A Liquid Chromatography-Mass Spectrometry Method for the Simultaneous Measurement of Fifteen Urinary Estrogens and Estrogen Metabolites: Assay Reproducibility and Inter-individual Variability

Abstract

Background

Accurate, reproducible, and sensitive measurements of endogenous estrogen exposure and individual patterns of estrogen metabolism are needed for etiologic studies of breast cancer. We have developed a high performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to quantitate simultaneously 15 urinary estrogens and estrogen metabolites (EM): estrone (E₁); estradiol (E₂); three catechol estrogens; five estrogens in the 16α pathway, including estriol (E₃); and five methoxy estrogens.

Methods

Overnight urines were obtained from 45 participants. For the reproducibility study, two blinded, randomized aliquots from 5 follicular and 5 luteal premenopausal women, 5 naturally postmenopausal women, and 5 men were assayed in each of four batches. Assay coefficients of variation (CVs) and intraclass correlation coefficients (ICCs) were calculated with analysis of variance models. Data from the additional 25 participants were added to compare EM levels by menstrual/sex group and assess inter-individual variability.

Results

For each EM, overall CVs were ≤10%. ICCs for each menstrual/sex group were generally ≥98%. Although geometric mean EM concentrations differed among the four groups, rankings were similar, with E₃, 2-hydroxyestrone, E₁, E₂, and 16-ketoestradiol accounting for 60–75% of total urinary EM. Within each group, inter-individual differences in absolute concentrations were consistently high; the range was 10–100 fold for nearly all EM.

Conclusion

Our LC-MS/MS method for measuring 15 urinary EM is highly reproducible, and the range of EM concentrations in each menstrual/sex group is quite large relative to assay variability. Whether these patterns persist in blood and target tissues awaits further development and application of this method.

Introduction

The link between elevated endogenous estrogen levels and postmenopausal breast cancer is well established, with substantial evidence accruing from prospective studies of both circulating and urinary estrogens (1–4). However, it has not been possible to determine which of the estrogens commonly measured is most predictive of risk. Indeed, the precise mechanism of estrogen-related breast carcinogenesis, including the contribution of individual patterns of estrogen metabolism, has yet to be fully elucidated. The prevailing hypotheses suggest that specific estrogens can not only stimulate mitogenic activity, inhibit apoptosis, and promote tissue growth but also be metabolized into genotoxic and mutagenic forms that may directly damage DNA (5).

Estrogen metabolism occurs primarily in the liver along an oxidative pathway although enzymes involved in hormone metabolism are also expressed and functional in estrogen target tissues, such as the breast (5). Hydroxylation of estrone (E₁) and estradiol (E₂) is catalyzed on either the A-ring or D-ring by various cytochrome P450 enzyme isoforms and results in the formation of several hydroxy and keto metabolites. Hydroxylation on the A-ring is predominately at the C2 position, which produces 2-hydroxyestrone (2-OHE₁) and 2-hydroxyestradiol (2-OHE₂), and, to a lesser extent, at the C4 position, which produces 4-hydroxyestrone (4-OHE₁) and 4-hydroxyestradiol (4-OHE₂) (6). These four estrogen metabolites are catechol estrogens, with adjacent hydroxyl groups on the aromatic A-ring. The 2- and 4-hydroxy derivatives are further converted by catechol-O-methyltransferase (COMT) to 2-, 3- and 4-methoxy estrogens, including 2-methoxyestrone (2-MeOE₁), 2-methoxyestradiol (2-MeOE₂), 2-hydroxyestrone-3-methyl ether (3-MeOE₁), 4-methoxyestrone (4-MeOE₁) and 4-methoxyestradiol (4-MeOE₂) (7). Hydroxylation at the 16α position of the D-ring produces 16α-hydroxyestrone (16α-OHE₁), which can be further metabolized to estriol (E₃), 17-epiestriol 17-epiE₃), 16-ketoestradiol 16-ketoE₂), and 16-epiestriol 16-epiE₃) (8). Following conjugation with sulfate, glucuronic acid or glutathione, estrogen metabolites are eliminated by excretion in the urine and/or feces. Evidence is accumulating that substantial differences exist in the genotoxic, mutagenic, and proliferative activities of the individual estrogens and estrogen metabolites (EM) and that these differences may play a role in breast cancer etiology (5, 8–13). Thus, the measurement of a wide spectrum of EM is needed to further our understanding of breast carcinogenesis.

