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Relationship: 1385

Title

The title of the KER should clearly define the two KEs being considered and the sequential relationship between them (i.e., which is upstream and which is downstream). Consequently all KER titles take the form “upstream KE leads to downstream KE”.  More help

Agonism, Androgen receptor leads to Reduction, Vitellogenin synthesis in liver

Upstream event
Upstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help
Downstream event
Downstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. 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

This table is automatically generated upon addition of a KER to an AOP. All of the AOPs that are linked to this KER will automatically be listed in this subsection. Clicking on the name of the AOP in the table will bring you to the individual page for that AOP. More help
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) non-adjacent High Low Dan Villeneuve (send email) Open for citation & comment WPHA/WNT Endorsed

Taxonomic Applicability

Select one or more structured terms 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. Authors can indicate the relevant taxa for this KER in this subsection. The process is similar to what is described for KEs (see pages 30-31 and 37-38 of User Handbook) More help
Term Scientific Term Evidence Link
fathead minnow Pimephales promelas High NCBI
Danio rerio Danio rerio Moderate NCBI
medaka Oryzias latipes Moderate NCBI
Fundulus heteroclitus Fundulus heteroclitus High NCBI

Sex Applicability

Authors can indicate the relevant sex for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of the User Handbook). More help
Sex Evidence
Female High

Life Stage Applicability

Authors can indicate the relevant life stage for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of User Handbook). More help
Term Evidence
Adult, reproductively mature High

Key Event Relationship Description

Provide a brief, descriptive summation of the KER. While the title itself is fairly descriptive, this section can provide details that aren’t inherent in the description of the KEs themselves (see page 39 of the User Handbook). This description section can be viewed as providing the increased specificity in the nature of upstream perturbation (KEupstream) that leads to a particular downstream perturbation (KEdownstream), while allowing the KE descriptions to remain generalised so they can be linked to different AOPs. The description is also intended to provide a concise overview for readers who may want a brief summation, without needing to read through the detailed support for the relationship (covered below). Careful attention should be taken to avoid reference to other KEs that are not part of this KER, other KERs or other AOPs. This will ensure that the KER is modular and can be used by other AOPs. More help

At present, a direct structural/functional linkage between androgen receptor agonism and reduced plasma vitellogenin concentrations is not known. Consequently, the relationship is supported primarily via association/correlation.

Evidence Supporting this KER

Assembly and description of the scientific evidence supporting KERs in an AOP is an important step in the AOP development process that sets the stage for overall assessment of the AOP (see pages 49-56 of the User Handbook). To do this, biological plausibility, empirical support, and the current quantitative understanding of the KER are evaluated with regard to the predictive relationships/associations between defined pairs of KEs as a basis for considering WoE (page 55 of User Handbook). In addition, uncertainties and inconsistencies are considered. More help

Updated 2017-03-17.

Biological Plausibility
Define, in free text, the biological rationale for a connection between KEupstream and KEdownstream. What are the structural or functional relationships between the KEs? For example, there is a functional relationship between an enzyme’s activity and the product of a reaction it catalyses. Supporting references should be included. However, it is recognised that there may be cases where the biological relationship between two KEs is very well established, to the extent that it is widely accepted and consistently supported by so much literature that it is unnecessary and impractical to cite the relevant primary literature. Citation of review articles or other secondary sources, like text books, may be reasonable in such cases. The primary intent is to provide scientifically credible support for the structural and/or functional relationship between the pair of KEs if one is known. The description of biological plausibility 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 (see page 40 of the User Handbook for further information).   More help

Synthesis of the steroidogenic enzymes that catalyze the formation of testosterone from cholesterol as a precursor as well as 17ß-estradiol (E2) from testosterone is stimulated by gonadotropins whose synthesis and secretion are in turn regulated by gonadotropin releasing hormone (GnRH) released from the hypothalamus (Payne and Hales 2004; Norris 2007; Miller 1988). Strong AR agonists are thought to exert negative feedback along the hypothalamic-pituitary-gonadal axis, leading to decreased stimulation of the steroidogenic pathway and subsequent declines in E2 production. E2 is known to be a major regulator of hepatic vitellogenin production (Tyler et al. 1996; Tyler and Sumpter 1996; Arukwe and GoksØyr 2003).

