Journal of Cancer Epidemiology

Journal of Cancer Epidemiology / 2012 / Article

Review Article | Open Access

Volume 2012 |Article ID 952508 | https://doi.org/10.1155/2012/952508

Deborah A. Kennedy, Seth J. Stern, Ilan Matok, Myla E. Moretti, Moumita Sarkar, Thomasin Adams-Webber, Gideon Koren, "Folate Intake, MTHFR Polymorphisms, and the Risk of Colorectal Cancer: A Systematic Review and Meta-Analysis", Journal of Cancer Epidemiology, vol. 2012, Article ID 952508, 24 pages, 2012. https://doi.org/10.1155/2012/952508

Folate Intake, MTHFR Polymorphisms, and the Risk of Colorectal Cancer: A Systematic Review and Meta-Analysis

Academic Editor: P. Vineis
Received23 Mar 2012
Revised26 May 2012
Accepted26 May 2012
Published18 Oct 2012

Abstract

Background. The objective was to determine whether relationships exist between the methylene-tetrahydrofolate reductase (MTHFR) polymorphisms and risk of colorectal cancer (CRC) and examine whether the risk is modified by level of folate intake. Methods. MEDLINE, Embase, and SCOPUS were searched to May 2012 using the terms “folic acid,” “folate,” “colorectal cancer,” “methylenetetrahydrofolate reductase,” “MTHFR.” Observational studies were included which (1) assessed the risk of CRC for each polymorphism and/or (2) had defined levels of folate intake for each polymorphism and assessed the risk of CRC. Results. From 910 references, 67 studies met our criteria; hand searching yielded 10 studies. The summary risk estimate comparing the 677CT versus CC genotype was 1.02 (95% CI 0.95–1.10) and for 677TT versus CC was 0.88 (95% CI 0.80–0.96) both with heterogeneity. The summary risk estimates for A1298C polymorphisms suggested no reduced risk. The summary risk estimate for high versus low total folate for the 677CC genotype was 0.70 (95% CI 0.56–0.89) and the 677TT genotype 0.63 (95% CI 0.41–0.97). Conclusion. These results suggest that the 677TT genotype is associated with a reduced risk of developing CRC, under conditions of high total folate intake, and this associated risk remains reduced for both MTHFR 677 CC and TT genotypes.

1. Introduction

Worldwide, colorectal cancer (CRC) is the third most frequently diagnosed cancer in males and the second in females [1]. Australia and New Zealand, Europe and North America have the highest incidence rates of CRC worldwide, and Africa and South-Central Asia, the lowest [1, 2]. Over 75% of CRCs occur sporadically, with only 25% of patients having a family history of CRC [3].

Folate insufficiency has been suggested as one of the possible mechanism for CRC development and progression. DNA strand breaks, impaired DNA methylation and repair have been associated with folate deficiency and CRC [47]. There are many enzymes involved with folates and one-carbon metabolism; however, the methylene tetrahydrofolate reductase (MTHFR) enzyme is a key enzyme responsible for determining whether reduced folates are directed towards DNA methylation pathways or pyrimidine or purine synthesis [8]. In 1995, a variant of MTHFR enzyme was identified which causes a substitution of C to T at nucleotide 677 [9]. The MTHFR C677T homozygous variant (TT genotype) is thermolabile, and its activity is reduced by 70% compared to the wild type (CC genotype) [10]. This reduced enzyme activity causes an accumulation of plasma homocysteine and higher rates of thymidylate synthesis [10, 11].

The distribution of the TT genotype varies from country to country. In Europe, there would appear to be a north-south gradient with the distribution of the TT genotype lowest in the north [12, 13] while in Asia, the frequency is highest in China and lowest in India [12, 1418]. In North America, African Americans have a much lower TT genotype frequency versus Caucasians [19]. Individuals with this variant are thought to be at greater risk for a number of diseases including cardiovascular disease, acute lymphocytic leukemia, and neural tube defects [10]. Some published studies have suggested that those with the TT genotype have a reduced risk of CRC versus those with the CC genotype (wild type) [2028]; however, other studies have found an increased risk [2931].

A second variant of the MTHFR enzyme, with a substitution of A to C at nucleotide 1298, has also been identified. Unlike the MTHFR C677T polymorphism, the enzyme activities of the variants of MTHFR A1298C polymorphism are not thermolabile, but the enzyme activity is reduced by approximately 40% of the wild type (AA genotype) in the variant genotype. Altered homocysteine levels have not been found in individuals with these variants [32]. The prevalence of the 1298CC genotype varies, with the homozygous genotype found in 7–12% of Caucasians, in Europeans, 4–12%, while in China, Japan, and Hawaiian studies the prevalence ranged between 1 and 4% [32, 33].

The objective of this effort was to conduct a systematic review and meta-analysis of the published data to determine whether relationships exist between the various MTHFR polymorphisms and the incidence of CRC. A secondary objective was to examine whether there exists a relationship between the level of folate intake for each MTHFR genotype and the risk of CRC.

2. Methods and Materials

2.1. Inclusion Criteria

We selected observational studies reporting on the polymorphisms of the MTHFR C677T and/or A1298C genes and the associated risk of CRC, colon, or rectal cancer in adult populations. Studies were also included if they reported on folate exposure (dietary or total) with at least two levels of folate intake and the associated rates of colorectal, colon and/or rectal cancer by genotype. Studies were excluded if they did not provide the information necessary to determine an odds ratio and 95% confidence interval for each genotype. No restrictions were placed on language of publication or country of study.

2.2. Search Strategy

The databases MEDLINE, Embase, and Scopus on the OVID platform were searched from inception to May 2012. Both database-specific subject headings and text words were searched using the terms “folic acid” OR “folate” and “colorectal cancer” and “colorectal neoplasms” AND “methylenetetrahydrofolate reductase or MTHFR or C667T” limiting the results to humans only. The results of the search in each of the three databases were placed in a bibliography tool, and, in order to ensure blinding, an extract of author, title, and year information was made and uploaded into a spreadsheet for the purposes of title review. Title review was conducted by one reviewer (DAK) blinded to the journal of publication, place of research, and results, to determine which study articles to retrieve. The methods section of the selected journal articles were retrieved by other team members (MS and IM) not responsible for reviewing the journal articles. The method sections were reviewed by two independent reviewers (DAK, SJS) blinded to the journal of publication, place of research, and results as to their meeting the inclusion criteria. In case of disagreement between the two reviewers, a third reviewer served as a tiebreaker (GK). Previous reviews were also hand searched to identify other relevant publications to include.

