Abstract
Estrogen metabolism profiles may play an important role in the relationship between body size and breast carcinogenesis. Previously, we observed inverse associations between current body mass index (BMI) and plasma levels of parent estrogens (estrone and estradiol) among premenopausal women during both follicular and luteal phases. Using data from the Nurses’ Health Study II, we assessed whether height, current BMI, and BMI at age 18 were associated with the urinary concentrations of 15 estrogens and estrogen metabolites (jointly referred to as EM) measured during the luteal phase among 603 premenopausal women. We observed inverse associations with total EM for height (P trend = 0.01) and current BMI (P trend = 0.01), but not BMI at age 18 (P trend = 0.26). Six EMs were 18–27 % lower in women with a height 68+ versus ≤62 in., primarily in the methylated catechol pathway (P trend = 0.04). Eight EMs were 18–50 % lower in women with a BMI of 30+ versus <20, primarily in the 2-catechol and methylated catechol pathways (P trend < 0.001 for both). Our results suggest that height and current BMI are associated with estrogen metabolism profiles in premenopausal women. Further studies with timed urine and blood collections are required to confirm and extend our findings.
Keywords: Body Mass Index, Breast Cancer Risk, Menstrual Cycle, Premenopausal Woman, Estrone
Introduction
Experimental studies have suggested that endogenous estrogens and estrogen metabolites may play an important role in breast carcinogenesis [43]. Mechanisms may include estrogen receptor-mediated signaling that increases breast cell proliferation as well as the genotoxic effects of some estrogen metabolites [15, 21, 26, 42]. Evidence from cell culture and animal experiments suggests that catechol estrogen metabolites derived from reactive quinones are genotoxic [6, 42]. While circulating estradiol and estrone consistently have been associated with increased risk of postmenopausal breast cancer in epidemiologic studies [12, 22, 28, 44], the relationship in premenopausal women is less clear [9, 19, 23–25, 27, 31, 36]. In the Nurses’ Health Study II (NHSII) among premenopausal women, we observed that higher plasma follicular free estradiol levels were associated with an increased risk of breast cancer (highest versus lowest quartile relative risk (RR) = 2.4, P trend = 0.01); however, luteal plasma estrogens were not associated clearly with risk [9]. Conversely, urinary excretion of conjugated estrone and estradiol during the mid-luteal phase was associated with a lower risk of breast cancer in the same population [10]. It is important to identify correlations of urinary estrogen metabolism, and we reported that certain reproductive factors, including menstrual irregularity, were associated with estrogen metabolism patterns [16].
Body size characteristics are important in determining breast cancer risk. Among premenopausal women, BMI has been inversely associated with breast cancer risk; compared with a BMI of less than 21 kg/m2, women with a BMI > 31 kg/m2 had a relative risk of 0.54 in a pooled analysis of seven prospective cohort studies [40]. Height has been positively associated with breast cancer risk; the RR per 10 cm increase in height was 1.17, 95 % confidence interval of 1.15–1.19 in a recent meta-analysis of prospective studies [17]. Further, in the NHSII, we previously observed that current BMI was inversely and significantly associated with plasma levels of estrone, estradiol, and estrone sulfate in premenopausal women [39].
Estrogen metabolism profiles may play an important role in the relationship between body size and breast carcinogenesis. Thus, we evaluated the associations between adult body size measures and 15 estrogens and estrogen metabolites (jointly referred to as EM) in luteal urine among 603 women from NHSII.
Methods
Study Population
The NHSII is a prospective cohort study established in 1989, when 116,430 female registered nurses, ages 25 to 42, completed a questionnaire. Biennially, the cohort has been followed to update exposure variables and ascertain newly diagnosed diseases. The population is 94 % Caucasian. Between 1996 and 1999, 29,611 cohort members, aged 32 to 54 years, provided urine samples. Of the women who were still having menstrual cycles (i.e., premenopausal), had not used oral contraceptives in the last 6 months, and were not pregnant or breastfeeding within the past 6 months, 18,521 provided their urine samples timed to the mid-luteal phase of the menstrual cycle (7 to 9 days before the anticipated start of their next menstrual cycle).
Urine samples were shipped to our laboratory, via overnight mail with a frozen water bottle, where the urine was aliquoted into labeled cryotubes and stored in liquid nitrogen freezers (≤130 °C) without any preservative. Approximately 93 % of luteal samples were received within 26 h of collection. Further details of sample collection, processing, and storage methods have been described elsewhere [33]. There were 603 participants with urinary EM measurements in this study: 493 were controls from a nested case–control study of breast cancer [10, 38], and 110 were from a biomarker reproducibility study [11]. The study was approved by the Committee on the Use of Human Subjects in Research at the Brigham and Women’s Hospital.
Covariate Data
At the time of urine collection, participants completed a questionnaire recording their current weight, details about the urine collection date and time, smoking status, physical activity, and whether the urine was a first morning sample. In addition, 97 % of the participants returned a postcard noting the first day of their next menstrual cycle, which allowed for a more accurate determination of the luteal day of the collection (date of next menstrual cycle minus date of urine collection) compared to forward counting [1]. Reproductive history, oral contraceptive use, history of benign breast disease, family history of breast cancer, age at menarche, menstrual cycle regularity, usual menstrual cycle length, weight at age 18, and attained height were reported on the 1989 questionnaire; oral contraceptive use and reproductive factors were updated on subsequent biennial NHSII questionnaires. Current BMI at blood collection and BMI at age 18 were calculated as weight in kilograms divided by attained height in meters squared.
We have conducted validation studies of self-reported current weight, weight at age 18, and waist and hip circumferences in our population [30, 37]. Mean self-reported weights were 1.5 kg less than the technician measurements and were, therefore, consistent with the difference between a random casual weight in clothing and a nude weight. The correlation between measured and self-reported weight was 0.96 and did not differ by BMI levels [37]. The correlation between recalled weight at age 18 and that documented in college or nursing school physical exam records was 0.84 [30].
Laboratory Assays
Details of the assay have been published previously [13, 41]. In brief, to measure urinary EM, 500 μL of frozen urine was sent to the Laboratory of Proteomics and Analytical Chemistry, SAIC-Frederick, Inc., Frederick, MD, USA. Each urine sample was thawed and mixed, and 400 μL was immediately aliquoted into a clean screw-cap glass tube and 20 μL of an internal standard solution containing 1.6 ng of each of five deuterated EM (17β-estradiol-d4, estriol-d3, 2-hydroxy-17β-estradiol-d5, 2-methoxy-17β-estradiol-d5, 16-epiestriol-d3) was added and an additional 0.5 mL of freshly prepared hydrolysis buffer containing 0.15 M acetate buffer, pH 4.1, 2 mg of ascorbic acid, and 5 μL of β-glucuronidase/sulfatase (Helix pomatia, Sigma-Aldrich, St. Louis, MO, USA). After incubating the sample for 20 h at 37 °C, 8 mL of dichloromethane was added. The sample was slowly rotated at 8 rpm (RKVSD™, ATR, Inc., Laurel, MD, USA) for 30 min. After extraction, the organic solvent portion was transferred into a clean glass tube and evaporated to dryness at 60 °C under nitrogen gas (Reacti-Vap III™, Pierce, Rockford, IL, USA). One hundred microliters of 0.1 M NaHCO3 buffer (pH at 9.0) and 100 μL of dansyl chloride solution (1 mg/mL in CH3COCH3) were added to the dried sample, followed by vortexing and heating at 60 °C (Reacti-Therm III™ Heating Module, Pierce, Rockford, IL, USA) for 5 min to form dansyl derivatives of the EM and istopically labeled EM. The liquid chromatography–tandem mass spectrometry (LC–MS/MS) measurements were acquired using a TSQ Quantum-AM triple quadrupole mass spectrometer coupled with a Surveyor high-performance liquid chromatography system (Thermo Scientific, San Jose, CA, USA). The entire LC–MS/MS system was controlled using Xcalibur software (Thermo Scientific). Quantification of urinary EM was carried out using Xcalibur Quan Browser software (Thermo Scientific). Calibration curves for the 15 EM were constructed by plotting EM/deuterium-labeled EM peak area ratios versus amounts of each EM. A linear function was used to interpolate the amount of each EM in the urine samples. Masked replicate quality control samples were placed in each batch to assess laboratory variability. The overall coefficients of variation (CVs) were <7 % except for 4-methoxyestrone (17 %) and 4-methoxyestradiol (15 %), which are present at the lowest concentrations among the EM measured. The lower level of quantitation for each EM was about 150 fmol/mL urine.
