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Relationship: 2273

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

Altered, Transcription of genes by AR leads to Reduced granulosa cell proliferation

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 (AR) antagonism leading to decreased fertility in females adjacent Moderate Low Cataia Ives (send email) Under development: Not open for comment. Do not cite

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
human Homo sapiens Low NCBI
mouse Mus musculus High NCBI
rat Rattus norvegicus High NCBI
Pig Pig High NCBI
cow Bos taurus Moderate NCBI
Monkey Monkey Moderate 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
During development and at adulthood 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

Decreased transcription of genes that are downstream of AR activation leads to reduced granulosa cell proliferation of the early-stage gonadotropin-independent ovarian follicles. Therefore, the follicle growth to the antral stage is decreased.

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

AR is a ligand-activated nuclear transcription factor expressed in the ovaries across mammalian species, including humans(Gervásio et al., 2014). During the gonadotropin independent follicular stage, AR activation is hypothesized to promote follicle growth, whereas in later stages it has been shown to inhibit growth and induce apoptosis(Franks and Hardy, 2018; Harlow et al., 1988). In humans, both mRNA and protein of AR are present in the oocyte, stroma cells, theca cells, but most prominently in granulosa cells of small antral follicles(Gervásio et al., 2014; Jeppesen et al., 2012).

In the mouse ovary, AR mRNA and protein are present in the oocyte, theca, and granulosa cells(Gill et al., 2004; Hirai et al., 1994; Szoltys and Slomczynska, 2000; Tetsuka and Hillier, 1996; Tetsuka et al., 1995). In the cow and sheep ovary, AR mRNA is present in granulosa and theca cells, and most prominently in granulosa of antral and early antral follicles(Hampton et al., 2004; Juengel et al., 2006). In the pig ovary, AR mRNA is mainly expressed in the granulosa cells until the antral stage(Cárdenas and Pope, 2002; Slomczynska et al., 2001). In the monkey ovary, AR mRNA and protein are present in theca, but mainly granulosa cells of antral and early antral follicles(Hillier et al., 1997; Weil et al., 1998).

In human follicles, the expression of the AR transcript is observed after the primordial stage and is most pronounced during the small antral stage(Rice et al., 2007). Throughout early folliculogenesis, AR expression controls transcription of genes involved in promoting growth and differentiation of granulosa cells and formation of antrum(Gervásio et al., 2014). Genes under the control of AR that are involved in these processes include Kit ligand (KITL), Bone morphogenetic protein 15 (BMP15), and Hepatocyte growth factor (HGF)(Astapova et al., 2019; Prizant et al., 2014).

In the monkey ovary, high levels of AR mRNA correlates with high levels of granulosa cell proliferation(Vendola et al., 1998; Weil et al., 1998) Increased AR activation is associated with increased follicle growth and increased granulosa cell proliferation in small antral rat follicles, supporting the important role for AR during this developmental stage(Lim et al., 2017a).

AR may mediate early follicle growth through FSHR, supported by studies correlating mRNA levels of AR and FSHR in granulosa cells of small antral follicles(Nielsen et al., 2011,,Weil et al., 1999). In mice, FSH-mediated in vitro follicle growth is increased by androgens, suggesting that androgens through AR may act synergistically with FSHR, which in turn increases follicle growth to antral follicles(Sen et al., 2014).

It is also hypothesized that FSHR activation through AR leads to increased AMH expression in granulosa cells of primary to small antral follicles(Lin et al., 2021). In turn, elevated levels of AMH lead to inhibition of FSH-induced aromatase activity, resulting in higher androgen levels that inhibit further follicular growth.

AR activation has been associated with Insulin-like Growth Factor 1 (IGF1) and Insulin-like Growth Factor 1 Receptor (IGFR1) and other key factors of the IGF signaling pathway, which is essential for granulosa growth and differentiation(Baumgarten et al., 2014),(Vendola et al., 1999). In human granulosa cells of primordial and primary follicles, AR and IGF-related factors are highly enriched at the transcriptional level(Steffensen et al., 2018).

AR activation affects the level of connexins, proteins that form gap junctions between granulosa cells and the oocyte and hence regulate intracellular communication; a prerequisite for folliculogenesis(Kamal et al., 2020).

