Aop: 17

Title

Each AOP should be given a descriptive title that takes the form “MIE leading to AO”. For example, “Aromatase inhibition [MIE] leading to reproductive dysfunction [AO]” or “Thyroperoxidase inhibition [MIE] leading to decreased cognitive function [AO]”. In cases where the MIE is unknown or undefined, the earliest known KE in the chain (i.e., furthest upstream) should be used in lieu of the MIE and it should be made clear that the stated event is a KE and not the MIE. More help

Binding of electrophilic chemicals to SH(thiol)-group of proteins and /or to seleno-proteins involved in protection against oxidative stress during brain development leads to impairment of learning and memory

Short name
A short name should also be provided that succinctly summarises the information from the title. This name should not exceed 90 characters. More help
Oxidative stress and Developmental impairment in learning and memory

Graphical Representation

A graphical summary of the AOP listing all the KEs in sequence, including the MIE (if known) and AO, and the pair-wise relationships (links or KERs) between those KEs should be provided. This is easily achieved using the standard box and arrow AOP diagram (see this page for example). The graphical summary is prepared and uploaded by the user (templates are available) and is often included as part of the proposal when AOP development projects are submitted to the OECD AOP Development Workplan. The graphical representation or AOP diagram provides a useful and concise overview of the KEs that are included in the AOP, and the sequence in which they are linked together. This can aid both the process of development, as well as review and use of the AOP (for more information please see page 19 of the Users' Handbook).If you already have a graphical representation of your AOP in electronic format, simple save it in a standard image format (e.g. jpeg, png) then click ‘Choose File’ under the “Graphical Representation” heading, which is part of the Summary of the AOP section, to select the file that you have just edited. Files must be in jpeg, jpg, gif, png, or bmp format. Click ‘Upload’ to upload the file. You should see the AOP page with the image displayed under the “Graphical Representation” heading. To remove a graphical representation file, click 'Remove' and then click 'OK.'  Your graphic should no longer be displayed on the AOP page. If you do not have a graphical representation of your AOP in electronic format, a template is available to assist you.  Under “Summary of the AOP”, under the “Graphical Representation” heading click on the link “Click to download template for graphical representation.” A Powerpoint template file should download via the default download mechanism for your browser. Click to open this file; it contains a Powerpoint template for an AOP diagram and instructions for editing and saving the diagram. Be sure to save the diagram as jpeg, jpg, gif, png, or bmp format. Once the diagram is edited to its final state, upload the image file as described above. More help

Authors

List the name and affiliation information of the individual(s)/organisation(s) that created/developed the AOP. In the context of the OECD AOP Development Workplan, this would typically be the individuals and organisation that submitted an AOP development proposal to the EAGMST. Significant contributors to the AOP should also be listed. A corresponding author with contact information may be provided here. This author does not need an account on the AOP-KB and can be distinct from the point of contact below. The list of authors will be included in any snapshot made from an AOP. More help

Florianne Tschudi-Monnet, Department of Physiology, University of Lausanne, Switzerland, and Swiss Center for Applied Human Toxicology (SCAHT), Florianne.Tschudi-Monnet@unil.ch

Marie-Gabrielle Zurich, Department of Physiology, University of Lausanne and SCAHT, Switzerland, mzurich@unil.ch

Carolina Nunes, Department of Physiology, University of Lausanne, Switzerland, carolina.nunes@unil.ch

Jenny Sandström, SCAHT, Switzerland, jsm.sandstrom@gmail.com

Rex FitzGerald, SCAHT, Switzerland, rex.fitzgerald@unibas.ch

Michael Aschner, Albert Einstein College of Medecine, New York, USA, michael.aschner@einstein.yu.edu

Joao Rocha, Department of Biochemistry and Molecular Biology, Federal University of Santa Maria, Santa Maria, Brazil, jbtrocha@gmail.com

The authors of KEs AOPwiki ID 1392 (oxidative stress), 55 (Cell injury/death), 386 (Decrease network function), of the AO (Learning and memory, impairment), and of KER 359 (decrease network function leads to impairment in learning and memory) are greatly acknowledged.

 

Point of Contact

Indicate the point of contact for the AOP-KB entry itself. This person is responsible for managing the AOP entry in the AOP-KB and controls write access to the page by defining the contributors as described below. Clicking on the name will allow any wiki user to correspond with the point of contact via the email address associated with their user profile in the AOP-KB. This person can be the same as the corresponding author listed in the authors section but isn’t required to be. In cases where the individuals are different, the corresponding author would be the appropriate person to contact for scientific issues whereas the point of contact would be the appropriate person to contact about technical issues with the AOP-KB entry itself. Corresponding authors and the point of contact are encouraged to monitor comments on their AOPs and develop or coordinate responses as appropriate.  More help
Marie-Gabrielle Zurich   (email point of contact)

Contributors

List user names of all  authors contributing to or revising pages in the AOP-KB that are linked to the AOP description. This information is mainly used to control write access to the AOP page and is controlled by the Point of Contact.  More help
  • Florianne Tschudi-Monnet
  • Marie-Gabrielle Zurich

Status

The status section is used to provide AOP-KB users with information concerning how actively the AOP page is being developed, what type of use or input the authors feel comfortable with given the current level of development, and whether it is part of the OECD AOP Development Workplan and has been reviewed and/or endorsed. “Author Status” is an author defined field that is designated by selecting one of several options from a drop-down menu (Table 3). The “Author Status” field should be changed by the point of contact, as appropriate, as AOP development proceeds. See page 22 of the User Handbook for definitions of selection options. More help
Author status OECD status OECD project SAAOP status
Under development: Not open for comment. Do not cite EAGMST Under Review 1.13 Included in OECD Work Plan
This AOP was last modified on February 07, 2020 05:32
The date the AOP was last modified is automatically tracked by the AOP-KB. The date modified field can be used to evaluate how actively the page is under development and how recently the version within the AOP-Wiki has been updated compared to any snapshots that were generated. More help

