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AOP: 25

Title

A descriptive phrase which references both the Molecular Initiating Event and Adverse Outcome.It should take the form “MIE leading to AO”. For example, “Aromatase inhibition leading to reproductive dysfunction” where Aromatase inhibition is the MIE and reproductive dysfunction the AO. In cases where the MIE is unknown or undefined, the earliest known KE in the chain (i.e., furthest upstream) should be used in lieu of the MIE and it should be made clear that the stated event is a KE and not the MIE.  More help

Aromatase inhibition leading to reproductive dysfunction

Short name
A name that succinctly summarises the information from the title. This name should not exceed 90 characters. More help
Aromatase inhibition leading to reproductive dysfunction
The current version of the Developer's Handbook will be automatically populated into the Handbook Version field when a new AOP page is created.Authors have the option to switch to a newer (but not older) Handbook version any time thereafter. More help
Handbook Version v1.0

Graphical Representation

A graphical representation of the AOP.This graphic should list all KEs in sequence, including the MIE (if known) and AO, and the pair-wise relationships (links or KERs) between those KEs. More help
Click to download graphical representation template Explore AOP in a Third Party Tool

Authors

The names and affiliations of the individual(s)/organisation(s) that created/developed the AOP. More help

Dan Villeneuve, US EPA Mid-Continent Ecology Division (villeneuve.dan@epa.gov)

Point of Contact

The user responsible for managing the AOP entry in the AOP-KB and controlling write access to the page by defining the contributors as described in the next section.   More help
Cataia Ives   (email point of contact)

Contributors

Users with write access to the AOP page.  Entries in this field are controlled by the Point of Contact. More help
  • Dan Villeneuve
  • Cataia Ives

Coaches

This field is used to identify coaches who supported the development of the AOP.Each coach selected must be a registered author. More help

OECD Information Table

Provides users with information concerning how actively the AOP page is being developed and whether it is part of the OECD Workplan and has been reviewed and/or endorsed. OECD Project: Assigned upon acceptance onto OECD workplan. This project ID is managed and updated (if needed) by the OECD. OECD Status: For AOPs included on the OECD workplan, ‘OECD status’ tracks the level of review/endorsement of the AOP . This designation is managed and updated by the OECD. Journal-format Article: The OECD is developing co-operation with Scientific Journals for the review and publication of AOPs, via the signature of a Memorandum of Understanding. When the scientific review of an AOP is conducted by these Journals, the journal review panel will review the content of the Wiki. In addition, the Journal may ask the AOP authors to develop a separate manuscript (i.e. Journal Format Article) using a format determined by the Journal for Journal publication. In that case, the journal review panel will be required to review both the Wiki content and the Journal Format Article. The Journal will publish the AOP reviewed through the Journal Format Article. OECD iLibrary published version: OECD iLibrary is the online library of the OECD. The version of the AOP that is published there has been endorsed by the OECD. The purpose of publication on iLibrary is to provide a stable version over time, i.e. the version which has been reviewed and revised based on the outcome of the review. AOPs are viewed as living documents and may continue to evolve on the AOP-Wiki after their OECD endorsement and publication.   More help
OECD Project # OECD Status Reviewer's Reports Journal-format Article OECD iLibrary Published Version
1.12 WPHA/WNT Endorsed
This AOP was last modified on May 26, 2024 20:39

Revision dates for related pages

Page Revision Date/Time
Decrease, Population growth rate January 03, 2023 09:09
Inhibition, Aromatase March 14, 2022 08:43
Reduction, Plasma 17beta-estradiol concentrations September 26, 2017 11:30
Reduction, Vitellogenin synthesis in liver May 27, 2021 01:10
Reduction, Vitellogenin accumulation into oocytes and oocyte growth/development September 16, 2017 10:14
Reduction, 17beta-estradiol synthesis by ovarian granulosa cells September 16, 2017 10:14
Reduction, Cumulative fecundity and spawning March 20, 2017 17:52
Reduction, Plasma vitellogenin concentrations September 16, 2017 10:14
Inhibition, Aromatase leads to Reduction, 17beta-estradiol synthesis by ovarian granulosa cells November 30, 2016 13:27
Reduction, 17beta-estradiol synthesis by ovarian granulosa cells leads to Reduction, Plasma 17beta-estradiol concentrations March 20, 2017 12:05
Reduction, Plasma 17beta-estradiol concentrations leads to Reduction, Vitellogenin synthesis in liver March 20, 2017 12:28
Reduction, Cumulative fecundity and spawning leads to Decrease, Population growth rate March 20, 2017 13:49
Reduction, Vitellogenin accumulation into oocytes and oocyte growth/development leads to Reduction, Cumulative fecundity and spawning March 20, 2017 13:35
Reduction, Plasma vitellogenin concentrations leads to Reduction, Vitellogenin accumulation into oocytes and oocyte growth/development March 20, 2017 13:21
Reduction, Vitellogenin synthesis in liver leads to Reduction, Plasma vitellogenin concentrations March 20, 2017 12:58
Reduction, Plasma 17beta-estradiol concentrations leads to Reduction, Plasma vitellogenin concentrations October 18, 2018 11:02
Fadrozole November 29, 2016 18:42