In humans, the importance of AR in follicular growth becomes evident with the beneficial effects of androgens in assisted reproductive technology outcomes(Bosdou et al., 2012; Casson et al., 2000; Fábregues et al., 2009; Kim et al., 2011, 2014; Nagels et al., 2015; Noventa et al., 2019; Petya Andreeva, Ivelina Oprova, Luboslava Valkova, Petya Chaveeva, Ivanka Dimova, 2020). Although the mechanism remains elusive, it has been suggested that androgen priming of women seeking fertility treatment promotes follicle growth resulting in an increase in the FSH-sensitive follicle pool(Hu et al., 2017). Gene expression studies in human small antral follicles reveal significant association of AR and FSHR levels, suggesting that the increase in follicle growth could be mediated through regulating AR transcription in granulosa cells(Hu et al., 2017; Nielsen et al., 2011). Epidemiological studies have shown that upon androgen pretreatment, increase in the number of antral follicles and mean follicular diameter were observed(Balasch et al., 2006; Kim et al., 2011). This increase supports the hypothesis that androgen receptor signaling is important for early follicle growth. Studies observing no effects upon androgen pre-treatment claim that dose and duration of the selected androgen might lead to contradicting results(Yeung et al., 2014).

Hypoandrogenism provides further evidence for an important role for androgen actions in human follicle development. Lower levels of DHEA or testosterone have been associated with women that have diminished ovarian reserve or premature ovarian aging(Gleicher et al., 2013). In the case of untreated primary adrenal insufficiency, the androgen deficient patient exhibit significantly reduced fertility(Erichsen et al., 2010).

Conclusions on the androgen significance can also be drawn from clinical evidence where women are exposed to an androgen excess.  Hyperandrogenism in the case of congenital adrenal hyperplasia and exogenous androgen treatments in trans males lead to polycystic ovaries(Walters and Handelsman, 2018). This indicated that the androgens stimulate early follicle growth and inhibit further maturation(Walters and Handelsman, 2018). In polycystic ovarian syndrome, a syndrome characterized by accumulation of small antral follicles in the ovarian cortex, a plausible cause for this morphology is hyperandrogenaemia(Balen et al., 2003; Lebbe and Woodruff, 2013).

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

Genomic and non-genomic effects are not distinguished in the studies included in the KER analysis. Hence, it cannot be concluded that all observations are solely due to directly perturbed transcription. However, since AR transcribes genes necessary for early folliculogenesis (KITLG, BMP15, HGF), it is reasonable to assume that genomic mechanisms are involved.

Other uncertainties to consider: different anti-androgenic compounds have different effects on the AR (e.g. different IC50, Cmax); compounds that are anti-androgenic may also affect other mechanisms/modalities; downstream effects of perturbed AR transcriptional function might depend on the duration of exposure as well as the developmental stage of the follicles. In humans, effects can be inconclusive since a part of the population can have androgen-related conditions such as polycystic ovary syndrome (PCOS)(Gleicher et al., 2011).

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

The nature of the response-response relationship between decreased AR activation and reduced granulosa cell proliferation in the early stage of follicular development is not clear. Some of the aforementioned studies claim the effects were dose-dependent; however, the limited number of concentrations tested prevents a solid conclusion(Murray et al., 1998; Wang et al., 2001; Yang and Fortune, 2006). Therefore, at present, the quantitative understanding of this KER is rated ‘low’.

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

Studies included in establishing this KER exhibit observed changes in vitro at 24h in pig granulosa cells, and in vivo studies after 48h in rats(Hickey et al., 2004, 2005; Kumari et al., 1978). The conclusion that can presently be drawn is that the approximate timescale of the changes in KEdownstream relative to changes in KEupstream is less than 48h. However, the species differences between the time scales of folliculogenesis need to be taken into consideration in order for human extrapolations to be made.

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

The E3 ubiquitin ligase protein Ring Finger Protein 6 (RNF6) regulates AR levels in granulosa cells through polyubiquitination and AR transcriptional activity for KITLG expression in small antral follicles(Lim et al., 2017b, 2017a).

