API

Aop: 189

AOP Title

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Short name:

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DIO1 inhib alters metamorphosis

Authors

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Sally A. Mayasich, National Health and Environmental Effects Research Laboratory, US EPA, Duluth, MN, USA <mayasich.sally@epa.gov>

Jonathan T. Haselman, National Health and Environmental Effects Research Laboratory, US EPA, Duluth, MN, USA <haselman.jon@epa.gov>

Sigmund J. Degitz, National Health and Environmental Effects Research Laboratory, US EPA, Duluth, MN, USA <degitz.sigmund@epa.gov>

Michael W. Hornung, National Health and Environmental Effects Research Laboratory, US EPA, Duluth, MN, USA <hornung.michael@epa.gov>

Point of Contact

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Jonathan Haselman

Contributors

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• Jonathan Haselman

Status

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This AOP was last modified on December 03, 2016 16:37

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Revision dates for related pages

Page	Revision Date/Time
Inhibition, Deiodinase 1	November 29, 2016 19:36
Decreased, Triiodothyronine (T3) in tissues	November 29, 2016 19:43
Decreased, Triiodothyronine (T3) in serum	September 16, 2017 10:16
Altered, Amphibian metamorphosis	December 03, 2016 16:37
Inhibition, Deiodinase 1 leads to Decreased, Triiodothyronine (T3) in tissues	December 03, 2016 16:38
Decreased, Triiodothyronine (T3) in tissues leads to Altered, Amphibian metamorphosis	December 03, 2016 16:38

Abstract

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This putative AOP describes an adverse outcome that results from the inhibition of Type I iodothyronine deiodinase (DIO1) during amphibian metamorphosis. Initial development of this AOP is based on literature in which amphibian deiodinases are genetically disrupted and prediction from tissue expression patterns. Chemical inhibition of DIO1, the molecular-initiating event (MIE), results in decreased transformation of thyroxine (T4) to the active form, 3,5,3’-triiodothyronine (T3), but also decreased inactivation of T3 to 3,3’,5’-triiodothyronine (rT3). Thyroid hormones (THs) are essential for normal sequential development of amphibian tissues and organs, and activities of the three deiodinases found in amphibians, as in mammals, function in a highly regulated balance. Therefore, chemicals that interfere with the DIO1 catalyzing reaction of T4 to T3 have the potential to cause insufficiency of the active form, but also disrupt the balance between active T3 and inactive rT3. Consequences of T4/T3/rT3 imbalance may vary based on timing of exposure and produce different effects in different tissues at different developmental stages. For example, T3 insufficiency due to DIO1 inhibition in the African clawed frog, Xenopus laevis, within several days post-fertilization (pre-metamorphosis) could affect brain development, and like the DIO2 enzyme, DIO1 inhibition in peripheral tissues through the larval phase and post-metamorphic climax may cause alterations in limb development, intestinal remodeling, gill resorption and/or tail resorption.

Background (optional)

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Summary of the AOP

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Stressors

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Describes stressors known to trigger the MIE and provides evidence supporting that initiation. This will often be a list of prototypical compounds demonstrated to interact with the target molecule in the manner detailed in the MIE description to initiate a given pathway (e.g., 2,3,7,8-TCDD as a prototypical AhR agonist; 17α-ethynyl estradiol as a prototypical ER agonist). However, depending on the information available, this could also refer to chemical categories (i.e., groups of chemicals with defined structural features known to trigger the MIE). It can also include non-chemical stressors such as genetic or environmental factors. The evidence supporting the stressor will typically consist of a brief description and citation of literature showing that particular stressors can trigger the MIE.

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Molecular Initiating Event

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Key Events

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Adverse Outcome

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Relationships Between Two Key Events (Including MIEs and AOs)

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Network View

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Life Stage Applicability

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Taxonomic Applicability

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Sex Applicability

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Graphical Representation

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Click to download graphical representation template

Overall Assessment of the AOP

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This section addresses the relevant domain of applicability (i.e., in terms of taxa, sex, life stage, etc.) and weight of evidence for the overall hypothesised AOP (i.e., including the MIE, KEs and AO) as a basis to consider appropriate regulatory application (e.g., priority setting, testing strategies or risk assessment). It draws upon the evidence assembled for each KER as one of several components which contribute to relative confidence in supporting information for the entire hypothesised pathway. An important component in assessing confidence in supporting information as a basis to consider regulatory application of AOPs beyond that described in Section 6 is the essentiality of each of the key events as a component of the entire pathway. This is normally investigated in specifically-designed stop/reversibility studies or knockout models (i.e., those where a key event can be blocked or prevented). Assessment of the overall AOP also contributes to the identification of KEs for which confidence in the quantitative relationship with the AO is greatest (i.e., to facilitate determining the most sensitive predictor of the AO).

