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Relationship: 2820

Title

A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

Decrease, AR activation leads to AGD, decreased

Upstream event

The causing Key Event (KE) in a Key Event Relationship (KER). More help

Decrease, AR activation

Downstream event

The responding Key Event (KE) in a Key Event Relationship (KER). More help

AGD, decreased

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

AOP Name	Adjacency	Weight of Evidence	Quantitative Understanding	Point of Contact	Author Status	OECD Status
5α-reductase inhibition leading to short anogenital distance (AGD) in male (mammalian) offspring	non-adjacent			Terje Svingen (send email)	Under development: Not open for comment. Do not cite	Under Development
Androgen receptor (AR) antagonism leading to short anogenital distance (AGD) in male (mammalian) offspring	non-adjacent			Terje Svingen (send email)	Under development: Not open for comment. Do not cite	Under Development
Decreased testosterone synthesis leading to short anogenital distance (AGD) in male (mammalian) offspring	non-adjacent	High	Moderate	Terje Svingen (send email)	Under development: Not open for comment. Do not cite	Under Development

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) 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. More help

Term	Scientific Term	Evidence	Link
human, mouse, rat	human, mouse, rat	High	NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help

Sex	Evidence
Male	High

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER. More help

Term	Evidence
Fetal to Parturition	High

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

This KER refers to a decrease in androgen receptor (AR) activation during fetal development leading to decreased anogenital distance (AGD) in male offspring. It should be noted that the upstream Key Event (KE) ‘decrease, androgen receptor activation’ (KE-1614 in AOP Wiki) specifically focuses on decreased activation of the androgen receptor in vivo, while most methods that can be used to measure AR activity are carried out in vitro. Indirect information about this KE may for example be provided from assays showing in vitro AR antagonism, decreased in vitro or in vivo testosterone production/levels or decreased in vitro or in vivo dihydrotestosterone (DHT) production/levels.

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER. For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings. Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

A systematic weight of evidence approach was applied to collect, evaluate, extract and integrate evidence from in vivo and epidemiological studies (flowchart can be found in Figure 1 in Holmer et al 2024).

Literature search

Search terms and search strings were developed for PubMed and Web of Science based on the review question “Does decreased androgen receptor activity (including reduced androgen levels and androgen receptor antagonism) during fetal development lead to reduced anogenital distance in mammals?”.

PubMed: ("androgen receptor*" OR "testosterone receptor*" OR "receptors, androgen"[MeSH Terms] OR "androgen*" OR "testosterone*" OR "dihydrotestosterone*" OR "androgens"[MeSH Terms] OR "androgen antagonists"[MeSH Terms]) AND ("anogenital distance*" OR "AGD")

Web of Science: TS=(("androgen receptor*" OR "testosterone receptor*" OR "androgen*" OR "testosterone*" OR "dihydrotestosterone*") AND ("anogenital distance*" OR "AGD"))

Literature searches in PubMed and Web of Science were performed on February 9, 2023. The obtained publications were imported to RAYYAN software (https://www.rayyan.ai) and duplicates were removed resulting in 826 publications (Figure 1).

The following inclusion and exclusion criteria were used for screening the titles and abstracts in RAYYAN.

Inclusion criteria:

· primary literature on

o exposure to androgenic or antiandrogenic compounds and AGD as an outcome in in vivo studies in mammals or in epidemiological studies

o measurement of androgen levels, AR activity or other androgen biomarkers and AGD in in vivo studies in mammals or in epidemiological studies

o in vitro and in vivo mechanistic studies on AGD

· reviews on AGD

Exclusion criteria:

· not in English

· abstracts and other non-full text publications

Study quality assessment and data extraction for in vivo and epidemiological studies on anogenital distance

