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Division of Preventive and Behavioral Medicine (J. H. F., J. R. H.), and Department of Obstetrics and Gynecology (C. L.), University of Massachusetts Medical Center, Worcester, Massachusetts 01655
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Abstract |
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 Top Abstract IntroductionMaterials and MethodsResultsDiscussionReferences |
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-hydroxyestrone acts as a breast tumor promoter. The alternative
product of estrogen metabolism, 2-hydroxyestrone, does not exhibit
estrogenic properties in breast tissue, and lower values of the ratio
2-hydroxyestrone:16-hydroxyestrone (2:16) in urine may be an
endocrine biomarker for greater breast cancer risk. Vegetables of the
Brassica genus, such as broccoli, contain a
phytochemical, which may shift estrogen metabolism and increase the
2:16 ratio. Adding 500 g/day of broccoli to a standard diet shifts 2:16
values upward in humans; however, it is unknown as to whether healthy
women are able to consume a sufficient quantity of
Brassica to affect breast cancer risk through this
mechanism. In this study, 34 healthy postmenopausal women participated
in an intensive intervention designed to facilitate the addition of
Brassica to the daily diet. The diet was measured by
repeated 24-h recall, and estrogen metabolites were measured by enzyme
immunoassay in 24-h urine samples. In a crude analysis, there was a
nonsignificant increase in the urinary 2:16 ratio associated with
greater Brassica consumption. With adjustment for other
dietary parameters, Brassica vegetable consumption was
associated with a statistically significant increase in 2:16
values, such that for each 10-g/day increase in
Brassica consumption, there was an increase in the 2:16
ratio of 0.08 (95% confidence interval, 0.02–0.15). To the extent
that the 2:16 ratio, as measured in urine, is associated with breast
cancer risk, future research should consider Brassica
vegetable consumption as a potentially effective and acceptable dietary
strategy to prevent breast cancer. |
Introduction |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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IGSLs are a category of phytochemicals that are capable of shifting estrogen metabolism and increasing the urinary 2:16 ratio. IGSLs are unique to vegetables of the Brassica genus, the most common of which in the United States are Brussels sprouts, broccoli, cabbage, kale, turnips, collards, and cauliflower. With cutting or chewing of the vegetable, IGSLs are degraded by the plant enzyme myrosinase to a variety of indole structures, including I3C, DIM, indole-3-acetonitrile, indole-3-acetic acid, and AG (14, 15) . In the body, these indole-containing compounds are either chemically or enzymatically converted to indolo[3,2-b]carbazole, a moderate aryl hydrocarbon receptor agonist (16–18) . The activated aryl hydrocarbon receptor binds to specific sites on DNA and induces the expression of P-450 enzymes of the CYP1 family in hepatic and extrahepatic tissue (19–22) . These P-450 enzymes hydroxylate E1 on the second carbon, leading to greater 2HE production and decreasing the pool of E1 available for conversion to 16HE, thus increasing the 2:16 ratio (21, 23–27) . In three small human intervention studies, the daily administration of I3C pills (400 mg/day) or broccoli (500 g/day) significantly increased the urinary 2:16 value (21, 28, 29) , consistent with reduced breast cancer risk.
There is incomplete evidence to demonstrate that Brassica vegetable consumption protects against breast cancer. In animal models of breast cancer, dietary I3C (25, 30–32) or a diet with cabbage (33) reduces tumor incidence or delays tumor onset. Results from one cross-national study found that those countries with higher cabbage intake had a lower breast cancer mortality rate (34) . Despite the availability only of data on cabbage of the entire Brassica genus, intercountry differences in cabbage consumption are sufficiently large to increase the likelihood of detecting a specific protective association. Observational studies conducted within a population have not identified a consistent association between Brassica intake and breast cancer risk. (35–39) . One of these studies did find a significant reduction in breast cancer risk with Brassica intake; however, there was no dose-response trend in this association [relative risk, 0.79 (0.67–0.92); Ref. 35 ]. These studies are limited by the very low levels of Brassica intake in the populations under evaluation, the limitations of individual dietary assessment techniques (e.g., food frequency questionnaires), and the absence of data regarding how the vegetables are prepared before consumption.
