Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2013 Aug 15.
Published in final edited form as: Int J Cancer. 2011 Nov 8;131(4):E518–E529. doi: 10.1002/ijc.26455

Folate, vitamin B6, vitamin B12, methionine and alcohol intake in relation to ovarian cancer risk

Holly R Harris 1, Daniel W Cramer 1,2, Allison F Vitonis 1, Mary DePari 1, Kathryn L Terry 1,2
PMCID: PMC3288483  NIHMSID: NIHMS327724  PMID: 21953625

Abstract

Folate, methionine, vitamin B6, and vitamin B12 may influence carcinogenesis due to their roles in the one-carbon metabolism pathway which is critical for DNA synthesis, methylation, and repair. Low intake of these nutrients has been associated with an increased risk of breast, colon, and endometrial cancers. Previous studies that have examined the relation between these nutrients and ovarian cancer risk have been inconsistent and have had limited power to examine the relation by histologic subtype. We investigated the association between folate, methionine, vitamin B6, vitamin B12, and alcohol among 1910 women with ovarian cancer and 1989 controls from a case-control study conducted in eastern Massachusetts and New Hampshire from 1992 to 2008. Diet was assessed via food frequency questionnaire. Participants were asked to recall diet one-year before diagnosis or interview. Logistic regression models were used to calculate odds ratios (OR) and 95% confidence intervals (95% CIs). We also examined whether the associations varied by ovarian cancer histologies using polytomous logistic regression. We observed an inverse association between dietary vitamin B6 (covariate-adjusted OR=0.76, 95% CI 0.64–0.92; ptrend=0.002) and methionine intake (covariate-adjusted OR=0.72, 95% CI=0.60–0.87; ptrend<0.001) and ovarian cancer risk comparing the highest to lowest quartile. The association with dietary vitamin B6 was strongest for serous borderline (covariate-adjusted OR=0.49, 95% CI=0.32–0.77; ptrend=0.001) and serous invasive (covariate-adjusted OR=0.74, 95% CI=0.58–0.94; ptrend=0.012) subtypes. Overall, we observed no significant association between folate and ovarian cancer risk. One-carbon metabolism related nutrients, especially vitamin B6 and methionine, may lower ovarian cancer risk.

Keywords: ovarian cancer, folate, alcohol, methionine, B-vitamins

INTRODUCTION

Folate, methionine, vitamin B6, and vitamin B12 may influence carcinogenesis due to their roles in the one-carbon metabolism pathway which is critical for DNA synthesis, methylation, and repair. In addition, alcohol and methionine, may influence folate’s physiologic effects. Alcohol inhibits folate at many levels including intestinal absorption, transport to tissues, storage, and release by the liver1 while methionine contributes to DNA methylation. Furthermore, some studies have found low intake of folate, methionine, vitamin B6, vitamin B12, and higher intake of alcohol have been associated with an increased risk of breast2, 3, colon cancer4–6, and endometrial cancer7–9. Folate receptor alpha, which is overexpressed in 90% of serous ovarian cancers10, has been shown to impart a growth advantage in vitro and has been identified as a potential target for immunologic therapies11, 12. Furthermore, folate receptor alpha expression is correlated with stage and grade of ovarian cancer, suggesting this pathway may be relevant to ovarian carcinogenesis and progression10.

Case-control studies that have examined the relation between dietary folate and ovarian cancer in women observed no association13–16, while most prospective studies have suggested a modest inverse association17–19. The few studies that have examined the associations of methionine and vitamin B6 with ovarian cancer risk have observed no association13, 19, and the one study that examined the association with vitamin B12 reported an inverse association16. Results for alcohol have been inconsistent20–34; but, a pooling project with 10 cohort studies reported no association35. Most of the previous studies examining the relation between these nutrients and ovarian cancer had limited power to examine the relation by histologic subtype. In addition, these studies occurred in populations not exposed to folic acid grain supplementation which was implemented by the United States in 1998.

In this study, we investigated whether folate, methionine, vitamin B6, vitamin B12 and alcohol intake were associated with ovarian cancer risk in the New England Case-Control Study. We also examined whether the associations were modified by the time period before and after folic acid grain supplementation, alcohol consumption, two polymorphisms of 5,10-methylene-tetrahydrofolate reductase (MTHFR), and histologic subtype.

MATERIALS AND METHODS

Study population

Data from the New England Case-Control Study (NECC) of ovarian cancer come from three enrollment phases (phase 1 1992–1997, phase 2 1998–2002, phase 3 2003–2008) corresponding to three funding periods. Details regarding case and control enrollment are described elsewhere36. Briefly, 3957 women residing in eastern Massachusetts or New Hampshire with a diagnosis of incident ovarian cancer were identified through hospital tumor boards and statewide cancer registries. Of these 3083 (78%) were eligible and 2203 (71%) agreed to participate. Controls were identified through a combination of random digit dialing, drivers’ license lists, and town resident lists. In the first phase, 420 (72%) of the eligible women identified through random digit dialing agreed to participate and 102 (51%) of the eligible women identified through townbooks agreed to participate. In the second and third phases, 4366 potential controls were identified, 2940 (67%) were eligible, 1362 (46%) declined to participate by phone or by mail via an “opt-out” postcard, and 1578 (54%) were enrolled. Controls were frequency matched to cases on age and state of residence.

All study participants were interviewed at the time of enrollment about known and suspected ovarian cancer risk factors. To avoid the possible impact of pre-clinical disease on exposure status, cases were asked about exposures that occurred at least one-year before diagnosis, and controls were asked about exposures that occurred more than one year before the interview date. This study was approved by the Institutional Review Boards of Brigham and Women’s Hospital and Dartmouth Medical School; each participant provided a signed informed consent.

Dietary assessment

Dietary data was collected using a semiquantitative food frequency questionnaire (FFQ), which asks how frequently food and beverage items were consumed (using common serving sizes) during the past year. Possible responses range from “almost never” to “six or more times per day”. Intake of folate, methionine, vitamin B6 and vitamin B12 were calculated by multiplying the frequency of consumption by the nutrient content of a serving size determined from the food composition values available from the US Department of Agriculture37. Total folate, total vitamin B6, total vitamin B12 include intake from multivitamins and supplements, while the dietary folate, dietary vitamin B6, and dietary vitamin B12 do not. The FFQ has been previously validated38–40 and has been shown to provide valid estimates of vitamin B6, vitamin B12 and alcohol intake with correlation coefficients between the FFQ and 1-week diet records of 0.58 for vitamin B640, 0.56 for vitamin B1238, and 0.90 for alcohol intake39. In addition, total folate as measured by the FFQ and erythrocyte folate concentration were correlated in Nurses’ Health Study (r=0.55)41. Methionine intake has not been validated with diet records. All dietary factors were adjusted for total energy using the residual method42.

Enrollment phase was used as a proxy for exposure to folic acid grain supplementation which was mandated by the United States in 1998. Participants in phase 2 (1998–2002) and phase 3 (2003–2008) were classified as exposed to folate supplementation (post-supplementation) while participants in phase 1 (1992–1997) were considered not exposed to supplementation (pre-suppplementation).

Genotyping methods

A detailed description of genotyping methods has been described previously.43 Briefly, over 95% of participants provided a blood sample. We genotyped MTHFR SNPs C677T (rs1801133) and A1298C (rs1801131) on whole genome amplified DNA from phase 1 and 2 participants at the Dana Farber Harvard Cancer Center High Throughput Polymorphism Detection Core. Gentoyping assays were performed by the 5′nuclease assay (Taqman®) on the Applied Biosystems Prism 7900HT Sequence Detection System (Applied Biosystems, Foster City, California). Concordance between the replicate samples was 100%.

Statistical analysis

Women were excluded if they did not complete a food frequency questionnaire (n=134) had an implausibly high (≥3500 calories) or low (≤ 500 calories) total energy intake (n=123). Intake of folate, methionine, vitamin B6, vitamin B12, and alcohol were categorized into quartiles based on the distribution among the controls. The quartile cutpoints for each nutrient were: dietary folate ≤ 268.6, 268.7–332.2, 332.3–400.6, ≥ 400.7 (mcg/day), total folate ≤ 325.5, 325.6–486.2, 486.3–724.3, ≥ 724.4 (mcg/day), methionine ≤ 1.5, 1.6–1.7, 1.8–2.0, ≥ 2.1 (g/day), dietary vitamin B6 ≤ 1.5, 1.6–1.7, 1.8–2.0, ≥ 2.1 (mg/day), total vitamin B6 ≤ 1.8, 1.9–2.7, 2.8–4.2, ≥ 4.3 (mg/day), dietary vitamin B12 ≤ 3.6, 3.7–4.8, 4.9–6.0 (mg/day), ≥ 6.1, total vitamin B12 ≤ 4.7, 4.8–8.3, 8.4–12.5, ≥ 12.6 (mg/day) and alcohol 0, 0.1–2.2, 2.3–8.2, ≥ 8.3 (g/day).

