Neighborhood Recreation Facilities and Facility Membership Are Jointly Associated with Objectively Measured Physical Activity

Efforts to increase physical activity have traditionally included either individual-level interventions (e.g., educational campaigns) or neighborhood-level interventions (e.g., additional recreational facilities). Little work has addressed the interaction between spatial proximity and individual characteristics related to facility use. We aimed to better understand the synergistic impact of both physical activity environments and recreational facility membership on objectively measured physical activity. Using the New York City Physical Activity and Transit (PAT) survey (n = 644), we evaluated associations between counts of commercial physical activity facilities within 1 km of participants' home addresses with both facility membership and accelerometry-measured physical activity. Individuals living near more facilities were more likely to report membership (adjusted odds ratio for top versus bottom quartile of facility count: 3.77 (95% CI 1.54-9.20). Additionally, while amount of facilities within a neighborhood was associated with more physical activity, this association was stronger for individuals reporting gym membership. Interventions aiming to increase physical activity should consider both neighborhood amenities and potential barriers, including the financial and social barriers of membership. Evaluation of neighborhood opportunities must expand beyond physical presence to consider multiple dimensions of accessibility.

A Local View of Informal Urban Environments: a Mobile Phone-Based Neighborhood Audit of Street-Level Factors in a Brazilian Informal Community

Street-level environment characteristics influence the health behaviors and safety of urban residents, and may particularly threaten health within informal communities. However, available data on how such characteristics vary within and among informal communities is limited. We sought to adapt street audit strategies designed to characterize the physical environment for use in a large informal community, Rio das Pedras (RdP) located in Rio de Janeiro, Brazil. A smartphone-based systematic observation protocol was used to gather street-level information for a high-density convenience sample of street segments (N = 630, estimated as 86% of all street segments in the community). We adapted items related to physical disorder and physical deterioration. Measures selected to illustrate the approach include the presence of the following: (1) low-hanging or tangled wires, (2) litter, (3) structural evidence of sinking, and (4) an unpleasant odor. Intercept-only spatial generalized additive models (GAM) were used to evaluate and visualize spatial variation within the RdP community. We also examined how our estimates and conclusions about spatial variation might have been affected by lower-density sampling from random subsets street observations. Random subsets were selected to determine the robustness of study results in scenarios with sparser street sampling. Selected characteristics were estimated to be present for between 18% (unpleasant odor) to 59% (low-hanging or tangled wires) of the street segments in RdP; estimates remain similar (± 6%) when relying on a random subset created to simulate lower-density spatial sampling. Spatial patterns of variation based on predicted probabilities across RdP differed by indicator. Structural sinking and low-hanging or tangled wires demonstrated relatively consistent spatial distribution patterns across full and random subset sample sizes. Smartphone-based systematic observations represent an efficient and potentially feasible approach to systematically studying neighborhood environments within informal communities. Future deployment of such tools will benefit from incorporating data collection across multiple time points to explore reliability and quantify neighborhood change. These tools can prove useful means to assess street-level exposures that can be modifiable health determinants across a wide range of informal urban settings. Findings can contribute to improved urban planning and provide useful information for identifying potential locations for neighborhood-scaled interventions that can improve living conditions for residents in Rio das Pedras.

Neighborhood food environment, dietary fatty acid biomarkers, and cardiac arrest risk

We explored links between food environments, dietary intake biomarkers, and sudden cardiac arrest in a population-based longitudinal study using cases and controls accruing between 1990 and 2010 in King County, WA. Surprisingly, presence of more unhealthy food sources near home was associated with a lower 18:1 trans-fatty acid concentration (-0.05% per standard deviation higher count of unhealthy food sources, 95% Confidence Interval [CI]: 0.01, 0.09). However, presence of more unhealthy food sources was associated with higher odds of cardiac arrest (Odds Ratio [OR]: 2.29, 95% CI: 1.19, 4.41 per standard deviation in unhealthy food outlets). While unhealthy food outlets were associated with higher cardiac arrest risk, circulating 18:1 trans fats did not explain the association.

Associations of Residential Socioeconomic, Food, and Built Environments With Glycemic Control in Persons With Diabetes in New York City From 2007-2013

In the present study, we examined the longitudinal associations between residential environmental factors and glycemic control in 182,756 adults with diabetes in New York City from 2007 to 2013. Glycemic control was defined as a hemoglobin A1c (HbA1c) level less than 7%. We constructed residential-level measures and performed principle component analysis to formulate a residential composite score. On the basis of this score, we divided residential areas into quintiles, with the lowest and highest quintiles reflecting the least and most advantaged residential environments, respectively. Several residential-level environmental characteristics, including more advantaged socioeconomic conditions, greater ratio of healthy food outlets to unhealthy food outlets, and residential walkability were associated with increased glycemic control. Individuals who lived continuously in the most advantaged residential areas took less time to achieve glycemic control compared with the individuals who lived continuously in the least advantaged residential areas (9.9 vs. 11.5 months). Moving from less advantaged residential areas to more advantaged residential areas was related to improved diabetes control (decrease in HbA1c = 0.40%, 95% confidence interval: 0.22, 0.55), whereas moving from more advantaged residential areas to less advantaged residential areas was related to worsening diabetes control (increase in HbA1c = 0.33%, 95% confidence interval: 0.24, 0.44). These results show that residential areas with greater resources to support healthy food and residential walkability are associated with improved glycemic control in persons with diabetes.

Street Audits to Measure Neighborhood Disorder: Virtual or In-Person?

Neighborhood conditions may influence a broad range of health indicators, including obesity, injury, and psychopathology. In particular, neighborhood physical disorder-a measure of urban deterioration-is thought to encourage crime and high-risk behaviors, leading to poor mental and physical health. In studies to assess neighborhood physical disorder, investigators typically rely on time-consuming and expensive in-person systematic neighborhood audits. We compared 2 audit-based measures of neighborhood physical disorder in the city of Detroit, Michigan: One used Google Street View imagery from 2009 and the other used an in-person survey conducted in 2008. Each measure used spatial interpolation to estimate disorder at unobserved locations. In total, the virtual audit required approximately 3% of the time required by the in-person audit. However, the final physical disorder measures were significantly positively correlated at census block centroids (r = 0.52), identified the same regions as highly disordered, and displayed comparable leave-one-out cross-validation accuracy. The measures resulted in very similar convergent validity characteristics (correlation coefficients within 0.03 of each other). The virtual audit-based physical disorder measure could substitute for the in-person one with little to no loss of precision. Virtual audits appear to be a viable and much less expensive alternative to in-person audits for assessing neighborhood conditions.

Quantifying Distance Overestimation From Global Positioning System in Urban Spaces

OBJECTIVES

To investigate accuracy of distance measures computed from Global Positioning System (GPS) points in New York City.

METHODS

We performed structured walks along urban streets carrying Globalsat DG-100 GPS Data Logger devices in highest and lowest quartiles of building height and tree canopy cover. We used ArcGIS version 10.1 to select walks and compute the straight-line distance (Geographic Information System-measured) and sum of distances between consecutive GPS waypoints (GPS-measured) for each walk.

RESULTS

GPS distance overestimates were associated with building height (median overestimate = 97% for high vs 14% for low building height) and to a lesser extent tree canopy (43% for high vs 28% for low tree canopy).