Dietary interventions can create variability in the food consumption pattern of a targeted study group, such that it may be possible to detect a physiological response consistent with reduced cancer risk. In this study, the intervention protocol facilitated daily Brassica consumption among free-living postmenopausal women. The objective was to reach a level of Brassica intake consistent with the range and variability of amounts consumed in Japan or other Asian countries (40–42) . An association between Brassica intake and higher urinary 2:16 values would suggest that healthy free-living postmenopausal women are able to shift their own estrogen profiles in such a way as to reduce breast cancer risk. Such a result would suggest that Brassica vegetables should be further evaluated as a strategy to reduce breast cancer risk.
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Materials and Methods |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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The study was restricted to women >45 years of age, without a menstrual cycle in the past 12 months, without present liver or kidney disease, and without adrenalectomy. Women with a hysterectomy but without ovariectomy were at least 54 years of age. Women were excluded if they presently used any tobacco products, antibiotics, hormone replacement therapy, nonprescription hormones (e.g., melatonin, dehydroepiandrosterone), black-cohosh, tamoxifen, diabetes medication, or cimetidine. Women under a physician-recommended diet or who reported a strong dislike for Brassica vegetables were excluded. Participants received no monetary compensation. Thirty-seven women met all eligibility criteria and started the study; however, three participants dropped-out because of family illness or scheduling conflicts. This analysis is restricted to the 34 participants who completed the intervention.
Dietary Intervention.
The study population was divided into three groups of women, with
between 9 and 13 women/group. The dietary intervention was administered
to each of these groups, and it consisted of four classes over a 4-week
period (Fig. 1
). The goal of the intervention was to facilitate the incorporation of
Brassica into the daily diet. Participants were asked to
consume Brassica every day, at a frequency and vegetable
combination that would approach a 70-mg/day intake of IGSLs. Estimated
indole content for each vegetable was extracted from a review by Rosa
et al. (43)
.
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Participant Characteristics.
Demographics, reproductive history, health history, tobacco use,
alcohol use, and medication use were collected by questionnaire during
the baseline study period. Additional questionnaires were administered
at follow-up to identify any changes in tobacco or medication use. The
psychological constructs "Social Approval" and "Social
Desirability" were measured by questionnaire during the baseline
period (44–46)
.
Urine and Blood Collection.
The study design and sample collection schedule are illustrated in Fig. 1
. Study participants provided two 24-h urine samples and two blood
samples before the intervention, 
2 weeks apart. Additional urine and
blood samples were collected during the last week of the intervention.
Both written and oral instructions regarding the urine collection
protocol were administered to all participants.
Dietary Assessment.
The diet was measured by 24HR during each week that urine and blood
samples were collected. Subjects were telephoned on three randomly
assigned days (2 weekdays and 1 weekend day) and asked to describe the
foods and portion sizes consumed during the prior day. A structured
interview protocol was strictly followed, all interviews were conducted
by highly trained registered dietitians, and participants were provided
a two-dimensional chart of typical foods to assist with portion size
estimation. Nutrient calculations were performed using the Nutrition
Data System software, developed by the Nutrition Coordinating Center,
University of Minnesota (Minneapolis, MN; Food Database: 13A; Nutrient
Database: 28; Ref. 47
). Nutrients derived from supplements
were added to the dietary estimates. Data from the three 24HR
administered within a given week were averaged, providing the single
best estimate of each participant’s dietary intake for that week.
Brassica vegetables were identified in the 24HR data. Data regarding the types of Brassica vegetable, the amount of vegetable, and whether the vegetable was consumed cooked or raw, were extracted. The grams of Brassica that were reported as cooked were adjusted to reflect grams of raw (fresh) Brassica. IGSL intake (mg/day) was calculated using published IGSL concentrations in fresh/raw vegetables across the varieties of Brassica (43) and the amount of Brassica reported in the 24HR.