Creatinine was measured in three batches at the Endocrine Core Laboratory at Emory University (Atlanta, GA, USA), Dr. Nader Rifai’s laboratory at Boston Children’s Hospital (Boston, MA, USA), and Dr. Vincent Ricchiuti’s laboratory at Brigham and Women’s Hospital (Boston, MA, USA). Overall CVs were ≤9.2 % in all labs.
Statistical Analyses
We standardized urinary EM concentrations (picomoles per milliliter) by urinary creatinine concentrations to account for urine dilution. There was no statistically significant fluctuation of creatinine concentrations across the primary exposure categories in our data (all P trend > 0.33). We log-transformed the resultant values (picomoles of EM per milligram of creatinine) in all analyses. We identified a small number of statistical outliers using the generalized extreme studentized deviate many-outlier detection approach [32] and excluded individual EM results with extreme values from the analyses. In addition, several EM values were missing because of technical difficulties or low sample volume; thus, the final sample size for each analysis varied by EM from 563 to 596. EM were evaluated individually, as well as grouped by metabolic pathway and as pathway ratios (see Table 2 for the specific groups and ratios).
Table 2.
EM measure | Number | Categories of height (in.) | Change per in. (%)a | P trendb | P c | ||||
---|---|---|---|---|---|---|---|---|---|
≤62 | 63 to 64 | 65 | 66 to 67 | 68+ | |||||
Number | 92~102 | 136~148 | 83~89 | 135~143 | 100~114 | ||||
Individual EM and metabolic pathway groups (pmol/mg creatinine) | |||||||||
Total EM | 590 | 147 | 126 | 129 | 127 | 123 | −2.1 | 0.01 | 0.01 |
Parent estrogens | 585 | 44 | 36 | 36 | 39 | 36 | −2.2 | 0.01 | 0.003 |
Estrone | 593 | 28 | 23 | 23 | 25 | 23 | −2.1 | 0.02 | 0.01 |
Estradiol | 587 | 15 | 12 | 12 | 13 | 11 | −3.1 | <0.001 | 0.001 |
Catechol EM | 589 | 40 | 32 | 31 | 33 | 30 | −3.1 | 0.03 | 0.02 |
2-Catechol EM | 591 | 33 | 27 | 27 | 28 | 27 | −2.4 | 0.06 | 0.03 |
2-Hydroxyestrone | 592 | 26 | 22 | 23 | 22 | 22 | −2.2 | 0.09 | 0.07 |
2-Hydroxyestradiol | 592 | 5.2 | 4.0 | 3.8 | 4.4 | 3.8 | −2.9 | 0.02 | 0.004 |
4-Catechol EM | |||||||||
4-Hydroxyestrone | 589 | 4.7 | 3.8 | 3.7 | 4.0 | 3.9 | −1.6 | 0.32 | 0.11 |
Methylated catechol EM | 567 | 11 | 9.6 | 9.2 | 9.5 | 9.3 | −2.2 | 0.04 | 0.02 |
Methylated 2-catechol EM | 577 | 11 | 9.3 | 9.0 | 9.4 | 8.9 | −2.2 | 0.03 | 0.02 |
2-Methoxyestrone | 592 | 9.1 | 7.0 | 7.2 | 7.7 | 6.7 | −2.9 | 0.01 | 0.01 |
2-Methoxyestradiol | 580 | 0.73 | 0.64 | 0.57 | 0.69 | 0.6 | −1.7 | 0.12 | 0.08 |
2-Hydroxyestrone-3-methyl ether | 592 | 1.2 | 0.97 | 0.94 | 1.1 | 0.99 | −1.6 | 0.16 | 0.02 |
Methylated 4-catechol EM | 585 | 0.16 | 0.14 | 0.14 | 0.14 | 0.13 | −2.4 | 0.10 | 0.13 |
4-Methoxyestrone | 596 | 0.11 | 0.09 | 0.10 | 0.10 | 0.08 | −4.0 | 0.02 | 0.06 |
4-Methoxyestradiol | 585 | 0.03 | 0.03 | 0.03 | 0.03 | 0.03 | −0.6 | 0.74 | 0.85 |
2-Hydroxylation pathway EMd | 576 | 46 | 40 | 40 | 39 | 39 | −2.2 | 0.05 | 0.05 |
4-Hydroxylation pathway EMe | 578 | 5.3 | 4.3 | 4.3 | 4.4 | 4.2 | −2.2 | 0.13 | 0.06 |
16-Hydroxylation pathway EM | 580 | 50 | 40 | 45 | 41 | 42 | −1.8 | 0.06 | 0.01 |
16α-Hydroxyestrone | 594 | 6.9 | 5.1 | 6.2 | 5.8 | 6.0 | −1.0 | 0.43 | 0.04 |
Estriol | 588 | 23 | 19 | 22 | 19 | 20 | −1.3 | 0.26 | 0.04 |
17-Epiestriol | 589 | 1.1 | 0.96 | 1.1 | 0.98 | 0.99 | −1.2 | 0.43 | 0.41 |
16-Ketoestradiol | 594 | 10 | 7.8 | 8.7 | 8.6 | 8.7 | −0.9 | 0.33 | 0.01 |
16-Epiestriol | 591 | 6.1 | 5.0 | 5.3 | 4.9 | 5.0 | −2.3 | 0.01 | 0.002 |
Metabolic pathway ratios | |||||||||
4-Catechol/2-catechols | 585 | 0.14 | 0.15 | 0.14 | 0.15 | 0.16 | 1.7 | 0.31 | 0.52 |
2-Catechols/16-pathway | 577 | 0.64 | 0.69 | 0.59 | 0.65 | 0.60 | −1.1 | 0.43 | 0.99 |
Catechols/16-pathway | 571 | 0.73 | 0.80 | 0.64 | 0.74 | 0.69 | −1.1 | 0.42 | 0.96 |
4-Pathway/2-pathway | 561 | 0.11 | 0.10 | 0.11 | 0.11 | 0.11 | 1.3 | 0.32 | 0.73 |
2-Pathway/16-pathway | 564 | 0.95 | 1.1 | 0.93 | 0.97 | 0.92 | −0.8 | 0.53 | 0.80 |
4-Pathway/16-pathway | 562 | 0.11 | 0.10 | 0.10 | 0.11 | 0.09 | −0.5 | 0.70 | 0.69 |
2,4-Pathway/16-pathway | 549 | 1.0 | 1.1 | 0.97 | 1.0 | 0.96 | −1.2 | 0.37 | 0.94 |
2-Pathway/4,16-pathway | 549 | 0.83 | 0.86 | 0.78 | 0.80 | 0.78 | −0.9 | 0.48 | 0.77 |
2-Catechols/methylated 2-catechols | 576 | 3.2 | 3.2 | 3.3 | 3.0 | 3.3 | −0.1 | 0.92 | 0.83 |
4-Catechol/methylated 4-catechols | 578 | 30 | 27 | 26 | 28 | 29 | 0.1 | 0.97 | 0.66 |
Catechols/methylated catechols | 561 | 3.5 | 3.6 | 3.6 | 3.4 | 3.6 | −0.4 | 0.71 | 0.96 |
Parent estrogens/estrogen metabolites | 539 | 0.43 | 0.42 | 0.39 | 0.43 | 0.40 | −0.8 | 0.24 | 0.44 |
2-Pathway/parent estrogens | 567 | 1.1 | 1.1 | 1.1 | 1.1 | 1.1 | 0.3 | 0.73 | 0.61 |
4-Pathway/parent estrogens | 567 | 0.12 | 0.13 | 0.12 | 0.12 | 0.13 | 0.6 | 0.70 | 0.78 |
16-Pathway/parent estrogens | 570 | 1.1 | 1.1 | 1.3 | 1.1 | 1.3 | 1.1 | 0.22 | 0.75 |
Adjusted for age at urine collection, first morning urine, month of urine collection, history of benign breast diseases, parity, oral contraceptive use, smoked within last month, ovulatory status, physical activity, and menstrual irregularity
aPercentage change for one unit increase of height when treating it as a continuous variable
bLinear trend across height using the Wald test determined the P trend
c P values from Wald test on dichotomous height (≤62, >62 in.)