In order to cover decreased AR activation resulting from both AR antagonism, decreased testosterone production/levels and decreased dihydrotestosterone (DHT) production/levels, information on model substances acting through these different pathways were included. Thus, full text publications on in vivo studies of effects on AGD in mammals after prenatal exposure to DEHP, finasteride, flutamide, procymidone or vinclozolin as well as epidemiological studies on association between maternal DEHP metabolites and length of AGD in boys were analyzed. Data from the publications were extracted into an Excel template and the reliability of the studies was assessed using the SciRAP in vivo and epi methodological quality tool (in vivo: http://www.scirap.org; epi:under development). The translation into reliability categories for each dataset was done using the principles laid out in table 1. Studies were divided into different datasets if different exposure doses, exposure windows or timepoints for measurement of AGD lead to different points of departure (NOAELs/LOAELs) or assignment to different reliability categories.

Table 1. Principles for translation of SciRAP scores to reliability categories.

Reliability Category	Principles
1.Reliable without restriction	SciRAP methodological quality Score > 80 and all key criteria* are “Fulfilled” and there are no deficiencies in the non-key criteria that might affect study reliability.
2. Reliable with restriction	SciRAP methodological quality Score > 65 and one or several of the key criteria are “Partially Fulfilled” or there are minor deficiencies in the non-key criteria that might affect study reliability.
3. Not reliable	SciRAP methodological quality Score < 65 or one or several of the key criteria are “Not Fulfilled” or there are major deficiencies in the non-key criteria that affect reliability.
4. Not assignable	Two or more of the key criteria are “Not Determined”

*Key criteria are criteria judged as specifically critical for reliability of the data in a certain case and are determined a priori. The following three key criteria were used for in vivo studies: A concurrent negative control group was included, the timing and duration of administration were appropriate for investigating the included endpoints, a sufficient number of animals per dose group were subjected to separate tests/data collection/measurements to generate reliable and valid results. The following five key criteria were used for epidemiological studies: The sample size was appropriate for the statistical analysis and study design, reliable and sensitive methods were used for measuring the exposure (direct and indirect assessment methods), reliable and sensitive methods were used for investigating the selected biomarker and/or outcome, important confounders were identified and statistical analyses were adjusted for those confounders, appropriate data processing and statistical methods were used.

The level of confidence in the overall data for each substance was categorized using the principles laid out in table 2.

Table 2. Principles for categorization.

Level of confidence	Principles for Categorization**
Strong	· Effects were observed in one or more datasets judged as reliable without restriction or reliable with restriction; there are no conflicting results from datasets judged as reliable with or without restriction. OR · Effects were observed in one or more datasets judged as reliable without restriction or reliable with restriction but conflicting results, i.e. no or opposite effects were observed in other datasets judged as reliable with or without restriction. However, conflicts of results could be explained by differences in study design, for example different exposure periods, doses or animal species or cell models.
Moderate	· Effects were observed in one or more datasets judged as reliable without restriction or reliable with restriction but conflicting results, i.e., no or opposite effects were observed in other datasets judged as reliable with or without restriction. Conflicts of results could not be explained by differences in study design, for example different exposure periods, doses or animal species or cell models. Effects were observed in at least half of the datasets.
Weak	· Effects were observed in one or more datasets judged as reliable without restriction or reliable with restriction but conflicting results, i.e., no or opposite effects were observed in other datasets judged as reliable with or without restriction. Conflicts of results could not be explained by differences in study design, for example different exposure periods, doses or animal species or cell models. Effects were observed in fewer than half of the datasets. OR · Effects were only observed in one or more datasets judged as not reliable or not assignable.
No effect	· No effects were observed in any of the datasets reviewed.

**Conflicting results from datasets judged as not reliable did not impact the categorization.

Identification of studies on mechanistic understanding of substances causing reduced anogenital distance

Relevant studies describing mechanisms for the substances flutamide, procymidone, vinclozolin, finasteride and DEHP were identified from 1) the reference lists in the included publications on in vivo studies of model substances, 2) mechanistic studies from the literature search, 3) review articles from the literature search, and 4) an additional search in PubMed for review papers on the pharmaceuticals finasteride and flutamide.

