
2007
;
297
:
2351
9
.
7
Kim
YI
. 
Folic Acid supplementation and cancer risk: point
.
Cancer Epidemiol Biomarkers Prev
2008
;
17
:
2220
5
.
8
Ulrich
CM
. 
Folate and cancer prevention-where to next? Counterpoint
.
Cancer Epidemiol Biomarkers Prev
2008
;
17
:
2226
30
.
9
Ulrich
CM
,
Curtin
K
,
Potter
JD
, et al
. 
Polymorphisms in the reduced folate carrier, thymidylate synthase, or methionine synthase and risk of colon cancer
.
Cancer Epidemiol Biomarkers Prev
2005
;
14
:
2509
16
.
10
Hum
DW
,
Bell
AW
,
Rozen
R
,
MacKenzie
RE
. 
Primary structure of a human trifunctional enzyme. Isolation of a cDNA encoding methylenetetrahydrofolate dehydrogenase-methenyltetrahydrofolate cyclohydrolase-formyltetrahydrofolate synthetase
.
J Biol Chem
1988
;
263
:
15946
50
.
11
Nguyen
TT
,
Dyer
DL
,
Dunning
DD
, et al
. 
Human intestinal folate transport: cloning, expression, and distribution of complementary RNA
.
Gastroenterology
1997
;
112
:
783
91
.
12
Frosst
P
,
Blom
HJ
,
Milos
R
, et al
. 
A candidate genetic risk factor for vascular disease: a common mutation in methylenetetrahydrofolate reductase
.
Nat Genet
1995
;
10
:
111
3
.
13
Leclerc
D
,
Campeau
E
,
Goyette
P
, et al
. 
Human methionine synthase: cDNA cloning and identification of mutations in patients of the cblG complementation group of folate/cobalamin disorders
.
Hum Mol Genet
1996
;
5
:
1867
74
.
14
Chen
LH
,
Liu
ML
,
Hwang
HY
, et al
. 
Human methionine synthase. cDNA cloning, gene localization, and expression
.
J Biol Chem
1997
;
272
:
3628
34
.
15
van der Put
NM
,
Gabreels
F
,
Stevens
EM
, et al
. 
A second common mutation in the methylenetetrahydrofolate reductase gene: an additional risk factor for neural-tube defects?
Am J Hum Genet
1998
;
62
:
1044
51
.
16
Finkelstein
JD
. 
The metabolism of homocysteine: pathways and regulation
.
Eur J Pediatr
1998
;
157
Suppl 2
:
S40
4
.
17
Sharp
L
,
Little
J
. 
Polymorphisms in genes involved in folate metabolism and colorectal neoplasia: a HuGE review
.
Am J Epidemiol
2004
;
159
:
423
43
.
18
Hazra
A
,
Wu
K
,
Kraft
P
, et al
. 
Twenty-four non-synonymous polymorphisms in the one-carbon metabolic pathway and risk of colorectal adenoma in the Nurses' Health Study
.
Carcinogenesis
2007
;
28
:
1510
9
.
19
Koushik
A
,
Kraft
P
,
Fuchs
CS
, et al
. 
Nonsynonymous polymorphisms in genes in the one-carbon metabolism pathway and associations with colorectal cancer
.
Cancer Epidemiol Biomarkers Prev
2006
;
15
:
2408
17
.
20
Hubner
RA
,
Houlston
RS
. 
MTHFR C677T and colorectal cancer risk: a meta-analysis of 25 populations
.
Int J Cancer
2007
;
120
:
1027
35
.
21
Huang
Y
,
Han
S
,
Li
Y
,
Mao
Y
,
Xie
Y
. 
Different roles of MTHFR C677T and A1298C polymorphisms in colorectal adenoma and colorectal cancer: a meta-analysis
.
J Hum Genet
2007
;
52
:
73
85
.
22
Chen
J
,
Giovannucci
E
,
Hankinson
SE
, et al
. 