dIncludes 2-hydroxyestrone, 2-hydroxyestradiol, 2-methoxyestrone, 2-methoxyestradiol, and 2-hydroxyestrone-3-methyl ether
eIncludes 4-hydroxyestrone, 4-methoxyestrone, and 4-methoxyestradiol
Primary analyses used generalized linear models to calculate adjusted geometric means of individual EM, metabolic pathway groups, and pathway ratios by category of attained height, BMI at urine collection, BMI at age 18, and secondarily of waist-to-hip ratio in 1993. Height was categorized into quintiles. BMI was categorized into six categories based on biological cutpoints. BMI at age 18 was categorized into four categories, since there were very few girls with BMI greater than 25 at age 18. Sample sizes for each category are shown in Tables 1, 2, 3, and 4. Test for trend analyses were conducted by modeling continuous exposure variables and calculating the Wald statistic. Multivariate models were adjusted for age at urine collection (continuous, in years), time of day of urine collection (1–8 am, 9 am–noon, 1 pm–midnight), month of collection (categorical), history of benign breast disease (yes, no), parity (0, 1+ children), duration of past oral contraceptive use (continuous), smoking (never, past, and current), physical activity (<3, 3–8, 9–17, 18–26, 27–41, and 42+ MET h/week), menstrual cycle irregularity (extremely regular, very regular, regular, and usually/always irregular), and ovulatory status of menstrual cycle during which urine was collected (an ovulatory cycle was defined as one with plasma progesterone collected on the same day as the urine sample ≥400 ng/dL). We also considered other potential confounders including family history of breast cancer, usual menstrual cycle length, age at menarche, and age at first birth; however, these did not change the estimates substantially and therefore were not included in the final models. Secondary analyses were restricted to those with ovulatory cycles (mid-luteal plasma progesterone ≥400 ng/dL), women who reported having regular menstrual cycles, women who provided sample during luteal days 4–10, parous women, and women who did not become menopausal until 2001 or later (thus were less likely to be perimenopausal at urine collection). We also stratified by the median age (43 years) and, for the height analyses, the median BMI (23.7 kg/m2). All P values were two-sided and considered to be statistically significant if ≤0.05. Given that there were 15 metabolites evaluated, we secondarily considered adjustment for multiple comparison using the Bonferroni method (P < 0.05/15 = 0.003) [3]. Analyses were conducted with SAS version 9 (SAS Institute, Cary, NC, USA).
Table 1.
Characteristics | Mean (SD) |
Age, years | 42.8 (3.8) |
Height, in. | 65.1 (2.7) |
BMI at urine collection, kg/m2 | 25.0 (5.5) |
BMI at age 18, kg/m2 | 21.1 (2.9) |
Physical activity, MET h/wk | 21.6 (20.5) |
Characteristics | Percentage |
First morning urine | 79.6 |
Family history of breast cancer | 15.4 |
History of benign breast disease | 15.3 |
Parous | 81.1 |
Ovulatory cyclea | 89.1 |
Current smoker | 7.0 |
Irregular menstrual cycle at age 18–22 | 4.5 |
Past oral contraceptive user | 83.9 |
aAn ovulatory cycle was defined as one with plasma progesterone collected on the same day as the urine sample ≥400 ng/dL
Table 3.
EM measure | Number | Current BMI (kg/m2) | Change per kg/m2 (%)a | P trendb | |||||
---|---|---|---|---|---|---|---|---|---|
<20 | 20 to <22.5 | 22.5 to <25 | 25 to <27.5 | 27.5 to <30 | 30+ | ||||
Number | 60~64 | 151~161 | 126~140 | 73~77 | 45~53 | 80~97 | |||
Individual EM and metabolic pathway groups (pmol/mg creatinine) | |||||||||
Total EM | 586 | 146 | 144 | 132 | 128 | 113 | 120 | −1.0 | 0.01 |
Parent estrogens | 581 | 40 | 40 | 39 | 41 | 35 | 37 | −0.5 | 0.29 |
Estrone | 589 | 27 | 26 | 25 | 25 | 23 | 23 | −0.8 | 0.11 |
Estradiol | 583 | 11 | 12 | 12 | 12 | 11 | 12 | 0.1 | 0.80 |
Catechol EM | 585 | 43 | 39 | 36 | 31 | 30 | 28 | −2.4 | <0.001 |
2-Catechol EM | 587 | 38 | 36 | 31 | 31 | 22 | 23 | −3.2 | <0.001 |
2-Hydroxyestrone | 588 | 32 | 30 | 26 | 26 | 18 | 18 | −3.4 | <0.001 |
2-Hydroxyestradiol | 588 | 4.8 | 5.5 | 4.5 | 4.6 | 3.1 | 3.2 | −3.1 | <0.001 |
4-Catechol EM | |||||||||
4-Hydroxyestrone | 585 | 4.9 | 4.0 | 3.9 | 3.2 | 3.8 | 4.2 | 0 | 0.96 |
Methylated catechol EM | 563 | 13 | 11 | 10 | 9.5 | 8.3 | 8.4 | −2.4 | <0.001 |
Methylated 2-catechol EM | 573 | 12 | 11 | 10 | 9.3 | 8.1 | 8.2 | −2.4 | <0.001 |
2-Methoxyestrone | 588 | 9.8 | 9.2 | 8.1 | 7.3 | 5.8 | 6.1 | −3.2 | <0.001 |
2-Methoxyestradiol | 576 | 0.86 | 0.73 | 0.71 | 0.61 | 0.56 | 0.56 | −2.2 | <0.001 |
2-Hydroxyestrone-3-methyl ether | 588 | 1.4 | 1.2 | 1.1 | 1.1 | 0.95 | 0.91 | −2.3 | <0.001 |
Methylated 4-catechol EM | 581 | 0.16 | 0.17 | 0.16 | 0.13 | 0.15 | 0.10 | −2.8 | <0.001 |
4-Methoxyestrone | 592 | 0.12 | 0.13 | 0.11 | 0.10 | 0.12 | 0.06 | −3.9 | <0.001 |
4-Methoxyestradiol | 581 | 0.04 | 0.04 | 0.04 | 0.03 | 0.03 | 0.03 | −1.8 | 0.06 |
2-Hydroxylation pathway EMc | 572 | 52 | 49 | 45 | 42 | 35 | 34 | −2.6 | <0.001 |
