This Key Event Relationship is licensed under the Creative Commons BY-SA license. This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. If you remix, adapt, or build upon the material, you must license the modified material under identical terms.

Relationship: 302

Title

A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

Reduction, Testosterone synthesis by ovarian theca cells leads to Reduction, 17beta-estradiol synthesis by ovarian granulosa cells

Upstream event

The causing Key Event (KE) in a Key Event Relationship (KER). More help

Reduction, Testosterone synthesis by ovarian theca cells

Downstream event

The responding Key Event (KE) in a Key Event Relationship (KER). More help

Reduction, 17beta-estradiol synthesis by ovarian granulosa cells

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes.Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

AOP Name	Adjacency	Weight of Evidence	Quantitative Understanding	Point of Contact	Author Status	OECD Status
Androgen receptor agonism leading to reproductive dysfunction (in repeat-spawning fish)	adjacent	High	Low	Dan Villeneuve (send email)	Open for citation & comment	WPHA/WNT Endorsed

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KER.In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER. More help

Term	Scientific Term	Evidence	Link
fathead minnow	Pimephales promelas	Moderate	NCBI
Fundulus heteroclitus	Fundulus heteroclitus	Moderate	NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help

Sex	Evidence
Unspecific	Not Specified

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER. More help

Term	Evidence
Adult, reproductively mature	Moderate

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

Figure 1. Overview of steroid biosynthesis pathway. Note, testosterone is converted to 17ß-estradiol through aromatization catalyzed by cyp19 (aromatase).

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER. For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings. Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

Evidence Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help

Biological Plausibility

Addresses the biological rationale for a connection between KEupstream and KEdownstream. This field can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured. More help

Theca cell-derived androgens (e.g., testosterone, androstenedione) are precursors for estrogen (e.g., 17β-estradiol, estrone) synthesis. Androgens secreted from the theca cells are aromatized to estrogens in the ovarian granulosa cells (Norris 2007; Senthilkumaran et al. 2004). Consequently, reductions in theca cell testosterone synthesis can be expected to reduce the rate of estradiol synthesis by the ovarian granulosa cells (Payne and Hales 2004; Miller 1988; Nagahama et al. 1993).

Empirical Evidence

Provides specific (citable) evidence that supports the idea of a change in the upstream KE (KEupstream) leading to, or being associated with, a subsequent change in the downstream KE (KEdownstream), assuming the perturbation of KEupstream is sufficient. More help

Ex vivo T production by ovary tissue collected from female fathead minnows exposed in vivo to 33 or 472 ng 17β-trenbolone/L was significantly reduced after 24 or 48 h of exposure (Ekman et al. 2011). Reductions in ex vivo T production preceded significant reductions in ex vivo E2 production.
Ketoconazole is a fungicide thought to inhibit CYP11A and CYP17 (both involved in theca cell androgen production) with greater potency than it inhibits CYP19 (aromatase) (Villeneuve et al. 2007). Ex vivo E2 and T production were significantly reduced following exposure to 30 or 300 μg ketoconazole/L (Ankley et al. 2012).

Uncertainties and Inconsistencies

Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance. More help

No significant inconsistencies identified to date. However, the literature review on this topic has not been comprehensive.

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references. More help

Quantitative Understanding of the Linkage

Captures information that helps to define how much change in the upstream KE, and/or for how long, is needed to elicit a detectable and defined change in the downstream KE. More help

At present we are unaware of any well established quantitative relationships between ex vivo T production (as an indirect measure of theca cell T synthesis) and ex vivo E2 production (as an indirect measure of granulosa cell E2 synthesis). There are considerable data available which might support the development of such a relationship. Additionally, there are a number of existing mathematical/computational models of ovarian steroidogenesis that may be adaptable to support a quantitative understanding of this linkage (Breen et al. 2007; Shoemaker et al. 2010; Quignot and Bois 2013).

Response-response Relationship

Provides sources of data that define the response-response relationships between the KEs. More help

Time-scale

Information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). More help

Known Feedforward/Feedback loops influencing this KER

Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help

Enzymes required for testosterone and 17ß-estradiol synthesis are only found in vertebrates and amphioxus (Markov et al. 2009; Baker 2011). They are not present in invertebrates. Consequently, this KER is not applicable to invertebrates.

References

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

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.
Baker ME. 2011. Origin and diversification of steroids: Co-evolution of enzymes and nuclear receptors. Mol Cell Endocrinol 334: 14-20.
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.
Ekman DR, Villeneuve DL, Teng Q, Ralston-Hooper KJ, Martinovic-Weigelt D, Kahl MD, et al. 2011. Use of gene expression, biochemical and metabolite profiles to enhance exposure and effects assessment of the model androgen 17beta-trenbolone in fish. Environmental toxicology and chemistry / SETAC 30(2): 319-329.
Markov GV, Tavares R, Dauphin-Villemant C, Demeneix BA, Baker ME, Laudet V. Independent elaboration of steroid hormone signaling pathways in metazoans. Proc Natl Acad Sci U S A. 2009 Jul 21;106(29):11913-8. doi: 10.1073/pnas.0812138106.
Miller WL. 1988. Molecular biology of steroid hormone synthesis. Endocrine reviews 9(3): 295-318.
Nagahama Y, Yoshikumi M, Yamashita M, Sakai N, Tanaka M. 1993. Molecular endocrinology of oocyte growth and maturation in fish. Fish Physiology and Biochemistry 11: 3-14.
Norris DO. 2007. Vertebrate Endocrinology. Fourth ed. New York: Academic Press.
Payne AH, Hales DB. 2004. Overview of steroidogenic enzymes in the pathway from cholesterol to active steroid hormones. Endocrine reviews 25(6): 947-970.
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.
Senthilkumaran B, Yoshikuni M, Nagahama Y. A shift in steroidogenesis occurring in ovarian follicles prior to oocyte maturation. Mol Cell Endocrinol. 2004 Feb 27;215(1-2):11-8.
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.
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.