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Relationship: 1776

Title

The title of the KER should clearly define the two KEs being considered and the sequential relationship between them (i.e., which is upstream and which is downstream). Consequently all KER titles take the form “upstream KE leads to downstream KE”.  More help

Cell injury/death leads to Increased pro-inflammatory mediators

Upstream event
Upstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help
Downstream event
Downstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. 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

This table is automatically generated upon addition of a KER to an AOP. All of the AOPs that are linked to this KER will automatically be listed in this subsection. Clicking on the name of the AOP in the table will bring you to the individual page for that AOP. More help
AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Endocytic lysosomal uptake leading to liver fibrosis adjacent High Allie Always (send email) Under development: Not open for comment. Do not cite EAGMST Under Review

Taxonomic Applicability

Select one or more structured terms 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. Authors can indicate the relevant taxa for this KER in this subsection. The process is similar to what is described for KEs (see pages 30-31 and 37-38 of User Handbook) More help
Term Scientific Term Evidence Link
human Homo sapiens NCBI
mouse Mus musculus NCBI

Sex Applicability

Authors can indicate the relevant sex for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of the User Handbook). More help
Sex Evidence
Unspecific

Life Stage Applicability

Authors can indicate the relevant life stage for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of User Handbook). More help
Term Evidence
All life stages

Key Event Relationship Description

Provide a brief, descriptive summation of the KER. While the title itself is fairly descriptive, this section can provide details that aren’t inherent in the description of the KEs themselves (see page 39 of the User Handbook). This description section can be viewed as providing the increased specificity in the nature of upstream perturbation (KEupstream) that leads to a particular downstream perturbation (KEdownstream), while allowing the KE descriptions to remain generalised so they can be linked to different AOPs. The description is also intended to provide a concise overview for readers who may want a brief summation, without needing to read through the detailed support for the relationship (covered below). Careful attention should be taken to avoid reference to other KEs that are not part of this KER, other KERs or other AOPs. This will ensure that the KER is modular and can be used by other AOPs. More help

Cell death, including both necrosis and apoptosis can lead toward inflammation. Faouzi and colleagues showed that apoptosis can induce hepatic inflammation equally as necrosis (Faouzi et al., 2001). Some studies indicate that phagocytes can produce inflammatory cytokines upon ingestion of apoptotic bodies (Uchimura et al., 1997).

When cells undergo necrosis they lose the integrity of their plasma membrane and release their intracellular contents, into the extracellular space. The same process can occur when apoptotic cells aren't cleared fast enough and their membrane becomes permeable to macromolecules, which presents secondary necrosis (Majno et al., 1995). There is evidence that the immune system has evolved the capacity to detect the release of intracellular molecules which stimulates the generation of adaptive immune responses to dying cells.

Intracellular content of dying cells that triggers immune response when excreted contains molecules named danger associated molecular patterns (DAMPs). DAMPs include for example HMGB-1, IL-1α, uric acid, DNA fragments, mitochondrial content, and ATP (Eigenbrod et al., 2008; Kono et al., 2010a; Sauter et al., 2000). DAMPs can be molecules that have non-inflammatory functions in living cells (such as HMGB-1, ATP) and acquire immunomodulatory properties when released (Rock and Kono, 2008), or alarmins, molecules that have cytokine-like properties (such as IL-1α, IL-6), which are stored in cells and released after cell lysis and contribute to the inflammatory response (Oppenheim and Yang, 2005; Vanden Berghe et al., 2006).

One of the most investigated DAMPs is HMGB-1 (Lotze et al., 2005). HMGB-1 is a nuclear protein that binds to chromatin and has a role in bending DNA and regulating gene transcription (Landsman et al., 1993). HMGB-1 is released by both necrotic and apoptotic cells (Scaffidi et al., 2002; Bell et al., 2006), but also apoptotic cells activate macrophages that engulf them to secrete HMGB-1 (Qin et al., 2006). This protein induces inflammation, dendritic cells maturation, migration, and T-cell activation (Scaffidi et al., 2002; Messmer et al., 2004; Rovere –Querini et al., 2004; Dumitriu et al., 2005; Yang et al., 2007).