4-Hydroxylation pathway EMd | 574 | 5.6 | 4.7 | 4.6 | 3.7 | 3.9 | 4.4 | −0.6 | 0.40 |
16-Hydroxylation pathway EM | 576 | 44 | 46 | 42 | 42 | 40 | 43 | −0.3 | 0.58 |
16α-Hydroxyestrone | 590 | 7.7 | 7.3 | 6.3 | 6.7 | 5.3 | 5.2 | −1.7 | 0.01 |
Estriol | 584 | 19 | 20 | 19 | 19 | 18 | 22 | 0.6 | 0.29 |
17-Epiestriol | 585 | 0.98 | 1.0 | 0.99 | 0.79 | 1.1 | 0.99 | 0.1 | 0.96 |
16-Ketoestradiol | 590 | 9.4 | 9.9 | 9.1 | 9.3 | 8.7 | 7.7 | −1.0 | 0.04 |
16-Epiestriol | 587 | 4.7 | 5.4 | 5.0 | 5.3 | 5.1 | 5.2 | 0.5 | 0.34 |
Metabolic pathway ratios | |||||||||
4-Catechol/2-catechols | 581 | 0.13 | 0.12 | 0.13 | 0.11 | 0.17 | 0.20 | 3.5 | <0.001 |
2-Catechols/16-pathway | 573 | 0.81 | 0.74 | 0.71 | 0.67 | 0.55 | 0.52 | −2.9 | <0.001 |
Catechols/16-pathway | 567 | 0.86 | 0.79 | 0.79 | 0.70 | 0.68 | 0.63 | −2.0 | 0.01 |
4-Pathway/2-pathway | 557 | 0.10 | 0.09 | 0.10 | 0.09 | 0.10 | 0.13 | 2.5 | <0.001 |
2-Pathway/16-pathway | 560 | 1.2 | 1.1 | 1.1 | 0.97 | 0.88 | 0.80 | −2.4 | <0.001 |
4-Pathway/16-pathway | 558 | 0.12 | 0.10 | 0.10 | 0.09 | 0.10 | 0.10 | −0.3 | 0.61 |
2,4-Pathway/16-pathway | 545 | 1.2 | 1.1 | 1.1 | 0.98 | 0.99 | 0.90 | −1.7 | 0.01 |
2-Pathway/4,16-pathway | 545 | 0.99 | 0.93 | 0.92 | 0.85 | 0.85 | 0.67 | −2.5 | <0.001 |
2-Catechols/methylated 2-catechols | 572 | 3.2 | 3.3 | 3.3 | 3.5 | 3.2 | 3.1 | −0.3 | 0.59 |
4-Catechol/methylated 4-catechols | 574 | 30 | 23 | 24 | 23 | 23 | 39 | 2.9 | 0.02 |
Catechols/methylated catechols | 557 | 3.4 | 3.6 | 3.5 | 3.6 | 3.5 | 3.6 | 0.4 | 0.48 |
Parent estrogens/estrogen metabolites | 535 | 0.35 | 0.38 | 0.42 | 0.44 | 0.44 | 0.44 | 1.2 | <0.001 |
2-Pathway/parent estrogens | 563 | 1.5 | 1.3 | 1.3 | 1.1 | 1.0 | 0.94 | −2.6 | <0.001 |
4-Pathway/parent estrogens | 563 | 0.15 | 0.13 | 0.12 | 0.10 | 0.12 | 0.12 | −0.3 | 0.52 |
16-Pathway/parent estrogens | 566 | 1.2 | 1.2 | 1.1 | 1.2 | 1.2 | 1.2 | −0.1 | 0.87 |
Adjusted for age at urine collection, first morning urine, month of urine collection, history of benign breast diseases, parity, oral contraceptive use, smoked within last month, ovulatory status, physical activity, and menstrual irregularity
aPercentage change for one unit increase of BMI when treating it as a continuous variable
bLinear trend across BMI using the Wald test determined the P trend
cIncludes 2-hydroxyestrone, 2-hydroxyestradiol, 2-methoxyestrone, 2-methoxyestradiol, and 2-hydroxyestrone-3-methyl ether
dIncludes 4-hydroxyestrone, 4-methoxyestrone, and 4-methoxyestradiol
Table 4.
EM measure | Number | BMI at age 18 (kg/m2) | Change per kg/m2 (%)a | P trendb | |||
---|---|---|---|---|---|---|---|
<20 | 20 to <22.5 | 22.5 to <25 | 25+ | ||||
Number | 205~227 | 217~232 | 78~89 | 39~47 | |||
Individual EM and metabolic pathway groups (pmol/mg creatinine) | |||||||
Total EM | 589 | 132 | 122 | 119 | 130 | −0.9 | 0.26 |
Parent estrogens | 585 | 40 | 36 | 36 | 37 | −1.3 | 0.17 |
Estrone | 592 | 26 | 22 | 23 | 23 | −1.3 | 0.19 |
Estradiol | 587 | 13 | 11 | 12 | 12 | −1.0 | 0.26 |
Catechol EM | 588 | 35 | 29 | 32 | 30 | −2.1 | 0.14 |
2-Catechol EM | 591 | 31 | 26 | 26 | 24 | −3.1 | 0.01 |
2-Hydroxyestrone | 592 | 26 | 21 | 21 | 19 | −3.4 | 0.01 |
2-Hydroxyestradiol | 592 | 4.6 | 3.9 | 3.9 | 3.6 | −2.2 | 0.07 |
4-Catechol EM | |||||||
4-Hydroxyestrone | 588 | 3.9 | 3.5 | 4.3 | 4.4 | 1.1 | 0.50 |
Methylated catechol EM | 567 | 10 | 9.1 | 9.8 | 9.1 | −1.5 | 0.15 |
Methylated 2-catechol EM | 577 | 10 | 8.8 | 9.5 | 8.8 | −1.5 | 0.15 |
2-Methoxyestrone | 591 | 8.2 | 6.9 | 7.5 | 6.3 | −2.7 | 0.02 |
2-Methoxyestradiol | 580 | 0.68 | 0.61 | 0.67 | 0.56 | −1.2 | 0.30 |
2-Hydroxyestrone-3-methyl ether | 591 | 1.1 | 0.99 | 1 | 0.91 | −1.4 | 0.22 |
Methylated 4-catechol EM | 584 | 0.14 | 0.12 | 0.14 | 0.14 | −2.0 | 0.18 |
4-Methoxyestrone | 595 | 0.1 | 0.09 | 0.1 | 0.08 | −3.6 | 0.03 |
4-Methoxyestradiol | 584 | 0.03 | 0.03 | 0.03 | 0.04 | 0 | 0.97 |
2-Hydroxylation pathway EMc | 576 | 43 | 37 | 38 | 39 | −2.0 | 0.10 |
4-Hydroxylation pathway EMd | 577 | 4.4 | 3.9 | 4.6 | 4.8 | 0.4 | 0.76 |
16-Hydroxylation pathway EM | 579 | 44 | 44 | 44 | 44 | −0.3 | 0.78 |
16α-Hydroxyestrone | 593 | 6.2 | 5.9 | 5.7 | 5.7 | −1.2 | 0.33 |
Estriol | 587 | 20 | 21 | 20 | 20 | 0 | 0.97 |
17-Epiestriol | 588 | 0.96 | 1.1 | 1.1 | 1.1 | 1.0 | 0.52 |
16-Ketoestradiol | 593 | 9.1 | 8.6 | 8.1 | 8.1 | −1.3 | 0.14 |
16-Epiestriol | 590 | 5.2 | 5.3 | 5 | 5.4 | 0.3 | 0.74 |
Metabolic pathway ratios | |||||||
4-Catechol/2-catechols | 585 | 0.13 | 0.15 | 0.18 | 0.19 | 4.5 | <0.001 |
2-Catechols/16-pathway | 577 | 0.68 | 0.58 | 0.58 | 0.56 | −2.4 | 0.11 |
Catechols/16-pathway | 571 | 0.77 | 0.65 | 0.69 | 0.65 | −2.1 | 0.17 |
4-Pathway/2-pathway | 561 | 0.1 | 0.11 | 0.13 | 0.12 | 2.6 | 0.04 |
2-Pathway/16-pathway | 564 | 1.0 | 0.88 | 0.91 | 0.91 | −1.8 | 0.18 |
4-Pathway/16-pathway | 561 | 0.1 | 0.09 | 0.1 | 0.11 | 0.3 | 0.82 |
2,4-Pathway/16-pathway | 549 | 1.1 | 0.91 | 0.96 | 0.99 | −1.8 | 0.21 |
2-Pathway/4,16-pathway | 549 | 0.86 | 0.75 | 0.73 | 0.74 | −2.1 | 0.10 |