Most studies that have assessed the role of urinary estrogens in breast cancer etiology in human populations have used direct or indirect radioimmunoassays (RIA) or enzyme immunoassays (EIA) to measure a limited number of EM (10). Direct assays can be conducted with relative ease and at low cost; however, since each analyte must be assayed separately, at least moderate quantities of biologic specimen are required. Moreover, concerns about the specificity, accuracy, reproducibility, and sensitivity of the commercial kits persist (14). Indirect assays, which incorporate extraction and chromatography prior to RIA, are more specific and accurate, but also more costly, time-consuming, and require more biologic sample (14). Unlike these assay methods, mass spectrometry (MS) methods have the potential to measure a spectrum of estrogen metabolites at once, using a single sample (15). The stable isotope dilution gas chromatography/mass spectrometry (GC/MS) method that has been considered the gold standard for steroid hormone measurement is reasonably accurate, specific and sensitive; however sample preparation is complicated and laborious (16).

To facilitate the study of the role of estrogen metabolism in large epidemiologic studies of hormonal carcinogenesis, accurate, precise, sensitive, robust, and relatively simple laboratory methods that require low volumes of biologic samples are needed. We have developed a stable isotope dilution high performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) method that requires only 0.5 mL of urine and a simple sample preparation, consisting of hydrolysis, extraction, and derivatization, yet is capable of measuring simultaneously at least 15 EM (17,18). In this report, we evaluated laboratory variability for our assay based on a formal reproducibility study in which blinded, randomized urine samples from premenopausal women in the follicular and luteal phase, postmenopausal women, and men, were assayed over several weeks. We also assessed the inter-individual variability of EM levels for each menstrual/sex group.

Study Design and Methods

Study Population and Sample Collection

A total of 45 subjects provided overnight urines for this study, including 10 men aged 21–65, 20 premenopausal women aged 21–45, and 15 naturally postmenopausal women aged 50–65. Since the purpose of this study was to assess the performance of the assay method, we did not select participants based on characteristics suspected of modifying EM profiles, such as age, race, medication use or anthropometry. However, subjects reporting current use of hormone replacement therapy, oral contraceptives or other hormone supplements were ineligible. Subjects were instructed to collect all urine from the overnight period, including the first morning void. For the 20 premenopausal women, urines were obtained as follows: 10 women collected urine during the mid-luteal phase, between days 19 and 23 of the current menstrual cycle, and another 10 women collected urine during the follicular phase, between days 1 and 10 of the menstrual cycle. Urine was collected in a half-gallon container with a teaspoon of L-ascorbic acid as a preservative and kept in ice or refrigerated until the following day when urines were decanted, aliquoted and stored at −70°C.

Study Design

To establish the range of values and optimize the assay technique, the laboratory initially measured EM in urines from 25 of the subjects, including 10 premenopausal (5 luteal, 5 follicular) women, 10 postmenopausal women, and 5 men. Samples were measured in 4 batches, with each batch containing duplicate urine aliquots from each of the 25 subjects. For this exploratory phase, the laboratory was aware of the sex and menstrual status of the participant that provided the sample. Following this, the reproducibility of the method was evaluated using urines from the remaining 20 subjects (5 follicular, 5 luteal and 5 postmenopausal women, and 5 men). For this component of the study, the laboratory received 4 batches of urines at one time, each containing 2 aliquots per subject, and was instructed to assay one batch at the start of each of 4 consecutive weeks. The 40 samples in each batch were placed randomly, and the laboratory was unaware of whether a sample came from a premenopausal or postmenopausal woman or a man. Samples were stored at −80°C until assayed.

A total of 8 measurements were obtained for each subject in both the initial optimization effort and the reproducibility study. All steps of the assay procedure, including hydrolysis, extraction, derivatization, and LC-MS/MS, were performed separately on each aliquot.