HMGB-1 is a stimulus for tumour necrosis factor (TNF) synthesis and release, but it also significantly activates the synthesis of IL-1 α, IL-1 β, IL-1RA, IL-6, IL-8, MIP-1 a, and MIP-1 (Andersson et al., 2000). It was shown that HMGB-1 released from late apoptotic cells remains bound to nucleosomes and that HMGB1-nucleosome complexes activate antigen-presenting cells (APC) and induce secretion of cytokines by macrophages and expression of co-stimulatory molecules in DCs (Urbonaviciute et al., 2008).

HMGB-1 is not the only pro-inflammatory DAMP released from dying cells. Other DAMPs, S100A8/A9 and S100A12 proteins induce pro-inflammatory cytokine production by macrophages (Hofmann et al., 1999; Yang et al., 2001; Viemann et al., 2004; Ehlerman et al., 2006; Pouliot et al., 2008).

The adjuvant activity of cells was reduced by enzymatic depletion of uric acid, indicating that it is a major DAMP, at least in some cells (Shi et al., 2003). Uric acid is a mediator released from necrotic or apoptotic cells that has immunostimulatory properties in vivo (Gordon et al., 1985; Shi et al., 2003). 

Insufficient autophagy of deteriorated mitochondria could lead to massive release of DAMPs such as mtDNA and possibly other mitochondrial proteins (Oka et al., 2012).

Receptors on host cells sense when DAMPs are released and that triggers the inflammatory process. These receptors are pattern-recognition receptors (PRRs) (Chen and Nunez, 2010). PRRs represent proteins by which cells recognize microbial entities, but also some of the host's own molecules and direct an immune response (Piccinini et al., 2010). PRRs can be broadly divided in five subfamilies: Toll-like receptors (TLRs), RIG-1-like receptors (RLRs), NOD like receptors (NLRs), AIM2-like receptors (ALRs) and C-type lectin receptors (CLRs) (Takeuchi and Akira, 2010; Wang et al., 2014). For example, HMGB-1 was reported to stimulate TLR2 and TLR4 (Park et al. 2004) and receptor for advanced glycation end products (RAGE) (Dumitriu et al., 2005), while NLRP3 has been involved in the inflammatory response to mono-sodium urate (MSU) (Martinon et al., 2006). Cellular nucleic acids can stimulate TLR7 and TLR9 on B cells to promote antibody responses (Green and Marshak-Rothstein, 2011; Leadbetter et al., 2002).

TLRs are placed either at the cell surface (TLR1, TLR2, TLR4, TLR5, and TLR6) or in the endolysosomal compartment (TLR3, TLR7, and TLR9) (Barton and Kagan, 2009). Upon binding with the ligand, they undergo a conformational change and initiate a signalling cascade via signal adaptor molecules: myeloid differentiation primary response gene 88 (MyD88), MyD88 adaptor-like protein (MAL, also known as TIR-domain-containing adaptor protein; TIRAP), TIR domain-containing adaptor protein inducing interferon-β (TRIF), and TRIF-related adaptor molecule (TRAM). MyD88 was essential for the inflammatory response to injected dead cells (Chen et al., 2007).

All TLRs, except TLR3, associate with MyD88, and this stimulates a kinase cascade resulting in the activation of mitogen activated protein kinases (MAPKs), c-Jun N-terminal kinases, p38, and extracellular signal–regulated kinases, and nuclear factor NF-kB (Akira and Takeda, 2004; Lee and Kim, 2007). NF-kB is an important transcription factor for IL -1β and NLRP3 (Wang et al., 2004; Bauernfeind et al., 2009).