2.3. Data Extraction

Data extraction was carried out by one reviewer and independently checked for accuracy by a second reviewer. Data collected included the type of study, location, study inclusion and exclusion criteria, case and comparator group size, folate intake levels, odds ratio or risk ratio, the number, for both case and control, and percentage frequency of each genotype, relevant adjustments, and conclusions. The genotype distribution of the control group was evaluated for agreement with the Hardy-Weinberg equilibrium (HWE) using chi-squared with a significant level of 0.05 and the results incorporated into Table 1.

(a) Characteristic of studies included in the systematic review and meta analysis.

StudyCountryYearStudy designSource of controlsRecruitment periodCancerSexCase/control Distribution of MTHFR C677T genotype in controlsHWE (yes/no) Distribution of MTHFR A1298C
genotype in controls
HWE (yes/no)Adjustments
CC (%)CT (%)TT (%)AA (%)AC (%)CC (%)

Park et al. [34]South Korea1999Case controlHealthy personsNot reportedCRCBoth200/46030.453.516.1NoCalculated OR, no adjustments

Delgado-Enciso et al. [15]Mexico2001Case controlNot reported1997CRCBoth74/11030.947.321.8YesCalculated OR, no adjustments

Keku et al. [35]USA2002Case controlHealthy persons1996–2000Colon-CaucBoth555/87549.241.49.4Yes 52.538.59.3YesAdjusted for sampling fraction, age, gender, and energy intake

Le Marchand et al. [23]USA2002Matched case controlHealthy persons1994–1998CRCBoth727/72739.24515.8Yes58.236.05.8NoAdjusted for age, gender, ethnicity, pack years of cigarette smoking, lifetime recreational physical activity, lifetime aspirin use, BMI 5 years ago, years of schooling, and intakes of nonstarch polysaccharides from vegetables and calcium from foods and supplements

Matsuo
et al. [16]
Japan2002Case controlHospital patients1999CRC
colon
rectal
Both142/241
72/241
70/241
33.651.514.9Yes65.131.13.7YesAdjusted for age

Shannon
et al. [36]
Australia2002Case controlHealthy persons1985–1998CRCBoth501/
1,207
44.246.49.4YesCalculated OR, no adjustments

Plaschke
et al. [37]
Germany2003Case controlHealthy personsNot reportedCRCBoth287/34643.145.911Yes44.543.611.8YesAdjusted for gender

Pufulete
et al. [38]
United Kingdom2003Case controlHospital patients2000-2001CRCBoth304/35254388Yes61.834.23.9YesAdjusted for age, gender, BMI, smoking, and ROH intake.

Toffoli
et al. [39]
Italy2003Case controlHealthy persons1999-2000ColonBoth276/27929.750.220.1Yes47.743.49YesCalculated OR, no adjustments

Jiang et al. [40]China2004Case controlHealthy person1990–2002CRCBoth126/34339.142.418.5No67.630.71.8YesAdjusted for age and sex

Miao et al. [41]China2005Case controlHealthy persons1999–2002CRCBoth198/42031.747.920.5Yes67.131.41.4NoNone reported

Ulvik et al. [20]Norway2004Nested case controlHealthy persons1992-1991CRCBoth2,168/
2,168
49.940.49.7YesAdjusted for age and gender

Yin et al. [21]Japan2004Case controlHospital patients2000–2003CRCBoth685/77835.747.217.1Yes66.231.42.4YesAdjusted for gender. 5-year age class, area and alcohol use

Jiang
et al. [42]
China2005Nested case controlHealthy persons1989-1990Colon
rectal
Both52/338
72/338
39.542.2 18.3No67.530.71.8NoAdjusted for gender, age, folate, methionine, total energy intake, smoking status, and drinking status

Landi et al. [43]Spain2005Case controlHospital patients1996–1998CRCBoth359/32035.34519.7Yes53.339.86.9YesAdjusted for age and sex

Matsuo
et al. [44]
Japan2005Matched case controlHospital patients2001–2004CRCBoth257/77137.545.117.3Yes62.533.54.0YesAdjusted for age, sex, referral patterns, smoking BMI, physical, exercise and family history of CRC

Otani et al. [45]Japan2005Matched case controlHospital patients1998–2002CRCBoth107/2242351.425.6Yes69.628.12.2YesMatching factors and adjusted for smoking, alcohol consumption, BMI, and total dietary fiber intake

Le Marchand
et al. [46]
USA
(Hawaii and California)
2005Nested case controlHealthy persons1993–1996CRC
colon
rectal
Both822/
2,021
48.938.512.6NoAdjusted for age, gender, and ethnicity

Battistelli et al. [47]Italy2006Case controlHealthy controlsNot reportedCRCBoth93/100305129YesCalculated OR, no adjustments

Van Guelpen
et al. [24]
Sweden2006Nested case controlHealthy persons1985–2002CRCBoth226/43752.838.78.5Yes45.942.012.1YesAdjusted for BMI, smoking, recreational and occupational physical activity, and alcohol intake

Wang et al. [48]India2006Case controlHealthy persons1999–2001CRC
colon
rectal
Both435/34087.612.40Yes36.146.417.5YesAdjusted for gender, age household income, education, religion, mother tongue, smoking, drinking, chewing, and vegetarianism

Lima
et al. [49]
Brazil2007Case controlHealthy persons1999–2001CRCBoth102/30047.742.310Yes63.731.05.3YesAdjusted for age, gender, and race

Chang
et al. [50]
Taiwan2007Matched case controlHospital patients2000-2001CRCBoth195/19547.244.68.2Yes61.533.35.1YesMatched on age and gender.