Evidence Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help

Biological Plausibility

Addresses the biological rationale for a connection between KEupstream and KEdownstream. This field 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. More help

The biological plausibility for this KER is judged to be high based on the following:

- Sexual differentiation happens in fetal life. The testes are developed and start to produce testosterone that is converted in other tissues by the enzyme 5-alpha-reductase to the more potent androgen dihydrotestosterone (DHT). Both hormones bind and activate the nuclear receptor and transcription factor AR that in turn drives masculinization of the male fetus (Welsh et al., 2014; Schwartz et. al, 2019).

- Fetal masculinization depends on activation of androgen signaling during a critical time window, the masculinization programming window (MPW), from gestational day (GD) 15.5-18.5 in rats, 14.5-16.5 in mice and presumably gestation weeks (GWs) 8-14 in humans (Welsh et al., 2008; Amato et al., 2022). The onset of AR expression in the tissues of the reproductive tract follows the timing of the MPW (Welsh et al., 2008).

- The fetal masculinization process involves a range of tissues and organs, including the perineum. Perineum length can be measured as the AGD, which is the distance between the anus and the genitalia. The AGD is approximately twice as long in male as in female newborn rodents and humans (Schwartz et al., 2019).

- Male AR knockout mice present shorter AGD than wildtype males, so short that it is indistinguishable from wildtype female littermates (Yeh et al., 2002, Sato et al., 2004).

- In human males, mutations decreasing AR activity also lead to feminization. One example is the androgen insensitivity syndrome (AIS), where mutations in the AR lead to an impaired or abolished response to androgens, and thereby some degree of feminization of XY individuals and even XY sex reversal in individuals with complete AIS (CAIS) (Thankamony et al., 2016; Hughes et al., 2012; Crouch et al., 2011). XY individuals with CAIS present as women with internally placed testes. A study showed that the clitoral to urethral distance in these individuals was similar to a control group of women, but it is not clear whether this measurement can work as a proxy for measuring the AGD (Thankamony et al 2016, Crouch 2011). Unfortunately, it seems the AGD has not at present been measured in CAIS individuals. Another example is human males lacking 5-alpha-reductase, also presenting female-like genitalia (Batista & Mendonca, 2022).

- The detailed mechanism by which androgens regulate the AGD is not known but it is hypothesized that the AGD is influenced by the size of the levator-ani and bulbocavernosus (LABC) muscle complex in the perineum. The growth of this complex is stimulated by AR activation, it is sexually dimorphic and larger in males than in females and (Schwartz et al., 2019). AR is required for the development of the LABC complex as demonstrated by AR general and muscle specific knockout mice. AR is expressed in non-myocytic cells in the LABC complex, starting at E15.5 in mice, and knockout of AR in these cells results in defects in the muscle formation (Ipulan et al., 2016;). Differential gene expression profiles in the perineum of male and female rats as well as in antiandrogen-exposed male rats have been identified providing further mechanistic understanding (Schwartz et al, 2019; Draskau et al, 2022).

Empirical Evidence

Provides specific (citable) evidence that supports the idea of a change in the upstream KE (KEupstream) leading to, or being associated with, a subsequent change in the downstream KE (KEdownstream), assuming the perturbation of KEupstream is sufficient. More help

Animal in vivo data

The empirical support from studies in animals for this KER is overall judged as high.

It should be noted that the KE decreased androgen receptor activation (KE-1614 in AOP Wiki) specifically focuses on decreased activation of the androgen receptor in vivo, with no methods currently available to measure this. Examples of assays that provide indirect information about KE-1614 are described in upstream MIE/KEs.

The empirical evidence for this KER from animal studies in vivo is based on studies using five different substances that result in decreased AR activation by different mechanisms. Flutamide, procymidone and vinclozolin bind to the AR and inhibit the receptor activity and thereby act as AR antagonists, see MIE26. Finasteride inhibits the 5-alpha-reductase enzyme that converts testosterone to DHT, see MIE1617. DEHP exposure during prenatal development in rats results in reduced fetal testosterone levels, see KE1690. (MIE26, MIE1617 and KE1690 can be found in AOP Wiki).

