Aop: 25


Each AOP should be given a descriptive title that takes the form “MIE leading to AO”. For example, “Aromatase inhibition [MIE] leading to reproductive dysfunction [AO]” or “Thyroperoxidase inhibition [MIE] leading to decreased cognitive function [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 short name should also be provided that succinctly summarises the information from the title. This name should not exceed 90 characters. More help
Aromatase inhibition leading to reproductive dysfunction

Graphical Representation

A graphical summary of the AOP listing all the KEs in sequence, including the MIE (if known) and AO, and the pair-wise relationships (links or KERs) between those KEs should be provided. This is easily achieved using the standard box and arrow AOP diagram (see this page for example). The graphical summary is prepared and uploaded by the user (templates are available) and is often included as part of the proposal when AOP development projects are submitted to the OECD AOP Development Workplan. The graphical representation or AOP diagram provides a useful and concise overview of the KEs that are included in the AOP, and the sequence in which they are linked together. This can aid both the process of development, as well as review and use of the AOP (for more information please see page 19 of the Users' Handbook).If you already have a graphical representation of your AOP in electronic format, simple save it in a standard image format (e.g. jpeg, png) then click ‘Choose File’ under the “Graphical Representation” heading, which is part of the Summary of the AOP section, to select the file that you have just edited. Files must be in jpeg, jpg, gif, png, or bmp format. Click ‘Upload’ to upload the file. You should see the AOP page with the image displayed under the “Graphical Representation” heading. To remove a graphical representation file, click 'Remove' and then click 'OK.'  Your graphic should no longer be displayed on the AOP page. If you do not have a graphical representation of your AOP in electronic format, a template is available to assist you.  Under “Summary of the AOP”, under the “Graphical Representation” heading click on the link “Click to download template for graphical representation.” A Powerpoint template file should download via the default download mechanism for your browser. Click to open this file; it contains a Powerpoint template for an AOP diagram and instructions for editing and saving the diagram. Be sure to save the diagram as jpeg, jpg, gif, png, or bmp format. Once the diagram is edited to its final state, upload the image file as described above. More help


List the name and affiliation information of the individual(s)/organisation(s) that created/developed the AOP. In the context of the OECD AOP Development Workplan, this would typically be the individuals and organisation that submitted an AOP development proposal to the EAGMST. Significant contributors to the AOP should also be listed. A corresponding author with contact information may be provided here. This author does not need an account on the AOP-KB and can be distinct from the point of contact below. The list of authors will be included in any snapshot made from an AOP. More help

Dan Villeneuve, US EPA Mid-Continent Ecology Division (

Point of Contact

Indicate the point of contact for the AOP-KB entry itself. This person is responsible for managing the AOP entry in the AOP-KB and controls write access to the page by defining the contributors as described below. Clicking on the name will allow any wiki user to correspond with the point of contact via the email address associated with their user profile in the AOP-KB. This person can be the same as the corresponding author listed in the authors section but isn’t required to be. In cases where the individuals are different, the corresponding author would be the appropriate person to contact for scientific issues whereas the point of contact would be the appropriate person to contact about technical issues with the AOP-KB entry itself. Corresponding authors and the point of contact are encouraged to monitor comments on their AOPs and develop or coordinate responses as appropriate.  More help
Cataia Ives   (email point of contact)


List user names of all  authors contributing to or revising pages in the AOP-KB that are linked to the AOP description. This information is mainly used to control write access to the AOP page and is controlled by the Point of Contact.  More help
  • Dan Villeneuve
  • Cataia Ives


The status section is used to provide AOP-KB users with information concerning how actively the AOP page is being developed, what type of use or input the authors feel comfortable with given the current level of development, and whether it is part of the OECD AOP Development Workplan and has been reviewed and/or endorsed. “Author Status” is an author defined field that is designated by selecting one of several options from a drop-down menu (Table 3). The “Author Status” field should be changed by the point of contact, as appropriate, as AOP development proceeds. See page 22 of the User Handbook for definitions of selection options. More help
Author status OECD status OECD project SAAOP status
Open for citation & comment WPHA/WNT Endorsed 1.12 Included in OECD Work Plan
This AOP was last modified on May 08, 2022 11:33
The date the AOP was last modified is automatically tracked by the AOP-KB. The date modified field can be used to evaluate how actively the page is under development and how recently the version within the AOP-Wiki has been updated compared to any snapshots that were generated. More help

Revision dates for related pages

Page Revision Date/Time
Decrease, Population growth rate March 29, 2022 11:50
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


In the abstract section, authors should provide a concise and informative summation of the AOP under development that can stand-alone from the AOP page. Abstracts should typically be 200-400 words in length (similar to an abstract for a journal article). Suggested content for the abstract includes the following: The background/purpose for initiation of the AOP’s development (if there was a specific intent) A brief description of the MIE, AO, and/or major KEs that define the pathway A short summation of the overall WoE supporting the AOP and identification of major knowledge gaps (if any) If a brief statement about how the AOP may be applied (optional). 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.

