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Relationship: 2833

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

Oxidative Stress leads to Tissue resident cell activation

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 Vinita Chauhan (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 Low NCBI
rat Rattus norvegicus Moderate NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help
Sex Evidence
Male Moderate
Female Not Specified
Unspecific Low

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER.  More help
Term Evidence
Adult Moderate
Not Otherwise Specified Low

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

Oxidative stress encompasses an increase in the production of free radicals (e.g., superoxide, hydrogen peroxide and hydroxyl radicals) and a loss of antioxidant mechanisms (e.g., superoxide dismutase (SOD), glutathione peroxidase (GSH-Px) and catalase (CAT)). This imbalance can lead to damaging by-products that can activate tissue resident cells. Reactive oxygen and nitrogen species (RONS) are examples of free radicals that may promote oxidative injury (Simpson & Oliver, 2020). In addition, excess free radicals can promote a reduced capacity of the cells to maintain redox balance and prevent ongoing oxidative damage (Huang, Zou & Corniola, 2012; Rojo et al., 2014). Depending on the organ/tissue, different resident cell types may become activated by oxidative stress. For example, in the brain, oxidative stress will specifically activate microglial cells and astrocytes (Lee, Cha & Lee, 2021). Microglia cells are macrophages in the brain that respond to tissue injury, provide surveillance to neurons, and maintain synaptic homeostasis (Zhu et al., 2022). Astrocytes are critical regulators of neurogenesis and synaptogenesis, blood brain barrier permeability, and responsible for maintenance of cellular homeostasis (Zhu et al., 2022). Both microglial cells and astrocytes can change from resting to reactive states, termed gliosis, in response to excess RONS (Lee, Cha & Lee, 2021). In response to RONS, Toll like receptors (TLRs) located on microglia become activated to mediate the immune response (Gill et al., 2010; Mehdipour et al., 2021). These receptors then initiate a cascade of signaling pathways that contribute to the production of pro-inflammatory cytokines and free radicals, resulting in neuroinflammation (Heidari et al., 2022). 

Reactive microglia cells increase in size and number, display a reduction in the length and density of their processes, and upregulate their macrophagic processes, marked by expression of proteins related to phagocytic activity such as cluster of differentiation 68 (CD68) (Hol & Pekny, 2015). Astrocytes undergoing astrogliosis exhibit cellular hypertrophy and an upregulation of glial fibrillary acidic protein (GFAP), an intermediate filament expressed exclusively in astrocytes that plays a critical role in astroglia cell activation (Hol & Pekny, 2015). Activation of both microglial cells and astrocytes can accelerate neuroinflammatory pathways that can ultimately promote further formation of ROS creating a feedforward loop (Lee, Cha & Lee, 2021; Simpson & Oliver, 2020; Zhu et al., 2022).  

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 Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help

Overall Weight of Evidence: Moderate 

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

Biological Plausibility is Moderate. RONS can activate some inflammatory and anti-inflammatory pathways (TLR, TGF-β, NF-kB), and RONS are an essential part of multiple inflammatory and anti-inflammatory pathways (TLR4, TNF-a, TGF-β, NF-kB). 

RONS activates or is essential to many inflammatory pathways including TGF-β (Barcellos-Hoff and Dix 1996; Jobling, Mott et al. 2006), TNF (Blaser, Dostert et al. 2016), Toll-like receptor (TLR) (Park, Jung et al. 2004; Nakahira, Kim et al. 2006; Powers, Szaszi et al. 2006; Miller, Goodson et al. 2017; Cavaillon 2018), and NF-kB signaling (Gloire, Legrand-Poels et al. 2006; Morgan and Liu 2011). These interactions principally involve ROS, but RNS can indirectly activate TLRs and possibly NF-kB. Since inflammatory signaling and activated immune cells can also increase the production of RONS, positive feedback and feedforward loops can occur (Zhao and Robbins 2009; Ratikan, Micewicz et al. 2015; Blaser, Dostert et al. 2016). 

Damage inflicted by RONS on cells activate TLRs and other receptors to promote release of cytokines (Ratikan, Micewicz et al. 2015). For example, oxidized lipids or oxidative stress-induced heat shock proteins can activate TLR4 (Miller, Goodson et al. 2017; Cavaillon 2018). 

ROS is essential to TLR4 activation of downstream signals including NF-kB. Activation of TLR4 promotes the surface expression and movement of TLR4 into signal-promoting lipid rafts (Nakahira, Kim et al. 2006; Powers, Szaszi et al. 2006). This signal promotion requires NADPH-oxidase and ROS (Park, Jung et al. 2004; Nakahira, Kim et al. 2006; Powers, Szaszi et al. 2006). ROS is also required for the TLR4/TRAF6/ASK-1/p38 dependent activation of inflammatory cytokines (Matsuzawa, Saegusa et al. 2005). ROS therefore amplifies the inflammatory process. 