NF-kB is a central mediator of pro-inflammatory gene induction and functions in both types of immune cells. NF-kB pathway is responsible for transcriptional induction of pro-inflammatory cytokines, chemokines and additional inflammatory mediators, such as NLRP3, pro-IL-1β and pro-IL-18 (Sun et al., 2013; Ghosh and Karin, 2002; Hayden and Ghosh, 2013).

Macrophages must first be ‘primed’ with a stimulus that induces the synthesis of pro-IL -1β and also upregulates the expression of NLRP3 (Bauernfeid et al., 2009; Franchi et al., 2009). The stimuli that can prime macrophages include TLR agonists and cytokines like TNF. When macrophages producing pro-IL -1β are stimulated with ATP or irritant particles, inactive pro-caspase 1 assembles into a molecular complex called the inflammasome and is cleaved into active form (Stutz et al., 2009; Schroder and Tschopp, 2010). Inflammasomes consist of caspase 1, apoptosis-associated speck-like protein containing CARD (ASC) and an NLRP (Schroder and Tschopp, 2010). The catalytically active caspase 1 then cleaves pro-IL-1β to its mature and active form (Stutz et al., 2009).  Macrophages lacking any of the inflammasome components don't make mature IL-1 when stimulated in culture with sterile particles (Hornung et al., 2008; Halle et al., 2008). NF-κB signaling pathway is also involved in the regulation of inflammasome (Guo et al., 2015).

Sometimes substantial sterile inflammatory response can be seen in caspase 1-deficient mice (eg. Chen et al., 2007). This contrasts with the much more marked reduction of these responses that is consistently observed in IL-1β -deficient mice. These data imply that there must be a caspase 1-independent pathway for generating mature IL-1β in vivo (Dinarello, 2009).

In the sterile inflammatory response to cell death, the contribution of TNF appears to be more modest than IL-1 (Rock et al., 2011). A possible explanation might be that the IL-1 is being released from the dying cells themselves (Eigenbrod et al., 2008).

After engulfment of apoptotic bodies, Kupffer cells in liver express TNF, TNF-related apoptosis-inducing ligand (TRAIL), and Fas ligand (FasL) (Canbay et al. 2003), which can induce apoptosis in hepatocytes and further aggravate liver inflammation. Engulfment of apoptotic bodies by macrophages also induces FasL expression (Kiener et al., 1997), which is known to exert a pro-inflammatory activity (Chen et al., 1998).

Evidence Supporting this KER

Assembly and description of the scientific evidence supporting KERs in an AOP is an important step in the AOP development process that sets the stage for overall assessment of the AOP (see pages 49-56 of the User Handbook). To do this, biological plausibility, empirical support, and the current quantitative understanding of the KER are evaluated with regard to the predictive relationships/associations between defined pairs of KEs as a basis for considering WoE (page 55 of User Handbook). In addition, uncertainties and inconsistencies are considered. More help
Biological Plausibility
Define, in free text, the biological rationale for a connection between KEupstream and KEdownstream. What are the structural or functional relationships between the KEs? For example, there is a functional relationship between an enzyme’s activity and the product of a reaction it catalyses. Supporting references should be included. However, it is recognised that there may be cases where the biological relationship between two KEs is very well established, to the extent that it is widely accepted and consistently supported by so much literature that it is unnecessary and impractical to cite the relevant primary literature. Citation of review articles or other secondary sources, like text books, may be reasonable in such cases. The primary intent is to provide scientifically credible support for the structural and/or functional relationship between the pair of KEs if one is known. The description of biological plausibility 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 (see page 40 of the User Handbook for further information).   More help

The severity of cell death activation determines the outcome for the cell: inflammation is part of the tissue regeneration process, and intermediate apoptotic stimuli are able to trigger this response. Recruitment of inflammatory cells such as neutrophils is meant as a beneficial process, as for example apoptotic bodies of bacteria-infected cells can be removed. Thus the apoptotic cells can secrete soluble "find-me" factors that trigger infiltration of immune cells. However, if this becomes chronic it has the potential to enhance tissue damage and ultimately induce fibrosis (Jaeschke, 2002; Cullen et al., 2013).