Curtin
et al. [51]
USA2007Matched case controlHealthy persons1991–1994ColonBoth916/
1,972
45.043.511.5Yes47.141.911YesCalculated OR, no adjustments

Hubner et al. [52]United Kingdom2007Case controlHealthy controlsNot reportedCRCBoth1,685/
2,695
43.644.312.1YesAdjusted for age, sex, family history, cancer location, stage, and grade

Jin et al. [53]China2007Case controlHealthy controls2002–2005CRCBoth449/67231.448.420.2YesAdjusted for age, sex, drinking, BMI, smoking, and family history

Murtaugh
et al. [54]
USA2007Matched case controlHealthy persons1997–2001Rectal-Men
Rectal-Women
Both
Men
Women
751/97948.2
47.5
40.1
41.4
11.7
11.1
No44.943.711.3YesAdjusted for age, BMI, activity, energy, fiber, calcium, ibuprofen use, smoking, and other MTHFR genotype

Osian et al. [55]Romania2007Matched case controlHospital patients2003–2005CRCBoth69/6770.225.44.5Yes61.137.31.5YesMatched on age and sex

Zeybek
et al. [17]
Turkey2007Case controlHospital patients2003–2005CRCBoth52/14444.445.110.4YesCalculated OR, no adjustments

Cao et al. [56]China2008Matched case controlHealthy persons2000–2002CRCBoth315/37132.749.517.8Yes64.432.13.5YesMatched on ethnicity, sex, and age

Küry et al. [57]France2008Matched case controlHealthy persons2002–2006CRCBoth1,023/1,12140.845.913.3Yes51.539.59YesMatched on age and sex

Lightfoot
et al. [58]
United Kingdom2008Matched case controlHospital patients1997–2000CRCBoth468/73445.8468.3Yes48.643.77.8YesAdjusted for gender and age

Mokarram
et al. [59]
Iran2008Case controlNot reported2003–2005ColonBoth151/8149.438.312.3YesCalculated OR, no adjustments

Sharp
et al. [60]
United Kingdom
(Scotland)
2008Matched case controlHealthy persons1998–2000CRCBoth264/40843.244.911.9Yes44.939.815.2NoAdjusted for age, gender, family history of CRC, physical activity, NAAID use, total energy intake, and type of dietary supplements

Theodoratou
et al. [61]
Scotland2008Case controlHealthy persons1999–2006CRCBoth2,028/
2,722
45.345.011.5Yes45.844.110.1YesAdjusted for age, sex, deprivation score, and family history risk

Zhang
et al. [62]
China2008Matched case controlHospital patients2003–2005CRCBoth300/30030.446.523.1Yes65.329.75YesAdjusted for age, sex, education, family history, smoking, and drinking.

El Awady
et al. [63]
Egypt2009Case controlHealthy persons2004–2007CRCBoth35/6865296Yes38548YesNone reported

Gallegos-Arreola
et al. [30]
Mexico2009Case controlHealthy persons2006–2008CRCBoth369/17033.634.132.2NoCalculated OR, no adjustments

Haghighi
et al. [22]
Iran2009Case controlHospital patients2004–2007CRCBoth234/25736.631.132.3YesNone reported

Iacopetta
et al. [18]
Australia2009Matched case controlHealthy persons2005–2007Proximal distal CRCBoth850/958454510YesMatched on gender, age, socioeconomic status, country of birth, educational level, and smoking status

Chandy
et al. [14]
India2010Matched case controlHealthy persons2006–2008CRCBoth100/8676.722.11.2Yes25.658.116.3YesMatched on age and gender

Cui et al. [28]South Korea2010Case controlHospital patients2004–2008CRCBoth1,829/
1,700
31.850.717.5YesAdjusted for age and sex

Eussen et al. [64]EPIC 2010Nested case controlHealthy persons1992–1998CRCBoth1,367/
2,325
43.145.511.5Yes46.542.611.0YesCalculated OR, no adjustments

Fernández-Peralta et al. [65]Spain2010Matched case controlHealthy persons1992–1996CRCBoth143/10342.748.68.7Yes55.342.71.9NoMatched on age and sex

Karpinski
et al. [66]
Poland2010Case controlHealthy personsNot reportedCRCBoth186/140513910YesAdjusted for age and sex

Komlósi et al. [67]Hungary2010Case controlHealthy persons2001–2007Colon
rectal
Both
Both
476/461
479/478
47
47
40
41
13
12
Yes
Yes
Adjusted for sex, age, and BMI
Adjusted for sex, age, and BMI

Naghib alhossaini
et al. [68]
Iran2010Case controlNot reportedNot reportedCRCBoth151/23042.4534.6Yes42.545.711.8YesAdjusted for age, sex, and smoking status

Promthet
et al. [69]
Thailand2010Matched case controlHealthy persons2002–2006ColonBoth130/13072.323.83.9Yes41.554.63.9NoMatched on age and sex

Wettergren
et al. [70]
Sweden2010Case controlHealthy persons1994–2004CRCBoth181/30055.935.88.4YesCalculated OR, no adjustments

Abuli et al. [71]Spain 2011Matched case controlHealthy person2000-2001CRCBoth515/51538.14813.9YesMatched on age and sex

Guimarães et al. [72]Brazil2011Case controlHealthy persons1992–2003CRCBoth113/18848.942.09Yes67.626.16.4NoAdjusted for age, sex, and ethnic origin

Jokić et al. [73]Croatia2011Case controlHealthy personsNot reportedColonBoth300/30047.343.39.3Yes46.742.710.6Yes

Pardini
et al. [25]
Czech Republic2011Case controlHospital patients2004–2006CRCBoth666/
1,377
44.545.69.9Yes42.346.311.3YesAdjusted for age and gender

Kim et al. [26]South Korea2011Case controlHospital patientsNot reportedCRCBoth67/5328.339.632.1Yes67.930.21.9YesNone reported

Sameer
et al. [74]
Kashmiri
(India)
2011Matched case controlHealthy persons2008-2009CRCBoth86/16075.616.97.5NoNone reported

Prasad and Wilkhoo [75]India2011Case controlHealthy personNot reportedCRCBoth110/24194.65.00.4YesNone reported

Zhu et al. [29]China2011Case controlHealthy persons2006–2008CRCBoth86/10049.041.010YesNone reported

Kim et al. [27]South Korea2012Case controlHospital patients1998–2004CRCBoth787/65631.344.124.7NoAdjusted for age, sex, family history, multivitamin use, BMI, smoking status, and total energy

Lee et al. [76]USA2012Nested case controlHealthy personsHealth professionals follow-up studyCRCMen173/3454439.916Yes47.742.610.3YesRR’s reported, so OR’s are calculated, no adjustments

Lee et al. [76]USA2012Nested Case ControlHealthy personsPhysicians’ health studyCRCMen240/40847.737.215Yes45.842.212.1YesRR’s reported, so OR’s are calculate, no adjustments

Lee et al. [76]USA2012Nested Case ControlHealthy personsNurse Health StudyCRCWomen189/37746.739.713.6Yes5138.310.7YesRR’s reported, so OR’s are calculated no adjustments

AA: African American, BMI: body mass index, Cauc: Caucasian CRC: colorectal cancer, HWE: Hardy Weinberg equilibrium, NSAID: nonsteroidal anti-inflammatory drug, OCP: oral contraceptive pill.
(b) Summary of cohorts studies.

