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Relationship: 364

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

Cell injury/death leads to N/A, Neurodegeneration

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
Binding of agonists to ionotropic glutamate receptors in adult brain causes excitotoxicity that mediates neuronal cell death, contributing to learning and memory impairment. adjacent Moderate Allie Always (send email) Open for citation & comment TFHA/WNT Endorsed
Acetylcholinesterase Inhibition Leading to Neurodegeneration adjacent High Allie Always (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

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

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

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

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

There is well established mechanistic understanding supporting the relationship between these two KEs.

Neurodegeneration in the strict sense of the word, is referring to any pathological condition primarily affecting brain cell populations (Przedborski et al., 2003). At histopathological level, neurodegenerative conditions are described by neuronal death and reactive gliosis (Przedborski et al., 2003).

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

Zebrafish has been exposed for 36-weeks to DomA and has showed no excitotoxic neuronal death and no histopathological lesions in glutamate-rich brain areas (Hiolski et al., 2014).

Administration of DomA (9.0 mg DomA kg(-1) bw, i.p.) to Sparus aurata (seabream) leads to measurement of 0.61, 0.96, and 0.36 mg DomA kg(-1) of brain tissue at 1, 2 and 4 hours. At this dose but also at lower concentrations (0.45 and 0.9 mg DomA kg(-1) bw) no major permanent brain damage has been detected (Nogueira et al., 2010). Leopard sharks possess the molecular target for DomA but it has been shown to be resistant to doses of DomA that can cause neurotoxicity to other vertebrates, suggesting the presence of some protective mechanism (Schaffer et al., 2006).

All these reports support the view that there is possible a species specific susceptibility to DomA toxicity.

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
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
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
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

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

There is an overall agreement regarding the histopathology of the brain lesions related to acute DomA neurotoxicity across certain species. Data derived from humans, rodents, non-human primates and sea lions suggest that common neudegeneration features in selected brain areas are found despite the fact that study design, estimated exposure, processing of samples and history of event may differ (Pulido, 2008).

Furthermore, the distribution of brain damage by DomA has also been established by magnetic resonance imaging microscopy (MRM) for both human and rat, demonstrating similar distribution as that described by histopathological studies (Pulido, 2008).

It is important to notice that human sensitivity to DomA exposure is well documented in the published literature and seems to be much higher than in other species (Lefebvre and Robertson 210; Barlow et al., 2004).In 1987 in Canada, more than 200 people became acutely ill after ingesting of mussels contaminated with DomA. The outbreak resulted in 20 hospitalizations and four deaths. Clinical effects observed included gastrointestinal symptoms and neurotoxic effects such as hallucinations, memory loss and coma. For this reason, the condition was termed amnesic shellfish poisoning (Barlow et al., 2004). The neurotoxic properties of domoic acid result in neuronal degeneration and necrosis in specific regions of the hippocampus (Teitelbaum et al., 1990).

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

Ananth C, Thameem DS, Gopalakrishnakone P, Kaur C., Domoic acid-induced neuronal damage in the rat hippocampus: changes in apoptosis related genes (bcl-2, bax, caspase-3) and microglial response. J Neurosci Res., 2001, 66: 177-190.

Ananth C, Gopalakrishnakone P, Kaur C., Induction of inducible nitric oxide synthase expression in activated microglia following domoic acid (DA)-induced neurotoxicity in the rat hippocampus. Neurosci Lett., 2003, 338: 49-52.

Antequera D, Bolos M, Spuch C, Pascual C, Ferrer I, Fernandez-Bachiller MI, Rodríguez-Franco MI, Carro E., Effects of a tacrine-8-hydroxyquinoline hybrid (IQM-622) on Aβ accumulation and cell death: involvement in hippocampal neuronal loss in Alzheimer's disease. Neurobiol Dis., 2012, 46: 682-691.

Appel NM, Rapoport SI, O'Callaghan JP., Sequelae of parenteral domoic acid administration in rats: comparison of effects on different anatomical markers in brain. Synapse, 1997, 25: 350-358.

Barlow Jeffery B, T, Moizer K, Paul S, and Boyle C., Amnesic shellfish poison. Food Chem Toxicol., 42: 545-557.

