Journal of Cancer Epidemiology

Volume 2012 (2012), Article ID 952508, 24 pages

doi:10.1155/2012/952508

Review Article

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

Deborah A. Kennedy,1,2 Seth J. Stern,1,3 Ilan Matok,¹ Myla E. Moretti,¹ Moumita Sarkar,¹ Thomasin Adams-Webber,¹ and Gideon Koren1,2,3

¹The Motherisk Program, Division of Clinical Pharmacology and Toxicology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, Canada, M5G 1X8

²Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, ON, Canada, M5S 3M2

³Department of Pharmacology and Toxicology, Faculty of Medicine, University of Toronto, Medical Sciences Building, 1 King's College Circle, Toronto, ON, Canada, M5S 1A8

Received 23 March 2012; Revised 26 May 2012; Accepted 26 May 2012

Academic Editor: P. Vineis

Copyright © 2012 Deborah A. Kennedy et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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 [4–7]. 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, 14–18]. 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) [20–28]; however, other studies have found an increased risk [29–31].

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.

Table 1

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

Study
Country
Year
Study design
Source of controls
Recruitment period
Cancer
Sex
Case/control
Distribution of MTHFR C677T genotype in controls
HWE (yes/no)
Distribution of MTHFR A1298C

genotype in controls
HWE (yes/no)
Adjustments

CC (%)
CT (%)
TT (%)

AA (%)
AC (%)
CC (%)

Park et al. [34]
South Korea
1999
Case control
Healthy persons
Not reported
CRC
Both
200/460
30.4
53.5
16.1
No

Calculated OR, no adjustments

Delgado-Enciso et al. [15]
Mexico
2001
Case control
Not reported
1997
CRC
Both
74/110
30.9
47.3
21.8
Yes

Calculated OR, no adjustments

Keku et al. [35]
USA
2002
Case control
Healthy persons
1996–2000
Colon-Cauc
Both
555/875
49.2
41.4
9.4
Yes
52.5
38.5
9.3
Yes
Adjusted for sampling fraction, age, gender, and energy intake

Le Marchand et al. [23]
USA
2002
Matched case control
Healthy persons
1994–1998
CRC
Both
727/727
39.2
45
15.8
Yes
58.2
36.0
5.8
No
Adjusted 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]
Japan
2002
Case control
Hospital patients
1999
CRC

colon

rectal
Both
142/241

72/241

70/241
33.6
51.5
14.9
Yes
65.1
31.1
3.7
Yes
Adjusted for age

Shannon

et al. [36]
Australia
2002
Case control
Healthy persons
1985–1998
CRC
Both
501/

1,207
44.2
46.4
9.4
Yes

Calculated OR, no adjustments

Plaschke

et al. [37]
Germany
2003
Case control
Healthy persons
Not reported
CRC
Both
287/346
43.1
45.9
11
Yes
44.5
43.6
11.8
Yes
Adjusted for gender

Pufulete

et al. [38]
United Kingdom
2003
Case control
Hospital patients
2000-2001
CRC
Both
304/352
54
38
8
Yes
61.8
34.2
3.9
Yes
Adjusted for age, gender, BMI, smoking, and ROH intake.

Toffoli

et al. [39]
Italy
2003
Case control
Healthy persons
1999-2000
Colon
Both
276/279
29.7
50.2
20.1
Yes
47.7
43.4
9
Yes
Calculated OR, no adjustments

Jiang et al. [40]
China
2004
Case control
Healthy person
1990–2002
CRC
Both
126/343
39.1
42.4
18.5
No
67.6
30.7
1.8
Yes
Adjusted for age and sex

Miao et al. [41]
China
2005
Case control
Healthy persons
1999–2002
CRC
Both
198/420
31.7
47.9
20.5
Yes
67.1
31.4
1.4
No
None reported

Ulvik et al. [20]
Norway
2004
Nested case control
Healthy persons
1992-1991
CRC
Both
2,168/

2,168
49.9
40.4
9.7
Yes

Adjusted for age and gender

Yin et al. [21]
Japan
2004
Case control
Hospital patients
2000–2003
CRC
Both
685/778
35.7
47.2
17.1
Yes
66.2
31.4
2.4
Yes
Adjusted for gender. 5-year age class, area and alcohol use

Jiang

et al. [42]
China
2005
Nested case control
Healthy persons
1989-1990
Colon

rectal
Both
52/338

72/338
39.5
42.2
18.3
No
67.5
30.7
1.8
No
Adjusted for gender, age, folate, methionine, total energy intake, smoking status, and drinking status

Landi et al. [43]
Spain
2005
Case control
Hospital patients
1996–1998
CRC
Both
359/320
35.3
45
19.7
Yes
53.3
39.8
6.9
Yes
Adjusted for age and sex

Matsuo

et al. [44]
Japan
2005
Matched case control
Hospital patients
2001–2004
CRC
Both
257/771
37.5
45.1
17.3
Yes
62.5
33.5
4.0
Yes
Adjusted for age, sex, referral patterns, smoking BMI, physical, exercise and family history of CRC

Otani et al. [45]
Japan
2005
Matched case control
Hospital patients
1998–2002
CRC
Both
107/224
23
51.4
25.6
Yes
69.6
28.1
2.2
Yes
Matching factors and adjusted for smoking, alcohol consumption, BMI, and total dietary fiber intake

Le Marchand

et al. [46]
USA

(Hawaii and California)
2005
Nested case control
Healthy persons
1993–1996
CRC

colon

rectal
Both
822/

2,021
48.9
38.5
12.6
No

Adjusted for age, gender, and ethnicity

Battistelli et al. [47]
Italy
2006
Case control
Healthy controls
Not reported
CRC
Both
93/100
30
51
29
Yes

Calculated OR, no adjustments

Van Guelpen

et al. [24]
Sweden
2006
Nested case control
Healthy persons
1985–2002
CRC
Both
226/437
52.8
38.7
8.5
Yes
45.9
42.0
12.1
Yes
Adjusted for BMI, smoking, recreational and occupational physical activity, and alcohol intake

Wang et al. [48]
India
2006
Case control
Healthy persons
1999–2001
CRC

colon

rectal
Both
435/340
87.6
12.4
0
Yes
36.1
46.4
17.5
Yes
Adjusted for gender, age household income, education, religion, mother tongue, smoking, drinking, chewing, and vegetarianism

Lima

et al. [49]
Brazil
2007
Case control
Healthy persons
1999–2001
CRC
Both
102/300
47.7
42.3
10
Yes
63.7
31.0
5.3
Yes
Adjusted for age, gender, and race

Chang

et al. [50]
Taiwan
2007
Matched case control
Hospital patients
2000-2001
CRC
Both
195/195
47.2
44.6
8.2
Yes
61.5
33.3
5.1
Yes
Matched on age and gender.

