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Carcinogenesis Advance Access originally published online on January 3, 2008
Carcinogenesis 2008 29(2):356-362; doi:10.1093/carcin/bgm295
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

One-carbon metabolism-related gene polymorphisms and risk of breast cancer

Takeshi Suzuki1,*, Keitaro Matsuo1,4, Kaoru Hirose2, Akio Hiraki1, Takakazu Kawase1, Miki Watanabe1, Toshinari Yamashita3, Hiroji Iwata3 and Kazuo Tajima1,4

1 Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya 464-8681, Japan
2 Department of Planning and Information, Aichi Prefectural Institute of Public Health, 7-6 Azanagare, Tsujimachi, Kita-ku, Nagoya 462-8576, Japan
3 Department of Breast Oncology, Aichi Cancer Center Hospital, 1-1 Kanokoden, Chikusa-ku, Nagoya 464-8681, Japan
4 Department of Epidemiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan

* To whom correspondence should be addressed. Tel: +81 52 762 6111; Fax: +81 52 763 5233; Email: t-suzuki{at}aichi-cc.jp


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 Funding
 References
 
Environmental exposures and/or genetic background in Japanese population, which might contribute to the relatively low breast cancer incidence rates in Japan, have not been clarified in detail. Folate plays an essential role in DNA methylation and synthesis, and thus may be involved in the development of breast cancer. Functional polymorphisms in genes encoding one-carbon metabolism enzymes, methylenetetrahydrofolate reductase (MTHFR C677T), methionine synthase (MTR A2756G), methionine synthase reductase (MTRR A66G) and thymidylate synthase (TS), influence folate metabolism, but epidemiological studies have yielded inconsistent findings. We therefore conducted a case–control study to clarify their associations with breast cancer risk. A total of 456 breast cancer cases and 912 age-matched and menopausal status-matched non-cancer controls were genotyped for the polymorphisms. Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated using conditional logistic models adjusted for potential confounders and gene–environment interactions between the polymorphisms and folate consumption were also evaluated. We observed an increased risk of postmenopausal breast cancer with the MTHFR 677TT genotype (OR = 1.83, 95% CI: 1.08–3.11) with a menopausal status-based analysis. In combination analysis, a significantly elevated OR was found among postmenopausal women with the MTHFR 677TT genotype and lower intake of dietary folate compared with those with 677CC genotype and adequate folate consumption (OR = 2.80, 95% CI: 1.11–7.07). In addition, interaction between the MTRR A66G polymorphism and folate intake for risk of postmenopausal breast cancer was observed (interaction P = 0.008). Our findings indicated that the MTHFR and MTRR polymorphisms were associated with individual susceptibility to breast cancer among postmenopausal women.

Abbreviations: CI, confidence interval; FFQ, food frequency questionnaire; HERPACC, Hospital-based Epidemiologic Research Program at Aichi Cancer Center; MTHFR, methylenetetrahydrofolate reductase; MTR, methionine synthase; MTRR, methionine synthase reductase; OR, odds ratio; TS, thymidylate synthetase


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 Funding
 References
 
The incidence of female breast cancer in Japan has increased constantly from 17.0 per 100 000 (standardized on the world population) in 1975 to 39.5 in 2001 (1), although the prevalence continues to be much lower than in Western countries. There is an interesting difference in the age distribution of breast cancer between Japan and Western populations, the incidence in Japan increasing rapidly until menopause, and then reaching a plateau or decreasing (2). This may be attributed to different etiologies and there is considerable interest in identification of risk factors that may modify the risk of breast cancer in Japan.

High intake of folate, which is plentiful in vegetables and fruits, has been associated with reduced risk of several cancers. Biological functions of folate within so-called ‘one-carbon metabolism’ are to facilitate de novo deoxynucleoside triphosphate synthesis and to provide methyl groups required for intracellular methylation reactions. Folate deficiency is thought to increase the risk of cancer through impaired DNA repair synthesis and disruption of DNA methylation that may lead to protooncogene activation (3). Several large prospective epidemiological studies have suggested an importance of folate for breast cancer risk, particularly among women who regularly consume alcohol (4–6), although the results are not consistent (7,8).

