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Relationship: 1629
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).
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Accumulation, Collagen leads to Pulmonary fibrosis
Upstream event
The causing Key Event (KE) in a Key Event Relationship (KER).
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Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER).
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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.
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AOPs Referencing Relationship
| AOP Name | Adjacency | Weight of Evidence | Quantitative Understanding | Point of Contact | Author Status | OECD Status |
|---|---|---|---|---|---|---|
| Latent Transforming Growth Factor beta1 activation leads to pulmonary fibrosis | adjacent | High | Cataia Ives (send email) | Under development: Not open for comment. Do not cite | ||
| Substance interaction with the pulmonary resident cell membrane components leading to pulmonary fibrosis | adjacent | High | Low | Cataia Ives (send email) | Under development: Not open for comment. Do not cite | EAGMST Under Review |
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.
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Sex Applicability
An indication of the the relevant sex for this KER.
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Life Stage Applicability
An indication of the the relevant life stage(s) for this KER.
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| Term | Evidence |
|---|---|
| Adult | High |
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.
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Fibrosis by definition is the end result of a healing process. It involves a series of lung remodelling and reorganisation events leading to permanent alteration in the lung architecture and a fixed scar tissue or fibrotic lesion (Wallace WA, 2007). Excessive deposition of extracellular matrix (ECM) or collagen is the hallmark of this disease and there is ample evidence to support this KER (Fukuda 1985, Meyer 2017, Richeldi 2017, Thannickal 2004, Zisman 2005).
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.
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| ID | Experimental Design | Species | Upstream Observation | Downstream Observation | Citation (first author, year) | Notes |
|---|
Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP.
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| 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.
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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.
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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.
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Since the adverse outcome of lung fibrosis involves multiple cell types, cell - cell interactions and cell–biomolecule interactions, it is difficult to recapitulate the entire process in one model. Therefore, an integrated approach, such as one consisting of cell systems that assess individual KEs and quantitative relationships between the KEs, is needed to predict the AO in humans.
Response-response Relationship
Provides sources of data that define the response-response relationships between the KEs.
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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?).
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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.
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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.
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Humans (Meyer 2017, Zisman 2005), rats (Williamson 2015), mice (Williamson 2015).