The evidence for the upstream KE is mainly based on data from in vitro assays (AR antagonism or 5-alpha-reductase inhibition in vitro) whereas the evidence for the downstream KE is based on in vivo studies, and there is generally not evidence for both KEs from the same study. However, decreased testosterone levels can be measured in vivo, and Borch et al., 2004 measured the effect of developmental DEHP exposure on both testosterone levels and AGD (see section about “Dose concordance”).

The empirical animal evidence for the five substances is summarized in table 3.

Table 3. Summary of empirical evidence for decreased androgen receptor activation, leading to decreased male AGD. References for the studies supporting the empirical evidence are found in section “Evidence for decreased AR activation (KE1614) by flutamide, procymidone, and vinclozolin, finasteride and DEHP” and in table 2.

Stressor(s)	Upstream effect (decreased AR activation)	Downstream effect (decreased male AGD)
Flutamide	AR antagonism in in vitro assay receptor binding and transactivation assays	Decreased male AGD after prenatal exposure in studies in rat
Procymidone	AR antagonism in in vitro assay receptor binding and transactivation assays	Decreased male AGD after prenatal exposure in studies in rat
Vinclozolin	AR antagonism in in vitro assay receptor binding and transactivation assays	Decreased male AGD after prenatal exposure in studies in rat and mouse
Finasteride	Inhibition of 5-alpha-reductase enzyme in in vitro assays	Decreased male AGD after prenatal exposure in studies in rat
DEHP	Reduced production of testosterone in fetal testis measured in ex vivo testis assays, reduced testosterone levels in testis and reduced fetal plasma or serum testosterone levels	Decreased male AGD after prenatal exposure in studies in rat

From table 3, it can be deducted that fetal exposure to substances known to decrease androgen receptor activation through antagonism of the AR (vinclozolin, procymidone, flutamide), inhibition of testosterone synthesis (DEHP) or inhibition of conversion of testosterone to DHT (finasteride), results in decreased AGD in rat and mouse male offspring.

Evidence for decreased AR activation (KE 1614) by flutamide, procymidone, vinclozolin, finasteride and DEHP

Flutamide, a pharmaceutical, binds the AR and inhibits the receptor activity, thereby acting as an AR antagonist. It has been used as an antiandrogen for treatment of prostate cancer and is used as a reference chemical for antiandrogenic activity in the AR transactivation assays in the OECD test guideline No 458 (Goldspiel & Kohler, 1990; Labrie, 1993; OECD, 2023; Simard et al., 1986).

Procymidone and vinclozolin are fungicides that have been shown to be AR antagonists. Procymidone binds to the AR and inhibits the agonist binding as shown in AR binding assays using rat prostate cytosol (Hosokawa et al., 1993) or AR transfected COS cells (Ostby et al., 1999). Procymidone also inhibits agonist activated transcription in AR reporter assays (Hass et al., 2012; Kojima et al., 2004; Orton et al., 2011; Ostby et al., 1999; Scholze et al., 2020). Vinclozolin binds to the AR and inhibits the agonist binding as shown in AR binding assays using rat epididymis cytosol (Kelce et al., 1997) or AR transfected COS-1 cells (Wong et al., 1995). Vinclozolin also inhibits agonist activated transcription in AR reporter assays (Euling et al, 2002; Kojima et al., 2004; Molina-Molina et al., 2006; Orton et al., 2011; Scholze et al., 2020; Shimamura et al., 2002; Wong et al., 1995). Finasteride is a pharmaceutical that inhibits the 5-alpha-reductase enzyme that converts testosterone to DHT. Finasteride is used to treat benign prostatic hypertrophy (Andersson & Russel, 1990; Rittmaster & Wood, 1994; Stoner, 1990).

