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. Author manuscript; available in PMC: 2011 Jun 1.
Published in final edited form as: Gut. 2009 Oct 14;59(6):794–799. doi: 10.1136/gut.2009.183707

DIETARY FOLATE, ALCOHOL, AND B VITAMINS IN RELATION TO LINE-1 HYPOMETHYLATION IN COLON CANCER

E S Schernhammer 1,2,3, E Giovannuccci 2, T Kawasaki 4, B Rosner 1, C S Fuchs 1,4, S Ogino 2,4,5
PMCID: PMC2895465  NIHMSID: NIHMS208650  PMID: 19828464

Abstract

BACKGROUND AND AIMS

Although critical for methylation reactions, how dietary folate and B vitamins affect global DNA methylation level in colon cancers is currently unknown. Long interspersed nucleotide element-1 (LINE-1) is an emerging indicator of genome-wide DNA methylation level that has previously been linked to colon cancer survival.

METHODS

We examined the association between dietary intake of folate, alcohol, and B vitamins and LINE-1 hypomethylation in 609 incident colon cancers, utilizing the database of two independent prospective cohort studies.

RESULTS

Participants with ≥400µg folate intake per day were significantly less likely to develop LINE-1 hypomethylated colon cancers than those reporting <200µg of folate intake per day (Relative risk (RR)=0.57, 95% confidence interval (CI)=0.36–0.91) for <55% LINE-1 methylated colon tumors; RR=0.74, 95% CI=0.51–1.06 for 55–64% LINE-1 methylated colon tumors; and RR=1.08, 95% CI=0.66–1.75 for ≥65% LINE-1 methylated tumors; Pinteraction=0.01). By contrast, high alcohol consumption conferred a higher risk of LINE-1 hypomethylated cancers (≥15g alcohol per day versus none, RR=1.67, 95% CI=1.04–2.67 for <55% LINE1 methylated tumors; and RR=1.55, 95% CI=1.10–2.18 for 55–64% LINE-1 methylated tumors) but had no association with ≥65% LINE-1 methylated tumors (RR=1.06, 95% CI=0.69–1.62). High intakes of vitamin B6, B12, or methionine were not significantly associated with colon cancers, regardless of LINE-1 methylation level.

CONCLUSION

The influence of dietary folate intake and alcohol consumption on colon cancer risk differs significantly according to tumoral LINE-1 methylation level.

Keywords: methylgroup donors, folate, vitamin B6, colorectal cancer, DNA methylation

INTRODUCTION

DNA methylation is an important epigenetic mechanism that plays a major role in gene silencing, imprinting and repression of endogenous retroviruses [1, 2, 3]. Genome-wide DNA hypomethylation is believed to play an important role in genomic instability and carcinogenesis [4, 5, 6, 7, 8, 9]. Several studies indicate a relation between global DNA hypomethylation and chromosomal instability (CIN) in tumor cells [5, 8, 9, 10, 11, 12]. Moreover, global DNA hypomethylation as determined by repetitive nucleotide elements such as LINE-1 (long interspersed nucleotide element-1) methylation level is inversely correlated with microsatellite instability (MSI) and the CpG island methylator phenotype [CIMP; [13]] In a prior (and to our knowledge, the first) large-scale survival study of 643 colon cancer patients, LINE-1 hypomethylation was associated with poor prognosis [14].

Folic acid and related B vitamins (one-carbon nutrients) are essential for DNA methylation and nucleotide biosynthesis; it is therefore plausible that chronic folate deficiency may be associated with global DNA methylation level. Adequate dietary intake of these nutrients has previously been related to a lower colon cancer risk [15, 16, 17], whereas alcohol consumption increases colorectal cancer risk,[18] likely through its anti-folate effects [19]. Whether one-carbon nutrient intake differentially affects subtypes of colon cancer stratified by global DNA methylation level has not been studied. We therefore assessed whether the influence of folate and B vitamin intake on colon cancer risk differed according to LINE-1 methylation level in two prospective cohort studies in which folate intake has been inversely associated with the risk of colon cancer [18, 20].

