To the extent possible under law, AOP-Wiki has waived all copyright and related or neighboring rights to KER:1688

Relationship: 1688

Title

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

Cell injury/death leads to Neuronal network function, Decreased

Upstream event
The causing Key Event (KE) in a Key Event Relationship (KER). More help
Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER). 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

AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
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 adjacent Moderate Brendan Ferreri-Hanberry (send email) Under development: Not open for comment. Do not cite EAGMST Approved

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KER.In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER.  More help
Term Scientific Term Evidence Link
rat Rattus norvegicus High NCBI
mouse Mus musculus High NCBI
fathead minnow Pimephales promelas Moderate NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help
Sex Evidence
Male
Female

Life Stage Applicability

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

Key Event Relationship Description

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

Under physiological conditions, in the developing nervous system, apoptosis occurs during the process of synaptogenesis, where competition leads to the loss of excess neurons and to the connection of the appropriate neurons (Buss et al., 2006; Mennerick and Zorumski, 2000; Oppenheim, 1991). When a stressor increases the number of apoptotic cells this KE has a negative effect on synaptogenesis as the reduced number of neurons (besides the ones that have been already eliminated through the physiological process of apoptosis) provides limited dendritic fields for receiving synaptic inputs from incoming axons. At the same time the loss of neurons also means that there are less axons to establish synaptic contacts (Olney, 2014), leading to reduced synaptogenesis. The ability of a neuron to communicate is based on neural network formation that relies on functional synapse establishment (Colón-Ramos, 2009). The main roles of synapses are the regulation of intercellular communication in the nervous system, and the information flow within neural networks. The connectivity and functionality of neural networks depends on where and when synapses are formed. Therefore, the decreased synapse formation due to cell death during the process of synaptogenesis is critical and leads to decrease of neural network formation and function in the adult brain.

Synaptic transmission and plasticity require the integrity of the anatomical substrate. The connectivity of axons emanating from one set of cells to post-synaptic side of synapse on the dendrites of the receiving cells must be intact for effective communication between neurons. Changes in the placement of cells within the network due to delays in neuronal migration, the absence of a full formation of dendritic arbors and spine upon which synaptic contacts are made, and the lagging of transmission of electrical impulses due to insufficient myelination will individually and cumulatively impair synaptic function.

Therefore, chemicals inducing neuronal cell death by apoptosis or necrosis, or interfering with a particular system of neurotransmitters, will alter network structure and function.

Evidence Collection Strategy

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

Evidence Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help
Biological Plausibility
Addresses the biological rationale for a connection between KEupstream and KEdownstream.  This field can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured.   More help

Recently, Dekkers et al. 2013 have reviewed how under physiological conditions components of the apoptotic machinery in developing brain regulate synapse formation and neuronal connectivity. For example, caspase activation is known to be required for axon pruning during development to generate neuronal network (reviewed in Dekkers et al., 2013). Experimental work carried out in Drosophila melanogaster and in mammalian neurons shows that components of apoptotic machinery are involved in axonal degeneration that can consequently interfere with synapse formation (reviewed in Dekkers et al., 2013). Furthermore, Bax mutant mice studies indicate that the lack of this pro-apoptotic protein BAX leads to disruption of intrinsically photosensitive retinal ganglion cells spacing and dendritic stratification that affects synapse localization and function (Chen et al., 2013).

Neuronal network formation and function are established via the process of synaptogenesis. The developmental period of synaptogenesis is critical for the formation of the basic circuitry of the nervous system, although neurons are able to form new synapses throughout life (Rodier, 1995). The brain electrical activity dependence on synapse formation is critical for proper neuronal communication.

Alterations in synaptic connectivity lead to refinement of neuronal networks during development (Cline and Haas, 2008). Indeed, knockdown of PSD-95 arrests the functional and morphological development of glutamatergic synapses (Ehrlich et al., 2007).

Studies of the last 30 years demonstrated that astrocytes possess functional receptors for neurotransmitters and respond to their stimulation via release of gliotransmitters, including glutamate. These findings have led to a new concept of neuron–glia intercommunication where astrocytes play an unsuspected dynamic role by integrating neuronal inputs and modulating synaptic activity (Rossi and Volterra, 2009). According to the concept termed "tripartite synapse", the emerging view is that brain function actually arises from the coordinated activity of a network comprising both neurons and astrocytes. Furthermore, myelinating glial cells are well-known to insulate axons and to speed up action potential propagation. Be it motor skill learning or social behaviors in higher vertebrates, proper myelination is critical in shaping brain functions. Neurons rely on their myelinating partners not only for setting conduction speed, but also for regulating the ionic environment and fueling their energy demands with metabolites. Also, long-term axonal integrity and neuronal survival are maintained by oligodendrocytes and loss of this well-coordinated axon-glial interplay contributes to brain diseases (Saab and Nave, 2017). Therefore, reduction in glial cell number and/or reduction in myelination of axons, will very much impact the neural network function.

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

Ogawa et al. (2011) reported decreased apoptosis and an increase in the number of Gabaergic interneurons in the dentate gyrus of Sprague-Dawley pups either maternally exposed to acrylamide or directly injected with acrylamide.

