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Relationship: 395

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

demethylation, PPARg promoter leads to reduction in ovarian granulosa cells, Aromatase (Cyp19a1)

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

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
rat Rattus norvegicus NCBI
human Homo sapiens Moderate NCBI
mouse Mus musculus Low 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

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

This KER establishes the link between PPARγ activation and reduced levels of aromatase in ovarian granulosa cells. Aromatase is a key enzyme in steroidogenesis, catalysing the conversion of androgens to estrogens.

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

Peroxisome proliferator-activated receptor γ (PPARγ) is master switch of lipid metabolism and cell differentiation, their role has also been acknowledged in regulation of reproductive function and development [reviewed by (P Froment et al., 2006), (Minge, Robker, & Norman, 2008)]. The PPARs are implicated in regulation of steroidogenesis from in vitro data [reviewed by (Carolyn M Komar, 2005)].

PPARγ involvement in aromatase regulation in granulosa cells

The PPARγ is activated upon the ligand binding in granulosa cells, and then indirectly alters the expression of aromatase, the rate-limiting enzyme in conversion of androgens to estrogens (Kwintkiewicz, Nishi, Yanase, & Giudice, 2010), (Lovekamp-Swan, Jetten, & Davis, 2003), (Mu et al., 2000). The ligands of PPARγ were also shown to regulate other enzymes involved in steroidogenesis (Dupont, Chabrolle, Ramé, Tosca, & Coyral-Castel, 2008). All PPAR isoforms have been detected in both human and rodent ovary [reviewed by (Carolyn M Komar, 2005)]. In female rats the PPARγ have been detected in granulosa cells.

• PPARγ is primarily expressed in the granulosa cells and pre-ovulatory follicles, less strongly in the theca cells and corpus luteum where its expression increases after ovulation and falls after the LH surge, (C M Komar, Braissant, Wahli, & Curry, 2001). In the absence of fertilization or embryo implantation, PPARγ expression decreases as a result of corpus luteum regression (Viergutz, Loehrke, Poehland, Becker, & Kanitz, 2000).

• PPARγ is directly involved in oocyte maturation and ovulation [reviewed by (P Froment et al., 2006)]

Additional studies have shown that PPARγ is active in the ovary (P Froment et al. 2003).

The precise molecular mechanism by which PPARγ regulates aromatase is unclear given the fact that the proximal promoter regulating aromatase expression in the rat ovary does not contain an obvious peroxisome proliferator response element (PPRE) (Young and McPhaul 1997). There are plausible ways by which the PPARγ (as transcriptionally active PPAR:RXR heterodimer) could modify the transcription of aromatase including activation of RXR competition for binding sites on DNA and competition for limiting co-activators required for gene transcription. A new insight in the mechanism of regulation of the aromatase gene and activation of PPAR gamma and RXR was brought by Fan et al proposing disruption of NF-κB interaction with the aromatase promoter (Fan et al. 2005). The authors showed that activation of PPARγ and RXR impaired the interaction between NF-κB and aromatase promoter II and the p65 based transcription in both ovarian and fibroblast cells in a PPARγ-dependent manner (Fan et al. 2005). Studies supporting that hypothesis show that both PPARγ ligand (Troglitazone) and RXR ligand (LG100268) suppress aromatase activity in human granulosa cells (Mu et al. 2000), (Mu et al. 2001) and together causing a greater reduction than either compound alone (Mu et al. 2000).

Another possibility is that PPARγ is able to modify protein–protein interactions involved in the transcription of aromatase. Activation of PPARγ may recruit cofactors away from aromatase to inhibit normal transcription. Further studies are necessary to determine how PPARγ transcriptionally repress aromatase.