Curtin

et al. [51]
USA
2007
Matched case control
Healthy persons
1991–1994
Colon
Both
916/

1,972
45.0
43.5
11.5
Yes
47.1
41.9
11
Yes
Calculated OR, no adjustments

Hubner et al. [52]
United Kingdom
2007
Case control
Healthy controls
Not reported
CRC
Both
1,685/

2,695
43.6
44.3
12.1
Yes

Adjusted for age, sex, family history, cancer location, stage, and grade

Jin et al. [53]
China
2007
Case control
Healthy controls
2002–2005
CRC
Both
449/672
31.4
48.4
20.2
Yes

Adjusted for age, sex, drinking, BMI, smoking, and family history

Murtaugh

et al. [54]
USA
2007
Matched case control
Healthy persons
1997–2001
Rectal-Men

Rectal-Women
Both

Men

Women
751/979
48.2

47.5
40.1

41.4
11.7

11.1
No
44.9
43.7
11.3
Yes
Adjusted for age, BMI, activity, energy, fiber, calcium, ibuprofen use, smoking, and other MTHFR genotype

Osian et al. [55]
Romania
2007
Matched case control
Hospital patients
2003–2005
CRC
Both
69/67
70.2
25.4
4.5
Yes
61.1
37.3
1.5
Yes
Matched on age and sex

Zeybek

et al. [17]
Turkey
2007
Case control
Hospital patients
2003–2005
CRC
Both
52/144
44.4
45.1
10.4
Yes

Calculated OR, no adjustments

Cao et al. [56]
China
2008
Matched case control
Healthy persons
2000–2002
CRC
Both
315/371
32.7
49.5
17.8
Yes
64.4
32.1
3.5
Yes
Matched on ethnicity, sex, and age

Küry et al. [57]
France
2008
Matched case control
Healthy persons
2002–2006
CRC
Both
1,023/1,121
40.8
45.9
13.3
Yes
51.5
39.5
9
Yes
Matched on age and sex

Lightfoot

et al. [58]
United Kingdom
2008
Matched case control
Hospital patients
1997–2000
CRC
Both
468/734
45.8
46
8.3
Yes
48.6
43.7
7.8
Yes
Adjusted for gender and age

Mokarram

et al. [59]
Iran
2008
Case control
Not reported
2003–2005
Colon
Both
151/81
49.4
38.3
12.3
Yes

Calculated OR, no adjustments

Sharp

et al. [60]
United Kingdom

(Scotland)
2008
Matched case control
Healthy persons
1998–2000
CRC
Both
264/408
43.2
44.9
11.9
Yes
44.9
39.8
15.2
No
Adjusted for age, gender, family history of CRC, physical activity, NAAID use, total energy intake, and type of dietary supplements

Theodoratou

et al. [61]
Scotland
2008
Case control
Healthy persons
1999–2006
CRC
Both
2,028/

2,722
45.3
45.0
11.5
Yes
45.8
44.1
10.1
Yes
Adjusted for age, sex, deprivation score, and family history risk

Zhang

et al. [62]
China
2008
Matched case control
Hospital patients
2003–2005
CRC
Both
300/300
30.4
46.5
23.1
Yes
65.3
29.7
5
Yes
Adjusted for age, sex, education, family history, smoking, and drinking.

El Awady

et al. [63]
Egypt
2009
Case control
Healthy persons
2004–2007
CRC
Both
35/68
65
29
6
Yes
38
54
8
Yes
None reported

Gallegos-Arreola

et al. [30]
Mexico
2009
Case control
Healthy persons
2006–2008
CRC
Both
369/170
33.6
34.1
32.2
No

Calculated OR, no adjustments

Haghighi

et al. [22]
Iran
2009
Case control
Hospital patients
2004–2007
CRC
Both
234/257
36.6
31.1
32.3
Yes

None reported

Iacopetta

et al. [18]
Australia
2009
Matched case control
Healthy persons
2005–2007
Proximal distal CRC
Both
850/958
45
45
10
Yes

Matched on gender, age, socioeconomic status, country of birth, educational level, and smoking status

Chandy

et al. [14]
India
2010
Matched case control
Healthy persons
2006–2008
CRC
Both
100/86
76.7
22.1
1.2
Yes
25.6
58.1
16.3
Yes
Matched on age and gender

Cui et al. [28]
South Korea
2010
Case control
Hospital patients
2004–2008
CRC
Both
1,829/

1,700
31.8
50.7
17.5
Yes

Adjusted for age and sex

Eussen et al. [64]
EPIC
2010
Nested case control
Healthy persons
1992–1998
CRC
Both
1,367/

2,325
43.1
45.5
11.5
Yes
46.5
42.6
11.0
Yes
Calculated OR, no adjustments

Fernández-Peralta et al. [65]
Spain
2010
Matched case control
Healthy persons
1992–1996
CRC
Both
143/103
42.7
48.6
8.7
Yes
55.3
42.7
1.9
No
Matched on age and sex

Karpinski

et al. [66]
Poland
2010
Case control
Healthy persons
Not reported
CRC
Both
186/140
51
39
10
Yes

Adjusted for age and sex

Komlósi et al. [67]
Hungary
2010
Case control
Healthy persons
2001–2007
Colon

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]
Iran
2010
Case control
Not reported
Not reported
CRC
Both
151/230
42.4
53
4.6
Yes
42.5
45.7
11.8
Yes
Adjusted for age, sex, and smoking status

Promthet

et al. [69]
Thailand
2010
Matched case control
Healthy persons
2002–2006
Colon
Both
130/130
72.3
23.8
3.9
Yes
41.5
54.6
3.9
No
Matched on age and sex

Wettergren

et al. [70]
Sweden
2010
Case control
Healthy persons
1994–2004
CRC
Both
181/300
55.9
35.8
8.4
Yes

Calculated OR, no adjustments

Abuli et al. [71]
Spain
2011
Matched case control
Healthy person
2000-2001
CRC
Both
515/515
38.1
48
13.9
Yes

Matched on age and sex

Guimarães et al. [72]
Brazil
2011
Case control
Healthy persons
1992–2003
CRC
Both
113/188
48.9
42.0
9
Yes
67.6
26.1
6.4
No
Adjusted for age, sex, and ethnic origin