Revision dates for related pages

Page Revision Date/Time
Binding, Thiol/seleno-proteins involved in protection against oxidative stress February 06, 2020 08:47
Oxidative Stress March 12, 2020 14:26
Glutamate dyshomeostasis November 29, 2019 04:53
Cell injury/death September 11, 2020 08:27
Neuroinflammation September 11, 2020 08:28
Decrease of neuronal network function May 28, 2018 11:36
Impairment, Learning and memory March 16, 2020 09:20
Tissue resident cell activation October 08, 2018 05:22
Increased Pro-inflammatory mediators March 16, 2020 05:27
Decreased protection against oxidative stress February 04, 2020 03:44
Binding, SH/SeH proteins involved in protection against oxidative stress leads to Protection against oxidative stress, decreased February 10, 2020 09:40
Protection against oxidative stress, decreased leads to Oxidative Stress February 07, 2020 04:27
Oxidative Stress leads to Glutamate dyshomeostasis February 06, 2020 11:57
Glutamate dyshomeostasis leads to Cell injury/death February 06, 2020 11:20
Cell injury/death leads to Neuroinflammation November 07, 2019 09:36
Cell injury/death leads to Tissue resident cell activation August 02, 2018 03:02
Neuroinflammation leads to Cell injury/death November 07, 2019 10:27
Increased pro-inflammatory mediators leads to Cell injury/death February 12, 2018 04:58
Cell injury/death leads to Neuronal network function, Decreased February 05, 2020 12:26
Neuronal network function, Decreased leads to Impairment, Learning and memory December 03, 2019 04:44
Oxidative Stress leads to Cell injury/death February 07, 2020 09:32
Methylmercuric(II) chloride November 29, 2016 18:42
Mercuric chloride November 29, 2016 18:42
Acrylamide November 08, 2017 11:15

Abstract

In the abstract section, authors should provide a concise and informative summation of the AOP under development that can stand-alone from the AOP page. Abstracts should typically be 200-400 words in length (similar to an abstract for a journal article). Suggested content for the abstract includes the following: The background/purpose for initiation of the AOP’s development (if there was a specific intent) A brief description of the MIE, AO, and/or major KEs that define the pathway A short summation of the overall WoE supporting the AOP and identification of major knowledge gaps (if any) If a brief statement about how the AOP may be applied (optional). The aim is to capture the highlights of the AOP and its potential scientific and regulatory relevance More help

This Adverse Outcome Pathway (AOP) describes the linkage between binding to sulfhydryl(SH)-/seleno-proteins involved in protection against oxidative stress and impairment in learning and memory, the Adverse Outcome (AO). Binding to SH-/ seleno-proteins involved in protection against oxidative stress has been defined as the Molecular Initiating Event (MIE). Production, binding and degradation of Reactive Oxygen Radicals (ROS) are tightly regulated, and an imbalance between production and protection may cause oxidative stress, which is common to many toxicity pathways. Oxidative stress may lead to an imbalance in glutamate neurotransmission, which is involved in learning and memory. Oxidative stress may also cause cellular injury and death. During brain development and in particular during the establishment of neuronal connections and networks, such perturbations may lead to functional impairment in learning and memory. Neuroinflammation (Resident cell activation; Increased pro-inflammatory mediators) is triggered early in cell injury cascades and is considered as an exacerbating factor. The weight-of-evidence supporting the relationship between the described key events is based mainly on developmental effects observed after an exposure to the heavy metal, mercury, known for its strong affinity to many SH-/seleno-containing proteins, but in particular to those having anti-oxidant properties, such as glutathione (GSH). The overall assessment of this AOP is considered as strong, based on the biological plausibility, the empirical support and on the essentiality of the Key Events (KEs), which are moderate to strong, since blocking, preventing or attenuating an upstream KE is mitigating the downstream KE. The gap of knowledge is mainly due to limited quantitative evaluations, impeding thus the development of predictive models.

Background (optional)

This optional subsection should be used to provide background information for AOP reviewers and users that is considered helpful in understanding the biology underlying the AOP and the motivation for its development. The background should NOT provide an overview of the AOP, its KEs or KERs, which are captured in more detail below. Examples of potential uses of the optional background section are listed on pages 24-25 of the User Handbook. More help

This AOP was originally started in a workshop report entitled: Adverse Outcome Pathways (AOP) relevant to Neurotoxicity and published in Critical Review in Toxicol: Bal-Price, A., Crofton, K.M., Sachana, M., Shafer, T.J., Behl, M., Forsby, A., Hargreaves, A., Landesmann, B., Lein, P.J., Louisse, J., Monnet-Tschudi, F., Paini, A., Rolaki, A., Schrattenholz, A., Sunol, C., van Thriel, C., Whelan, M., Fritsche, E., 2015. Putative adverse outcome pathways relevant to neurotoxicity. Crit Rev Toxicol 45(1), 83-91.

The process of inflammation is common to many tissues and can be described by several KEs, as proposed in a dedicated workshop (Villeneuve et al., 2018). Brain inflammation called Neuroinflammation can be described by the two common KEs: Tissue resident cell, activation and pro-inflammatory mediators, increased. However, Neuroinflammation is a concept accepted by the regulators and is found in the whole literature describing brain inflammation. Therefore, in accord with the external reviewers, we decided to use the KE Neuroinflammation  for building the KERs of this AOP, but we introduced in the list of the KEs the two KEs common to the inflammatory process, as proposed in Villeneuve et al., 2018.

Summary of the AOP

This section is for information that describes the overall AOP. The information described in section 1 is entered on the upper portion of an AOP page within the AOP-Wiki. This is where some background information may be provided, the structure of the AOP is described, and the KEs and KERs are listed. More help

Events:

Molecular Initiating Events (MIE)
An MIE is a specialised KE that represents the beginning (point of interaction between a stressor and the biological system) of an AOP. More help
Key Events (KE)
This table summarises all of the KEs of the AOP. This table is populated in the AOP-Wiki as KEs are added to the AOP. Each table entry acts as a link to the individual KE description page.  More help
Adverse Outcomes (AO)
An AO is a specialised KE that represents the end (an adverse outcome of regulatory significance) of an AOP.  More help
Sequence Type Event ID Title Short name
1 MIE 1487 Binding, Thiol/seleno-proteins involved in protection against oxidative stress Binding, SH/SeH proteins involved in protection against oxidative stress
2 KE 1538 Decreased protection against oxidative stress Protection against oxidative stress, decreased
3 KE 1392 Oxidative Stress Oxidative Stress
4 KE 1488 Glutamate dyshomeostasis Glutamate dyshomeostasis
5 KE 55 Cell injury/death Cell injury/death
6 KE 188 Neuroinflammation Neuroinflammation
7 KE 1492 Tissue resident cell activation Tissue resident cell activation
8 KE 1493 Increased Pro-inflammatory mediators Increased pro-inflammatory mediators
9 KE 386 Decrease of neuronal network function Neuronal network function, Decreased
10 AO 341 Impairment, Learning and memory Impairment, Learning and memory

