Estrogen Metabolite Ratios: Time for Us to Let Go
by Jacob Schor, ND, FABNO (January 2013)
Schor's Rebuttal to This Article
Response to Wright and Klug (May 2013)
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Early well-designed studies with the EIA for urinary estrogen metabolites of women with histologically confirmed breast cancer found the anticipated metabolic shift resulting in significantly reduced EMR in cancer. For example, in a study of 58 predominantly postmenopausal women with newly diagnosed cancer, compared with matched negative controls, Ho et al. reported a 3-fold reduction of the EMR in cases vs. controls (EMR = 0.7 versus 2.2 ). The hazard ratio; that is, the relative risk of having breast cancer for women with higher EMR, was 0.1 (95% confidence interval [CI] 2.6–33).6 A study of breast cancer in 64 predominantly postmenopausal women of mixed ethnicity as reported by Kabat et al. found that the EMR was significantly lower in cases than controls (1.41 vs. 1.81, p < 0.05). Adjusted hazard ratio for the intermediate and lowest tertiles of the EMR vs. controls was 9.73 and 33, respectively (95% CI 3.36–319). The lower EMR in postmenopausal cases in this study was due to significantly higher urinary levels of 16aOHE1.7 Note that in these studies, the "normal" controls had been selected and scrutinized by the same histological procedures used in the primary diagnosis of breast cancer cases. These studies also reported that the EMR of black participants was significantly lower than in white and Hispanic participants. A study by Coker et al. highlighted the role of ethnicity in the urinary EMR in women with and without breast cancer. African American women were found to have very significantly reduced urinary 2OHE1 compared with Caucasian women (p < 0.001). By contrast, when statistical analysis was adjusted for the waist-to-hip ratio or body mass index (BMI) in this study, differences were no longer significant.8 BMI and waist-to hip ratio may be considered to be a lifestyle risk factor. A recent study of the EMR in women at high risk for breast cancer found that the EMR (2-hydroxyestrone/16-alpha-hydroxyestrone) in women at high risk for breast cancer was similar to that observed in the breast cancer group (1.76 ± 2.33 versus 1.29 ± 0.80) and lower than in controls (2.47 ± 1.14; p = 0.00).9 Risk factors in these women included genetic risk factors and presence of benign breast disease including first-degree family history, lobular carcinoma in situ, ductal carcinoma in situ, fibrocystic breast disease, mutations in either BRCA1 or BRCA2, and Ashkenazi Jewish descent.
Numerous research and human clinical studies with the EIA for urinary metabolites have demonstrated reduction in the EMR in case-control studies of other types of cancer including cancer of the thyroid, head and neck, and prostate. Moreover, dietary factors such as consumption of cruciferous vegetables, soy, and flaxseed were shown to shift metabolism toward increased 2-hydroxylation of estrogens and increase the EMR.10,11 Indole-3-carbinol (I3C) and its derivative diindolylmethane (DIM), compounds found in cruciferous vegetables, were found to be very potent inducers of 2-hydroxylation.11
The balance of estrogen metabolism in breast cancer, and perhaps other cancers then, seems to be shifted toward the more potent estrogens that drive increased cellular proliferation. Would an opposite extreme shift in the EMR away from 16a-hydroxyestrone toward the less potent 2-hydroxylated estrogen metabolites be associated with estrogen deficient diseases? Indeed, in several studies that included measurement of urinary 2OHE1, 2 methoxyE1, and 16aOHE1 by EIA, a higher than average urinary 2OHE1, 2MeoE1, and EMR correlated positively with significantly higher rate of bone loss as determined by bone scans, most strongly in trabecular bone.12 The increase in 2-methoxyestrone metabolite was found to correlate most strongly with the rate of bone loss.
These very positive findings led researchers to suggest that interventions to induce 2-hydroxylation as by consumption of natural dietary constituents such as I3C or DIM might alter the course of estrogen dependent disease. Recurrent respiratory papillomatosis (RRP) is a human papilloma virus (HPV)-associated disease characterized by papillomatous growths of the aerodigestive mucosa. Frequent surgical removal is usually required to maintain an adequate airway. A trial with I3C (200 mg per diem) was done in children with RRP following surgical clearing of papillomas. The efficacy of the treatment was monitored by measurement of the EMR. Two-thirds of the children showed an increase in the EMR, which corresponded to the absence of papilloma growth.13 Follow-up studies illustrated that the extent of increase in the EMR correlated with the disease-free interval. DIM was found to be more effective than I3C in increasing EMR in RRP.11
As cervical intraepithelial neoplasia (CIN) is also associated with the HPV virus, intervention trials were done with I3C. In a double-blind study, I3C or placebo was administered. None (0 of 10) of the patients in the placebo group had regression of CIN. In contrast, 4 of 8 patients in the 200 mg/day arm and 4 of 9 patients in the 400 mg/day arm had complete regression based on their 12-week biopsy. The EMR changed in a dose-dependent fashion.14 More recent larger single dose intervention studies with DIM (150–200 mg per diem) have largely confirmed these initial findings, in CIN grade 2 or 3 lesions, but the EMR had not been incorporated in these recent studies.