Polymorphisms in critical enzymes involved in one-carbon metabolism, methylenetetrahydrofolate reductase (MTHFR), methionine synthase (MTR), methionine synthase reductase (MTRR) and thymidylate synthetase (TS), play important and interrelated roles in folate metabolism (Figure 1), thus these polymorphisms may influence the risk of cancer. MTHFR plays a central role, irreversibly converting 5,10-methylenetetrahydrofolate to 5-methyl tetrahydrofolate, the primary circulating form of folate. A change of C to T at nucleotide 677 in MTHFR C677T results in altered enzyme activity (9). Individuals with the 677TT genotype have ~30% the MTHFR enzyme activity of those with the 677CC genotype, whereas heterozygotes (677CT) have ~65%, as assessed in vitro (10). Reduced MTHFR enzyme capacity results in diminished 5-methyl tetrahydrofolate availability for homocysteine to be converted to methionine by MTR and MTRR, so that subjects with the MTHFR 677TT variant have lower methylation levels than those with other genotypes (11).


Figure 1
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  		Fig. 1. Overview of folate metabolism. Enzymes with polymorphisms investigated in this study are boxed. THF, tetrahydrofolate; DHF, dihydrofolate; dUMP, deoxyuridine monophoshate; dTMP, deoxythymidine monophoshate; SAM, S-adenosylmethionine and SAH, S-adenosylhomocysteine.

 
It has been suggested that breast carcinogenesis could be associated with alteration of estrogen receptor gene methylation patterns (12) and global DNA methylation (13). It is biologically plausible that polymorphisms or gene–environment interactions rather than the folate intake alone would have the impact on breast cancer risk since functional polymorphisms in folate-related genes contribute to the alteration of folate metabolism (14). Therefore, MTHFR polymorphisms have been intensively examined, but an effect of the polymorphism on breast cancer risk has not been consistently found (8,15). One problem may be that studies have been predominantly conducted in Caucasian populations, and information on breast cancer with respect to this polymorphism in other populations is limited. In addition, polymorphisms in other one-carbon-related metabolism gene, MTR, MTRR and TS, have been studied less thoroughly (15–20). Here, to evaluate the association between the polymorphisms of one-carbon-related metabolism gene and breast cancer risk, we conducted a case–control study using data from the Hospital-based Epidemiologic Research Program at Aichi Cancer Center (HERPACC).


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 Funding
 References
 
Study population
The subjects, aged 20–79 years, in the present study were enrolled between January 2001 and November 2005 in the framework of HERPACC. Details of the HERPACC have been described elsewhere (21,22). In brief, the first version of HERPACC (HERPACC-I) was initiated in Aichi Cancer Center Hospital, Nagoya, Japan, in 1988, with information on lifestyle factors collected from all first-visit outpatients including cancer and non-cancer patients. Following HERPACC-I, the second version of HERPACC (HERPACC-II) was launched in 2001, asking all first-visit outpatients to provide 7 ml of blood as well as information on lifestyle factors. Patients were asked about their lifestyle when healthy or before the current symptoms developed. Information from the questionnaire was systematically collected and checked by trained interviewers and completed by 96.7% of 29 538 eligible subjects in HERPACC-II. Of those who completed an interview, 50.7% donated a blood sample. Questionnaire data were loaded into the HERPACC database and periodically linked with the hospital cancer registry system to update on cancer incidence. All participants gave written informed consent and the study was approved by the Ethics Committee of Aichi Cancer Center.

Cases and controls
A total of 466 newly and histopathologically diagnosed breast cancer patients, who donated the completed questionnaire and blood samples, were deemed to be potential cases. We excluded 10 patients with a prior history of cancer, leaving 456 cases eligible for the analysis.

Control subjects were randomly selected from first-visit outpatients who visited our hospital at the same period. A total of 5728 women who donated the completed questionnaire and blood samples and were confirmed to have no cancer according to cancer registry and medical record were deemed to be potential controls. We excluded 385 patients with a prior history of cancer, leaving 5343 controls eligible for the analysis. Eventually, 912 controls were individually matched for age (±3 years) and menopausal status (premenopause or postmenopause) to cases with a 1:2 case–control ratio. On the examination at our hospital, 31% of the controls in this study had no abnormal finding, 20% had digestive diseases (e.g. gastric or colon polyp and hepatitis), 5% had respiratory diseases (e.g. pneumonia and benign tumors), 12% had benign breast diseases (e.g. fibroadenoma and mastopathy), 15% had gynecologic diseases (e.g. cervical dysplasia and ovarian cyst), 7% had head and neck diseases (e.g. benign tumors) and 9% had miscellaneous other illnesses (e.g. skin and orthopedic disorders). Our previous study demonstrated that it is feasible to use non-cancer outpatients at our hospital as controls in epidemiological studies because their general lifestyles are accordant with those of general population randomly selected from the electoral roll in Nagoya City, Aichi Prefecture (23). All subjects for the present study were Japanese, living in and around Aichi Prefecture, central Japan.