Laboratory Methods

Details of our analytical method for urinary EM, which includes hydrolysis, extraction, derivatization, and LC-MS/MS with stable isotope-labeled internal standards, have been published elsewhere (17, 18). A summary of the laboratory method is presented here. Fifteen estrogens and estrogen metabolites (EM), including E₁, E₂, E₃, 2-OHE₁, 2-MeOE₁, 2-OHE₂, 2-MeOE₂, 3-MeOE₁, 4-OHE₁, 4-MeOE₁, 4-MeOE₂, 16α-OHE₁, 17-epiE₃, 16-ketoE₂, and 16-epiE₃, were obtained from Steraloids, Inc. (Newport, RI). Four deuterium-labeled estrogens and estrogen metabolites (d-EM), including estradiol-2,4,16,16-d₄ (d₄-E₂), estriol-2,4,17-d₃ (d₃-E₃), 2-hydroxyestradiol-1,4,16,16,17-d₅ (d₅-2-OHE₂), and 2-methoxyestradiol-1,4,16,16,17-d₅ (d₅-2-MeOE₂), were purchased from C/D/N Isotopes, Inc. (Pointe-Claire, Quebec, Canada). A fifth d-EM, 16-epiestriol-2, 4,16-d₃ (d₃-16-epiE₃) was obtained from Medical Isotopes, Inc. (Pelham, NH). Charcoal-stripped human urine (Golden West Biologicals, Temecula, CA) that contained 0.1% (w/v) L-ascorbic acid and had no detectable level of any EM was used for preparation of calibration standards and quality control samples. For all the deuterated internal standards, the purity was greater than 98%.

Since endogenous estrogens and their metabolites are mostly present in urine as glucuronide and sulfate conjugates, an initial hydrolysis step that has been optimized for this purpose was included (16,19). To a 0.5 mL aliquot of urine, 20 µL of the d-EM internal standard solution (1.6 ng of each d-EM) was added, followed by 0.5 mL of freshly prepared enzymatic hydrolysis buffer containing 2.5 mg of L-ascorbic acid and 5 µL of β-glucuronidase/sulfatase from Helix pomatia (Type HP-2, ≥500 Sigma units β-glucuronidase and ≤37.5 units sulfatase activity, Sigma Chemical Co., St. Louis, MO) in 0.5 mL of 0.15 M sodium acetate buffer (pH 4.6). The sample was incubated for 20 hours at 37°C, and then extracted with 8 mL dichloromethane. After extraction, the aqueous layer was discarded and the organic solvent portion was transferred to a clean glass tube and evaporated to dryness at 60°C under a stream of nitrogen gas. Ascorbic acid had been added to the samples to prevent oxidation of individual EM. Levels of the calibration and quality control standards were relatively stable, which suggested degradation was minimal during sample preparation.

All EM and d-EM were quantitatively dansylated to improve their ionization efficiency, and thus the sensitivity of the assay. The dried sample residue was redissolved in 100 µL of 0.1 M sodium bicarbonate buffer (pH 9.0) and 100 µL of dansyl chloride solution (1 mg/mL in acetone), and incubated at 60°C for 5 min. A 20 µL sample (1/10 of final volume) was injected for LC-MS/MS analysis.

The LC-MS/MS analysis was performed using a ThermoFinnigan TSQ™ Quantum-AM triple quadrupole mass spectrometer equipped with an electrospray ionization source and coupled directly to a Surveyor HPLC system (ThermoFinnigan, San Jose, CA). Both the chromatography system and mass spectrometer were controlled using Xcalibur™ software (ThermoFinnigan). Reversed-phase LC was carried out on a 150 mm long×2.0 mm i.d. C₁₈ column packed with 4 µm Synergi Hydro-RP particles (Phenomenex, Torrance, CA) and maintained at 40°C. The mobile phase, operating at a flow rate of 200 µL/min, consisted of methanol as solvent A and 0.1% (v/v) formic acid in water as solvent B. A linear gradient changing A from 72% to 85% in 75 min was employed. After washing with 100% A for 13 min, the column was re-equilibrated with a mobile phase of 72% A for 12 min prior to the next injection. The general MS conditions were as follows: source: ESI; ion polarity: positive; spray voltage: 4,600 V; sheath and auxiliary gas: nitrogen; sheath gas pressure: 49 arbitrary units; auxiliary gas pressure: 23 arbitrary units; ion transfer capillary temperature: 350°C; scan type: selected reaction monitoring (SRM); collision gas: argon; collision gas pressure: 1.5 mTorr. The following MS parameters were used for all experiments: scan width: 0.7 u; scan time: 0.50 s; Q1 peak width: 0.70 u full width at half maximum (FWHM); Q3 peak width: 0.70 u FWHM.

