Search tips
Search criteria 


Logo of wtpaEurope PMCEurope PMC Funders GroupSubmit a Manuscript
Cancer Epidemiol Biomarkers Prev. Author manuscript; available in PMC 2010 November 1.
Published in final edited form as:
PMCID: PMC2880712

Plasma folate, related genetic variants and colorectal cancer risk in EPIC


A potential dual role of folate in colorectal cancer (CRC) is currently subject to debate. Previous studies on plasma folate and CRC risk were small and inconclusive. We therefore investigate associations between plasma folate, a number of relevant folate-related polymorphisms and CRC risk. In this nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, 1367 incident CRC cases were matched to 2325 controls for study center, age and sex. Risk ratios (RR) were estimated with conditional logistic regression and further adjusted for smoking, education, physical activity, and intake of alcohol and fiber. Overall analyses did not reveal associations of plasma folate with CRC. The RR (95% CI), Ptrend) for the fifth vs. the first quintile of folate status was 0.94 ((0.74; 1.20), 0.44). The polymorphisms MTHFR 677C→T, MTHFR 1298A→C, MTR 2756A→G, MTRR 66A→G, and MTHFD1 1958G→A were not associated with CRC risk. However, in individuals with the lowest plasma folate concentrations, the MTHFR 677TT genotype showed a statistically non-significant increased CRC risk (RR (95% CI, Ptrend) TT vs. CC =1.39 (0.87; 2.21), 0.12), whereas in those with the highest folate concentrations showed a non-significant decreased CRC risk (RR TT vs. CC=0.74 (0.39; 1.37), 0.34). The SLC19A1 80G→A showed a positive association with CRC risk (RR AA vs. GG1.30 (1.06; 1.59), <0.01).

Within this large European prospective multicenter study we did not observe an association of CRC risk with plasma folate status, nor with the MTHFR polymorphisms.

Keywords: Plasma folate, genetic variants, colorectal cancer, prospective study


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 summarised in two meta-analyses (2, 3), indicate a 20% to 40% CRC risk reduction in individuals with the highest folate intake compared to those with the lowest folate intake. The Nurses Health Study demonstrated 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 to those taking them less than 15 years or never (4). However, a temporally increased CRC incidence has been reported to coincide with mandatory folic acid supplementation in the US and Canada (5). In addition, explorative analyses of the first randomised controlled intervention trial of folic acid for 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 6-8 years (6). As a result of these contradictory findings, a potential dual role of folate has been hypothesised (1, 7, 8), i.e. 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) which provide methylgroups 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) (12-15), which requires 5-methyltetrahydrofolate as a methyl donor for the remethylation of homocysteine to methionine in order to provides methylgroups for e.g. DNA methylation. Regeneration of 5-methyltetrahydrofolate from tetrahydrofolate is catalyzed by the enzyme methylenetetrahydrofolate reductase (MTHFR) (16) (Figure 1). Among the one-carbon related SNPs 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 sparce 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 to the CC or CT variants, has been shown to be either a risk factor for colorectal cancer (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

The associations between plasma folate and CRC risk has been investigated in a number of previous studies (30, 37, 39-42). However the associations were inconsistent. Therefore, we investigated the association between plasma folate status and colorectal cancer in a very large scale prospective cohort study within the European Prospective Investigation into Cancer and Nutrition (EPIC). We also assessed 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, Netherlands, Norway, Spain, Sweden and United Kingdom). Between 1992 and 1998, country-specific dietary questionnaires, standardized lifestyle 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 non-fasting blood samples of at least 30mL were drawn from those participants who provided a blood sample and stored at 5-10°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 centres 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, 107 controls) and EPIC-Norway (5 cases, 9 controls) samples were excluded from the present analyses.

In all countries, except Denmark and Sweden, blood was separated into 0.5mL 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 centre and the other half in the central EPIC biorepository at the International Agency for Research on Cancer (IARC; Lyon, France). In Denmark, blood fraction aliquots of 1.0mL were stored locally at −150°C under nitrogen vapour. In Sweden, samples were stored in −80°C freezers.

This study was approved by the Ethical Review Board of the International Agency for Research on Cancer (IARC; Lyon, France) 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, Netherlands, Norway, Spain, Sweden and the United Kingdom) or via 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), and December 31, 2002 (Denmark and Umeå), 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 via active follow-up were verified by physicians and pathology reports. In these countries, pathology reports are available for at least 95% of cases, and 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, histological confirmation of CRC was available for 93%, whereas 6% was diagnosed via clinical observation, cytology or autopsy, and information on 1% was missing. Current information regarding 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, 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). Colorectal cancer (CRC) is defined as a combination of the colon and rectal cancer cases. The present study includes a total of 1367 incident CRC cases (colon n = 850; rectal n = 517). The distribution of cases (colon/rectal) by country was Denmark = 206/ 172, Sweden = 100/ 84, France = 30/ 3, Greece = 14/ 13, Germany = 98/ 61, Italy = 106/ 43, The Netherlands = 102/ 49, Spain = 80/ 43, and United Kingdom = 114/ 49. Ninety-six % (n=1299) of cancer cases were classified as adenocarcinomas, whereas the remaining 4% of the tumors 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 years) and study center (to account of centre 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) differences in age between cases and controls within each caseset were −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, Bonaluz, Switzerland) (54), and plasma total homocysteine (tHcy) by a method based on methylchloroformate derivatization and gas chromatography-mass spectrometry (55). In total, 1.89 % of the samples could not be analyses due to e.g. insufficient sample volumes. Within- and between-day coefficients of variation for folate and total homocysteine were 3%-20%(54) and 6%-22%(55), respectively.