RONS can also fail to activate or actively inhibit inflammatory pathways, and the circumstances determining response to RONS are not well known (Gloire, Legrand-Poels et al. 2006). 

Responses to oxidative stress can vary depending on the organ system. In the central nervous system (CNS), biological plausibility supporting the connection between increased oxidative stress to tissue resident cell activation is moderately supported by evidence compiled from studies using animal and in vitro models. Multiple studies have shown that microglial cells and astrocytes are activated in response to RONS, meaning they change from resting to reactive states by secreting pro-inflammatory mediators and initiating antioxidant defenses mediated through TLRs (Simpson & Oliver, 2020; Heidari et al., 2022). Literature reviews describing the role of oxidative stress imbalances and glial cell activation in the context of general oxidative injury (Lee, Cha & Lee, 2021), stroke (Zhu et al., 2022) and neurodegenerative diseases (Reynolds et al., 2007; Simpson & Oliver, 2020) also suggest a relationship between increased oxidative stress and increased tissue resident cell activation in the CNS.

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

Although ROS can activate NF-KB (Gloire, Legrand-Poels et al. 2006), not all studies consistently show NF-kB activation after RONs stressor IR. It is possible that the link between ROS and NF-kB depends on the local environmental context, with different studies not adequately controlling all influential variables. One study offers a possible explanation based on temporal response: in macrophages, NF-kB was activated by shorter exposures to H2O2 (30 min), but the response disappeared with longer exposures (Nakao, Kurokawa et al. 2008). 

While many models in vivo and in vitro showed a decreased inflammatory response to RONS stressors IR in combination with antioxidants, in endothelial cells in culture the increase in IL6 and IL8 after IR was not reduced by antioxidants, although a synergistic increase in those cytokines occurring with combined TNF-a and IR treatment was reduced by antioxidants (Meeren, Bertho et al. 1997). This is a reminder that multiple mechanisms can increase inflammation, that inflammatory factors participate in positive feedback loops, and that responses to stimuli vary between cells. 

Many studies do not report direct measures of RONS. As RONS are quickly scavenged, the quantitative understanding of this relationship can be inconsistent, due to varied response of antioxidant enzymes across experimental conditions and time measurements.  

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 

KuA (antioxidant) 

After 30 Gy X-ray whole-brain irradiation of rats, activated microglia increased to over 320% of control. KuA at 5 mg/kg decreased this to 240%, at 10 mg/kg decreased it to 180% and at 20 mg/kg decreased it to 170%. 

Zhang et al., 2017 

Drug 

 L-16504 (PPARδ agonist, involved in anti-inflammatory responses) 

Treatment prevented the increase in ROS and reduced NF-κB and AP-1 DNA binding. 

Schnegg et al., 2012 

Drug 

Curcumin (antioxidant) 

Treatment increased SOD and GSH-Px levels and decreased the number of GFAP-positive cells. 

Wang et al., 2017; Daverey & Agrawal, 2016 

Age 

Increased age 

Increased age can cause susceptibility to ROS accumulation and tissue-resident cell activation. 

Liguori et al., 2018; Hanslik, Marino & Ulland, 2021 

Diet 

High antioxidant diet 

Increased antioxidants in diet can lead to reduced oxidative stress. 

Ávila-Escalante et al., 2020 

Diet 

Hypocaloric diet 

Caloric restriction has been shown to lead to reduced markers of oxidative stress. 

Ávila-Escalante et al., 2020 

Smoking 

Active smokers 

Active smokers show reduced GSH-Px activity compared to non-smokers (measured in patients with coronary artery disease). 

Kamceva et al., 2016 

Prior Disease 

Neurodegenerative diseases like Alzheimer’s and Parkinson’s 

These diseases can generate an environment of increased oxidative stress and promotes the activation of glial cells. 

Hanslik, Marino & Ulland, 2021 

Genotype 

SOD knockout mice 

SOD2 knockout mice experienced increased microglia activation following irradiation, indicating an impact of genotype on tissue resident cell activation. 

Fishman et al., 2009 

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

Since inflammatory signaling and activated immune cells can also increase the production of RONS, positive feedback and feedforward loops can occur (Zhao and Robbins 2009; Ratikan, Micewicz et al. 2015; Blaser, Dostert et al. 2016). Similarly, positive feedforward and feedback loops regarding RONS, cellular activation, and inflammation also occur in the CNS. Both RONS and microglial cell activation can accelerate neuroinflammatory pathways that can ultimately promote further formation of RONS (Lee, Cha & Lee, 2021; Simpson & Oliver, 2020; Zhu et al., 2022).  

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 human- and mouse-derived models, as well as in vivo rat models. Most of the evidence are in male adult and male models, although sex and age are not always specified.  

References

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

Ávila‐Escalante, M. L. et al. (2020), "The effect of diet on oxidative stress and metabolic diseases—Clinically controlled trials", Journal of Food Biochemistry, Vol. 44/5, https://doi.org/10.1111/jfbc.13191. 