Quantitation of each EM in urine was carried out using the Xcalibur™ Quan Browser (ThermoFinnigan). Calibration curves for the fifteen EM were constructed by plotting EM-dansyl/d-EM-dansyl peak area ratios obtained from calibration standards versus amounts of EM and fitting these data using linear regression with 1/X weighting. The amount of each EM in a urine sample was then interpolated using this linear function. Quality control samples at three concentrations (0.12, 0.96, and 6.4 ng of each EM/mL) were included in each batch of assays. The limit of quantitation is 2 pg on the column for each EM. The reported EM concentrations, in pg EM/mg creatinine, are for unconjugated forms of the EM. No corrections were made for molecular weight differences between the conjugated and unconjugated forms.

Since deuteriums at the α-position to the carbonyl group of ketolic estrogens are especially susceptible to exchange loss, only deuterium-labeled standards that exhibited no significant exchange loss under the assay conditions were employed. Based on structural similarity and retention times, d₄-E₂ was used as the internal standard for E₂ and E₁; d₃-E₃ for E₃, 16-ketoE₂, and 16α-OHE₁; d₃-16-epiE₃ for 16-epiE₃ and 17-epiE₃; d₅-2-MeOE₂ for 2-MeOE₂, 4-MeOE₂, 2-MeOE₁, 4-MeOE₁, and 3-MeOE₁; d₅-2-OHE₂ for 2-OHE₂, 2-OHE₁, and 4-OHE₁.

Urinary creatinine was measured with the Beckman LX20 analyzer (Brea CA), using a technique based on the Jaffe reaction (20). Laboratory CVs were 2% for creatinine concentrations of 70 mg/dL and 155 mg/dL.

Statistical Methods and Analysis

Inter-Individual Variability in Urinary EM

Urinary EM levels from all 45 participants were used to examine inter-individual differences in metabolite concentrations. In the initial phase of this study, the laboratory was provided samples from the first 25 subjects to optimize the method and was not blinded as to the participant’s sex and menstrual group status. Urines from these 25 subjects were assayed 8 times, with duplicate aliquots measured in each of 4 batches. These results were then combined with those from the 20 subjects evaluated in the reproducibility study described below, where blinded urine samples were also measured 8 times, twice in each of four batches. Data were analyzed on the logarithmic scale. For each EM, the geometric mean (expressed as pg EM/mg creatinine) and the arithmetic mean for percent of total EM were calculated for each menstrual/sex group. Rank order statistics and box plots were used to compare the distributions of EM concentrations among the menstrual/sex groups.

Reproducibility Study

The reproducibility study included only the 20 subjects whose samples were randomized and identifiers removed before shipment to the laboratory. A nested, within-person analysis of variance model (ANOVA) was used to assess assay reproducibility over the 4-week period (21). Data were analyzed on the logarithmic scale. Estimates of the variability among subjects (σ²_a), of assay variability among batches for a given subject (σ²_b), and of assay variability associated with different aliquots in the same batch for the same subject (σ²) were obtained from the SAS procedure Proc VARCOMP (22). With y_ijk denoting the mean of the natural logarithm of assay measurements of duplicate aliquots for subject i=1,2,3…20 at week j(i)=1,2,3,4 on aliquot k(ij)=1,2, the model is y_ijk= Φ + a_i + b_j(i)+ ε_k(ij), where a_i, b_j(i) and ε_k(ij) are independent variables, each with a mean of zero and respective variances σ²_a, σ²_b, and σ². From the variance estimates, we computed estimates of the total, intrabatch, and interbatch coefficients of variation (CV) of the assay. We also computed the intraclass correlation coefficients [ICC = (σ²_a/(σ²_a + σ²_b + σ²)] for each menstrual/sex group.