Genotyping of MTHFR, MTR, MTRR and TS
DNA of each subject was extracted from the buffy coat fraction using BioRobot EZ1 and an EZ1 DNA Blood 350 ml Kit (Qiagen, Tokyo, Japan). Genotyping for the MTHFR C677T (dbSNP ID: rs1801133), MTR A2756G (rs1805087) and MTRR A66G (rs1801394) were based on TaqMan Assays by Applied Biosystems (Foster City, CA). The TS 28 bp variable number of tandem repeat polymorphism was defined by polymerase chain reaction using 5'-CGTGGCTCCTGCGTTTCC-3' and 5'-GAGCCGGCCACAGGCAT-3' primers. In our laboratory, quality of genotyping was routinely assessed statistically by using the Hardy–Weinberg test. When allelic distributions for controls departed from the Hardy–Weinberg frequency, genotyping was assessed using direct sequencing.

Assessment of folate intake and other exposure
Food frequency questionnaire (FFQ) consisted of 47 single food items with frequencies in the eight categories of never or seldom, one to three times per month, one to two times per week, three to four times per week, five to six times per week, once per day, twice per day and more than three times per day (24,25). We estimated the average daily intake of nutrients by multiplying the food intake (in grams) by the nutrient content per 100 g of food as listed in the standard tables of food composition. Folate consumption from supplements could not be considered in total consumption because the questionnaire for multivitamins was not quantitative. Energy-adjusted intake of nutrients was calculated by the residual method (26). The FFQ was validated by referring to a 3 day weighed dietary record as a standard, which showed validity (27) and reproducibility (28) to be acceptable. The deattenuated correlation coefficients for energy-adjusted intakes of folate were 0.36 [95% confidence interval (CI): 0.12–0.58] in men and 0.38 (95% CI: 0.25–0.62) in women, respectively.

Total alcohol consumption was estimated as the summarized amount of pure alcohol consumption. Drinking habits were entered in the four categories of never, former, current moderate and heavy drinkers. Heavy drinkers were defined as those currently drinking alcoholic beverages 5 days or more per week in a daily amount of 23 g (one Japanese drinks) or more, whereas moderate drinkers were defined as those currently consuming less frequently than 5 days/week, in lower amounts or both. Cumulative smoking dose was evaluated as pack years, the product of the number of packs consumed per day and years of smoking. Smoking habits were entered under the four categories of never, former, current smokers of <20 and ≥20 pack years. Former drinkers or smokers were defined as those who quit drinking or smoking at least 1 year before the survey, respectively.

Statistical analysis
To assess the strength of the associations between polymorphic genes involved in folate metabolism and dietary folate intake and risk of breast cancer, odds ratios (ORs) with 95% CIs were estimated using age-matched and menopausal status-matched conditional logistic models adjusted for potential confounders. Folate and other nutrient intakes were categorized into three groups as first, second and third tertiles of dietary intake among controls. Potential confounders considered in the multivariate analyses were age, drinking habit (never drinkers, former drinkers, moderate or heavy drinkers), smoking habit (never smokers, former smokers and current smokers of <20 or ≥20 pack years), current body mass index (<18.5, 18.5–24.9 and ≥25.0), regular exercise (yes or no), family history of breast cancer (yes and no), total non-alcohol energy intake (as a continuous variable), dietary folate intake (microgram per day, tertiles), soybean products intake (gram per day, tertiles) (29), multivitamin use (at least once per week for 1 year or longer, yes or no), menopausal status (premenopause and postmenopause), age at menarche (≤12, 13–14 and ≥15), parity (0, 1–2 and ≥3), past usage of hormone replacement therapy (never, 1–6 months and >6 months), referral pattern to our hospital (patient's discretion, family or friends recommendation, referral from other clinics, secondary screening after primary screening or others) and age at menopause for postmenopausal women (≤47, 48–52 and ≥53). We used non-cancer patients at our hospital as controls, given the likelihood that our cases arose within this population base. To modify for any difference between cases and controls, we also adjusted for referral pattern. Menopause was defined as the complete cessation of menstrual bleeding due to natural, chemical or surgical causes (according to self-report). Differences in categorized demographic variables between the cases and controls were tested by the chi-squared test. Mean values for age and total non-alcohol energy intake were compared for cases and controls by the Student's t-test. Accordance with the Hardy–Weinberg equilibrium was checked for controls using the chi-squared test and used to assess any discrepancies between genotype and allele frequencies. As a basis for the trend test, the median values for each tertile of folate intake consumption were included in the model. Gene–environment interactions between folate intake and genotypes in each polymorphism were evaluated under the multiplicative model. Products of scores for genotype (0, homozygous genotype for reference allele; 1, heterozygote genotype and 2, homozygous genotype for non-reference allele) and folate intake (0, tertile 2 + 3 and 1, tertile 1) were included as interaction terms. A P value of <0.05 was considered statistically significant. All analyses were performed using STATA version 10 (Stata Corporation, College Station, TX).