Jokić et al. [73]
Croatia
2011
Case control
Healthy persons
Not reported
Colon
Both
300/300
47.3
43.3
9.3
Yes
46.7
42.7
10.6
Yes

Pardini

et al. [25]
Czech Republic
2011
Case control
Hospital patients
2004–2006
CRC
Both
666/

1,377
44.5
45.6
9.9
Yes
42.3
46.3
11.3
Yes
Adjusted for age and gender

Kim et al. [26]
South Korea
2011
Case control
Hospital patients
Not reported
CRC
Both
67/53
28.3
39.6
32.1
Yes
67.9
30.2
1.9
Yes
None reported

Sameer

et al. [74]
Kashmiri

(India)
2011
Matched case control
Healthy persons
2008-2009
CRC
Both
86/160
75.6
16.9
7.5
No

None reported

Prasad and Wilkhoo [75]
India
2011
Case control
Healthy person
Not reported
CRC
Both
110/241
94.6
5.0
0.4
Yes

None reported

Zhu et al. [29]
China
2011
Case control
Healthy persons
2006–2008
CRC
Both
86/100
49.0
41.0
10
Yes

None reported

Kim et al. [27]
South Korea
2012
Case control
Hospital patients
1998–2004
CRC
Both
787/656
31.3
44.1
24.7
No

Adjusted for age, sex, family history, multivitamin use, BMI, smoking status, and total energy

Lee et al. [76]
USA
2012
Nested case control
Healthy persons
Health professionals follow-up study
CRC
Men
173/345
44
39.9
16
Yes
47.7
42.6
10.3
Yes
RR’s reported, so OR’s are calculated, no adjustments

Lee et al. [76]
USA
2012
Nested Case Control
Healthy persons
Physicians’ health study
CRC
Men
240/408
47.7
37.2
15
Yes
45.8
42.2
12.1
Yes
RR’s reported, so OR’s are calculate, no adjustments

Lee et al. [76]
USA
2012
Nested Case Control
Healthy persons
Nurse Health Study
CRC
Women
189/377
46.7
39.7
13.6
Yes
51
38.3
10.7
Yes
RR’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)

Study
Country
Year
Study design
Source of control
Recruitment period
Cancer
Sex
Case/control
Follow-up period
CT versus CC
TT versus CC
AC versus AA
CC versus AA

De Vogel et al. [77]
Netherlands
2009
Cohort
Healthy persons
Recruited in 1986
CRC
Both
689/1,793
7.3 years
1.23 (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]
Netherlands
2003
Cohort
Elderly healthy men
Recruited in 1985
CRC
Both
18/793
10 years
1.16 (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 [85–87]. 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.

Figure 1: Search strategy flow chart.

Figure 2: Forest plot of the risk of colorectal cancer for MTHFR 677CT versus CC.

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].

Figure 3: Forest plot of the risk of colorectal cancer for MTHFR 677TT versus CC.

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).

Table 2: Subgroup analysis for the MTHFR C677T polymorphism.

Number of studies
Number of participants in case/control
Summary effect estimate
95% CI
Tests for heterogeneity

CC genotype
Comparator genotype

Subgroup by sex

Pooled studies for sex

(%)

    CT versus CC
11
1,650/1,833
1,420/1,523
1.04
0.94–1.16
χ² = 14.28, df = 10 (P = 0.16)
30

    TT versus CC
11
1,650/1,833
326/425
0.87
0.75–1.01
χ² = 14.01, df = 10 (P = 0.17)
29

Men

    CT versus CC
9
1,257/1,436§
1,081/1,199§
1.12
0.94–1.34
χ² = 18.68, df = 8 (P = 0.02)
57

    TT versus CC
9
1,257/1,436§
271/346§
0.87
0.74–1.02
χ² = 8.36, df = 8 (P = 0.40)
4

Women

    CT versus CC
8
755/897§
627/773§
0.98
0.85–1.12
χ² = 7.63, df = 7 (P = 0.37)
8

    TT versus CC
8
755/897§
162/217§
0.92
0.65–1.31
χ² = 20.74, df = 7 (P = 0.004)
66

Subgroup by cancer type

Pooled studies

    CT versus CC
27
3,735/6,767
3,403/6,307
1.01
0.95–1.08
χ² = 23.65, df = 26 (P = 0.60)
0

    TT versus CC
24*
3,735/6,767
886/2,117
0.80
0.71–0.89
χ² = 31.45, df = 23 (P = 0.11)
27

Colon cancer studies

    CT versus CC
16
2,096/4,463
1,933/4,090
1.01
0.93–1.10
χ² = 11.23, df = 15 (P = 0.74)
0

    TT versus CC
14**
2,096/4,463
452/1,352
0.76
0.64–0.91
χ² = 22.79, df = 13 (P = 0.04)
43

Rectal cancer studies

    CT versus CC
11
1,639/3,291
1,470/2,996
1.10
0.92–1.31
χ² = 27.95, df = 10 (P = 0.002)
64

    TT versus CC
10
1,639/3,291
386/1,020
0.82
0.72–0.94
χ² = 8.38, df = 9 (P = 0.50)
0

Subgroup by location

Asian countries

    CT versus CC
22
2,640/3,401
2,985/3,903
0.98
0.89–1.06
χ² = 23.98, df = 21 (P = 0.29)
12

    TT versus CC
20**
2,640/3,401
1,001/1,565
0.83
0.69–1.01
χ² = 49.66, df = 19 (P = 0.0001)
62

European countries

    CT versus CC
22
5,480/6,960
5,374/6,857
1.00
0.87–1.13
χ² = 109.92, df = 21 (P < 0.00001)
81

    TT versus CC
22
5,480/6,960
1,294/1,793
0.92
0.80–1.06
χ² = 43.74, df = 21 (P = 0.003)
52

USA

    CT versus CC
8
2,011/3,355
1,932/2,997
0.98
0.90–1.07
χ² = 6.07, df = 7 (P = 0.53)
0

    TT versus CC
8
2,011/3,355
436/1,055
0.73
0.63–0.84
χ² = 1.91, df = 7 (P = 0.96)
0

Middle Eastern countries

    CT versus CC
5
277/374
274/302
1.46
0.62–3.46
χ² = 45.30, df = 4 (P < 0.00001)
91

    TT versus CC
5
277/374
72/105
0.69
0.42–1.13
χ² = 5.56, df = 4 (P = 0.23)
28

Subgroup by control

Healthy person controls

    CT versus CC
45
8,706/12,958
8,043/12,044
1.02
0.94–1.11
χ² = 154.26, df = 44 (P < 0.00001)
71

    TT versus CC
43**
8,706/12,958
2,136/3,636
0.90
0.81–1.00
χ² = 88.37, df = 42 (P = 0.0001)
52

Hospital patient controls

    CT versus CC
16
2,418/2,863
2,932/3,619
0.93
0.83–1.05
χ² = 27.35, df = 15 (P = 0.03)
45

    TT versus CC
16
2,418/2,863
939/1,254
0.82
0.68–1.00
χ² = 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).