We calculated odds ratios (OR) and 95% confidence intervals (CI) using unconditional logistic regression. In the simple model we adjusted for age (continuous), study center (Massachusetts or New Hampshire) and total energy intake (continuous). In covariate-adjusted models, we adjusted for the following a priori potential confounders: oral contraceptive use (< 3, 3–24, 25–60, ≥ 61 months), parity (0, 1, 2, ≥ 3 liveborn), tubal ligation (yes, no), and family history of ovarian cancer (yes, no). In addition, race/ethnicity, education, and lactose intake were also assessed but were not included in the final models as they did not materially alter the risk estimates. Tests for trend were calculated using a trend variable based on the median nutrient value for each quartile category. To examine the joint effects of folate, methionine, and alcohol we calculated a methyl score4. A high methyl score was defined as alcohol intake <5 g/day and intake of folate and methionine in the highest quartile and a low methyl score was defined as alcohol intake ≥15 g/day and intake of folate and methionine in the lowest quartile. All other combinations were considered an intermediate methyl score.

Effect modification by alcohol intake (<5 g/day, ≥5 g/day), MTHFR polymorphism, and implementation of folate supplementation were assessed with a likelihood ratio test comparing a model with interaction terms and main effects to a model with only main effects. Analyses involving the MTHFR SNPs were restricted to Causasian study participants because allele frequencies varied by race. Polytomous logistic regression was used to test for heterogeneity in the effect estimates by ovarian cancer histologies (serous borderline, serous invasive, mucinous, endometrioid, clear cell). Statistical analyses were performed using SAS Version 9.2 (SAS Institute Inc, Cary, NC).

RESULTS

A total of 1910 women with ovarian cancer and 1989 controls were included in the final analytic sample. Cases were more likely than controls to be nulliparous but were less likely to have taken oral contraceptives or have had a tubal ligation (Table 1). Total energy (kcal/day) was higher among cases while energy-adjusted intake of dietary and total folate and vitamin B6 were slightly lower in cases than controls, but standard deviations were large.

Table 1.

Characteristics of study participants, New England Case-Control Study, 1992–2008

Case Control
n 1910 1989
Age (years), mean (SD) 54 (12) 53 (13)
Age at menarche, mean (SD) 13 (1) 13 (2)
BMI (kg/m2) at reference, mean (SD) 26 (6) 26 (6)
Multivitamin Use, n (%)
 Yes 979 (52) 1038 (53)
 No 919 (48) 928 (47)
Oral contraceptive use, n (%) 1003 (53) 1263 (64)
Number liveborn, n (%)
 0 616 (32) 353 (18)
 1 272 (14) 253 (13)
 2 500 (26) 634 (32)
 ≥3 522 (27) 749 (38)
Tubal ligation, n (%) 256 (13) 392 (20)
Family History of Ovarian cancer, n (%) 90 (5) 54 (3)
Total Calories (kcal), mean (SD) 1886 (574) 1851 (563)
Nutrients, mean (SD)
 Dietary folate (mcg/day) 346 (128) 350 (121)
 Total Folate (mcg/day) 539 (283) 560 (299)
 Methionine (g/day) 1.7 (0.4) 1.7 (0.4)
 Dietary B6 (mg/day) 1.7 (0.5) 1.8 (0.5)
 Total B6 (mg/day) 9.3 (25.7) 10.1 (27.0)
 Dietary B12 (mg/day) 5.6 (3.5) 5.4 (3.0)
 Total B12 (mg/day) 12.8 (16.3) 13.7 (19.5)
Alcohol (g/day) among drinkers, mean (SD) 8.8 (10.5) 8.7 (9.9)
Non-drinkers, n(%) 671 (35) 602 (30)
Tumor histology, n (%)
 Serous Borderline 226 (12)
 Serous Invasive 791 (41)
 Mucinous 217 (11)
 Endometrioid 306 (16)
 Clear Cell 243 (13)
 Other/undifferentiated 127 (7)
Open in a new tab

We observed a non-significant inverse association between dietary folate and ovarian cancer risk (covariate-adjusted OR=0.88, 95% CI 0.74–1.06) comparing the highest to lowest quartile (Table 2). This association was similar for total folate, which includes folate from non-dietary sources (covariate-adjusted OR=0.90, 95% CI=0.75–1.08). We observed no association between multivitamins (which make up approximately 30% of the total folate variable) and ovarian cancer (covariate-adjusted OR = 0.95, 95% CI=0.83–1.08). When we considered the association between dietary folate and ovarian cancer before the Food and Drug Administration (FDA) required folic acid supplementation of grains in 1998, the reduction in ovarian cancer risk for women in the highest quartile of folate intake was more apparent for women enrolled prior to supplementation (covariate-adjusted OR=0.57, 95% CI=0.37–0.87) compared to those enrolled after supplementation (covariate-adjusted OR=1.02, 95% CI=0.81–1.28) (pinteraction=0.001) (Table 3).

Table 2.

Odds ratios (OR) and 95% confidence intervals (CI) of ovarian cancer by quartile of one-carbon metabolism related nutrients, New England Case-Control Study, 1992–2008

Nutrient Controls
n (%)		 Cases
n (%)		 OR (95% CI)* MV Adjusted†
OR (95% CI)		 ptrend‡
Dietary folate
 Q1 498 (25) 521 (27) 1.00 1.00 0.18
 Q2 505 (25) 469 (25) 0.89 (0.75, 1.06) 0.89 (0.74, 1.06)
 Q3 458 (23) 409 (21) 0.85 (0.71, 1.02) 0.84 (0.69, 1.01)
 Q4 528 (27) 511 (27) 0.93 (0.78, 1.10) 0.88 (0.74, 1.06)
Total folate
 Q1 502 (25) 527 (28) 1.00 1.00 0.43
 Q2 481 (24) 431 (23) 0.83 (0.69, 1.00) 0.82 (0.68, 0.99)
 Q3 487 (24) 460 (24) 0.87 (0.73, 1.04) 0.85 (0.70, 1.02)
 Q4 519 (26) 492 (26) 0.90 (0.75, 1.07) 0.90 (0.75, 1.08)
Methionine
 Q1 516 (26) 592 (31) 1.00 1.00 <0.001
 Q2 421 (21) 412 (22) 0.85 (0.71, 1.02) 0.87 (0.72, 1.05)
 Q3 610 (31) 549 (29) 0.78 (0.66, 0.92) 0.79 (0.67, 0.94)
 Q4 442 (22) 357 (19) 0.71 (0.59, 0.85) 0.72 (0.60, 0.87)
Dietary B6
 Q1 518 (26) 582 (30) 1.00 1.00 0.002
 Q2 460 (23) 438 (23) 0.84 (0.70,1.00) 0.85 (0.71,1.02)
 Q3 538 (27) 465 (24) 0.76 (0.64,0.90) 0.76 (0.64,0.91)
 Q4 473 (24) 425 (22) 0.79 (0.66,0.94) 0.76 (0.63,0.91)
Total B6
 Q1 507 (25) 594 (31) 1.00 1.00 0.08
 Q2 472 (24) 379 (20) 0.65 (0.54,0.78) 0.63 (0.52,0.77)
 Q3 533 (27) 502 (26) 0.77 (0.65,0.92) 0.78 (0.65,0.93)
 Q4 477 (24) 435 (23) 0.75 (0.63,0.90) 0.73 (0.61,0.88)
Dietary B12
 Q1 476 (24) 491 (26) 1.00 1.00 0.76
 Q2 539 (27) 486 (25) 0.87 (0.73, 1.03) 0.91 (0.76, 1.09)
 Q3 465 (23) 422 (22) 0.87 (0.73, 1.05) 0.91 (0.76, 1.10)
 Q4 509 (26) 511 (27) 0.95 (0.80, 1.14) 0.95 (0.79, 1.14)
Total B12
 Q1 466 (23) 463 (24) 1.00 1.00 0.56
 Q2 522 (26) 502 (26) 0.94 (0.78, 1.12) 0.95 (0.79, 1.15)
 Q3 506 (25) 458 (24) 0.89 (0.74, 1.07) 0.89 (0.74, 1.08)
 Q4 495 (25) 487 (26) 0.97 (0.80, 1.16) 0.93 (0.77, 1.12)
Alcohol
 Q1 602 (30) 671 (35) 1.00 1.00 0.21
 Q2 390 (20) 376 (20) 0.86 (0.72, 1.03) 0.88 (0.73, 1.07)
 Q3 503 (25) 411 (22) 0.73 (0.62, 0.87) 0.77 (0.64, 0.92)
 Q4 494 (25) 452 (24) 0.83 (0.70, 0.98) 0.86 (0.72, 1.03)
Methyl score§
 Low 23 (1) 28 (1) 1.00 1.00 0.14
 Middle 1882 (95) 1813 (95) 0.79 (0.46, 1.38) 0.66 (0.37, 1.18)
 High 84 (4) 69 (4) 0.68 (0.36, 1.29) 0.57 (0.30, 1.11)
Open in a new tab
*

Adjusted for age, study center, total energy.