Epidermal growth factor receptor (EGFR) may mediate the androgen-induced granulosa cell proliferation(Franks and Hardy, 2018).

Sixteen different mutations of the AR gene (Xq11.2-q12) that cause androgen insensitivity syndrome have been identified(Jiang et al., 2020).

The number of CAG repeats on the N-terminal domain of the AR has been associated with effects on fertility and ovarian reserve(Hickey et al., 2002; Lledo et al., 2014).

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

Activated AR can transcriptionally regulate its own expression through a negative feedback loop(Gelmann, 2002). However, in granulosa cells of monkey ovaries, AR was shown to have the opposite effect, thus creating an autocrine positive feedback(Weil et al., 1998). More studies are needed to understand when AR regulation of its own expression is positive or negative.

During the early stages of folliculogenesis, mainly from the secondary to the small antral stage, activated AR can induce FSH activities in granulosa cells and promote granulosa cell differentiation and follicle maturation, even though follicles are still not gonadotropin-dependent(Gleicher et al., 2011). These activities include changes in androgen metabolism due to altered expression of steroidogenic enzymes. Therefore, it has been suggested that androgens can bind to the AR to establish a loop between activated AR and FSH action(Gleicher et al., 2011; Lenie and Smitz, 2009).

A positive feedback loop connecting activated AR and AMH through FSHR is also hypothesized. Activated AR could lead to increased expression of AMH through FSHR activation, resulting in inhibition of FSH-induced aromatase, ultimately increasing levels of androgens and AR activation(Dewailly et al., 2016). Typically, elevated levels of androgens, for instance in transgender males and PCOS patients, correlate with increased levels of AMH, however, contradictory results exist connecting elevated androgen or FSH levels to reduced AMH(Caanen et al., 2015; Li et al., 2011).

There is also evidence of an intra-follicular feedback loop that regulates steroidogenesis during the secondary follicle stage, causing downregulation of androgen synthesis upon exogenous androgen exposure and upregulation upon androgen receptor antagonism(Lebbe et al., 2017).

As mentioned, genes involved in early folliculogenesis like KITLG and HGF are under the control of AR. Those two genes have been shown to create a positive feedback loop in mice, by increasing the expression levels of each other(Guglielmo et al., 2011).

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

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

Astapova, O., Minor, B.M.N., and Hammes, S.R. (2019). Physiological and Pathological Androgen Actions in the Ovary. Endocrinology 160, 1166–1174. https://doi.org/10.1210/en.2019-00101.

Balasch, J., Fábregues, F., Peñarrubia, J., Carmona, F., Casamitjana, R., Creus, M., Manau, D., Casals, G., and Vanrell, J.A. (2006). Pretreatment with transdermal testosterone may improve ovarian response to gonadotrophins in poor-responder IVF patients with normal basal concentrations of FSH. Human Reproduction 21, 1884–1893. https://doi.org/10.1093/humrep/del052.

Balen, A.H., Laven, J.S.E., Tan, S.L., and Dewailly, D. (2003). Ultrasound assessment of the polycystic ovary: International consensus definitions. Human Reproduction Update 9, 505–514. https://doi.org/10.1093/humupd/dmg044.

Baumgarten, S.C., Convissar, S.M., Fierro, M.A., Winston, N.J., Scoccia, B., and Stocco, C. (2014). IGF1R signaling is necessary for FSH-induced activation of AKT and differentiation of human cumulus granulosa cells. Journal of Clinical Endocrinology and Metabolism 99, 2995–3004. https://doi.org/10.1210/jc.2014-1139.

Bosdou, J.K., Venetis, C.A., Kolibianakis, E.M., Toulis, K.A., Goulis, D.G., Zepiridis, L., and Tarlatzis, B.C. (2012). The use of androgens or androgen-modulating agents in poor responders undergoing in vitro fertilization: A systematic review and meta-analysis. Human Reproduction Update 18, 127–145. https://doi.org/10.1093/humupd/dmr051.