CONCLUSIONS

Algorithms using distances between successive GPS points to infer speed or travel mode may misclassify trips differentially by context. Researchers studying urban spaces may prefer alternative mode identification techniques.

Use of Google Street View to Assess Environmental Contributions to Pedestrian Injury

OBJECTIVES

To demonstrate an information technology-based approach to assess characteristics of streets and intersections associated with injuries that is less costly and time-consuming than location-based studies of pedestrian injury.

METHODS

We used imagery captured by Google Street View from 2007 to 2011 to assess 9 characteristics of 532 intersections within New York City. We controlled for estimated pedestrian count and estimated the relation between intersections' characteristics and frequency of injurious collisions.

RESULTS

The count of pedestrian injuries at intersections was associated with the presence of marked crosswalks (80% increase; 95% confidence interval [CI] = 2%, 218%), pedestrian signals (156% increase; 95% CI = 69%, 259%), nearby billboards (42% increase; 95% CI = 7%, 90%), and bus stops (120% increase; 95% CI = 51%, 220%). Injury incidence per pedestrian was lower at intersections with higher estimated pedestrian volumes.

CONCLUSIONS

Consistent with in-person study observations, the information-technology approach found traffic islands, visual advertising, bus stops, and crosswalk infrastructures to be associated with elevated counts of pedestrian injury in New York City. Virtual site visits for pedestrian injury control studies are a viable and informative methodology.

Neighborhood Physical Disorder in New York City

Neighborhood physical disorder, or the deterioration of urban environments, is associated with negative mental and physical health outcomes. Eleven trained raters used CANVAS, a web-based system for conducting reliable virtual street audits, to collect data on nine indicators of physical disorder using Google Street View imagery of 532 block faces in New York City, New York, USA. We combined the block face indicator data into a disorder scale using item response theory; indicators ranged in severity from presence of litter, a weak indicator of disorder, to abandoned cars, a strong indicator. Using this scale, we estimated disorder at the center point of each sampled block. We then used ordinary kriging to interpolate estimates of disorder levels throughout the city. The resulting map condenses a complex estimation process into an interpretable visualization of the spatial distribution of physical disorder in New York City.

Measuring health-relevant businesses over 21 years: refining the National Establishment Time-Series (NETS), a dynamic longitudinal data set

Background

The densities of food retailers, alcohol outlets, physical activity facilities, and medical facilities have been associated with diet, physical activity, and management of medical conditions. Most of the research, however, has relied on cross-sectional studies. In this paper, we assess methodological issues raised by a data source that is increasingly used to characterize change in the local business environment: the National Establishment Time Series (NETS) dataset.

Discussion

Longitudinal data, such as NETS, offer opportunities to assess how differential access to resources impacts population health, to consider correlations among multiple environmental influences across the life course, and to gain a better understanding of their interactions and cumulative health effects. Longitudinal data also introduce new data management, geoprocessing, and business categorization challenges. Examining geocoding accuracy and categorization over 21 years of data in 23 counties surrounding New York City (NY, USA), we find that health-related business environments change considerably over time. We note that re-geocoding data may improve spatial precision, particularly in early years. Our intent with this paper is to make future public health applications of NETS data more efficient, since the size and complexity of the data can be difficult to exploit fully within its 2-year data-licensing period. Further, standardized approaches to NETS and other “big data” will facilitate the veracity and comparability of results across studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-015-1482-4) contains supplementary material, which is available to authorized users.

No-threshold dose-response curves for nongenotoxic chemicals: findings and applications for risk assessment

We tested the hypothesis that no threshold exists when estradiol acts through the same mechanism as an active endogenous estrogen. A Michaelis-Menten (MM) equation accounting for response saturation, background effects, and endogenous estrogen level fit a turtle sex-reversal data set with no threshold and estimated the endogenous dose. Additionally, 31 diverse literature dose-response data sets were analyzed by adding a term for nonhormonal background; good fits were obtained but endogenous dose estimations were not significant due to low resolving power. No thresholds were observed. Data sets were plotted using a normalized MM equation; all 178 data points were accommodated on a single graph. Response rates from approximately 1% to >95% were well fit. The findings contradict the threshold assumption and low-dose safety. Calculating risk and assuming additivity of effects from multiple chemicals acting through the same mechanism rather than assuming a safe dose for nonthresholded curves is appropriate.

Diethylstilbestrol versus estradiol as neonatal disruptors of the hamster (Mesocricetus auratus) cervix

The synthetic estrogen diethylstilbestrol (DES) is an established, estrogenic endocrine disruptor (ED). The Syrian golden hamster (Mesocricetus auratus) offers some unique advantages as an experimental system to investigate the perinatal ED action of DES and other estrogenic EDs. Previous analyses regarding the consequences of neonatal administration (100 microg) of DES versus estradiol-17beta (E2) showed that DES had a more potent disruptive effect on morphogenesis and gene expression in the uterus, oviduct, and ovary as well as in the testis and male accessory organs. The objectives of the present study were to describe the histopathological consequences of the two neonatal treatment regimens in the hamster cervix and to compare them with our previous observations in the hamster uterus. As previously found in the hamster uterus, DES was more potent than E2 as a neonatal disruptor of the hamster cervix in prepubertal animals and in ovarian-intact adult animals. However, the cervix-versus-uterus scenario diverged in animals that were ovariectomized prepubertally and then chronically stimulated with natural estrogen (E2). We confirmed previous observations that neonatal exposure to DES, but not to E2, permanently alters estrogen responsiveness in the adult hamster uterus, but neither neonatal treatment regimen affected estrogen responsiveness in the adult hamster cervix. These results suggest that an unidentified ovarian factor influences the extent of neonatal DES-induced disruption of the cervix, but not of the uterus, in hamsters.

Comparative molecular field analysis (CoMFA) model using a large diverse set of natural, synthetic and environmental chemicals for binding to the androgen receptor

A large number of natural, synthetic and environmental chemicals are capable of disrupting the endocrine systems of experimental animals, wildlife and humans. These so-called endocrine disrupting chemicals (EDCs), some mimic the functions of the endogenous androgens, have become a concern to the public health. Androgens play an important role in many physiological processes, including the development and maintenance of male sexual characteristics. A common mechanism for androgen to produce both normal and adverse effects is binding to the androgen receptor (AR). In this study, we used Comparative Molecular Field Analysis (CoMFA), a three-dimensional quantitative structure-activity relationship (3D-QSAR) technique, to examine AR-ligand binding affinities. A CoMFA model with r2 = 0.902 and q2 = 0.571 was developed using a large training data set containing 146 structurally diverse natural, synthetic, and environmental chemicals with a 10(6)-fold range of relative binding affinity (RBA). By comparing the binding characteristics derived from the CoMFA contour map with these observed in a human AR crystal structure, we found that the steric and electrostatic properties encoded in this training data set are necessary and sufficient to describe the RBA of AR ligands. Finally, the CoMFA model was challenged with an external test data set; the predicted results were close to the actual values with average difference of 0.637 logRBA. This study demonstrates the utility of this CoMFA model for real-world use in predicting the AR binding affinities of structurally diverse chemicals over a wide RBA range.