Abstract

A concise and informative summation of the AOP under development that can stand-alone from the AOP page. The aim is to capture the highlights of the AOP and its potential scientific and regulatory relevance. More help

This adverse outcome pathway details the linkage between inhibition of gonadal aromatase activity in females and reproductive dysfunction, as measured through the adverse effect of reduced cumulative fecundity and spawning. Initial development of this AOP draws heavily on evidence collected using repeat-spawning fish species. Cumulative fecundity is the most apical endpoint considered in the OECD 229 Fish Short Term Reproduction Assay. The OECD 229 assay serves as screening assay for endocrine disruption and associated reproductive impairment (OECD 2012). Cumulative fecundity is one of several variables known to be of demographic significance in forecasting fish population trends. Therefore, this AOP has utility in supporting the application of measures of aromatase, or in silico predictions of the ability to inhibit aromatase, as a means to identify chemicals with known potential to adversely affect fish populations and potentially other oviparous vertebrates.

AOP Development Strategy

Context

Used to provide background information for AOP reviewers and users that is considered helpful in understanding the biology underlying the AOP and the motivation for its development.The background should NOT provide an overview of the AOP, its KEs or KERs, which are captured in more detail below. More help

Strategy

Provides a description of the approaches to the identification, screening and quality assessment of the data relevant to identification of the key events and key event relationships included in the AOP or AOP network.This information is important as a basis to support the objective/envisaged application of the AOP by the regulatory community and to facilitate the reuse of its components.  Suggested content includes a rationale for and description of the scope and focus of the data search and identification strategy/ies including the nature of preliminary scoping and/or expert input, the overall literature screening strategy and more focused literature surveys to identify additional information (including e.g., key search terms, databases and time period searched, any tools used). More help

Summary of the AOP

This section is for information that describes the overall AOP.The information described in section 1 is entered on the upper portion of an AOP page within the AOP-Wiki. This is where some background information may be provided, the structure of the AOP is described, and the KEs and KERs are listed. More help

Events:

Molecular Initiating Events (MIE)
An MIE is a specialised KE that represents the beginning (point of interaction between a prototypical stressor and the biological system) of an AOP. More help
Key Events (KE)
A measurable event within a specific biological level of organisation. More help
Adverse Outcomes (AO)
An AO is a specialized KE that represents the end (an adverse outcome of regulatory significance) of an AOP. More help
Type Event ID Title Short name
MIE 36 Inhibition, Aromatase Inhibition, Aromatase
KE 219 Reduction, Plasma 17beta-estradiol concentrations Reduction, Plasma 17beta-estradiol concentrations
KE 285 Reduction, Vitellogenin synthesis in liver Reduction, Vitellogenin synthesis in liver
KE 309 Reduction, Vitellogenin accumulation into oocytes and oocyte growth/development Reduction, Vitellogenin accumulation into oocytes and oocyte growth/development
KE 3 Reduction, 17beta-estradiol synthesis by ovarian granulosa cells Reduction, 17beta-estradiol synthesis by ovarian granulosa cells
KE 78 Reduction, Cumulative fecundity and spawning Reduction, Cumulative fecundity and spawning
KE 221 Reduction, Plasma vitellogenin concentrations Reduction, Plasma vitellogenin concentrations
AO 360 Decrease, Population growth rate Decrease, Population growth rate

Relationships Between Two Key Events (Including MIEs and AOs)

This table summarizes all of the KERs of the AOP and is populated in the AOP-Wiki as KERs are added to the AOP.Each table entry acts as a link to the individual KER description page. More help

Network View

This network graphic is automatically generated based on the information provided in the MIE(s), KEs, AO(s), KERs and Weight of Evidence (WoE) summary tables. The width of the edges representing the KERs is determined by its WoE confidence level, with thicker lines representing higher degrees of confidence. This network view also shows which KEs are shared with other AOPs. More help

Prototypical Stressors

A structured data field that can be used to identify one or more “prototypical” stressors that act through this AOP. Prototypical stressors are stressors for which responses at multiple key events have been well documented. More help
Name
Fadrozole

Life Stage Applicability

The life stage for which the AOP is known to be applicable. More help
Life stage Evidence
Adult, reproductively mature

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) can be selected.In many cases, individual species identified in these structured fields will be those for which the strongest evidence used in constructing the AOP was available. More help
Term Scientific Term Evidence Link
medaka Oryzias latipes Moderate NCBI
zebrafish Danio rerio Moderate NCBI
fathead minnow Pimephales promelas High NCBI

Sex Applicability

The sex for which the AOP is known to be applicable. More help
Sex Evidence
Female High

Overall Assessment of the AOP

Addressess the relevant biological domain of applicability (i.e., in terms of taxa, sex, life stage, etc.) and Weight of Evidence (WoE) for the overall AOP as a basis to consider appropriate regulatory application (e.g., priority setting, testing strategies or risk assessment). More help