†

Adjusted for age, study center, total energy, oral contraceptive use, parity, tubal ligation, and family history of ovarian cancer.

‡

Tests for trend were performed using the median of the interval for each quartile and correspond to the MV adjusted analyses. Medians for dietary categories in controls are as follows: dietary folate (234.0 mcg/day, 300.5, 362.5, 465.5), total folate (257.6 mcg/day, 397.0, 613.4, 856.5), alcohol (0 g/day, 1.2, 4.6,

14.5) methionine (1.3 g/day, 1.6, 1.8, 2.2), dietary B6 (1.3 mg/day, 1.6, 1.8, 2.2), total B6 (1.5 mg/day, 2.1, 3.5, 7.3), dietary B12 (2.9 mg/day, 4.2, 5.3, 8.2), total B12 (3.7 mg/day, 6.0, 10.2, 25.0).

§

A low methyl score was defined as alcohol intake ≥ 15 g/d and folate and methionine intake in the lowest quartile; a high methyl score was defined as alcohol intake <5 g/d and folate and methionine intake in the highest quartile; all other were considered the middle score.

Table 3.

Odds ratios (OR) and 95% confidence intervals (CI) of ovarian cancer by quartile of one-carbon metabolism related nutrients, pre (1992–97) and post (1998–2008) folic acid grain supplementation enrollment status*, New England Case-Control Study

Participants enrolled between 1992–1997 Participants enrolled between 1998–2008
Nutrient Cases
n (%)		 Controls
n (%)		 MV Adjusted†
OR (95% CI)		 ptrend‡ Cases
n (%)		 Controls
n (%)		 MV Adjusted†
OR (95% CI)		 ptrend‡ pinteraction
Dietary folate
 Q1 285 (54) 240 (48) 1.00 0.002 236 (17) 258 (17) 1.00 0.94 0.001
 Q2 119 (23) 124 (25) 0.73 (0.53,1.00) 350 (25) 381 (26) 1.02 (0.80,1.29)
 Q3 67 (13) 76 (15) 0.65 (0.44,0.96) 342 (25) 382 (26) 0.96 (0.75,1.21)
 Q4 54 (10) 63 (13) 0.57 (0.37,0.87) 457 (33) 465 (31) 1.02 (0.81,1.28)
Total folate
 Q1 275 (52) 248 (49) 1.00 0.70 252 (18) 254 (17) 1.00 0.38 0.42
 Q2 95 (18) 130 (26) 0.67 (0.48,0.94) 346 (25) 366 (25) 0.86 (0.67,1.09)
 Q3 100 (19) 83 (16) 0.98 (0.69,1.39) 350 (25) 389 (26) 0.80 (0.63,1.02)
 Q4 55 (11) 42 (8) 1.12 (0.71,1.76) 437 (32) 477 (32) 0.87 (0.69,1.09)
Methionine
 Q1 192 (37) 157 (31) 1.00 0.02 400 (29) 359 (24) 1.00 0.005 0.72
 Q2 119 (23) 101 (20) 0.99 (0.70,1.40) 293 (21) 320 (22) 0.84 (0.67,1.04)
 Q3 135 (26) 144 (29) 0.75 (0.54,1.04) 414 (30) 466 (31) 0.80 (0.65,0.98)
 Q4 79 (15) 101 (20) 0.66 (0.46,0.97) 278 (20) 341 (23) 0.73 (0.59,0.91)
Dietary B6
 Q1 201 (38) 141 (28) 1.00 <0.0001 381 (28) 377 (25) 1.00 0.16 0.05
 Q2 102 (19) 107 (21) 0.65 (0.45,0.93) 336 (24) 353 (24) 0.94 (0.76,1.16)
 Q3 112 (21) 119 (24) 0.62 (0.44,0.88) 353 (25) 419 (28) 0.83 (0.67,1.02)
 Q4 110 (21) 136 (27) 0.49 (0.35,0.70) 315 (23) 337 (23) 0.88 (0.70,1.09)
Total B6
 Q1 215 (41) 185 (37) 1.00 0.42 379 (27) 322 (22) 1.00 0.15 0.35
 Q2 118 (22) 140 (28) 0.69 (0.50,0.97) 261 (19) 332 (22) 0.60 (0.48,0.76)
 Q3 104 (19) 85 (17) 1.01 (0.70,1.45) 398 (29) 448 (30) 0.72 (0.58,0.89)
 Q4 88 (17) 93 (18) 0.77 (0.53,1.11) 347 (25) 384 (26) 0.71 (0.57,0.89)
Dietary B12
 Q1 158 (30) 124 (25) 1.00 0.57 333 (24) 352 (24) 1.00 0.93 0.59
 Q2 128 (24) 139 (28) 0.75 (0.53,1.06) 358 (26) 400 (27) 1.00 (0.81,1.24)
 Q3 101 (19) 121 (24) 0.69 (0.47,0.99) 321 (23) 344 (23) 1.02 (0.82,1.28)
 Q4 138 (26) 119 (24) 0.85 (0.59,1.21) 373 (27) 390 (26) 1.01 (0.81,1.25)
Total B12
 Q1 160 (30) 160 (32) 1.00 0.87 303 (22) 306 (21) 1.00 0.60 0.60
 Q2 160 (30) 154 (31) 1.11 (0.80,1.54) 342 (25) 368 (25) 0.89 (0.71,1.12)
 Q3 110 (21) 109 (22) 1.01 (0.70,1.45) 348 (25) 397 (27) 0.86 (0.69,1.08)
 Q4 95 (18) 80 (16) 1.07 (0.73,1.58) 392 (28) 415 (28) 0.89 (0.71,1.12)
Alcohol
 Q1 193 (37) 176 (35) 1.00 0.58 478 (35) 426 (29) 1.00 0.08 0.14
 Q2 114 (22) 108 (21) 1.03 (0.73,1.46) 262 (19) 282 (19) 0.83 (0.67,1.04)
 Q3 100 (19) 116 (23) 0.86 (0.61,1.23) 311 (22) 387 (26) 0.74 (0.60,0.91)
 Q4 118 (22) 103 (20) 1.11 (0.78,1.57) 334 (24) 391 (26) 0.79 (0.64,0.97)
Open in a new tab
*

Enrollment phase was used as a proxy for exposure to folic acid grain supplementation. Participants in phase 2 (1998–2002) and phase 3 (2003–2008) were classified as post-supplementation and participants in phase 1 (1992–97) were classified as pre-supplementation.

†

Adjusted for age, study center, total energy, oral contraceptive use, parity, tubal ligation, and family history of ovarian cancer.

‡

Tests for trend were performed using the median of the interval for each quartile.

We observed an inverse association between methionine intake and ovarian cancer risk (Table 2). Compared to women in the lowest quartile of methionine intake, women in the highest quartile had a significant reduction in ovarian cancer risk (covariate-adjusted OR=0.72, 95% CI=0.60–0.87; ptrend<0.001). An inverse association was also observed between dietary vitamin B6 and ovarian cancer risk (covariate-adjusted OR=0.76, 95% CI 0.63–0.91; ptrend=0.002). This association was similar for total vitamin B6 intake (covariate-adjusted OR=0.73, 95% CI=0.61–0.88), however the trend was no longer significant (ptrend=0.076). No association was observed for dietary vitamin B12 or total vitamin B12. When we considered mutual adjustment for folate, vitamin B6, vitamin B12, and methionine the association with methionine remained significant (covariate-adjusted OR=0.75, 95% CI=0.60–0.93; ptrend=0.003) while the association with vitamin B6 was borderline significant (covariate-adjusted OR=0.80, 95% CI 0.64–1.01; ptrend=0.059).