Results

Inter-individual Variability

For each urinary EM, geometric mean concentrations (pg EM/mg creatinine), mean percent of total urinary EM, and rank order by concentration are presented in Table 1 for follicular phase women, luteal phase women, postmenopausal women, and men. Results from all 45 subjects are included in this table. In all groups, the ranking of EM concentrations was similar. Levels of E₃, 2-OHE₁, E₁, E₂ and 16-ketoE₂ were the highest, accounting for 60–75% of the total urinary EM. E₃ was the predominant urinary EM in all groups except follicular phase women where 2-OHE₁ was highest. The catechol estrogens comprised approximately 20% of the total, with concentrations of 4-OHE_1, and 2-OHE₂ being much lower than that of 2-OHE₁. With the exception of 2-MeOE₁, concentrations of the methoxy estrogens tended to be very low for all groups, comprising less than 10% of total urinary EM. Levels of 4-MeOE₂ were below the detection limit for three males in the study, and measured in some, but not all, batches for one postmenopausal woman. The total concentration of urinary EM was similar for follicular and luteal phase women and, of note, comparable for men and postmenopausal women.

Table 1.

Geometric Mean Concentration^*, Percent of Total EM, and Rank Order of Fifteen Urinary Estrogens and Estrogen Metabolites (EM) By Menstrual/Sex Group

	Premenopausal Women						Postmenopausal Women			Men
	Follicular Phase			Luteal Phase
	(n = 10)			(n = 10)			(n = 15)			(n = 10)
EM	Mean	%	Rank	Mean	%	Rank	Mean	%	Rank	Mean	%	Rank
E1	7064	15.1	3	7694	19.7	2	1507	16.3	3	1753	16.3	2
E2	3623	7.7	4	5234	14.9	4	758	13.4	5	1028	14.9	4
Catechol estrogens
2-OHE1	7683	16.4	1	6482	12.5	3	1673	14.8	2	1539	13.1	3
2-OHE2	1264	2.7	10	1294	2.5	10	434	3.8	8	356	3.0	7
4-OHE1	1579	3.4	9	2002	3.9	7	548	4.9	6	264	2.2	9
16α pathway
16α-OHE1	2115	4.5	7	1971	3.8	8	290	2.6	10	257	2.2	9
17-epiE3	401	0.9	11	285	0.6	13	135	1.2	14	104	0.9	12
E3	7319	15.6	2	10177	19.7	1	1844	16.3	1	2675	22.7	1
16-ketoE2	3002	6.4	5	3628	7.0	5	769	6.8	4	917	7.8	5
16-epiE3	2310	4.9	6	1940	3.7	9	416	3.7	9	756	6.4	6
Methoxy estrogens
2-MeOE1	1995	4.3	8	2349	4.5	6	548	4.9	6	311	2.6	8
2-MeOE2	293	0.6	12	334	0.6	11	138	1.2	13	30	0.3	15
3-MeOE1	213	0.5	14	198	0.4	14	165	1.5	12	77	0.7	13
4-MeOE1	292	0.6	13	292	0.6	12	182	1.6	11	107	0.9	11
4-MeOE2^	94	0.2	15	81	0.2	15	66	0.6	15	41	0.4	14
Total EM	46,822			51,737			11,283			11,781

^*mean concentrations expressed as pg EM/mg creatinine

^{^}4-MeOE₂ concentrations were below the detection limit for 3 men.