Domain of Applicability

Addressess the relevant biological domain(s) of applicability in terms of sex, life-stage, taxa, and other aspects of biological context. More help
  • Sex: The AOP applies to females only. Males have relatively low gonadal aromatase expression and activity and the androgen 11-KT, rather than the estrogen E2 is a stronger driver of reproductive functions in males. That said, at least in fish, there is a potential autocrine and paracrine for estrogens synthesized in the brain in regulating reproductive behaviors. However, those potential effects are addressed through an alternative AOP that shares the MIE of aromatase inhibition.
  • Life stages: The relevant life stages for this AOP are reproductively mature adults. This AOP does not apply to adult stages that lack a sexually mature ovary, for example as a result of seasonal or environmentally-induced gonadal senescence (i.e., through control of temperature, photo-period, etc. in a laboratory setting).
  • Taxonomic: At present, the assumed taxonomic applicability domain of this AOP is class Osteichthyes. In all likelihood, the AOP will also prove applicable to all classes of fish (e.g., Agnatha and Chondrithyes as well). Additionally, all the key events described should be conserved among all oviparous vertebrates, suggesting that the AOP may also have relevance for amphibians, reptiles, and birds. However, species-specific differences in reproductive strategies/life histories, ADME (adsorption, distribution, metabolism, and elimination), compensatory reproductive endocrine responses may influence the outcomes, particularly from a quantitative standpoint.

Essentiality of the Key Events

The essentiality of KEs can only be assessed relative to the impact of manipulation of a given KE (e.g., experimentally blocking or exacerbating the event) on the downstream sequence of KEs defined for the AOP. Consequently, evidence supporting essentiality is assembled on the AOP page, rather than on the independent KE pages that are meant to stand-alone as modular units without reference to other KEs in the sequence. The nature of experimental evidence that is relevant to assessing essentiality relates to the impact on downstream KEs and the AO if upstream KEs are prevented or modified. This includes: Direct evidence: directly measured experimental support that blocking or preventing a KE prevents or impacts downstream KEs in the pathway in the expected fashion. Indirect evidence: evidence that modulation or attenuation in the magnitude of impact on a specific KE (increased effect or decreased effect) is associated with corresponding changes (increases or decreases) in the magnitude or frequency of one or more downstream KEs. More help

Support for the essentiality of a number of key events in the AOP was provided by several time-course, stop-reversibility, experiments with fathead minnows exposed to aromatase inhibitors.

1. Villeneuve et al. 2009 and 2013 examined a time-course of key event responses to fadrozole as well as the time-course of recovery following cessation of fadrozole delivery. Once fadrozole was removed from the system, ex vivo E2 production increased, followed by increases in plasma E2 concentrations, and then increases in plasma vitellogenin concentrations. Additionally, while exposure to the chemical was on-going, compensatory up-regulation of CYP19a1a gene expression resulted in increases in ex vivo E2 production, followed by increased plasma E2 and plasma VTG. The essentiality of aromatase inhibition relative to impaired E2 production was further supported by the observation of an "overshoot" in E2 production, relative to controls, shortly after cessation of fadrozole delivery.

2. Similar support was provided in a study by Ankley et al. (2009a). Cessation of prochloraz delivery resulted in rapid recovery of ex vivo E2 production and plasma E2 concentrations, with recovery of vitellogenin concentrations lagging slightly behind. Increased expression of cyp19a1a mRNA during the exposure period aligned with increased ex vivo E2 production, and increased plasma E2, compared to the first day of exposure.

Rationale for essentiality calls:

• Aromatase, inhibition: [Strong] There is good evidence from stop/reversibility studies that ceasing delivery of the aromatase inhibitor leads to recovery of the subsequent key events.

• 17beta-estradiol synthesis by ovarian granulosa cells, reduction: [Strong] In both exposure studies and stop/reversibility studies, when ex vivo E2 production (as measure of this KE) recovers either through compensation or due to removal of the stressor, subsequent KEs have been shown to recover after a lag period.

• plasma 17beta-estradiol concentrations, reduction: [Strong] In both exposure studies and stop/reversibility studies, when plasma E2 concentrations recover either through compensation or due to removal of the stressor, subsequent KEs have been shown to recover after a lag period.

• vitellogenin production in liver (transcription, translation), reduction: [Moderate] This endpoint was not specifically examined in stop/reversibility studies with aromatase inhibitors, but biological plausibility provides strong support for the essentiality of this event.

• plasma vitellogenin concentrations, reduction: [Strong] Shown to recover in a predictable fashion consistent with the order of events in the AOP in stop/recovery studies.

• vitellogenin accumulation into oocytes and oocyte growth/development, reduction: [Weak] Some contradictory evidence regarding the essentiality of this event. No stop/reversibility studies have explicitly considered this key event.

• cumulative fecundity and spawning, reductions: [Moderate] By definition, some degree of spawning is required to maintain population.

Evidence Assessment

Addressess the biological plausibility, empirical support, and quantitative understanding from each KER in an AOP. More help

Biological plausibility: Biological plausibility refers to the structural or functional relationship between the key events based on our fundamental understanding of "normal biology". In general, the biological plausibility and coherence linking aromatase inhibition through decreases in circulating concentrations of E2 is very solid. The biochemistry of steroidogenesis and the predominant role of the gonad in synthesis of the sex steroids is well established. Similarly, the role of E2 as the major regulator of hepatic vitellogenin production is widely documented in the literature. The direct link between reduced VTG concentrations in the plasma and reduced uptake into oocytes is highly plausible, as the plasma is the primary source of the VTG. However, the direct connection between reduced VTG uptake and impaired spawning/reduced cumulative fecundity is more tentative. It is not clear, for instance whether impaired VTG uptake limits oocyte growth and failure to reach a critical size in turn impairs physical or inter-cellular signaling processes that promote release of the oocyte from the surrounding follicles. In at least one experiment, oocytes with similar size to vitellogenic oocytes, but lacking histological staining characteristic of vitellogenic oocytes was observed (R. Johnson, personal communication). Regulation of oocyte maturation and spawning involves many factors other than vitellogenin accumulation (Clelland and Peng, 2009). At present, the link between reductions in circulating VTG concentrations and reduced cumulative fecundity are best supported by the correlation between those endpoints across multiple experiments, including those that impact VTG via other molecular initiating events (Miller et al. 2007).