Caanen, M.R., Soleman, R.S., Kuijper, E.A.M., Kreukels, B.P.C., De Roo, C., Tilleman, K., De Sutter, P., Van Trotsenburg, M.A.A., Broekmans, F.J., and Lambalk, C.B. (2015). Antimüllerian hormone levels decrease in female-to-male transsexuals using testosterone as cross-sex therapy. Fertility and Sterility 103, 1340–1345. https://doi.org/10.1016/J.FERTNSTERT.2015.02.003.

Cárdenas, H., and Pope, W.F. (2002). Androgen receptor and follicle-stimulating hormone receptor in the pig ovary during the follicular phase of the estrous cycle*. Molecular Reproduction and Development 62, 92–98. https://doi.org/10.1002/mrd.10060.

Casson, P.R., Lindsay, M.S., Pisarska, M.D., Carson, S.A., and Buster, J.E. (2000). Dehydroepiandrosterone supplementation augments ovarian stimulation in poor responders: A case series. Human Reproduction 15, 2129–2132. https://doi.org/10.1093/humrep/15.10.2129.

Dewailly, D., Robin, G., Peigne, M., Decanter, C., Pigny, P., and Catteau-Jonard, S. (2016). Interactions between androgens, FSH, anti-Müllerian hormone and estradiol during folliculogenesis in the human normal and polycystic ovary. Human Reproduction Update 22, 709–724. https://doi.org/10.1093/HUMUPD/DMW027.

Erichsen, M.M., Husebye, E.S., Michelsen, T.M., Dahl, Alv.A., and Løvås, K. (2010). Sexuality and Fertility in Women with Addison’s Disease. The Journal of Clinical Endocrinology & Metabolism 95, 4354–4360. https://doi.org/10.1210/jc.2010-0445.

Fábregues, F., Peñarrubia, J., Creus, M., Manau, D., Casals, G., Carmona, F., and Balasch, J. (2009). Transdermal testosterone may improve ovarian response to gonadotrophins in low-responder IVF patients: A randomized, clinical trial. Human Reproduction 24, 349–359. https://doi.org/10.1093/humrep/den428.

Franks, S., and Hardy, K. (2018). Androgen action in the ovary. Frontiers in Endocrinology 9, 452. https://doi.org/10.3389/fendo.2018.00452.

Gelmann, E.P. (2002). Molecular biology of the androgen receptor. Journal of Clinical Oncology 20, 3001–3015. https://doi.org/10.1200/JCO.2002.10.018.

Gervásio, C.G., Bernuci, M.P., Silva-de-Sá, M.F., and Rosa-e-Silva, A.C.J. de S. (2014). The Role of Androgen Hormones in Early Follicular Development. ISRN Obstetrics and Gynecology 2014, 1–11. https://doi.org/10.1155/2014/818010.

Gill, A., Jamnongjit, M., and Hammes, S.R. (2004). Androgens promote maturation and signaling in mouse oocytes independent of transcription: a release of inhibition model for mammalian oocyte meiosis. Molecular Endocrinology 18, 97–104. .

Gleicher, N., Weghofer, A., and Barad, D.H. (2011). The role of androgens in follicle maturation and ovulation induction: friend or foe of infertility treatment? Reproductive Biology & Endocrinology 9, 116. https://doi.org/https://dx.doi.org/10.1186/1477-7827-9-116.

Gleicher, N., Kim, A., Weghofer, A., Kushnir, V.A., Shohat-Tal, A., Lazzaroni, E., Lee, H.J., and Barad, D.H. (2013). Hypoandrogenism in association with diminished functional ovarian reserve. Human Reproduction 28, 1084–1091. https://doi.org/https://dx.doi.org/10.1093/humrep/det033.

González-Sanz, S., Barreñada, O., Rial, E., Brieño-Enriquez, M.A., and del Mazo, J. (2020). The antiandrogenic vinclozolin induces differentiation delay of germ cells and changes in energy metabolism in 3D cultures of fetal ovaries. Scientific Reports 10, 1–13. https://doi.org/10.1038/s41598-020-75116-3.

Guglielmo, M.C., Ricci, G., Catizone, A., Barberi, M., Galdieri, M., Stefanini, M., and Canipari, R. (2011). The effect of hepatocyte growth factor on the initial stages of mouse follicle development. Journal of Cellular Physiology 226, 520–529. https://doi.org/10.1002/jcp.22361.