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Domain of Applicability

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The relevant domain(s) of applicability in terms of sex, life-stage, taxa, and other aspects of biological context are defined in this section. Domain of applicability is informed by the “Description” and “Taxonomic Relevance” section of each KE description and the “Description of the KER” section of each KER description. The relevant domain of applicability of the AOP as a whole will most often be defined based on the most narrowly restricted of its KEs. For example, if most of the KEs apply to either sex, but one is relevant to females only, the domain of applicability of the AOP as a whole would generally be limited to females. While much of the detail defining the domain of applicability may be found in the individual KE descriptions, the rationale for defining the relevant domain of applicability of the overall AOP should be briefly summarised on the AOP page.

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Essentiality of the Key Events

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The essentiality of various of the KEs is influential in considering confidence in an overall hypothesised AOP for potential regulatory application being secondary only to biological plausibility of KERs (Meek et al., 2014; 2014a). The defining question for determining essentiality (included in Annex 1) relates to whether or not downstream KEs and/or the AO is prevented if an upstream event is experimentally blocked. It is assessed, generally, then, on the basis of direct experimental evidence of the absence/reduction of downstream KEs when an upstream KE is blocked or diminished (e.g., in null animal models or reversibility studies). Weight of evidence for essentiality of KEs would be considered high if there is direct evidence from specifically designed experimental studies illustrating essentiality for at least one of the important key events [e.g., stop/reversibility studies, antagonism, knock out models, etc.) moderate if there is indirect 25 evidence that experimentally induced change of an expected modulating factor attenuates or augments a key event (e.g., augmentation of proliferative response (KEupstream) leading to increase in tumour formation (KEdownstream or AO)) and weak if there is no or contradictory experimental evidence of the essentiality of any of the KEs (Annex 1).

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Weight of Evidence Summary

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This involves evaluation of the Overall AOP based on Relative Level of Confidence in the KERs, Essentiality of the KEs and Degree of Quantitative Understanding based on Annexes 1 and 2. Annex 1 (“Guidance for assessing relative level of confidence in the Overall AOP”) guides consideration of the weight of evidence or degree of confidence in the predictive relationship between pairs of KEs based on KER descriptions and support for essentiality of KEs. It is designed to facilitate assignment of categories of high, moderate or low against specific considerations for each a series of defined element based on current experience in assessing MOAs/AOPs. In addition to increasing consistency through delineation of defining questions for the elements and the nature of evidence associated with assignment to each of the categories, importantly, the objective of completion of Annex 1 is to transparently delineate the rationales for the assignment based on the specified considerations. While it is not necessary to repeat lengthy text which appears in earlier parts of the document, the entries for the rationales should explicitly express the reasoning for assignment to the categories, based on the considerations for high, moderate or low weight of evidence included in the columns for each of the relevant elements. 24 While the elements can be addressed separately for each of the KERs, the essentiality of the KEs within the AOP is considered collectively since their interdependence is often illustrated through prevention or augmentation of an earlier or later key event. Where it is not possible to experimentally assess the essentiality of the KEs within the AOP (i.e., there is no experimental model to prevent or augment the key events in the pathway), this should be noted. Identified limitations of the database to address the biological plausibility of the KERs, the essentiality of the KEs and empirical support for the KERs are influential in assigning the categories for degree of confidence (i.e., high, moderate or low). Consideration of the confidence in the overall AOP is based, then, on the extent of available experimental data on the essentiality of KEs and the collective consideration of the qualitative weight of evidence for each of the KERs, in the context of their interdependence leading to adverse effect in the overall AOP. Assessment of the overall AOP is summarized in the Network View, which represents the degree of confidence in the weight of evidence both for the rank ordered elements of essentiality of the key events and biological plausibility and empirical support for the interrelationships between KEs. The AOP-Wiki provides such a network graphic based on the information provided in the MIE, KE, AO, and KER tables. The Key Event Essentiality calls are used to determine the size of each key event node with larger sizes representing higher confidence for essentiality. The Weight of Evidence summary in the KER table is used to determine the width of the lines connecting the key events with thicker lines representing higher confidence.