The preponderance of the evidence supports the EMR hypothesis. Why, then, do the results of recent large studies done by epidemiologists, some noted by Dr. Schor, not support the EMR hypothesis? Unfortunately, while many epidemiologists do not understand the biology of breast cancer, the chemistry of estrogen metabolism, and the EMR hypothesis, they still design studies to test it. Most significantly, the cohorts used in their studies to test the EMR hypothesis were originally gathered to study entirely different questions and test different hypotheses. Therefore, participant inclusion and exclusion criteria for these cohorts are generally not appropriate to test the EMR hypothesis. Rather than simply designing a study to correlate presence or absence of breast cancer with the EMR, epidemiologists take a different approach. Epidemiologists seek to obtain the largest possible number of study participants so as to gain what is called statistical "power." This, unfortunately, often limits participant inclusion and exclusion criteria. Epidemiologists attempt to compensate for the latter by statistically sorting out the contribution of many variables in the study (e.g., age, BMI) to the variation in the dependent variable (EMR). Mistakes in assignment of these variables, missing data, and other factors can destroy simple correlations seen in simpler studies. A careful review of participants' records, however, might be able to find a subcohort more appropriate for hypothesis testing by simpler analysis.
The study of estrogen metabolism reported by Ursin et al. is particularly informative in this regard. Using the urinary estrogen metabolite EIA test, these investigators reported no difference in the EMR between breast cancer cases and controls.15 Examination of their study's inclusion and exclusion criteria, however, revealed that the women in the breast cancer category had been recruited for a previous study, but for the study to test the EMR hypothesis had provided urine samples again seven years after being diagnosed with breast cancer! The authors excluded patients with advanced breast cancer at diagnosis (stages III and IV) due to the very significant mortality in this group after the original study. The study by Kabat et al. had earlier reported that women with advanced stages of breast cancer have greater reduction in EMR than women with the early stage breast cancer.7 This biased study is, amazingly, still cited and included in meta-analyses by epidemiologists.
In the light of another study, the results of this apparently negative study in fact provide strong support for the EMR hypothesis. The Isle of Guernsey III study was a population-based survey with extended follow-up of 5104 women aged 35-plus years living on Guernsey (Channel Islands) entering the study between 1977 and 1985. During extended follow-up, 142 women were diagnosed with cancer, and 102 met criteria for inclusion for analysis of estrogen metabolism. Sixty of the cases were premenopausal women, 42 were postmenopausal women. Estrogen metabolism was determined by the urinary EIA in samples taken at time of entrance into the study. Follow-up data on cases provided mortality data for the 102 women with breast cancer. A Cox proportional hazards model was used to adjust for age at diagnosis and size of the tumor. Surprisingly, survival curves were distinctly different for women with EMR above as compared with those with EMR below 2.0 at entrance to the study. Combined pre- and postmenopausal breast cancer cases with urinary 2OHE1 baseline values above the median value experienced one-half the mortality rate from cancer during follow-up. The unadjusted hazard ratio was 0.45–0.52, p < 0.05.16 Using the EMR, a better survival was experienced by premenopausal women with an EMR above the median with an adjusted hazard ratio of 0.23 (95% CI 0.06–0.86, p < 0.03).17 Therefore, using long-term breast cancer cases as done by Ursin et al. in their study noted above, biased the EMR of cases toward the higher values of EMR in controls, resulting in nonsignificant differences between cases and controls. The results of the Guernsey III study, therefore, strongly suggest that the EMR and relative levels of 2OHE in breast cancer may predict mortality and, by inference, that inducing higher 2OHE might decrease mortality in women with breast cancer. Nearly all of the large epidemiology studies done to test the EMR hypothesis have used cohorts retrospectively with exclusion/inclusion criteria inappropriate testing the EMR hypothesis. In defense of epidemiologists, sample accruement, storage, record-keeping, and so on are very expensive and time-consuming for large numbers of samples. Thus, they are limited to what retrospective materials are most readily and affordably available to them. But more importantly, the analytical techniques used in some of these studies are problematic.