Uncertainties and Inconsistencies
In addition to outlining the evidence supporting a particular linkage, it is also important to identify inconsistencies or uncertainties in the relationship. Additionally, while there are expected patterns of concordance that support a causal linkage between the KEs in the pair, it is also helpful to identify experimental details that may explain apparent deviations from the expected patterns of concordance. Identification of uncertainties and inconsistencies contribute to evaluation of the overall WoE supporting the AOPs that contain a given KER and to the identification of research gaps that warrant investigation (seep pages 41-42 of the User Handbook).Given that AOPs are intended to support regulatory applications, AOP developers should focus on those inconsistencies or gaps that would have a direct bearing or impact on the confidence in the KER and its use as a basis for inference or extrapolation in a regulatory setting. Uncertainties that may be of academic interest but would have little impact on regulatory application don’t need to be described. In general, this section details evidence that may raise questions regarding the overall validity and predictive utility of the KER (including consideration of both biological plausibility and empirical support). It also contributes along with several other elements to the overall evaluation of the WoE for the KER (see Section 4 of the User Handbook).  More help

The inflammatory role of HMGB-1 is still not completely clear. There are many studies that confirm its pro-inflammatory activity. However, in some experiments highly purified HMGB-1 had little pro-inflammatory activity (Rouhiainen et al., 2007), while in another injection of recombinant HMGB-1 into infarcted heart muscle in vivo stimulated regeneration and repair (Limana et al., 2005).

Response-response Relationship
This subsection should be used to define sources of data that define the response-response relationships between the KEs. In particular, information regarding the general form of the relationship (e.g., linear, exponential, sigmoidal, threshold, etc.) should be captured if possible. If there are specific mathematical functions or computational models relevant to the KER in question that have been defined, those should also be cited and/or described where possible, along with information concerning the approximate range of certainty with which the state of the KEdownstream can be predicted based on the measured state of the KEupstream (i.e., can it be predicted within a factor of two, or within three orders of magnitude?). For example, a regression equation may reasonably describe the response-response relationship between the two KERs, but that relationship may have only been validated/tested in a single species under steady state exposure conditions. Those types of details would be useful to capture.  More help
Time-scale
This sub-section should be used to provide 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?). This can be useful information both in terms of modelling the KER, as well as for analyzing the critical or dominant paths through an AOP network (e.g., identification of an AO that could kill an organism in a matter of hours will generally be of higher priority than other potential AOs that take weeks or months to develop). Identification of time-scale can also aid the assessment of temporal concordance. For example, for a KER that operates on a time-scale of days, measurement of both KEs after just hours of exposure in a short-term experiment could lead to incorrect conclusions regarding dose-response or temporal concordance if the time-scale of the upstream to downstream transition was not considered. More help
Known modulating factors
This sub-section presents information regarding modulating factors/variables known to alter the shape of the response-response function that describes the quantitative relationship between the two KEs (for example, an iodine deficient diet causes a significant increase in the slope of the relationship; a particular genotype doubles the sensitivity of KEdownstream to changes in KEupstream). Information on these known modulating factors should be listed in this subsection, along with relevant information regarding the manner in which the modulating factor can be expected to alter the relationship (if known). Note, this section should focus on those modulating factors for which solid evidence supported by relevant data and literature is available. It should NOT list all possible/plausible modulating factors. In this regard, it is useful to bear in mind that many risk assessments conducted through conventional apical guideline testing-based approaches generally consider few if any modulating factors. More help
Known Feedforward/Feedback loops influencing this KER
This subsection should define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits? In some cases where feedback processes are measurable and causally linked to the outcome, they should be represented as KEs. However, in most cases these features are expected to predominantly influence the shape of the response-response, time-course, behaviours between selected KEs. For example, if a feedback loop acts as compensatory mechanism that aims to restore homeostasis following initial perturbation of a KE, the feedback loop will directly shape the response-response relationship between the KERs. Given interest in formally identifying these positive or negative feedback, it is recommended that a graphical annotation (page 44) indicating a positive or negative feedback loop is involved in a particular upstream to downstream KE transition (KER) be added to the graphical representation, and that details be provided in this subsection of the KER description (see pages 44-45 of the User Handbook).  More help