Figure 4: Forest plot of the risk of colorectal cancer for MTHFR 1298AC versus AA.

Figure 5: Forest plot of the risk of colorectal cancer for MTHFR 1298CC versus AA.

(a)

(b)

Figure 6: Forest plot of the risk of colorectal cancer comparing high versus low folate intake within each MTHFR C677T polymorphism.

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].

Table 3: Subgroup analysis for the MTHFR A1298C polymorphism.

Number of studies
Number of participants in case/control
Summary effect estimate
95% CI
Tests for heterogeneity

AA genotype
Comparator genotype

Subgroup by location

Asian countries

(%)

    AC versus AA
15
1,727/3,047
991/1,615
0.99
0.84–1.16
χ² = 26.56, df = 14 (P = 0.02)
47

    CC versus AA
14*
1,727/3,047
116/178
0.72
0.55–0.93
χ² = 14.37, df = 13 (P = 0.35)
10

European countries

    AC versus AA
14
2,971/4,119
2,404/3,746
1.05
0.97–1.14
χ² = 14.78, df = 13 (P = 0.32)
12

    CC versus AA
14
2,971/4,119
683/908
1.14
1.01–1.28
χ² = 13.13, df = 13 (P = 0.44)
1

USA

    AC versus AA
7
1,678/2,694
1,365/2,244
0.99
0.88–1.11
χ² = 7.96, df = 6 (P = 0.24)
25

    CC versus AA
7
1,678/2,694
247/559
0.73
0.57–0.92
χ² = 10.20, df = 6 (P = 0.12)
41

Subgroup by control

Hospital controls

    AC versus AA
12
1,872/2,795
1,258/1,874
1.05
0.95–1.16
χ² = 4.42, df = 11 (P = 0.96)
0

    CC versus AA
12
1,872/2,795
232/311
1.12
0.88–1.42
χ²= 13.22, df = 11 (P = 0.28)
17

Healthy controls

    AC versus AA
27
5,083/7,939
3,926/6,325
1.02
0.93–1.11
χ²= 48.87, df = 26 (P = 0.004)
47

    CC versus AA
26*
5,083/7,939
912/1,439
0.88
0.76–1.03
χ²= 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.

Table 4: Summary effect estimate results for the MTHFR C677T and A1298C polymorphism combinations.

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

CC/AA genotype
Comparator genotype§

I (%)

CC/AC
12
609/775
677/870
0.96
0.82–1.11
χ² = 7.56, df = 11 (P = 0.75)
0

CC/CC
12
609/775
180/312
0.90
0.64–1.27
χ² = 21.33, df = 11 (P = 0.03)
48

CT/AA
12
609/775
753/912
0.99
0.86–1.15
χ² = 9.63, df = 11 (P = 0.56)
0

CT/AC
12
609/775
491/678
1.06
0.79–1.44
χ² = 30.68, df = 11 (P = 0.001)
64

CT/CC
5
609/775
18/36
1.40
0.33–6.03
χ² = 7.78, df = 4 (P = 0.10)
49

TT/AA
12
609/775
311/465
0.77
0.58–1.03
χ² = 19.00, df = 11 (P = 0.06)
42

TT/AC
4
609/775
11/17
N/a

TT/CC
3
609/775
0/6
N/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).

Table 5: Case Control Studies: comparison of high versus low folate intake.

Study
Country
Year
Study design
Population of controls
Recruitment period
Cancer
Gender
Number of quantiles
Dietary folate (mcg/day)
Total folate (mcg/day)
Adjustments

Chen et al. [90]
USA
1996
Nested case control
Healthy persons
1986–1994
CRC
Men
3
<317 versus >461

Adjusted for age, family history, and intake of folate, methionine, and alcohol

Slattery et al. [91]
USA
1999
Matched case control
Healthy persons
1991–1994
Colon
Both
3
<126 versus >197

per 1000 kcals

Adjusted for age, BMI, physical activity, energy intake, dietary fiber, and smoking

Le Marchand et al. [23]
USA
2002
Matched case control
Healthy persons
1994–1998
CRC
Both
3
<278 versus >372
<336 versus >1583
Adjusted 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]
China
2005
Nested case control
Healthy persons
1989-1990
Colon

rectal
Both
4
<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)
2005
Nested case control
Healthy persons
1993–1996
CRC
Both
3
<253 versus >412
<322 versus >590
Adjusted for age, gender, and ethnicity

Otani et al. [45]
Japan
2005
Matched case control
Hospital patients
1998–2002
CRC
Both
3
<343 versus >485

Matching factors and adjusted for smoking, alcohol consumption, BMI, and total dietary fiber intake

Lightfoot et al. [58]
United Kingdom
2008
Matched case control
Hospital patients
1997–2000
CRC
Both
3

<267 versus >397
Adjusted for gender, and age

Sharp et al. [60]
United Kingdom
2008
Matched case control
Healthy persons
1998–2000
CRC
Both
4

<263.9 versus >348.6
Adjusted for age, gender and total energy intake.

Guerreiro et al. [31]
Portugal
2008
Case control
Healthy persons
Not reported
CRC
Both
2
≤406.7>

Adjusted for age, gender and CRC history

Haghighi et al. [22]
Iran
2009
Case control
Hospital patients
2004–2007
CRC
Both
2
≤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 [29–31]. 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.

References

A. Jemal, F. Bray, M. M. Center, J. Ferlay, E. Ward, and D. Forman, “Global cancer statistics,” CA Cancer Journal for Clinicians, vol. 61, no. 2, pp. 69–90, 2011.

M. M. Center, A. Jemal, R. A. Smith, and E. Ward, “Worldwide variations in colorectal cancer,” CA Cancer Journal for Clinicians, vol. 59, no. 6, pp. 366–378, 2009.

L. Migliore, F. Migheli, R. Spisni, and F. Copped, “Genetics, cytogenetics, and epigenetics of colorectal cancer,” Journal of Biomedicine and Biotechnology, vol. 2011, Article ID 792362, 19 pages, 2011.