Relationships Between Two Key Events (Including MIEs and AOs)

This table summarises all of the KERs of the AOP and is populated in the AOP-Wiki as KERs are added to the AOP. Each table entry acts as a link to the individual KER description page.To add a key event relationship click on either Add relationship: events adjacent in sequence or Add relationship: events non-adjacent in sequence.For example, if the intended sequence of KEs for the AOP is [KE1 > KE2 > KE3 > KE4]; relationships between KE1 and KE2; KE2 and KE3; and KE3 and KE4 would be defined using the add relationship: events adjacent in sequence button.  Relationships between KE1 and KE3; KE2 and KE4; or KE1 and KE4, for example, should be created using the add relationship: events non-adjacent button. This helps to both organize the table with regard to which KERs define the main sequence of KEs and those that provide additional supporting evidence and aids computational analysis of AOP networks, where non-adjacent KERs can result in artifacts (see Villeneuve et al. 2018; DOI: 10.1002/etc.4124).After clicking either option, the user will be brought to a new page entitled ‘Add Relationship to AOP.’ To create a new relationship, select an upstream event and a downstream event from the drop down menus. The KER will automatically be designated as either adjacent or non-adjacent depending on the button selected. The fields “Evidence” and “Quantitative understanding” can be selected from the drop-down options at the time of creation of the relationship, or can be added later. See the Users Handbook, page 52 (Assess Evidence Supporting All KERs for guiding questions, etc.).  Click ‘Create [adjacent/non-adjacent] relationship.’  The new relationship should be listed on the AOP page under the heading “Relationships Between Two Key Events (Including MIEs and AOs)”. To edit a key event relationship, click ‘Edit’ next to the name of the relationship you wish to edit. The user will be directed to an Editing Relationship page where they can edit the Evidence, and Quantitative Understanding fields using the drop down menus. Once finished editing, click ‘Update [adjacent/non-adjacent] relationship’ to update these fields and return to the AOP page.To remove a key event relationship to an AOP page, under Summary of the AOP, next to “Relationships Between Two Key Events (Including MIEs and AOs)” click ‘Remove’ The relationship should no longer be listed on the AOP page under the heading “Relationships Between Two Key Events (Including MIEs and AOs)”. More help

Network View

The stressor field is a structured data field that can be used to annotate an AOP with standardised terms identifying stressors known to trigger the MIE/AOP. Most often these are chemical names selected from established chemical ontologies. 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. Although AOPs themselves are not chemical or stressor-specific, linking to stressor terms known to be relevant to different AOPs can aid users in searching for AOPs that may be relevant to a given stressor. More help

Stressors

The stressor field is a structured data field that can be used to annotate an AOP with standardised terms identifying stressors known to trigger the MIE/AOP. Most often these are chemical names selected from established chemical ontologies. 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. Although AOPs themselves are not chemical or stressor-specific, linking to stressor terms known to be relevant to different AOPs can aid users in searching for AOPs that may be relevant to a given stressor. More help
Name Evidence Term
Methylmercuric(II) chloride High
Mercuric chloride High
Acrylamide Low

Life Stage Applicability

Identify the life stage for which the KE is known to be applicable. More help
Life stage Evidence
During brain development

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) can be selected. In many cases, individual species identified in these structured fields will be those for which the strongest evidence used in constructing the AOP was available in relation to this KE. More help
Term Scientific Term Evidence Link
rat Rattus norvegicus High NCBI
mouse Mus musculus High NCBI
human Homo sapiens Moderate NCBI

Sex Applicability

The authors must select from one of the following: Male, female, mixed, asexual, third gender, hermaphrodite, or unspecific. More help
Sex Evidence
Male
Female

Overall Assessment of the AOP

This section addresses the relevant biological domain of applicability (i.e., in terms of taxa, sex, life stage, etc.) and WoE for the overall AOP as a basis to consider appropriate regulatory application (e.g., priority setting, testing strategies or risk assessment). The goal of the overall assessment is to provide a high level synthesis and overview of the relative confidence in the AOP and where the significant gaps or weaknesses are (if they exist). Users or readers can drill down into the finer details captured in the KE and KER descriptions, and/or associated summary tables, as appropriate to their needs.Assessment of the AOP is organised into a number of steps. Guidance on pages 59-62 of the User Handbook is available to facilitate assignment of categories of high, moderate, or low confidence for each consideration. While it is not necessary to repeat lengthy text that appears elsewhere in the AOP description (or related KE and KER descriptions), a brief explanation or rationale for the selection of high, moderate, or low confidence should be made. More help

Experimental and epidemiological evidences indicate that compared to the adult central nervous system (CNS), the developing CNS is generally more susceptible to toxicant exposure (Costa et al., 2004; Grandjean and Landrigan, 2006). Pre-natal and post-natal exposure may have long-term consequences, i.e. not detected immediately at the end of the exposure period. Such effects on visuospatial memory for example have been described on child development in communities with chronic low level mercury exposure (Castoldi et al., 2008a; Debes et al., 2006; Grandjean et al., 2014; Lam et al., 2013).