Hampton, J.H., Manikkam, M., Lubahn, D.B., Smith, M.F., and Garverick, H.A. (2004). Androgen receptor mRNA expression in the bovine ovary. Domestic Animal Endocrinology 27, 81–88. .

Harlow, C.R., Shaw, H.J., Hillier, S.G., and Hodges, J.K. (1988). Factors Influencing Follicle-Stimulating Hormone-Responsive Steroidogenesis in Marmoset Granulosa Cells: Effects of Androgens and the Stage of Follicular Maturity. Endocrinology 122, 2780–2787. https://doi.org/10.1210/ENDO-122-6-2780.

Hickey, T., Chandy, A., and Norman, R.J. (2002). The androgen receptor CAG repeat polymorphism and X-chromosome inactivation in Australian Caucasian women with infertility related to polycystic ovary syndrome. Journal of Clinical Endocrinology and Metabolism 87, 161–165. https://doi.org/10.1210/jcem.87.1.8137.

Hickey, T.E., Marrocco, D.L., Gilchrist, R.B., Norman, R.J., and Armstrong, D.T. (2004). Interactions between androgen and growth factors in granulosa cell subtypes of porcine antral follicles. Biology of Reproduction 71, 45–52. .

Hickey, T.E., Marrocco, D.L., Amato, F., Ritter, L.J., Norman, R.J., Gilchrist, R.B., and Armstrong, D.T. (2005). Androgens augment the mitogenic effects of oocyte-secreted factors and growth differentiation factor 9 on porcine granulosa cells. Biology of Reproduction 73, 825–832. .

Hillier, S.G., Tetsuka, M., and Fraser, H.M. (1997). Location and developmental regulation of androgen receptor in primate ovary. Human Reproduction 12, 107–111. .

Hirai, M., Hirata, S., Osada, T., Hagihara, K., and Kato, J. (1994). Androgen receptor mRNA in the rat ovary and uterus. Journal of Steroid Biochemistry & Molecular Biology 49, 1–7. .

Hu, Q., Hong, L., Nie, M., Wang, Q., Fang, Y., Dai, Y., Zhai, Y., Wang, S., Yin, C., and Yang, X. (2017). The effect of dehydroepiandrosterone supplementation on ovarian response is associated with androgen receptor in diminished ovarian reserve women. Journal of Ovarian Research 10, 32. https://doi.org/https://dx.doi.org/10.1186/s13048-017-0326-3.

Jeppesen, J. V, Kristensen, S.G., Nielsen, M.E., Humaidan, P., Dal Canto, M., Fadini, R., Schmidt, K.T., Ernst, E., and Yding Andersen, C. (2012). LH-receptor gene expression in human granulosa and cumulus cells from antral and preovulatory follicles. Journal of Clinical Endocrinology & Metabolism 97, E1524-31. https://doi.org/https://dx.doi.org/10.1210/jc.2012-1427.

Jiang, X., Teng, Y., Chen, X., Liang, N., Li, Z., Liang, D., and Wu, L. (2020). Six novel Mutation analysis of the androgen receptor gene in 17 Chinese patients with androgen insensitivity syndrome. Clinica Chimica Acta 506, 180–186. https://doi.org/10.1016/j.cca.2020.03.036.

Juengel, J.L., Heath, D.A., Quirke, L.D., and McNatty, K.P. (2006). Oestrogen receptor alpha and beta, androgen receptor and progesterone receptor mRNA and protein localisation within the developing ovary and in small growing follicles of sheep. Reproduction 131, 81–92. .

Kamal, D.A.M., Ibrahim, S.F., and Mokhtar, M.H. (2020). Androgen effect on connexin expression in the mammalian female reproductive system: A systematic review. Bosnian Journal of Basic Medical Sciences 20, 293–302. https://doi.org/10.17305/bjbms.2019.4501.

Kim, C.H., Howles, C.M., and Lee, H.A. (2011). The effect of transdermal testosterone gel pretreatment on controlled ovarian stimulation and IVF outcome in low responders. Fertility and Sterility 95, 679–683. https://doi.org/10.1016/j.fertnstert.2010.07.1077.

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