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Quantitative Considerations

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The extent of quantitative understanding of the various KERs in the overall hypothesised AOP is also critical in consideration of potential regulatory application. For some applications (e.g. doseresponse analysis in in depth risk assessment), quantitative characterisation of downstream KERs may be essential while for others, quantitative understanding of upstream KERs may be important (e.g., QSAR modelling for category formation for testing). Because evidence that contributes to quantitative understanding of the KER is generally not mutually exclusive with the empirical support for the KER, evidence that contributes to quantitative understanding should generally be considered as part of the evaluation of the weight of evidence supporting the KER (see Annex 1, footnote b). General guidance on the degree of quantitative understanding that would be characterised as weak, moderate, or strong is provided in Annex 2.

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Considerations for Potential Applications of the AOP (optional)

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At their discretion, the developer may include in this section discussion of the potential applications of an AOP to support regulatory decision-making. This may include, for example, possible utility for test guideline development or refinement, development of integrated testing and assessment approaches, development of (Q)SARs / or chemical profilers to facilitate the grouping of chemicals for subsequent read-across, screening level hazard assessments or even risk assessment. While it is challenging to foresee all potential regulatory application of AOPs and any application will ultimately lie within the purview of regulatory agencies, potential applications may be apparent as the AOP is being developed, particularly if it was initiated with a particular application in mind. This optional section is intended to provide the developer with an opportunity to suggest potential regulatory applications and describe his or her rationale. Detailing such considerations can aid the process of transforming narrative descriptions of AOPs into practical tools. In this context, it is necessarily beneficial to involve members of the regulatory risk assessment community on the development and assessment team. The Network view which is generated based on assessment of weight of evidence/degree of confidence in the hypothesized AOP taking into account the elements described in Section 7 provides a useful summary of relevant information as a basis to consider appropriate application in a regulatory context. Consideration of application needs then, to take into consideration the following rank ordered qualitative elements: Confidence in biological plausibility for each of the KERs Confidence in essentiality of the KEs Empirical support for each of the KERs and overall AOP The extent of weight of evidence/confidence in both these qualitative elements and that of the quantitative understanding for each of the KERs (e.g., is the MIE known, is quantitative understanding restricted to early or late key events) is also critical in determining appropriate application. For example, if the confidence and quantitative understanding of each KER in a hypothesised AOP are low and or low/moderate and the evidence for essentiality of KEs weak (Section 7), it might be considered as appropriate only for applications with less potential for impact (e.g., prioritisation, category formation for testing) versus those that have immediate implications potentially for risk management (e.g., in depth assessment). If confidence in quantitative understanding of late key events is high, this might be sufficient for an in depth assessment. The analysis supporting the Network view is also essential in identifying critical data gaps based on envisaged regulatory application.

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References

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Galton, V.A., Schneider, M.J., Clark, A.S., St. Germain, D.L. (2009). “Life without thyroxine to 3,5,3’-triiodothyronine conversion: studies in mice devoid of the 5’-deiodinases.” Endocrinology 150(6): 2957–2963.

Kuiper, G.G.J.M., Klootwijk, W., Morvan-Dubois, G., Destree, O., Darras, V.M., Van der Geyten, S., Demeneix, B.A., Visser, T.J. (2006). “Characterization of recombinant Xenopus laevis Type I Iodothyronine deiodinase: Substitution of a proline residue in the catalytic center by serine (Pro132Ser) restores sensitivity to 6-propyl-2-thiouricil.” Endocrinology 147(7): 3519-3529.

Morvan-Dubois, G., Demeneix, B.A., Sachs, L.M. (2008). “Xenopus laevis as a model for studying thyroid hormone signaling: From development to metamorphosis.” Mol Cell Endocrinol. 293: 71-79.

Morvan-Dubois, G., Sebillot, A., Kuiper, G.G.J.M., Verhoelst, C.H.J., Darras, V.M., Visser, T.J., Demeneix, B.A. (2006). “Deiodinase activity is present in Xenopus laevis during early embryogenesis.” Endocrinolgy 147(10): 4941-4949.