Incidence rate ratio (RR) of CRC (95% CI)
StudyCountryYearStudy designSource of controlRecruitment periodCancerSexCase/controlFollow-up periodCT versus CCTT versus CCAC versus AACC versus AA

De Vogel et al. [77]Netherlands2009CohortHealthy personsRecruited in 1986CRCBoth689/1,7937.3 years1.23 (1.02–1.50)0.80
(0.56–1.15)
0.89
(0.72–1.09)
1.05
(0.79–1.38)
Adjusted for age and sex

Heijmans et al. [78]Netherlands2003CohortElderly healthy menRecruited in 1985CRCBoth18/79310 years1.16 (0.41–3.30)3.65
(1.97–12.5)
Adjusted for age

The Downs and Black scoring instrument was used to determine the quality of the studies included in this paper. The Down and Black scoring tool provides a means to assess the quality of a study based on 5 subscales (1) reporting of the study results, (2) external validity for the purposes of assessing generalizability of the findings, (3) bias in measurement and outcomes, (4) bias in the selection of study subjects, and (5) the power of the study [79]. The score was independently calculated for each study by two team members. Disagreements were resolved by consensus. The last question on the Downs and Black tool relates to the power of the study. If a priori power calculation was reported in the paper, this question was scored with a one, otherwise, zero was scored.

2.4. Statistical Analysis

The meta-analysis for the genotype risk comparisons was performed using the inverse variance method under a random effects model, odds ratios (ORs) along with 95% confidence intervals (CIs) were used for the case control studies according to the DerSimonian and Laird method [80]. All identified studies with available data were included in the summary effect estimate for each genotype combination. For the meta-analysis of the risk of CRC associated with genotype, the wild type (677CC or 1298AA) was used as the reference group, and comparisons were made to either the heterozygous (677CT or 1298AC) or homozygous variant type (677TT or 1298CC). If studies grouped genotypes together for comparison purposes, or did not report ORs and 95% confidence intervals and the raw numbers were available in the paper, unadjusted ORs and associated 95% confidence intervals were calculated according to the method described by Silman and MacFarlane [81]. These are identified in Table 1 as “OR calculated, no adjustments” in the column titled Adjustments. The meta-analyses were performed using Review Manager 5.1 Software [82].

The meta-analyses for the comparison of high versus low folate intake and the associated risk of CRC were performed using the inverse variance method under a random effects model, odds ratios (ORs) along with 95% confidence intervals (CIs) were calculated according to the DerSimonian and Laird method [80]. All identified studies with available data were included in the summary effect estimate for each high versus low folate intake within a genotype. For those studies that compared folate intake by “quantile” and assessed the risk of CRC by genotype, many used the 677CC or 677CC/CT lowest folate intake quantile as the reference group to determine the OR for all genotypes and folate intake levels. For the purposes of this analysis, however, the desire was to compare the risk of CRC between the highest folate intake to lowest folate intake within a genotype. The method described by Hamling et al. and the associated MS Excel spreadsheet, which recalculates the adjusted odds ratios permitting alternative comparisons, were used to derive the ORs of highest compared to the lowest folate intake within the genotype [83, 84]. This analysis was performed using Microsoft Excel (Microsoft Corporation (2007), Redmond, WA, USA). An analysis of folate intake and CRC risk for the MTHFR A1298C gene was not possible due to an insufficient number of studies reporting on this data. In performing this analysis, the result from the highest “quantile” identified in the study was used to compare the lowest “quantile” in the study. Dietary folate intake for the lowest “quantile” ranged from a low of less than 115.6 to 406 mcg/day; the range for the highest was from 320 to 485 mcg/day or more. Although these ranges do overlap, they represent the highest and the lowest folate intake for the study population upon which the specific study odds ratios were derived. The meta-analyses were performed using Review Manager 5.1 Software [82].

Publication bias was assessed via the Begg and Mazumdar’s rank correlation test, Egger’s linear regression, and the Trim and Fill methods [8587]. The assessment of publication bias was performed using the Comprehensive Meta-analysis (CMA) software (Biostat, Version 2.2, Englewood, NJ, USA) [88]. Summary effect estimates from CMA were compared with the RevMan results to ensure that they were both in agreement prior to executing the tests for publication bias.

Assessment of heterogeneity was performed using both Cochran’s and . The Cochran’s test assesses whether the differences in results are due to chance only [89]. Heterogeneity exists when the value is low, that is, [89]. The statistic is the percentage of variability in the effect estimates that is due to heterogeneity rather than chance. An statistic value over 50% indicates that substantial heterogeneity may be present [89]. The analysis was performed using Review Manager 5.1 software [82].

Kruskal-Wallis was performed on the quality of the studies to determine whether there were differences in the quality of the studies based on the directionality of the outcome. For the purposes of this analysis, directionality was assessed as positive (statistical significant ), neutral (nonsignificant OR), or negative (statistical significant ). IBM’s SPSS for Windows version 17 was used for the analysis (IBM SPSS, Version 17, Chicago, IL, USA).

The Forest plots of the MTHFR C677T and A1298C (Figures 2 through 5) were sorted according to the percentage of the comparator genotype (either 677CT, 677TT, 1298AC, or 1298CC) in the control group, from highest to lowest, while the remaining Forest plots (Figure 6) were organized by increasing year of publication.

3. Results

The pooled search resulted in 910 records. Of these 67 met our inclusion criteria, 10 studies were found on hand searching (Figure 1). Four identified studies were not included in the paper. In two studies, newborns comprised either all or part of the control group, which suggested that these studies were related to the determination of the prevalence of genotypes rather than risk of CRC since few newborns have had the opportunity to develop colorectal cancer [8, 92]. The remaining two studies did not report the separate case control numbers for each genotype; therefore, ORs could not be calculated for all genotypes; however the folate intake results, reported on in one of these studies, are included in the high versus low folate intake analysis [31, 93]. The majority of the studies included in the systematic review and meta-analysis were case control or nested case control studies, two cohort studies were identified (Table 1). The meta-analysis results presented here update two previously published meta-analyses on MTHFR polymorphisms and the risk of colorectal cancer, that of Taioli et al. 2009 meta-analysis on the MTHFR C677T polymorphisms and Kono and Chen’s 2005 meta-analysis on the MTHFR A1298C polymorphisms [94, 95]. All case control studies, with available data, were included in the meta-analysis, regardless of the quality score.

