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Relationship: 1268

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

Activation, Constitutive androstane receptor leads to Altered expression of hepatic CAR-dependent genes

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
Constitutive androstane receptor activation leading to hepatocellular adenomas and carcinomas in the mouse and the rat adjacent High Moderate Brendan Ferreri-Hanberry (send email) Open for citation & comment EAGMST Under Review

Taxonomic Applicability

Select one or more structured terms that help to define the biological applicability domain of the KER. In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER. Authors can indicate the relevant taxa for this KER in this subsection. The process is similar to what is described for KEs (see pages 30-31 and 37-38 of User Handbook) More help
Term Scientific Term Evidence Link
rat Rattus norvegicus High NCBI
mouse Mus musculus High NCBI
human Homo sapiens 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
Mixed 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
All life stages 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

Activation of CAR by an endogenous or foreign substance leads to translocation of the CAR-RXR heterodimer into the nucleus, and this dimer binds to DNA recognition elements in the regulatory region of CAR-responsive genes. CAR activation thus alters gene expression and upregulates xenobiotic-metabolizing enzymes such as CYP2B, CYP2C, CYP3A, sulfotransferases, UDP-glucuronyltransferases and glutathione transferases, as well as xenobiotic transporters such as Mrp2 and Mrp4 (Omiecinski et al., 2011a). In addition, CAR alters genes involved in lipid homeostasis, glucose utilization and energy metabolism. In rats and mice, the expression of additional genes involved in cell proliferation and apoptosis control are altered; Gadd45beta and Cdc20 are examples of genes that function in this way and are upregulated in mice within hours of treatment with a CAR activator (Peffer et al., 2018aPeffer et al., 2018bTojima et al., 2012).

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

For the MIE of CAR activation, direct measurement of this step after exposure to a stressor in vivo is difficult to attain, because of the complex sequence of intermediate steps that follow. Nuclear translocation of a fluorescently tagged CAR molecule following activation by a stressor such as phenobarbital has been observed in vitro in hepatocytes, and occurs fairly rapidly (i.e. within a few hours) (Chen et al., 2010). More commonly, indirect measurements of downstream effects, and absence of those effects in CAR-null mice or rats, are employed to demonstrate that a particular molecule or other stressor can activate CAR (Huang et al., 2005Peffer et al., 2018bPeffer et al., 2007Yamamoto et al., 2004).

Following the activation of CAR by stressors such as phenobarbital, TCPOBOP or metofluthrin in rats or mice, the in vivo and in vitro data are strong that demonstrate a characteristic pattern of changes in CAR-responsive genes. The data for these example molecules are described further within this KER.

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

It is highly plausible that activation of CAR would produce changes in expression of specific genes, since transcription of genes specifically associated with CAR response elements is how this nuclear receptor achieves its biological effects (Tien and Negishi, 2006). In mice, rat and human hepatocytes, CAR activation produces changes in genes related to CYP2B and CYP3A enzymes, certain sulfotransferase and glucuronyltransferase enzymes, hepatic transport proteins and genes related to lipid and glucose metabolism (Maglich et al., 2003Omiecinski et al., 2011bOmiecinski et al., 2011aTien and Negishi, 2006). In mice and rats, CAR activation has been shown to also achieve alterations in genes that give an overall pathway change associated with increased progression through the cell cycle such as Gadd45b and Cdc20 (Deguchi et al., 2009Geter et al., 2014Ross et al., 2010Tojima et al., 2012).

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

In general, CAR activators show very consistent, large fold-increases for the characteristic expression of Cyp2b isoforms across in vivo studies in multiple species and with many different molecules. While certain genes related to a pro-proliferative effect appear to be CAR-mediated and reproducibly impacted in multiple studies (Currie et al., 2014Deguchi et al., 2009Geter et al., 2014Peffer et al., 2007Tojima et al., 2012), there are examples where changes in a specific gene was not observed. For example, Ross et al. (2010) tested 80 mg/kg/day (ip dosing) phenobarbital for 4 days in WT C57BL/6J mice, and they observed a 15.8-fold increase in Cdc20, but did not see an increased expression of Gadd45b. Mapping of a specific genes’ changes following activation of CAR by a particular CAR activator may be affected by the species, strain, dose level and time point examined, as well as the other non-CAR effects of that molecule. Examining for a significant pathway change is likely to be a more reliable measure of this Key Event Relationship (Oshida et al., 2015a), but this is also somewhat dependent on the experimental design, the species and duration of treatment, and the pathway analysis tools.