Concordance of dose-response relationships: Dose response concordance considers the degree to which upstream events are shown to occur at test concentrations equal to or lower than those that cause significant effects on downstream key events, the underlying assumption being that all KEs can be measured with equal precision. There are a limited number of studies in which multiple key events were considered in the same study. These were considered the most useful for evaluating the concordance of dose-response relationships. In general, effects on downstream key events occurred at concentrations equal to or greater than those at which upstream events occurred (Concordance table: [1]). However, there are exceptions. There are cases where no significant effects on estradiol synthesis by ovarian granulosa cells (ovary explants) were observed, but significant effects on plasma E2 or VTG concentrations were observed. Likewise, there are cases where impacts on plasma VTG were observed at concentrations lower than those reported to reduce plasma E2 concentrations. Based on knowledge of the studies in question, the apparent lack of concordance in some cases is driven by two primary factors. First, differences in the sensitivity and dynamic range of the measurements being made. Second, the effects of compensatory responses along the HPG axis. For instance, although ex vivo E2 production is rapidly affected by exposure to fadrozole, it is also a response that is more rapidly corrected through upregulation of aromatase transcripts (see Villeneuve et al. 2009), meaning that it recovers more quickly than plasma concentrations of E2 or plasma VTG concentrations. Thus, at certain time points, one can get an apparent effect on plasma E2 or T without a measurable impact on E2 production by the gonad tissue, because the upstream insult occurred earlier in time and was subsequently offset by a compensatory response, but the compensation has yet to propagate through the pathway. Sensitivity and dynamic range of the measurement methods is also an issue. Vitellogenin concentrations have a highly dynamic range and can change by orders of magnitude. Other endpoints like plasma steroids are regulated in a narrower range, making differences more difficult to distinguish statistically. Therefore, in our assessment, the deviations from concordance do not call the KERs into question.

The concentration-dependence of the key event responses with regard to the concentration of aromatase inhibitor has been established in vitro and/or in vivo for nearly all key events in the AOP.

  1. Concentration-dependent aromatase inhibition: (Villeneuve et al. 2006; Ankley et al. 2005; M et al. 2004; AM et al. 2000; Shilling et al. 1999)
  2. Concentration-dependent decreases in E2 production in vitro, ex vivo: (Ankley et al. 2002; Villeneuve et al. 2007; Villeneuve et al. 2009; Ankley et al. 2005; a Marca Pereira et al. 2011; Lee et al. 2006).
  3. Concentration-dependent decreases in circulating E2 concentrations: (Ankley et al. 2002; Villeneuve et al. 2009; Ankley et al. 2005; Ankley et al. 2009a; GT et al. 2001)
  4. Concentration-dependent decreases in vitellogenin mRNA expression: (Sun et al. 2010; Sun et al. 2011; Zhang et al. 2008)
  5. Concentration-dependent decreases in circulating vitellogenin concentrations: (Ankley et al. 2002; Villeneuve et al. 2009; Ankley et al. 2005; Ankley et al. 2009a; Sun et al. 2007; GT et al. 2001; Ralston-Hooper et al. 2013)
  6. Concentration-dependent reductions in VTG uptake into oocytes or impaired oocyte development: Concentration-dependence of these effects has not been well demonstrated. The effects, when seen, have typically been documented at the greatest exposure concentration tested, but concentration-dependence of the severity or frequency of the impact was not documented (e.g., (Ankley et al. 2002; Ankley et al. 2005; Sun et al. 2007)
  7. Concentration-dependent reductions in cumulative fecundity: (Ankley et al. 2002; Ankley et al. 2005; Sun et al. 2007; Zhang et al. 2008)
  8. Declining population trajectory: Modeled population trajectories show a concentration-dependent reduction in projected population size, however, those results are driven by the concentration-dependence of cumulative fecundity. Population-level effects have not been measured directly.

Temporal concordance: Temporal concordance refers to the degree to which the data support the hypothesized sequence of the key events; i.e., the effect on KE1 is observed before the effect on KE2, which is observed before the effect on KE3 and so on. Temporal concordance of the AOP from aromatase inhibition to decreased E2 production, decreased circulating E2, and decreased plasma VTG concentrations has been established (e.g., (Villeneuve et al. 2009; Ankley et al. 2009a; Skolness et al. 2011). Temporal concordance has not been established beyond that key event, in large part due to disconnect in the time-scales over which the events can be measured. For example, most small fish used in reproductive toxicity testing will can spawn anywhere from once daily to several days per week. Given the variability in daily spawning rates, it is neither practical nor effective to evaluate cumulative fecundity at a time scale shorter than roughly a week. Since the impacts at lower levels of biological organization can be detected within hours of exposure, lack of impact on cumulative fecundity before the other key events are impacted cannot be effectively measured. Overall, among those key events whose temporal concordance can reasonably be evaluated, the temporal profile observed is consistent with the AOP.