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

There is substantial evidence in literature supporting the KER, however the underlying mechanism are to be investigated, together with other pathways involved in aromatase down regulation. The pattern of the PPARγ expression in ovarian follicles is not steady, unlike expression of PPARs α and δ. This fact adds to the complexity to the interpretation of mechanisms involved in the pathway. The PPARγ is down-regulated in response to the LH surge (C M Komar, Braissant, Wahli, & Curry, 2001), but only in follicles that have responded to the LH surge (Carolyn M Komar & Curry, 2003). Because PPARγ is primarily expressed in granulosa cells, it may influence development of these cells and their ability to support normal oocyte maturation. PPARγ could also potentially affect somatic cell/oocyte communication not only by impacting granulosa cell development, but by direct effects on the oocyte. Modulation of the PPARγ activity/expression in the ovary therefore, could potentially affect oocyte developmental competence. Some evidence implies that the regulatory role of PPARγ might be connected to the other events in estradiol synthesis like the impairment of cholesterol transport to mitochondria (Cui et al., 2002).

PPARα The experimental data supports the parallel involvement of another member of PPAR superfamily of nuclear receptors, PPARα. PPARα was shown to be implicated in the down regulation of aromatase in rat: in vitro (Lovekamp-Swan et al., 2003); in vivo (Xu et al., 2010) and in mice in vivo (Toda, Okada, Miyaura, & Saibara, 2003). The ovarian aromatase promoter contains one half of a PPRE (peroxisome proliferator response element), which is the binding site for steroidogenic factor 1 (SF-1) (Young & McPhaul, 1997). While it is unknown whether PPARα can compete for binding on an incomplete response element, disruption of SF-1 binding to this half site would disrupt normal aromatase transcription. Studies by S. Plummer et al showed that PPARα and SF1 share a common coactivator (S. Plummer, Sharpe, Hallmark, Mahood, & Elcombe, 2007), (S. M. Plummer et al., 2013), CREB-binding protein (CBP), which is present in limiting concentrations (McCampbell, 2000). Binding of CBP to PPARα could therefore starve SF1 a cofactor essential for its transactivation functions. Surprisingly, aromatase levels were increased in ovaries of PPARα-null mice upon treatment with PPARα ligand (Toda et al., 2003).

PPARα was also reported to regulate other enzymes involved in steroidogenesis like: 17 beta-hydroxysteroid dehydrogenase type IV (HSD IV) (Corton et al., 1996), 3 beta-hydroxysteroid dehydrogenase (Wong, Ye, Muhlenkamp, & Gill, 2002) or 11beta-hydroxysteroid dehydrogenase type (Hermanowski-Vosatka et al., 2000). While PPARα/γ activators (like MEHP ) suppress aromatase, they showed no effect on Cholesterol side-chain cleavage enzyme (P450scc) in granulosa cells, demonstrating a more specific effect on steroidogenesis (Lovekamp-Swan et al., 2003). Experiments with PPARα-null mice indicate involvement of the receptor in reproductive toxicity, however cannot be entirely explained by the activation of PPARα mediated pathway as PPARα-null mice remain sensitive to DEHP-mediated reproductive toxicity (Ward et al. 1998), which implies other players including PPARγ. The above evidence supports the involvement of PPARα in regulation of steroidogenesis on its different steps. As PPARα is found primarily in the theca and stroma and the expression of PPARα in granulosa cells is very low (Carolyn M Komar, 2005) therefore it might be involved in steps in steroidogenesis upstream of aromatase.

Retinoid X Receptor (RXR)

Chemicals are able to activate RXR–PPARγ through RXR because this heterodimer interacts poorly with co-repressors in vivo and belongs to the group of so-called ‘permissive’ heterodimers, which can be stimulated by RXR ligands on their own (Germain, Iyer, Zechel, & Gronemeyer, 2002). Studies demonstrated that a PPARγ ligand and/or a RXR ligand decreased the aromatase activity in both cultured human ovarian granulosa cells (Mu et al., 2000), (Mu et al., 2001) and human granulosa-like tumor KGN cells (Kwintkiewicz et al., 2010) and combined treatment causes a greater reduction than either compound alone (Mu et al., 2000), (Mu et al., 2001).