For women in the highest two quartiles of alcohol intake there was the suggestion of an inverse association with ovarian cancer (covariate-adjusted OR for third quartile=0.77, 95% CI=0.64–0.92 and fourth quartile=0.86, 95% CI=0.72–1.03) compared to women in the lowest quartile although the trend was not significant (ptrend=0.206) (Table 2). When women with any intake of alcohol were compared to those with no alcohol intake, alcohol drinkers had a 17% lower risk of ovarian cancer compared to non-drinkers (95% CI=0.73–0.96), but this was attenuated after adjustment for education and race (OR=0.89, 95% CI=0.77–1.03).

Alcohol consumption was most strongly inversely associated with risk among women whose total folate was below the median value in the controls (486.3 mcg/day). The covariate-adjusted OR in this group was 0.70 (95% CI=0.55–0.90; ptrend=0.002) comparing the highest to lowest quartile. The corresponding value for women above the median was 1.06 (95% CI=0.82–1.36; ptrend=0.286) (data not shown). In addition, the association between total folate and ovarian cancer differed by alcohol consumption (<5 g/d vs ≥5 g/d) (pinteraction=0.049). Among women consuming <5 g/day a statistically significant inverse association was observed (covariate-adjusted OR=0.78, 95% CI=0.62–0.98; ptrend=0.047) while total folate was not associated with ovarian cancer risk in women consuming ≥5 g/d. A similar pattern was observed for dietary folate, dietary B6 and B12, and total B6 and B12 but these results were not significant (all pinteraction>0.05) (Table 4). The association between methionine and ovarian cancer did not vary by alcohol consumption.

Table 4.

Odds ratios (OR) and 95% confidence intervals (CI) of ovarian cancer by quartile of one-carbon metabolism related nutrients stratified by alcohol intake, New England Case-Control Study, 1992–2008

<5 g/day ≥5 g/day
Nutrient Cases
n (%)		 Controls
n (%)		 MV Adjusted*
OR (95% CI)		 ptrend ‡ Cases
n (%)		 Controls
n (%)		 MV Adjusted*
OR (95% CI)		 ptrend† pinteraction
Dietary folate †
 Q1 364 (29) 328 (26) 1.00 0.06 157 (25) 170 (24) 1.00 0.69 0.11
 Q2 312 (24) 314 (24) 0.89 (0.71,1.12) 157 (25) 191 (27) 0.88 (0.64,1.21)
 Q3 261 (20) 288 (23) 0.77 (0.61,0.98) 148 (23) 170 (24) 0.99 (0.71,1.36)
 Q4 339 (27) 349 (27) 0.82 (0.65,1.02) 172 (27) 179 (25) 1.02 (0.74,1.40)
Total folate
 Q1 367 (29) 319 (25) 1.00 0.05 160 (25) 183 (26) 1.00 0.17 0.05
 Q2 298 (23) 308 (24) 0.80 (0.64,1.01) 134 (21) 178 (25) 0.87 (0.63,1.21)
 Q3 298 (23) 314 (25) 0.78 (0.62,0.99) 161 (25) 168 (24) 1.00 (0.73,1.39)
 Q4 313 (25) 338 (26) 0.78 (0.62,0.98) 179 (28) 181 (25) 1.18 (0.86,1.61)
Methionine
 Q1 378 (30) 328 (26) 1.00 0.009 214 (34) 188 (26) 1.00 0.006 0.92
 Q2 267 (21) 267 (21) 0.88 (0.70,1.11) 145 (23) 154 (22) 0.86 (0.63,1.17)
 Q3 377 (30) 392 (31) 0.80 (0.65,0.99) 172 (27) 218 (31) 0.76 (0.57,1.02)
 Q4 254 (20) 292 (23) 0.75 (0.59,0.94) 103 (16) 150 (21) 0.65 (0.46,0.90)
Dietary B6
 Q1 387 (30) 320 (25) 1.00 0.0005 195 (31) 198 (28) 1.00 0.57 0.16
 Q2 296 (23) 293 (23) 0.82 (0.65,1.03) 142 (22) 167 (23) 0.90 (0.66,1.23)
 Q3 309 (24) 344 (27) 0.71 (0.57,0.89) 156 (24) 194 (27) 0.84 (0.62,1.14)
 Q4 284 (22) 322 (25) 0.68 (0.54,0.85) 141 (22) 151 (22) 0.93 (0.68,1.28)
Total B6
 Q1 414 (32) 304 (24) 1.00 0.002 180 (28) 203 (29) 1.00 0.24 0.91
 Q2 258 (20) 312 (24) 0.55 (0.43,0.70) 121 (19) 160 (23) 0.82 (0.59,1.14)
 Q3 324 (25) 337 (26) 0.67 (0.54,0.84) 178 (28) 196 (28) 0.99 (0.73,1.34)
 Q4 280 (22) 326 (25) 0.58 (0.46,0.73) 155 (25) 151 (21) 1.11 (0.81,1.52)
Dietary B12
 Q1 311 (24) 293 (23) 1.00 0.24 180 (28) 183 (26) 1.00 0.33 0.91
 Q2 333 (26) 333 (26) 1.01 (0.80,1.27) 153 (24) 206 (29) 0.76 (0.56,1.03)
 Q3 283 (22) 298 (23) 0.93 (0.74,1.18) 139 (22) 167 (24) 0.87 (0.63,1.20)
 Q4 349 (27) 355 (28) 0.89 (0.71,1.12) 162 (26) 154 (22) 1.07 (0.78,1.47)
Total B12
 Q1 311 (24) 284 (22) 1.00 0.05 152 (24) 182 (26) 1.00 0.10 0.18
 Q2 348 (27) 334 (26) 0.94 (0.75,1.19) 154 (24) 188 (26) 0.95 (0.69,1.31)
 Q3 302 (24) 325 (25) 0.82 (0.65,1.04) 156 (25) 181 (25) 1.03 (0.75,1.42)
 Q4 315 (25) 336 (26) 0.79 (0.62,1.00) 172 (27) 159 (22) 1.24 (0.90,1.72)
Open in a new tab
*

Adjusted for age, study center, total energy, oral contraceptive use, parity, tubal ligation, and family history of ovarian cancer.

†

Tests for trend were performed using the median of the interval for each quartile.

A high methyl score (alcohol intake <5 g/day and intake of folate and methionine in the highest quartile) was non-significant inverse associated with ovarian cancer risk with a covariate-adjusted OR of 0.57 (95% CI 0.30–1.11) compared to those with a low methyl score (alcohol intake ≥15 g/day and intake of folate and methionine in the lowest quartile) (Table 2); however, these results are based on small numbers in the low methyl group.

No interactions were observed by the C677T polymorphism (Supplemental Table 1) and only one significant interaction was observed by the A1298C polymorphism (Supplemental Table 2). Methionine was statistically significantly inversely associated with ovarian cancer risk among women who were wildtype for A1298C (covariate-adjusted OR=0.59, 95% CI 0.40–0.86), while this association was not significant among women who were heterozygous or homozygous for the minor allele (pinteraction=0.011).

We also evaluated the association between dietary factors and risk of ovarian cancer defined by histologic subtypes. The association with dietary vitamin B6 differed significantly by histologic subtype (pheterogeneity=0.027) with the strongest inverse associations observed for the serious borderline (covariate-adjusted OR=0.49, 95% CI=0.31–0.76; ptrend=0.001) and serous invasive (covariate-adjusted OR=0.74, 95% CI=0.58–0.94; ptrend=0.012) subtypes. No statistically significant differences by histologic subtype were observed for the other nutrients or alcohol (Table 5).

Table 5.