2-Catechols/methylated 2-catechols | 576 | 3.2 | 3.1 | 3.0 | 3.3 | −0.6 | 0.60 |
4-Catechol/methylated 4-catechols | 577 | 26 | 27 | 28 | 32 | 2.9 | 0.20 |
Catechols/methylated catechols | 561 | 3.6 | 3.4 | 3.4 | 3.8 | −0.4 | 0.76 |
Parent estrogens/estrogen metabolites | 539 | 0.42 | 0.41 | 0.41 | 0.4 | 0.4 | 0.59 |
2-Pathway/parent estrogens | 567 | 1.2 | 1.1 | 1.1 | 1.1 | −1.5 | 0.09 |
4-Pathway/parent estrogens | 567 | 0.12 | 0.12 | 0.13 | 0.14 | 1.3 | 0.36 |
16-Pathway/parent estrogens | 570 | 1.2 | 1.3 | 1.3 | 1.2 | 0.5 | 0.64 |
Adjusted for age at urine collection, first morning urine, month of urine collection, history of benign breast diseases, parity, oral contraceptive use, smoked within last month, ovulatory status, physical activity, and menstrual irregularity
aPercentage change for one unit increase of BMI at age 18 when treating it as a continuous variable
bLinear trend across BMI at age 18 using the Wald test determined the p-trend
cIncludes 2-hydroxyestrone, 2-hydroxyestradiol, 2-methoxyestrone, 2-methoxyestradiol, and 2-hydroxyestrone-3-methyl ether
dIncludes 4-hydroxyestrone, 4-methoxyestrone, and 4-methoxyestradiol
Results
Among the 603 women available for analysis, the average age was 42.7 years (range 33.3–50.9 years; Table 1). Eighty-nine percent of women had an ovulatory cycle at urine collection, 15 % had a family history of breast cancer, 44 % had a history of benign breast disease, 81 % had given birth to at least one child, 86 % were 4–10 days before the next cycle, and 80 % gave a first morning urine. The average height was 65.1 in. (standard deviation = 2.7). On average, BMI at age 18 and current BMI were 21.1 kg/m2 (standard deviation = 2.9) and 25.0 kg/m2 (standard deviation = 5.5), respectively.
Height was inversely associated with total urinary EM (P trend = 0.01) and with six of 15 urinary EM, including estrone (P trend = 0.02), estradiol (P trend < 0.001), 2-hydroxyestradiol (P trend = 0.02), 2-methoxyestrone (P trend = 0.01), 4-methoxyestrone (P trend = 0.02), and 16-epiestriol (P trend = 0.01) (Table 2). Compared to women with a height ≤62 in., levels in those with height ≥68 in. were 18 % lower for estrone, 27 % lower for estradiol, 27 % lower for 2-hydroxyestradiol, 26 % lower for 2-methoxyestrone, 27 % lower for 4-methoxyestrone, and 18 % lower for 16-epiestriol. Height was associated with the 2-hydroxylation pathway (P trend = 0.05) and the methylated catechol pathway (P trend = 0.04), but not with the other pathways or any metabolic pathway ratios. The associations between height and EM appeared to be driven by the high EM values in the lowest category (≤62 in). Therefore, in a post hoc analysis, we evaluated the possibility of a non-linear association by dichotomizing height at above or below 62 in. and also present the results of the Wald test from multivariate linear regression models. The interpretation of the results based on this approach was similar to the linear trend tests, except that the associations for the 2-hydroxyestrone-3-methyl ether, 16α-hydroxyestrone, estriol, and 16-ketoestradiol were statistically significant when evaluating associations dichotomized at 62 in. versus the trend test.
Current BMI also was inversely associated with total urinary EM (P trend = 0.01) and with eight out of 15 urinary EM, including 2-hydroxyestrone (P trend < 0.001), 2-hydroxyestradiol (P trend < 0.001), 2-methoxyestrone (P trend < 0.001), 2-methoxyestradiol (P trend < 0.001), 2-hydroxyestrone-3-methyl ether (P trend < 0.001), 4-methoxyestrone (P trend < 0.001), 16α-hydroxyestrone (P trend = 0.01), and 16-ketoestradiol (P trend = 0.04) (Table 3). Compared to women with a BMI < 20 kg/m2 levels in those with BMI ≥ 30 were 44 % lower for 2-hydroxyestrone, 33 % lower for 2-hydroxyestradiol, 38 % lower for 2-methoxyestrone, 35 % lower for 2-methoxyestradiol, 35 % lower for 2-hydroxyestrone-3-methyl ether, 50 % lower for 4-methoxyestrone, 32 % lower for 16α-hydroxyestrone, and 18 % lower for 16-ketoestradiol. BMI was associated with the 2-hydroxylation pathway (P trend < 0.001), the catechol pathway (P trend < 0.001), 2-catechol pathway (P trend < 0.001), and the methylated catechol pathways (P trend < 0.001), but not with the 4- or 16-hydroxylation pathways. In addition, higher current BMI was associated with a higher 4-pathway/2-pathway ratio (P trend = 0.001), a lower 2-pathway/16-pathway ratio (P trend < 0.001), a lower 2,4-pathway/16-pathway ratio (P trend < 0.001), and a higher parent estrogen/EM ratio (P trend < 0.001), among others.
BMI at age 18 was not associated with total urinary EM concentrations (P trend = 0.26). However, BMI at age 18 was inversely associated with 2-hydroxyestrone (P trend = 0.01), 2-methoxyestrone (P trend = 0.02), and 4-methoxyestrone (P trend = 0.03), but not other EM (Table 4). BMI at age 18 was not associated with the 2-, 4-, or 16-hydroxylation pathways. It also was positively associated with ratios of 4-catechol/2-catechols (P trend < 0.001) and 4-pathway/2-pathway (P trend = 0.04).