Inconsistencies

No effect on aromatase protein expression was observed after PPARγ ligand (rosiglitazone) treatment in porcine ovarian follicles (Rak-Mardyła & Karpeta, 2014).

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 the 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

Barak, Y., Nelson, M. C., Ong, E. S., Jones, Y. Z., Ruiz-Lozano, P., Chien, K. R., … Evans, R. M. (1999). PPAR gamma is required for placental, cardiac, and adipose tissue development. Molecular Cell, 4(4), 585–95.

Bhattacharya, N., Dufour, J. M., Vo, M.-N., Okita, J., Okita, R., & Kim, K. H. (2005). Differential effects of phthalates on the testis and the liver. Biology of Reproduction, 72(3), 745–54. doi:10.1095/biolreprod.104.031583

Corton, J., Bocos, C., Moreno, E., Merritt, A., Marsman, D., Sausen, P., … Gustafsson, J. (1996). Rat 17 beta-hydroxysteroid dehydrogenase type IV is a novel peroxisome proliferator-inducible gene. Mol. Pharmacol., 50(5), 1157–1166.

Cui, Y., Miyoshi, K., Claudio, E., Siebenlist, U. K., Gonzalez, F. J., Flaws, J., … Hennighausen, L. (2002). Loss of the peroxisome proliferation-activated receptor gamma (PPARgamma ) does not affect mammary development and propensity for tumor formation but leads to reduced fertility. The Journal of Biological Chemistry, 277(20), 17830–5. doi:10.1074/jbc.M200186200

Dufour, J. M., Vo, M.-N., Bhattacharya, N., Okita, J., Okita, R., & Kim, K. H. (2003). Peroxisome proliferators disrupt retinoic acid receptor alpha signaling in the testis. Biology of Reproduction, 68(4), 1215–24. doi:10.1095/biolreprod.102.010488

Dupont, J., Chabrolle, C., Ramé, C., Tosca, L., & Coyral-Castel, S. (2008). Role of the peroxisome proliferator-activated receptors, adenosine monophosphate-activated kinase, and adiponectin in the ovary. PPAR Research, 2008, 176275. doi:10.1155/2008/176275

Dupont, J., Reverchon, M., Cloix, L., Froment, P., & Ramé, C. (2012). Involvement of adipokines, AMPK, PI3K and the PPAR signaling pathways in ovarian follicle development and cancer. The International Journal of Developmental Biology, 56(10-12), 959–67. doi:10.1387/ijdb.120134jd

Fan, W., Yanase, T., Morinaga, H., Mu, Y.-M., Nomura, M., Okabe, T., … Nawata, H. (2005). Activation of peroxisome proliferator-activated receptor-gamma and retinoid X receptor inhibits aromatase transcription via nuclear factor-kappaB. Endocrinology, 146(1), 85–92. doi:10.1210/en.2004-1046

Feige, J. N., Gelman, L., Rossi, D., Zoete, V., Métivier, R., Tudor, C., … Desvergne, B. (2007). The endocrine disruptor monoethyl-hexyl-phthalate is a selective peroxisome proliferator-activated receptor gamma modulator that promotes adipogenesis. The Journal of Biological Chemistry, 282(26), 19152–66. doi:10.1074/jbc.M702724200

Froment, P., Fabre, S., Dupont, J., Pisselet, C., Chesneau, D., Staels, B., & Monget, P. (2003). Expression and functional role of peroxisome proliferator-activated receptor-gamma in ovarian folliculogenesis in the sheep. Biology of Reproduction, 69(5), 1665–74. doi:10.1095/biolreprod.103.017244

Froment, P., Gizard, F., Defever, D., Staels, B., Dupont, J., & Monget, P. (2006). Peroxisome proliferator-activated receptors in reproductive tissues: from gametogenesis to parturition. The Journal of Endocrinology, 189(2), 199–209. doi:10.1677/joe.1.06667