MATERIALS AND METHODS

Study Subjects and Covariate Assessment

Two independent prospective cohort studies, the Nurses’ Health Study (121,701 women followed since 1976 [21]) and the Health Professionals Follow-up Study (51,529 men followed since 1986 [22]), formed the study population. Information on potential risk factors and newly diagnosed cases of cancer was updated biennially. Dietary intake of various nutrients including folate, vitamin B6, B12, and methionine as well as daily alcohol consumption were assessed by self-administered semiquantitative food frequency questionnaires (SFFQ; [23, 24]) All nutrient contributions including those from supplements were added to the specific nutrient intake from foods to calculate a daily intake for each participant [23]. We assumed an ethanol content of 13.1 g for a 12-ounce (38-dl) can or bottle of beer, 11.0g for a 4-ounce (12-dl) glass of wine, and 14.0 g for a standard portion of spirits. After excluding participants who did not complete the baseline dietary questionnaire, or who reported a baseline history of cancer (except non-melanoma skin cancer), inflammatory bowel disease, hereditary nonpolyposis colorectal cancer, or a familial polyposis syndrome, 88,691 women and 47,365 men were eligible for analysis.

Ascertainment of Colon Cancer and Deaths

We included colon cancers reported in the NHS and the HPFS on biennial questionnaires between the return of the 1980 or 1986 questionnaires, respectively, and June 1, 2002. With permission from study participants, colon cancer was confirmed through physicians’ review of the participants’ medical records. If permission was denied, we attempted to confirm the self-reported cancer with an additional letter or phone call. We also searched the National Death Index to identify deaths among nonrespondents. The computerized National Death Index is a highly sensitive method for identifying deaths in these cohorts [25]. For all deaths attributable to colon cancer, we requested permission from family members (subject to state regulation) to review the medical records. Colon cancer was considered the cause of death if the medical records or autopsy reports confirmed fatal colon cancer or if colon cancer was listed as the underlying cause of death without another more plausible cause. We collected paraffin-embedded tissue blocks from hospitals where colon cancer patients underwent resections of primary tumors [22]. In a previous analysis of these cohorts, folate intake was significantly associated with the risk of colon cancer but had no influence on the risk of rectal cancer [20]; as a result, we did not include incident rectal cancer among the study participants in this analysis. Like rectal cancer cases, cases of colon cancer for which we were unable to assess LINE-1 methylation level were censored from the analyses at their date of diagnosis and were not included as endpoints.

Quantification of tumoral LINE-1 methylation levels

Based on the availability of adequate tissue specimens, we analyzed 606 colon cancers for LINE-1 methylation level. Characteristics of those cancers for whom we did and did not analyze for molecular markers have previously been found to be very similar.[22] In order to accurately quantify relatively high methylation levels, we utilized Pyrosequencing technology using the PyroMark kit and the PSQ HS 96 System (Biotage, Uppsala, Sweden) as previously described [13]. The nucleotide dispensation order was: ACT CAG TGT GTC AGT CAG TTA GTC TG. Complete conversion of cytosine at a non-CpG site ensured successful bisulfite conversion. The percentage of C relative to the sum of the amounts of C and T at each CpG site was calculated. The average of the relative amounts of C in the 4 CpG sites was used as overall LINE-1 methylation level in a given sample. Pyrosequencing to measure LINE-1 methylation has been previously validated and shown to be a good indicator of cellular 5-methylcytocine level [13, 26, 27].

Statistical Analyses

We used a previously described method of competing risk analysis utilizing duplication method Cox regression to compare the specific association of baseline intake of folate and other nutrients with colon cancer risk according to three categories of LINE-1 methylation level (<55%; 55–64%; and ≥65%) [28, 29]. We assessed the statistical significance of the difference between the risk estimates according to tumor type using a likelihood ratio test comparing the model that allowed for separate associations of folate and other nutrients according to LINE-1 methylation level with a model that assumed a common association. To represent interaction effects between dietary folate intake and LINE-1 methylation level, we created models with an indicator variable for LINE-1 methylation level in three categories as well as a product term of this indicator variable and dietary folate intake (continuously), and reported the Wald test statistic of this product term. Established or suspected risk factors for colon cancer were included in the multivariate models, as described at the bottom of Table 2. We used SAS version 9.1.3 (Cary, NC) for all analyses. Tissue collection and analyses were approved by the Harvard School of Public Health and Brigham and Women’s Hospital Institutional Review Boards.