Study of 202 Natural, Synthetic, and Environmental Chemicals for Binding to the Androgen Receptor

A number of environmental and industrial chemicals are reported to possess androgenic or antiandrogenic activities. These androgenic endocrine disrupting chemicals may disrupt the endocrine system of humans and wildlife by mimicking or antagonizing the functions of natural hormones. The present study developed a low cost recombinant androgen receptor (AR) competitive binding assay that uses no animals. We validated the assay by comparing the protocols and results from other similar assays, such as the binding assay using prostate cytosol. We tested 202 natural, synthetic, and environmental chemicals that encompass a broad range of structural classes, including steroids, diethylstilbestrol and related chemicals, antiestrogens, flutamide derivatives, bisphenol A derivatives, alkylphenols, parabens, alkyloxyphenols, phthalates, siloxanes, phytoestrogens, DDTs, PCBs, pesticides, organophosphate insecticides, and other chemicals. Some of these chemicals are environmentally persistent and/or commercially important, but their AR binding affinities have not been previously reported. To the best of our knowledge, these results represent the largest and most diverse data set publicly available for chemical binding to the AR. Through a careful structure-activity relationship (SAR) examination of the data set in conjunction with knowledge of the recently reported ligand-AR crystal structures, we are able to define the general structural requirements for chemical binding to AR. Hydrophobic interactions are important for AR binding. The interaction between ligand and AR at the 3- and 17-positions of testosterone and R1881 found in other chemical classes are discussed in depth. The SAR studies of ligand binding characteristics for AR are compared to our previously reported results for estrogen receptor binding.

Developing a laboratory animal model for perinatal endocrine disruption: the hamster chronicles

At the biomedical, regulatory, and public level, considerable concern surrounds the concept that inappropriate exposure to endocrine-disrupting chemicals, especially during the prenatal and/or neonatal period, may disrupt normal reproductive tract development and adult function. The intent of this review was to 1. Describe some unique advantages of the hamster for perinatal endocrine disruptor (ED) studies, 2. Summarize the morphological and molecular consequences of exposure to the established perinatal ED, diethylstilbestrol, in the female and male hamster, 3. Present some new, histomorphological insight into the process of neonatal diethylstilbestrol-induced disruption in the hamster uterus, and 4. Introduce recent efforts and future plans to evaluate the potency and mechanism of action of other putative EDs in the hamster experimental system. Taken together, the findings indicate that the hamster represents a unique and sensitive in vivo system to probe the phenomenon of endocrine disruption. The spectrum of candidate endpoints includes developmental toxicity, neoplasia, and more subtle endpoints of reproductive dysfunction.

Goitrogenic and estrogenic activity of soy isoflavones

Soy is known to produce estrogenic isoflavones. Here, we briefly review the evidence for binding of isoflavones to the estrogen receptor, in vivo estrogenicity and developmental toxicity, and estrogen developmental carcinogenesis in rats. Genistein, the major soy isoflavone, also has a frank estrogenic effect in women. We then focus on evidence from animal and human studies suggesting a link between soy consumption and goiter, an activity independent of estrogenicity. Iodine deficiency greatly increases soy antithyroid effects, whereas iodine supplementation is protective. Thus, soy effects on the thyroid involve the critical relationship between iodine status and thyroid function. In rats consuming genistein-fortified diets, genistein was measured in the thyroid at levels that produced dose-dependent and significant inactivation of rat and human thyroid peroxidase (TPO) in vitro. Furthermore, rat TPO activity was dose-dependently reduced by up to 80%. Although these effects are clear and reproducible, other measures of thyroid function in vivo (serum levels of triiodothyronine, thyroxine, and thyroid-stimulating hormone; thyroid weight; and thyroid histopathology) were all normal. Additional factors appear necessary for soy to cause overt thyroid toxicity. These clearly include iodine deficiency but may also include additional soy components, other defects of hormone synthesis, or additional goitrogenic dietary factors. Although safety testing of natural products, including soy products, is not required, the possibility that widely consumed soy products may cause harm in the human population via either or both estrogenic and goitrogenic activities is of concern. Rigorous, high-quality experimental and human research into soy toxicity is the best way to address these concerns. Similar studies in wildlife populations are also appropriate.

Phytoestrogens and mycoestrogens bind to the rat uterine estrogen receptor

Consumption of phytoestrogens and mycoestrogens in food products or as dietary supplements is of interest because of both the potential beneficial and adverse effects of these compounds in estrogen-responsive target tissues. Although the hazards of exposure to potent estrogens such as diethylstilbestrol in developing male and female reproductive tracts are well characterized, less is known about the effects of weaker estrogens including phytoestrogens. With some exceptions, ligand binding to the estrogen receptor (ER) predicts uterotrophic activity. Using a well-established and rigorously validated ER-ligand binding assay, we assessed the relative binding affinity (RBA) for 46 chemicals from several chemical structure classes of potential phytoestrogens and mycoestrogens. Although none of the test compounds bound to ER with the affinity of the standard, 17beta-estradiol (E(2)), ER binding was found among all classes of chemical structures (flavones, isoflavones, flavanones, coumarins, chalcones and mycoestrogens). Estrogen receptor relative binding affinities were distributed across a wide range (from approximately 43 to 0.00008; E(2) = 100). These data can be utilized before animal testing to rank order estimates of the potential for in vivo estrogenic activity of a wide range of untested plant chemicals (as well as other chemicals) based on ER binding.

An integrated "4-phase" approach for setting endocrine disruption screening priorities--phase I and II predictions of estrogen receptor binding affinity

Recent legislation mandates the US Environmental Protection Agency (EPA) to develop a screening and testing program for potential endocrine disrupting chemicals (EDCs), of which xenoestrogens figure prominently. Under the legislation, a large number of chemicals will undergo various in vitro and in vivo assays for their potential estrogenicity, as well as other hormonal activities. There is a crucial need for priority setting before this strategy can be effectively implemented. Here we report an integrated computational approach to priority setting using estrogen receptor (ER) binding as an example. This approach rationally integrates different predictive computational models into a "Four-Phase" scheme so that it can effectively identify potential estrogenic EDCs based on their predicted ER relative binding affinity (RBA). The system has been validated using an in-house ER binding assay dataset for 232 chemicals that was designed to have both broad structural diversity and a wide range of binding affinities. When applied to 58,000 chemicals identified by Walker et al. as candidates for endocrine disruption screening, some 9100 chemicals were predicted to bind to ER. Of these, only 3600 were expected to bind to ER at RBA values up to 100,000-fold less than that of 17beta-estradiol. The method ruled out 83% of the chemicals as non-binders with a very low rate of false negatives. We believe that the same integrated scheme will be equally applicable to endpoints of other endocrine disrupting mechanisms, e.g. androgen receptor binding.

Prediction of estrogen receptor binding for 58,000 chemicals using an integrated system of a tree-based model with structural alerts

A number of environmental chemicals, by mimicking natural hormones, can disrupt endocrine function in experimental animals, wildlife, and humans. These chemicals, called "endocrine-disrupting chemicals" (EDCs), are such a scientific and public concern that screening and testing 58,000 chemicals for EDC activities is now statutorily mandated. Computational chemistry tools are important to biologists because they identify chemicals most important for in vitro and in vivo studies. Here we used a computational approach with integration of two rejection filters, a tree-based model, and three structural alerts to predict and prioritize estrogen receptor (ER) ligands. The models were developed using data for 232 structurally diverse chemicals (training set) with a 10(6) range of relative binding affinities (RBAs); we then validated the models by predicting ER RBAs for 463 chemicals that had ER activity data (testing set). The integrated model gave a lower false negative rate than any single component for both training and testing sets. When the integrated model was applied to approximately 58,000 potential EDCs, 80% (approximately 46,000 chemicals) were predicted to have negligible potential (log RBA < -4.5, with log RBA = 2.0 for estradiol) to bind ER. The ability to process large numbers of chemicals to predict inactivity for ER binding and to categorically prioritize the remainder provides one biologic measure to prioritize chemicals for entry into more expensive assays (most chemicals have no biologic data of any kind). The general approach for predicting ER binding reported here may be applied to other receptors and/or reversible binding mechanisms involved in endocrine disruption.