Odds ratios* (OR) and 95% confidence intervals (CI) of ovarian cancer by quartile of one-carbon metabolism related nutrients by histologic subtype, New England Case-Control Study, 1992–2008

Controls Serous Borderline Serous Invasive Mucinous Endometrioid Clear Cell
N (%) N (%) MV Adjusted OR N (%) MV Adjusted OR N (%) MV Adjusted OR N (%) MV Adjusted OR N (%) MV Adjusted OR
Dietary folate
 Q1 498 (25) 81 (36) 1.00 191 (24) 1.00 72 (33) 1.00 84 (28) 1.00 58 (24) 1.00
 Q2 505 (25) 50 (22) 0.67 (0.46,0.98) 203 (26) 1.00 (0.79,1.28) 46 (21) 0.68 (0.45,1.01) 77 (25) 0.88 (0.63,1.24) 62 (26) 1.05 (0.71,1.54)
 Q3 458 (23) 52 (23) 0.79 (0.54,1.15) 157 (20) 0.84 (0.65,1.08) 47 (22) 0.77 (0.52,1.14) 75 (25) 0.95 (0.67,1.34) 57 (24) 1.05 (0.70,1.55)
 Q4 528 (26) 43 (19) 0.56 (0.38,0.84) 240 (31) 1.05 (0.83,1.33) 52 (24) 0.74 (0.50,1.09) 70 (23) 0.73 (0.51,1.03) 66 (27) 1.01 (0.69,1.48)
pheterogeneity†=0.08 ptrend‡=0.01 ptrend‡=0.79 ptrend‡=0.21 ptrend‡=0.10 ptrend‡=0.99
Total folate
 Q1 502 (25) 77 (34) 1.00 195 (25) 1.00 71 (33) 1.0 91 (30) 1.00 56 (23) 1.00
 Q2 481 (24) 59 (26) 0.84 (0.58,1.22) 174 (22) 0.87 (0.68,1.12) 47 (22) 0.71 (0.48,1.06) 72 (23) 0.80 (0.57,1.12) 64 (26) 1.17 (0.79,1.72)
 Q3 487 (25) 44 (20) 0.67 (0.48,1.05) 190 (24) 0.94 (0.74,1.20) 50 (23) 0.79 (0.54,1.17) 74 (24) 0.82 (0.58,1.15) 62 (26) 1.10 (0.74,1.62)
 Q4 519 (26) 46 (20) 0.78 (0.52,1.16) 232 (29) 1.00 (0.79,1.26) 49 (23) 0.83 (0.56,1.23) 69 (23) 0.72 (0.51,1.02) 61 (25) 1.05 (0.70,1.55)
pheterogeneity†=0.37 ptrend‡=0.17 ptrend‡=0.75 ptrend‡=0.50 ptrend‡=0.11 ptrend‡=0.99
Alcohol
 Q1 602 (30) 75 (32) 1.00 288 (36) 1.00 63 (29) 1.00 113 (37) 1.00 81 (33) 1.00
 Q2 390 (20) 48 (21) 0.92 (0.62,1.36) 149 (19) 0.89 (0.70,1.13) 46 (22) 1.06 (0.71,1.60) 48 (16) 0.66 (0.46,0.96) 55 (23) 1.09 (0.75,1.58)
 Q3 503 (25) 54 (25) 0.76 (0.52,1.11) 163 (21) 0.81 (0.64,1.02) 41 (19) 0.69 (0.45,1.05) 72 (24) 0.77 (0.56,1.08) 58 (24) 0.87 (0.60,1.26)
 Q4 494 (25) 49 (22) 0.80 (0.54,1.19) 191 (24) 0.90 (0.72,1.13) 67 (31) 1.26 (0.86,1.83) 73 (24) 0.81 (0.58,1.12) 49 (21) 0.73 (0.49,1.07)
pheterogeneity†=0.15 ptrend‡=0.33 ptrend‡=0.58 ptrend‡=0.16 ptrend‡=0.55 ptrend‡=0.06
Methionine
 Q1 517 (26) 80 (35) 1.00 245 (31) 1.00 66 (30) 1.00 79 (27) 1.00 64 (26) 1.00
 Q2 421 (21) 50 (22) 0.78 (0.53,1.15) 163 (21) 0.85 (0.67,1.09) 46 (21) 0.88 (0.58,1.31) 77 (26) 0.93 (0.66,1.31) 58 (24) 1.16 (0.79,1.70)
 Q3 610 (31) 63 (28) 0.69 (0.48,0.99) 226 (29) 0.79 (0.64,0.99) 62 (29) 0.83 (0.57,1.21) 74 (25) 0.89 (0.65,1.23) 71 (29) 0.98 (0.68,1.41)
 Q4 442 (22) 33 (15) 0.50 (0.33,0.78) 157 (20) 0.79 (0.62,1.00) 43 (20) 0.80 (0.53,1.20) 62 (21) 0.67 (0.46,0.97) 50 (21) 0.95 (0.64,1.42)
pheterogeneity†=0.23 ptrend‡=0.001 ptrend‡=0.04 ptrend‡=0.25 ptrend‡=0.04 ptrend‡=0.69
Dietary B6
 Q1 518 (26) 82 (37) 1.00 230 (29) 1.00 67 (31) 1.00 96 (32) 1.00 66 (27) 1.00
 Q2 461(23) 64 (28) 0.97 (0.68,1.39) 177 (23) 0.82 (0.65, 1.05) 52 (24) 0.96 (0.65,1.42) 60 (20) 0.71 (0.50,1.01) 53 (22) 0.92 (0.63,1.36)
 Q3 538 (27) 49 (22) 0.65 (0.44,0.95) 204 (26) 0.79 (0.62, 0.99) 51 (24) 0.81 (0.55,1.20) 73 (24) 0.73 (0.53,1.03) 52 (21) 0.77 (0.52,1.13)
 Q4 473 (24) 31 (14) 0.49 (0.31 0.76) 180 (23) 0.74 (0.58, 0.94) 47 (22) 0.88 (0.59,1.31) 77 (25) 0.83 (0.60,1.16) 72 (30) 1.14 (0.79,1.65)
pheterogeneity†=0.03 ptrend‡=0.0005 ptrend‡=0.01 ptrend‡=0.43 ptrend‡=0.33 ptrend‡=0.53
Total B6
 Q1 507 (25) 96 (42) 1.00 224 (28) 1.00 73 (33) 1.00 97 (32) 1.00 61 (25) 1.00
 Q2 472 (24) 40 (18) 0.48 (0.32,0.72) 149 (19) 0.66 (0.52,0.85) 51 (24) 0.79 (0.53,1.16) 69 (22) 0.73 (0.52,1.03) 53 (22) 0.90 (0.61,1.34)
 Q3 533 (27) 53 (23) 0.67 (0.46,0.97) 213 (27) 0.79 (0.63,1.00) 50 (23) 0.78 (0.53,1.15) 75 (25) 0.73 (0.52,1.03) 74 (30) 1.16 (0.80,1.68)
 Q4 477 (24) 37 (16) 0.54 (0.36,0.82) 205 (26) 0.79 (0.63,1.01) 43 (20) 0.78 (0.52,1.18) 65 (21) 0.67 (0.47,0.96) 55 (23) 0.93 (0.63,1.39)
pheterogeneity†=0.45 ptrend‡=0.04 ptrend‡=0.49 ptrend‡=0.41 ptrend‡=0.09 ptrend‡=0.84
Dietary B12
 Q1 476 (24) 69 (31) 1.00 179 (23) 1.00 60 (28) 1.00 81 (26) 1.00 65 (27) 1.00
 Q2 539 (27) 63 (28) 0.86 (0.59,1.25) 208 (26) 1.08 (0.85,1.38) 57 (26) 0.87 (0.59,1.28) 69 (23) 0.78 (0.55,1.11) 57 (23) 0.80 (0.55,1.17)
 Q3 465 (23) 42 (19) 0.73 (0.48,1.11) 169 (21) 0.95 (0.74,1.22) 50 (23) 0.96 (0.64,1.43) 76 (25) 1.00 (0.70,1.41) 60 (25) 0.98 (0.67,1.43)
 Q4 509 (26) 52 (23) 0.87 (0.59,1.29) 235 (30) 1.10 (0.87,1.40) 50 (23) 0.91 (0.61,1.36) 80 (26) 0.90 (0.64,1.27) 61 (25) 0.85 (0.58,1.24)
pheterogeneity†=0.84 ptrend‡=0.54 ptrend‡=0.52 ptrend‡=0.78 ptrend‡=0.87 ptrend‡=0.58
Total B12
 Q1 466 (23) 68 (30) 1.00 176 (22) 1.00 61 (28) 1.00 74 (24) 1.00 51 (21) 1.00
 Q2 522 (26) 73 (32) 1.04 (0.72,1.50) 177 (22) 0.88 (0.69,1.14) 62 (29) 0.95 (0.65,1.39) 92 (30) 1.09 (0.78,1.53) 67 (28) 1.16 (0.79,1.72)
 Q3 506 (25) 48 (21) 0.82 (0.55,1.22) 185 (23) 0.87 (0.68,1.12) 54 (25) 0.96 (0.64,1.42) 71 (23) 0.87 (0.61,1.25) 67 (28) 1.18 (0.80,1.76)
 Q4 495 (25) 37 (16) 0.73 (0.47,1.13) 253 (32) 1.07 (0.84,1.36) 40 (18) 0.82 (0.53,1.26) 69 (23) 0.81 (0.56,1.17) 58 (24) 1.01 (0.67,1.53)
pheterogeneity†=0.08 ptrend‡=0.10 ptrend‡=0.22 ptrend‡=0.37 ptrend‡=0.13 ptrend‡=0.73
Open in a new tab
*

Adjusted for age, study center, total energy, oral contraceptive use, parity, tubal ligation, and family history of ovarian cancer.