Overall, results for height, current BMI, and BMI at age 18 did not change when excluding women with anovulatory cycles (10 % of the population) or irregular menstrual cycles (5 %), when restricting to parous women (81 %), women with mid-luteal urine samples collected 4–10 days prior to the next menstrual cycle (85 %), or women who did not become menopausal within 4 years after sample collection (88 %) (data not shown). Further, the results did not vary by age, and the height results did not vary by current BMI (data not shown). When both height and current BMI were included in the same multivariate models, each was a statistically significant predictor for certain urinary EM (data not shown). When both current BMI and BMI at age 18 were included in the same multivariate models, current BMI remained statistically significant for most urinary EM (data not shown). We assessed different ways of adjusting for urine dilution in the statistical models: standardizing individual EM and grouped EM (picomoles per milliliter urine) by creatinine (milligrams per milliliter urine) as the outcome variables (primary analysis) and using EM and grouped EM (picomoles per milliliter urine) as the outcome variables with creatinine (milligrams per milliliter urine) as a covariate. These methods produced similar results (data not shown).
Using the Bonferroni correction P value of 0.003, height remained significantly associated with estradiol, and BMI remained statistically significantly associated with six EM including 2-hydroxyestrone, 2-hydroxyestradiol, 2-methoxyestrone, 2-methoxyestradiol, 2-hydroxyestrone-3-mehyl ether, and 4-methoxyestrone.
Discussion
To our knowledge, this study is the first to examine relationships between anthropometric measures and urinary estrogen metabolites. Attained height and current BMI were strongly inversely associated with total urinary EM as well as multiple specific EM and related pathways among premenopausal women. The patterns of associations with individual EM were different for height and current BMI. This is summarized in Fig. 1, which combines knowledge about endogenous estrogen metabolism with our study results. Height was inversely associated with parent EM, catechol EM, and the 2-hydroxylation pathway. Current BMI was inversely associated with nearly all EM along the 2- and 4-pathways, though there was a U-shaped relationship with 4-hydroxyestrone. BMI at age 18 was not associated clearly with urinary EM with the possible exceptions of 2-catechols.
Our results suggest possibly different underlying mechanisms of associations for height and BMI with EM. For example, BMI was strongly inversely associated with 2-hydroxylation pathway, but not associated with the 16-hydroxylation pathway, which is thought to have strong estrogenic and genotoxic activity [35]. Metabolism of the parent estrogens, estrone and estradiol, has several mutually exclusive pathways that produce different metabolic products. Oxidation of estrone and estradiol can occur at the C-2, C-4, or C-16 positions on the steroid ring to create catechol estrogens [45]. With further metabolism, the catechol EMs can be methylated at one of the adjacent hydroxyl groups, generating methylated catechol EMs. EMs in the 16-hydroxylation pathway are metabolized into 17-epiestriol, estriol, 16-ketoestradiol, and 16-epiestriol [45]. Experimental studies suggest that metabolites along these pathways may have differential levels of estrogenic and genotoxic activities [45]. It has been hypothesized that estrogens metabolized through the 2-hydroxylation pathway may have a more favorable breast cancer risk profile over the 16-hydroxylation pathway [2, 4, 5, 10]. In our study, current BMI, but not height, was inversely associated with the ratio of 2-pathway/16-pathway.
Our results suggest that the positive association between height and premenopausal breast cancer risk [46] may be explained, at least in part, by estrogen metabolism profile, especially for the shortest women who had the most distinct hormone profile. Our data suggest that height may be inversely related to urinary concentrations of many EMs, particularly the methylated catechols, which may be beneficial for breast carcinogenesis [10]. These EMs generally were inversely related to risk of premenopausal cancer in the same population [10]. Further studies should explore the potential mechanism linking height to premenopausal estrogen metabolism.
With respect to BMI, our results are consistent with previous studies of circulating estrogens. Some studies reported that obese premenopausal women had lower plasma estradiol concentrations than that of normal weight women [7, 8, 18, 29, 47]. We observed that BMI was inversely associated with plasma levels of estradiol both during follicular and luteal phase among premenopausal women [39]. Other studies also reported that obesity was associated with significant decreases in 2-hydroxylation of estradiol in premenopausal women [14, 34]. This is consistent with our current results that BMI was inversely associated with total urinary estrogens, total estrone and estradiol levels, and a series of downstream metabolites of estradiol in urine, including a reduction in 2-hydroxylation. This seems to suggest that the regulatory mechanism linking BMI and estrogens is similar for circulating estrogen metabolism as well as for excretion in urine.
In the NHSII, we reported that both EM and BMI were inversely associated with breast cancer risk in premenopausal women [10, 20]. This appears to conflict with our results that BMI was associated with lower EM. Thus, it is possible that estrogen metabolism is not a mechanism through which BMI influences breast cancer risk in premenopausal women. Alternate etiologic pathways for the BMI–breast cancer association in premenopausal women should be explored.
Limitations
The primary limitation of our study is its cross-sectional nature without ability to examine causal relationships. However, our study is large, with 603 women. In addition, participants in our study were all healthy women with carefully timed urine samples, which is helpful to reduce misclassification by time in the menstrual cycle of the collection. Another limitation may be multiple comparisons. We evaluated associations with a number of a priori derived measures, including grouping of individual EM and ratios of these groupings. However, we did so based on what is known about estrogen metabolism; the metabolic pathway groups and pathways ratios that we derived are based on recognized metabolic pathways, shared biochemistry, and/or etiologic hypotheses. Even under Bonferroni correction for multiple comparisons, many of the associations remained statistically significant; however, since the metabolic levels are correlated, Bonferroni correction is a conservative estimate of statistical significance. Third, the associations between height and several EM were driven by differences in the lowest category of height. We cannot rule out the possibility of residual confounding or a threshold effect. However, we adjusted for multiple potential confounders, including menstrual irregularity [16]. In general, the associations observed in the individual EMs were recapitulated in the summary pathway measures. A final limitation is that little is known about the relationships of urinary EM to circulating parent estrogens or EM.
Conclusions
Our results suggest that taller height and higher current BMI were associated with lower levels of urinary EM in the mid-luteal phase among premenopausal women. As this is the first analysis to examine body size with these 15 urinary EM, further studies with appropriately timed samples are required to confirm our findings.
Acknowledgments
We thank participants of the Nurses’ Health Study II for their longstanding contributions and support to this study. This project was supported by NCI grants R01 CA67262 and R01 CA50385, as well as the National Cancer Institute Intramural Funding Program of the Division of Cancer Epidemiology and Genetics and federal funds from the National Cancer Institute awarded under contract HHSN261200800001E to SAIC Frederick, Inc. J Xie is supported by the Breast Cancer Research Foundation, the Harvey V. Fineberg Fellowship in Cancer Prevention 2010–2011, and other scholarships of Harvard University. The content of this publication does not necessarily reflect the views or policies of the US Department of Health and Human Services nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government.
Conflict of Interest
None declared.