Cendes F, Andermann F, Carpenter S, Zatorre RJ, Cashman NR., Temporal lobe epilepsy caused by domoic acid intoxication: evidence for glutamate receptor-mediated excitotoxicity in humans. Ann Neurol., 1995, 37: 123-6.

Colman JR, Nowocin KJ, Switzer RC, Trusk TC, Ramsdell JS., Mapping and reconstruction of domoic acid-induced neurodegeneration in the mouse brain. Neurotoxicol Teratol., 2005, 27: 753-767.

Hiolski EM, Kendrick PS, Frame ER, Myers MS, Bammler TK, Beyer RP, Farin FM, Wilkerson HW, Smith DR, Marcinek DJ, Lefebvre KA., Chronic low-level domoic acid exposure alters gene transcription and impairs mitochondrial function in the CNS. Aquat Toxicol., 2014, 155: 151-159.

Jakobsen B, Tasker A, Zimmer J., Domoic acid neurotoxicity in hippocampal slice cultures. Amino Acids, 2002, 23: 37-44.

Lefebvre Kathi A. and Robertson Alison, Domoic acid and human exposure risks: A review, Toxicon, 2010, 56: 218–230.

Lu J, Wu DM, Zheng YL, Hu B, Cheng W, Zhang ZF., Purple sweet potato color attenuates domoic acid-induced cognitive deficits by promoting estrogen receptor-α-mediated mitochondrial biogenesis signaling in mice. Free Radic Biol Med., 2012, 52: 646-659.

Nogueira I, Lobo-da-Cunha A, Afonso A, Rivera S, Azevedo J, Monteiro R, Cervantes R, Gago-Martinez A, Vasconcelos V., Toxic effects of domoic acid in the seabream Sparus aurata. Mar Drugs, 2010, 8: 2721-2732.

Przedborski S, Vila M, Jackson-Lewis V., Neurodegeneration: What is it and where are we? J Clin Invest., 2003, 111: 3-10.

Pulido OM., Domoic acid toxicologic pathology: a review. Mar Drugs, 2008, 6: 180-219.

Qiu S, Currás-Collazo MC., Histopathological and molecular changes produced by hippocampal microinjection of domoic acid. Neurotoxicol Teratol., 2006, 28: 354-362.

Scallet AC, Schmued LC., Johannessen JN. Neurohistochemical biomarkers of the marine neurotoxicant, domoic acid. Neurotoxicol Teratol., 2005, 27: 745-752.

Schaffer P, Reeves C, Casper DR, Davis CR., Absence of neurotoxic effects in leopard sharks, Triakis semifasciata, following domoic acid exposure. Toxicon., 2006, 47: 747-752.

Slikker W Jr, Scallet AC, Gaylor DW., Biologically-based dose-response model for neurotoxicity risk assessment. Toxicol Lett., 1998, 102-103: 429-433.

Teitelbaum JS, Zatorre RJ, Carpenter S, Gendron D, Evans AC, Gjedde A, and Cashman NR., Neurologic sequelae of domoic acid intoxication due to the ingestion of contaminated mussels. N Engl J Med., 1990, 322: 1781-1787.

Tiedeken JA, Muha N, Ramsdell JS., A cupric silver histochemical analysis of domoic acid damage to olfactory pathways following status epilepticus in a rat model for chronic recurrent spontaneous seizures and aggressive behavior. Toxicol Pathol., 2013a, 41: 454-69.

Tiedeken JA, Ramsdell JS., Persistent neurological damage associated with spontaneous recurrent seizures and atypical aggressive behavior of domoic acid epileptic disease. Toxicol Sci., 2013b, 133: 133-43.

Truelove J, Mueller R, Pulido O, Martin L, Fernie S, Iverson F., 30-day oral toxicity study of domoic acid in cynomolgus monkeys: lack of overt toxicity at doses approaching the acute toxic dose. Nat Toxins., 1997, 5: 111-114.

Tryphonas L, Truelove J, Nera E, Iverson F., Acute neurotoxicity of domoic acid in the rat. Toxicol Pathol., 1990, 18: 1-9.