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

Because the extent or degree of activation of CAR is not readily measurable with in vivo studies, the nature of the relationship between CAR activation and altered mRNA expression (e.g. linear, exponential, other) cannot be stated. In addition, the direction of change in certain CAR-responsive genes is variable, in that CAR activation causes an increase in expression of some genes and a decrease in expression of other genes. For example, in mice treated with TCPOBOP by ip injection, Tojima et al. (2012) showed large increases in expression of Cyp2b10 (151x), Cdc20 (37x) and Gadd45b (14x), plus decreases in expression of lipid-related genes Acsl5 (0.5x), Slc21a1 (0.2x) and Hmgcs2 (0.3x). The different fold-change values for specific genes also indicates that the magnitude of the gene expression differences can be very dependent on the properties of the individual gene, and whether it is normally active or quiescent prior to treatment with a CAR activator.

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

The onset of CAR activation (upstream KE) and the time scale of measurable differences in gene expression (downstream KE) are influenced by variables such as pharmacokinetics and route of administration of an administered stressor. However, it is established that exposure of the livers of mice to a CAR activator (TCPOBOP) by intraperitoneal injection, thus bypassing the intestinal transit and absorption processes, was able to achieve large changes in gene expression in the liver after 12 hours (Tojima et al., 2012). The cascade of normal biological events following CAR activation by a ligand (i.e. binding, nuclear translocation, altered gene expression, and post-transcriptional modifications of mRNA) likely takes several hours to be completed, after which a measurable difference vs. control in mRNA levels is detectable by RT-PCR or microarrays. After the initial perturbation by a stressor of CAR, the time course of changes in gene expression is indefinite. That is, some gene expression changes can continue to be observed for as long as the CAR activator is present. For example, in mice treated with phenobarbital for up to 32 weeks following initiation with a single dose of diethylnitrosamine, differences in gene expression of CAR-responsive genes such as Gadd45b and Cdc2 continued to be observed throughout the entire treatment period in both non-neoplastic liver tissue and in liver tumors of treated vs. untreated animals (Phillips et al., 2009a).

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

Activation of PXR (NR1I2), a related nuclear receptor to CAR (NR1I3), is a possible confounding factor that may be operative for certain substances. There is much cross-talk between CAR and PXR, and similar responsive genes, and a particular agent could produce a mixed set of gene expression response by activating both PXR and CAR (Tojima et al., 2012; Stanley et al., 2006).

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

In terms of this specific KER1 of activation of CAR (MIE) leading directly to altered expression of CAR-responsive genes (KE1), there are no known feedback loops that would affect this overall process.  As an example of this lack of feedback alteration, when mice were treated long-term with phenobarbital, they continued to show significant changes in expression of CAR-responsive genes up through 32 weeks of treatment (Phillips et al., 2009).

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

CAR receptors are present in the livers of virtually all mammalian species; however, there are important differences in protein sequence and thus ligand binding properties (Omiecinski et al., 2011bReschly and Krasowski, 2006). In reporter assays for mouse, rat, dog and human CAR, clear qualitative as well as quantitative differences in the ability of suspected CAR activators to activate CAR from the different species were demonstrated (Omiecinski et al., 2011b). In terms of the specific KER of CAR activation directly leading to altered gene expression specific to CAR activation, in vitro hepatocyte experiments indicate that human hepatocytes have only partial overlap with mice and rats in terms of the genes that are affected. In particular, genes that are related to CYP induction (e.g. Cyp2b isoforms) show increases in expression across mouse, rat and human if the CAR molecule for that species is activated, but the pro-proliferative gene pathways  have been shown to be activated only in mice and rats (Elcombe et al., 2014Hasmall and Roberts, 1999Hirose et al., 2009Lake, 2009).  For example, the total number of altered genes in livers of chimeric mice that reflected human hepatocytes (293) compared to livers of similarly treated CD-1 mice (846) was much lower, and only 10 differentially expressed genes (primarily CYP genes) were common to both species’ liver samples following treatment with phenobarbital at dose levels of 1000 – 2500 ppm in the diet (Yamada et al., 2014).

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

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