The single nucleotide polymorphisms (SNPs) of genes related to one-carbon metabolism were determined by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (56). These included methylenetetrahydrofolate reductase (MTHFR 677C→T; rs#1801133 and MTHFR 1298A→C; rs#1801131), methionine synthase (MTR 2756A→G; rs#1805087), methionine synthase reductase (MTRR 66A→G; rs#1801394), methylenetetrahydrofolate dehydrogenase (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, while categorical variable differences were assessed by χ2-tests.

Relative risks (RR) and 95% confidence intervals (95%CI) for colorectal cancer 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, Cary, NC), stratified by the case-control set. In our study the relative risk indicated the incidence rate ratio, which is reflected by the odds ratio calculated from conditional logistic regression(57). The relative risks for CRC risk were examined by quintile categories with cut-off points based on the distribution of folate and homocysteine in all 2325 controls combined. Since 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, missing), alcohol consumption (continuous), dietary fiber (continuous), intake of red and processed meat (continuous), physical activity (inactive, moderately inactive, moderately active, active), educational level (none, primary school completed, technical/professional school, secondary school, university degree, not specified), and body mass index (BMI, kg/m2). Although none of these variables altered the risk estimates as obtained by the matched analysed, we present matched analyses which were further adjusted for these covariates in order 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 vs rectal), European region (North (Denmark, Sweden) vs Central (France, United Kingdom, the Netherlands, Germany) vs South (Italy, Spain, Greece)), time from blood donation to cancer diagnosis (≤ 3.6 (median follow-up time) yrs vs. > 3.6 yrs), age (≤ 60 yrs vs. > 60 yrs), sex, and alcohol intake (0-30 grams/day vs. ≥ 30 grams/day). Effect modification was tested by adding the product term of folate and potential effect modifiers in the model. All statistical tests were 2-tailed and p < 0.05 was considered statistically significant.

The associations between the polymorphisms and colorectal cancer 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-colorectal cancer 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 1367 cancer cases and 2325 matched controls. The sex distribution, and mean age at recruitment was comparable among cases and controls. The median (range) follow up time between blood donation and colorectal cancer diagnosis was 3.6 (0.0 – 10.3) years. Median folate concentrations in cases were slightly lower compared to their matched controls (P for difference = 0.08), whereas no differences in total homocysteine concentrations were observed between cases and controls (Table 1).

Table 1
Characteristics of Cohort Members

Data integrity

Table 2 shows folate and tHcy concentrations among the 2325 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 (P for all 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 (P all correlations <0.0001).

Table 2
Folate and Homocysteine Concentrations (mean/ median (P5 – P95)) by Selected Characteristics in control cohort members (n=2320)

Associations of folate with colorectal cancer

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 to overall colorectal cancer 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 vs. the lowest folate concentrations of 0.56 ((0.29; 1.09), 0.04) (data not shown). Total homocysteine 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 relative risks (95% CI)* for colorectal cancer by quintiles of plasma folate concentrations

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 less than 30 g alcohol/day, the RR ((95% CI), Ptrend) for the fifth vs. the first quintile of folate status for males was 0.79 ((0.52 to 1.23), 0.19), and for females 0.96 ((0.67 1.37), 0.73). Among those drinking more than 30 g alcohol/day, the RR ((95% CI), Ptrend) for the fifth vs. the first quintile of folate status for for males was 0.91 ((0.47 to 1.75, 0.87), and for females 2.59 (0.53 to 12.75), 0.47). The association between folate and CRC risk within different categories of alcohol intake did not differ by gender (Pinteraction <30 g alcohol/day = 0.56; Pinteraction ≥ 30 g alcohol/day = 0.15), and within each gender not by alcohol intake (Pinteraction males = 0.96; Pinteraction females = 0.15).

The folate related single nucleotide polymorphisms and their associations with CRC risk

All the SNPs were in Hardy-Weinberg equilibrium ([Hebrew letter Alef]2 test p-values > 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 with CRC risk (Ptrend=0.06). Compared with the SLC19A1 GG homozygotes, both the GA and AA genotypes were associated with significanctly 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 associations with CRC risk and MTHFR 677C→ T in 1298AA individuals, and MTHFR 1298A→ C association in 677CC individuals in order 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 colorectal cancer risk

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 to 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 to 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 to 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 vs. 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 vs. 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
Relative risks (95% CI)* for colorectal cancer in folate related SNPs by quintiles of plasma folate status

Table 6 shows that individuals with the MTHFR 677TT genotype who consumed ≥ 30 grams of alcohol/ day had a slight increased CRC risk (Ptrend 0.09) compared to 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 (P interactions > 0.31; data not shown).