Threshold analysis of selected dose-response data for endocrine active chemicals

Using a biologically relevant mathematical model, the Michaelis-Menten equation, we examined published data from endocrine active chemicals for evidence of no-threshold dose-response curves. Data were fit to a modified Michaelis-Menten equation which accounted for total background response. Subsequently, the data sets were analyzed using non-linear regression in order to estimate the four parameters of interest (non-hormone controlled background (Bnh), maximum response (Rmax), endogenous hormone level (D0), and the dose at which a half-maximal response was observed (ED50)) and to determine the fit to the fully modified Michaelis-Menten equation. Subsequently, response data were adjusted to account for Bnh and then normalized to Rmax, while dose data were adjusted to account for D0 and then normalized to the ED50. This data set was combined into a single, composite data set and fit to the fully modified Michaelis-Menten equation. We examined 31 data sets (24 endpoints) from studies on 9 different chemical/hormone treatments. Twenty-six of the data sets fit the modified Michaelis-Menten equation with high multiple correlation coefficients (r>0.90). The normalized data demonstrated a good fit to the modified Michaelis-Menten equation. These results indicate that a variety of biological responses fit the modified Michaelis-Menten equation, which does not have a threshold dose term.

Structure-activity relationships for a large diverse set of natural, synthetic, and environmental estrogens

Understanding structural requirements for a chemical to exhibit estrogen receptor (ER) binding has been important in various fields. This knowledge has been directly and indirectly applied to design drugs for human estrogen replacement therapy, and to identify estrogenic endocrine disruptors. This paper reports structure-activity relationships (SARs) based on a total of 230 chemicals, including both natural and xenoestrogens. Activities were generated using a validated ER competitive binding assay, which covers a 10(6)-fold range. This study is focused on identification of structural commonalities among diverse ER ligands. It provides an overall picture of how xenoestrogens structurally resemble endogenous 17beta-estradiol (E(2)) and the synthetic estrogen diethylstilbestrol (DES). On the basis of SAR analysis, five distinguishing criteria were found to be essential for xenoestrogen activity, using E(2) as a template: (1) H-bonding ability of the phenolic ring mimicking the 3-OH, (2) H-bond donor mimicking the17beta-OH and O-O distance between 3- and 17beta-OH, (3) precise steric hydrophobic centers mimicking steric 7alpha- and 11beta-substituents, (4) hydrophobicity, and (5) a ring structure. The 3-position H-bonding ability of phenols is a significant requirement for ER binding. This contributes as both a H-bond donor and acceptor, although predominantly as a donor. However, the 17beta-OH contributes as a H-bond donor only. The precise space (the size and orientation) of steric hydrophobic bulk groups is as important as a 17beta-OH. Where a direct comparison can be made, strong estrogens tend to be more hydrophobic. A rigid ring structure favors ER binding. The knowledge derived from this study is rationalized into a set of hierarchical rules that will be useful in guidance for identification of potential estrogens.

QSAR models using a large diverse set of estrogens

Endocrine disruptors (EDs) have a variety of adverse effects in humans and animals. About 58,000 chemicals, most having little safety data, must be tested in a group of tiered assays. As assays will take years, it is important to develop rapid methods to help in priority setting. For application to large data sets, we have developed an integrated system that contains sequential four phases to predict the ability of chemicals to bind to the estrogen receptor (ER), a prevalent mechanism for estrogenic EDs. Here we report the results of evaluating two types of QSAR models for inclusion in phase III to quantitatively predict chemical binding to the ER. Our data set for the relative binding affinities (RBAs) to the ER consists of 130 chemicals covering a wide range of structural diversity and a 6 orders of magnitude spread of RBAs. CoMFA and HQSAR models were constructed and compared for performance. The CoMFA model had a r2 = 0.91 and a q2LOO = 0.66. HQSAR showed reduced performance compared to CoMFA with r2 = 0.76 and q2LOO = 0.59. A number of parameters were examined to improve the CoMFA model. Of these, a phenol indicator increased the q2LOO to 0.71. When up to 50% of the chemicals were left out in the leave-N-out cross-validation, the q2 remained significant. Finally, the models were tested by using two test sets; the q2pred for these were 0.71 and 0.62, a significant result which demonstrates the utility of the CoMFA model for predicting the RBAs of chemicals not included in the training set. If used in conjunction with phases I and II, which reduced the size of the data set dramatically by eliminating most inactive chemicals, the current CoMFA model (phase III) can be used to predict the RBA of chemicals with sufficient accuracy and to provide quantitative information for priority setting.

Quantitative comparisons of in vitro assays for estrogenic activities

Substances that may act as estrogens show a broad chemical structural diversity. To thoroughly address the question of possible adverse estrogenic effects, reliable methods are needed to detect and identify the chemicals of these diverse structural classes. We compared three assays--in vitro estrogen receptor competitive binding assays (ER binding assays), yeast-based reporter gene assays (yeast assays), and the MCF-7 cell proliferation assay (E-SCREEN assay)--to determine their quantitative agreement in identifying structurally diverse estrogens. We examined assay performance for relative sensitivity, detection of active/inactive chemicals, and estrogen/antiestrogen activities. In this examination, we combined individual data sets in a specific, quantitative data mining exercise. Data sets for at least 29 chemicals from five laboratories were analyzed pair-wise by X-Y plots. The ER binding assay was a good predictor for the other two assay results when the antiestrogens were excluded (r(2) is 0.78 for the yeast assays and 0.85 for the E-SCREEN assays). Additionally, the examination strongly suggests that biologic information that is not apparent from any of the individual assays can be discovered by quantitative pair-wise comparisons among assays. Antiestrogens are identified as outliers in the ER binding/yeast assay, while complete antagonists are identified in the ER binding and E-SCREEN assays. Furthermore, the presence of outliers may be explained by different mechanisms that induce an endocrine response, different impurities in different batches of chemicals, different species sensitivity, or limitations of the assay techniques. Although these assays involve different levels of biologic complexity, the major conclusion is that they generally provided consistent information in quantitatively determining estrogenic activity for the five data sets examined. The results should provide guidance for expanded data mining examinations and the selection of appropriate assays to screen estrogenic endocrine disruptors.