The aim of this AOP is to capture the KEs and the KERs that occur after binding to thiol- and selenol groups of proteins involved in protection against oxidative stress, the MIE, and impairment in learning and memory, the AO, which is a neurotoxicity marker belonging to the OECD regulatory tool box. The chemical initiators used for the empirical support are methylmercury and mercury chloride, and acrylamide. Data are most extensive for mercury as stressor during development; data for acrylamide are much more limited and restricted to some KEs. Chronic, low-dose prenatal MeHg exposure from maternal consumption of fish has been associated with endpoints of neurotoxicity in children, including poor performance on neurobehavioral tests, particularly on tests of attention, fine-motor function, language, visual-spatial abilities (e.g., drawing), and verbal memory (NRC, 2000). However, it is important to note that some uncertainties remain about the effects of low dose of mercury during brain development (Grandjean et al., 1999). Epidemiological studies in Seychelles on prenatal exposure through fish consumption did not evidenced adverse effects on memory when analyses were performed at 22 and 24 years (Van Wyngaarden et al., 2017), whereas similar experiments made in the Faroe Islands revealed dysfunctions in language, attention and memory at 7 years (Grandjean et al., 1997). And a clear association was observed between mercury cord blood level and memory deficit (Grandjean et al., 1997; Debes et al., 2006). Castoldi and coworkers (2008) proposed that modulating factors, such as diet, nutrition, gender, pattern of exposure and co-exposure could explain the discrepancies of these epidemiological studies. Nevertheless, there are experimental evidences showing that the neurocognitive domain, in particular dentate gyrus, hippocampus and cortex are susceptible to the neurotoxicity of mercury in the developing brain (Sokolowski et al., 2011, 2013; Ceccatelli et al., 2013); therefore, we focus on impairment in learning and memory as the AO. Some –SH- or –SeH-containing proteins involved in protection against oxidative stress have been demonstrated to be inhibited by MeHg either in vitro or in vivo, but a causal relationship has not been established between these inhibitory effects and the final pathological events (Oliveira, 2017). However, the analysis of the essentiality of the KEs and of the weight of evidence for the KERs supports a plausible mechanistic link between the MIE and the AO.

Domain of Applicability

The relevant biological domain(s) of applicability in terms of sex, life-stage, taxa, and other aspects of biological context are defined in this section. Biological domain of applicability is informed by the “Description” and “Biological Domain of Applicability” sections of each KE and KER description (see sections 2G and 3E for details). In essence the taxa/life-stage/sex applicability is defined based on the groups of organisms for which the measurements represented by the KEs can feasibly be measured and the functional and regulatory relationships represented by the KERs are operative.The relevant biological domain of applicability of the AOP as a whole will nearly always be defined based on the most narrowly restricted of its KEs and KERs. For example, if most of the KEs apply to either sex, but one is relevant to females only, the biological domain of applicability of the AOP as a whole would be limited to females. While much of the detail defining the domain of applicability may be found in the individual KE and KER descriptions, the rationale for defining the relevant biological domain of applicability of the overall AOP should be briefly summarised on the AOP page. More help

This AOP is mainly focused on the developmental period, although it cannot be excluded that long-term exposure in adult may trigger a similar cascade of KEs leading also to impairment in learning and memory, as observed in neurodegenerative diseases such as Alzheimer's disease (Mutter et al., 2004). While no specific sex differences have been analyzed/described for most KEs, Curtis and coworkers (2010) observed a higher level of TNF-a in hippocampus of male prairie wolf than in female, both treated for 10 weeks with inorganic mercury, in the form of HgCl2; whereas Zhang and coworkers (2013) found a higher neuroinflammatory response associated with altered social behavior in female mice offspring than in male, following gestational exposure to HgCl2. However, after developmental methylmercury exposure, long-lasting behavioral alterations were more prominent in males (Ceccatelli et al., 2013; Castoldi et al., 2008b). These discrepancies may be due to sex differences in kinetics or susceptibility (Vahter et al., 2006).

Essentiality of the Key Events

An important aspect of assessing an AOP is evaluating the essentiality of its KEs. The essentiality of KEs can only be assessed relative to the impact of manipulation of a given KE (e.g., experimentally blocking or exacerbating the event) on the downstream sequence of KEs defined for the AOP. Consequently evidence supporting essentiality is assembled on the AOP page, rather than on the independent KE pages that are meant to stand-alone as modular units without reference to other KEs in the sequence.The nature of experimental evidence that is relevant to assessing essentiality relates to the impact on downstream KEs and the AO if upstream KEs are prevented or modified. This includes: Direct evidence: directly measured experimental support that blocking or preventing a KE prevents or impacts downstream KEs in the pathway in the expected fashion. Indirect evidence: evidence that modulation or attenuation in the magnitude of impact on a specific KE (increased effect or decreased effect) is associated with corresponding changes (increases or decreases) in the magnitude or frequency of one or more downstream KEs.When assembling the support for essentiality of the KEs, authors should organise relevant data in a tabular format. The objective is to summarise briefly the nature and numbers of investigations in which the essentiality of KEs has been experimentally explored either directly or indirectly. See pages 50-51 in the User Handbook for further definitions and clarifications.  More help

Support for Essentiality of KEs

Defining Question

Are downstream KEs and/or the AO prevented if an upstream KE is blocked ?

High (Strong)

Moderate

Low (Weak)

Direct evidence from specifically designed experimental studies illustrating essentiality for at least one of the important KEs (e.g. stop/reversibility studies, antagonism, knock out models, etc.)

Indirect evidence that sufficient modification of an expected modulating factor attenuates or augments a KE leading to increase in KE down or AO

No or contradictory experimental evidence on the essentiality of any of the KEs

 

KE1

Decreased protection against oxidative stress

HIGH

RATIONALE: The fact that a decrease in anti-oxidant properties causes oxidative stress is well accepted. In addition, experimental evidences of knocking out proteins involved in protection against oxidative stress incresed the susceptibilty to oxidative stress.

KE2

Oxidative stress

HIGH

RATIONALE: The deleterious consequences of oxidative stress are well accepted in various animal models. Oxygen radical scavengers, such as glutathione, catalase, selenium and cysteine can block the deleterious effects of oxidative stress.

KE3

Glutamate dyshomeostasis

HIGH

RATIONALE: Glutamate is the main excitatory transmitter, and is involved in memory processes, it is well accepted that perturbation of glutamate homeostasis has deleterious functional consequences. Disruption of glutamate signaling is thought to play a role, at least in part, in the etiology underlying several neurodevelopmental disorders, including memory dysfunction.

KE4

Cell Injury/death, increased

HIGH

RATIONALE: Cell injury/death is a highly converging node in AOPs. Decrease in synaptic connectivity or cell loss will in turn induce perturbations in the establishment of neuronal connections and trigger inflammatory responses, which through a feedback loop can exacerbate this KE. Therefore, prevention of cell injury/death by anti-oxidant or by inhibitors of NMDA receptors prevents the downstream KEs.