Body Measurements.
Weight, height, and the circumferences of the waist, abdomen, and hips
were measured during each week in which a urine sample was collected.
Body mass index was calculated as weight (kg)/height
(m)2, and the waist:hip ratio was calculated by
dividing the waist circumference by the hip circumference. Total body
fat was calculated using the Tran and Weltman prediction equation,
which combines measures of body circumference, weight, age, and height
to produce an estimate of the fat (kg) in the body (48, 49)
. This prediction equation has been validated in women >50
years of age.
Laboratory Analyses.
Urinary 2HE and 16HE were measured at the University of Massachusetts
Medical School (C. Longcope) using a solid-phase enzyme immunoassay kit
from Immuna Care Corporation (50)
. All assays were
performed on samples in random order, in triplicate, within one batch,
and by a single technician who was blinded as to the sequence of the
sample collection. Serum E2 levels were measured by radioimmunoassay
(Diagnostic Products Corp., Los Angeles, CA). There were six serum
samples from four individuals that had unexpectedly high (>40 pg/ml)
E2 levels. For these samples, the E2 assay was repeated, with identical
results. The intra-assay coefficients of variation for E2, 2HE, and
16HE were 3.4%, 4.0%, and 4.0% respectively, whereas interassay
coefficients of variation were 6.8%, 10.0%, and 9.9%, respectively.
Standard urine samples were from women of a similar age and estrogen
level as the study participants.
Statistical Analysis.
Individual changes in Brassica consumption or urinary 2:16
values between baseline and the intervention study phase were
calculated by subtraction. Across the two baseline measurements,
urinary 2:16 values and Brassica intake were not
significantly different. Therefore, these values were pooled to provide
a more stable baseline estimate. Changes in 2:16 were compared with
changes in Brassica intake using least-squares linear
regression (SAS/STAT Statistical Software, version 6.12, SAS Institute,
Cary, NC). The regression coefficient (b) represents
the change in 2:16 for each 10-g/day change in Brassica
intake. Additionally, the pattern of the 2:16 ratio was evaluated
across categories of the change in Brassica vegetable
intake. The significance of the a linear trend was determined by
inclusion into the regression model of a continuous variable with
values representing each category of change in Brassica
intake.
Several dietary macronutrients (i.e., total fat, protein, carbohydrates, energy, and fiber) and body habitus measures were defined a priori as potentially affecting urinary 2:16 values. Although the mechanisms by which these nutrients may affect urinary estrogen metabolite levels are uncertain, these factors previously have been associated with estrogen metabolism, drug metabolism, or the excretion of estrogens and are treated as potential confounders (51–53) . Adjusted regression coefficients were calculated to remove the influence of changes in these factors over time. Baseline 2:16 values were forced into the regression model to control for the possibility that large change scores result from unusual baseline values (regression to the mean).
The association between Brassica intake and 2:16 values were evaluated in a cross-sectional nature during the intervention study phase to explore the possibility of identifying an association between 2:16 and the diet across individuals.
The impact of the dietary intervention on total estrogen production was evaluated by comparing E2 values over the study by repeated measures ANOVA. An unstructured covariance matrix was used because this approach provided the best fit of the data (54) . The distribution of serum E2 was highly skewed, and E2 levels were transformed logarithmically (base e) to meet the statistical assumptions.
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Results |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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9 g/day (Table 2
). During the intervention study phase, Brassica consumption
increased to 193 g/day. The frequency of Brassica vegetable
consumption increased from about two servings per week at baseline to
about two servings per day during the intervention phase, and estimated
IGSL intake (mg/day) followed the same trend as self-reported Brassica
vegetable intake.