The ranges in absolute urinary EM concentrations (pg EM/mg creatinine), according to menstrual/sex group, are shown by box plots in Figure 1, with estrone and estradiol in Figure 1a, the catechol estrogens in Figure 1b, the estrogens in the 16α pathway in Figure 1c, and the methoxy estrogens in Figure 1d. As these plots demonstrate, inter-individual differences in each menstrual/sex group were very large, with the highest concentration for each EM at least five times the lowest. For nearly all the EM, 10 to 100-fold differences between individuals were observed. The exceptions were 4-MeOE₁ in follicular women; 16-ketoE₂ and 4-MeOE₁ in luteal women; 2-OHE₁, 2-OHE₂, and 2-MeOE₁ in postmenopausal women; and E₁, E₂, 2-OHE₂, 4-OHE₁, 16-epiE₃ and 2-MeOE₁ in men, for which the ranges were less than 10-fold, and 16α-OHE₁ in follicular women, 4-OHE₁ in luteal women, 16α-OHE₁ and 2-MeOE₂ in postmenopausal women, and 17-epiE₃ in men, where the differences between participants were more than 100-fold.

Figure 1.

Box plots of concentrations for urinary estrogens and estrogen metabolites (EM) in urine (y axis) for 10 premenopausal follicular phase women, 10 premenopausal luteal phase women, 15 postmenopausal women, and 10 men (x axis). Figure 1a includes estrone (E₁) and estradiol (E₂); Figure 1b, the catechol estrogens: 2-hydroxyestrone (2-OHE₁), 2-hydroxyestradiol (2-OHE₂), and 4-hydroxyestrone (4-OHE₁); Figure 1c, the 16α pathway estrogens: 16α-hydroxyestrone (16α-OHE₁), 17-epiestriol 17-epiE₃), estriol (E3), 16-ketoestradiol 16-ketoE₂) and 16-epiestriol (16epiE₃); Figure 1d, the methoxy estrogens: 2-methoxyestrone (2-MeOE₁), 2-methoxyestradiol (2-MeOE₂), 2-hydroxyestrone-3-methyl ether (3-MeOE₁), 4-methoxyestrone (4-MeOE₁), and 4-methyoxyestradiol (4-MeOE₂). The y-axis shows pg EM/mg creatinine on a logarithmic scale. The horizontal line within the box represents the median value of the distribution; the top and bottom of the box represent, respectively, the 75^th and 25^th percentiles of the distribution. Outliers are represented as stars [(>1.5 but ≤3 times the interquartile range (IQR) and open circles (> 3 times the IQR).

In contrast, inter-individual differences in relative urinary EM concentrations, expressed as percent of total urinary EM, were not as large. For the majority of the EM, the difference between the highest and lowest values in each menstrual/sex group was less than 10-fold, and for E₁ and E_2, in particular, the range in percent EM was less than 6-fold (data not shown).

Assay Reproducibility

The design of the reproducibility component of this study is presented in Figure 2. The duplicate readings for 16α-OHE₁ in each of 4 batches are shown for 5 follicular phase women in (a); 5 luteal phase women in (b); 5 postmenopausal women in (c); and 5 males in (d). Data are plotted on a logarithmic scale. Each distinct symbol in each plot corresponds to a different subject in that menstrual/sex group. Where only one symbol per subject is shown, the values for the duplicate readings in that batch overlapped. These plots depict several sources of variability in urinary hormones assessed in this study, including differences among subjects, measurement variability over batches for a given subject, and variability among duplicate aliquots in a given batch. Note that this does not measure the variability over time for a given subject; for this, we would need different urine samples collected at different times from each subject. For this EM and all the EM studied (see additional plots in Appendix, Supplemental Figures 1–14), there was little difficulty in distinguishing one subject from another. In men, for example, where levels of 16α-OHE₁ were particularly low, the assay successfully separated the readings for each subject. Furthermore, even at these low concentrations, measurements varied little from one batch to the next, or between duplicate aliquots in the same batch.

Figure 2.

Results of the assay reproducibility study for 16α-hydroxyestrone (16α-OHE₁). The concentration of 16α-OHE₁ (pg metabolite / ml urine) is plotted on a logarithmic scale on the y axis, and the x axis identifies the four batches. Duplicate readings are shown in each batch for 5 premenopausal follicular women (Figure 2a); 5 premenopausal luteal women (Figure 2b), 5 postmenopausal women (Figure 2c), and 5 males (Figure 2d). Each symbol in each of the plots corresponds to a different subject in that menstrual/sex group. If the values for the duplicate readings for an individual in a batch overlapped, only one symbol is shown. Similar plots for the other 14 estrogens and estrogen metabolites (EM) are presented in the online Appendix, Figures 3–16.