Study results were reported from twenty-five countries: Asia (China, India, Japan, South Korea, Taiwan, and Thailand), Australia, Europe (EPIC Cohort (10 European Centers), Czech Republic, Croatia, France, Germany, Hungary, Italy, Norway, Poland, Romania, Spain, Sweden, and United Kingdom), Latin America (Mexico), Middle East (Egypt, Iran, and Turkey), South America (Brazil), and USA. Six papers were written in another language with an English abstract: five in Chinese: the other in Spanish [31, 40, 41, 53, 62, 93]. When duplicate studies were found, for example, Nurses’ Health study and Health Professionals study, only the most recently published results were used in this analysis. There were five studies whose recruitment period was during the early days of folate fortification in USA; otherwise none of the studies were conducted in an environment of food fortification [35, 54, 76]. A blood sample was the most often used medium to assess genotype. There were two studies that used buccal samples as the tissue source for genotyping [18, 60].

3.1. Colorectal Cancer Risk and MTHFR C677T Genotype

For the comparison of 677CT versus 677CC, the summary risk estimate of the adjusted ORs was 1.02 (95% CI 0.95–1.10), , , , with significant heterogeneity (Figure 2). For the comparison of 677TT versus 677CC genotype, the summary risk estimate was 0.88 (95% CI 0.80–0.96) , , , with significant heterogeneity (Figure 3). Two studies, Wang et al and Promthet et al., did not have any case participants with a TT genotype [48, 69].

3.1.1. Subgroup Analysis

Subgroup analysis was performed on sex. The pooled summary risk estimate of the studies reporting on sex for 677CT versus 677CC was 1.04 (95% CI 0.94–1.16), , , , and 677TT versus 677CC was 0.87 (95% CI 0.75–1.01), , , , with heterogeneity (Table 2). The summary risk estimates for CRC risk between 677CT versus 677CC for men only were 1.12 (95% CI 0.94–1.34), , , , with significant heterogeneity (Table 2) and for women only 0.98 (95% CI 0.85–1.12), , , , (Table 2). The summary risk estimates for 677TT versus 677CC for men were 0.87 (95% CI 0.74–1.02), , , , (Table 2) and for women only were 0.92 (95% CI 0.65–1.31), , , , with significant heterogeneity (Table 2).


Number of studiesNumber of participants in case/control Summary effect estimate 95% CI Tests for heterogeneity
CC genotypeComparator genotype

Subgroup by sex

Pooled studies for sex (%)
 CT versus CC111,650/1,8331,420/1,5231.040.94–1.16χ² = 14.28, df = 10 (P = 0.16)30
 TT versus CC111,650/1,833326/4250.870.75–1.01χ² = 14.01, df = 10 (P = 0.17)29
Men
 CT versus CC91,257/1,436§1,081/1,199§1.120.94–1.34χ² = 18.68, df = 8 (P = 0.02)57
 TT versus CC91,257/1,436§271/346§0.870.74–1.02χ² = 8.36, df = 8 (P = 0.40)4
Women
 CT versus CC8755/897§627/773§0.980.85–1.12χ² = 7.63, df = 7 (P = 0.37)8
 TT versus CC8755/897§162/217§0.920.65–1.31χ² = 20.74, df = 7 (P = 0.004)66

Subgroup by cancer type

Pooled studies
 CT versus CC273,735/6,7673,403/6,3071.010.95–1.08χ² = 23.65, df = 26 (P = 0.60)0
 TT versus CC24*3,735/6,767886/2,1170.800.71–0.89χ² = 31.45, df = 23 (P = 0.11)27
Colon cancer studies
 CT versus CC162,096/4,4631,933/4,0901.010.93–1.10χ² = 11.23, df = 15 (P = 0.74)0
 TT versus CC14**2,096/4,463452/1,3520.760.64–0.91χ² = 22.79, df = 13 (P = 0.04)43
Rectal cancer studies
 CT versus CC111,639/3,2911,470/2,9961.100.92–1.31χ² = 27.95, df = 10 (P = 0.002) 64
 TT versus CC101,639/3,291386/1,0200.820.72–0.94χ² = 8.38, df = 9 (P = 0.50)0

Subgroup by location

Asian countries
 CT versus CC222,640/3,4012,985/3,9030.980.89–1.06χ² = 23.98, df = 21 (P = 0.29)12
 TT versus CC20**2,640/3,4011,001/1,5650.830.69–1.01χ² = 49.66, df = 19 (P = 0.0001)62
European countries
 CT versus CC225,480/6,9605,374/6,8571.000.87–1.13χ² = 109.92, df = 21 (P < 0.00001)81
 TT versus CC225,480/6,9601,294/1,7930.920.80–1.06χ² = 43.74, df = 21 (P = 0.003)52
USA
 CT versus CC82,011/3,3551,932/2,9970.980.90–1.07χ² = 6.07, df = 7 (P = 0.53)0
 TT versus CC82,011/3,355436/1,0550.730.63–0.84χ² = 1.91, df = 7 (P = 0.96)0
Middle Eastern countries
 CT versus CC5277/374274/3021.460.62–3.46χ² = 45.30, df = 4 (P < 0.00001)91
 TT versus CC5277/37472/1050.690.42–1.13χ² = 5.56, df = 4 (P = 0.23)28

Subgroup by control

Healthy person controls
 CT versus CC458,706/12,9588,043/12,0441.020.94–1.11χ² = 154.26, df = 44 (P < 0.00001)71
 TT versus CC43**8,706/12,9582,136/3,6360.900.81–1.00χ² = 88.37, df = 42 (P = 0.0001)52
Hospital patient controls
 CT versus CC162,418/2,8632,932/3,6190.930.83–1.05χ² = 27.35, df = 15 (P = 0.03)45
 TT versus CC162,418/2,863939/1,2540.820.68–1.00χ² = 36.07, df = 15 (P = 0.002)58

§Not all studies reported both case and control numbers.
*There were two studies without TT genotype information, one study with rectal cancer data, and two studies with colon cancer data.
**There were two studies that had 0 people for the TT genotype.
CRC: colorectal cancer.

