To the extent possible under law, AOP-Wiki has waived all copyright and related or neighboring rights to KER:396

Relationship: 396

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

reduction in ovarian granulosa cells, Aromatase (Cyp19a1) leads to Reduction, 17beta-estradiol synthesis by ovarian granulosa cells

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
Aromatase (Cyp19a1) reduction leading to impaired fertility in adult female adjacent Moderate Allie Always (send email) Open for citation & comment EAGMST Under Review

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

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

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

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

Aromatase is the cytochrome P450 enzyme complex responsible for the conversion of androgens to estrogens during steroidogenesis [reviewed by (Simpson et al., 1994)], which is a key reaction in the sex differentiation in vertebrates. Reduction in level of aromatase or in the catalytic activity of the aromatase itself will reduce the levels of estrogens in tissues and dramatically disrupt estrogen (E2) hormone action.

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
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

Aromatase in the specialized cells of the ovary, hypothalamus, and placenta clearly serves crucial role in reproduction for mammalian and other vertebrates by converting the androgens to estrogens. Therefore, the coordinated and cell-specific expression of the aromatase (Cyp19a1) gene in the ovary plays a key role in the 17beta-estradiol (E2) synthesis. Within the ovary, aromatase expression and activity is primarily localized in the granulosa cells (reviewed in (Havelock, Rainey, & Carr, 2004). C-19 androgens diffuse from the theca cells into granulosa cells where aromatase can catalyze their conversion to C-18 estrogens. Therefore, inhibition, decrease of level or activity of ovarian aromatase can generally be assumed to directly impact E2 synthesis by the granulosa cells.

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

Upstream events An upstream event has been postulated to involve PPARγ activation, however the studies confirming its role in the reduction of aromatase levels are incomplete. The mechanisms involving Peroxisome Proliferator Activated receptor γ activation leading to aromatase (Cyp19a1) reduction relating to the pathway are described in greater detail in the page Peroxisome Proliferator Activated receptor γ activation indirectly leads to aromatase (Cyp19a1) reduction .

Availability or reduced aromatase levels

Studies by Davis et al showed that MEHP impacts on availability (degradation) of aromatase as the decrease in E2 production is evident after the treatment with transcription and translation blockers (actinomycin D or cycloheximide). MEHP was further decreased E2 production independently of the presence of inhibitors pointing out at mechanisms of degradation rather than aromatase synthesis (Davis et al., 1994). MEHP can indirectly impact on aromatase rates by decreasing necessary cofactors (availability) or activation of aromatase inhibitors. Treinin et al showed in vitro dose dependent inhibition of progesterone production by MEHP in granulosa cells and reduced FSH-stimulated cAMP accumulation in granulosa cells implicating a direct or indirect effect of MEHP on FSH receptor (Treinen, Dodson, & Heindel, 1990). Similar effects of cAMP accumulation were seen in Sertoli cells (Lloyd & Foster, 1988), (Heindel & Chapin, 1989), (Heindel & Powell, 1992). Since granulosa and Sertoli cells share several structural and functional characteristics this mechanism is plausible. Study by Ma et al showed that inhaled DEHP (5 and 25 mg/m3) increased levels of LH and E2 in serum of prepubertal rats, and it increased ovarian Cyp19a1 expression (Ma et al., 2006), which is in disagreement with the key event relationship. This difference might be due to measurements of hormones during different phases of the estrous cycle, alterations in the experimental approaches used (in vivo versus in vitro) as well as exposure routes and doses given.

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

See table 1.