Many studies that have sought to study estrogen metabolism have been done using invalid analytical methods. The importance of this point may be illustrated by the conflicting evidence for the effect of flaxseed on the EMR. Dr. Schor cited the study of Sturgeon et al. wherein supplementation of 43 postmenopausal women with an escalating dose of ground flaxseed from 7.5 g/day for 6 weeks to 15 g/day for an additional 6 weeks found that mean urinary 16aOHE1 as measured by a GCMS method was higher at the end of the study and the EMR was lower (p = 0.02), a finding apparently in conflict with the EMR hypothesis.18 By contrast, a similar study of 28 postmenopausal women in three 7-week feeding periods by a randomized crossover design gave an opposite result. With diets supplemented with flaxseed (0, 5, 10 g/day), and urinary metabolites concentrations measured by the direct EIA, researchers found that flaxseed supplementation significantly (p < 0.0005) increased urinary 2OHE1, and significantly (p < 0.05) increased EMR in a linear, dose-dependent fashion.10 Although the GCMS method used in the study of Sturgeon et al. was modified from that of Adlercreutz for measurement of estrogen metabolites, several modifications to increase sample throughput and to generalize the prior method to measurement of 27 dietary components in urine in the same GCMS run, likely compromised accurate detection of estrogens.3 Other indirect chromatographic-mass spectroscopic methods are inaccurate due to inadequate deconjugation procedures and loss of metabolites, especially the unstable 2-and 16a-hydroxyestrone due to use of certain organic chemicals and extensive chromatographic procedures. For example, a frequently cited procedure used in studies of estrogen metabolism attempts to enzymatically deconjugate estrogen metabolites in urine without isolation from factors in urine that are known to interfere with the glucuronidase and arylsulphatases enzymes from Helix pomatia extracts.19 This interference is well known to Adlercreutz and others steroid chemists. Further, this method exposes metabolites to alkaline pH at elevated temperatures, a condition known to degrade 16aOHE1.3 The amounts of urinary estrogen metabolites found by these complex indirect methods are lower and their respective EMRs are significantly higher than that found by the original GCMS method of Adlercreutz and the validated direct EIA method. In addition, there is little agreement between research groups that use these complicated methods to measure estrogen metabolites. Likewise, the conflicting research results from the influence of soy supplementation on the EMR are likely due to differences in test methodologies. Differences in the amount of soy, and the duration of the study, have also led to confusion. A dose-response study using purified compounds derived from soy, or at least a standardized fermented soy extract, would help clarify the issue.
In conclusion, we have shown that the preponderance of evidence from the study of estrogen metabolites in tissues and urine supports the EMR hypothesis, and that the EMR can be modulated in a predictable manner through dietary changes and use of certain nutraceuticals. Shifts in estrogen metabolism have been shown to improve disease status in several studies. Conflicting results from large retrospective epidemiology studies are perhaps an expected outcome due to their varied inclusion and exclusion criteria. Many of these studies, moreover, utilized problematic, invalid analytical methods. Smaller studies done with samples collected under tight inclusion/exclusion criteria in recognition of the many factors that could influence estrogen metabolism have supported the EMR concept. We believe that future longitudinal studies are needed to determine whether appropriate shifts in estrogen metabolism result in persistent improvements in disease status and improved health. Women with very low EMR that cannot be induced to increase 2-hydroxylation appear to be at particularly high risk for development of breast cancer and other estrogen-driven diseases. Women in this category need to be the focus for intervention studies. Increasing lean body mass is currently the best known intervention that can increase survival in women with breast cancer. Since increased body mass correlates positively with increased EMR, might the EMR be used to monitor efficacy of this type of therapy?20 Studies to link breast cancer occurrence directly with estrogen metabolism are far more difficult to contemplate. Observations have been made in humans that suggest that childhood exposure to genistein in soy or to some other bioactive food components reduces later breast cancer risk, although they may have no effect if consumed during adulthood. Could appropriate shifting of estrogen metabolism in utero through maternal shifts in EMR, or before or during puberty lead, to reduced incidence of breast cancer? In light of past studies, and with hope in future answers to the many questions before us, I am convinced that it is not time to let go of the EMR hypothesis.
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