Domain of Applicability

As for the KEs, there is also a free-text section of the KER description that the developer can use to explain his/her rationale for the structured terms selected with regard to taxonomic, life stage, or sex applicability, or provide a more generalizable or nuanced description of the applicability domain than may be feasible using standardized terms. More help

Human (Andersson et al., 2000; Scaffidi et al., 2002; Bell et al., 2006; Clarke et al., 2010)

Mouse (Faouzi et al., 2001; Chen et al., 2007)

References

List of the literature that was cited for this KER description using the appropriate format. Ideally, the list of references should conform, to the extent possible, with the OECD Style Guide (OECD, 2015). More help

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Dumitriu IE, Baruah P, Valentinis B, Voll RE, Herrmann M, Nawroth PP, Arnold B, Bianchi ME, Manfredi AA, and Rovere-Querini P.Release of high mobility group box 1 by dendritic cells controls T cell activation via the receptor for advanced glycation end products. J Immunol (2005) 174:7506–7515.

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Faouzi S, Burckhardt BE, Hanson JC, Campe CB, Schrum LW, Rippe RA, Maher JJ. Anti-Fas induces hepatic chemokines and promotes inflammation by an NF-B-independent, caspase-3-dependent pathway. J Biol Chem (2001) 276:49077-49082.

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Franchi L, Eigenbrod T, Nunez G. Cutting edge: TNF-alpha mediates sensitization to ATP and silica via the NLRP3 inflammasome in the absence of microbial stimulation. J Immunol. (2009) 183:792–796.

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Hornung V, Bauernfeind F, Halle A, Samstad EO, Kono H, Rock KL, Fitzgerald KA, Latz E. Silica crystals and aluminium salts activate the NALP3 inflammasome through phagosomal destabilization. Nat Immunol (2008) 9:847–856.

Imaeda AB, Watanabe A, Sohail MA, Mahmoud S, Mohamadnejad M, Sutterwala FS, Flavell RA, Mehal WZ. Acetaminophen-induced hepatotoxicity in mice is dependent on Tlr9 and the Nalp3 inflammasome. J Clin Invest (2009) 119:305–314.

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Limana F, Germani A, Zacheo A, Kajstura J, Di Carlo A, Borsellino G, Leoni O, Palumbo R, Battistini L, Rastaldo R, Müller S, Pompilio G, Anversa P, Bianchi ME, Capogrossi MC. Exogenous high-mobility group box 1 protein induces myocardial regeneration after infarction via enhanced cardiac C-kit+ cell proliferation and differentiation. Circ Res. (2005) 97(8): e73–e83

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Qin S, Wang H, Yuan R, Li H, Ochani M, Ochani K, Rosas-Ballina M, Czura CJ, Huston JM, Miller E, Lin X, Sherry B, Kumar A, LaRosa G, Newman W, Tracey KJ, Yang H. Role of HMGB1 in apoptosis-mediated sepsis lethality. The Journal of Experimental Medicine. (2006) 203(7):1637-1642.

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Rovere-Querini P, Scaffidi P, Valentinis B, Catalanotti F, Giazzon M, Dumitriu IE, Müller S, Iannacone M, Traversari C, Bianchi ME, Manfredi AA. HMGB1 is an endogenous immune adjuvant released by necrotic cells. EMBO Rep (2004) 5:825–30.

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