Table 2.

Relative risk of baseline folate intake and colon cancer according to LINE-1 methylation level among 88,691 women from the Nurses’ Health Study (NHS) and 47,363 men from the Health Professionals Follow-up Study (HPFS).

Energy-adjusted Folate Intake, µg/day Ptrend
<200 200–299 300–399 ≥400
All cancer cases
 No. cases / Person-years 101 / 461357 166 / 756398 132 / 472313 210 / 873018
 Age-adjusted RR (95% CI) 1.0 0.84 (0.66–1.08) 0.91 (0.70–1.19) 0.79 (0.62–1.00) 0.07
 Multivariate RR (95% CI)* 1.0 0.80 (0.62–1.03) 0.82 (0.62–1.09) 0.76 (0.59–0.99) 0.16
LINE-1 low (<55%) cancer cases†
 No. cases / Person-years 31 / 461416 34 / 756511 36 / 472406 47 / 873179
 Age-adjusted RR (95% CI) 1.0 0.57 (0.35–0.92) 0.83 (0.51–1.34) 0.58 (0.37–0.92) 0.05
 Multivariate RR (95% CI)* 1.0 0.54 (0.33–0.88) 0.75 (0.46–1.23) 0.57 (0.36–0.91) 0.08
LINE-1 medium (55–64%) cancer cases†
 No. cases / Person-years 47 / 461399 77 / 756478 46 / 472394 95 / 873124
 Age-adjusted RR (95% CI) 1.0 0.84 (0.58–1.21) 0.68 (0.45–1.02) 0.76 (0.53–1.08) 0.21
 Multivariate RR (95% CI)* 1.0 0.80 (0.55–1.15) 0.61 (0.40–0.93) 0.74 (0.51–1.06) 0.31
LINE-1 high (≥65%) cancer cases†
 No. cases / Person-years 23 / 461420 55 / 756494 50 / 472383 68 / 873145
 Age-adjusted RR (95% CI) 1.0 1.23 (0.75–2.00) 1.51 (0.92–2.48) 1.11 (0.69–1.79) 0.92
 Multivariate RR (95% CI)* 1.0 1.17 (0.72–1.90) 1.36 (0.82–2.26) 1.08 (0.66–1.75) 0.94
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*

Multivariate models are adjusted for age (continuous), gender, energy intake (kcal), screening sigmoidoscopy or colonoscopy (yes/no), family history of colorectal cancer (yes/no), aspirin use (≥2 tablets/week or less), smoking (packyears), physical activity in METs (quintiles), body mass index in five categories (<21, 21–22.9, 23–24.9, 25–29.9, 30+), colon polyps (yes/no), beef intake (quintiles), calcium intake (quintiles), multi-vitamin use (yes/no), alcohol use (none, <5, 5–14.9, ≥15g/day), and intake of vitamin B6, B12, and methionine (quintiles).

†

LINE-1, long interspersed nucleotide element-1.

RESULTS

Among all 88,691 women and 47,363 men included in these analyses, those with a baseline folate intake of <200 µg/day were slightly more likely to eat meat and to smoke and less likely to exercise or use multivitamins (Table 1).

Table 1.