Table 6
Relative risks (95% CI) for colorectal cancer with MTHFR 677C→T in subgroups of alcohol consumption and folate status


In this large European Prospective Investigation into Cancer and Nutrition (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 so far, and its large sample size allowed us to perform subgroup analyses. Extensive information on lifestyle factors has been collected for each cohort member, which allowed adjustment for potential confounders and assessment of possible effect modification. Another important strength of this study is the collection of blood samples prior to cancer diagnosis. All study centers collected and stored blood samples according to a standardized protocol (43), and all biochemical analyses were performed 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 multi-country 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 to 5% and 8% in Central and Southern Europe, respectively. Moreover, mean plasma folate concentrations were lower in Northern European countries compared to 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, even though 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 > 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 since 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 which 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), a number of small randomised placebo-controlled intervention studies on surrogate endpoints 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 therefore not 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 US 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 epidemiological (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 hypothesised dual effect of folate status.

The present study investigated SNPs which occurred in genes related to folate absorption, transport, and utilization (65). Two meta-analyses observed a CRC risk reduction of 7-17% in individuals with the MTHFR 677TT genotype compared to individuals with the 677CC genotype in worldwide populations (20, 21). However, stratification for geographical regions revealed moderate significant risk reductions in US and Asian studies, but a null-finding for European studies (20), which is in agreement 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 which requires confirmation in future studies.

In line with alcohol as a risk factor for colorectal cancer (66) and an antagonistic effect of alcohol on folate status (67), have many studies on folate intake (66, 68) and some on plasma folate (30, 40, 41) have demonstrated an increased CRC risk in individuals with low folate status and high alcohol consumption compared to 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 since 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 grams alcohol/day compared to 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 relative risks, 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 in order to elucidate potential time dependent associations between folate and CRC risk. In addition, larger sample sizes are needed to adequately investigate gene-environment interactions.


Financial support

This work was supported by the European Commission: Public Health and Consumer Protection Directorate 1993-2004; 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 (AIRC); 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; Foundation to promote research into functional vitamin B12-deficiency, Norway. We would like to 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.


Potential conflicts of interest:

None of the co-authors reported conflicts of interest


1. Kim YI. Folate and colorectal cancer: an evidence-based critical review. Mol Nutr Food Res. 2007;51:267–92. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
7. Kim YI. Folic Acid supplementation and cancer risk: point. Cancer Epidemiol Biomarkers Prev. 2008;17:2220–5. [PubMed]
8. Ulrich CM. Folate and cancer prevention--where to next? Counterpoint. Cancer Epidemiol Biomarkers Prev. 2008;17:2226–30. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
16. Finkelstein JD. The metabolism of homocysteine: pathways and regulation. Eur J Pediatr. 1998;157(Suppl 2):S40–4. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
20. Hubner RA, Houlston RS. MTHFR C677T and colorectal cancer risk: A meta-analysis of 25 populations. Int J Cancer. 2007;120:1027–35. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PMC free article] [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
34. Marugame T, Tsuji E, Inoue H, et al. Methylenetetrahydrofolate reductase polymorphism and risk of colorectal adenomas. Cancer Lett. 2000;151:181–6. [PubMed]
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. [PubMed]
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. [PubMed]
37. Van Guelpen B, Hultdin J, Johansson I, et al. Low folate levels may protect against colorectal cancer. Gut. 2006;55:1461–6. [PMC free article] [PubMed]
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. [PubMed]
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. [PubMed]
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. [PMC free article] [PubMed]
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. [PubMed]
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. [PubMed]
43. Riboli E, Kaaks R. The EPIC Project: rationale and study design. European Prospective Investigation into Cancer and Nutrition. Int J Epidemiol. 1997;26(Suppl 1):S6–14. [PubMed]
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. [PubMed]
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. [PubMed]
46. IARC Cancer Incidence in Five Continents. 1 edition Vol. 9. International Agency for Research on Cancer; Lyon: 2009. pp. 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. [PMC free article] [PubMed]
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. [PubMed]
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. [PubMed]
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. [PMC free article] [PubMed]
51. EPIC-European Prospective Investigation into Cancer and Nutrition. [Accessed on November 26, 2009].
52. Bergstralh EJ, Kosanke JL, Jacobsen SJ. Software for optimal matching in observational studies. Epidemiology. 1996;7:331–2. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
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 [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
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. [PubMed]
62. Trends in wheat-flour fortification with folic acid and iron--worldwide, 2004 and 2007. MMWR Morb Mortal Wkly Rep. 2008;57:8–10. [PubMed]
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. European Communities; Brussels, Belgium: 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. [PubMed]
65. Molloy AM. Folate and homocysteine interrelationships including genetics of the relevant enzymes. Curr Opin Lipidol. 2004;15:49–57. [PubMed]
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. [PubMed]
67. Hillman RS, Steinberg SE. The effects of alcohol on folate metabolism. Annu Rev Med. 1982;33:345–54. [PubMed]
68. Giovannucci E. Alcohol, one-carbon metabolism, and colorectal cancer: recent insights from molecular studies. J Nutr. 2004;134:2475S–81S. [PubMed]