KE5

Neuroinflammation

KE5' Tissue resident cell activation

KE5'' Pro-inflammatory mediators, increased

MODERATE

RATIONALE: It is widely accepted in different experimental animal models that the use of minocycline, an antibiotic, which blocks microglial reactivity has protective effects, as have other interferences with any inflammatory mediators. However, we rate the essentiality of this KE as moderate given the complexity of the neuroinflammatory response, having either protective/reparative or aggravating consequences,

KE6

Decreased network formation and function

HIGH

RATIONALE: Glutamate neurotransmission is an important mechanism underlying memory function (for review: Featherstone, 2010). During brain development, glutamate has also trophic effects, by stimulating BDNF production or through the activation of the different glutamate receptors. The trophic effect of glutamate receptor activation is developmental stage-dependent and may play an important role in determining the selective survival of neurons that made proper connections (Balazs, 2006).

 AO

Impairment of learning and memory

HIGH

RATIONALE: Impairment in learning and memory is a converging KE in several AOPs related to brain development. Regarding this AOP and its chemical initiators, it was shown that the neurocognitive domain, in particular dentate gyrus, hippocampus and cortex are susceptible to the neurotoxicity of mercury in the developing brain (Sokolowski et al., 2011, 2013; Ceccatelli et al., 2013). Chronic, low-dose prenatal MeHg exposure from maternal consumption of fish has been associated with endpoints of neurotoxicity in children, including poor performance on neurobehavioral tests, particularly on tests of attention, fine-motor function, language, visual-spatial abilities (e.g., drawing), and verbal memory (NRC, 2000). Prenatal MeHg exposure is associated with childhood memory and learning deficits, particularly visual memory performance in school-aged children (Orenstein, 2014).

Evidence Assessment

The biological plausibility, empirical support, and quantitative understanding from each KER in an AOP are assessed together.  Biological plausibility of each of the KERs in the AOP is the most influential consideration in assessing WoE or degree of confidence in an overall hypothesised AOP for potential regulatory application (Meek et al., 2014; 2014a). Empirical support entails consideration of experimental data in terms of the associations between KEs – namely dose-response concordance and temporal relationships between and across multiple KEs. It is examined most often in studies of dose-response/incidence and temporal relationships for stressors that impact the pathway. While less influential than biological plausibility of the KERs and essentiality of the KEs, empirical support can increase confidence in the relationships included in an AOP. For clarification on how to rate the given empirical support for a KER, as well as examples, see pages 53- 55 of the User Handbook.  More help

Dose-response and temporal concordance of KEs

There is no study where all KEs are measured simultaneously after exposure to several doses, impeding a dose-response and concordance analysis. In one single study (in blue in the table), three downstream KEs were measured following pre-natal exposure to methylmercury. Comparisons of all animal studies show that doses used are ranging from 0.5 - 5 mg/kg; but dose-response was seldom performed. In these studies, the time (pre-natal, post-natal, lactation,...) and duration of exposure are quite diverse and no analysis of brain mercury content was made, so it is not possible to compare doses between studies. Therefore, based on the present data, it is impossible to define whether KEs up occur at lower doses and earlier time points than KEs down.

For in vitro studies, KEs up are often measured after acute exposure to high concentrations.

The following table summarizes concentrations/doses, time, and duration of exposure for the various test systems and KEs.

MIE

KE1

KE2

KE3

KE4

KE5

KE6

AO

Binding to SH-/seleno-proteins

Decreased protection against oxidative stress

Oxidative stress

Glutamate dyshomeostasis

Cell injury/death

Neuroinflammation

Decreased network formation and function

Impairment in learning and memory

In vitro

In vivo

In vivo

In vivo

In vivo

In vivo

In vivo

In vivo

Binding of Hg to thiol groups and to various selenium-containing proteins:

Glutathione, thioredoxin reductase, thioredoxin, glutaredoxin, glutathione reductase was measured using purified proteins

(Carvahlo et aé., 2008, 2011; Wiederhold et al., 2010; Sugiura et al., 1978; Arnold et al., 1986; Han et al., 2001; Qiao et al., 2017)

 

C57BL/6J mice dosed with 5 mg MeHg/L in drinking water during gestation and lactation

Cytoplasmic and nuclear TrxR and Cytoplasmic Gpx were reduced in cerebral and cerebellar cortex of 22 days-old offspring

(Ruszkiewicz, 2016)

Male C57BL/6NJcl mice exposed to methylmercury (1.5 mg/kg/day

for 6-weeks)

(Fujimura, 2017)

Adult male Sprague-Dawley rats exposed to methylmercury (1 mg/kg orally for 6 months) (Joshi, 2014)

Zebra fish brain exposed to Hg2+, MeHg 1.8 molar (measured in brain tissue), for 28 days.

(Branco, 2012)

Prenatal and postnatal exposure of mice to 40 ppm of HgCl2 decreased the activity of catalase, thioredoxin reductase, Gpx, superoxide dismutase (Malqui et al., 2017)

Male C57BL/6NJcl mice exposed to methylmercury (1.5 mg/kg/day

for 6-weeks)

(Fujimura, 2017)

Adult male Sprague-Dawley rats exposed to methylmercury (1 mg/kg orally for 6 months) (Joshi, 2014)

Adult male Sprague-Dawley rats exposed to methylmercury (1 mg/kg orally for 6 months) (Joshi, 2014)

Zebra fish brain exposed to Hg2+, MeHg 1.8 molar (measured in brain tissue), for 28 days.

(Branco, 2012)

Prenatal and postnatal exposure of mice to 40 ppm of HgCl2 caused oxidative stress evaluated by increased lipid peroxidation (Malqui et al., 2017)

Rat Young (3-4 weeks) dosed with acrylamide by gavage (5, 15, 30 mg/

kg, 5 applications per week during 4 weeks)

(Tian, 2018)

Microdialysis probe in adult Wistar rats showed that acute exposure to methylmercury (10, 100 mM) induced an increase release of extracellular glutamate (9.8 fold at 10 mM and 2.4 fold at 100 mM). This extracellular glutamate level remained elevated at least 90 min.