The estrogen receptor relative binding affinities of 188 natural and xenochemicals: structural diversity of ligands

We have utilized a validated (standardized) estrogen receptor (ER) competitive-binding assay to determine the ER affinity for a large, structurally diverse group of chemicals. Uteri from ovariectomized Sprague-Dawley rats were the ER source for the competitive-binding assay. Initially, test chemicals were screened at high concentrations to determine whether a chemical competed with [3H]-estradiol for the ER. Test chemicals that exhibited affinity for the ER in the first tier were subsequently assayed using a wide range of concentrations to characterize the binding curve and to determine each chemical's IC50 and relative binding affinity (RBA) values. Overall, we assayed 188 chemicals, covering a 1 x 10(6)-fold range of RBAs from several different chemical or use categories, including steroidal estrogens, synthetic estrogens, antiestrogens, other miscellaneous steroids, alkylphenols, diphenyl derivatives, organochlorines, pesticides, alkylhydroxybenzoate preservatives (parabens), phthalates, benzophenone compounds, and a number of other miscellaneous chemicals. Of the 188 chemicals tested, 100 bound to the ER while 88 were non-binders. Included in the 100 chemicals that bound to the ER were 4-benzyloxyphenol, 2,4-dihydroxybenzophenone, and 2,2'-methylenebis(4-chlorophenol), compounds that have not been shown previously to bind the ER. It was also evident that certain structural features, such as an overall ring structure, were important for ER binding. The current study provides the most structurally diverse ER RBA data set with the widest range of RBA values published to date.

Quantitative mechanistically based dose-response modeling with endocrine-active compounds

A wide range of toxicity test methods is used or is being developed for assessing the impact of endocrine-active compounds (EACs) on human health. Interpretation of these data and their quantitative use in human and ecologic risk assessment will be enhanced by the availability of mechanistically based dose-response (MBDR) models to assist low-dose, interspecies, and (italic)in vitro(/italic) to (italic)in vivo(/italic) extrapolations. A quantitative dose-response modeling work group examined the state of the art for developing MBDR models for EACs and the near-term needs to develop, validate, and apply these models for risk assessments. Major aspects of this report relate to current status of these models, the objectives/goals in MBDR model development for EACs, low-dose extrapolation issues, regulatory inertia impeding acceptance of these approaches, and resource/data needs to accelerate model development and model acceptance by the research and the regulatory community.

Differential activity of diethylstilbestrol versus estradiol as neonatal endocrine disruptors in the female hamster (Mesocricetus auratus) reproductive tract

The synthetic estrogen diethylstilbestrol (DES) is a potent neonatal endocrine disruptor in the hamster. To test the specificity of this phenomenon, newborn animals were treated with 100 microgram of either DES or the natural estrogen, estradiol-17beta (E2). Of the two, neonatal DES exposure caused greater morphological disruption throughout the female reproductive tract in prepubertal animals and in adults that either retained their ovaries or were ovariectomized and then given the same levels of chronic E2 stimulation. In the uterus, a characteristic histopathological profile, including enhancement of both hyperplastic and apoptotic activity, was initiated prepubertally and exclusively in the endometrial epithelial cell compartment from the neonatally DES-treated animals and then was promoted by E2 stimulation during adulthood. Interestingly, apoptotic activity was not detected in an area of endometrial epithelium that progressed to the neoplastic state in a DES-exposed animal. Lastly, chronic estrogen induction of lactoferrin was also restricted to the DES-exposed endometrium. We conclude that 1) DES is more active than E2 as a perinatal endocrine disruptor in the hamster and 2) this experimental system should be generally useful as a means to screen compounds for such activity and then probe their mechanism of action.

Tissue-specific expression of messenger ribonucleic acids for insulin-like growth factors and insulin-like growth factor-binding proteins during perinatal development of the rat uterus

Insulin-like growth factor (IGF)-I and IGF-II play a number of important roles in growth and differentiation, and IGF-binding proteins (IGFBPs) modulate IGF biological activity. IGF-I has been shown previously to be essential for normal uterine development. Therefore, we used in situ hybridization assays to characterize the unique tissue- and developmental stage-specific pattern of expression for each IGF and IGFBP gene in the rat uterus during perinatal development (gestational day [GD]-20 to postnatal day [PND]-24). IGF-I and IGFBP-1 mRNAs were expressed in all uterine tissues throughout this period. IGFBP-3 mRNA was not detectable at GD-20 but became detectable beginning at PND-5, and the signal intensity appeared to increase during stromal and muscle development. IGFBP-4 mRNA was abundant throughout perinatal development in the myometrium and in the stroma, particularly near the luminal epithelium. IGFBP-5 mRNA was abundantly expressed in myometrium throughout perinatal development. IGFBP-6 mRNA was detected throughout perinatal development in both the stroma and myometrium in a diffuse expression pattern. IGF-II and IGFBP-2 mRNAs were not detected in perinatal uteri. Our results suggest that coordinated temporal and spatial expression of IGF-I and its binding proteins (IGFBP-1,-3,-4,-5, and -6) could play important roles in perinatal rodent uterine development.

No threshold dose for estradiol-induced sex reversal of turtle embryos: how little is too much?

Risk assessments for nongenotoxic chemicals assume a threshold below which no adverse outcomes are seen. However, when an endogenous chemical, such as 17ss-estradiol (E2), occurs at a concentration sufficient to cause an effect, the threshold is already exceeded. Under these circumstances, exogenous estradiol is not expected to provide a threshold dose. This principle is demonstrated for E2 in the red-eared slider, a turtle with temperature-dependent sex determination. In this species, gonadal sex is determined by egg incubation temperature; female development requires endogenous estrogen produced by elevated temperature. While normal production of females by endogenous estrogens is not an adverse effect, exogenous estrogens can sex reverse presumptive males, which can be an adverse effect. A large dose-response study was conducted using seven doses and a vehicle control (starting n = 300/group); a single E2 dose was applied to the eggshell of recently laid eggs. Animals were sexed after hatching. The incubation temperature chosen, 28.6 degrees C, generates a minority of females. Thus, the criteria for testing the threshold hypothesis were met, i.e., there is evidence that there is endogenous estrogen and that it generates an irreversible response. The lowest E2 dose tested, 400 pg/egg (40 ng/kg), sex reversed 14.4% of the animals, demonstrating very low dose sensitivity. The data were fit with a modified Michaelis-Menten equation, which provided an estimate of 1.7 ng/egg for endogenous estradiol. The median effective dose (ED50) was 5.0 +/- 2.0 ng/egg (95% confidence limits), of which 1.7 ng/egg was endogenous estradiol and 3.3 ng/egg came from the applied estradiol. There was no apparent threshold dose for E2. A smaller replication confirmed these results. These results provide a simple biologically based dose-response model and suggest that chemicals which act mechanistically like E2 may also show no threshold dose. If so, even low environmental concentrations of such chemicals may carry risk for sex reversal.

Comparison of estrogen receptor alpha and beta subtypes based on comparative molecular field analysis (CoMFA)

A substantial body of evidence indicates that both humans and wildlife suffer adverse health effects from exposure to environmental chemicals that are capable of interacting with the endocrine system. The recent cloning of the estrogen receptor beta subtype (ER-beta) suggests that the selective effects of estrogenic compounds may arise in part by the control of different subsets of estrogen-responsive promoters by the two ER subtypes, ER-alpha and ER-beta. In order to identify the structural prerequisites for ligand-ER binding and to discriminate ER-alpha and ER-beta in terms of their ligand-binding specificities, Comparative Molecular Field Analysis (CoMFA) was employed to construct a three-dimensional Quantitative Structure-Activity Relationship (3D-QSAR) model on a data set of 31 structurally-diverse compounds for which competitive binding affinities have been measured against both ER-alpha and ER-beta. Structural alignment of the molecules in CoMFA was achieved by maximizing overlap of their steric and electrostatic fields using the Steric and Electrostatic ALignment (SEAL) algorithm. The final CoMFA models, generated by correlating the calculated 3D steric and electrostatic fields with the experimentally observed binding affinities using partial least-squares (PLS) regression, exhibited excellent self-consistency (r2 > 0.99) as well as high internal predictive ability (q2 > 0.65) based on cross-validation. CoMFA-predicted values of RBA for a test set of compounds outside of the training set were consistent with experimental observations. These CoMFA models can serve as guides for the rational design of ER ligands that possess preferential binding affinities for either ER-alpha or ER-beta. These models can also prove useful in risk assessment programs to identify real or suspected EDCs.