Footnotes
R. G. Zeigler and S. S. Tworoger contributed equally to this work.
References
- 1.Baird DD, Robert McConnaughey D, Weinberg CR, Musey PI, Collins DC, Kesner JS, Knecht EA, Wilcox AJ. Application of a method for estimating day of ovulation using urinary estrogen and progesterone metabolites. Epidemiology. 1995;6(5):547–550. doi: 10.1097/00001648-199509000-00015. [DOI] [PubMed] [Google Scholar]
- 2.Bentz AT, Schneider CM, Westerlind KC. The relationship between physical activity and 2-hydroxyestrone, 16α-hydroxyestrone, and the 2/16 ratio in premenopausal women (United States) Cancer Causes Control. 2005;16(4):455–461. doi: 10.1007/s10552-004-6256-6. [DOI] [PubMed] [Google Scholar]
- 3.Bonferroni CE. Teoria statistica delle classi e calcolo delle probabilità. Pubblicazioni del R Istituto Superiore di Scienze Economiche e Commerciali di Firenze. 1936;8:3–62. [Google Scholar]
- 4.Bradlow HL, Davis DL, Lin G, Sepkovic D, Tiwari R. Effects of pesticides on the ratio of 16α/2-hydroxyestrone: a biologic marker of breast cancer risk. Environ Heal Perspect. 1995;103(Suppl 7):147–150. doi: 10.1289/ehp.95103s7147. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Bradlow HL, Hershcopf RJ, Martucci CP, Fishman J. Estradiol 16 alpha-hydroxylation in the mouse correlates with mammary tumor incidence and presence of murine mammary tumor virus: a possible model for the hormonal etiology of breast cancer in humans. Proc Natl Acad Sci U S A. 1985;82(18):6295–6299. doi: 10.1073/pnas.82.18.6295. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Cavalieri E, Frenkel K, Liehr JG, Rogan E, Roy D. Chapter 4: Estrogens as endogenous genotoxic agents—DNA adducts and mutations. JNCI Monogr. 2000;2000(27):75–94. doi: 10.1093/oxfordjournals.jncimonographs.a024247. [DOI] [PubMed] [Google Scholar]
- 7.De Pergola G, Giorgino F, Cospite MR, Giagulli VA, Cignarell M, Ferri G, Giorgino R. Relation between sex hormones and serum lipoprotein and lipoprotein(a) concentrations in premenopausal obese women. Arterioscler Thromb. 1993;13(5):675–679. doi: 10.1161/01.ATV.13.5.675. [DOI] [PubMed] [Google Scholar]
- 8.Dunaif A, Mandeli J, Fluhr H, Dobrjansky A. The impact of obesity and chronic hyperinsulinemia on gonadotropin release and gonadal steroid secretion in the polycystic ovary syndrome. J Clin Endocrinol Metab. 1988;66:131–139. doi: 10.1210/jcem-66-1-131. [DOI] [PubMed] [Google Scholar]
- 9.Eliassen AH, Missmer SA, Tworoger SS, Spiegelman D, Barbieri RL, Dowsett M, Hankinson SE. Endogenous steroid hormone concentrations and risk of breast cancer among premenopausal women. J Natl Cancer Inst. 2006;98(19):1406–1415. doi: 10.1093/jnci/djj376. [DOI] [PubMed] [Google Scholar]
- 10.Eliassen AH, Spiegelman D, Xia X, Keefer LK, Veenstra TD, Barbieri RL, Willett WC, Hankinson SE, Ziegler RG. Urinary estrogens and estrogen metabolites and subsequent risk of breast cancer among premenopausal women. Cancer Res. 2012;72(3):696–706. doi: 10.1158/0008-5472.CAN-11-2507. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Eliassen AH, Ziegler RG, Rosner B, Veenstra TD, Roman JM, Xia X, Hankinson SE. Reproducibility of fifteen urinary estrogens and estrogen metabolites over a 2- to 3-year period in premenopausal women. Cancer Epidemiol Biomarkers Prev. 2009;18(11):2860–2868. doi: 10.1158/1055-9965.EPI-09-0591. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.The Endogenous Hormones Breast Cancer Collaborative Group Endogenous sex hormones and breast cancer in postmenopausal women: reanalysis of nine prospective studies. J Natl Cancer Inst. 2002;94(8):606–616. doi: 10.1093/jnci/94.8.606. [DOI] [PubMed] [Google Scholar]
- 13.Falk RT, Xia X, Keefer L, Veenstra TD, Ziegler RG. A liquid chromatography-mass spectrometry method for the simultaneous measurement of 15 urinary estrogens and estrogen metabolites: assay reproducibility and interindividual variability. Cancer Epidemiol Biomarkers Prev. 2008;17(12):3411–3418. doi: 10.1158/1055-9965.EPI-08-0355. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Fishman J, Boyar RM, Hellman L. Influence of body weight on estradiol metabolism in young women. J Clin Endocrinol Metab. 1975;41(5):989–991. doi: 10.1210/jcem-41-5-989. [DOI] [PubMed] [Google Scholar]
- 15.Flötotto T, Djahansouzi S, Gläser M, Hanstein B, Niederacher D, Brumm C, Beckmann MW. Hormones and hormone antagonists: mechanisms of action in carcinogenesis of endometrial and breast cancer. Horm Metab Res. 2001;33(08):451–457. doi: 10.1055/s-2001-16936. [DOI] [PubMed] [Google Scholar]
- 16.Fortner RT, Hankinson SE, Schairer C, Xia X, Ziegler RG, Heather Eliassen A (2012) Association between reproductive factors and urinary estrogens and estrogen metabolites in premenopausal women. Cancer Epidemiol Biomarkers Prev. doi:10.1158/1055-9965.epi-12-0171 [DOI] [PMC free article] [PubMed]
- 17.Green J, Cairns BJ, Delphine Casabonne F, Wright L, Reeves G, Beral V. Height and cancer incidence in the Million Women Study: prospective cohort, and meta-analysis of prospective studies of height and total cancer risk. Lancet Oncol. 2011;12(8):785–794. doi: 10.1016/S1470-2045(11)70154-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Grenman S, Ronnemaa T, Irjala K, Kaihola HL, Gronroos M. Sex steroid, gonadotropin, cortisol, and prolactin levels in healthy, massively obese women: correlation with abdominal fat cell size and effect of weight reduction. J Clin Endocrinol Metab. 1986;63(6):1257–1261. doi: 10.1210/jcem-63-6-1257. [DOI] [PubMed] [Google Scholar]
- 19.Helzlsouer KJ, Alberg AJ, Bush TL, Longcope C, Gordon GB, Comstock GW. A prospective study of endogenous hormones and breast cancer. Cancer Detect Prev. 1994;18(2):79–85. [PubMed] [Google Scholar]
- 20.Huang Z, Hankinson SE, Colditz GA, Stampfer MJ, Hunter DJ, Manson JAE, Hennekens CH, Rosner B, Speizer FE, Willett WC. Dual effects of weight and weight gain on breast cancer risk. JAMA: J Am Med Assoc. 1997;278(17):1407–1411. doi: 10.1001/jama.1997.03550170037029. [DOI] [PubMed] [Google Scholar]
- 21.Jozan S, Moure C, Gillois M, Bayard F. Effects of estrone on cell proliferation of a human breast cancer (MCF-7) in long term tissue culture. J Steroid Biochem. 1979;10(3):341–342. doi: 10.1016/0022-4731(79)90263-2. [DOI] [PubMed] [Google Scholar]
- 22.Kaaks R, Rinaldi S, Key TJ, Berrino F, Peeters PHM, Biessy C, Dossus L, et al. Postmenopausal serum androgens, oestrogens and breast cancer risk: the European prospective investigation into cancer and nutrition. Endocr Relat Cancer. 2005;12(4):1071–1082. doi: 10.1677/erc.1.01038. [DOI] [PubMed] [Google Scholar]