Age and age-standardized baseline characteristics of the Nurses’ Health Study and Health Professionals Follow-up cohort*

Energy-adjusted Folate Intake, µg/day
Women Men
Characteristic* <200 200–299 300–399 ≥400 <200 200–299 300–399 ≥400
N=20,907 N=28,882 N=12,997 N=25,905 N=1,512 N=10,121 N=13,423 N=22,307
Total intakeψ
 Folate (µg/day) 159 246 341 677 173 258 347 682
 Vitamin B6 (mg/day) 1.59 2.05 2.76 5.15 3.29 3.73 4.80 13.6
 Vitamin B12 (mg/day) 5.55 6.45 7.78 15.1 7.89 8.79 9.78 16.4
 Alcohol (g/day) 6.7 6.4 6.0 6.3 13.4 13.0 11.4 10.5
 Methionine (mg/day) 1.74 1.86 1.95 1.93 2.03 2.13 2.20 2.21
 Calcium (mg/day) 574 710 797 796 577 743 858 987
 Beef, pork, or lamb as a main dish (servings/week) 3.1 2.6 2.3 2.3 2.4 2.1 1.8 1.5
Other characteristics*
Median age (yr) 46.6 46.8 46.8 46.6 54.4 54.4 54.4 54.4
Former or current smoker (%) 60 56 54 55 60 55 51 50
 Pack-yr † 23.3 20.4 18.7 19.2 31.7 27.2 24.1 23.1
Regular aspirin user 31 32 32 35 26 27 28 32
Body mass index (kg/m2)‡ 24.4 24.5 24.3 24.0 25.8 25.9 25.6 25.3
Physical activity, METS/wk (%) § 11.1 13.8 15.8 15.6 12.9 17.0 20.5 23.7
Post-menopausal (%) 44 44 44 44 – – – –
 Never used hormones (%) 64 62 61 59 – – – –
 Past use of hormones (%) 18 19 19 19 – – – –
 Current use of hormones (%) 18 19 20 22 – – – –
Current multivitamin use (%) 8 13 24 84 12 15 23 67
Prior lower endoscopy (%) 2 2 2 2 22 24 26 27
Colorectal cancer in a parent or sibling (%) 8 8 7 8 9 8 8 9
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*

Dietary intake and other characteristics at baseline questionnaire in 1980 (NHS) and 1986 (HPFS). Mean value, unless otherwise indicated. All values have been directly standardized according to the age distribution of the cohort.

†

Pack-years were calculated for former and current smokers only.

‡

The body-mass index is the weight in kilograms divided by the square of the height in meters.

§

METS are metabolic equivalents. This was calculated based on the frequency of a range of physical activities (such as jogging) in 1986.

Hormones are defined as post-menopausal estrogen or estrogen/progesterone preparations. Percent of never, past, and current use was calculated among post-menopausal women only.

ψ

Nutrient values (folate, vitamin B6, B12, methionine, and calcium) represent the mean of energy-adjusted intake.

We documented 609 incident cases of colon cancer accessible for LINE-1 methylation data during 2,563,086 person-years. Of these, the LINE-1 methylation levels of 148 (24.3%) tumors were <55%, 265 (43.5%) were 55–64%, and 196 (32.2%) were ≥65%. LINE-1 methylation levels were approximately normally distributed (mean, 61.4%, median, 62.3%, standard deviation, 9.4). Median time interval between baseline folate intake and the diagnosis of incident colon cancer in our analyses was 17.2 years.

As in our previous studies [18, 20, 30, 31], we identified an inverse association between folate and vitamin B6 intake and colon cancer risk among all cases in this study. The multivariate relative risk of colon cancer was 0.76 (95% CI, 0.59–0.99) for total daily folate intake of ≥400 µg compared to <200 µg folate (Table 2). The influence of total folate intake differed according to LINE-1 methylation; comparing extreme categories of folate intake (≥ 400 µg/day versus <200 µg/day), the RR was 0.57 (95% CI, 0.36–0.91) for <55% LINE-1 methylated tumors, 0.74 (95% CI, 0.51–1.06) for 55–64% LINE-1 methylated tumors, and 1.08 (95% CI, 0.66–1.75) for ≥65% LINE-1 methylated tumors (Pinteraction = 0.01). In analyses restricted to folate from dietary sources, these RRs were generally similar albeit slightly weaker (data not shown). Similarly, using folate intake updated until up to 12 years before cancer diagnosis did not materially alter our results.