As these plots suggest, laboratory reproducibility for each EM across the menstrual/sex groups was very similar; thus we present reproducibility results for the entire study group of 20 subjects combined (Table 2). The overall laboratory CVs were 10% or lower for all urinary EM and 5% or lower for 11 of the 15. The within and between batch CVs were consistently <3% and <10%, respectively.

Table 2.

Liquid Chromatography-Tandem Mass Spectrometry Assay Reproducibility

	Coefficient of Variation (%)			Intraclass Correlation Coefficient (%)
	Within Batch	Between Batch	Overall	Follicular	Luteal	Postmenopausal	Men
EM
E1	0.8	2.1	2.3	99.9	99.9	99.8	99.9
E2	0.9	1.9	2.1	98.6	99.9	99.8	99.9
Catechol estrogens
2-OHE1	1.0	3.0	3.1	99.9	99.9	98.4	99.8
2-OHE2	1.7	4.0	4.3	99.9	99.9	99.6	99.3
4-OHE1	2.0	5.9	6.2	99.9	99.9	94.8	98.8
16α pathway
16α-OHE1	1.8	3.6	4.0	99.9	99.9	99.0	99.9
17 -epiE3	2.9	9.9	10.3	99.9	99.9	87.0	99.2
E3	0.6	0.9	1.1	99.9	99.9	99.9	99.9
16-ketoE2	0.6	1.4	1.5	99.9	99.9	99.8	99.9
16 -epiE3	1.7	3.8	4.2	99.9	99.9	98.7	99.6
Methoxy estrogens
2-MeOE1	1.6	2.8	3.3	99.9	99.9	99.8	98.7
2-MeOE2	2.2	3.4	4.1	99.9	99.8	99.5	98.8
3-MeOE1	2.4	4.5	6.9	99.7	99.0	99.0	99.0
4-MeOE1	2.5	4.5	5.2	99.5	96.4	98.3	99.3
4-MeOE2	2.8	6.6	7.2	99.6	95.8	96.7	99.3

ICCs are also presented in Table 2. In light of the large differences in EM concentrations among the menstrual/sex groups, the ICCs were calculated separately for each of the four groups. With the exception of 17-epiE₃ in postmenopausal women, the ICCs were uniformly very high (>95%).

Discussion

To study the role of endogenous estrogens in carcinogenesis, including specific EM and individual patterns of estrogen metabolism, evaluating EM levels in urine may be advantageous because of the ease of sample collection, potentially higher participation rates, and the integration of exposure over time for hormones with pulsatile, circadian or menstrual cycle variability. In our study, laboratory results were highly reproducible, with overall CVs for each of the 15 EM ≤10%, and the majority being <5%. These findings compare favorably with the GC-MS method for measuring urinary EM and phytoestrogens developed by Adlercreutz et al (19), where intra- and inter-batch CVs for two known standards were 2–13% and 4–16%, respectively. Further, ICCs for all the 15 EM were very high, generally ≥ 98% in each menstrual/sex group. Although it may be argued that results from the small number of participants in this study may not adequately represent the underlying population values and provide imprecise estimates of the variance components used to calculate the relevant statistics, the consistency of the reproducibility and ICC findings across the menstrual/sex groups is remarkable.