Uncertainties and Inconsistencies
In addition to outlining the evidence supporting a particular linkage, it is also important to identify inconsistencies or uncertainties in the relationship. Additionally, while there are expected patterns of concordance that support a causal linkage between the KEs in the pair, it is also helpful to identify experimental details that may explain apparent deviations from the expected patterns of concordance. Identification of uncertainties and inconsistencies contribute to evaluation of the overall WoE supporting the AOPs that contain a given KER and to the identification of research gaps that warrant investigation (seep pages 41-42 of the User Handbook).Given that AOPs are intended to support regulatory applications, AOP developers should focus on those inconsistencies or gaps that would have a direct bearing or impact on the confidence in the KER and its use as a basis for inference or extrapolation in a regulatory setting. Uncertainties that may be of academic interest but would have little impact on regulatory application don’t need to be described. In general, this section details evidence that may raise questions regarding the overall validity and predictive utility of the KER (including consideration of both biological plausibility and empirical support). It also contributes along with several other elements to the overall evaluation of the WoE for the KER (see Section 4 of the User Handbook).  More help

None noted.

Response-response Relationship
This subsection should be used to define sources of data that define the response-response relationships between the KEs. In particular, information regarding the general form of the relationship (e.g., linear, exponential, sigmoidal, threshold, etc.) should be captured if possible. If there are specific mathematical functions or computational models relevant to the KER in question that have been defined, those should also be cited and/or described where possible, along with information concerning the approximate range of certainty with which the state of the KEdownstream can be predicted based on the measured state of the KEupstream (i.e., can it be predicted within a factor of two, or within three orders of magnitude?). For example, a regression equation may reasonably describe the response-response relationship between the two KERs, but that relationship may have only been validated/tested in a single species under steady state exposure conditions. Those types of details would be useful to capture.  More help
Time-scale
This sub-section should be used to provide 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?). This can be useful information both in terms of modelling the KER, as well as for analyzing the critical or dominant paths through an AOP network (e.g., identification of an AO that could kill an organism in a matter of hours will generally be of higher priority than other potential AOs that take weeks or months to develop). Identification of time-scale can also aid the assessment of temporal concordance. For example, for a KER that operates on a time-scale of days, measurement of both KEs after just hours of exposure in a short-term experiment could lead to incorrect conclusions regarding dose-response or temporal concordance if the time-scale of the upstream to downstream transition was not considered. More help
Known modulating factors
This sub-section presents information regarding modulating factors/variables known to alter the shape of the response-response function that describes the quantitative relationship between the two KEs (for example, an iodine deficient diet causes a significant increase in the slope of the relationship; a particular genotype doubles the sensitivity of KEdownstream to changes in KEupstream). Information on these known modulating factors should be listed in this subsection, along with relevant information regarding the manner in which the modulating factor can be expected to alter the relationship (if known). Note, this section should focus on those modulating factors for which solid evidence supported by relevant data and literature is available. It should NOT list all possible/plausible modulating factors. In this regard, it is useful to bear in mind that many risk assessments conducted through conventional apical guideline testing-based approaches generally consider few if any modulating factors. More help
Known Feedforward/Feedback loops influencing this KER
This subsection should define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits? In some cases where feedback processes are measurable and causally linked to the outcome, they should be represented as KEs. However, in most cases these features are expected to predominantly influence the shape of the response-response, time-course, behaviours between selected KEs. For example, if a feedback loop acts as compensatory mechanism that aims to restore homeostasis following initial perturbation of a KE, the feedback loop will directly shape the response-response relationship between the KERs. Given interest in formally identifying these positive or negative feedback, it is recommended that a graphical annotation (page 44) indicating a positive or negative feedback loop is involved in a particular upstream to downstream KE transition (KER) be added to the graphical representation, and that details be provided in this subsection of the KER description (see pages 44-45 of the User Handbook).  More help

Domain of Applicability

As for the KEs, there is also a free-text section of the KER description that the developer can use to explain his/her rationale for the structured terms selected with regard to taxonomic, life stage, or sex applicability, or provide a more generalizable or nuanced description of the applicability domain than may be feasible using standardized terms. More help

This KER is potentially applicable to reproductively mature, adult, oviparous vertebrates.

  • Androgen receptor orthologs are primarily limited to vertebrates (Baker 1997; Thornton 2001; Eick and Thornton 2011; Markov and Laudet 2011). 
  • Oviparous vertebrates synthesize yolk precursor proteins that are transported in the circulation for uptake by developing oocytes. Many invertebrates also synthesize vitellogenins that are taken up into developing oocytes via active transport mechanisms. However, invertebrate vitellogenins are transported in hemolymph or via other transport mechanisms rather than plasma.