(Juarez et al., 2002)

Rat, perinatal exposure to methylmercury (GD7-PD21, i.e. 35 days)

0.5 mg/kg bw/day in drinking water

(Roda et al., 2008)

Rat Young (3-4 weeks) exposed to acrylamide by gavage (5, 15, 30 mg/kg, 5 applications per week during 4 weeks)

(Tian, 2018)

Rat pregnant

exposed to methylmercury (1.5 mg/kg orally) from GD5 till parturition                (Jacob, 2017)

Rat, perinatal exposure to methylmercury (GD7-PD21, i.e. 35 days)

0.5 mg/kg bw/day in drinking water

(Roda et al., 2008)

Monkeys, 6,12,18 months oral exposure

50 mg/kg bw

(Charleston et al., 1996)

Mice dosed during postnatal week 1-3 with subcutaneous 2-5 mg mercury chloride/kg/once per week  (Eddins et al., 2008)

Pregnant rat dosed on GD 15 with 8 mg/kg of methylmercury by gavage. Offsprings were tested at day 16, 21 and 60. (Cagiano et al., 1990)

Rat pregnant

exposed to methylmercury (1.5 mg/kg orally) from GD5 till parturition               (Jacob, 2017)

Mice dosed during postnatal week 1-3 with subcutaneous 2-5 mg mercury chloride/kg/once per week (Eddins et al., 2008)

Pregnant rat dosed on GD 15 with 8 mg/kg of methylmercury by gavage. Offsprings were tested at day 16, 21 and 60.     (Cagiano et al., 1990)

Rat pregnant

exposed to methylmercury (1.5 mg/kg orally) from GD5 till parturition                (Jacob, 2017)

Pregnant mice received 0.5 mg methylmercury/kg/day in drinking water from gestational day 7 until day 7 after delivery. Offspring behavior was monitored at 5-15 and 26-36 weeks of age.                (Onishchenko et al., 2007)

Balb mice exposed to methylmercury in diet (low dose: 1.5 mg/kg; high dose: 4.5 mg/kg) during 11 weeks (6 weeks prior mating, 3 weeks during gestation and 2 weeks post-partum). Offsprings tested at PD 15 showed an accumulation of Hg in brain (0.08 mg/kg for low dose and 0.25 mg/kg for the high dose)                (Glover et al., 2009)

Prenatal and postnatal exposure of mice to 40 ppm of HgCl2 caused impairment of memory (object recognition, Y maze) Malqui et al., 2017)

In vitro

In vitro

In vitro

In vitro

In vitro

 

Mouse primary cortical cultures exposed to 5 mM of methylmercury for 24h

(Rush, 2012)

MeHg inhibits ex vivo rat thioredoxin reductase; IC50 0.158 μM (cerebral),

(Wagner et al., 2010)

Mouse primary cortical cultures exposed to 5 mM of methylmercury for 24h

(Rush, 2012)

Methylmercury (2-10 µM) in synaptic vesicles isolated from rat brain (with LD50 at 50 µM ).

(Porciuncula et al., 2003)

Mouse

astrocytes, neurons in mono- or co-cultures exposed to methylmercury 1-50 µM for 24h                    (Morken, 2005)

Methylmercury (2-10 µM) in synaptic vesicles isolated from rat brain (with LD50 at 50 µM).

(Porciuncula et al., 2003

Mouse

astrocytes, neurons in mono- or co-cultures exposed to methylmercury 1-50 µM for 24h                   (Morken, 2005)

3D rat brain cell cultures

10 day treatment

HgCl2 10-9-10-6M

MeHgCl 10-9-3x10-7M

(Monnet-Tschudi et al., 1996; Eskes et al., 2002)

In human in vitro

In human in vitro

In human

Human neuroblastoma cells (SH-SY5Y)exposed to 1 µM of methylmercury for 6 or 24 h

(Branco, 2017; Franco, 2009)

Human neuroblastoma cells (SH-SY5Y)exposed to 1 µM of methylmercury for 6-24 h

(Franco, 2009)

Maternal peripartum hair mercury level was measured to assess prenatal mercury exposure. The concentrations of mercury was found in the range of 0.3-5.1 µg/g, similar to fish-eating population in US. Statistical analyses revealed that each ug/g increase in hair Hg was associated with a decrement in visual memory, learning and verbal memory.   (Orenstein et al., 2014)

Epidemiological studies in the Faroe Islands revealed that mercury exposure through fish consumption (maternal hair conc. 10 ug/g) dysfunctions in memory, language and attention at age 7  (Grandjean et al., 1997; Debes et al., 2006)

Biological Plausibility and Empirical Support of the KERs  

Support for Biological Plausibility of KERs

Defining Question

Is there a mechanistic (i.e. structural or functional) relationship between KEup and KEdown consistent with established biological knowledge?

High (Strong)

Moderate

Low (Weak)

Extensive understanding of the KER based on extensive previous documentation and broad acceptance

The KER is plausible based on analogy to accept biological relationship but scientific understanding is not completely established

There is empirical support for a statistical association between KEs but the structural or functional relationship between them is not understood

MIE to KE Decrease protection against oxidative stress

MODERATE

RATIONALE: Thiol- and selenol containing proteins, which mainly belong to the anti-oxidant protections, have a high affinity for binding soft metals such as mercury (Farina, 2011). Binding to these thiol/sulfhydryl/SH/SeH groups results in structural modifications affecting the catalytic capacity, and thereby reducing the capacity to neutralize ROS. However, binding to other SH/SeH groups of other proteins not involved in protection against oxidative stress can occur and trigger other neurotoxicity pathways.

KE Decrease protection against oxidative stress to KE Oxidative stress

HIGH

RATIONALE: Oxidative stress is defined as an imbalance in the production of reactive oxygen species (ROS) and antioxidant defenses. Several studies have shown depletion of GSH, the main anti-oxidant, and an increase in oxidative stress following methylmercury or mercury chloride exposures (Meinerz, 2011; Rush, 2012; Agrawal, 2015). Protection against oxidative stress was observed by supplementation with diphenyl selenide (Meinerz, 2011) or by glutathione ester (Rush, 2012). Limited conflicting data.