Separate estimates for colon cancer and rectal cancer were also evaluated. For the summary risk estimates related to colon or rectal cancer, only those studies that reported separate results for either colon or rectal cancer were included. The pooled summary risk estimate of the studies reporting on either colon or rectal cancer only for 677CT versus 677CC was 1.01 (95% CI 0.95–1.08) , , and 677TT versus 677CC was 0.80 (95% CI 0.71–0.89) , , , with some heterogeneity evident (Table 2). The summary risk estimates for 677CT versus 677CC colon cancer only were 1.01 (95% CI 0.93–1.10), , , , (Table 2) and 677TT versus 677CC colon cancer only 0.76 (95% CI 0.64–0.91 , ,   , (Table 2). The summary risk estimates for 677CT versus 677CC rectal cancer only were 1.10 (95% CI 0.92–1.31), ,   , , (Table 2) and 677TT versus 677CC rectal cancer only 0.82 (95% CI 0.72–0.94), , , , (Table 2).

3.1.2. Sensitivity Analysis

In an attempt to identify the studies contributing to the heterogeneity in the genotype summary risk effect results, sensitivity analysis was performed according the sequential algorithm proposed by Patsopoulos and colleagues [96]. This method involves sequentially dropping one study from the meta-analysis to determine the impact on the statistic with the objective of identifying the study or studies that will reduce the below a set threshold. Using this method, we were not successful in reducing the heterogeneity below the threshold value of an value of less than 25%, which would have suggested that there was minimal heterogeneity in the results.

Given that the typical diets of Asian cultures can be substantially different from that of Europe and North America, separate analyses were conducted including just the studies in the Asian locations (China, India, Japan, South Korea, and Taiwan), separate from the European locations (Czech Republic, Croatia, European EPIC study, France, Germany, Hungary, Italy, Norway, Poland, Romania, Spain, Sweden, and United Kingdom), USA, and Middle East (Egypt, Iran, and Turkey) (Table 2). The protective effect of the 677TT genotype was sustained in each geography; however, only in the USA was the risk reduction significant with no heterogeneity.

A further analysis was performed by comparing the results based on the source of controls: either hospital patients or healthy persons. The heterogeneity was sustained (Table 2).

3.1.3. Publication Bias

Publication bias was assessed using three different tests: Begg and Mazumdar’s rank correlation test, Egger’s linear regression, and the Trim and Fill methods. For the MTHFR 677CT genotype there may be some evidence for publication bias. The Begg and Mazumdar test returned a value 0.03, Egger’s a value 0.005, and Trim and Fill found that an additional 12 studies would be necessary to form a symmetrical funnel plot. Whereas, for the MTHFR 677TT genotype, the Begg and Mazumdar test returned a value 0.33, Egger’s a value 0.38, and Trim and Fill found that additional 4 studies would be necessary to form a symmetrical funnel plot, suggesting that publication bias may not be significant concern.

3.1.4. Correlation between Study Quality versus Results

There was no statistically significant difference found in the quality of the studies based on outcome (positive versus neutral versus negative) ( ).

3.2. Colorectal Cancer Risk and MTHFR A1298C Genotype

For the comparison of 1298AC versus 1298AA, the summary risk estimate was 1.03 (95% CI 0.96–1.10), , , , with some heterogeneity (Figure 4). For the comparison of 1298CC versus 1298AA genotype, the summary risk estimate was 0.93 (95% CI 0.82–1.06), , , , with heterogeneity (Figure 5).

3.2.1. Sensitivity Analysis

In an attempt to identify the studies contributing to the heterogeneity in the genotype summary risk effect results for 1298CC, the previously described process for sensitivity analysis was performed. The resulting summary effects estimate for 1298CC versus 1298AA was 1.04 (95% CI 0.94–1.14) , ,  , with no significant heterogeneity (data not shown). In this analysis, the studies contributing to the heterogeneity were conducted in Germany, India, and the USA [35, 37, 48, 54, 76].

3.2.2. Subgroup Analysis

There were an insufficient number of studies that reported CRC risk by sex; however, subgroups, by geography, and source of controls were performed.

Subgroup analysis by geography was performed for the MTHFR A1298C polymorphism according to the country groups previously described. There were an insufficient number of studies from the Middle East to include this location in the analysis. The subgroup analysis revealed that for European countries there was an associated, significant increased risk of CRC for those with the 1298CC genotype, while Asian and USA studies suggest a significant associated decrease in risk (Table 3). This variability in the associated risk of the 1298CC genotype by geography was also noted by Kono and Chen in their meta-analysis [95].


Number of studiesNumber of participants in case/control Summary effect estimate 95% CI Tests for heterogeneity
AA genotype Comparator genotype

Subgroup by location

Asian countries (%)
 AC versus AA151,727/3,047991/1,6150.990.84–1.16χ² = 26.56, df = 14 (P = 0.02)47
 CC versus AA14*1,727/3,047116/1780.720.55–0.93χ² = 14.37, df = 13 (P = 0.35)10
European countries
 AC versus AA142,971/4,1192,404/3,7461.050.97–1.14χ² = 14.78, df = 13 (P = 0.32)12
 CC versus AA142,971/4,119683/9081.141.01–1.28χ² = 13.13, df = 13 (P = 0.44)1
USA
 AC versus AA71,678/2,6941,365/2,2440.990.88–1.11χ² = 7.96, df = 6 (P = 0.24)25
 CC versus AA71,678/2,694247/5590.730.57–0.92χ² = 10.20, df = 6 (P = 0.12)41

Subgroup by control

Hospital controls
 AC versus AA121,872/2,7951,258/1,8741.05 0.95–1.16χ² = 4.42, df = 11 (P = 0.96)0
 CC versus AA121,872/2,795232/3111.120.88–1.42χ²= 13.22, df = 11 (P = 0.28)17
Healthy controls
 AC versus AA275,083/7,9393,926/6,3251.020.93–1.11χ²= 48.87, df = 26 (P = 0.004)47
 CC versus AA26*5,083/7,939912/1,4390.880.76–1.03χ²= 45.33, df = 25 (P = 0.008)45

*There was one study that had no results for this genotype.

