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Relationship: 2834

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

Tissue resident cell activation leads to Increase, Pro-Inflammatory Mediators

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
Deposition of Energy Leading to Learning and Memory Impairment adjacent Moderate Low Brendan Ferreri-Hanberry (send email) Open for citation & comment

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
human Homo sapiens Low NCBI
mouse Mus musculus Moderate NCBI
rat Rattus norvegicus Moderate NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help
Sex Evidence
Unspecific Moderate

Life Stage Applicability

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

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

Tissue-resident cell activation refers to the stimulation of resident cells in organ systems. Tissue-resident immune cells can be found throughout the body, each tissue and organ containing specific resident immune cells (Chen et al., 2018; Gray & Farber, 2022). Monocytes, found in the blood, and macrophages, found in all tissues in the body, are the main components of the immune system (Ivanova & Orekhov, 2016). In the brain, the primary tissue-resident macrophages are microglia, while astrocytes are also important cells found in the brain (Bourgognon & Cavanagh, 2020; Greene-Schloesser et al., 2012; Wang et al., 2020). Activated tissue-resident cells can undergo gliosis, whereby they adopt a hypertrophic morphology and proliferate, exhibiting rounding of the cell body and retraction of cell processes (Greene-Schloesser et al., 2012; Phatnani & Maniatis, 2015). It is well-characterized that activated tissue-resident cells can increase expression of pro-inflammatory mediators (Hladik & Tapio, 2016; Lumniczky, Szatmari & Safrany, 2017; Kaur et al., 2019). Acute inflammation from controlled biosynthesis of pro-inflammatory mediators protects tissue and promotes healing (Kim & Joh, 2006; Vezzani & Viviani, 2015). Prolonged tissue-resident cell activation leads to dysregulation in production or secretion of pro-inflammatory mediators, which results in chronic inflammation and damage to tissue (Kim & Joh, 2006; Vezzani & Viviani, 2015). Additionally, activated tissue-resident cells can show increased levels of transcription factor nuclear factor κB (NF-κB) and activated protein 1 (AP-1) DNA binding due to increased oxidative stress or DNA damage (Betlazar et al., 2016; Lumniczky, Szatmari & Safrany, 2017). Through the activity of NF-κB, AP-1 and other signaling pathways, activated immune cells can together produce/secrete a variety of cytokines and chemokines (Betlazar et al., 2016; Chen et al., 2018; Greene-Schloesser et al., 2012; Kim & Joh, 2006; Phatnani & Maniatis, 2015; Smith et al., 2012; Wang et al., 2020). Chronic secretion of these inflammatory proteins can lead to downstream detriments, such as in the brain, altering blood-brain barrier permeability (Lumniczky, Szatmari & Safrany, 2017). 

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

The strategy for collating the evidence to support the relationship is described in Kozbenko et al 2022. Briefly, a scoping review methodology was used to prioritize studies based on a population, exposure, outcome, endpoint statement.

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

More work could be done to observe this relationship in human models. 

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

Modulating factor  

Details  

Effects on the KER  

References  

Drug 

Flavonoids 

Flavonoids can inhibit NF-κB, preventing transcription of pro-inflammatory mediators in active glial cells. 

Wang et al., 2020 

Drug 

Tamoxifen (estrogen receptor 

modulator commonly used in breast cancer treatment) 

Treatment with Tamoxifen decreased the radiation-induced activation of glial cells. It also consistently decreased the amount of TNF-α and IL-1β and blood-brain barrier permeability after irradiation at various doses. 

Liu et al., 2010 

Drug 

RA (modulates inflammatory effects in different cell types) 

RA treatment completely inhibited the increase in pro-inflammatory mediators after LPS-induced glial activation. 

van Neerven et al., 2010 

Drug 

SP (JNK, c-jun N-terminal kinase, inhibitor) 

AP-1 DNA binding (glial activation) was reduced by SP treatment after irradiation. TNF-α, Cox-2 and IL-1β were reduced by SP treatment after irradiation or viral infection. 

Ramanan et al., 2008  

Drug 

Q (NF-κB inhibitor) 

NF-κB DNA binding (glial activation) was reduced by Q treatment after irradiation. IL-1β was also reduced by Q treatment after irradiation. 

Ramanan et al., 2008 

Drug 

NS-398 (Cox-2 inhibitor) 

Treatment with NS-398 reduced TNF-α, IL-1β, IL-6, ICAM-1 and MCP-1 expression after irradiation. 

Kyrkanides et al., 2002 

Age 

Increased age 

Aging tissue becomes more sensitive to immune signals and increases inflammation. In the aging brain, microglia will produce more pro-inflammatory mediators. 

Patterson, 2015 

Drug 

NAC 

NAC treatment inhibited pro-inflammatory mediator production in macrophages. 

Komatsu et al., 2017 

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

Evidence for this relationship comes from in vitro mouse- and human-derived models, as well as in vivo mouse and rat models. The relationship is not sex or life stage specific.