Next, we examined the influence of vitamin B6 intake according to LINE-1 methylation (Table 3). The benefit of vitamin B6 intake also appeared confined to <65% LINE-1 methylated tumors, though none of these associations was statistically significant. Of note, for both folate and B6 intake, risk was principally elevated among participants in the lowest category, whereas the risk did not appear to decline substantially beyond the second category of exposure. The influence of intake of vitamin B12 and methionine (in quintiles) on colon cancer did not appear to differ by LINE-1 status (Table 3).

Table 3.

Risk of colon cancer according to baseline quintiles of one-carbon nutrient intake by tumoral LINE-1 methylation level among 88,691 women and 47,363 men (NHS and HPFS combined).

Energy-adjusted daily
one-carbon nutrient
intake		 RR (95% CI)* Ptrend
Methionine (g) Q1 Q2 Q3 Q4 Q5
All cancer cases
 Cases / Person-years 136 / 511094 140 / 512592 99 / 517670 125 / 512400 109 / 509330
 Age-adjusted 1.0 1.02 (0.81–1.30) 0.71 (0.55–0.92) 0.88 (0.69–1.12) 0.72 (0.56–0.93) 0.22
 Multivariate* 1.0 1.03 (0.81–1.30) 0.72 (0.55–0.93) 0.91 (0.71–1.17) 0.77 (0.59–1.00) 0.10
LINE-1 low (<55%)†
 Cases / Person-years 33 / 511199 37 / 512685 29 / 517734 23 / 512491 26 / 509403
 Age-adjusted 1.0 1.12 (0.70–1.78) 0.86 (0.52–1.41) 0.67 (0.39–1.14) 0.71 (0.42–1.18) 0.51
 Multivariate* 1.0 1.12 (0.70–1.79) 0.86 (0.52–1.43) 0.69 (0.40–1.18) 0.76 (0.45–1.27) 0.36
LINE-1 medium (55–64%)†
 Cases / Person-years 54 / 511174 71 / 512653 36 / 517727 60 / 512457 44 / 509383
 Age-adjusted 1.0 1.31 (0.92–1.86) 0.65 (0.42–0.99) 1.06 (0.74–1.53) 0.73 (0.49–1.09) 0.06
 Multivariate* 1.0 1.31 (0.92–1.87) 0.66 (0.43–1.00) 1.10 (0.76–1.60) 0.78 (0.52–1.17) 0.03
LINE-1 high (≥65%)†
 Cases / Person-years 49 / 511171 32 / 514772 34 / 512686 42 / 517727 39 / 509393
 Age-adjusted 1.0 0.65 (0.42–1.02) 0.67 (0.44–1.04) 0.82 (0.54–1.24) 0.71 (0.47–1.09) 0.57
 Multivariate 1.0 0.65 (0.42–1.02) 0.68 (0.44–1.06) 0.85 (0.56–1.29) 0.76 (0.50–1.17) 0.81
Vitamin B6 (mg) Q1 Q2 Q3 Q4 Q5 P Trend
All cancer cases
 Cases / Person-years 135 / 518267 134 / 514617 116 / 513711 98 / 510531 126 / 505964
 Age-adjusted 1.0 0.91 (0.71–1.15) 0.70 (0.55–0.90) 0.60 (0.47–0.78) 0.77 (0.60–0.98) 0.47
 Multivariate* 1.0 0.92 (0.73–1.18) 0.75 (0.58–0.97) 0.66 (0.51–0.87) 0.88 (0.68–1.11) 0.40
LINE-1 low (<55%)†
 Cases / Person-years 36 / 518360 31 / 514695 27 / 513793 22 / 510606 32 / 506058
 Age-adjusted 1.0 0.79 (0.49–1.27) 0.61 (0.37–1.01) 0.51 (0.30–0.86) 0.73 (0.45–1.18) 0.88
 Multivariate* 1.0 0.80 (0.50–1.30) 0.65 (0.40–1.08) 0.56 (0.33–0.95) 0.84 (0.52–1.36) 0.83
LINE-1 medium (55–64%)†
 Cases / Person-years 62 / 518333 59 / 514677 48 / 513771 49 / 510573 47 / 506040