Daverey, A. and S. K. Agrawal. (2016), "Curcumin alleviates oxidative stress and mitochondrial dysfunction in astrocytes", Neuroscience, Vol. 333, https://doi.org/10.1016/j.neuroscience.2016.07.012. 

Fishman, K. et al. (2009), "Radiation-induced reductions in neurogenesis are ameliorated in mice deficient in CuZnSOD or MnSOD", Free Radical Biology and Medicine, Vol. 47/10, https://doi.org/10.1016/j.freeradbiomed.2009.08.016. 

Gill, R., A. Tsung and T. Billiar. (2010), "Linking oxidative stress to inflammation: Toll-like receptors", Free Radical Biology and Medicine, Vol. 48/9, https://doi.org/10.1016/j.freeradbiomed.2010.01.006. 

Hanslik, K. L., K. M. Marino and T. K. Ulland. (2021), "Modulation of Glial Function in Health, Aging, and Neurodegenerative Disease", Frontiers in Cellular Neuroscience, Vol. 15, https://doi.org/10.3389/fncel.2021.718324

Heidari, A., N. Yazdanpanah and N. Rezaei. (2022), "The role of Toll-like receptors and neuroinflammation in Parkinson’s disease", Journal of Neuroinflammation, Vol. 19/1, https://doi.org/10.1186/s12974-022-02496-w. 

Hol, E. M. and M. Pekny. (2015), "Glial fibrillary acidic protein (GFAP) and the astrocyte intermediate filament system in diseases of the central nervous system", Current Opinion in Cell Biology, Vol. 32, https://doi.org/10.1016/j.ceb.2015.02.004

Huang, T. T., Y. Zou and R. Corniola. (2012), "Oxidative stress and adult neurogenesis—Effects of radiation and superoxide dismutase deficiency", Seminars in Cell & Developmental Biology, Vol. 23/7, https://doi.org/10.1016/j.semcdb.2012.04.003. 

Kamceva, G. et al. (2016), "Cigarette Smoking and Oxidative Stress in Patients with Coronary Artery Disease", Open Access Macedonian Journal of Medical Sciences, Vol. 4/4, https://doi.org/10.3889/oamjms.2016.117. 

Lee, K. H., M. Cha and B. H. Lee. (2021), "Crosstalk between Neuron and Glial Cells in Oxidative Injury and Neuroprotection", International Journal of Molecular Sciences, Vol. 22/24, https://doi.org/10.3390/ijms222413315. 

Liguori, I. et al. (2018), "Oxidative stress, aging, and diseases", Clinical Interventions in Aging, Vol.13, https://doi.org/10.2147/CIA.S158513. 

Mehdipour, A. et al. (2021), "Ionizing radiation and toll like receptors: A systematic review article", Human Immunology, Vol. 82/6, https://doi.org/10.1016/j.humimm.2021.03.008. 

Reynolds, A. et al. (2007), "Oxidative Stress and the Pathogenesis of Neurodegenerative Disorders", International Review of Neurobiology, Vol. 82, https://doi.org/10.1016/S0074-7742(07)82016-2

Rojo, A. I. et al. (2014), "Redox Control of Microglial Function: Molecular Mechanisms and Functional Significance", Antioxidants & Redox Signaling, Vol. 21/12, https://doi.org/10.1089/ars.2013.5745. 

Schnegg, C. I. et al. (2012), "PPARδ prevents radiation-induced proinflammatory responses in microglia via transrepression of NF-κB and inhibition of the PKCα/MEK1/2/ERK1/2/AP-1 pathway", Free Radical Biology and Medicine, Vol. 52/9, Pergamon, https://doi.org/10.1016/J.FREERADBIOMED.2012.02.032. 

Simpson, D. S. A. and P. L. Oliver. (2020), "ROS Generation in Microglia: Understanding Oxidative Stress and Inflammation in Neurodegenerative Disease", Antioxidants, Vol. 9/8, https://doi.org/10.3390/antiox9080743. 

Wang, Y. L. et al. (2017), "Protective Effect of Curcumin Against Oxidative Stress-Induced Injury in Rats with Parkinson’s Disease Through the Wnt/ β-Catenin Signaling Pathway", Cellular Physiology and Biochemistry, Vol. 43/6, https://doi.org/10.1159/000484302. 

Zhang, Y. et al. (2017), "Kukoamine A Prevents Radiation-Induced Neuroinflammation and Preserves Hippocampal Neurogenesis in Rats by Inhibiting Activation of NF-κB and AP-1", Neurotoxicity Research, Vol. 31/2, https://doi.org/10.1007/s12640-016-9679-4. 

Zhu, G. et al. (2022), "Crosstalk Between the Oxidative Stress and Glia Cells After Stroke: From Mechanism to Therapies", Frontiers in Immunology, Vol. 13, https://doi.org/10.3389/fimmu.2022.852416.