A prospective study of methylenetetrahydrofolate reductase and methionine synthase gene polymorphisms, and risk of colorectal adenoma
.
Carcinogenesis
1998
;
19
:
2129
32
.
23
Ma
J
,
Stampfer
MJ
,
Christensen
B
, et al
. 
A polymorphism of the methionine synthase gene: association with plasma folate, vitamin B12, homocyst(e)ine, and colorectal cancer risk
.
Cancer Epidemiol Biomarkers Prev
1999
;
8
:
825
9
.
24
Ulvik
A
,
Vollset
SE
,
Hansen
S
, et al
. 
Colorectal cancer and the methylenetetrahydrofolate reductase 677C→T and methionine synthase 2756A→G polymorphisms: a study of 2,168 case-control pairs from the JANUS cohort
.
Cancer Epidemiol Biomarkers Prev
2004
;
13
:
2175
80
.
25
Le Marchand
L
,
Donlon
T
,
Hankin
JH
, et al
. 
B-vitamin intake, metabolic genes, and colorectal cancer risk (United States)
.
Cancer Causes Control
2002
;
13
:
239
48
.
26
Chen
J
,
Kyte
C
,
Valcin
M
, et al
. 
Polymorphisms in the one-carbon metabolic pathway, plasma folate levels and colorectal cancer in a prospective study
.
Int J Cancer
2004
;
110
:
617
20
.
27
Kawakami
K
,
Ruszkiewicz
A
,
Bennett
G
, et al
. 
DNA hypermethylation in the normal colonic mucosa of patients with colorectal cancer
.
Br J Cancer
2006
;
94
:
593
8
.
28
Eklof
V
,
Van Guelpen
B
,
Hultdin
J
, et al
. 
The reduced folate carrier (RFC1) 80G>A and folate hydrolase 1 (FOLH1) 1561C>T polymorphisms and the risk of colorectal cancer: a nested case-referent study
.
Scand J Clin Lab Invest
2007
:
1
9
.
29
Chen
J
,
Giovannucci
E
,
Kelsey
K
, et al
. 
A methylenetetrahydrofolate reductase polymorphism and the risk of colorectal cancer
.
Cancer Res
1996
;
56
:
4862
4
.
30
Ma
J
,
Stampfer
MJ
,
Giovannucci
E
, et al
. 
Methylenetetrahydrofolate reductase polymorphism, dietary interactions, and risk of colorectal cancer
.
Cancer Res
1997
;
57
:
1098
102
.
31
Slattery
ML
,
Potter
JD
,
Samowitz
W
,
Schaffer
D
,
Leppert
M
. 
Methylenetetrahydrofolate reductase, diet, and risk of colon cancer
.
Cancer Epidemiol Biomarkers Prev
1999
;
8
:
513
8
.
32
Ulrich
CM
,
Kampman
E
,
Bigler
J
, et al
. 
Colorectal adenomas and the C677T MTHFR polymorphism: evidence for gene-environment interaction?
Cancer Epidemiol Biomarkers Prev
1999
;
8
:
659
68
.
33
Levine
AJ
,
Siegmund
KD
,
Ervin
CM
, et al
. 
The methylenetetrahydrofolate reductase 677C→T polymorphism and distal colorectal adenoma risk
.
Cancer Epidemiol Biomarkers Prev
2000
;
9
:
657
63
.
34
Marugame
T
,
Tsuji
E
,
Inoue
H
, et al
. 
Methylenetetrahydrofolate reductase polymorphism and risk of colorectal adenomas
.
Cancer Lett
2000
;
151
:
181
6
.
35
Chen
J
,
Ma
J
,
Stampfer
MJ
, et al
. 
Linkage disequilibrium between the 677C>T and 1298A>C polymorphisms in human methylenetetrahydrofolate reductase gene and their contributions to risk of colorectal cancer
.
Pharmacogenetics
2002
;
12
:
339
42
.
36
Ulrich
CM
,
Kampman
E
,
Bigler
J
, et al
. 