 Age-adjusted 1.0 0.87 (0.61–1.24) 0.63 (0.43–0.92) 0.66 (0.45–0.96) 0.62 (0.43–0.91) 0.91
 Multivariate* 1.0 0.89 (0.62–1.27) 0.68 (0.46–0.99) 0.72 (0.49–1.06) 0.71 (0.48–1.05) 0.86
LINE-1 high (≥65%)†
 Cases / Person-years 37 / 518353 44 / 514681 41 / 513775 27 / 510596 47 / 506037
 Age-adjusted 1.0 1.09 (0.70–1.68) 0.91 (0.51–1.42) 0.61 (0.37–1.00) 1.05 (0.68–1.61) 0.29
 Multivariate 1.0 1.11 (0.72–1.72) 0.97 (0.62–1.52) 0.67 (0.41–1.10) 1.20 (0.77–1.86) 0.25
Vitamin B12 (g) Q1 Q2 Q3 Q4 Q5 P Trend
All cancer cases
 Cases / Person-years 132 / 515939 120 / 515415 120 / 514236 123 / 509953 114 / 507543
 Age-adjusted 1.0 0.88 (0.69–1.13) 0.85 (0.66–1.09) 0.83 (0.65–1.06) 0.74 (0.58–0.96) 0.82
 Multivariate* 1.0 0.87 (0.68–1.11) 0.84 (0.66–1.08) 0.86 (0.67–1.11) 0.77 (0.59–0.99) 0.86
LINE-1 low (<55%)†
 Cases / Person-years 34 / 516037 37 / 515487 26 / 514318 27 / 510040 24 / 507630
 Age-adjusted 1.0 1.05 (0.66–1.68) 0.71 (0.43–1.19) 0.71 (0.43–1.17) 0.61 (0.36–1.02) 0.88
 Multivariate* 1.0 1.04 (0.65–1.65) 0.71 (0.43–1.18) 0.73 (0.44–1.22) 0.62 (0.37–1.06) 0.84
LINE-1 medium (55–64%)†
 Cases / Person-years 54 / 516011 49 / 515474 51 / 514301 57 / 510012 54 / 507596
 Age-adjusted 1.0 0.88 (0.60–1.30) 0.88 (0.60–1.29) 0.94 (0.65–1.37) 0.86 (0.59–1.25) 0.62
 Multivariate* 1.0 0.87 (0.59–1.28) 0.88 (0.60–1.29) 0.97 (0.67–1.42) 0.89 (0.61–1.30) 0.61
LINE-1 high (≥65%)†
 Cases / Person-years 44 / 516016 34 / 515484 43 / 514300 39 / 510027 36 / 507614
 Age-adjusted 1.0 0.75 (0.48–1.17) 0.91 (0.60–1.39) 0.79 (0.52–1.22) 0.71 (0.45–1.10) 0.99
 Multivariate 1.0 0.74 (0.47–1.16) 0.91 (0.60–1.39) 0.82 (0.53–1.27) 0.73 (0.47–1.13) 0.97
Alcohol (g) No alcohol <5 g/day 5–14.9 g/day ≥15 g/day P Trend
All cancer cases
 Cases / Person-years 157 / 759573 165 / 800196 145 / 608441 142 / 395877
 Age-adjusted 1.0 1.06 (0.85–1.31) 1.12 (0.89–1.40) 1.51 (1.21–1.90) 0.0001
 Multivariate* 1.0 1.08 (0.88–1.39) 1.10 (0.88–1.39) 1.41 (1.11–1.79) 0.01
LINE-1 low (<55%)†
 Cases / Person-years 35 / 758687 37 / 800305 39 / 608541 37 / 395979
 Age-adjusted 1.0 1.06 (0.67–1.69) 1.35 (0.86–2.13) 1.79 (1.12–2.84) 0.004
 Multivariate* 1.0 1.07 (0.68–1.71) 1.34 (0.85–2.12) 1.67 (1.04–2.67) 0.02
LINE-1 medium (55–64%)†
 Cases / Person-years 69 / 758650 70 / 800273 57 / 608526 69 / 395945
 Age-adjusted 1.0 1.02 (0.73–1.42) 1.00 (0.70–1.41) 1.67 (1.19–2.33) 0.002
 Multivariate* 1.0 1.03 (0.74–1.44) 0.99 (0.69–1.41) 1.55 (1.10–2.18) 0.03
LINE-1 high (≥65%)†
 Cases / Person-years 53 / 758658 58 / 800285 49 / 608528 36 / 395970
 Age-adjusted 1.0 1.10 (0.76–1.59) 1.11 (0.76–1.64) 1.13 (0.74–1.73) 0.48
 Multivariate 1.0 1.12 (0.77–1.62) 1.10 (0.75–1.63) 1.06 (0.69–1.62) 0.87
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*