†

Determined using polytomous logistic regression.

‡

Tests for trend were performed using the median of the interval for each quartile.

DISCUSSION

Overall, we observed a decreased risk of ovarian cancer with intake of methionine and dietary vitamin B6 but no overall association with folate or B12. However, we observed an association between dietary folate and ovarian cancer before the mandatory folate supplementation of grains in 1998. In addition, there was the suggestion of a nonlinear inverse association between alcohol intake and ovarian cancer.

Four previous case-control studies and four cohort studies have evaluated the association between folate and ovarian cancer. All four case-control studies reported no significant association between dietary folate and ovarian cancer risk13–16, though one reported a non-significant increase in risk16 and another reported a non-significant decreased risk limited to the fifth quintile14. Among three of the cohort studies, dietary folate was inversely associated with ovarian cancer risk in some subgroups17–19 while in one study dietary folate was associated with a non-significant increase in risk24. Total folate was associated with a non-significant increase in ovarian cancer risk in both studies that examined this association19, 24. We observed effect estimates that were inverse but not significant for both dietary and total folate in our main analyses. Different associations between folate intake and ovarian cancer observed across studies may be due to varying ranges of folate intake in different populations; the cutpoints for dietary folate categories varied across studies from ≥204 μg/day in the highest category for the Swedish Mammography Cohort17 to >425 μg/day in the Western New York Diet Study14. Our effect estimates for dietary folate assessed from 1992–1997, the time period that overlaps with previous studies, showed a decreased risk of ovarian cancer with increasing dietary folate intake, a result that is consistent with the most of the cohort studies as well as the other U.S. based case-control study.

Some have expressed concern that folic acid fortification may unintentionally increase cancer risk as folate has been shown to influence carcinogenesis differently depending on the dose and timing of exposure44, 45. Folate deficiency in normal cells may play a part in initiating carcinogenesis while folate supplementation may promote the growth of existing tumors46. In our study, we observed a decreased risk of ovarian cancer risk with dietary folate intake before supplementation and no association after supplementation. As our study asked participants to recall dietary folate one year before diagnosis, this finding may suggest that higher levels of dietary folate do not have a promoting effect on preclinical tumors and may help prevent ovarian cancer carcinogenesis in a low folate setting. To our knowledge no previous studies of folate and ovarian cancer have stratified by supplementation as most studies in the United States were before 1998 or in countries that do not supplement the food supply. However, in the Nurses’ Health Study II (NHS II) no association was observed between folate and breast cancer47 while in the Nurses’ Health Study (NHS) an inverse association was observed between folate intake and ER-negative breast cancer48. The authors suggest this may partially be due to the higher levels of post-fortification folate intake in the NHS II population as this population had folate levels in the first quintile that were in the range of the second quintile in NHS47.

To date, only one study19, has examined the direct association between methionine and ovarian cancer risk, while two studies13, 19 have examined the association with vitamin B6, and no associations were observed between these nutrients and ovarian cancer. In contrast, we observed significant inverse associations between methionine and dietary vitamin B6 and ovarian cancer risk. In addition, we observed that the associations with dietary vitamin B6 varied by histologic subtype with the strongest associations for serous borderline and serous invasive. Differences between our study and previous results may be due to differences in the distribution of ovarian cancer histologies in these studies as well as the range of dietary exposures in each population. In addition to playing a role the one-carbon metabolism pathway vitamin B6 may influence ovarian cancer risk through its antioxidant properties. Laboratory studies have demonstrated that vitamin B6 is effective at scavenging free radicals which if not properly controlled can promote carcinogenesis49.

The literature regarding alcohol and ovarian cancer is mixed with studies reporting null results20, 22, 25, 29–32 as well as increased17, 28, 33 and decreased21, 23, 24 risk of ovarian cancer with some associations varying by folate intake. A large pooling project involving ten cohort studies reported no association between alcohol35 and ovarian cancer. Our results suggested a decreased risk with alcohol intake that may be limited to women with lower intake of folate, though confouding by socioeconomic status cannot be ruled out..

We are the first to investigate whether MTHFR SNPs C677T and A1298C modify the association between one-carbon metabolism related nutrients and ovarian cancer. A previous analysis in a subset of this population found no association between either SNP and overall ovarian cancer risk but significant associations were observed for both SNPs and serous ovarian cancer. However, these findings were not replicated in the Nurses’ Health Study or the Mayo Clinic Ovarian Cancer Case-Control Study due to differences in the case populations43. We observed a stronger inverse association for methionine among women who were wildtype for A1298C perhaps indicating methionine is more effective in reducing ovarian cancer risk among individuals without reduced MTHFR activity. However, given our overall findings between MTFHR SNPs and ovarian cancer differed from other studies these results should be interpreted with caution.

Our study has limitations stemming from its case-control design. Our dietary assessment is limited to a short time period that may not be the most relevant time period in relation to ovarian cancer development. In order to avoid capturing changes to diet immediately before or after diagnosis, we have asked women to recall their diet one year before diagnosis or interview for controls. Despite these efforts, women with preclinical disease one year before diagnosis may have changed their dietary habits due to symptoms, making it difficult to distinguish whether their diet influenced disease onset or their disease influenced dietary changes. Secondly, as with any case-control study, recall bias is a possibility. However, we observed associations with dietary and as well as known risk factors for ovarian cancer that were similar to those reported by cohort studies, making dietary changes due to preclinical symptoms or recall bias less likely. In addition, one-carbon metabolism related nutrients have not been established as risk factors for ovarian cancer and thus it is unlikely that cases reported their intake of foods containing these nutrients differently than controls. Finally, women with the most aggressive cases may have died before they could be enrolled in the study; therefore, dietary factors associated with survival could influence our results.

In addition, limited variability in the diet across the study population may have restricted our ability to detect an effect of a particular nutrient on cancer risk. For instance, the median alcohol intake in our population is two g/d which corresponds to less that half a drink per day. Considering 10 g/d of alcohol is needed to increase breast cancer risk 10%50, an association of similar magnitude with ovarian cancer could be easily missed in our study. Similarly, FDA-mandated supplementation essentially eliminated folate deficiency in the United States and thereby diminished our ability to detect an association between folate and ovarian cancer risk. Since our study with the introduction of folate supplementation a spurious association could be observed between folate and ovarian cancer if cases and controls are not enrolled at the same time. Consequently, we adjusted for time of enrollment to minimize this potential bias. Additionally, our results may not be generalizable to populations folate supplementation is not mandatory. Finally, as we examined associations between nine exposure variables and three potential effect modifiers, as well as by histologic subtype, the potential for chance associations cannot be ruled out.

Strengths of our study include its large sample size. With over 1900 cases and 1900 controls, we are able to evaluate not only main effects but also histologic subtypes and potential effect modifiers. Additionally we have comprehensive dietary data and information on many important covariates.

In conclusion, we observed that vitamin B6 and methionine may decrease ovarian cancer risk and that the association between dietary folate and ovarian cancer differed before and after folic acid grain supplementation.

Supplementary Material

Supp Table S1-S2

Novelty and impact.

This study investigated whether one-carbon metabolism related nutrients were associated with ovarian cancer risk and whether theses associations were modified by the time period before and after folic acid grain supplementation, alcohol consumption, two polymorphisms of 5,10-methylene-tetrahydrofolate reductase (MTHFR), and histologic subtype. Few studies have had the power to examine these potential interactions and to our knowledge no previous studies of folate and ovarian cancer have stratified by supplementation as most studies in the United States were before 1998 or in countries that do not supplement the food supply. We observed that vitamin B6 and methionine may decrease ovarian cancer risk and that the association between dietary folate and ovarian cancer differed before and after folic acid grain supplementation. In addition, the association between total folate intake and ovarian cancer risk differed by alcohol consumption.

Acknowledgments

Supported by National Cancer Institute grants CA054419 and P50 CA105009 and the Department of Defense Ovarian Cancer Academy.