Consistency: We are aware of no cases where the pattern of key events described was observed without also observing a significant impact on cumulative fecundity. The final adverse outcome is not specific to this AOP. Many of the key events included in this AOP overlap with AOPs linking other molecular initiating events to reproductive dysfunction in small fish.

Uncertainties, inconsistencies, and data gaps: The current major uncertainty in this AOP is whether there is a direct biological linkage between impaired VTG uptake into oocytes and impaired spawning/reduced cumulative fecundity. Plausible biological connections have been hypothesized, but have not yet been tested experimentally.

Known Modulating Factors

Modulating factors (MFs) may alter the shape of the response-response function that describes the quantitative relationship between two KES, thus having an impact on the progression of the pathway or the severity of the AO.The evidence supporting the influence of various modulating factors is assembled within the individual KERs. More help
Modulating Factor (MF) Influence or Outcome KER(s) involved
     

Quantitative Understanding

Optional field to provide quantitative weight of evidence descriptors.  More help

Assessment of quantitative understanding of the AOP:

At present, quantitative understanding of the AOP is approaching the point where an in vitro measurement of aromatase inhibition could be used as an input parameter into a series of coupled computational models that could generate quantitative predictions across multiple key events (e.g., circulating E2 concentrations, circulating VTG concentrations, predicted impacts on cumulative fecundity, and effects on population trajectories). A sequence of supporting models has been coupled together and predictions have been made for novel aromatase inhibitors (identified through high throughput in vitro screening; Conolly et al. 2017).

Q-AOP model-based predictions for short-term key events, were tested experimentally for five chemicals identified as aromatase inhibitors (Villeneuve et al. 2021). 

Q-AOP-based predictions extending over the entire AOP were evaluated empirically for imazalil in 60 h, 10 d, and 21 day studies (Villeneuve et al. 2023).

In general, model predictions were within 1-2 orders of magnitude, but differences and toxicokinetics and additional bioactivities (interactions in a broader AOP network) may lead to error/uncertainty in the model predictions.

Considerations for Potential Applications of the AOP (optional)

Addressess potential applications of an AOP to support regulatory decision-making.This may include, for example, possible utility for test guideline development or refinement, development of integrated testing and assessment approaches, development of (Q)SARs / or chemical profilers to facilitate the grouping of chemicals for subsequent read-across, screening level hazard assessments or even risk assessment. More help
  • The present AOP can provide potential support for the use of alternatives to the fish short term reproduction assay as a screen for aromatase inhibitors.
  • The present AOP can serve as a foundation for tiered testing strategies and IATA related to risk assessments on chemicals identified as aromatase inhibitors.
  • The present AOP can be used to guide endpoint selection for effects-based monitoring studies at sites where aromatase inhibition has been identified as a relevant biological activity of interest (e.g., through bioeffects prediction or bioeffects surveillance approaches; see Schroeder et al. 2016).

Schroeder, A. L., Ankley, G. T., Houck, K. A. and Villeneuve, D. L. (2016), Environmental surveillance and monitoring—The next frontiers for high-throughput toxicology. Environ Toxicol Chem, 35: 513–525. doi:10.1002/etc.3309

  • A series of computational models aligned with this AOP (i.e., a quantitative AOP construct) can be applied to estimate in vivo bench-mark doses based on in vitro screening results. Case studies evaluating this application are under way.

References

List of the literature that was cited for this AOP. More help

1. OECD. 2012. Test No. 229: Fish Short Term Reproduction Assay. Paris, France:Organization for Economic Cooperation and Development.

2. Petkov PI, Temelkov S, Villeneuve DL, Ankley GT, Mekenyan OG. 2009. Mechanism-based categorization of aromatase inhibitors: a potential discovery and screening tool. SAR QSAR Environ Res 20(7-8): 657-678.

3. Lephart ED, Simpson ER. 1991. Assay of aromatase activity. Methods Enzymol 206: 477-483.

4. Letcher RJ, van Holsteijn I, Drenth H-J, Norstrom RJ, Bergman A, Safe S, et al. 1999. Cytotoxicity and aromatase (CYP19) activity modulation by organochlorines in human placental JEG-3 and JAR choriocarcinoma cells. Toxicology and applied pharmacology 160: 10-20.

5. Sanderson J, Seinen W, Giesy J, van den Berg M. 2000. 2-chloro-triazine herbicides induce aromatase (CYP19) activity in H295R human adrenocortical carcinoma cells: a novel mechanism for estrogenicity. Toxicological Sciences 54: 121-127.

6. Villeneuve DL, Knoebl I, Kahl MD, Jensen KM, Hammermeister DE, Greene KJ, et al. 2006. Relationship between brain and ovary aromatase activity and isoform-specific aromatase mRNA expression in the fathead minnow (Pimephales promelas). Aquat Toxicol 76(3-4): 353-368.

7. Ankley GT, Kahl MD, Jensen KM, Hornung MW, Korte JJ, Makynen EA, et al. 2002. Evaluation of the aromatase inhibitor fadrozole in a short-term reproduction assay with the fathead minnow (Pimephales promelas). Toxicological Sciences 67: 121-130.