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 Funding
 References
 
Data from 456 breast cancer cases and 912 controls were available for analysis. Table I shows the distribution of cases and controls by background characteristics. Age was appropriately matched. Neither the drinking nor the smoking habit significantly differed between the two groups. Lower intakes of folate and soybean products were found among the cases. With regard to referral pattern, family recommendation and referral from other clinics were more frequent, whereas patient's discretion and secondary screening were less common among the case group than the control group.


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  		Table I. Characteristics of case and controls

 
Table II shows the impact of dietary folate consumption on breast cancer risk according to menopausal status. Breast cancer risk was inversely associated with consumption of dietary folate. The adjusted OR was 0.65 (95% CI: 0.46–0.91) for the top tertile of folate intake compared with the lowest tertile of folate intake (trend P = 0.010). In subgroup analysis, a statistically significant reduced risk was observed among postmenopausal women with the top tertile intake of dietary folate (OR = 0.60, 95% CI: 0.38–0.97) compared with the lowest tertile of intake of folate, although the trend P did not reach statistical significance (P = 0.055).


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  		Table II. ORs and 95% CIs for dietary folate intake with risk of breast cancer

 
Table III shows genotype distributions for MTHFR, MTR, MTRR and TS and their ORs and 95% CIs for breast cancer risk. The genotype frequencies for all the polymorphisms were in accordance with the Hardy–Weinberg law in controls: MTHFR C677T (P = 0.52), MTR A2756G (P = 0.50), MTRR A66G (P = 0.19) and TS 28 bp variable number of tandem repeat (P = 0.72). In the analysis of breast cancer overall, none of the polymorphisms showed any significant impact on breast risk by genotype. On subgroup analysis according to menopausal status, MTRR A66G polymorphisms were associated with a slightly increased risk of breast cancer in premenopausal women (trend P = 0.041). In postmenopausal women, we found a significant increased risk of breast cancer among individuals with the MTHFR 677TT genotype (OR = 1.83, 95% CI: 1.08–3.11, trend P = 0.048) compared with those with the MTHFR 677CC genotype. Similar associations were observed in matched factors- (age and menopausal status) only analysis (OR = 1.46, 95% CI: 1.02–2.07 for MTHFR CT genotype and OR = 1.76, 95% CI: 1.13–2.76 for MTHFR TT genotype; trend P = 0.008).


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  		Table III. ORs and 95% CIs for MTHFR, MTR, MTRR and TS polymorphisms with risk of breast cancer

 
Joint associations of the polymorphisms and dietary folate with breast cancer risk are presented in Table IV. With respect to the MTHFR C677T polymorphism, compared with individuals with the 677CC genotype and adequate folate intake, elevation of breast cancer risk was most pronounced among 677TT women who consumed low levels of dietary folate among postmenopausal women (OR = 2.80, 95% CI: 1.11–7.07), although the interaction was not significant. There were interactions between folate intake and MTRR A66G in postmenopausal women (interaction P = 0.008). Significant interactions between drinking and smoking habit and these four polymorphisms were not found (data not shown).