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. Serum E2 levels were 20 pg/ml
at baseline and 16 pg/ml during the intervention study phase. Crude
urinary 2:16 levels and E2 levels did not significantly change across
the two baseline measures and the intervention measurement (repeated
measured ANOVA of 2:16 or E2 across time: P = 0.31 and
P = 0.35, respectively). E2 levels, or changes in E2
levels over time, were not significantly associated with urinary 2:16
values. Disease history, family history of breast cancer, or other
breast cancer risk factors were not consistently associated with
urinary 2:16 values or adherence to the intervention guidelines (not
shown). The crude association between changes in Brassica intake and changes in 2:16 values indicated that urinary 2:16 values increased 0.03 for every 10 g of Brassica consumed (regression coefficient = 0.03; 95% CI, -0.02 to 0.06).
Several dietary variables were considered as potential sources of bias, including changes in dietary protein (g), fat (g), carbohydrates (g), energy (kcal), and fiber (g), as well as previously defined body habitus measures and psychosocial scales that have been linked with dietary misreport. Dietary fat intake, carbohydrate intake, and measures of body habitus did not alter the Brassica-2:16 association and were not significant predictors of 2:16, and these parameters were excluded from the final model to improve the precision of the analysis. With adjustment for dietary fiber, protein, energy, and scores of social approval, the increase in Brassica consumption from baseline to intervention was significantly associated with an increase in the 2:16 ratio, such that each 10-g/day increase in Brassica consumption increased the 2:16 ratio by 0.08 (regression coefficient = 0.08; 95% CI, 0.02–0.15). Similarly, estimated indole intake shifted the urinary 2:16 ratio upward (regression coefficient = 0.21; 95% CI, 0.03–0.39 for 10 mg/day of IGSL).
Participant compliance from baseline to the intervention study phase
was categorized into four groups to explore any dose-response
relationship. Changes in Brassica intake were categorized
across quartiles of the distribution, and crude and adjusted changes in
urinary 2:16 values were calculated. Those participants who consumed
less Brassica did not show any increase in urinary 2:16
values (Table 3
). Those participants who consumed more Brassica had a
greater increase in urinary 2:16 values, with a significant linear
dose-response trend in the adjusted analysis.
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) consistent with a shift in estrogen metabolism toward 2HE in response
to IGSL consumption.
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Discussion |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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Kall et al. (21) found the urinary 2:16 ratio increased 0.40 with administration of 500 g of broccoli/day to a small group of young men and women, and Bradlow et al. (29) observed a 0.40 shift in 2:16 with the daily administration of pills containing I3C. Unlike pills, Brassica vegetables expose the body to a complex mixture of indole structures, including I3C, AG, and DIM; and AG or DIM may be more potent than I3C alone (18, 59, 60) . In this study, different vegetable types appeared to be effective in shifting the urinary 2:16 ratio, with cabbage intake having the strongest effect. Finally, the larger response observed in this study might be specific to postmenopausal women, or advances in the laboratory procedures used to detect estrogen metabolites in urine.
Glucosinolates and glucosinolate break-down products are hydrophilic, and as much as 63% of the glucosinolate content of a vegetable may leach into the cooking water during boiling (20, 26) . However, vegetable preparation did not diminish the ability of the vegetables to shift estrogen metabolism in this study. Participants were instructed to cook the Brassica only lightly, by either light steaming or as stir-fry, and they were provided guided practice in vegetable preparation techniques. Steaming provides less opportunity for leaching, and stir-fried vegetables retain glucosinolate levels (61) . Light cooking may disrupt plant cell membranes without leaching of the indoles into the cooking medium, providing the opportunity for myrosinase to release these indoles for eventual conversion to indolo[3,2-b]carbazole (15, 18, 20, 26, 62, 63) .
Another potential source of error in a study such as this is improper collection of biological samples. There was no indication that the 24-h urine samples were collected improperly. All participants understood the urine collection procedure, and participants recorded the time and dates of urine collection. The relationship between Brassica consumption and the 2:16 ratio was not significantly modified by the time period between urine collection and storage (i.e., urine age), and there was no evidence of differences in sample handling over time. However, there was no way to be sure of whether samples were contaminated or whether urine samples represented a complete 24-h collection.
