This Key Event Relationship is licensed under the Creative Commons BY-SA license. This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. If you remix, adapt, or build upon the material, you must license the modified material under identical terms.

Relationship: 1868

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

Activation, hepatic stellate cells leads to Liver Injury

Upstream event

The causing Key Event (KE) in a Key Event Relationship (KER). More help

Activation, hepatic stellate cells

Downstream event

The responding Key Event (KE) in a Key Event Relationship (KER). More help

Liver Injury

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 N-linked glycosylation leads to liver injury	adjacent	Not Specified	Not Specified	Marvin Martens (send email)	Under development: Not open for comment. Do not cite

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

Stellate cell activation produces alterations in the extracellular matrix composition which lead to liver injury

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

Apoptosis of hepatocytes from CHOP leads to Kupffer cell activation, which leads to induction of TGF-β1 expression. This in turn activates stellate cells and activation of inflammation response. This results in collagen accumulation and change in extracellular matrix composition in the liver causing fibrosis. (Vinken et al 2015, Ladesmann 2016) (Iracheta-Vellve et al., 2016)(Koo et al., 2016)(Guicciardi et al., 2013)

Empirical Evidence

Provides specific (citable) evidence that supports the idea of a change in the upstream KE (KEupstream) leading to, or being associated with, a subsequent change in the downstream KE (KEdownstream), assuming the perturbation of KEupstream is sufficient. More help

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

Inflamation response, not direct key event.

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

Quantitative Understanding of the Linkage

Captures information that helps to define how much change in the upstream KE, and/or for how long, is needed to elicit a detectable and defined change in the downstream KE. 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

References

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

Guicciardi, M. E. et al. (2013) ‘Apoptosis and Necrosis in the Liver Maria’, Comprehensive Physiology, 3(2), pp. 977–1010. doi: 10.1002/cphy.c120020.Apoptosis.

Iracheta-Vellve, A. et al. (2016) ‘Endoplasmic reticulum stress-induced hepatocellular death pathways mediate liver injury and fibrosis via stimulator of interferon genes’, Journal of Biological Chemistry. doi: 10.1074/jbc.M116.736991.

Koo, J. H. et al. (2016) ‘Endoplasmic Reticulum Stress in Hepatic Stellate Cells Promotes Liver Fibrosis via PERK-Mediated Degradation of HNRNPA1 and Up-regulation of SMAD2’, Gastroenterology. Elsevier, Inc, 150(1), p. 181–193.e8. doi: 10.1053/j.gastro.2015.09.039.