8. Castro LF, Santos MM, Reis-Henriques MA. 2005. The genomic environment around the Aromatase gene: evolutionary insights. BMC evolutionary biology 5: 43.

9. Norris DO. 2007. Vertebrate Endocrinology. Fourth ed. New York: Academic Press.

10. Yaron Z. 1995. Endocrine control of gametogenesis and spawning induction in the carp. Aquaculture 129: 49-73.

11. Havelock JC, Rainey WE, Carr BR. 2004. Ovarian granulosa cell lines. Molecular and cellular endocrinology 228(1-2): 67-78.

12. Villeneuve DL, Ankley GT, Makynen EA, Blake LS, Greene KJ, Higley EB, et al. 2007. Comparison of fathead minnow ovary explant and H295R cell-based steroidogenesis assays for identifying endocrine-active chemicals. Ecotoxicol Environ Saf 68(1): 20-32.

13. McMaster ME MK, Jardine JJ, Robinson RD, Van Der Kraak GJ. 1995. Protocol for measuring in vitro steroid production by fish gonadal tissue. Canadian Technical Report of Fisheries and Aquatic Sciences 1961 1961: 1-78.

14. Ankley GT, Jensen KM, Kahl MD, Makynen EA, Blake LS, Greene KJ, et al. 2007. Ketoconazole in the fathead minnow (Pimephales promelas): reproductive toxicity and biological compensation. Environ Toxicol Chem 26(6): 1214-1223.

15. Villeneuve DL, Mueller ND, Martinovic D, Makynen EA, Kahl MD, Jensen KM, et al. 2009. Direct effects, compensation, and recovery in female fathead minnows exposed to a model aromatase inhibitor. Environ Health Perspect 117(4): 624-631.

16. Baker ME. 2011. Origin and diversification of steroids: co-evolution of enzymes and nuclear receptors. Molecular and cellular endocrinology 334(1-2): 14-20.

17. Jensen K, Korte J, Kahl M, Pasha M, Ankley G. 2001. Aspects of basic reproductive biology and endocrinology in the fathead minnow (Pimephales promelas). Comparative Biochemistry and Physiology Part C 128: 127-141.

18. Biales AD, Bencic DC, Lazorchak JL, Lattier DL. 2007. A quantitative real-time polymerase chain reaction method for the analysis of vitellogenin transcripts in model and nonmodel fish species. Environ Toxicol Chem 26(12): 2679-2686.

19. Schmieder P, Tapper M, Linnum A, Denny J, Kolanczyk R, Johnson R. 2000. Optimization of a precision-cut trout liver tissue slice assay as a screen for vitellogenin induction: comparison of slice incubation techniques. Aquat Toxicol 49(4): 251-268.

20. Navas JM, Segner H. 2006. Vitellogenin synthesis in primary cultures of fish liver cells as endpoint for in vitro screening of the (anti)estrogenic activity of chemical substances. Aquat Toxicol 80(1): 1-22.

21. Korte JJ, Kahl MD, Jensen KM, Mumtaz SP, Parks LG, LeBlanc GA, et al. 2000. Fathead minnow vitellogenin: complementary DNA sequence and messenger RNA and protein expression after 17B-estradiol treatment. Environmental Toxicology and Chemistry 19(4): 972-981.

22. Tyler C, van der Eerden B, Jobling S, Panter G, Sumpter J. 1996. Measurement of vitellogenin, a biomarker for exposure to oestrogenic chemicals, in a wide variety of cyprinid fish. Journal of Comparative Physiology and Biology 166: 418-426.

23. Tyler C, Sumpter J. 1996. Oocyte growth and development in teleosts. Reviews in Fish Biology and Fisheries 6: 287-318.

24. Leino R, Jensen K, Ankley G. 2005. Gonadal histology and characteristic histopathology associated with endocrine disruption in the adult fathead minnow. Environmental Toxicology and Pharmacology 19: 85-98.

25. Wolf JC, Dietrich DR, Friederich U, Caunter J, Brown AR. 2004. Qualitative and quantitative histomorphologic assessment of fathead minnow Pimephales promelas gonads as an endpoint for evaluating endocrine-active compounds: a pilot methodology study. Toxicol Pathol 32(5): 600-612.

26. Miller DH, Ankley GT. 2004. Modeling impacts on populations: fathead minnow (Pimephales promelas) exposure to the endocrine disruptor 17b-trenbolone as a case study. Ecotoxicology and Environmental Safety 59: 1-9.

27. Ankley GT, Jensen KM, Durhan EJ, Makynen EA, Butterworth BC, Kahl MD, et al. 2005. Effects of two fungicides with multiple modes of action on reproductive endocrine function in the fathead minnow (Pimephales promelas). Toxicol Sci 86(2): 300-308.

28. Ankley GT, Bencic D, Cavallin JE, Jensen KM, Kahl MD, Makynen EA, et al. 2009a. Dynamic nature of alterations in the endocrine system of fathead minnows exposed to the fungicide prochloraz. Toxicol Sci 112(2): 344-353.

29. Skolness SY, Durhan EJ, Garcia-Reyero N, Jensen KM, Kahl MD, Makynen EA, et al. 2011. Effects of a short-term exposure to the fungicide prochloraz on endocrine function and gene expression in female fathead minnows (Pimephales promelas). Aquat Toxicol 103(3-4): 170-178.