Y. I. Kim, “Role of folate in colon cancer development and progression,” Journal of Nutrition, vol. 133, no. 11, supplement 1, pp. 3731S–3739S, 2003.

B. N. Ames, “DNA damage from micronutrient deficiencies is likely to be a major cause of cancer,” Mutation Research—Fundamental and Molecular Mechanisms of Mutagenesis, vol. 475, no. 1-2, pp. 7–20, 2001.

S. J. Duthie, “Folic acid deficiency and cancer: mechanisms of DNA instability,” British Medical Bulletin, vol. 55, no. 3, pp. 578–592, 1999.

M. Fenech, “The role of folic acid and Vitamin B12 in genomic stability of human cells,” Mutation Research—Fundamental and Molecular Mechanisms of Mutagenesis, vol. 475, no. 1-2, pp. 57–67, 2001.

B. M. Ryan and D. G. Weir, “Relevance of folate metabolism in the pathogenesis of colorectal cancer,” Journal of Laboratory and Clinical Medicine, vol. 138, no. 3, pp. 164–176, 2001.

M. Mukherjee, S. Joshi, S. Bagadi, M. Dalvi, A. Rao, and K. R. Shetty, “A low prevalence of the C677T mutation in the methylenetetrahydrofolate reductase gene in Asian Indians,” Clinical Genetics, vol. 61, no. 2, pp. 155–159, 2002.

C. M. Ulrich, K. Robien, and R. Sparks, “Pharmacogenetics and folate metabolism—a promising direction,” Pharmacogenomics, vol. 3, no. 3, pp. 299–313, 2002.

K. Robien, A. Boynton, and C. M. Ulrich, “Pharmacogenetics of folate-related drug targets in cancer treatment,” Pharmacogenomics, vol. 6, no. 7, pp. 673–689, 2005.

R. M. Guéant-Rodriguez, J. L. Guéant, R. Debard et al., “Prevalence of methylenetetrahydrofolate reductase 677T and 1298C alleles and folate status: a comparative study in Mexican, West African, and European populations,” American Journal of Clinical Nutrition, vol. 83, no. 3, pp. 701–707, 2006.

B. Wilcken, F. Bamforth, Z. Li et al., “Geographical and ethnic variation of the 677 allele of 5, 10 methylenetetrahydrofolate reductase (MTHFR): findings from over 7000 newborns from 16 areas world wide,” Journal of Medical Genetics, vol. 40, no. 8, pp. 619–625, 2003.

S. Chandy, M. N. S. Adiga, N. Ramachandra et al., “Association of methylenetetrahydrofolate reductase gene polymorphisms & colorectal cancer in India,” Indian Journal of Medical Research, vol. 131, no. 5, pp. 659–664, 2010.

I. Delgado-Enciso, S. G. Martínez-Garza, A. Rojas-Martínez et al., “677T mutation of the MTHFR gene in adenomas and colorectal cancer in a population sample from the Northeastern Mexico. Preliminary results,” Revista de Gastroenterologia de Mexico, vol. 66, no. 1, pp. 32–37, 2001.

K. Matsuo, N. Hamajima, T. Hirai, et al., “Methionine synthase reductase gene A66G polymorphism is associated with risk of colorectal cancer,” Asian Pacific Journal of Cancer Prevention, vol. 3, no. 4, pp. 353–359, 2002.

U. Zeybek, I. Yaylim, H. Yilmaz et al., “Methylenetetrahydrofolate reductase C677T polymorphism in patients with gastric and colorectal cancer,” Cell Biochemistry and Function, vol. 25, no. 4, pp. 419–422, 2007.

B. Iacopetta, J. Heyworth, J. Girschik, F. Grieu, C. Clayforth, and L. Fritschi, “The MTHFR C677T and ΔDNMT3B C-149T polymorphisms confer different risks for right- and left-sided colorectal cancer,” International Journal of Cancer, vol. 125, no. 1, pp. 84–90, 2009.

L. D. Botto and Q. Yang, “5,10-Methylenetetrahydrofolate reductase gene variants and congenital anomalies: a HuGE review,” American Journal of Epidemiology, vol. 151, no. 9, pp. 862–877, 2000.

A. Ulvik, S. E. Vollset, S. Hansen, R. Gislefoss, E. Jellum, and P. M. Ueland, “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 Epidemiology Biomarkers and Prevention, vol. 13, no. 12, pp. 2175–2180, 2004.

G. Yin, S. Kono, K. Toyomura et al., “Methylenetetrahydrofolate reductase C677T and A1298C polymorphisms and colorectal cancer: the Fukuoka Colorectal Cancer study,” Cancer Science, vol. 95, no. 11, pp. 908–913, 2004.

M. M. Haghighi, R. Radpour, T. Mahmoudi, S. R. Mohebbi, M. Vahedi, and M. R. Zali, “Association between MTHFR polymorphism (C677T) with nonfamilial colorectal cancer,” Oncology Research, vol. 18, no. 2-3, pp. 57–63, 2009.

L. Le Marchand, T. Donlon, J. H. Hankin, L. N. Kolonel, L. R. Wilkens, and A. Seifried, “B-vitamin intake, metabolic genes, and colorectal cancer risk (United States),” Cancer Causes and Control, vol. 13, no. 3, pp. 239–248, 2002.

B. van Guelpen, A. M. Dahlin, J. Hultdin et al., “One-carbon metabolism and CpG island methylator phenotype status in incident colorectal cancer: a nested case-referent study,” Cancer Causes and Control, vol. 21, no. 4, pp. 557–566, 2010.

B. Pardini, R. Kumar, A. Naccarati et al., “MTHFR and MTRR genotype and haplotype analysis and colorectal cancer susceptibility in a case-control study from the Czech Republic,” Mutation Research—Genetic Toxicology and Environmental Mutagenesis, vol. 721, no. 1, pp. 74–80, 2011.

J. W. Kim, H. M. Park, Y. K. Choi, S. Y. Chong, D. Oh, and N. K. Kim, “Polymorphisms in genes involved in folate metabolism and plasma DNA methylation in colorectal cancer patients,” Oncology Reports, vol. 25, no. 1, pp. 167–172, 2011.

J. Kim, Y. A. Cho, D. H. Kim et al., “Dietary intake of folate and alcohol, MTHFR C677T polymorphism, and colorectal cancer risk in Korea,” American Journal of Clinical Nutrition, vol. 95, no. 2, pp. 405–412, 2012.