All models are adjusted for age (continuous), energy intake, gender, screening sigmoidoscopy or colonoscopy, family history of colorectal cancer, aspirin use, smoking, physical activity in METs, baseline body mass index, a history of colon polyps, beef intake, calcium, multi-vitamin use, and baseline folate, vitamin B6, B12, methionine, and alcohol if not primary exposure.

Abbreviations: LINE-1, long interspersed nucleotide element-1.

We further evaluated the influence of alcohol consumption on colon cancer risk according to LINE-1 methylation level. For daily alcohol consumption (Table 3), the overall increased risk of colon cancer with ≥15g alcohol compared to no alcohol consumption (RR 1.41; 95% CI, 1.11–1.79) appeared to be essentially restricted to <65% LINE-1 methylated tumors. Comparing extreme categories of alcohol consumption, the RR was 1.67 (95% CI, 1.04–2.67; Ptrend = 0.02) for <55% LINE-1 methylated tumors, 1.55 (95% CI, 1.10–2.18; Ptrend = 0.03) for 55–64%, and 1.06 (95% CI, 0.69–1.62; Ptrend = 0.87) for ≥65% LINE-1 methylated tumors (Pinteraction = 0.13).

Because previous analyses have suggested that the association between alcohol consumption and colon carcinogenesis is increased in individuals with inadequate folate intake,[18] we examined dietary contrasts of total folate availability and daily alcohol consumption. The RR in participants with <299 µg folate intake/day and >5g alcohol consumption/day (i.e., dual depleted folate status) was 1.85 (95% 1.12–3.03) for <55% LINE-1 methylated tumors and 1.76 (95% CI, 1.17–2.64) for 55–64% LINE-1 methylated tumors, when compared to participants with ≥300 µg folate intake and <5g alcohol per day, whereas this RR was 1.04 (95% CI, 0.64–1.69) for ≥65% LINE-1 methylated tumors.

DISCUSSION

In this large prospective cohort study, we found that low folate and, to a lesser degree, vitamin B6 intake and excess alcohol consumption were associated with increased risk of colon cancers with LINE-1 hypomethylation. The elevation in risk was principally limited to participants with the lowest levels of folate and vitamin B6 intake, and no additional risk reduction was observed for intake beyond the second lowest category of consumption. Specifically, higher doses of either vitamin did not appear to confer any additional benefit. By contrast, the increased risk with alcohol consumption appeared to follow a linear dose-response. Overall, our data support a possible etiologic link between deficiency in some one-carbon nutrients and genome-wide DNA hypomethylation during colorectal carcinogenesis.

To our knowledge, no prior study has assessed the influence of one-carbon nutrients on colon cancer risk according to LINE-1 methylation level, and only two previous studies have examined colon cancer survival according to LINE-1 methylation level. The larger study was based on data from our own cohorts, reporting LINE-1 hypomethylation to be an independent predictor of shorter survival in colon cancer patients [14]. Another much smaller study (with only 93 tumors) also identified a trend (albeit non-significant) towards poor survival in DNA-hypomethylated tumors [32].

We have previously shown evidence supporting that folate prevents p53 mutational events in colorectal carcinogenesis, but we did observe no influence of folate on p53-wild-type tumors [33]. The processes underlying aggressive tumor behavior in LINE-1 hypomethylated tumors are currently unknown. Possible mechanisms include activation of retroviruses at transposons, which may cause genomic instability, in particular chromosomal instability [34, 35].