30. Breen M, Villeneuve DL, Ankley GT, Bencic DC, Breen MS, Watanabe KH, et al. 2013. Developing Predictive Approaches to Characterize Adaptive Responses of the Reproductive Endocrine Axis to Aromatase Inhibition: II. Computational Modeling. Toxicological sciences : an official journal of the Society of Toxicology.

31. Breen MS, Villeneuve DL, Breen M, Ankley GT, Conolly RB. 2007. Mechanistic computational model of ovarian steroidogenesis to predict biochemical responses to endocrine active compounds. Annals of biomedical engineering 35(6): 970-981.

32. Shoemaker JE, Gayen K, Garcia-Reyero N, Perkins EJ, Villeneuve DL, Liu L, et al. 2010. Fathead minnow steroidogenesis: in silico analyses reveals tradeoffs between nominal target efficacy and robustness to cross-talk. BMC systems biology 4: 89.

33. Quignot N, Bois FY. 2013. A computational model to predict rat ovarian steroid secretion from in vitro experiments with endocrine disruptors. PloS one 8(1): e53891.

34. Ankley GT, Bencic DC, Cavallin JE, Jensen KM, Kahl MD, Makynen EA, et al. 2009b. Dynamic nature of alterations in the endocrine system of fathead minnows exposed to the fungicide prochloraz. Toxicological sciences : an official journal of the Society of Toxicology 112(2): 344-353.

35. Villeneuve DL, Breen M, Bencic DC, Cavallin JE, Jensen KM, Makynen EA, et al. 2013. Developing Predictive Approaches to Characterize Adaptive Responses of the Reproductive Endocrine Axis to Aromatase Inhibition: I. Data Generation in a Small Fish Model. Toxicological sciences : an official journal of the Society of Toxicology.

36. Ankley GT, Cavallin JE, Durhan EJ, Jensen KM, Kahl MD, Makynen EA, et al. 2012. A time-course analysis of effects of the steroidogenesis inhibitor ketoconazole on components of the hypothalamic-pituitary-gonadal axis of fathead minnows. Aquatic toxicology 114-115: 88-95.

37. Li Z, Kroll KJ, Jensen KM, Villeneuve DL, Ankley GT, Brian JV, et al. 2011a. A computational model of the hypothalamic: pituitary: gonadal axis in female fathead minnows (Pimephales promelas) exposed to 17alpha-ethynylestradiol and 17beta-trenbolone. BMC systems biology 5: 63.

38. A A, A G. 2003. Eggshell and egg yolk proteins in fish: hepatic proteins for the next generation: oogenetic, population, and evolutionary implications of endocrine disruption. Comparative Hepatology 2(4): 1-21.

39. Sun L, Wen L, Shao X, Qian H, Jin Y, Liu W, et al. 2010. Screening of chemicals with anti-estrogenic activity using in vitro and in vivo vitellogenin induction responses in zebrafish (Danio rerio). Chemosphere 78(7): 793-799.

40. Iguchi T, Irie F, Urushitani H, Tooi O, Kawashima Y, Roberts M, et al. 2006. Availability of in vitro vitellogenin assay for screening of estrogenic and anti-estrogenic activities of environmental chemicals. Environ Sci 13(3): 161-183.

41. Murphy CA, Rose KA, Thomas P. 2005. Modeling vitellogenesis in female fish exposed to environmental stressors: predicting the effects of endocrine disturbance due to exposure to a PCB mixture and cadmium. Reproductive toxicology 19(3): 395-409.

42. Murphy CA, Rose KA, Rahman MS, Thomas P. 2009. Testing and applying a fish vitellogenesis model to evaluate laboratory and field biomarkers of endocrine disruption in Atlantic croaker (Micropogonias undulatus) exposed to hypoxia. Environmental toxicology and chemistry / SETAC 28(6): 1288-1303.

43. Ankley GT, Miller DH, Jensen KM, Villeneuve DL, Martinovic D. 2008. Relationship of plasma sex steroid concentrations in female fathead minnows to reproductive success and population status. Aquatic toxicology 88(1): 69-74.

44. Schmid T, Gonzalez-Valero J, Rufli H, Dietrich DR. 2002. Determination of vitellogenin kinetics in male fathead minnows (Pimephales promelas). Toxicol Lett 131(1-2): 65-74.

45. Schultz IR, Orner G, Merdink JL, Skillman A. 2001. Dose-response relationships and pharmacokinetics of vitellogenin in rainbow trout after intravascular administration of 17alpha-ethynylestradiol. Aquatic toxicology 51(3): 305-318.

46. Bowman CJ, Kroll KJ, Hemmer MJ, Folmar LC, Denslow ND. 2000. Estrogen-induced vitellogenin mRNA and protein in sheepshead minnow (Cyprinodon variegatus). General and comparative endocrinology 120(3): 300-313.

47. Genovese G, Regueira M, Piazza Y, Towle DW, Maggese MC, Lo Nostro F. 2012. Time-course recovery of estrogen-responsive genes of a cichlid fish exposed to waterborne octylphenol. Aquatic toxicology 114-115: 1-13.