Lack of association between the C677T MTHFR polymorphism and colorectal hyperplastic polyps
.
Cancer Epidemiol Biomarkers Prev
2000
;
9
:
427
33
.
37
Van Guelpen
B
,
Hultdin
J
,
Johansson
I
, et al
. 
Low folate levels may protect against colorectal cancer
.
Gut
2006
;
55
:
1461
6
.
38
Giovannucci
E
,
Rimm
EB
,
Ascherio
A
, et al
. 
Alcohol, low-methionine-low-folate diets, and risk of colon cancer in men
.
J Natl Cancer Inst
1995
;
87
:
265
73
.
39
Otani
T
,
Iwasaki
M
,
Sasazuki
S
,
Inoue
M
,
Tsugane
S
. 
Plasma folate and risk of colorectal cancer in a nested case-control study: the Japan Public Health Center-based prospective study
.
Cancer Causes Control
2008
;
19
:
67
74
.
40
Kato
I
,
Dnistrian
AM
,
Schwartz
M
, et al
. 
Serum folate, homocysteine and colorectal cancer risk in women: a nested case-control study
.
Br J Cancer
1999
;
79
:
1917
22
.
41
Glynn
SA
,
Albanes
D
,
Pietinen
P
, et al
. 
Colorectal cancer and folate status: a nested case-control study among male smokers
.
Cancer Epidemiol Biomarkers Prev
1996
;
5
:
487
94
.
42
Bird
CL
,
Swendseid
ME
,
Witte
JS
, et al
. 
Red cell and plasma folate, folate consumption, and the risk of colorectal adenomatous polyps
.
Cancer Epidemiol Biomarkers Prev
1995
;
4
:
709
14
.
43
Riboli
E
,
Kaaks
R
,
European Prospective Investigation into Cancer and Nutrition
. 
The EPIC Project: rationale and study design
.
Int J Epidemiol
1997
;
26
Suppl 1
:
S6
14
.
44
Riboli
E
,
Hunt
KJ
,
Slimani
N
, et al
. 
European Prospective Investigation into Cancer and Nutrition (EPIC): study populations and data collection
.
Public Health Nutr
2002
;
5
:
1113
24
.
45
Juzeniene
A
,
Thu Tam
TT
,
Iani
V
,
Moan
J
. 
5-Methyltetrahydrofolate can be photodegraded by endogenous photosensitizers
.
Free Radic Biol Med
2009
;
47
:
1199
204
.
46
IARC Cancer Incidence in Five Continents
. 1st ed.
9
.
Lyon
:
International Agency for Research on Cancer
; 
2009
, p.
1
898
.
47
Benetou
V
,
Trichopoulou
A
,
Orfanos
P
, et al
. 
Conformity to traditional Mediterranean diet and cancer incidence: the Greek EPIC cohort
.
Br J Cancer
2008
;
99
:
191
5
.
48
Steinbrecher
A
,
Nimptsch
K
,
Husing
A
,
Rohrmann
S
,
Linseisen
J
. 
Dietary glucosinolate intake and risk of prostate cancer in the EPIC-Heidelberg cohort study
.
Int J Cancer
2009
;
125
:
2179
86
.
49
Cottet
V
,
Touvier
M
,
Fournier
A
, et al
. 
Postmenopausal breast cancer risk and dietary patterns in the E3N-EPIC prospective cohort study
.
Am J Epidemiol
2009
;
170
:
1257
67
.
50
Kesse
E
,
Clavel-Chapelon
F
,
Boutron-Ruault
MC
. 
Dietary patterns and risk of colorectal tumors: a cohort of French women of the National Education System (E3N)
.
Am J Epidemiol
2006
;
164
:
1085
93
.
51
EPIC-European Prospective Investigation into Cancer and Nutrition. http://epic.iarc.fr. Accessed on November 26, 2009.
52
Bergstralh
EJ
,
Kosanke
JL
,
Jacobsen
SJ
. 