Germain, P., Iyer, J., Zechel, C., & Gronemeyer, H. (2002). Co-regulator recruitment and the mechanism of retinoic acid receptor synergy. Nature, 415(6868), 187–92. doi:10.1038/415187a Hermanowski-Vosatka, A., Gerhold, D., Mundt, S. S., Loving, V. A., Lu, M., Chen, Y., … Thieringer, R. (2000). PPARalpha agonists reduce 11beta-hydroxysteroid dehydrogenase type 1 in the liver. Biochemical and Biophysical Research Communications, 279(2), 330–6. doi:10.1006/bbrc.2000.3966

Hurst, C. H., & Waxman, D. J. (2003). Activation of PPAR ␣ and PPAR ␥ by Environmental Phthalate Monoesters, 308, 297–308. doi:10.1093/toxsci/kfg145

Kaya, T., Mohr, S. C., Waxman, D. J., & Vajda, S. (2006). Computational screening of phthalate monoesters for binding to PPARgamma. Chemical Research in Toxicology, 19(8), 999–1009. doi:10.1021/tx050301s

Komar, C. M. (2005). Peroxisome proliferator-activated receptors (PPARs) and ovarian function--implications for regulating steroidogenesis, differentiation, and tissue remodeling. Reproductive Biology and Endocrinology : RB&E, 3, 41. doi:10.1186/1477-7827-3-41

Komar, C. M., Braissant, O., Wahli, W., & Curry, T. E. (2001). Expression and localization of PPARs in the rat ovary during follicular development and the periovulatory period. Endocrinology, 142(11), 4831–8. doi:10.1210/endo.142.11.8429

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

Lapinskas, P. J., Brown, S., Leesnitzer, L. M., Blanchard, S., Swanson, C., Cattley, R. C., & Corton, J. C. (2005). Role of PPARα in mediating the effects of phthalates and metabolites in the liver. Toxicology, 207(1), 149–163.

Lovekamp-Swan, T., Jetten, A. M., & Davis, B. J. (2003). Dual activation of PPARalpha and PPARgamma by mono-(2-ethylhexyl) phthalate in rat ovarian granulosa cells. Molecular and Cellular Endocrinology, 201(1-2), 133–41.

Luebker, D. J., Hansen, K. J., Bass, N. M., Butenhoff, J. L., & Seacat, A. M. (2002). Interactions of fluorochemicals with rat liver fatty acid-binding protein. Toxicology, 176(3), 175–85.

Maloney, E. K., & Waxman, D. J. (1999). trans-Activation of PPARα and PPARγ by Structurally Diverse Environmental Chemicals. Toxicology and Applied Pharmacology, 161(2), 209–218.

McCampbell, A. (2000). CREB-binding protein sequestration by expanded polyglutamine. Human Molecular Genetics, 9(14), 2197–2202. doi:10.1093/hmg/9.14.2197 Minge, C. E., Robker, R. L., & Norman, R. J. (2008). PPAR Gamma: Coordinating Metabolic and Immune Contributions to Female Fertility. PPAR Research, 2008, 243791. doi:10.1155/2008/243791

Mu, Y. M., Yanase, T., Nishi, Y., Takayanagi, R., Goto, K., & Nawata, H. (2001). Combined treatment with specific ligands for PPARgamma:RXR nuclear receptor system markedly inhibits the expression of cytochrome P450arom in human granulosa cancer cells. Molecular and Cellular Endocrinology, 181(1-2), 239–48.