Background (optional)

This optional subsection should be 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. Examples of potential uses of the optional background section are listed on pages 24-25 of the User Handbook. 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


Molecular Initiating Events (MIE)
An MIE is a specialised KE that represents the beginning (point of interaction between a stressor and the biological system) of an AOP. More help
Key Events (KE)
This table summarises all of the KEs of the AOP. This table is populated in the AOP-Wiki as KEs are added to the AOP. Each table entry acts as a link to the individual KE description page.  More help
Adverse Outcomes (AO)
An AO is a specialised KE that represents the end (an adverse outcome of regulatory significance) of an AOP.  More help
Sequence Type Event ID Title Short name
1 MIE 36 Inhibition, Aromatase Inhibition, Aromatase
2 KE 219 Reduction, Plasma 17beta-estradiol concentrations Reduction, Plasma 17beta-estradiol concentrations
3 KE 285 Reduction, Vitellogenin synthesis in liver Reduction, Vitellogenin synthesis in liver
4 KE 309 Reduction, Vitellogenin accumulation into oocytes and oocyte growth/development Reduction, Vitellogenin accumulation into oocytes and oocyte growth/development
5 KE 3 Reduction, 17beta-estradiol synthesis by ovarian granulosa cells Reduction, 17beta-estradiol synthesis by ovarian granulosa cells
6 KE 78 Reduction, Cumulative fecundity and spawning Reduction, Cumulative fecundity and spawning
7 KE 221 Reduction, Plasma vitellogenin concentrations Reduction, Plasma vitellogenin concentrations
8 AO 360 Decrease, Population growth rate Decrease, Population growth rate

Relationships Between Two Key Events (Including MIEs and AOs)

This table summarises 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.To add a key event relationship click on either Add relationship: events adjacent in sequence or Add relationship: events non-adjacent in sequence.For example, if the intended sequence of KEs for the AOP is [KE1 > KE2 > KE3 > KE4]; relationships between KE1 and KE2; KE2 and KE3; and KE3 and KE4 would be defined using the add relationship: events adjacent in sequence button.  Relationships between KE1 and KE3; KE2 and KE4; or KE1 and KE4, for example, should be created using the add relationship: events non-adjacent button. This helps to both organize the table with regard to which KERs define the main sequence of KEs and those that provide additional supporting evidence and aids computational analysis of AOP networks, where non-adjacent KERs can result in artifacts (see Villeneuve et al. 2018; DOI: 10.1002/etc.4124).After clicking either option, the user will be brought to a new page entitled ‘Add Relationship to AOP.’ To create a new relationship, select an upstream event and a downstream event from the drop down menus. The KER will automatically be designated as either adjacent or non-adjacent depending on the button selected. The fields “Evidence” and “Quantitative understanding” can be selected from the drop-down options at the time of creation of the relationship, or can be added later. See the Users Handbook, page 52 (Assess Evidence Supporting All KERs for guiding questions, etc.).  Click ‘Create [adjacent/non-adjacent] relationship.’  The new relationship should be listed on the AOP page under the heading “Relationships Between Two Key Events (Including MIEs and AOs)”. To edit a key event relationship, click ‘Edit’ next to the name of the relationship you wish to edit. The user will be directed to an Editing Relationship page where they can edit the Evidence, and Quantitative Understanding fields using the drop down menus. Once finished editing, click ‘Update [adjacent/non-adjacent] relationship’ to update these fields and return to the AOP page.To remove a key event relationship to an AOP page, under Summary of the AOP, next to “Relationships Between Two Key Events (Including MIEs and AOs)” click ‘Remove’ The relationship should no longer be listed on the AOP page under the heading “Relationships Between Two Key Events (Including MIEs and AOs)”. More help

Network View

The AOP-Wiki automatically generates a network view of the AOP. This network graphic is based on the information provided in the MIE, KEs, AO, KERs and 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


The stressor field is a structured data field that can be used to annotate an AOP with standardised terms identifying stressors known to trigger the MIE/AOP. Most often these are chemical names selected from established chemical ontologies. However, depending on the information available, this could also refer to chemical categories (i.e., groups of chemicals with defined structural features known to trigger the MIE). It can also include non-chemical stressors such as genetic or environmental factors. Although AOPs themselves are not chemical or stressor-specific, linking to stressor terms known to be relevant to different AOPs can aid users in searching for AOPs that may be relevant to a given stressor. More help

Life Stage Applicability

Identify the life stage for which the KE 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 in relation to this KE. 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 authors must select from one of the following: Male, female, mixed, asexual, third gender, hermaphrodite, or unspecific. More help
Sex Evidence
Female High