L. H. Cui, M. H. Shin, S. S. Kweon et al., “Methylenetetrahydrofolate reductase C677T polymorphism in patients with gastric and colorectal cancer in a Korean population,” BMC Cancer, vol. 10, article 236, 2010.

Q. Zhu, Z. Jin, Y. Yuan, Q. Lu, D. Ge, and M. Zong, “Impact of MTHFR gene C677T polymorphism on Bcl-2 gene methylation and protein expression in colorectal cancer,” Scandinavian Journal of Gastroenterology, vol. 46, no. 4, pp. 436–445, 2011.

M. P. Gallegos-Arreola, J. E. García-Ortiz, L. E. Figuera, A. M. Puebla-Pérez, G. Morgan-Villela, and G. M. Zúñiga-González, “Association of the 677C→T polymorphism in the MTHFR gene with colorectal cancer in Mexican patients,” Cancer Genomics and Proteomics, vol. 6, no. 3, pp. 183–188, 2009.

C. S. Guerreiro, B. Carmona, S. Gonçalves et al., “Risk of colorectal cancer associated with the C677T polymorphism in 5,10-methylenetetrahydrofolate reductase in Portuguese patients depends on the intake of methyl-donor nutrients,” American Journal of Clinical Nutrition, vol. 88, no. 5, pp. 1413–1418, 2008.

L. B. Bailey, Folate in Health and Disease, Taylor & Francis, Boca Raton, Fla, USA, 2nd edition, 2010.

L. Sharp and J. Little, “Polymorphisms in genes involved in folate metabolism and colorectal neoplasia: a HuGE review,” American Journal of Epidemiology, vol. 159, no. 5, pp. 423–443, 2004.

K. S. Park, J. W. Mok, and J. C. Kim, “The 677 mutation in 5,10-methylenetetrahydrofolate reductase and colorectal cancer risk,” Genetic Testing, vol. 3, no. 2, pp. 233–236, 1999.

T. Keku, R. Millikan, K. Worley et al., “5,10-Methylenetetrahydrofolate reductase codon 677 and 1298 polymorphisms and colon cancer in African Americans and whites,” Cancer Epidemiology Biomarkers and Prevention, vol. 11, no. 12, pp. 1611–1621, 2002.

B. Shannon, S. Gnanasampanthan, J. Beilby, and B. Iacopetta, “A polymorphism in the methylenetetrahydrofolate reductase gene predisposes to colorectal cancers with microsatellite instability,” Gut, vol. 50, no. 4, pp. 520–524, 2002.

J. Plaschke, U. Schwanebeck, S. Pistorius, H. D. Saeger, and H. K. Schackert, “Methylenetetrahydrofolate reductase polymorphisms and risk of sporadic and hereditary colorectal cancer with or without microsatellite instability,” Cancer Letters, vol. 191, no. 2, pp. 179–185, 2003.

M. Pufulete, R. Al-Ghnaniem, A. J. M. Leather et al., “Folate status, genomic DNA hypomethylation, and risk of colorectal adenoma and cancer: a case control study,” Gastroenterology, vol. 124, no. 5, pp. 1240–1248, 2003.

G. Toffoli, R. Gafà, A. Russo et al., “Methylenetetrahydrofolate reductase 677 C→T polymorphism and risk of proximal colon cancer in North Italy,” Clinical Cancer Research, vol. 9, no. 2, pp. 743–748, 2003.

Q. T. Jiang, K. Chen, X. Y. Ma et al., “A case-control study on the polymorphisms of methylenetetrahydrofolate reductases, drinking interaction and susceptibility in colorectal cancer,” Chinese Journal of Epidemiology, vol. 25, no. 7, pp. 612–616, 2004.

X. P. Miao, S. Yang, W. Tan et al., “Association between genetic variations in methylenetetrahydrofolate reductase and risk of colorectal cancer in a Chinese population,” Chinese Journal of Preventive Medicine, vol. 39, no. 6, pp. 409–411, 2005.

Q. Jiang, K. Chen, X. Ma et al., “Diets, polymorphisms of methylenetetrahydrofolate reductase, and the susceptibility of colon cancer and rectal cancer,” Cancer Detection and Prevention, vol. 29, no. 2, pp. 146–154, 2005.

S. Landi, F. Gemignani, V. Moreno et al., “A comprehensive analysis of phase I and phase II metabolism gene polymorphisms and risk of colorectal cancer,” Pharmacogenetics and Genomics, vol. 15, no. 8, pp. 535–546, 2005.

K. Matsuo, H. Ito, K. Wakai et al., “One-carbon metabolism related gene polymorphisms interact with alcohol drinking to influence the risk of colorectal cancer in Japan,” Carcinogenesis, vol. 26, no. 12, pp. 2164–2171, 2005.

T. Otani, M. Iwasaki, T. Hanaoka et al., “Folate, vitamin B6, vitamin B12, and vitamin B 2 intake, genetic polymorphisms of related enzymes, and risk of colorectal cancer in a hospital-based case-control study in Japan,” Nutrition and Cancer, vol. 53, no. 1, pp. 42–50, 2005.

L. Le Marchand, L. R. Wilkens, L. N. Kolonel, and B. E. Henderson, “The MTHFR C677T polymorphism and colorectal cancer: the multiethnic cohort study,” Cancer Epidemiology Biomarkers and Prevention, vol. 14, no. 5, pp. 1198–1203, 2005.

S. Battistelli, A. Vittoria, M. Stefanoni, C. Bing, and F. Roviello, “Total plasma homocysteine and methylenetetrahydrofolate reductase C677T polymorphism in patients with colorectal carcinoma,” World Journal of Gastroenterology, vol. 12, no. 38, pp. 6128–6132, 2006.

J. Wang, V. Gajalakshmi, J. Jiang et al., “Associations between 5,10-methylenetetrahydrofolate reductase codon 677 and 1298 genetic polymorphisms and environmental factors with reference to susceptibility to colorectal cancer: a case-control study in an Indian population,” International Journal of Cancer, vol. 118, no. 4, pp. 991–997, 2006.

C. S. P. Lima, H. Nascimento, L. C. Bonadia et al., “Polymorphisms in methylenetetrahydrofolate reductase gene (MTHFR) and the age of onset of sporadic colorectal adenocarcinoma,” International Journal of Colorectal Disease, vol. 22, no. 7, pp. 757–763, 2007.

S. C. Chang, P. C. Lin, J. K. Lin, S. H. Yang, H. S. Wang, and A. Fen-Yau Li, “Role of MTHFR polymorphisms and folate levels in different phenotypes of sporadic colorectal cancers,” International Journal of Colorectal Disease, vol. 22, no. 5, pp. 483–489, 2007.

