Androgen receptor (AR) antagonism leading to decreased fertility in females

Eleftheria-Maria Panagiotou; Karolinska Institutet and Karolinska University Hospital, SE-14186 Stockholm, Sweden

Pauliina Damdimopoulou; Karolinska Institutet and Karolinska University Hospital, SE-14186 Stockholm, Sweden

Terje Svingen; National Food Institute, Technical University of Denmark, Kongens Lyngby, 2800 Denmark

The proposed AOP (Figure 2) links AR antagonism (MIE26) to ovarian cycle irregularities (KE405) and reduced female fertility (KE406) via three key events: decreased AR activity (KE1614), altered AR gene transcription (KE286), and reduced granulosa cell proliferation (KE1800). Briefly, the binding of an antagonist to the AR prevents receptor activation and subsequent transcriptional regulation, ultimately disrupting expression of AR target genes necessary for follicle growth. This attenuates granulosa cell proliferation, leading to changes in the follicle population, which again disrupts the finely tuned ovarian cycle leading to subfertility.

The six KEs span a selected causal pathway between direct AR antagonism and reduced fertility in females. The first three KEs describe the essential component linking a chemical’s direct interaction with the AR preventing normal ligand binding and receptor activation, leading to altered AR-regulated gene transcription in target cells and tissues in complex in vivo systems (Draskau et al 2024, accepted). The first two KEs may have broad taxonomic applicability, whereas KE286 serves as a placeholder KE for tissue/organ-specific changes in gene regulation; for this AOP the ovaries.

Decreased AR activity described in KE1614 can result from several upstream events, notably lower androgen levels, or as presented in this AOP, from AR antagonism (KE26). KE26 can be easily measured in vitro either by using reporter gene assays or by monitoring AR dimerization and nucleus translocation, both essential for the canonical AR pathway. KE1614 is not measured directly in mammals, but an assay in fish, the RADAR assay, is available.

Although AR can have both non-genomic and genomic actions, we have focussed on the canonical genomic actions in this AOP, including KE286 which refers to altered expression of AR-target genes. In principle, KE286 can describe the transcriptional changes in specific organs or tissues at specific life stages in response to AR antagonism, which will be specific for whichever AO it leads to. There is currently no standardized method for measuring this KE; however, standard methods such as reverse transcription-quantitative PCR (RT-qPCR) or RNA sequencing can be employed.

The fourth KE, ‘reduced granulosa cell proliferation’(KE1800), represents an ovary-specific outcome of reduced AR signaling which integrates several known signaling pathways, such as PI3K/Akt, but also kit-ligand (Kitl) and growth differentiation factor 9 (Gdf9) that all may be under the control of the AR in the granulosa cells (Shiina et al., 2006). With the many pathways potentially involved in granulosa cell proliferation, they are challenging to measure in isolation, hence cell proliferation was considered the most pragmatic KE leading to disrupted  pathway progression. KE1800 can be measured in vitro by proliferation assays using commercially available granulosa-like cell lines. Granulosa cell proliferation manifests as follicle growth, therefore counting and assessing the growth stage of follicles is the currently standardized method to measure this KE in vivo. Follicle growth can also be assessed with detection of proliferation markers in situ, albeit not currently included in test guidelines.

KE405 relates to ovarian cycle irregularities, encompassing variations in cycle length and/or ovulation problems (deferred ovulation or anovulation). These irregularities indicate disturbances in any parts of the Hypothalamic-Pituitary-Ovarian (HPO) axis, which regulates reproductive processes. Therefore, we have considered KE405 as an AO. It can be measured in vivo by estrous cycle monitoring, an endpoint in several guideline tests. Lastly, the AO on impaired female fertility refers to the capacity to conceive and is measured by calculating fertility rate based on born offspring numbers.

The development of AOP345 was based on a pragmatic approach, as previously proposed (Svingen et al., 2021), yet adhering to the OECD’s AOP Developer’s Handbook (available on AOPwiki). Accordingly, the development strategy was decided individually for each KER based on whether the knowledge was deemed canonical or not. Furthermore, KEs 26, 1614 and 286 along with the KERs connecting them, were recently published as an upstream network (Draskau et al 2024, accepted). KER2273, connecting disrupted gene transcription (KE286) to granulosa cell proliferation (KE1800) was considered non-canonical and therefore developed using a systematic literature search approach, also published as a case-study for KER development (Panagiotou et al., 2022). KER3142, connecting reduced granulosa cell proliferation (KE1800) to ovarian cycle irregularities (KE405) was considered canonical but a semi-systematic approach was nevertheless employed to gather more non-biased supporting evidence for overall AOP assessment. The purpose of the semi-systematic approach was not to be as rigorous and exhaustive as the systematic, but rather through a structured literature search, gain an overview of the existing evidence. KER394, connecting ovarian cycle irregularities (KE405) to impaired fertility (KE406) was pre-existing on AOPwiki and is part of two additional AOPs (IDs 7 and 398) currently under OECD review.

Weight of evidence assessment is conducted for the AOP overall to establish the confidence in the causal relationships between linked KEs. Using modified Bradford-Hill criteria, we subjectively rated the overall confidence in AOP345 as ‘moderate’, with the weakest link, relative to scientific evidence, being KER2273.

Female reproductive disorders are on the rise and there is increasing evidence supporting a role for exposure to environmental chemicals, not least EDCs (Johansson et al., 2017). Despite this proposed causal relationship, there is still a lack of sensitive endpoints and understanding of causal mechanisms. This AOP addresses a knowledge gap as far as EDC identification is concerned, by providing an analytically constructed causal pathway linking disrupted androgen signaling with ovarian dysfunction and reduced fertility in females. Importantly, most KEs of the pathway include methods for effect measurements, which can support causal inference between in vitro data and adverse effects in an intact organism.

AOP345 also highlight gaps in knowledge and assay capacity, which can encourage the development of new approach methodologies (NAMs) to aid with chemical testing and regulation. Furthermore, it highlights the importance of ovarian follicle counts as an endpoint that currently is only optional in OECD test guidelines. Notably, however, follicle counting is a subjective, time-consuming and labor-intensive endpoint to measure, thus replacing it with a method assessing granulosa cell proliferation could be valuable. Such a method could potentially compliment estrus cycle monitoring, an endpoint that is potentially affected by different experimental set-ups, for example group size, study length and statistical analyses. AOP345 therefore offers a promising approach to address these methodological challenges. Finally, as quantitative understanding of this AOP continues to develop, it can provide a standardized methodology for assessing chemical effects and guide future regulatory decisions for the complex endpoint of female fertility.

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