Prenatal exposure to DEHP in rats results in reduced production of testosterone in fetal testis measured in ex vivo testis assays, reduced testosterone levels in testis and reduced fetal plasma or serum testosterone levels (Borch et al., 2004; Borch et al., 2006; Culty et al., 2008; Hannas et al., 2011; Hannas et al., 2012; Klinefelter et al., 2012; Parks et al., 2000; Wilson et al., 2004; Wilson et al., 2007; Vo et al., 2009). Two studies don’t show an effect on testosterone levels in testis or fetal plasma testosterone levels, respectively (Andrade et al., 2006; Borch et al., 2006). The precise underlying mechanism is presently unknown.

Evidence for decreased AGD in males (KE1688) by prenatal exposure to flutamide, procymidone, vinclozolin, finasteride and DEHP

All datasets that were used for the weight of evidence assessment were judged as reliable without or with restriction. The majority of datasets assessed showed a decreased male AGD. The conclusion was that the level of confidence was strong for all five substances. The studies are summarized in table 4.

Empirical evidence for the included substances

Table 4. Empirical evidence for decreased AGD in males (KE1688) by prenatal exposure to flutamide, procymidone, vinclozolin, finasteride and DEHP. *One dose only.

>>>>>TABLE 4<<<<<

Species	Exposure window	Measurement timepoint	NOAEL (mg/kg bw/day)	LOAEL (mg/kg bw/day)	Reference
Flutamide
rat	GD12-21	PND1 and PND100	No	6.25	McIntyre et al., 2001
rat	GD16, 17, 18 or 19	PND1 and PND100	--*	50	Foster & Harris, 2005
rat	GD7-21	PND1	No	0.5	Hass et al., 2007
rat	GD6-17 + GD16-21	GD21	No	3	Goto et al., 2004
rat	GD6-PND4	PND4	0.4	2	Yamasaki et al., 2005
rat	GD6-PND1	PND1	0.25	2.5	Fussell et al., 2015
rat	GD13-20	PND4 and PND23	--*	20	Kita et al., 2016
rat	GD11-21	PND 14, 21 and 120	--*	5 mg per rat	Casto et al., 2003
Procymidone
rat	GD7-PND16	at birth, GD22-24	No	12.5	Hass et al., 2012
rat	GD7-PND16	at birth, GD22-24	10	25	Hass et al., 2007
rabbit	GD6-28	GD29	125	No effect	Inawaka et al., 2010
rat	GD14-PND3	PND2	No	25	Ostby et al., 1999
Vinclozolin
Rat	GD16-17 + GD18-19	PND1	--*	400	Wolf et al., 2000
Rat	GD14-19	PND1	No	200	Wolf et al., 2000
Rat	GD7-21	PND1	5	10	Hass et al., 2007
Mouse	GD10-18	PND1 and 7	--*	100	Shimamura et al., 2002
Rat	GD4-PND3	PND2	No	3.125	Gray et al., 1994

Finasteride
rat	GD12-21	PND1 and PND90	No	0.01	Bowman et al., 2003
rat	GD7-21	PND0	0.01	0.1	Christiansen et al., 2009
rat	GD15-21	PND1	0.0003	0.03	Clark et al., 1993
rat	GD15-21	PND22 and PND114-117	0.03	3	Clark et al., 1993
rat	GD12-21	PND1 and PND90	--*	10	Martinez et al., 2011

Epidemiological data on DEHP

The biggest relevant epidemiological dataset was identified on associations between DEHP and AGD.

Six prospective cohort studies and one cross-sectional study on the association between maternal DEHP metabolites and length of AGD (anopenile distance (APD) and anoscrotal distance (ASD)) in boys were assessed as reliable without or with restriction. Decreased AGD (anopenile distance (APD) and/or anoscrotal distance (ASD)) was observed in three prospective cohort studies (Martino-Adrade et al., 2016; Swan et al., 2005 reviewed and updated in Swan 2008; Wenzel et al., 2018). In contrast, no significant association was observed in three other prospective cohort studies (Arbuckle et al., 2018; Henriksen et al., 2023; Jensen et al., 2016) and the cross-sectional study (Sunman et al., 2019). This inconsistency introduces a level of uncertainty regarding the overall association. Therefore, the level of confidence was judged as weak.