K. Curtin, M. L. Slattery, C. M. Ulrich et al., “Genetic polymorphisms in one-carbon metabolism: associations with CpG island methylator phenotype (CIMP) in colon cancer and the modifying effects of diet,” Carcinogenesis, vol. 28, no. 8, pp. 1672–1679, 2007.

R. A. Hubner, S. Lubbe, I. Chandler, and R. S. Houlston, “MTHFR C677T has differential influence on risk of MSI and MSS colorectal cancer,” Human Molecular Genetics, vol. 16, no. 9, pp. 1072–1077, 2007.

X. X. Jin, Z. Z. Zhu, A. Z. Wang, and H. R. Jia, “Association of methylenetetrahydrofolate reductase C677T polymorphism with genetic susceptibility to colorectal cancer,” World Chinese Journal of Digestology, vol. 15, no. 25, pp. 2754–2757, 2007 (Chinese).

M. A. Murtaugh, K. Curtin, C. Sweeney et al., “Dietary intake of folate and co-factors in folate metabolism, MTHFR polymorphisms, and reduced rectal cancer,” Cancer Causes and Control, vol. 18, no. 2, pp. 153–163, 2007.

G. Osian, L. Procopciuc, and L. Vlad, “MTHFR polymorphisms as prognostic factors in sporadic colorectal cancer,” Journal of Gastrointestinal and Liver Diseases, vol. 16, no. 3, pp. 251–256, 2007.

H. X. Cao, C. M. Gao, T. Takezaki et al., “Genetic polymorphisms of methylenetetrahydrofolate reductase and susceptibility to colorectal cancer,” Asian Pacific Journal of Cancer Prevention, vol. 9, no. 2, pp. 203–208, 2008.

S. Küry, B. Buecher, S. Robiou-du-Pont et al., “Low-penetrance alleles predisposing to sporadic colorectal cancers: a French case-controlled genetic association study,” BMC Cancer, vol. 8, article 326, 2008.

T. J. Lightfoot, J. H. Barrett, T. Bishop et al., “Methylene tetrahydrofolate reductase genotype modifies the chemopreventive effect of folate in colorectal adenoma, but not colorectal cancer,” Cancer Epidemiology Biomarkers and Prevention, vol. 17, no. 9, pp. 2421–2430, 2008.

P. Mokarram, F. Naghibalhossaini, M. Saberi Firoozi et al., “Methylenetetrahydrofolate reductase C677T genotype affects promoter methylation of tumor-specific genes in sporadic colorectal cancer through an interaction with folate/vitamin B12 status,” World Journal of Gastroenterology, vol. 14, no. 23, pp. 3662–3671, 2008.

L. Sharp, J. Little, N. T. Brockton et al., “Polymorphisms in the methylenetetrahydrofolate reductase (MTHFR) gene, intakes of folate and related B vitamins and colorectal cancer: a case-control study in a population with relatively low folate intake,” British Journal of Nutrition, vol. 99, no. 2, pp. 379–389, 2008.

E. Theodoratou, S. M. Farrington, A. Tenesa et al., “Dietary vitamin B6 intake and the risk of colorectal cancer,” Cancer Epidemiology Biomarkers and Prevention, vol. 17, no. 1, pp. 171–182, 2008.

Y. L. Zhang, X. Y. Yuan, Z. Zhang et al., “Relationship of genetic polymorphisms in methylenetetrahydrofolate reductase and alcohol drinking with the risk of colorectal cancer,” Chinese Journal of Cancer Prevention and Treatment, vol. 15, no. 17, pp. 1298–1301, 2008 (Chinese).

M. K. El Awady, A. M. Karim, L. S. Hanna et al., “Methylenetetrahydrofolate reductase gene polymorphisms and the risk of colorectal carcinoma in a sample of Egyptian individuals,” Cancer Biomarkers, vol. 5, no. 6, pp. 233–240, 2009.

S. J. P. M. Eussen, S. E. Vollset, J. Igland et al., “Plasma folate, related genetic variants, and colorectal cancer risk in EPIC,” Cancer Epidemiology Biomarkers and Prevention, vol. 19, no. 5, pp. 1328–1340, 2010.

A. M. Fernández-Peralta, L. Daimiel, N. Nejda, D. Iglesias, V. Medina Arana, and J. J. González-Aguilera, “Association of polymorphisms MTHFR C677T and A1298C with risk of colorectal cancer, genetic and epigenetic characteristic of tumors, and response to chemotherapy,” International Journal of Colorectal Disease, vol. 25, no. 2, pp. 141–151, 2010.

P. Karpinski, A. Myszka, D. Ramsey et al., “Polymorphisms in methyl-group metabolism genes and risk of sporadic colorectal cancer with relation to the CpG island methylator phenotype,” Cancer Epidemiology, vol. 34, no. 3, pp. 338–344, 2010.

V. Komlósi, E. Hitre, É. Pap et al., “SHMT1 1420 and MTHFR 677 variants are associated with rectal but not colon cancer,” BMC Cancer, vol. 10, article 525, 2010.

F. Naghibalhossaini, P. Mokarram, I. Khalili et al., “MTHFR C677T and A1298C variant genotypes and the risk of microsatellite instability among Iranian colorectal cancer patients,” Cancer Genetics and Cytogenetics, vol. 197, no. 2, pp. 142–151, 2010.

S. S. Promthet, C. Pientong, T. Ekalaksananan et al., “Risk factors for colon cancer in northeastern thailand: interaction of MTHFR codon 677 and 1298 genotypes with environmental factors,” Journal of Epidemiology, vol. 20, no. 4, pp. 329–338, 2010.

Y. Wettergren, E. Odin, S. Nilsson, et al., “MTHFR, MTR, and MTRR polymorphisms in relation to p16 (INK4A) gene promoter hypermethylation in colorectal mucosa and clinical outcome of patients with colorectal cancer,” Pteridines, vol. 20, no. 3, pp. 98–99, 2009.

A. Abuli, C. Fernandez-Rozadilla, V. Alonso-Espinaco et al., “Case-control study for colorectal cancer genetic susceptibility in EPICOLON: previously identified variants and mucins,” BMC Cancer, vol. 11, article 339, 2011.

J. L. M. Guimarães, M. D. L. Ayrizono, C. S. R. Coy, and C. S. P. Lima, “Gene polymorphisms involved in folate and methionine metabolism and increased risk of sporadic colorectal adenocarcinoma,” Tumor Biology, vol. 32, no. 5, pp. 853–861, 2011.