Evaluation of quantitative structure-activity relationship methods for large-scale prediction of chemicals binding to the estrogen receptor

Three different QSAR methods, Comparative Molecular Field Analysis (CoMFA), classical QSAR (utilizing the CODESSA program), and Hologram QSAR (HQSAR), are compared in terms of their potential for screening large data sets of chemicals as endocrine disrupting compounds (EDCs). While CoMFA and CODESSA (Comprehensive Descriptors for Structural and Statistical Analysis) have been commercially available for some time, HQSAR is a novel QSAR technique. HQSAR attempts to correlate molecular structure with biological activity for a series of compounds using molecular holograms constructed from counts of sub-structural molecular fragments. In addition to using r2 and q2 (cross-validated r2) in assessing the statistical quality of QSAR models, another statistical parameter was defined to be the ratio of the standard error to the activity range. The statistical quality of the QSAR models constructed using CoMFA and HQSAR techniques were comparable and were generally better than those produced with CODESSA. It is notable that only 2D-connectivity, bond and elemental atom-type information were considered in building HQSAR models. Since HQSAR requires no conformational analysis or structural alignment, it is straightforward to use and lends itself readily to the rapid screening of large numbers of compounds. Among the QSAR methods considered, HQSAR appears to offer many attractive features, such as speed, reproducibility and ease of use, which portend its utility for prioritizing large numbers of potential EDCs for subsequent toxicological testing and risk assessment.

Flavonoids inhibit estrogen binding to rat alpha-fetoprotein

There is considerable interest in the role(s) of plant-derived compounds such as bioflavonoids in regulating steroid hormone action in mammals, and in particular, the possible effects of the bioflavonoids on the growth of steroid-dependent breast and prostate tumors and on possible abnormal development of steroid-sensitive tissues. Studies of the hormone-like actions of bioflavonoids often use fetal or neonatal rats, which contain high levels of serum alpha-fetoprotein (AFP), a protein that binds estradiol with a Kd approximately 5 x 10(-9) M. Interaction of bioflavonoids with AFP could affect the availability of estrogens to estrogen-responsive cells, as well as the actions of bioflavonoids. These considerations motivated us to study the effect of several flavonoids (quercetin, rutin, naringenin, chrysin, apigenin, kaempferol, myricetin, morin, fisetin) and isoflavonoids (daidzein, genistein) on estrogen binding to rat AFP. We found that naringenin, a flavanone, and quercetin and kaempferol, flavonols, inhibit estrogen binding to AFP with apparent Kds of about 5 x 10(-7) M. To our surprise, the two isoflavonoids, daidzein and genistein, have Kds of about 5 x 10(-6) M for AFP. This 10-fold [correction of 1Q-fold] difference in affinity for AFP between flavonoids and isoflavonoids suggests that AFP has a specificity for the flavonoid structure. Moreover, the affinities of bioflavonoids for rat AFP are sufficiently high to suggest that flavonoids and isoflavonoids could modulate estradiol and estrone binding to rat AFP in vivo, when present at dietary levels. Additionally, the potency of the plant estrogens may be altered by binding to AFP. The flavonoids that we tested have different hydroxyl and glucoside substituents on the A, B, and C rings, which allows us to define some of the spatial requirements for binding to AFP. We find that 5,7-hydroxyl groups in ring A and a 4'-hydroxyl group in ring B are important for binding to AFP. This information, combined with molecular modeling studies, may elucidate the molecular basis for recognition of flavonoids and estrogens by AFP. Also, these findings indicate that the flavonoid levels in the diet need to be considered in studies of the effects of various xenobiotics and endocrine manipulations on experimental animals, particularly during development when serum estrogen binding protein concentrations are often elevated. Finally, bioflavonoids should be useful tools for understanding the variety of estrogen actions initiated by different structural classes of estrogens.

Herbal medicines, phytoestrogens and toxicity: risk:benefit considerations

There are several suggested health benefits of phytoestrogens, particularly those found in soy products. Herbal medicines are also widely thought to confer health benefits. Additionally, drugs are prescribed to improve human health, but unlike phytoestrogens and herbal medicines, toxicities are defined in experimental animals and monitored in humans before and after marketing. Knowledge of toxicity is crucial to decrease the risk:benefit ratio; this knowledge defines appropriate conditions for use and strategies for development of safer products. However, our awareness of the toxicity of herbal medicines and phytoestrogen-containing foods is dramatically limited compared to drugs. Some aspects of the toxicity of herbal medicines are briefly reviewed; it is concluded that virtually all of our knowledge is derived from human exposures leading to acute toxicities. Importantly, detection of toxicity is sporadic, and little information is available from prior animal experimentation. Additionally, well-organized monitoring of human populations (as occurs for drugs) is virtually nonexistent. Important toxicities with long latencies are particularly difficult to associate with a causative agent during or even after large scale exposures, as exemplified by tobacco smoking and lung cancer; estrogen replacement therapy and endometrial cancer; diethylstilbestrol and reproductive tract cancers; and fetal alcohol exposure and birth defects. These considerations suggest that much closer study in experimental animals and human populations exposed to phytoestrogen-containing products, and particularly soy-based foods, is necessary. Among human exposures, infant soy formula exposure appears to provide the highest of all phytoestrogen doses, and this occurs during development, often the most sensitive life-stage for induction of toxicity. Large, carefully controlled studies in this exposed infant population are a high priority.

Physiological "constants" for PBPK models for pregnancy

Physiologically based pharmacokinetic (PBPK) models for pregnancy are inherently more complex than conventional PBPK models due to the growth of the maternal and embryo/fetal tissues. Physiological parameters such as compartmental volumes or flow rates are relatively constant at any particular time during gestation when an acute experiment might be conducted, but vary greatly throughout the course of gestation (e.g., contrast relative fetal weight during the first month of gestation with the ninth month). Maternal physiological parameters change during gestation, depending upon the particular system; for example, cardiac output increases by approximately 50% during human gestation; plasma protein concentration decreases during pregnancy; overall metabolism remains fairly constant. Maternal compartmental volumes may change by 10-30%; embryo/fetal volume increases over a billionfold from conception to birth. Data describing these physiological changes in the human are available from the literature. Human embryo/fetal growth can be well described using the Gompertz equation. By contrast, very little of these same types of data is available for the laboratory animal. In the rodent there is a dearth of information during organogenesis as to embryo weights, and even less organ or tissue weight or volume data during embryonic or fetal periods. Allometric modeling offers a reasonable choice to extrapolate (approximately) from humans to animals; validation, however, is confined to comparisons with limited data during the late embryonic and fetal periods of development (after gestation d 11 in the rat and mouse). Embryonic weight measurements are limited by the small size of the embryo and the current state of technology. However, the application of the laser scanning confocal microscope (LSCM) to optically section intact embryos offers the capability of precise structural measurements and computer-generated three-dimensional reconstruction of early embryos. Application of these PBPK models of pregnancy in laboratory animal models at teratogenically sensitive periods of development provides exposure values at specific target tissues. These exposures provide fundamentally important data to help design and interpret molecular probe investigations into mechanisms of teratogenesis.