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

Davis, B. J., Weaver, R., Gaines, L. J., & Heindel, J. J. (1994). Mono-(2-ethylhexyl) phthalate suppresses estradiol production independent of FSH-cAMP stimulation in rat granulosa cells. Toxicology and Applied Pharmacology, 128(2), 224–8. doi:10.1006/taap.1994.1201

Gupta, R. K., Singh, J. M., Leslie, T. C., Meachum, S., Flaws, J. a, & Yao, H. H.-C. (2010). Di-(2-ethylhexyl) phthalate and mono-(2-ethylhexyl) phthalate inhibit growth and reduce estradiol levels of antral follicles in vitro. Toxicology and Applied Pharmacology, 242(2), 224–30. doi:10.1016/j.taap.2009.10.011

Havelock, J. C., Rainey, W. E., & Carr, B. R. (2004). Ovarian granulosa cell lines. Molecular and Cellular Endocrinology, 228(1-2), 67–78. doi:10.1016/j.mce.2004.04.018

Heindel, J. J., & Chapin, R. E. (1989). Inhibition of FSH-stimulated cAMP accumulation by mono(2-ethylhexyl) phthalate in primary rat Sertoli cell cultures. Toxicology and Applied Pharmacology, 97(2), 377–85.

Heindel, J. J., & Powell, C. J. (1992). Phthalate ester effects on rat Sertoli cell function in vitro: effects of phthalate side chain and age of animal. Toxicology and Applied Pharmacology, 115(1), 116–23.

Kwintkiewicz, J., Nishi, Y., Yanase, T., & Giudice, L. C. (2010). Peroxisome proliferator-activated receptor-gamma mediates bisphenol A inhibition of FSH-stimulated IGF-1, aromatase, and estradiol in human granulosa cells. Environmental Health Perspectives, 118(3), 400–6. doi:10.1289/ehp.0901161

Lloyd, S. C., & Foster, P. M. (1988). Effect of mono-(2-ethylhexyl)phthalate on follicle-stimulating hormone responsiveness of cultured rat Sertoli cells. Toxicology and Applied Pharmacology, 95(3), 484–9.

Lovekamp, T. N., & Davis, B. J. (2001). Mono-(2-ethylhexyl) phthalate suppresses aromatase transcript levels and estradiol production in cultured rat granulosa cells. Toxicology and Applied Pharmacology, 172(3), 217–24. doi:10.1006/taap.2001.9156

Ma, M., Kondo, T., Ban, S., Umemura, T., Kurahashi, N., Takeda, M., & Kishi, R. (2006). Exposure of prepubertal female rats to inhaled di(2-ethylhexyl)phthalate affects the onset of puberty and postpubertal reproductive functions. Toxicological Sciences : An Official Journal of the Society of Toxicology, 93(1), 164–71. doi:10.1093/toxsci/kfl036

Reinsberg, J., Wegener-Toper, P., van der Ven, K., van der Ven, H., & Klingmueller, D. (2009). Effect of mono-(2-ethylhexyl) phthalate on steroid production of human granulosa cells. Toxicology and Applied Pharmacology, 239(1), 116–23. doi:10.1016/j.taap.2009.05.022

Simpson, E. R., Mahendroo, M. S., Means, G. D., Kilgore, M. W., Hinshelwood, M. M., Graham-Lorence, S., … Michael, M. D. (1994). Aromatase cytochrome P450, the enzyme responsible for estrogen biosynthesis. Endocrine Reviews, 15(3), 342–55. doi:10.1210/edrv-15-3-342

Treinen, K. A., Dodson, W. C., & Heindel, J. J. (1990). Inhibition of FSH-stimulated cAMP accumulation and progesterone production by mono(2-ethylhexyl) phthalate in rat granulosa cell cultures. Toxicology and Applied Pharmacology, 106(2), 334–40.

Xu, C., Chen, J.-A., Qiu, Z., Zhao, Q., Luo, J., Yang, L., … Shu, W. (2010). Ovotoxicity and PPAR-mediated aromatase downregulation in female Sprague-Dawley rats following combined oral exposure to benzo[a]pyrene and di-(2-ethylhexyl) phthalate. Toxicology Letters, 199(3), 323–32. doi:10.1016/j.toxlet.2010.09.015