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Relationship: 45

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

Inhibition, Aromatase 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
Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER). More help

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
Aromatase inhibition leading to reproductive dysfunction adjacent High Moderate 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

Sex Applicability

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

Life Stage Applicability

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

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

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

Within the ovary, aromatase expression and activity is primarily localized in the granulosa cells (reviewed in (Norris 2007; Yaron 1995; Havelock et al. 2004) and others). C-19 androgens diffuse from the theca cells into granulosa cells where aromatase can catalyze their conversion to C-18 estrogens. Therefore, inhibition of ovarian aromatase activity can generally be assumed to directly impact E2 synthesis by the granulosa cells.

 

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

Based on the limited set of studies available to date, there are no known inconsistencies.

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
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

Aromatase (CYP19) orthologs are known to be present among most of the vertebrate lineage, at least down to the cartilaginous fishes. Orthologs have generally not been found in invertebrates, however, CYP19 was detected in the invertebrate chordate, amphioxus and analysis of conservation of gene order and content suggests a possible origin among primitive chordates (Castro et al. 2005).

References

List of the literature that was cited for this KER description. More help
  • Norris DO. 2007. Vertebrate Endocrinology. Fourth ed. New York: Academic Press.
  • Yaron Z. 1995. Endocrine control of gametogenesis and spawning induction in the carp. Aquaculture 129: 49-73.
  • Havelock JC, Rainey WE, Carr BR. 2004. Ovarian granulosa cell lines. Molecular and cellular endocrinology 228(1-2): 67-78.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.