Site-directed mutagenesis on the m2 muscarinic acetylcholine receptor: the significance of Tyr403 in the binding of agonists and functional coupling

The first step in the transmembrane signal mediated by G protein-coupled receptors is binding of agonist to receptors at the cell surface. The mechanism of the resulting receptor activation is not clear, but models based on the ternary complex model are capable of explaining most of the observations that have been reported in G protein-coupled receptors. This model suggests that a single agonist/receptor/G protein complex capable of activating G protein is formed as the result of agonist binding. Extensions of this basic model differ primarily in whether an equilibrium between active and inactive conformations is required to explain experimental results. We report results on ligand binding and coupling to physiological effector systems of the m2 muscarinic acetylcholine receptor site-directed mutant Y403F (residue 403 mutated from tyrosine to phenylalanine) expressed in Chinese hamster ovary cells and compare our results with results reported for the homologous Y506F mutation in the m3 muscarinic receptor [J. Biol. Chem. 267:19313-19319 (1992)]. The mutation in the m2 muscarinic receptor reduced absolute agonist affinities more dramatically than in the m3 muscarinic receptor. Unlike the results reported for the m3 subtype mutant, in which coupling to physiological effector systems was reduced, coupling to effector systems for the mutant in the m2 subtype was robust. In the Y403F m2 muscarinic receptor, the difference between the two agonist binding affinities was greater than in the wild-type receptor, whereas in the m3 subtype, the effect of the mutation was to decrease this difference. A prediction of the ternary complex model is that relative binding affinities will affect the steady state concentration of the agonist/receptor/G protein complex and, as the result, the extent of G protein coupling. These results can best be rationalized by this model, which suggests that the activation of G protein-coupled receptors is achieved by the relative affinity of agonist for two receptor states and does not require the existence of multiple states in conformational equilibrium.

Expression of a truncated, kinase-defective TGF-beta type II receptor in mouse skeletal tissue promotes terminal chondrocyte differentiation and osteoarthritis

Members of the TGF-beta superfamily are important regulators of skeletal development. TGF-betas signal through heteromeric type I and type II receptor serine/threonine kinases. When over-expressed, a cytoplasmically truncated type II receptor can compete with the endogenous receptors for complex formation, thereby acting as a dominant-negative mutant (DNIIR). To determine the role of TGF-betas in the development and maintenance of the skeleton, we have generated transgenic mice (MT-DNIIR-4 and -27) that express the DNIIR in skeletal tissue. DNIIR mRNA expression was localized to the periosteum/perichondrium, syno-vium, and articular cartilage. Lower levels of DNIIR mRNA were detected in growth plate cartilage. Transgenic mice frequently showed bifurcation of the xiphoid process and sternum. They also developed progressive skeletal degeneration, resulting by 4 to 8 mo of age in kyphoscoliosis and stiff and torqued joints. The histology of affected joints strongly resembled human osteo-arthritis. The articular surface was replaced by bone or hypertrophic cartilage as judged by the expression of type X collagen, a marker of hypertrophic cartilage normally absent from articular cartilage. The synovium was hyperplastic, and cartilaginous metaplasia was observed in the joint space. We then tested the hypothesis that TGF-beta is required for normal differentiation of cartilage in vivo. By 4 and 8 wk of age, the level of type X collagen was increased in growth plate cartilage of transgenic mice relative to wild-type controls. Less proteoglycan staining was detected in the growth plate and articular cartilage matrix of transgenic mice. Mice that express DNIIR in skeletal tissue also demonstrated increased Indian hedgehog (IHH) expression. IHH is a secreted protein that is expressed in chondrocytes that are committed to becoming hypertrophic. It is thought to be involved in a feedback loop that signals through the periosteum/ perichondrium to inhibit cartilage differentiation. The data suggest that TGF-beta may be critical for multifaceted maintenance of synovial joints. Loss of responsiveness to TGF-beta promotes chondrocyte terminal differentiation and results in development of degenerative joint disease resembling osteoarthritis in humans.

Quantitative structure-activity relationships (QSARs) for estrogen binding to the estrogen receptor: predictions across species

The recognition of adverse effects due to environmental endocrine disruptors in humans and wildlife has focused attention on the need for predictive tools to select the most likely estrogenic chemicals from a very large number of chemicals for subsequent screening and/or testing for potential environmental toxicity. A three-dimensional quantitative structure-activity relationship (QSAR) model using comparative molecular field analysis (CoMFA) was constructed based on relative binding affinity (RBA) data from an estrogen receptor (ER) binding assay using calf uterine cytosol. The model demonstrated significant correlation of the calculated steric and electrostatic fields with RBA and yielded predictions that agreed well with experimental values over the entire range of RBA values. Analysis of the CoMFA three-dimensional contour plots revealed a consistent picture of the structural features that are largely responsible for the observed variations in RBA. Importantly, we established a correlation between the predicted RBA values for calf ER and their actual RBA values for human ER. These findings suggest a means to begin to construct a more comprehensive estrogen knowledge base by combining RBA assay data from multiple species in 3D-QSAR based predictive models, which could then be used to screen untested chemicals for their potential to bind to the ER. Another QSAR model was developed based on classical physicochemical descriptors generated using the CODESSA (Comprehensive Descriptors for Structural and Statistical Analysis) program. The predictive ability of the CoMFA model was superior to the corresponding CODESSA model.

QSAR models for binding of estrogenic compounds to estrogen receptor alpha and beta subtypes

We have developed Quantitative Structure-Activity Relationship (QSAR) models based on Comparative Molecular Field Analysis (CoMFA) for 31 estrogenic chemicals whose relative binding affinity (RBA) is available for both ER-alpha and ER-beta. The models demonstrated a significant correlation (r2>0.95) between the CoMFA-calculated steric/electrostatic fields and corresponding RBA data and a good predictive capability (q2>0.6) based on cross-validation. The CoMFA models and contour plots obtained for ER-alpha and ER-beta suggest a close similarity between the receptors in terms of mode of binding and provide a rational basis for ligand selectivity.

Endometrial hyperplasia and apoptosis following neonatal diethylstilbestrol exposure and subsequent estrogen stimulation in both host and transplanted hamster uteri

Prenatal exposure to the synthetic estrogen diethylstilbestrol (DES) causes morphogenetic alterations and neoplasia in the human reproductive tract. In the hamster, neonatal DES exposure alters early uterine morphogenesis and induces endometrial adenocarcinomas in adults. We now demonstrate that the preneoplastic stages of this phenomenon in the hamster reflect an abnormal uterotropic response to estrogen that is characterized by hyperplastic lesions in the endometrial epithelium and includes an immune and/or inflammatory component. Interestingly, biochemical and in situ analysis revealed that the hyperplastic epithelium is also an active site of cell death by apoptosis. To further probe the mechanism of this phenomenon, uteri from 7-day-old control or DES-exposed donors were transplanted into the cheek pouches of control or neonatally DES-exposed adult hosts, and both host groups were treated to provide high circulating levels of estradiol. Among the four ectopic scenarios, histopathological lesions (epithelial hyperplasia, dysplasia, and apoptosis), segregated almost exclusively to the two that consisted of neonatally DES-exposed uteri. The virtual absence of lesions in control uteri transplanted to DES hosts eliminated host systemic factors as causative agents. Therefore, we conclude that DES or its metabolites alter the cellular physiology and/or composition of the developing uterus (initiating event) in such a way that it thereafter responds abnormally to estrogenic stimulation (promoting event). These observations serve to further define a unique experimental system for probing: (a) various aspects of the clinical "DES Syndrome"; (b) how estrogen regulates normal uterine growth and morphogenesis; and (c) how this process can degenerate to the unregulated neoplastic state.