Dose concordance

Dose concordance is challenging to assess for this KER since in vivo AR activity is currently not possible to measure, but only can be informed indirectly by measures of upstream events.

However, some studies provide useful information that support dose concordance between the KEs.

In a publication by Borch et al., rats were exposed in utero to DEHP at GD7-21. Fetal testosterone levels in testes and serum and testosterone production in fetal testes ex vivo were investigated at GD21, whereas AGD was investigated at PND3. The LOAELs for reduced testosterone production in ex vivo fetal testes and reduced testosterone levels in fetal testes were 300 mg/kg/d, whereas the LOAEL for decreased AGD in male offspring was 750 mg/kg/d (Borch et al., 2004).

In a publication by Scholze et al, AR antagonism and decreased testosterone synthesis was quantitatively assessed (IC50) in vitro for a list of substances. In addition, internal concentrations in male fetuses and effects on AGD were measured after fetal exposure to the same substances. In utero exposure to all the substances lead to reduced AGDIndex (AGDI) in the exposed male offspring. Further, for all substances except Cyprodinil, the internal exposure levels in the fetuses leading to reduced AGD exceeded the IC50 levels observed in one or both of the in vitro assays. Three different doses of linuron exposure were included. The medium exposure dose led to a higher level of internal exposure and a higher degree of AGDI reduction than the low dose. AGDI could not be determined in the highest dose due to maternal toxicity (Scholze et al., 2020).

Temporal concordance

Temporal concordance can only be considered from a theoretical perspective since the downstream event, decreased AGD, is usually measured at GD21, PND0 or PND1 in rats, and due to the size of the fetuses is not feasible to measure at earlier timepoints.

Considering the biology, the upstream event – decreased AR activation in vivo – is foreseen to happen minutes to hours after exposure. If a substance decreases AR activation through inhibition of the AR, the upstream event is expected to happen immediately after exposure. If a substance decreases androgen receptor activation through inhibition of testosterone synthesis, the upstream event is expected to happen minutes to hours after the exposure, though it is uncertain exactly when the change will be big enough to be measurable. On the other hand, the downstream event – decreased AGD - is a measurement of relative growth of the perineal tissue, which is expected to take days in the developing fetus.

Uncertainties and Inconsistencies

Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance. More help

For the model substances, there were some inconsistencies in the empirical evidence, but they could be explained by differences in study designs and uncertainties in measurements, see appendix 1.

Species differences in effects of phthalates (including DEHP and DBP) on fetal testes testosterone production have been observed between humans, mice and rats. In human fetal testes exposed to DEHP or DBP in vitro or ex vivo, no suppression of testosterone production is observed, which contrasts observations in rat fetal testes under similar conditions. Also in mice, testosterone production in the fetal testes is unaffected by treatment with DEHP or DBP in vitro or in utero (Sharpe, 2020).

The species differences described above are specific for some phthalates and their interference with fetal testicular testosterone production. This uncertainty should not be reflected on other antiandrogenic substances, especially not those acting through other mechanisms of action. The association between exposure to DEHP and reduced AGD in humans is judged to be weak, which may further support a species difference between rodents and humans, but it may also reflect the large uncertainties inherent in the epidemiological studies.

Observational epidemiological studies face challenges in proving cause-effect relationships as they cannot control conditions like experimental animal and in vitro studies. Human studies can identify associations between variables but cannot offer conclusive proof of causation (Lanzoni et al., 2019). Various study designs and statistical methods are employed to strengthen evidence within the inherent limitations of observational research (Song & Chung, 2010; Olier et al., 2023). Inconsistencies in epidemiological data arise from various factors, such as different methodologies used in exposure and outcome measurement and also in statistical analyses.