Mu, Y. M., Yanase, T., Nishi, Y., Waseda, N., Oda, T., Tanaka, A., … Nawata, H. (2000). Insulin sensitizer, troglitazone, directly inhibits aromatase activity in human ovarian granulosa cells. Biochemical and Biophysical Research Communications, 271(3), 710–3. doi:10.1006/bbrc.2000.2701

Plummer, S. M., Dan, D., Quinney, J., Hallmark, N., Phillips, R. D., Millar, M., … Elcombe, C. R. (2013). Identification of transcription factors and coactivators affected by dibutylphthalate interactions in fetal rat testes. Toxicological Sciences : An Official Journal of the Society of Toxicology, 132(2), 443–57. doi:10.1093/toxsci/kft016

Plummer, S., Sharpe, R. M., Hallmark, N., Mahood, I. K., & Elcombe, C. (2007). Time-dependent and compartment-specific effects of in utero exposure to Di(n-butyl) phthalate on gene/protein expression in the fetal rat testis as revealed by transcription profiling and laser capture microdissection. Toxicological Sciences : An Official Journal of the Society of Toxicology, 97(2), 520–32. doi:10.1093/toxsci/kfm062

Rak-Mardyła, A., & Karpeta, A. (2014). Rosiglitazone stimulates peroxisome proliferator-activated receptor gamma expression and directly affects in vitro steroidogenesis in porcine ovarian follicles. Theriogenology, 82(1), 1–9. doi:10.1016/j.theriogenology.2014.02.016

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

Rotman, N., Haftek-Terreau, Z., Lücke, S., Feige, J., Gelman, L., Desvergne, B., & Wahli, W. (2008). PPAR Disruption: Cellular Mechanisms and Physiological Consequences. CHIMIA International Journal for Chemistry, 62(5), 340–344. doi:10.2533/chimia.2008.340

Saitoh, M., Yanase, T., Morinaga, H., Tanabe, M., Mu, Y. M., Nishi, Y., Nomura, M., Okabe, T., Goto, K., Takayanagi, R., and Nawata, H. (2001). Tributyltin or triphenyltin inhibits aromatase activity in the human granulosa-like tumor cell line KGN. Biochem. Biophys. Res. Commun., 289, 198–204.

Toda, K., Okada, T., Miyaura, C., & Saibara, T. (2003). Fenofibrate, a ligand for PPARalpha, inhibits aromatase cytochrome P450 expression in the ovary of mouse. Journal of Lipid Research, 44(2), 265–70. doi:10.1194/jlr.M200327-JLR200

ToxCastTM Data. “ToxCastTM Data.” US Environmental Protection Agency. http://www.epa.gov/ncct/toxcast/data.html.

Venkata, N. G., Robinson, J. a, Cabot, P. J., Davis, B., Monteith, G. R., & Roberts-Thomson, S. J. (2006). Mono(2-ethylhexyl)phthalate and mono-n-butyl phthalate activation of peroxisome proliferator activated-receptors alpha and gamma in breast. Toxicology Letters, 163(3), 224–34. doi:10.1016/j.toxlet.2005.11.001

Viergutz, T., Loehrke, B., Poehland, R., Becker, F., & Kanitz, W. (2000). Relationship between different stages of the corpus luteum and the expression of the peroxisome proliferator-activated receptor gamma protein in bovine large lutein cells. Journal of Reproduction and Fertility, 118(1), 153–61.

Willson, T. M., Brown, P. J., Sternbach, D. D., & Henke, B. R. (2000). The PPARs: from orphan receptors to drug discovery. Journal of Medicinal Chemistry, 43(4), 527–50.

Wong, J. S., Ye, X., Muhlenkamp, C. R., & Gill, S. S. (2002). Effect of a peroxisome proliferator on 3 beta-hydroxysteroid dehydrogenase. Biochemical and Biophysical Research Communications, 293(1), 549–53. doi:10.1016/S0006-291X(02)00235-8

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

Young, M., & McPhaul, M. J. (1997). Definition of the elements required for the activity of the rat aromatase promoter in steroidogenic cell lines. The Journal of Steroid Biochemistry and Molecular Biology, 61(3-6), 341–8.

Synthetic ligand, rosiglitazone stimulates AMP-activated protein kinase (AMPK) and enhances the meiotic resumption of mouse oocytes (Dupont, Reverchon, Cloix, Froment, & Ramé, 2012).