It is plausible that chronic folate deficiency may be associated with genome-wide DNA hypomethylation, given the importance of folate in DNA methylation and synthesis. Recent experimental data show a significant reduction in global DNA methylation level in colonic epithelial cells of mice with folate deficient diet [36]. A prior study explored the association between folate and other methyl donors and colon cancer subtypes [37]. While the overall inverse association between folate and colon cancer did not differ significantly according to microsatellite instability (MSI) status, there was the suggestion of a slightly stronger association between folate and MSI-high colon tumors (RR 0.79, 95% CI, 0.60–1.03 for microsatellite stable (MSS) /MSI-low colon cancers and RR 0.61, 95% CI, 0.37–1.02 for MSI-high colon cancers). Our current findings of a stronger association between low folate and LINE-1 hypomethylation are in line with a prior report that LINE-1 hypomethylation is inversely associated with MSI in these cohorts [13]. Further, as previously described, survival was poorer among colon cancer patients with deplete prediagnostic plasma folate in our cohorts [38]. If, as suggested by our data, LINE-1 hypomethylated colon tumors occur more frequently in folate deplete individuals, this provides compelling mechanistic support for the association between folate depletion and poor colon cancer survival.

In a recent report, Figueiredo et al. showed that folate supplementation did not alter LINE-1 methylation levels in normal colorectal mucosa [39]. Together with our data, this could suggest that folate levels may not be relevant in terms of LINE-1 methylation in normal mucosa, with relatively normal cellular kinetics, but once neoplasia develops some factor, possibly the increase in cellular proliferation, may reveal the relationship between folate and LINE-1 methylation.

Our study has several important strengths. First, because we collected detailed, updated information on a number of dietary and lifestyle covariates relevant to colon carcinogenesis over up to 22 years of follow-up and with high follow-up rates, we were able to examine long-term exposures to one-carbon nutrients and to take into consideration important confounding factors. Second, our study is prospective, eliminating concerns about differential recall bias, particularly with regard to our dietary assessments. Any remaining bias from exposure misclassification would thus be nondifferential by nature, biasing our results toward the null. Thirdly, our molecular characterization of colon cancer has proven very reliable, resulting in a number of interesting epidemiologic observations relating to colon cancer and tissue biomarkers [13, 14, 22, 37].

Limitations of note relate to folate fortification, which became mandatory in 1998 [40]. We did obtain multiple assessments of one-carbon nutrient intakes prior to fortification. In addition, since the development of colon cancer likely requires some induction period before the onset of a clinically apparent tumor, it is unlikely that the post-fortification folate exposure would substantially influence colon cancer risk through 2002. Another potential limitation is that we were unable to obtain tumor tissue from all cases of confirmed colon cancer in the two cohorts. However, risk factors in cases unavailable for tissue analysis did not appreciably differ from those in cases with tumor tissue available.

In conclusion, we show that the reduced risk of colon cancer associated with replete folate status varies by LINE-1 methylation level, an indicator of global DNA methylation status. Thus, genome-wide DNA hypomethylation may be one mechanism by which folate affects colon cancer risk and survival, but additional studies are needed to further elucidate these preventive effects.

ACKNOWLEDGMENTS

All of the authors declare no relevant conflict of interest. This work is supported by National Institutes of Health research grants CA70817, CA87969, CA55075, CA42812, CA58684, CA90598, CA122826, the Bennett Family Fund and Entertainment Industry Foundation, and the Entertainment Industry Foundation National Colorectal Cancer Research Alliance (NCCRA). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health. We thank the participants of the Nurses’ Health Study and Health Professionals Follow-up Study for their cooperation and participation, and hospitals and pathology departments throughout the US for generously providing us with tumor tissue materials. The authors are grateful to Gregory Kirkner for technical and administrative assistance.

Footnotes

The authors declare no conflict of interest relevant to this article

The corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence (or non exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd and its Licensees to permit this article (if accepted) to be published in Gut editions and any other BMJPGL products to exploit all subsidiary rights, as set out in our licence (http://group.bmj.com/products/journals/instructions-for-authors/licence-forms).

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