KE Oxidative stress to KE Glutamate (Glu) dyshomeostasis

LOW

RATIONALE: Glutamate transport is driven by the Na+ ion gradient, which is dependent on the Na/K ATPase, which, in turn, requires energy. Glutamate enters the cells accompanied by 2 Na+and an H+.  Perturbations of energy metabolism such as mitochondrial dysfunction and increased production of ROS will lead to glutamate dyshomeostasis, due to the indirect coupling of glutamate transporters with ATP level, and to the important role of glutamate transporters in glutamate homeostasis. (Boron and Boulpaep, 2003). Methylmercury was shown to inhibit both the H+-ATPase activity and vesicular glutamate uptake (Porciuncula et al., 2003). As, on one hand, ROS production can interfere with glutamate uptake, and on the other hand, glutamate accumulation leads to excitotoxicity and ROS production, the exact sequence of the KER is difficult to assess. But the fact that both KEs are involved in mercury-induced neurotoxicity is broadly accepted (Farina et al., 2011; Antunes dos Santos et al., 2016; Morris et al., 2017; Kern et al., 2016).

KE Glutamate dyshomeostasis to KE Cell injury/death

HIGH

RATIONALE: Glutamate dyshomeostasis, in particular excess of glutamate in the synaptic cleft, leads to overactivation of ionotropic glutamate receptors, referred to as excitotoxicity. This, in turn, will cause cell injury/death via ROS production. This KER is also inherent to the developing brain, where glutamate ionotropic receptors are expressed early in various neural cells and when NMDA receptors are expressed in neurons. There is empirical support for all three chemical initiators (mercury, acrylamide, acrolein). In addition, several experiments aiming at blocking glutamate excitotoxicity and the resulting ROS production are protective for cell injury/death. Limited conflicting data.

KE Cell injury/death to KE Neuroinflammation

MODERATE

RATIONALE: It is widely accepted that cell/neuronal injury and death lead to neuroinflammation (microglial and astrocyte reactivities) in adult brain, and in the developing brain, where neuroinflammation was observed after cell injury/death induced by excitotoxic lesions (Acarin et al., 1997; Dommergues et al., 2003). Empirical support is available for all three chemical initiators (mercury, acrylamide, acrolein).  Few experiments, showing a protection when blocking any feature of neuroinflammation have been described. There are some contradicting data showing an absence of neuroinflammatory response despite the occurrence of mercury-induced apotosis and slight behavioral alterations.

KE Neuroinflammation to KE Cell injury/death

MODERATE

RATIONALE: In vitro co-culture experiments have demonstrated that reactive glial cells (microglia and astrocytes) can kill neurons via the release of pro-inflammatory cytokines, such as TNF-a, IL-1b and IL-6 and/or ROS/RNS (Chao et al., 1995; Brown and Bal-Price, 2003; Kraft and Harry, 2011; Taetzsch and Block, 2013) and that interventions aiming at blocking these inflammatory biomolecules can rescue the neurons (Yadav et al., 2012; Brzozowski et al., 2015). Several reports showed that modulating mercury or acrylamide-induced neuroinflammation was protective for neurons. Because of the complexity of the neuroinflammatory response, that can have neuroprotective or neurodegenerative consequences depending on the duration, local environment or still unknown factors, the rating of this KER was kept as moderate. The vicious cycle between cell injury/death and neuroinflammation is well known and was described in other AOPs. Neuroinflammation could be considered as a modulating factor, but because of the numerous inhibiting experiments, it is considered as an essential KE. Some conflicting data due to the dual role of some inflammatory mediators have been reported.

KE Cell injury/death to KE Decreased network formation and function

HIGH

RATIONALE: Neuronal network formation and functional crosstalk are established via synaptogenesis. It was shown that under physiological conditions components of the apoptotic machinery in the developing brain regulate synapse formation and neuronal connectivity (Dekkers et al., 2013). The brain’s electrical activity dependence on synapse formation is critical for proper neuronal communication. Glial cells are also involved in the establishment and stabilization of the neuronal network. Extensive experimental support for the adverse effects of mercury on synaptogenesis exist, establishing a strong link between mercury-induced apoptosis and/or neuronal loss and perturbations in a number of neurotransmitter systems (Jacob, 2017; Bridges, 2017) and perturbations of functionality (Falluel-Morel, 2007; Ferraro, 2009; Teixera, 2014; Onishchenko, 2007). Limited protective experiments and conflicting data reported.

KE Decreased network formation and function to AO Impairment in learning and memory

HIGH

RATIONALE: A review on the Morris water maze (MWM) (Morris, 1981), as an investigative tool of spatial learning and memory in laboratory rats (Vorhees and Williams, 2006) pointed out that perturbed neuronal networks rather than neuronal death per se in certain regions is responsible for the impairment in MWM performance . Functional integrated neural networks that involve the coordination action of different brain regions are consequently important for spatial learning and memory performance (D'Hooge and De Deyn, 2001). Broad empirical support showing mercury-induced effects on learning and memory as consequence of network disruption (Sokolowski et al. 2013; Eddins et al., 2008; Glover et al., 2009). Similar observations were made in humans (Orenstein et al., 2014; Yorifuji et al., 2011).  Interestingly, behavioral alterations were detected long time after exposure (delayed effects). Few conflicting data have been reported, but other behavioral deficits, such as alterations in motor activity and increased anxiety suggest that systems other than hippocampus-related learning and memory are also affected.

KE oxidative stress to KE Cell injury/death

HIGH

RATIONALE: The central nervous system is especially vulnerable to free radical damage since it has a high oxygen consumption rate, an abundant lipid content and reduced levels of antioxidant enzymes (Coyle and Puttfarcken, 1993; Markesbery, 1997). The developing nervous system is particularly vulnerable to chemical insults (Grandjean & Landrigan, 2014). One reason for this higher vulnerability is the incapacity of immature neural cells to cope with oxidative stress by increasing glutathione (GSH) production (Sandström et al., 2017a). Broad empirical support for mercury and acrylamide showing an association between increased ROS production and/or decreased protection against oxidative stress and apoptosis and/or necrosis (Lu et al., 2011; Sarafian et al., 1994; Allam et al., 2011; Lakshmi et al., 2012). Anti-oxidant treatments proved to be protective. Few conflicting data, except a mercury-induced upregulation of GSH level and GR activity as an adaptive mechanism following lactational exposure to methylmercury (10 mg/L in drinking water) associated with motor deficit, suggesting neuronal impairment (Franco et al., 2006).