Abbreviations

OR

odds ratio

95% CI

95% confidence interval

MTHFR

5,10-methylene-tetrahydrofolate reductase

NEC

New England Case-Control Study

SNP

single-nucleotide polymorphism

mcg

microgram

g

gram

mg

milligram

kcal

kilocalorie

References

  • 1.Hillman RS, Steinberg SE. The Effects of Alcohol on Folate Metabolism. Ann Rev of Med. 1982;33:345–54. doi: 10.1146/annurev.me.33.020182.002021. [DOI] [PubMed] [Google Scholar]
  • 2.Sellers TA, Kushi LH, Cerhan JR, Vierkant RA, Gapstur SM, Vachon CM, Olson JE, Therneau TM, Folsom AR. Dietary folate intake, alcohol, and risk of breast cancer in a prospective study of postmenopausal women. Epidemiology. 2001;12:420–8. doi: 10.1097/00001648-200107000-00012. [DOI] [PubMed] [Google Scholar]
  • 3.Lajous M, Lazcano-Ponce E, Hernandez-Avila M, Willett W, Romieu I. Folate, Vitamin B6, and Vitamin B12 Intake and the Risk of Breast Cancer Among Mexican Women. Cancer Epidemiol Biomarkers Prev. 2006;15:443–48. doi: 10.1158/1055-9965.EPI-05-0532. [DOI] [PubMed] [Google Scholar]
  • 4.Giovannucci E, Rimm EB, Ascherio A, Stampfer MJ, Colditz GA, Willett WC. Alcohol, Low-Methionine-Low-Folate Diets, and Risk of Colon Cancer in Men. J Natl Cancer Inst. 1995;87:265–73. doi: 10.1093/jnci/87.4.265. [DOI] [PubMed] [Google Scholar]
  • 5.La Vecchia C, Negri E, Pelucchi C, Franceschi S. Dietary folate and colorectal cancer. Int J Cancer. 2002;102:545–7. doi: 10.1002/ijc.10720. [DOI] [PubMed] [Google Scholar]
  • 6.Giovannucci E. Epidemiologic Studies of Folate and Colorectal Neoplasia: a Review. J Nutr. 2002;132:2350S–55S. doi: 10.1093/jn/132.8.2350S. [DOI] [PubMed] [Google Scholar]
  • 7.McCann SE, Freudenheim JL, Marshall JR, Brasure JR, Swanson MK, Graham S. Diet in the epidemiology of endometrial cancer in western New York (United States) Cancer Causes Control. 2000;11:965–74. doi: 10.1023/a:1026551309873. [DOI] [PubMed] [Google Scholar]
  • 8.Negri E, La Vecchia C, Franceschi S, Levi F, Parazzini F. Intake of selected micronutrients and the risk of endometrial carcinoma. Cancer. 1996;77:917–23. doi: 10.1002/(sici)1097-0142(19960301)77:5<917::aid-cncr17>3.0.co;2-6. [DOI] [PubMed] [Google Scholar]
  • 9.Xu WH, Shrubsole MJ, Xiang YB, Cai Q, Zhao GM, Ruan ZX, Cheng JR, Zheng W, Shu XO. Dietary folate intake, MTHFR genetic polymorphisms, and the risk of endometrial cancer among Chinese women. Cancer Epidemiol Biomarkers Prev. 2007;16:281–7. doi: 10.1158/1055-9965.EPI-06-0798. [DOI] [PubMed] [Google Scholar]
  • 10.Toffoli G, Cernigoi C, Russo A, Gallo A, Bagnoli M, Boiocchi M. Overexpression of folate binding protein in ovarian cancers. Int J Cancer. 1997;74:193–98. doi: 10.1002/(sici)1097-0215(19970422)74:2<193::aid-ijc10>3.0.co;2-f. [DOI] [PubMed] [Google Scholar]
  • 11.Bottero F, Tomassetti A, Canevari S, Miotti S, Ménard S, Colnaghi MI. Gene Transfection and Expression of the Ovarian Carcinoma Marker Folate Binding Protein on NIH/3T3 Cells Increases Cell Growth in Vitro and in Vivo. Cancer Res. 1993;53:5791–96. [PubMed] [Google Scholar]
  • 12.Konner JA, Bell-McGuinn KM, Sabbatini P, Hensley ML, Tew WP, Pandit-Taskar N, Els NV, Phillips MD, Schweizer C, Weil SC, Larson SM, Old LJ. Farletuzumab, a Humanized Monoclonal Antibody against Folate Receptor α, in Epithelial Ovarian Cancer: a Phase I Study. Clin Cancer Res. 2010;16:5288–95. doi: 10.1158/1078-0432.CCR-10-0700. [DOI] [PubMed] [Google Scholar]
  • 13.Bidoli E, La Vecchia C, Talamini R, Negri E, Parpinel M, Conti E, Montella M, Carbone MA, Franceschi S. Micronutrients and ovarian cancer: a case-control study in Italy. Ann Oncol. 2001;12:1589–93. doi: 10.1023/a:1013124112542. [DOI] [PubMed] [Google Scholar]
  • 14.McCann SE, Freudenheim JL, Marshall JR, Graham S. Risk of human ovarian cancer is related to dietary intake of selected nutrients, phytochemicals and food groups. J Nutr. 2003;133:1937–42. doi: 10.1093/jn/133.6.1937. [DOI] [PubMed] [Google Scholar]
  • 15.Pelucchi C, Mereghetti M, Talamini R, Negri E, Montella M, Ramazzotti V, Franceschi S, La Vecchia C. Dietary folate, alcohol consumption, and risk of ovarian cancer in an Italian case-control study. Cancer Epidemiol Biomarkers Prev. 2005;14:2056–8. doi: 10.1158/1055-9965.EPI-05-0192. [DOI] [PubMed] [Google Scholar]
  • 16.Salazar-Martinez E, Lazcano-Ponce EC, Lira-Lira GG, Escudero-De los Rios P, Hernandez-Avila M. Nutritional Determinants of Epithelial Ovarian Cancer Risk: A Case-Control Study in Mexico. Oncology. 2002;63:151–57. doi: 10.1159/000063814. [DOI] [PubMed] [Google Scholar]
  • 17.Larsson SC, Giovannucci E, Wolk A. Dietary folate intake and incidence of ovarian cancer: the Swedish Mammography Cohort. J Natl Cancer Inst. 2004;96:396–402. doi: 10.1093/jnci/djh061. [DOI] [PubMed] [Google Scholar]
  • 18.Navarro Silvera SA, Jain M, Howe GR, Miller AB, Rohan TE. Dietary folate consumption and risk of ovarian cancer: a prospective cohort study. Eur J Cancer Prev. 2006;15:511–5. doi: 10.1097/01.cej.0000220627.54986.bf. [DOI] [PubMed] [Google Scholar]
  • 19.Tworoger SS, Hecht JL, Giovannucci E, Hankinson SE. Intake of folate and related nutrients in relation to risk of epithelial ovarian cancer. Am J Epidemiol. 2006;163:1101–11. doi: 10.1093/aje/kwj128. [DOI] [PubMed] [Google Scholar]
  • 20.Adami H-O, McLaughlin JK, Hsing AW, Wolk A, Ekbom A, Holmberg L, Persson I. Alcoholism and cancer risk: a population-based cohort study. Cancer Causes Control. 1992;3:419–25. doi: 10.1007/BF00051354. [DOI] [PubMed] [Google Scholar]
  • 21.Goodman MT, Tung KH. Alcohol consumption and the risk of borderline and invasive ovarian cancer. Obstet Gynecol. 2003;101:1221–8. doi: 10.1016/s0029-7844(03)00050-4. [DOI] [PubMed] [Google Scholar]
  • 22.Gwinn ML, Webster LA, Lee NC, Layde PM, Rubin GL, Cancer T, Group SHS. Alcohol Consumption and Ovarian Cancer Risk. Am J Epidemiol. 1986;123:759–66. doi: 10.1093/oxfordjournals.aje.a114304. [DOI] [PubMed] [Google Scholar]
  • 23.Kato I, Tominaga S, Terao C. Alcohol Consumption and Cancers of Hormone-related Organs in Females. Jpn J Clin Oncol. 1989;19:202–07. [PubMed] [Google Scholar]
  • 24.Kelemen LE, Sellers TA, Vierkant RA, Harnack L, Cerhan JR. Association of folate and alcohol with risk of ovarian cancer in a prospective study of postmenopausal women. Cancer Causes Control. 2004;15:1085–93. doi: 10.1007/s10552-004-1546-6. [DOI] [PubMed] [Google Scholar]