Our LC-MS/MS method for measuring urinary EM is relatively rapid and robust so that it can be applied to the multiple samples collected in epidemiologic studies. Sample preparation for this method is comparatively easy and could be automated. Preparation entails hydrolysis of the conjugated EM with glucoronidase and sulfatase enzymes, extraction, and then dansylation of the unconjugated EM with established technology. LC-MS/MS is accomplished with commercially available LC and MS systems, and peaks corresponding to the EM of interest are interpreted with automated software. While the results are reviewed to ensure accuracy, most steps in the LC-MS/MS process are unattended. A total of 40 – 45 study samples, along with the necessary quality control and calibration curve standards, can be assayed per week. Although relatively time-consuming in comparison to measurement methods for single EM, our method does provide urinary hormone measurements for 15 analytes in a single run. Concerns have been raised regarding the high throughput capability of this method due to difficulties with sample preparation and the interpretation of MS peaks. Sample preparation for this method is relatively easy to perform, and can be automated using a liquid handling station. Preparation entails liquid extraction, followed by hydrolysis of the conjugated estrogens using glucoronidase and sulfatase enzymes. Dansylation of the estrogens is established technology, requiring sample incubation with dansyl chloride. The mass spectrometry (MS) step is accomplished using commercially available LC and MS systems, with interpretation of the peaks corresponding to the estrogen metabolites of interest using automated software. While the results are manually validated to ensure accuracy and high quality, most steps in the MS process are unattended. A total of 40 samples can be assayed per week. Although relatively time-consuming in comparison to other assay methods, to our knowledge, there is no comparable method available that provides urinary hormone measurements for 15 analytes in a single run. To date, we have completed hormone assays for two large epidemiologic studies, each containing several hundred samples.

Several caveats must be borne in mind when evaluating inter-individual differences in this study. First, of the 45 subjects studied, samples from the initial 25 were not blinded for the laboratory. While this has the potential of introducing bias, this is not likely in light of the very strong laboratory performance observed in the formal blinded reproducibility study. Second, the relatively small number of participants in each menstrual/sex group limits our ability to explore hormonal profiles with regards to demographic, clinical and anthropometric characteristics, and awaits hormone measurements in large population-based studies. Further, we did not attempt to evaluate the consistency of hormone measurements within subjects over time, which may be a source of considerable variability, particularly among pre-menopausal women. Thus, although not conclusive, we did find inter-individual differences in absolute urinary levels were quite high in all four menstrual/sex groups for each of the 15 EM, with values differing from 10 to 100-fold within each group. In both women and men, E_3, 2-OHE₁ and E₁ were the most abundant of the urinary estrogens, followed by E₂ and 16-ketoE₃. Except for 2-MeOE₁, levels of the methoxy estrogens were relatively low. The finding of relatively high levels of 2-MeOE₁ in urine is notable in light of the suggestion that 2-MeOE₁ and 2-MeOE₂ interconvert under physiologic conditions (23,24). 2-MeOE₂ shows promise as a potential anticancer agent, with in vitro and in vivo studies suggesting that it may inhibit cell proliferation, angiogenesis, and tumor growth (23,25,26).

The correlation of EM levels in various tissues is not known. Urinary EM levels reflect extensive hydroxylation, methylation, ketone formation, and conjugation in the liver and kidneys and may not be predictive of circulating or breast tissue levels. In addition, several estrogen metabolism enzymes are expressed and functional in estrogen target tissues (5). Considerable evidence demonstrates large inter-individual variation in the hepatic and extrahepatic expression of some cytochrome P450 (CYP) enzymes in the estrogen metabolic pathway, which is largely due to genetic and/or environmental factors. Gender differences for some liver CYP isoforms involved in estrogen metabolism have been documented in animal models (5), but studies of human liver microsomes have not found gender differences with regard to either the enzymatic activity of CYP isoforms with high estrogen metabolizing activity (27), or the estrogen metabolites formed (28,29). While not conclusive, our observation of similar patterns of estrogen metabolites for men and women supports these in vitro findings.

Both normal and neoplastic breast tissue produce the enzymes required for localized estrogen synthesis, oxidation, conjugation, and deconjugation (12,30,31), but how estrogen metabolism proceeds in normal and neoplastic tissue is unresolved. More detailed and accurate knowledge about EM patterns in breast tissue may suggest new approaches to the early detection and treatment of breast tumors. Further, although many accepted hormone-related breast cancer risk factors, such as ages at menarche, first birth, and menopause are not easily modifiable, estrogen metabolism can be altered by diet, smoking, exercise, coffee consumption, alcohol intake and chemopreventive and other drugs (32–35). Clarifying the role of individual compounds as well as patterns of estrogen metabolism in breast carcinogenesis may, therefore, be relevant to prevention strategies. To these ends, efforts to optimize mass spectrometry methods such as ours for the measurement of individual EM in blood and tumor tissue are needed.