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  		Table IV. Interaction between MTHFR, MTR, MTRR and TS polymorphisms and folate intake for breast cancer risk

 

   Discussion
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
Funding
 References
 
The results of the present study of associations between dietary folate intake or one-carbon metabolism-related gene polymorphisms and breast cancer risk suggested that (i) intake of dietary folate is inversely associated with breast cancer risk; (ii) the MTHFR 677TT genotype is positively associated with breast cancer risk among postmenopausal women and (iii) MTRR A66G may modify postmenopausal breast risk by folate consumption.

Many observational studies have highlighted the importance of adequate folate intake in breast cancer prevention, as reviewed in a recent meta-analysis, but the results were inconsistent (8). Almost all studies were conducted in predominantly USA populations, where fortification of folic acid intake with supplements causes difficulty in the evaluation of folate consumption (30). On the other hand, folate intake in Japan is almost exclusively from natural sources, mainly from plant sources such as vegetables, with spinach making the highest contribution followed by rice and green tea (31). However, few studies in Asia including Japan have investigated associations between folate intake and breast cancer risk (32) and further investigations in various populations are clearly warranted.

Our results showed individuals with MTHFR 677TT genotype to be at increased risk for postmenopausal breast cancer, whereas some case–control studies in other countries have failed to reveal an association between MTHFR C677T polymorphisms and breast cancer risk by menopausal status (16,33,34). One possible explanation for our results is that there is a difference in expression of estrogen receptors. The breast cancers in older women are more likely to express estrogen receptors than their counterparts in younger women (35). In postmenopausal women, the risk of breast cancer increases with increasing levels of endogenous estradiol (36). After menopause, adipose tissue is the major source of estrogen and obese postmenopausal women have both higher levels of endogenous estrogen and a higher risk of breast cancer (37). In addition, a prospective study of breast cancer risk noted stronger hormone replacement therapy effects in older women (38). These findings support the conclusion that development of postmenopausal breast cancers is predominantly dependent on estrogen receptor expression than premenopausal. Alterations of methylation patterns in the MTHFR 677TT genotype can result in estrogen receptor gene misregulation. Imbalance of DNA methylation in estrogen receptors may be more frequent in postmenopausal breast cancer patients.

The combined analysis in this study showed that individuals with the MTHFR 677TT genotype were at more increased risk of breast cancer with lower intake of dietary folate, consistent with previous studies (39,40). This is reasonable because enzyme activity with the MTHFR 677TT genotype is lower and thus less folate is available for DNA methylation. Our study also showed a significant interaction between the MTRR A66G and folate intake. The MTRR 66GG genotype increases the risk among postmenopausal women with low intake of folate, but not with adequate consumption of folate in the present study. While functional effects have yet to be fully established, the G allele of MTRR is considered to decrease the enzyme activity compared with the A allele (41). Subjects with MTRR 66GG may have reduced methionine levels compared with those who had other genotypes and therefore our finding of increased risk in low folate intake postmenopausal women is plausible. However, the results in this study may be chance due to small size of MTRR GG genotype and information on MTRR polymorphisms and breast cancer is scarce, thus further investigations are needed.

The age distribution of breast cancer incidence in Japanese women is very different from that in Western countries. The age trend falls after menopause in Japan, whereas the age-dependent elevation of risk in premenopausal women is somewhat similar in both countries. The drop in the age-specific incidence curve for breast cancer follows the average age of menopause. The difference in breast cancer incidence rate by the menopausal status may be attributed to environmental exposures and/or lifestyle. For instance, body mass index is inversely associated with premenopausal breast cancer, but is positively associated with postmenopausal breast cancer (42). The much lower prevalence of obesity in Japan than in USA may in part explain why the risk for postmenopausal breast cancer is lower in Japan than in USA. Increased production of endogenous estradiol by aromatase in adipose tissue affects the risk of developing postmenopausal breast cancer among high body mass index women (43), thus it may be reasonable that one-carbon metabolism-related polymorphisms affected on Japanese postmenopausal women with a little influence of estrogen.

In the present study, age and menopausal status confounding could be completely controlled by exact matching of these factors. The matched design validates a better estimate of menopausal status-based analysis. In addition, we estimated folate intake by using a validated questionnaire in a country that does not fortify foodstuffs with folate. Misclassification of the folate intake from foods is probably to be small.