- 23.Kaaks R, Berrino F, Key T, Rinaldi S, Dossus L, Biessy C, Secreto G, et al. Serum sex steroids in premenopausal women and breast cancer risk within the European Prospective Investigation into Cancer and Nutrition (EPIC) J Natl Cancer Inst. 2005;97(10):755–765. doi: 10.1093/jnci/dji132. [DOI] [PubMed] [Google Scholar]
- 24.Kabat GC, O’Leary ES, Gammon MD, Sepkovic DW, Teitelbaum SL, Britton JA, Terry MB, Neugut AI, Leon Bradlow H. Estrogen metabolism and breast cancer. Epidemiology. 2006;17(1):80–88. doi: 10.1097/01.ede.0000190543.40801.75. [DOI] [PubMed] [Google Scholar]
- 25.Kabuto M, Akiba S, Stevens RG, Neriishi K, Land CE. A prospective study of estradiol and breast cancer in Japanese women. Cancer Epidemiol Biomarkers Prev. 2000;9(6):575–579. [PubMed] [Google Scholar]
- 26.Lippman M, Monaco ME, Bolan G. Effects of estrone, estradiol, and estriol on hormone-responsive human breast cancer in long-term tissue culture. Cancer Res. 1977;37(6):1901–1907. [PubMed] [Google Scholar]
- 27.Micheli A, Muti P, Secreto G, Krogh V, Meneghini E, Venturelli E, Sieri S, Pala V, Berrino F. Endogenous sex hormones and subsequent breast cancer in premenopausal women. Int J Cancer. 2004;112(2):312–318. doi: 10.1002/ijc.20403. [DOI] [PubMed] [Google Scholar]
- 28.Missmer SA, Heather Eliassen A, Barbieri RL, Hankinson SE. Endogenous estrogen, androgen, and progesterone concentrations and breast cancer risk among postmenopausal women. J Natl Cancer Inst. 2004;96(24):1856–1865. doi: 10.1093/jnci/djh336. [DOI] [PubMed] [Google Scholar]
- 29.Potischman N, Swanson CA, Siiteri P, Hoover RN. Reversal of relation between body mass and endogenous estrogen concentrations with menopausal status. J Natl Cancer Inst. 1996;88(11):756–758. doi: 10.1093/jnci/88.11.756. [DOI] [PubMed] [Google Scholar]
- 30.Rimm EB, Stampfer MJ, Colditz GA, Chute CG, Litin LB, Willett WC. Validity of self-reported waist and hip circumferences in men and women. Epidemiology. 1990;1(6):466–473. doi: 10.1097/00001648-199011000-00009. [DOI] [PubMed] [Google Scholar]
- 31.Rosenberg CR, Pasternack BS, Shore RE, Koenig KL, Toniolo PG. Premenopausal estradiol levels and the risk of breast cancer: a new method of controlling for day of the menstrual cycle. Am J Epidemiol. 1994;140(6):518–525. doi: 10.1093/oxfordjournals.aje.a117278. [DOI] [PubMed] [Google Scholar]
- 32.Rosner B. Percentage points for a generalized ESD many-outlier procedure. Technometrics. 1983;25(2):165–172. doi: 10.1080/00401706.1983.10487848. [DOI] [Google Scholar]
- 33.Schernhammer ES, Rosner B, Willett WC, Laden F, Colditz GA, Hankinson SE. Epidemiology of urinary melatonin in women and its relation to other hormones and night work. Cancer Epidemiol Biomarkers Prev. 2004;13(6):936–943. [PubMed] [Google Scholar]
- 34.Schneider J, Bradlow HL, Strain G, Levin J, Anderson K, Fishman J. Effects of obesity on estradiol metabolism: decreased formation of nonuterotropic metabolites. J Clin Endocrinol Metab. 1983;56(5):973–978. doi: 10.1210/jcem-56-5-973. [DOI] [PubMed] [Google Scholar]
- 35.Telang NT, Suto A, Wong GY, Osborne MP, Leon Bradlow H. Induction by estrogen metabolite 16α-hydroxyestrone of genotoxic damage and aberrant proliferation in mouse mammary epithelial cells. J Natl Cancer Inst. 1992;84(8):634–638. doi: 10.1093/jnci/84.8.634. [DOI] [PubMed] [Google Scholar]
- 36.Thomas HV, Key TJ, Allen DS, Moore JW, Dowsett M, Fentiman IS, Wang DY. A prospective study of endogenous serum hormone concentrations and breast cancer risk in premenopausal women on the island of Guernsey. Br J Cancer. 1997;75(7):1075–1079. doi: 10.1038/bjc.1997.183. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Troy LM, Hunter DJ, Manson JE, Colditz GA, Stampfer MJ, Willett WC. The validity of recalled weight among younger women. Int J Obes Relat Metab Disord. 1995;19(8):570–572. [PubMed] [Google Scholar]
- 38.Tworoger SS, Sluss P, Hankinson SE. Association between plasma prolactin concentrations and risk of breast cancer among predominately premenopausal women. Cancer Res. 2006;66(4):2476–2482. doi: 10.1158/0008-5472.CAN-05-3369. [DOI] [PubMed] [Google Scholar]
- 39.Tworoger SS, Heather Eliassen A, Missmer SA, Baer H, Rich-Edwards J, Michels KB, Barbieri RL, Dowsett M, Hankinson SE. Birthweight and body size throughout life in relation to sex hormones and prolactin concentrations in premenopausal women. Cancer Epidemiol Biomarkers Prev. 2006;15(12):2494–2501. doi: 10.1158/1055-9965.EPI-06-0671. [DOI] [PubMed] [Google Scholar]
- 40.van den Brandt PA, Spiegelman D, Yaun S-S, Adami H-O, Beeson L, Folsom AR, Fraser G, et al. Pooled analysis of prospective cohort studies on height, weight, and breast cancer risk. Am J Epidemiol. 2000;152(6):514–527. doi: 10.1093/aje/152.6.514. [DOI] [PubMed] [Google Scholar]
- 41.Xu X, Veenstra TD, Fox SD, Roman JM, Issaq HJ, Falk R, Saavedra JE, Keefer LK, Ziegler RG. Measuring fifteen endogenous estrogens simultaneously in human urine by high-performance liquid chromatography-mass spectrometry. Anal Chem. 2005;77(20):6646–6654. doi: 10.1021/ac050697c. [DOI] [PubMed] [Google Scholar]
- 42.Yager JD. Chapter 3: Endogenous estrogens as carcinogens through metabolic activation. JNCI Monogr. 2000;2000(27):67–73. doi: 10.1093/oxfordjournals.jncimonographs.a024245. [DOI] [PubMed] [Google Scholar]
- 43.Yager JD, Davidson NE. Estrogen carcinogenesis in breast cancer. N Engl J Med. 2006;354(3):270–282. doi: 10.1056/NEJMra050776. [DOI] [PubMed] [Google Scholar]
- 44.Zeleniuch-Jacquotte A, Shore RE, Koenig KL, Akhmedkhanov A, Afanasyeva Y, Kato I, Kim MY, Rinaldi S, Kaaks R, Toniolo P. Postmenopausal levels of oestrogen, androgen, and SHBG and breast cancer: long-term results of a prospective study. Br J Cancer. 2004;90(1):153–159. doi: 10.1038/sj.bjc.6601517. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Zhu BT, Conney AH. Functional role of estrogen metabolism in target cells: review and perspectives. Carcinogenesis. 1998;19(1):1–27. doi: 10.1093/carcin/19.1.1. [DOI] [PubMed] [Google Scholar]
- 46.Ziegler RG. Anthropometry and breast cancer. J Nutr. 1997;127(5):924S–928S. doi: 10.1093/jn/127.5.924S. [DOI] [PubMed] [Google Scholar]
- 47.Zumoff B. Relationship of obesity to blood estrogens. Cancer Res. 1982;42(8 Suppl):3289s–3294s. [PubMed] [Google Scholar]