48. Ankley GT, Jensen KM, Makynen EA, Kahl MD, Korte JJ, Hornung MW, et al. 2003. Effects of the androgenic growth promoter 17-b-trenbolone on fecundity and reproductive endocrinology of the fathead minnow. Environmental Toxicology and Chemistry 22(6): 1350-1360.

49. Sun L, Zha J, Spear PA, Wang Z. 2007. Toxicity of the aromatase inhibitor letrozole to Japanese medaka (Oryzias latipes) eggs, larvae and breeding adults. Comp Biochem Physiol C Toxicol Pharmacol 145(4): 533-541.

50. Li Z, Villeneuve DL, Jensen KM, Ankley GT, Watanabe KH. 2011b. A computational model for asynchronous oocyte growth dynamics in a batch-spawning fish. Can J Fish Aquat Sci 68: 1528-1538.

51. Miller DH, Jensen KM, Villeneuve DL, Kahl MD, Makynen EA, Durhan EJ, et al. 2007. Linkage of biochemical responses to population-level effects: a case study with vitellogenin in the fathead minnow (Pimephales promelas). Environ Toxicol Chem 26(3): 521-527.

52. Miller DH, Tietge JE, McMaster ME, Munkittrick KR, Xia X, Ankley GT. 2013. Assessment of Status of White Sucker (Catostomus Commersoni) Populations Exposed to Bleached Kraft Pulp Mill Effluent. Environmental toxicology and chemistry / SETAC.

53. M H, M vdB, JT S. 2004. A comparison of human H295R and rat R2C cell lines as in vitro screening tools for effects on aromatase. Toxicol Lett 146: 183-194.

54. AM V, C H, V B, JC L. 2000. Screening of selected pesticides for inhibition of CYP19 aromatase activity in vitro. Toxicology In Vitro 14: 227-234.

55. Shilling AD, Carlson DB, Williams DE. 1999. Rainbow trout, Oncorhynchus mykiss, as a model for aromatase inhibition. J Steroid Biochem Mol Biol 70(1-3): 89-95.

56. a Marca Pereira ML, Wheeler JR, Thorpe KL, Burkhardt-Holm P. 2011. Development of an ex vivo brown trout (Salmo trutta fario) gonad culture for assessing chemical effects on steroidogenesis. Aquat Toxicol 101(3-4): 500-511.

57. Lee PS, Pankhurst NW, King HR. 2006. Effects of aromatase inhibitors on in vitro steroidogenesis by Atlantic salmon (Salmo salar) gonadal and brain tissue. Comp Biochem Physiol A Mol Integr Physiol 145(2): 195-203.

58. GT A, KM J, MD K, JJ K, EA M. 2001. Description and evaluation of a short-term reproduction test with the fathead minnow (Pimephales promelas). Environmental Toxicology and Chemistry 20(6): 1276-1290.

59. Sun L, Shao X, Chi J, Hu X, Jin Y, Fu Z. 2011. Transcriptional responses in the brain, liver and gonad of Japanese ricefish (Oryzias latipes) exposed to two anti-estrogens. Comp Biochem Physiol C Toxicol Pharmacol 153(4): 392-401.

60. Zhang X, Hecker M, Tompsett AR, Park JW, Jones PD, Newsted J, et al. 2008. Responses of the medaka HPG axis PCR array and reproduction to prochloraz and ketoconazole. Environ Sci Technol 42(17): 6762-6769.

61. Ralston-Hooper KJ, Turner ME, Soderblom EJ, Villeneuve D, Ankley GT, Moseley MA, et al. 2013. Application of a Label-free, Gel-free Quantitative Proteomics Method for Ecotoxicological Studies of Small Fish Species. Environ Sci Technol 47(2): 1091-1100.

62. Clelland E, Peng C. Endocrine/paracrine control of zebrafish ovarian development. Mol Cell Endocrinol. 2009. 312(1-2):42-52. doi: 10.1016/j.mce.2009.04.009.

63. Villeneuve DL, Blackwell BR, Blanksma CA, Cavallin JE, Cheng WY, Conolly RB, Conrow K, Feifarek DJ, Heinis LJ, Jensen KM, Kahl MD, Milsk RY, Poole ST, Randolph EC, Saari TW, Watanabe KH, Ankley GT. Case Study in 21st-Century Ecotoxicology: Using In Vitro Aromatase Inhibition Data to Predict Reproductive Outcomes in Fish In Vivo. Environ Toxicol Chem. 2023 Jan;42(1):100-116. doi: 10.1002/etc.5504. 

64. Villeneuve DL, Blackwell BR, Cavallin JE, Cheng WY, Feifarek DJ, Jensen KM, Kahl MW, Milsk RY, Poole ST, Randolph EC, Saari TW, Ankley GT. Case Study in 21st Century Ecotoxicology: Using In Vitro Aromatase Inhibition Data to Predict Short-Term In Vivo Responses in Adult Female Fish. Environ Toxicol Chem. 2021 Apr;40(4):1155-1170. doi: 10.1002/etc.4968. 

65. Conolly RB, Ankley GT, Cheng W, Mayo ML, Miller DH, Perkins EJ, Villeneuve DL, Watanabe KH. Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology. Environ Sci Technol. 2017 Apr 18;51(8):4661-4672. doi: 10.1021/acs.est.6b06230