Although it appears evident that a decrease in cell number, in dendritic arborization or in axonal growth, as well as synapse alterations may lead to decreased neuronal network formation and function, the exact mechanism remain to be elucidated.

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references.  More help
Response-response Relationship
Provides sources of data that define the response-response relationships between the KEs.  More help
Time-scale
Information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). More help
Known Feedforward/Feedback loops influencing this KER
Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

Domain of Applicability

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

Support for the link between cell injury/death and decreased neuronal network formation and function can be found in rat, mouse and minnow. (for references, see empirical evidences)

References

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

Buss, R.R., Sun, W., Oppenheim, R.W., 2006. Adaptive roles of programmed cell death during nervous system development. Annu Rev Neurosci 29, 1-35.

Chen, S.K., Chew, K.S., McNeill, D.S., Keeley, P.W., Ecker, J.L., Mao, B.Q., Pahlberg, J., Kim, B., Lee, S.C., Fox, M.A., Guido, W., Wong, K.Y., Sampath, A.P., Reese, B.E., Kuruvilla, R., Hattar, S., 2013. Apoptosis regulates ipRGC spacing necessary for rods and cones to drive circadian photoentrainment. Neuron 77, 503-515.

Cline, H., Haas, K., 2008. The regulation of dendritic arbor development and plasticity by glutamatergic synaptic input: a review of the synaptotrophic hypothesis. J Physiol 586, 1509-1517.

Colon-Ramos, D.A., 2009. Synapse formation in developing neural circuits. Curr Top Dev Biol 87, 53-79.

Dekkers, M.P., Nikoletopoulou, V., Barde, Y.A., 2013. Cell biology in neuroscience: Death of developing neurons: new insights and implications for connectivity. J Cell Biol 203, 385-393.

Ehrlich, I., Klein, M., Rumpel, S., Malinow, R., 2007. PSD-95 is required for activity-driven synapse stabilization. Proc Natl Acad Sci U S A 104, 4176-4181.

Falluel-Morel, A., Sokolowski, K., Sisti, H.M., Zhou, X., Shors, T.J., Dicicco-Bloom, E., 2007. Developmental mercury exposure elicits acute hippocampal cell death, reductions in neurogenesis, and severe learning deficits during puberty. J Neurochem 103, 1968-1981.

Ferraro, L., Tomasini, M.C., Tanganelli, S., Mazza, R., Coluccia, A., Carratu, M.R., Gaetani, S., Cuomo, V., Antonelli, T., 2009. Developmental exposure to methylmercury elicits early cell death in the cerebral cortex and long-term memory deficits in the rat. Int J Dev Neurosci 27, 165-174.

Jacob, S., Thangarajan, S., 2017. Effect of Gestational Intake of Fisetin (3,3',4',7-Tetrahydroxyflavone) on Developmental Methyl Mercury Neurotoxicity in F1 Generation Rats. Biol Trace Elem Res 177, 297-315.

Mennerick, S., Zorumski, C.F., 2000. Neural activity and survival in the developing nervous system. Mol Neurobiol 22, 41-54.

Nagashima, K., 1997. A review of experimental methylmercury toxicity in rats: neuropathology and evidence for apoptosis. Toxicol Pathol 25, 624-631.

Nagashima, K., Fujii, Y., Tsukamoto, T., Nukuzuma, S., Satoh, M., Fujita, M., Fujioka, Y., Akagi, H., 1996. Apoptotic process of cerebellar degeneration in experimental methylmercury intoxication of rats. Acta Neuropathol 91, 72-77.

Ogawa, B., Ohishi, T., Wang, L., Takahashi, M., Taniai, E., Hayashi, H., Mitsumori, K., Shibutani, M., 2011. Disruptive neuronal development by acrylamide in the hippocampal dentate hilus after developmental exposure in rats. Arch Toxicol 85, 987-994.

Olney, J.W., 2014. Focus on apoptosis to decipher how alcohol and many other drugs disrupt brain development. Front Pediatr 2, 81.

Oppenheim, R.W., 1991. Cell death during development of the nervous system. Annu Rev Neurosci 14, 453-501.

Perea, G., Navarrete, M., Araque, A., 2009. Tripartite synapses: astrocytes process and control synaptic information. Trends Neurosci 32, 421-431.

Rodier, P.M., 1995. Developing brain as a target of toxicity. Environ Health Perspect 103 Suppl 6, 73-76.

Rossi, D., Volterra, A., 2009. Astrocytic dysfunction: insights on the role in neurodegeneration. Brain Res Bull 80, 224-232.

Saab, A.S., Nave, K.A., 2017. Myelin dynamics: protecting and shaping neuronal functions. Curr Opin Neurobiol 47, 104-112.

Wang, Y.T., Lin, H.C., Zhao, W.Z., Huang, H.J., Lo, Y.L., Wang, H.T., Lin, A.M., 2017. Acrolein acts as a neurotoxin in the nigrostriatal dopaminergic system of rat: involvement of alpha-synuclein aggregation and programmed cell death. Sci Rep 7, 45741.