The single-armed design could not control for any unmeasured factors. Duplicate baseline measures were collected to produce a stable estimate of the usual dietary intake and hormone levels. There were no significant differences in nutrient or hormone values between these baseline time points, suggesting that these factors, at the very least, were consistent across the short term within study population. Prescription medication use was monitored throughout the study, and participants followed a stable drug regime. Soy food and bean food consumption was very low in this Central Massachusetts study population consisting primarily of European-Americans, with consumption consistently estimated at about 0.25 g/day, on average (only eight participants ate any bean or soy products). Not surprisingly, this very low soy-food intake was not associated with urinary 2:16 values. The short duration of the intervention (4 weeks) minimized the opportunity for the influences of seasonal variation in the diet or a social trend that might affect 2:16 values.
The laboratory data suggest the hypothesis that 2:16 is important in breast cancer etiologically, but epidemiological studies evaluating the role of 2:16 and breast cancer risk are inconsistent. Four case-control studies found significantly lower 2:16 levels or higher 16HE levels among breast cancer cases (13, 64–66) , whereas a recent analysis of a prospective study reported a nonsignificant 30% reduction in breast cancer risk with higher urinary 2:16 values (67) . Recently, Ursin et al. (68) reported an inconsistent finding, where only women who were in the middle tertile of the 2:16 distribution were less likely to be diagnosed with breast cancer [ORT2 versus T1 = 0.34 (0.12–0.98); ORT3 versus T1 = 1.13 (0.46–2.78)]. At present, it is not possible to conclude that 2:16 is a valid endocrine biomarker for breast cancer risk. Further studies should be conducted to evaluate this relationship.
To the extent that the urinary 2:16 ratio is etiologically relevant to breast cancer, frequent Brassica intake may be able to reduce breast cancer risk. Studies evaluating urinary 2:16 values and breast cancer risk identify differences in 2:16 values between the case and control series ranging from 0.1 to 0.7. A shift of 0.08 in the 2:16 ratio for every 10 g/day of Brassica suggests that the population would need to increase Brassica consumption between 12.5 g/day to 75 g/day to move 2:16 ratios to a favorable level to affect the causal mechanism leading to breast cancer. Of course, caution must be used when comparing results across laboratories, and the above interpretation should be considered only as a rough guideline. Brassica vegetable consumption in the United States is estimated between 5 and 11 g/day (fresh; Refs. 41 and 69 ). This suggests that even a small increase in Brassica vegetable consumption across the population could have an impact on the incidence of breast cancer.
Presently, there are three approaches to risk reduction: prophylactic surgery, pharmaceuticals, and behavioral change. None of these options are universally acceptable or appropriate. It would be ideal to have a variety of strategies that could be tailored to an individual’s characteristics and risk profile. Brassica vegetable consumption appears to shift estrogen metabolism in a way consistent with reduced breast cancer risk. Future work should clarify the relationship between the 2:16 endocrine biomarker and breast cancer and the relationship between Brassica intake and breast cancer risk, and it should identify those women most susceptible to the beneficial action of increased Brassica consumption.
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Footnotes |
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2 To whom requests for reprints should be
addressed, at Division of Population Studies, South Carolina Cancer
Center, Suite 301, 15 Richmond Memorial Park, Columbia, SC 29203.
3 The abbreviations used are: 16HE,
16-hydroxyestrone; E1, estrone; E2, serum 17ß-estradiol; 2HE,
2-hydroxyestrone; IGSL, indole glucosinolate; I3C, indole-3-carbinol;
DIM, 3,3'-diindolylmethane; AG, ascorbigen; 24HR, 24-h recall;
CI, confidence interval.
Received 12/ 1/99; revised 5/ 3/00; accepted 5/17/00.
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References |
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TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
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