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Relationship: 907

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

Degeneration of dopaminergic neurons of the nigrostriatal pathway leads to Neuroinflammation

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
Inhibition of the mitochondrial complex I of nigro-striatal neurons leads to parkinsonian motor deficits adjacent Moderate Moderate Cataia Ives (send email) Open for citation & comment WPHA/WNT Endorsed

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

Sex Applicability

An indication of the the relevant sex for this KER. More help

Life Stage Applicability

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

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

Several chemokines and chemokines receptors (fraktalkine, CD200) control the neuron-microglia interactions and a loss of this control on the side of neurons can trigger microglial reactivity without any further positive signal required (Blank and Prinz, 2013; Chapman et al., 2000; Streit et al., 2001). Upon neuronal injury, signals termed “Damage-Associated Molecular Patterns (DAMPs)” are released by damaged neurons to promote microglial reactivity (Marin-Teva et al., 2011; Katsumoto et al., 2014). These are for instance detected by Toll-like receptors (TLRs) (for review, see Hayward and Lee, 2014). TLR-2 functions as a master sensing receptor to detect neuronal death and tissue damage in many different neurological conditions including nerve transection injury, traumatic brain injury and hippocampal excitotoxicity (Hayward and Lee, 2014). Astrocytes, the other cellular actor of neuroinflammation besides microglia (Ranshoff and Brown, 2012) are also able to sense tissue injury via e.g. TLR-3 (Farina et al., 2007; Rossi, 2015), and neuronal injury can result in astrocytic activation (Efremova, 2015).

The SNpc can be particularly vulnarable to the inflammatory process; its contains more microglia than astrocytes when compared with other areas of the brain and this can promote stronger neuroinfammation (Mena et al. 2008, Kim et al. 2000).

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 Map 2.0

ID Experimental Design Species Upstream Observation Downstream Observation Citation (first author, year) Notes

Evidence Map

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help
Title First Author
Biological Plausibility
Dose Concordance
Temporal Concordance
Incidence Concordance
Biological Plausibility
Dose Concordance Evidence
Temporal Concordance Evidence
Incidence Concordance Evidence
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

• Triggering of glia by injured neurons may not necessarily be due to the damage of neurons, but it may also be due to released synuclein (Sanchez-Guajardo, 2010)

• In a AAV alpha-synucleinoptahy model, it was shown that cytoskeletal perturbation and accumulation of alpha-synuclein were sufficient to induce microglial reactivity, suggesting that neuroinflammation appears early in the disease process and is not a result triggered by cell death (Chung et al., 2009)

• Direct effects of toxicants on glia cannot be completely excluded. They have been reported for most toxicants in one or the other publication (rotenone, paraquat, MPP+) (Zhang et al., 2014; Rappold et al., 2011; Brooks et al., 1989). The overwhelming evidence speaks against such effects for rotenone and MPP+ (Klintworth et al., 2009), but for paraquat there is evidence of direct interaction with microglial membrane NADPH oxidase (Rappold et al., 2011).

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

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

Beside the rodent models, the concept of vicious circle with neuronal injury leading to neuroinflammation and neuroinflammation triggering or enhancing neurodegeneration is described in several neurodegenerative diseases in human, without any sex restriction (Hirsch and Hunot, 2009; Tansey and Goldberg, 2009; Griffin et al., 1998; McGeer and Mc Geer, 1998; Blasko et al., 2004; Cacquevel et al., 2004; Rubio-Perez and Morillas-Ruiz, 2012; Thundyil and Lim, 2014; Barbeito et al., 2010). Aging is an aggravating factor and increases the risk for developing a neurodegenerative disease (Kawas et al., 2000; Blasko et al., 2004).