Effects of toremifene on neonatal rat uterine growth and differentiation

In the developing rodent uterus, the estrogen agonist activity of triphenylethylene antiestrogens such as tamoxifen alters uterine luminal epithelium morphology and inhibits uterine gland genesis. We examined uterine growth and differentiation in female offspring from date-mated Sprague-Dawley rats given the structurally related antiestrogen, toremifene, by s.c. injection in 10 microl of sesame oil on postnatal days (PND) 1-5, 10-14, or 20-24. Toremifene given on PND 10-14, a period of rapid uterine gland differentiation, caused a dose-related increase in uterine weight, tripled luminal epithelium cell height, and completely inhibited uterine gland development on PND 14 at doses of 10 microg or higher. Based on this dose-response analysis, a 10-microg dose of toremifene was chosen to assess uterine development after neonatal exposure (PND 1-5). Uterine weights and luminal epithelium cell heights were significantly increased by toremifene on PND 5 but returned to control levels by PND 26. Uterine gland numbers were reduced to 50% those of controls on PND 26. Dose-related uterine weight and luminal epithelium cell height increases were also observed in rats given toremifene on PND 20-24. This estrogen agonist activity of toremifene, revealed primarily in the uterine luminal epithelium, indicates that toremifene is developmentally toxic.

Ontogeny of estrogen receptor messenger ribonucleic acid expression in the postnatal rat uterus

During the first 2 wk of postnatal life, the rodent uterus undergoes a period of marked growth and differentiation. To further examine the role of the estrogen receptor (ER) in the mediation of uterine development, we analyzed the ontogeny of ER mRNA expression in the postnatal rat uterus using in situ hybridization. ER mRNA was present in the uterine stroma on the day of birth and progressively increased in abundance during the first 2 wk of postnatal life. In contrast, ER mRNA was not detectable in the luminal epithelium at birth and did not become abundant in this region until postnatal day (P) 7. ER mRNA abundance increased in the luminal epithelium and in the invaginating and fully formed glandular epithelium during the second week of life. At P21 ER mRNA was more abundant in the glandular epithelium than in any other uterine cell type. These results are consistent with, and extend the findings of, previous studies using uterine homogenate binding assays and immunohistochemistry to define ER ontogeny in rodents. Delineation of the temporal and cell-type specific pattern of ER mRNA ontogeny in the postnatal rat uterus furthers our understanding of the molecular basis of both endogenous and exogenous estrogen effects on uterine growth and development.

Research needs for the risk assessment of health and environmental effects of endocrine disruptors: a report of the U.S. EPA-sponsored workshop

The hypothesis has been put forward that humans and wildlife species adverse suffered adverse health effects after exposure to endocrine-disrupting chemicals. Reported adverse effects include declines in populations, increases in cancers, and reduced reproductive function. The U.S. Environmental Protection Agency sponsored a workshop in April 1995 to bring together interested parties in an effort to identify research gaps related to this hypothesis and to establish priorities for future research activities. Approximately 90 invited participants were organized into work groups developed around the principal reported health effects-carcinogenesis, reproductive toxicity, neurotoxicity, and immunotoxicity-as well as along the risk assessment paradigm-hazard identification, dose-response assessment, exposure assessment, and risk characterization. Attention focused on both ecological and human health effects. In general, group felt that the hypothesis warranted a concerted research effort to evaluate its validity and that research should focus primarily on effects on development of reproductive capability, on improved exposure assessment, and on the effects of mixtures. This report summarizes the discussions of the work groups and details the recommendations for additional research.

ICI 182,780 inhibits endogenous estrogen-dependent rat uterine growth and tamoxifen-induced developmental toxicity

To assess the effects of the steroidal antiestrogen ICI 182,780 on postnatal uterine development, female Sprague-Dawley rats were given s.c. injections of ICI 182,780 (0.1-100 micrograms/rat) on each of postnatal days (PND) 10-14. ICI 182,780 inhibited uterine growth, as measured by uterine weight, in a dose-dependent manner but had no effect on either uterine luminal epithelium hypertrophy or gland genesis. Immunohistochemical analysis revealed that ICI 182,780 (10 micrograms) markedly reduced uterine estrogen receptor (ER) immunoreactivity in all uterine cell types while tamoxifen (10 micrograms) increased ER immunoreactivity, most notably in the luminal epithelium. In addition, tamoxifen increased uterine weight and induced luminal epithelium hypertrophy but inhibited uterine gland genesis--outcomes also seen with synthetic estrogens such as diethylstilbestrol. To test the hypothesis that these effects are a consequence of the estrogen agonist activity of tamoxifen, rats were cotreated with ICI 182,780 (10 micrograms, PND 8-14) and tamoxifen (10 micrograms, PND 10-14). ICI 182,780 greatly reduced or completely blocked tamoxifen-induced uterine weight gain, luminal epithelium hypertrophy, tamoxifen-induced ER immunoreactivity, and the inhibition of uterine gland genesis. ICI 182,780 given daily on PND 1-5 did not alter PND 5 uterine weight or uterine differentiation on PND 26. We conclude that postnatal exposure to ICI 182,780 does not affect uterine growth or differentiation at an age when the uterus is not dependent on estrogen for growth, i.e., PND 1-5, but does inhibit later endogenous estrogen-dependent uterine growth. The blockade of tamoxifen-induced uterine developmental alterations by ICI 182,780 demonstrates that these tamoxifen effects result from its estrogen agonist activity.

Ovarian and adrenal contributions to postnatal growth and differentiation of the rat uterus

We tested the hypothesis that ovarian and/or adrenal factors contribute to uterine growth, differentiation, and acquisition of estrogen responsiveness in the postnatal rat. In untreated rats, normalized uterine weight (5.2 mg/10 g BW on postnatal days [PND] 1-10) increased by about 35% on PND 11-19; PND 6 ovariectomy (OVX) eliminated this increase. Adrenalectomy (ADX) on PND 6 lowered normalized uterine weight only when combined with OVX and only on PND 16 and 19, demonstrating the presence of uterotropic adrenal products. OVX +/- ADX on PND 6 delayed uterine gland genesis by about 2 days but did not alter final gland numbers. There was no change in the normal pattern of luminal epithelium morphology. A uterotropic response to 17 beta-estradiol (E2) occurred on PND 10 in OVX rats and on PND 12 in OVX + ADX rats, but not until PND 14 in controls. We conclude that normal uterine growth is independent of the ovaries and adrenals prior to PND 10, partially dependent during PND 10-15, and completely dependent during PND 16-26. Additionally, a uterotropic response to exogenous E2 occurs concomitantly with, but independently of, the endogenous estrogen surge. Finally, while uterine gland genesis is slightly retarded by OVS +/- ADX, estrogens from these organs do not induce uterine differentiation.