Several methodological limitations of the study warrant consideration. First, as with other hospital-based case–control studies, the controls may have differed from the general population. Our previous comparison of lifestyle characteristics of HERPACC controls and individuals selected randomly from the general population in Nagoya city, however, confirmed no substantial difference (23). Referral patterns in Japan differ from those in USA, where people visit a local general clinic first and are then referred to a hospital, which functions as secondary and/or specific facility for further medical treatment. Like most general hospitals in Japan, in contrast, our hospital accepts new outpatients who visit of their own volition, with or without a doctor's referral, notwithstanding our description as a ‘Cancer Center’. Equivalence in the genotype distribution for the MTHFR C677T polymorphism between our controls and the general population in Japan has been confirmed (44). Second, data obtained from an FFQ may not accurately reflect folate intake. Nevertheless, the validity and reproducibility of the FFQ were acceptable (27,28). We could not consider consumption of folate from supplements in total consumption, but the proportion of users of only folate supplements is very low in Japan (0.1%) (45). Therefore, it appears that there are few Japanese who take the folate consciously. Third, we are completely unable to ignore recall of diet. However, the questionnaires were completed prior to the examination in our hospital, although in some cases patients referred to the hospital have known the diagnosis. Thus, it is likely that the effect of the bias is relatively small. Fourth, we did not examine the A1298C polymorphism of MTHFR that has been identified as other functional polymorphisms of the MTHFR gene (46). Future studies on the polymorphism are needed in this population. Lastly, our study had a modest sample size and influences might reach significance in a larger study. The powers for detection of the OR of 1.30 for MTHFR 677CT and 1.69 for MTHFR 677TT were 89% (alpha error = 0.05, two-sided) (47).

In summary, our case–control study adds to the increasing evidence that risk of breast cancer is reduced with increasing intake of dietary folate and provides some new evidence that the MTHFR 677TT genotype contributes to the etiology of breast cancer among postmenopausal women.


   Funding
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Funding
References
 
Grant-in Aid for Scientific Research on Cancer Epidemiology in a Special Priority Area (C) (17015052) from the Ministry of Education, Science, Sports, Culture and Technology of Japan; Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare of Japan.


   Acknowledgments
 
The authors are grateful to all the doctors, nurse's technical staff and hospital business staff of Aichi Cancer Center Hospital for the daily administration of the HERPACC study. We are greatly indebted to the staff of the Department of Breast Oncology, Aichi Cancer Center Hospital for their support and helpful discussions.

Conflict of Interest Statement: None declared.


   References
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Funding
 References
 