These differences collectively contribute to the complexity of interpreting and weighing the evidence in epidemiological research.

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references. More help

A well established modulating factor is genetic variations in the AR which decrease the function of the receptor. For example, longer CAG repeat lengths have been associated with decreased AR activation (Tut et al 1997, Chamberlain et al 1994) and a shorter AGD in adult men (Eisenberg et al., 2013). Other modulating factors being discussed in the literature is maternal age and parity (Barrett et al., 2014), but these associations are only suggestive with more studies needed to confirm the associations (Barrett et al., 2014).

Quantitative Understanding of the Linkage

Captures information that helps to define how much change in the upstream KE, and/or for how long, is needed to elicit a detectable and defined change in the downstream KE. More help

The quantitative understanding of the linkage is low. This is a consequence of it not being possible to measure the upstream and the downstream event in the same study.

Response-response Relationship

Provides sources of data that define the response-response relationships between the KEs. More help

In one study, a quantitative model was developed to predict the decrease in AGD from in vitro AR antagonism or in vitro decreased testosterone synthesis. The authors conclude that predicting the effect on AGD in vivo based on the in vitro results is only possible on a qualitative level, but the model cannot predict AGD reductions quantitatively (Scholze et al., 2020).

Time-scale

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?). More help

AR activation operates on a time-scale of minutes. The AR is a ligand-activated nuclear receptor and transcription factor. Upon ligand binding a conformational change and subsequent dimerization of the AR takes place within 3-6 minutes (Schaufele et al., 2005). Nuclear translocation (Nightingale et al., 2003) and promoter interactions occur within 15 minutes of ligand binding, and RNA polymerase II and coactivator recruitment are then proposed to occur transiently with cycles of approximately 90 minutes (Kang et al., 2002).

For the downstream event, the time-scale for observing a measurable effect on growth of a tissue (in this case the perineum) is closer to days and weeks depending on species. For instance, in humans, the masculinization programming window is presumed to start around GW 8, while a sexual dimorphism of the AGD can first be observed from around GWs 11-13 (Thankamony et al., 2016) and reaches its maximum 2-fold difference around GWs 17-20 (Sharpe, 2020).

It has been demonstrated that exposure to flutamide for one day (Foster & Harris, 2005) or vinclozolin for two days (Wolf et al., 2000) during the sensitive window of exposure can elicit a detectable decrease in the AGD in male rat offspring.

Known Feedforward/Feedback loops influencing this KER

Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

Not relevant for this KER.

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help

Taxonomic

Fetal masculinization including the AGD is regulated by androgens interacting with the AR in all mammals, including humans (Murashima et al., 2015; Thankamony et al., 2016), although, the size of the AGD and difference between the sexes vary between species. A large number of studies exist showing that fetal exposure to anti-androgens causes shortened AGD in male rats and mice (Schwartz et al., 2019, see also Table 2). Some epidemiological studies find associations between exposure to anti-androgenic compounds and shorter AGD in boys (Thankamony et al., 2016). However, the associations are not very clear and confidence in the data is limited by conflicting results, possibly due to differences in study design and methods for exposure measurements and analyses. Nevertheless, the KER is considered applicable to humans, based on current understanding of the role of AR activation in fetal masculinization.

Life stage

Programming of the AGD occurs during the masculinization programming window in fetal life. This takes place in rats around embryonic days 15.5-19.5 (GD16-20) and likely gestation weeks 8-14 in humans (Welsh et al., 2008). It should be mentioned that though AGD is believed to be relatively stable throughout life, it can be responsive to postnatal changes in androgen levels (Schwartz et al., 2019).

Sex

Data presented in this KER support that disruption of androgen action during fetal life can lead to a short AGD in male offspring. While exposure to chemicals during fetal life can also shorten female AGD, the biological significance and the mechanism driving the effect is unknown (Schwartz et al., 2019).

References

List of the literature that was cited for this KER description. More help

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