  • 25.Kuper H, Titus-Ernstoff L, Harlow BL, Cramer DW. Population based study of coffee, alcohol and tobacco use and risk of ovarian cancer. Int J Cancer. 2000;88:313–18. doi: 10.1002/1097-0215(20001015)88:2<313::aid-ijc26>3.0.co;2-5. [DOI] [PubMed] [Google Scholar]
  • 26.Lagiou P, Ye W, Wedrén S, Ekbom A, Nyrén O, Trichopoulos D, Adami H-O. Incidence of ovarian cancer among alcoholic women: A cohort study in Sweden. Int J Cancer. 2001;91:264–66. doi: 10.1002/1097-0215(200002)9999:9999<::aid-ijc1027>3.3.co;2-b. [DOI] [PubMed] [Google Scholar]
  • 27.Larsson SC, Wolk A. Wine Consumption and Epithelial Ovarian Cancer. Cancer Epidemiol Biomarkers Prev. 2004;13:1823–24. [PubMed] [Google Scholar]
  • 28.Modugno F, Ness RB, Allen GO. Alcohol consumption and the risk of mucinous and nonmucinous epithelial ovarian cancer. Obstet Gynecol. 2003;102:1336–43. doi: 10.1016/j.obstetgynecol.2003.08.008. [DOI] [PubMed] [Google Scholar]
  • 29.Riman T, Dickman P, Nilsson S, Nordlinder H, Magnusson CM, Persson IR. Some life-style factors and the risk of invasive epithelial ovarian cancer in Swedish women. Eur J Epidemiol. 2004;19:1011–19. doi: 10.1007/s10654-004-1633-8. [DOI] [PubMed] [Google Scholar]
  • 30.Schouten LJ, Zeegers MPA, Goldbohm RA, van den Brandt PA. Alcohol and ovarian cancer risk: results from the Netherlands Cohort Study. Cancer Causes Control. 2004;15:201–09. doi: 10.1023/B:CACO.0000019512.71560.2b. [DOI] [PubMed] [Google Scholar]
  • 31.Sigvardsson S, Hardell L, Przybeck TR, Cloninger R. Increased Cancer Risk among Swedish Female Alcoholics. Epidemiology. 1996;7:140–43. doi: 10.1097/00001648-199603000-00006. [DOI] [PubMed] [Google Scholar]
  • 32.Tavani A, Gallus S, Dal Maso L, Franceschi S, Montella M, Conti E, La Vecchia C. Coffee and alcohol intake and risk of ovarian cancer: an Italian case-control study. Nutr Cancer. 2001;39:29–34. doi: 10.1207/S15327914nc391_4. [DOI] [PubMed] [Google Scholar]
  • 33.Tzonou A, Day NE, Trichopoulos D, Walker A, Saliaraki M, Papapostolou M, Polychronopoulou A. The epidemiology of ovarian cancer in Greece: a case-control study. Eur J Cancer Clin Oncol. 1984;20:1045–52. doi: 10.1016/0277-5379(84)90107-x. [DOI] [PubMed] [Google Scholar]
  • 34.Webb PM, Purdie DM, Bain CJ, Green AC. Alcohol, Wine, and Risk of Epithelial Ovarian Cancer. Cancer Epidemiol Biomarkers Prev. 2004;13:592–99. [PubMed] [Google Scholar]
  • 35.Genkinger JM, Hunter DJ, Spiegelman D, Anderson KE, Buring JE, Freudenheim JL, Goldbohm RA, Harnack L, Hankinson SE, Larsson SC, Leitzmann M, McCullough ML, et al. Alcohol intake and ovarian cancer risk: a pooled analysis of 10 cohort studies. Br J Cancer. 2006;94:757–62. doi: 10.1038/sj.bjc.6603020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Terry KL, De Vivo I, Titus-Ernstoff L, Sluss PM, Cramer DW. Genetic variation in the progesterone receptor gene and ovarian cancer risk. Am J Epidemiol. 2005;161:442–51. doi: 10.1093/aje/kwi064. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.National Nutrient Database for Standard Reference. 2001. [Google Scholar]
  • 38.Rimm EB, Giovannucci EL, Stampfer MJ, Colditz GA, Litin LB, Willett WC. Reproducibility and Validity of an Expanded Self-Administered Semiquantitative Food Frequency Questionnaire among Male Health Professionals. Am J Epidemiol. 1992;135:1114–26. doi: 10.1093/oxfordjournals.aje.a116211. [DOI] [PubMed] [Google Scholar]
  • 39.Salvini S, Hunter DJ, Sampson L, Stampfer MJ, Colditz GA, Rosner B, Willett WC. Food-Based Validation of a Dietary Questionnaire: The Effects of Week-to-Week Variation in Food Consumption. Int J Epidemiol. 1989;18:858–67. doi: 10.1093/ije/18.4.858. [DOI] [PubMed] [Google Scholar]
  • 40.Willett WC, Sampson L, Stampfer MJ, Rosner B, Bain C, Witsch J, Hennekens CH, Speizer FE. Reproducibility and Validity of a Semiquantitative Food Frequency Questionnaire. Am J Epidemiol. 1985;122:51–65. doi: 10.1093/oxfordjournals.aje.a114086. [DOI] [PubMed] [Google Scholar]
  • 41.Giovannucci E, Stampfer MJ, Colditz GA, Rimm EB, Trichopoulos D, Rosner BA, Speizer FE, Willett WC. Folate, methionine, and alcohol intake and risk of colorectal adenoma. J Natl Cancer Inst. 1993;85:875–84. doi: 10.1093/jnci/85.11.875. [DOI] [PubMed] [Google Scholar]
  • 42.Willett W. Nutritional Epidemiology. 2. Oxford: Oxford University Press; 1998. [Google Scholar]
  • 43.Terry KL, Tworoger SS, Goode EL, Gates MA, Titus-Ernstoff L, Kelemen LE, Sellers TA, Hankinson SE, Cramer DW. MTHFR polymorphisms in relation to ovarian cancer risk. Gynecol Oncol. 2010;119:319–24. doi: 10.1016/j.ygyno.2010.08.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Kim Y-I. Will mandatory folic acid fortification prevent or promote cancer? Am J Clin Nutr. 2004;80:1123–28. doi: 10.1093/ajcn/80.5.1123. [DOI] [PubMed] [Google Scholar]
  • 45.Mason JB, Dickstein A, Jacques PF, Haggarty P, Selhub J, Dallal G, Rosenberg IH. A Temporal Association between Folic Acid Fortification and an Increase in Colorectal Cancer Rates May Be Illuminating Important Biological Principles: A Hypothesis. Cancer Epidemiol Biomarkers Prev. 2007;16:1325–29. doi: 10.1158/1055-9965.EPI-07-0329. [DOI] [PubMed] [Google Scholar]
  • 46.Kim Y-I. Folate and carcinogenesis: evidence, mechanisms, and implications. J Nutr Biochem. 1999;10:66–88. doi: 10.1016/s0955-2863(98)00074-6. [DOI] [PubMed] [Google Scholar]
  • 47.Cho E, Holmes M, Hankinson SE, Willett WC. Nutrients Involved in One-Carbon Metabolism and Risk of Breast Cancer among Premenopausal Women. Cancer Epidemiol Biomarkers Prev. 2007;16:2787–90. doi: 10.1158/1055-9965.EPI-07-0683. [DOI] [PubMed] [Google Scholar]
  • 48.Zhang SM, Hankinson SE, Hunter DJ, Giovannucci EL, Colditz GA, Willett WC. Folate Intake and Risk of Breast Cancer Characterized by Hormone Receptor Status. Cancer Epidemiol Biomarkers Prev. 2005;14:2004–08. doi: 10.1158/1055-9965.EPI-05-0083. [DOI] [PubMed] [Google Scholar]
  • 49.Matxain JM, Padro D, Ristilä M, Strid Å, Eriksson LA. Evidence of High •OH Radical Quenching Efficiency by Vitamin B6. J Phys Chem B. 2009;113:9629–32. doi: 10.1021/jp903023c. [DOI] [PubMed] [Google Scholar]
  • 50.Key J, Hodgson S, Omar R, Jensen T, Thompson S, Boobis A, Davies D, Elliott P. Meta-analysis of Studies of Alcohol and Breast Cancer with Consideration of the Methodological Issues. Cancer Causes Control. 2006;17:759–70. doi: 10.1007/s10552-006-0011-0. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supp Table S1-S2
NIHMS327724-supplement-Supp_Table_S1-S2.doc (216.5KB, doc)

RESOURCES