Overall Assessment of the AOP

This section addresses the relevant biological domain of applicability (i.e., in terms of taxa, sex, life stage, etc.) and WoE for the overall AOP as a basis to consider appropriate regulatory application (e.g., priority setting, testing strategies or risk assessment). The goal of the overall assessment is to provide a high level synthesis and overview of the relative confidence in the AOP and where the significant gaps or weaknesses are (if they exist). Users or readers can drill down into the finer details captured in the KE and KER descriptions, and/or associated summary tables, as appropriate to their needs.Assessment of the AOP is organised into a number of steps. Guidance on pages 59-62 of the User Handbook is available to facilitate assignment of categories of high, moderate, or low confidence for each consideration. While it is not necessary to repeat lengthy text that appears elsewhere in the AOP description (or related KE and KER descriptions), a brief explanation or rationale for the selection of high, moderate, or low confidence should be made. More help

Domain of Applicability

The relevant biological domain(s) of applicability in terms of sex, life-stage, taxa, and other aspects of biological context are defined in this section. Biological domain of applicability is informed by the “Description” and “Biological Domain of Applicability” sections of each KE and KER description (see sections 2G and 3E for details). In essence the taxa/life-stage/sex applicability is defined based on the groups of organisms for which the measurements represented by the KEs can feasibly be measured and the functional and regulatory relationships represented by the KERs are operative.The relevant biological domain of applicability of the AOP as a whole will nearly always be defined based on the most narrowly restricted of its KEs and KERs. For example, if most of the KEs apply to either sex, but one is relevant to females only, the biological domain of applicability of the AOP as a whole would be limited to females. While much of the detail defining the domain of applicability may be found in the individual KE and KER descriptions, the rationale for defining the relevant biological domain of applicability of the overall AOP should be briefly summarised on the AOP page. 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

An important aspect of assessing an AOP is evaluating the essentiality of its KEs. 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.When assembling the support for essentiality of the KEs, authors should organise relevant data in a tabular format. The objective is to summarise briefly the nature and numbers of investigations in which the essentiality of KEs has been experimentally explored either directly or indirectly. See pages 50-51 in the User Handbook for further definitions and clarifications.  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

The biological plausibility, empirical support, and quantitative understanding from each KER in an AOP are assessed together.  Biological plausibility of each of the KERs in the AOP is the most influential consideration in assessing WoE or degree of confidence in an overall hypothesised AOP for potential regulatory application (Meek et al., 2014; 2014a). Empirical support entails consideration of experimental data in terms of the associations between KEs – namely dose-response concordance and temporal relationships between and across multiple KEs. It is examined most often in studies of dose-response/incidence and temporal relationships for stressors that impact the pathway. While less influential than biological plausibility of the KERs and essentiality of the KEs, empirical support can increase confidence in the relationships included in an AOP. For clarification on how to rate the given empirical support for a KER, as well as examples, see pages 53- 55 of the User Handbook.  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.

Quantitative Understanding

Some proof of concept examples to address the WoE considerations for AOPs quantitatively have recently been developed, based on the rank ordering of the relevant Bradford Hill considerations (i.e., biological plausibility, essentiality and empirical support) (Becker et al., 2017; Becker et al, 2015; Collier et al., 2016). Suggested quantitation of the various elements is expert derived, without collective consideration currently of appropriate reporting templates or formal expert engagement. Though not essential, developers may wish to assign comparative quantitative values to the extent of the supporting data based on the three critical Bradford Hill considerations for AOPs, as a basis to contribute to collective experience.Specific attention is also given to how precisely and accurately one can potentially predict an impact on KEdownstream based on some measurement of KEupstream. This is captured in the form of quantitative understanding calls for each KER. See pages 55-56 of the User Handbook for a review of quantitative understanding for KER's. 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), but those predictions have not yet been validated experimentally. The present models are also unable to account for pharmacokinetic considerations (e.g., adsorption, distribution, metabolism/biotransformation, and elimination) and have demonstrated only partial success in simulating compensatory/feedback responses to aromatase inhibition (e.g., (Breen et al. 2013).

Considerations for Potential Applications of the AOP (optional)

At their discretion, the developer may include in this section discussion of the 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. While it is challenging to foresee all potential regulatory application of AOPs and any application will ultimately lie within the purview of regulatory agencies, potential applications may be apparent as the AOP is being developed, particularly if it was initiated with a particular application in mind. This optional section is intended to provide the developer with an opportunity to suggest potential regulatory applications and describe his or her rationale.To edit the “Considerations for Potential Applications of the AOP” section, on an AOP page, in the upper right hand menu, click ‘Edit.’ This brings you to a page entitled, “Editing AOP.” Scroll down to the “Considerations for Potential Applications of the AOP” section, where a text entry box allows you to submit text. In the upper right hand menu, click ‘Update AOP’ to save your changes and return to the AOP page or 'Update and continue' to continue editing AOP text sections.  The new text should appear under the “Considerations for Potential Applications of the AOP” section on the AOP page. 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.


List the bibliographic references to original papers, books or other documents used to support the 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.