A further analysis was performed by comparing the results based on the source of controls; either hospital patients or healthy persons. For the CC variant, the healthy controls had a nonsignificant reduced risk associated with CRC versus hospital control, within some increase in heterogeneity (Table 3).

3.2.3. Publication Bias

The results of the statistical test for publication bias for the MTHFR A1298C polymorphisms suggest that publication bias may not be a concern. For MTHFR 1298AC, the Begg and Mazumdar test returned a value 0.24, Egger’s a value 0.398, and Trim and Fill found that an additional 5 studies would be necessary to form a symmetrical funnel plot whereas, for the 1298CC genotype, the Begg and Mazumdar test returned a value 0.88, Egger’s a value 0.74, and Trim and Fill found that no additional studies would be necessary to form a symmetrical funnel plot.

3.3. Colorectal Cancer Risk and Combinations of the MTHFR C677T and A1298C Genotypes

The combinations of variants of the MTHFR C677T and A1298C genotypes are in linkage disequilibrium such that rarely are there individuals with the 677TT/1298AC and 677TT/1298CC combinations [95]. The results of the summary risk estimates for the remaining combinations are presented in Table 4. The combination of 677TT/1298AA was associated with lowest risk of CRC with a summary risk estimate of 0.77 (95% CI 0.58–1.03), , , , with significant heterogeneity.


Comparator genotype Number of studiesNumber of participants in case/control Summary effect estimate 95% CITests for heterogeneity
CC/AA genotype Comparator genotype§

I (%)
CC/AC12609/775677/8700.960.82–1.11χ² = 7.56, df = 11 (P = 0.75)0
CC/CC12609/775180/3120.900.64–1.27χ² = 21.33, df = 11 (P = 0.03)48
CT/AA12609/775753/9120.990.86–1.15χ² = 9.63, df = 11 (P = 0.56)0
CT/AC12609/775491/6781.060.79–1.44χ² = 30.68, df = 11 (P = 0.001)64
CT/CC5609/77518/361.400.33–6.03χ² = 7.78, df = 4 (P = 0.10)49
TT/AA12609/775311/4650.770.58–1.03χ² = 19.00, df = 11 (P = 0.06)42
TT/AC4609/77511/17N/a
TT/CC3609/7750/6N/a

§There was one study that did not report case control numbers for the combinations.
3.4. Colorectal Cancer Risk, Comparison of High versus Low Folate Intake by Genotype

Of the articles that met our inclusion criteria, there were 10 studies that reported on CRC risk by “quantile” of folate intake for the MTHFR C677T polymorphism; however, an insufficient number of studies reported on the folate intake for the A1298C polymorphism to complete the analysis for this polymorphism. A food frequency questionnaire (FFQ) was the usual method used to collect dietary intake information. Dietary information was captured for one to two years preceding diagnosis, or for the control group, at the time of enrolment in the study. The range of dietary folate intake, defined as folate from food sources, for the lowest “quantile” ranged from a low of less than 115.6 to 406 mcg/day; the range for the highest was from 320 to 485 mcg/day or more (Table 5). The summary risk estimate for high versus low dietary folate intake for the 677CC genotype was 0.76 (95% CI 0.62–0.94), , , , , for the 677CT genotype 0.88 (95% CI 0.76–1.02), , , , and the 677TT genotype 0.78 (95% CI 0.53–1.13), , , , (Figure 6).


StudyCountryYearStudy designPopulation of controlsRecruitment periodCancerGenderNumber of quantilesDietary folate (mcg/day)Total folate (mcg/day)Adjustments

Chen et al. [90]USA1996Nested case control Healthy persons1986–1994CRCMen3<317 versus >461Adjusted for age, family history, and intake of folate, methionine, and alcohol

Slattery et al. [91]USA1999Matched case controlHealthy persons1991–1994ColonBoth3<126 versus >197
per 1000 kcals
Adjusted for age, BMI, physical activity, energy intake, dietary fiber, and smoking

Le Marchand et al. [23]USA2002Matched case controlHealthy persons1994–1998CRCBoth3<278 versus >372<336 versus >1583Adjusted for age, gender, ethnicity, pack years of cigarette smoking, lifetime recreational physical activity, lifetime aspirin use, BMI 5 years ago, years of schooling, and intakes of nonstarch polysaccharides from vegetables and calcium from foods and supplements

Jiang et al. [42]China2005Nested case controlHealthy persons1989-1990Colon
rectal
Both4<115.6 versus >172
per 1000 kcals
Adjusted for sex, age, methionine, smoking status drinking status, and zinc

Le Marchand et al. [46]USA (Hawaii and California)2005Nested case controlHealthy persons1993–1996CRCBoth3<253 versus >412<322 versus >590Adjusted for age, gender, and ethnicity

Otani et al. [45]Japan2005Matched case controlHospital patients1998–2002CRCBoth3<343 versus >485Matching factors and adjusted for smoking, alcohol consumption, BMI, and total dietary fiber intake

Lightfoot et al. [58]United Kingdom2008Matched case controlHospital patients1997–2000CRCBoth3<267 versus >397Adjusted for gender, and age

Sharp et al. [60]United Kingdom2008Matched case controlHealthy persons1998–2000CRCBoth4<263.9 versus >348.6Adjusted for age, gender and total energy intake.

Guerreiro et al. [31]Portugal2008Case controlHealthy personsNot reportedCRCBoth2 ≤406.7>Adjusted for age, gender and CRC history

Haghighi et al. [22]Iran2009Case controlHospital patients2004–2007CRCBoth2 ≤320> ≤450>Not reported

BMI: body mass index, CRC: colorectal cancer.

Total folate intake information was also reported in some studies. Total folate was defined as folate from dietary and supplemental sources. The lowest “quantile” ranged from less than 264 to 450 mcg/day and the higher “quantile” ranged from 348 to 1583 mcg/day or more (Table 5). The summary risk estimate for high versus low total folate intake for the 677CC genotype was 0.70 (95% CI 0.56–0.89), , ,   , and the 677TT genotype 0.63 (95% CI 0.41–0.97), , , , (Figure 6). Only two studies had information available for the 677CT genotype; therefore, the summary risk estimate was not determined.