References

List of the literature that was cited for this KER description using the appropriate format. Ideally, the list of references should conform, to the extent possible, with the OECD Style Guide (OECD, 2015). More help
  • Ankley GT, Jensen KM, Kahl MD, Durhan EJ, Makynen EA, Cavallin JE, Martinović D, Wehmas LC, Mueller ND, Villeneuve DL. Use of chemical mixtures to differentiate mechanisms of endocrine action in a small fish model. Aquat Toxicol. 2010 Sep 1;99(3):389-96. doi: 10.1016/j.aquatox.2010.05.020.
  • 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.
  • Baker ME. 1997. Steroid receptor phylogeny and vertebrate origins. Molecular and cellular endocrinology 135(2): 101-107.
  • Eick GN, Thornton JW. 2011. Evolution of steroid receptors from an estrogen-sensitive ancestral receptor. Molecular and cellular endocrinology 334(1-2): 31-38.
  • Ekman DR, Villeneuve DL, Teng Q, Ralston-Hooper KJ, Martinović-Weigelt D, Kahl MD, Jensen KM, Durhan EJ, Makynen EA, Ankley GT, Collette TW. Use of gene expression, biochemical and metabolite profiles to enhance exposure and effects assessment of the model androgen 17β-trenbolone in fish. Environ Toxicol Chem. 2011 Feb;30(2):319-29. doi: 10.1002/etc.406.
  • Jensen KM, Makynen EA, Kahl MD, Ankley GT. Effects of the feedlot contaminant 17alpha-trenbolone on reproductive endocrinology of the fathead minnow. Environ Sci Technol. 2006 May 1;40(9):3112-7.
  • Jolly C, Katsiadaki I, Le Belle N, Mayer I, Dufour S. 2006. Development of a stickleback kidney cell culture assay for the screening of androgenic and anti-androgenic endocrine disrupters. Aquatic toxicology 79(2): 158-166.
  • LaLone CA, Villeneuve DL, Cavallin JE, Kahl MD, Durhan EJ, Makynen EA, Jensen KM, Stevens KE, Severson MN, Blanksma CA, Flynn KM, Hartig PC, Woodard JS, Berninger JP, Norberg-King TJ, Johnson RD, Ankley GT. Cross-species sensitivity to a novel androgen receptor agonist of potential environmental concern, spironolactone. Environ Toxicol Chem. 2013 Nov;32(11):2528-41. doi: 10.1002/etc.2330.
  • Li Z, Kroll KJ, Jensen KM, Villeneuve DL, Ankley GT, Brian JV, Sepúlveda MS, Orlando EF, Lazorchak JM, Kostich M, Armstrong B, Denslow ND, Watanabe KH. A computational model of the hypothalamic: pituitary: gonadal axis in female fathead minnows (Pimephales promelas) exposed to 17α-ethynylestradiol and 17β-trenbolone. BMC Syst Biol. 2011 May 5;5:63. doi: 10.1186/1752-0509-5-63.
  • Markov GV, Laudet V. 2011. Origin and evolution of the ligand-binding ability of nuclear receptors. Molecular and cellular endocrinology 334(1-2): 21-30.
  • Miller WL. 1988. Molecular biology of steroid hormone synthesis. Endocrine reviews 9(3): 295-318.
  • 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.
  • Rutherford R, Lister A, Hewitt LM, MacLatchy D. Effects of model aromatizable (17α-methyltestosterone) and non-aromatizable (5α-dihydrotestosterone) androgens on the adult mummichog (Fundulus heteroclitus) in a short-term reproductive endocrine bioassay. Comp Biochem Physiol C Toxicol Pharmacol. 2015 Apr;170:8-18. doi: 10.1016/j.cbpc.2015.01.004.
  • Seki M, Fujishima S, Nozaka T, Maeda M, Kobayashi K. Comparison of response to 17 beta-estradiol and 17 beta-trenbolone among three small fish species. Environ Toxicol Chem. 2006 Oct;25(10):2742-52.
  • Sharpe RL, MacLatchy DL, Courtenay SC, Van Der Kraak GJ. Effects of a model androgen (methyl testosterone) and a model anti-androgen (cyproterone acetate) on reproductive endocrine endpoints in a short-term adult mummichog (Fundulus heteroclitus) bioassay. Aquat Toxicol. 2004 Apr 28;67(3):203-15.
  • Thornton JW. 2001. Evolution of vertebrate steroid receptors from an ancestral estrogen receptor by ligand exploitation and serial genome expansions. Proceedings of the National Academy of Sciences of the United States of America 98(10): 5671-5676.
  • Tyler C, Sumpter J. 1996. Oocyte growth and development in teleosts. Reviews in Fish Biology and Fisheries 6: 287-318.
  • 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.
  • Villeneuve DL, Jensen KM, Cavallin JE, Durhan EJ, Garcia-Reyero N, Kahl MD, Leino RL, Makynen EA, Wehmas LC, Perkins EJ, Ankley GT. Effects of the antimicrobial contaminant triclocarban, and co-exposure with the androgen 17β-trenbolone, on reproductive function and ovarian transcriptome of the fathead minnow (Pimephales promelas). Environ Toxicol Chem. 2017 Jan;36(1):231-242. doi: 10.1002/etc.3531.
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