M. Jokić, K. Brčić-Kostić, J. Stefulj et al., “Association of MTHFR, MTR, MTRR, RFC1, and DHFR gene polymorphisms with susceptibility to sporadic colon cancer,” DNA and Cell Biology, vol. 30, no. 10, pp. 771–776, 2011.

A. S. Sameer, Z. A. Shah, S. Nissar, S. Mudassar, and M. A. Siddiqi, “Risk of colorectal cancer associated with the methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism in the Kashmiri population,” Genetics and Molecular Research, vol. 10, no. 2, pp. 1200–1210, 2011.

V. V. T. S. Prasad and H. Wilkhoo, “Association of the functional polymorphism C677T in the methylenetetrahydrofolate reductase gene with colorectal, thyroid, breast, ovarian, and cervical cancers,” Onkologie, vol. 34, no. 8-9, pp. 422–426, 2011.

J. E. Lee, E. K. Wei, C. S. Fuchs, et al., “Plasma folate, methylenetetrahydrofolate reductase (MTHFR), and colorectal cancer risk in three large nested case-control studies,” Cancer Causes and Control, vol. 23, no. 4, pp. 537–545, 2012.

S. de Vogel, K. A. D. Wouters, R. W. H. Gottschalk et al., “Genetic variants of methyl metabolizing enzymes and epigenetic regulators: associations with promoter CpG island hypermethylation in colorectal cancer,” Cancer Epidemiology Biomarkers and Prevention, vol. 18, no. 11, pp. 3086–3096, 2009.

B. T. Heijmans, J. M. A. Boer, H. E. D. Suchiman et al., “A common variant of the methylenetetrahydrofolate reductase gene (1p36) is associated with an increased risk of cancer,” Cancer Research, vol. 63, no. 6, pp. 1249–1253, 2003.

S. H. Downs and N. Black, “The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions,” Journal of Epidemiology and Community Health, vol. 52, no. 6, pp. 377–384, 1998.

R. DerSimonian and N. Laird, “Meta-analysis in clinical trials,” Controlled Clinical Trials, vol. 7, no. 3, pp. 177–188, 1986.

A. J. Silman and G. J. MacFarlane, Epidemiological Studies: A Practical Guide, Cambridge University Press, New York, NY, USA, 2nd edition, 2002.

“Review Manager (RevMan),” The Nordic Cochrane Centre, The Cochrane Collaboration, Copenhagen, Denmark, 2008

J. Hamling, P. Lee, R. Weitkunat, and M. Ambühl, “Facilitating meta-analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category,” Statistics in Medicine, vol. 27, no. 7, pp. 954–970, 2008.

J. Hamling, “Alternative comparisons from related odds ratios or relative risks: RR Est—relative risk estimation program,” P N Lee Statistics and Computing Ltd, 2007

C. B. Begg and M. Mazumdar, “Operating characteristics of a rank correlation test for publication bias,” Biometrics, vol. 50, no. 4, pp. 1088–1101, 1994.

M. Egger, G. D. Smith, M. Schneider, and C. Minder, “Bias in meta-analysis detected by a simple, graphical test,” British Medical Journal, vol. 315, no. 7109, pp. 629–634, 1997.

S. Duval and R. Tweedie, “Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis,” Biometrics, vol. 56, no. 2, pp. 455–463, 2000.

M. Borenstein, L. Hedges, J. Higgins, et al., Comprehensive Meta-Analysis Version 2.0, Biostat, Englewood, NJ, USA, 2005.

J. T. P. Higgins and S. Green, Cochrane Handbook for Systematic Reviews of Interventions, Wiley-Blackwell, Hoboken, NJ, USA, 2008.

J. Chen, E. Giovannucci, K. Kelsey et al., “A methylenetetrahydrofolate reductase polymorphism and the risk of colorectal cancer,” Cancer Research, vol. 56, no. 21, pp. 4862–4864, 1996.

M. L. Slattery, J. D. Potter, W. Samowitz, D. Schaffer, and M. Leppert, “Methylenetetrahydrofolate reductase, diet, and risk of colon cancer,” Cancer Epidemiology Biomarkers and Prevention, vol. 8, no. 6, pp. 513–518, 1999.

N. Matevska, T. Josifovski, A. Kapedanovska et al., “Methylenetetrahydrofolate reductase C677T polymorphism and risk of colorectal cancer in the macedonian population,” Balkan Journal of Medical Genetics, vol. 11, no. 2, pp. 17–24, 2008.

K. Chen, L. Song, M. J. Jin, C. H. Fan, Q. T. Jiang, and W. P. Yu, “Association between genetic polymorphisms in folate metabolic enzyme genes and colorectal cancer: a nested case-control study,” Zhonghua Zhong Liu Za Zhi, vol. 28, no. 6, pp. 429–432, 2006.

E. Taioli, M. A. Garza, Y. O. Ahn et al., “Meta-and pooled analyses of the methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism and colorectal cancer: a HuGE-GSEC review,” American Journal of Epidemiology, vol. 170, no. 10, pp. 1207–1221, 2009.

S. Kono and K. Chen, “Genetic polymorphisms of methylenetetrahydrofolate reductase and colorectal cancer and adenoma,” Cancer Science, vol. 96, no. 9, pp. 535–542, 2005.

N. A. Patsopoulos, E. Evangelou, and J. P. A. Ioannidis, “Sensitivity of between-study heterogeneity in meta-analysis: proposed metrics and empirical evaluation,” International Journal of Epidemiology, vol. 37, no. 5, pp. 1148–1157, 2008.

H. J. Blom and Y. Smulders, “Overview of homocysteine and folate metabolism. With special references to cardiovascular disease and neural tube defects,” Journal of Inherited Metabolic Disease, vol. 34, no. 1, pp. 75–81, 2011.

R. M. Pitkin, “Folate and neural tube defects,” American Journal of Clinical Nutrition, vol. 85, no. 1, pp. 285S–288S, 2007.

DRI, Dietary Reference Intakes for Thiamin, Riboflavin, Niacin, Vitamin Bb6s, Folate, Vitamin Bb12s, Pantothenic Acid, Biotin, and Choline, National Academy Press, Washington, DC, USA, 1998.

V. L. Stevens, M. L. McCullough, J. Sun, E. J. Jacobs, P. T. Campbell, and S. M. Gapstur, “High levels of folate from supplements and fortification are not associated with increased risk of colorectal cancer,” Gastroenterology, vol. 141, no. 1, pp. 98.e1–105.e1, 2011.