4. Discussion

The results of the analysis suggest that the homozygous variant genotype MTHFR 677TT confers a degree of protection against the development of CRC, affording an associated risk reduction of 12%. In contrast, the heterozygous genotype, MTHFR 677CT, was found to have the same risk as the genotype, MTHFR 677CC. These results are consistent with the previous meta-analysis completed in 2009 [94]. The thermolabile nature of MTHFR 677TT enzyme results in the reduced conversion of 5,10-methylene-tetrahydrofolate to 5-methyl-tetrahydrofolate, which acts as cofactor in the conversion of homocysteine to methionine, permitting a larger pool of 5,10-methylene-tetrahydrofolate for thymidylate biosynthesis. This protective effect would suggest that preferential availability of folates to contribute pyrimidine synthesis, and therefore a reduction in uracil misincorporation and subsequent DNA breaks, could be important in the pathogenesis of CRC [32].

This reduced risk of CRC for the 677TT genotype was not supported by all of the included studies. In several individual studies, the 677TT genotype was associated with an increased risk of CRC [2931]. The authors of these studies theorized that conditions of low folate intake, which is characteristic of the diet in these countries (Brazil, Mexico), may explain the increased risk found between the 677TT genotype and CRC. This would appear to be substantiated by the reduced risk apparent in the summary risk estimated for 677CC and 677TT genotypes when comparing high versus low total folate intake (Figure 6) and would suggest that folate intake can alter the risk of CRC. Evidence for the alteration of disease through adequate folic acid intake has been found in other situations. For example, a maternal MTHFR 677TT genotype is associated with a higher risk of having an offspring with a neural tube defect [97]. Increased folic acid supplementation, periconceptionally and during the first trimester, has been found to reduce this risk [98].

Many of the studies incorporated both men and women into the case control groups. However, far fewer studies stratified their results based on sex. Of the eleven studies included in this subgroup analysis, representing over 7,000 case/control study participants, only one reported significant OR based on sex and genotype, which was contrary to the summary results in this meta-analysis (Table 2). Lightfoot et al. found that the men with the 677CT genotype had a reduced risk of CRC, and women with the 677TT genotype had an increased risk [58]. In the subgroup analysis on sex, the risk reduction of the 677TT genotype and significant summary risk estimate for both sexes was no longer evident. This may represent lack of statistical power; it is possible that more studies are necessary to determine whether there may be a gender bias favoring one sex over another regarding the protective nature of the 677TT genotype.

The A1298C polymorphisms would not appear to be associated with any substantial reduction in the associated risk of CRC. However, subgroup analysis did reveal some variability in the associated risk for the 1298CC genotype, with lower risks associated with Asian and USA studies. What might be contributing to these geographical differences is unclear. Perhaps, as with the subgroup analysis by sex, additional studies with larger numbers of participants with this genotype are necessary to more clearly understand the relationship.

Many of the studies included in the high versus low folate intake meta-analysis compared the risk of CRC using the 677CC or 677CC/CT genotype and low folate intake as the reference group for the calculation of the odds ratio in other genotypes and folate intake “quantiles.” Generally, the findings of these studies were that high folate intake and the 677TT genotype were associated with a nonsignificant reduction in CRC risk versus low folate intake. This is the first study to perform a meta-analysis of the risk of CRC comparing high versus low folate intake within a genotype. The meta-analysis findings for the homozygous genotypes (677CC and 677TT) indicate that there is greater risk reduction with higher levels of folate intake. The upper range of high folate intake reported in the studies was, generally, over the Institute of Medicine’s (IOM) recommended daily intake (RDI) of 400 mcg/day and in one case over 1 mg/day [23, 99]. There were no clear boundaries in the definition of low folate intake versus high folate intake in this analysis as there was overlap in the ranges in daily folate amounts that defined the lowest folate intake versus the highest intake. This does prevent generalizing an amount of folate intake for each genotype that may be related to reducing colorectal cancer risk, which is a limitation of this analysis. Further, there is insufficient data to verify the shape (linear versus nonlinear) of the dose effect curve. More studies at this level of detail are necessary to provide further insight into the shape of the dose effect curve for folate and its associated impact on the risk of colorectal cancer.

The available studies used food frequency questionnaires (FFQs) or an adapted Coronary Artery Risk Development in Young Adults (CARDIAs) dietary history questionnaire to capture the food eaten on a regular basis; however, it is possible that not all of the folate food sources were captured thereby underestimating intake. Furthermore, tools such as the FFQ in case control studies are subject to recall bias since dietary intake was surveyed after a diagnosis of CRC. These two factors could lead to some under- or overreporting of folate intake resulting in misclassification of participants into their respective “quantiles.” While mandatory folate fortification was implemented in the USA in 1998, none of the studies included in the meta-analysis on folate intake were conducted during times of folate fortification. Interestingly, a recent large observational study conducted in USA, after the mandated folate fortification period, found that higher folate intake levels were associated with a protective effect against CRC [100].

The studies included in the meta-analysis were conducted in twenty-five different countries. This is potentially both a strength and weakness of our analysis. Different countries represent different sources of folate and different food choice combinations, thus broadening the generalizability of our results. The potential weakness rests with the increased heterogeneity of some of the results. In the 2009 meta-analysis conducted by Taioli et al, their results indicate that in Asia the 677TT genotype was afforded a significant risk reduction [94]. In our analysis, the 677TT genotype is no longer significantly protective.

In conclusion, the results of this meta-analysis suggest that the MTHFR 677TT genotype is associated with a reduced risk of CRC. In addition, under conditions of high total folate intake, the associated risk of CRC is also reduced for both the MTHFR 677 CC and TT genotypes.

Conflict of Interests

D. A. Kennedy is supported by a career development grant from Sickkids Foundation. G. Koren holds the Research Leadership for Better Pharmacotherapy during Pregnancy and Breastfeeding (Sickkids Hospital) and the Ivey Chair in Molecular Toxicology (University of Western Ontario). The Motherisk Program is conducting research supported by Duchesnay Inc. manufacturer of prenatal vitamins. These vitamins were not utilized in any of the studies included in this meta-analysis. The remaining authors have no financial interests to declare.

Acknowledgments

The authors would like to thank Yen Ming and Yuqi (Alice) Liang for their assistance in translating the articles in Chinese. They would like to thank Jan Hamling for her guidance with the MS Excel spreadsheet application used to recalculate the adjusted odd ratios to perform the high versus low folate intake analysis within the genotype.

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