Quantitative Understanding

Some proof of concept examples to address the WoE considerations for AOPs quantitatively have recently been developed, based on the rank ordering of the relevant Bradford Hill considerations (i.e., biological plausibility, essentiality and empirical support) (Becker et al., 2017; Becker et al, 2015; Collier et al., 2016). Suggested quantitation of the various elements is expert derived, without collective consideration currently of appropriate reporting templates or formal expert engagement. Though not essential, developers may wish to assign comparative quantitative values to the extent of the supporting data based on the three critical Bradford Hill considerations for AOPs, as a basis to contribute to collective experience.Specific attention is also given to how precisely and accurately one can potentially predict an impact on KEdownstream based on some measurement of KEupstream. This is captured in the form of quantitative understanding calls for each KER. See pages 55-56 of the User Handbook for a review of quantitative understanding for KER's. More help

Some quantitative relationships have been described between the upstream early KEs (MIE, oxidative stress, Cell injury/death), although the diversity of test systems and posology (dosing/exposure amount and duration) hampers comparison between studies. It is more difficult to evaluate quantitative relationships between later downstream KEs, such as Neuroinflammation and Decreased Network Function. Neuroinflammation is a complex adaptive mechanism which is not yet completely understood; it can have neuroprotective or neurodegenerative consequences, depending on triggering signals, duration, microenvironment or other unknown influences, which may determine the outcome of the neuroinflammatory process. Decreased network function is currently difficult to quantify because quantitative technologies for mapping and understanding of brain networks (and their plasticity) are still under development.

Optimally, we would like data from a single type of test system showing that exposure to stressor, e.g. mercury, is correlated with changes in all KEs. Such models are emerging, using cells of human origin (Pamies et al., 2016; Sandström et al., 2017b; Fritsche et al., 2017) and/or non-mammalian models, such as zebrafish (Geier et al., 2018; Padilla et al., 2018) and will allow in the future generation of quantitative data which may be used for in silico hazard prediction.

Summary table of Quantitative Evaluations

Dose

CH3Hg (MeHg; methylmercury)

KE

Decreased protection against oxidative stress

KE

Oxidative stress

KE

Glutamate Dyshomeostasis

KE

Cell injury/death

KE

Neuroinflammation

KE

Decreased network function

AO

Impairment, Learning and memory

5 uM (mouse brain in vitro

(Rush, 2012)

GSH reduced (80% of control)

(24h)

ROS increased (120-150% of control)

(24h)

15–30 uM

(mouse brain, after 40 mg/L in drinking water for 21 days)

(Glaser, 2013)

Cortical mitochondrial  GPx activity decreased (70% of control), GR increased (ca 170% of control)

(21 days)

Cortical mitochondrial TBA-RS increased (ca 140% of control) and complex I, II-III, and IV activity decreased (ca 50% of control).. Brain 8-OHdG content increased (ca 400% of control).

(21 days)

1 uM (mouse cerebral cortex ex vivo after oral dosing)

(Lu et al 2011; conc. from Huang et al 2008)

GSH decreased (ca 50% of control)

(7 weeks)

LPO increased (ca 200% of control)

(7 weeks)

Apoptosis-related gene expression: Bcl-2 decreased, ca 50% of control; Bax, Bak, p53, caspase-3,-5,-7 increased, ca 200-350% of control

(7 weeks)

17-24, 75-89 uM (rat cerebral cortex ex vivo after 4w ip dosing)

(Xu, 2012; Liu 2013; Feng, 2014)

Antioxidants NPSH, SOD, GSH-Px decreased (ca 80% and 50% of control)

(4w)

ROS (DCF) increased (190 and 400% of control at 22,87 μM).

Glutamine synthetase decreased (80 and 50% of control at 24,89 μM)

Glutamate content increased (100 and 120% of control at 24,89 uM).

Glutamine content decreased (80 and 50% of control at 24,89 μM)

(4w)

Apoptosis increased dose-dependently (ca 300 and 853% of control at 24,89 uM).

8-OHdG expression increased (200 and 450% of control at 24,89 uM)

(4w)

HgCl2 (mercuric chloride; Hg2+)

KE

Decrease of protection against oxidative stress

KE

Oxidative stress

KE

Glutamate Dyshomeostasis

KE

Cell injury/death

KE

Neuroinflammation

KE

Decreased network function

AO

Impairment, Learning and memory

6 uM (rat brain, 1.13 ug Hg/g)

(Agrawal, 2015)

Blood GSH decreased (ca 90% of control)

(6mo)

Serum AST increased (ca 140% of control).

Brain noradrenaline and dopamine content decreased (ca 30% of control).

(6mo)

0.1-100 uM (cultured mouse cerebellar granule cells)

(Fonfria, 2005)

Glutamate (3H-aspartate) uptake inhibited (IC50 3.5 uM).

Glutamate release stimulated (47% of total endogenous glutamate at 10 uM)

(10min)

Cell viability (MTT) decreased (ca 10% of control at 10 uM)

(10 min)

Considerations for Potential Applications of the AOP (optional)

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.To edit the “Considerations for Potential Applications of the AOP” section, on an AOP page, in the upper right hand menu, click ‘Edit.’ This brings you to a page entitled, “Editing AOP.” Scroll down to the “Considerations for Potential Applications of the AOP” section, where a text entry box allows you to submit text. In the upper right hand menu, click ‘Update AOP’ to save your changes and return to the AOP page or 'Update and continue' to continue editing AOP text sections.  The new text should appear under the “Considerations for Potential Applications of the AOP” section on the AOP page. More help
  • Contribution to the network of KEs/AOPs on Developmental Neurotoxicity (DNT)
  • Generating quantitative data by measuring all KEs in a single model after repeated/long term exposure to a wide concentration range of the chemical initiators to facilitate the development of computational predictive approaches

References

List the bibliographic references to original papers, books or other documents used to support the AOP. More help

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