Software for optimal matching in observational studies
.
Epidemiology
1996
;
7
:
331
2
.
53
Rosenbaum
P
. 
Optimal matching for observational studies
.
J Am Stat Assoc
1989
;
84
:
1024
32
.
54
Molloy
AM
,
Scott
JM
. 
Microbiological assay for serum, plasma, and red cell folate using cryopreserved, microtiter plate method
.
Methods Enzymol
1997
;
281
:
43
53
.
55
Windelberg
A
,
Arseth
O
,
Kvalheim
G
,
Ueland
PM
. 
Automated assay for the determination of methylmalonic acid, total homocysteine, and related amino acids in human serum or plasma by means of methylchloroformate derivatization and gas chromatography-mass spectrometry
.
Clin Chem
2005
;
51
:
2103
9
.
56
Fredriksen
A
,
Meyer
K
,
Ueland
PM
, et al
. 
Large-scale population-based metabolic phenotyping of thirteen genetic polymorphisms related to one-carbon metabolism
.
Hum Mutat
2007
;
28
:
856
65
.
57
Knol
MJ
,
Vandenbroucke
JP
,
Scott
P
,
Egger
M
. 
What do case-control studies estimate? Survey of methods and assumptions in published case-control research
.
Am J Epidemiol
2008
;
168
:
1073
81
.
58
De Bree
A
,
Verschuren
WM
,
Kromhout
D
,
Kluijtmans
LA
,
Blom
HJ
. 
Homocysteine determinants and the evidence to what extent homocysteine determines the risk of coronary heart disease
.
Pharmacol Rev
2002
;
54
:
599
618
.
59
Meyer
K
,
Fredriksen
A
,
Ueland
PM
. 
High-level multiplex genotyping of polymorphisms involved in folate or homocysteine metabolism by matrix-assisted laser desorption/ionization mass spectrometry
.
Clin Chem
2004
;
50
:
391
402
.
60
Kim
J
,
Kim
DH
,
Lee
BH
, et al
. 
Folate intake and the risk of colorectal cancer in a Korean population
.
Eur J Clin Nutr
2009
;
63
:
1057
64
.
61
Skeie
G
,
Braaten
T
,
Hjartaker
A
, et al
. 
Use of dietary supplements in the European Prospective Investigation into Cancer and Nutrition calibration study
.
Eur J Clin Nutr
2009
;
63
Suppl 4
:
S226
38
.
62
Trends in wheat-flour fortification with folic acid and iron-worldwide, 2004 and 2007
.
MMWR Morb Mortal Wkly Rep
2008
;
57
:
8
10
.
63
European Commission Health and Consumer Protection Directorate-General
.
Discussion paper on the Setting of Maximum and Minimum Amounts for Vitamins and Minerals in Foodstuffs
.
Brussels, Belgium
:
European Communities
; 
2006
.
64
Martinez
ME
,
Henning
SM
,
Alberts
DS
. 
Folate and colorectal neoplasia: relation between plasma and dietary markers of folate and adenoma recurrence
.
Am J Clin Nutr
2004
;
79
:
691
7
.
65
Molloy
AM
. 
Folate and homocysteine interrelationships including genetics of the relevant enzymes
.
Curr Opin Lipidol
2004
;
15
:
49
57
.
66
Ferrari
P
,
Jenab
M
,
Norat
T
, et al
. 
Lifetime and baseline alcohol intake and risk of colon and rectal cancers in the European prospective investigation into cancer and nutrition (EPIC)
.
Int J Cancer
2007
;
121
:
2065
72
.
67
Hillman
RS
,
Steinberg
SE
. 
The effects of alcohol on folate metabolism
.
Annu Rev Med
1982
;
33
:
345
54
.
68
Giovannucci
E
. 
Alcohol, one-carbon metabolism, and colorectal cancer: recent insights from molecular studies
.
J Nutr
2004
;
134
:
2475
81S
.