  1. Center for Cancer Control and Information Services, National Cancer Center. (2006) Cancer Incidence (1975–2001). Center for Cancer Control and Information Services, National Cancer Center, Japan.
  2. Matsuno RK, et al. Early- and late-onset breast cancer types among women in the United States and Japan. Cancer Epidemiol. Biomarkers Prev. (2007) 16:1437–1442.[Abstract/Free Full Text]
  3. Duthie SJ. Folic acid deficiency and cancer: mechanisms of DNA instability. Br. Med. Bull. (1999) 55:578–592.[Abstract/Free Full Text]
  4. Zhang S, et al. A prospective study of folate intake and the risk of breast cancer. JAMA (1999) 281:1632–1637.[Abstract/Free Full Text]
  5. Rohan TE, et al. Dietary folate consumption and breast cancer risk. J. Natl Cancer Inst. (2000) 92:266–269.[Free Full Text]
  6. Sellers TA, et al. Dietary folate intake, alcohol, and risk of breast cancer in a prospective study of postmenopausal women. Epidemiology (2001) 12:420–428.[CrossRef][Web of Science][Medline]
  7. Feigelson HS, et al. Alcohol, folate, methionine, and risk of incident breast cancer in the American Cancer Society Cancer Prevention Study II Nutrition Cohort. Cancer Epidemiol. Biomarkers Prev. (2003) 12:161–164.[Abstract/Free Full Text]
  8. Lewis SJ, et al. Meta-analyses of observational and genetic association studies of folate intakes or levels and breast cancer risk. J. Natl Cancer Inst. (2006) 98:1607–1622.[Abstract/Free Full Text]
  9. Goyette P, et al. Human methylenetetrahydrofolate reductase: isolation of cDNA, mapping and mutation identification. Nat. Genet. (1994) 7:195–200.[CrossRef][Web of Science][Medline]
  10. Rozen R. Genetic predisposition to hyperhomocysteinemia: deficiency of methylenetetrahydrofolate reductase (MTHFR). Thromb. Haemost. (1997) 78:523–526.[Web of Science][Medline]
  11. Friso S, et al. A common mutation in the 5,10-methylenetetrahydrofolate reductase gene affects genomic DNA methylation through an interaction with folate status. Proc. Natl Acad. Sci. USA (2002) 99:5606–5611.[Abstract/Free Full Text]
  12. Nass SJ, et al. CpG islands increases with malignant progression in human breast cancer. Cancer Res. (2000) 60:4346–4348.[Abstract/Free Full Text]
  13. Soares J, et al. Global DNA hypomethylation in breast carcinoma: correlation with prognostic factors and tumor progression. Cancer (1999) 85:112–118.[CrossRef][Web of Science][Medline]
  14. Sharp L, et al. Polymorphisms in genes involved in folate metabolism and colorectal neoplasia: a HuGE review. Am. J. Epidemiol. (2004) 159:423–443.[Abstract/Free Full Text]
  15. Lissowska J, et al. Genetic polymorphisms in the one-carbon metabolism pathway and breast cancer risk: a population-based case-control study and meta-analyses. Int. J. Cancer (2007) 120:2696–2703.[CrossRef][Medline]
  16. Justenhoven C, et al. One-carbon metabolism and breast cancer risk: no association of MTHFR, MTR, and TYMS polymorphisms in the GENICA study from Germany. Cancer Epidemiol. Biomarkers Prev. (2005) 14:3015–3018.[Free Full Text]
  17. Zhai X, et al. Polymorphisms in thymidylate synthase gene and susceptibility to breast cancer in a Chinese population: a case-control analysis. BMC Cancer (2006) 6:138.[CrossRef][Medline]
  18. Shrubsole MJ, et al. MTR and MTRR polymorphisms, dietary intake, and breast cancer risk. Cancer Epidemiol. Biomarkers Prev. (2006) 15:586–588.[Free Full Text]
  19. Xu X, et al. Polymorphisms of one-carbon-metabolizing genes and risk of breast cancer in a population-based study. Carcinogenesis (2007) 28:1504–1509.[Abstract/Free Full Text]
  20. Stevens VL, et al. Association of polymorphisms in one-carbon metabolism genes and postmenopausal breast cancer incidence. Cancer Epidemiol. Biomarkers Prev. (2007) 16:1140–1147.[Abstract/Free Full Text]
  21. Tajima K, et al. A Model of Practical Cancer Prevention for Out-patients Visiting a Hospital: the Hospital-based Epidemiologic Research Program at Aichi Cancer Center (HERPACC). Asian Pac. J. Cancer Prev. (2000) 1:35–47.[Medline]
  22. Hamajima N, et al. Gene-environment Interactions and Polymorphism Studies of Cancer Risk in the Hospital-based Epidemiologic Research Program at Aichi Cancer Center II (HERPACC-II). Asian Pac. J. Cancer Prev. (2001) 2:99–107.[Medline]
  23. Inoue M, et al. Epidemiological features of first-visit outpatients in Japan: comparison with general population and variation by sex, age, and season. J. Clin. Epidemiol. (1997) 50:69–77.[CrossRef][Web of Science][Medline]
  24. Tokudome S, et al. Development of data-based semi-quantitative food frequency questionnaire for dietary studies in middle-aged Japanese. Jpn. J. Clin. Oncol. (1998) 28:679–687.[Abstract/Free Full Text]
