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Relationship: 253

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, Plasma 17beta-estradiol concentrations leads to Reduction, Vitellogenin accumulation into oocytes and oocyte growth/development

Upstream event

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

Reduction, Plasma 17beta-estradiol concentrations

Downstream event

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

Reduction, Vitellogenin accumulation into oocytes and oocyte growth/development

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

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

Vitellogenin synthesized in the liver and transported to the ovary via the circulation is the primary source of egg yolk proteins in fish (Tyler and Sumpter 1996; Arukwe and Goksøyr 2003). In many teleosts vitellogenesis can account for up to 95% of total egg size (Tyler and Sumpter 1996).

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

Include consideration of temporal concordance here

In some (Ankley et al. 2002; Ankley et al. 2003; Lalone et al. 2013), but not all (Ankley et al. 2005; Sun et al. 2007; Skolness et al. 2013) fish reproduction studies, reductions in plasma vitellogenin have been associated with visible decreases in yolk protein content in oocytes and overall reductions in ovarian stage.

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

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

Is it known how much change in the first event is needed to impact the second? Are there known modulators of the response-response relationships? Are there models or extrapolation approaches that help describe those relationships?

Rates of vitellogenin uptake as a function of ovarian follicle surface area have been estimated for rainbow trout, an annual spawning fish species, and may exceed 700 ng/mm2 follicle surface per hour (Tyler and Sumpter 1996). However, comparable data are lacking for repeat-spawning species and kinetic relationships between plasma concentrations and uptake rates within the ovary have not been defined. A model based on a statistical relationship between plasma E2 concentrations, spawning interval, and cumulative fecundity has been developed to predict changes in cumulative fecundity from plasma VTG (Li et al. 2011b), but it does not incorporate a model of the kinetics of VTG uptake nor the influence of VTG uptake on oocyte growth.

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

References

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

Tyler C, Sumpter J. 1996. Oocyte growth and development in teleosts. Reviews in Fish Biology and Fisheries 6: 287-318.
Arukwe A, Goksøyr A. 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.
Ankley GT, Jensen KM, Makynen EA, Kahl MD, Korte JJ, Hornung MW, et al. 2003. Effects of the androgenic growth promoter 17--trenbolone on fecundity and reproductive endocrinology of the fathead minnow. Environmental Toxicology and Chemistry 22(6): 1350-1360.
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.
Lalone CA, Villeneuve DL, Cavallin JE, Kahl MD, Durhan EJ, Makynen EA, et al. 2013. Cross species sensitivity to a novel androgen receptor agonist of environmental concern, spironolactone. Environmental toxicology and chemistry / SETAC (in press).
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.
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.
Skolness SY, Blanksma CA, Cavallin JE, Churchill JJ, Durhan EJ, Jensen KM, et al. 2013. Propiconazole Inhibits Steroidogenesis and Reproduction in the Fathead Minnow (Pimephales promelas). Toxicological sciences : an official journal of the Society of Toxicology 132(2): 284-297.
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.