  25. Tokudome S, et al. Development of a data-based short food frequency questionnaire for assessing nutrient intake by middle-aged Japanese. Asian Pac. J. Cancer Prev. (2004) 5:40–43.[Medline]
  26. Willett W, et al. Total energy intake: implications for epidemiologic analyses. Am. J. Epidemiol. (1986) 124:17–27.[Free Full Text]
  27. Tokudome Y, et al. Relative validity of a short food frequency questionnaire for assessing nutrient intake versus three-day weighed diet records in middle-aged Japanese. J. Epidemiol. (2005) 15:135–145.[CrossRef][Web of Science][Medline]
  28. Imaeda N, et al. Reproducibility of a short food frequency questionnaire for Japanese general population. J. Epidemiol. (2007) 17:100–107.[CrossRef][Medline]
  29. Hirose K, et al. Soybean products and reduction of breast cancer risk: a case-control study in Japan. Br. J. Cancer (2005) 93:15–22.[CrossRef][Medline]
  30. Honein MA, et al. Impact of folic acid fortification of the US food supply on the occurrence of neural tube defects. JAMA (2001) 285:2981–2986.[Abstract/Free Full Text]
  31. Ishihara J, et al. Validity of a self-administered food frequency questionnaire (FFQ) and its generalizability to the estimation of dietary folate intake in Japan. Nutr. J. (2005) 4:26.[CrossRef][Medline]
  32. Shrubsole MJ, et al. Dietary folate intake and breast cancer risk: results from the Shanghai Breast Cancer Study. Cancer Res. (2001) 61:7136–7141.[Abstract/Free Full Text]
  33. Le Marchand L, et al. MTHFR polymorphisms, diet, HRT, and breast cancer risk: the multiethnic cohort study. Cancer Epidemiol. Biomarkers Prev. (2004) 13:2071–2077.[Abstract/Free Full Text]
  34. Lee SA, et al. Methylenetetrahydrofolate reductase polymorphism, diet, and breast cancer in Korean women. Exp. Mol. Med. (2004) 36:116–121.[Web of Science][Medline]
  35. Dunnwald LK, et al. Hormone receptor status, tumor characteristics, and prognosis: a prospective cohort of breast cancer patients. Breast Cancer Res. (2007) 9:R6.[CrossRef][Medline]
  36. Key T, et al. Endogenous sex hormones and breast cancer in postmenopausal women: reanalysis of nine prospective studies. J. Natl Cancer Inst. (2002) 94:606–616.[Abstract/Free Full Text]
  37. Harris JR, et al. Breast cancer (1). N. Engl. J. Med. (1992) 327:319–328.[Web of Science][Medline]
  38. Colditz GA, et al. The use of estrogens and progestins and the risk of breast cancer in postmenopausal women. N. Engl. J. Med. (1995) 332:1589–1593.[Abstract/Free Full Text]
  39. Shrubsole MJ, et al. MTHFR polymorphisms, dietary folate intake, and breast cancer risk: results from the Shanghai Breast Cancer Study. Cancer Epidemiol. Biomarkers Prev. (2004) 13:190–196.[Abstract/Free Full Text]
  40. Chen J, et al. One-carbon metabolism, MTHFR polymorphisms, and risk of breast cancer. Cancer Res. (2005) 65:1606–1614.[Abstract/Free Full Text]
  41. Olteanu H, et al. Differences in the efficiency of reductive activation of methionine synthase and exogenous electron acceptors between the common polymorphic variants of human methionine synthase reductase. Biochemistry Mosc. (2002) 41:13378–13385.[CrossRef]
  42. van den Brandt PA, et al. Pooled analysis of prospective cohort studies on height, weight, and breast cancer risk. Am. J. Epidemiol. (2000) 152:514–527.[Abstract/Free Full Text]
  43. Hankinson SE, et al. Alcohol, height, and adiposity in relation to estrogen and prolactin levels in postmenopausal women. J. Natl Cancer Inst. (1995) 87:1297–1302.[Abstract/Free Full Text]
  44. Yoshimura K, et al. Allele frequencies of single nucleotide polymorphisms (SNPs) in 40 candidate genes for gene-environment studies on cancer: data from population-based Japanese random samples. J. Hum. Genet. (2003) 48:654–658.[CrossRef][Web of Science][Medline]
  45. Imai T, et al. Dietary supplement use by community-living population in Japan: data from the National Institute for Longevity Sciences Longitudinal Study of Aging (NILS-LSA). J. Epidemiol. (2006) 16:249–260.[CrossRef][Web of Science][Medline]
  46. van der Put NM, et al. A second common mutation in the methylenetetrahydrofolate reductase gene: an additional risk factor for neural-tube defects? Am. J. Hum. Genet. (1998) 62:1044–1051.[CrossRef][Web of Science][Medline]
  47. Gauderman WJ. Sample size requirements for matched case-control studies of gene-environment interaction. Stat. Med. (2002) 21:35–50.[CrossRef][Web of Science][Medline]
Received November 13, 2007; revised December 15, 2007; accepted December 15, 2007.


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