API

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: 2073

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, PPARα leads to Decreased, cholesterol

Upstream event
The causing Key Event (KE) in a Key Event Relationship (KER). More help
Activation, PPARα
Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER). More help
Decreased, cholesterol

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
PPARalpha Agonism Leading to Decreased Viable Offspring via Decreased 11-Ketotestosterone adjacent High Not Specified Arthur Author (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
teleost fish teleost fish High NCBI
Homo sapiens Homo sapiens High NCBI
mice Mus sp. High NCBI
mammals mammals Moderate NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help
Sex Evidence
Male High
Female Moderate

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER.  More help
Term Evidence
Adults High

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

PPARα is a nuclear receptor. With an agonist it promotes transcription of many genes, several of which are involved in cholesterol transport and metabolism (reviewed in Rakhshandehroo et al., 2010).

Hydrophobic lipid molecules (such as cholesterol, cholesteryl ester, and triglycerides) are transported in the aqueous plasma of organisms by forming lipoprotein complexes with apolipoproteins. There are different groups of lipoproteins which use different apolipoproteins and ratios of lipids: low-density (LDL), very low-density (VLDL), and high density (HDL).

Fibrates are a class of drug that agonize PPARα to lower LDL and VLDL while slightly increasing HDL in humans (Singh & Correa, 2020).

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 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

Although humans taking fibrate medications show lowed LDL and VLDL but slightly increased HDL, this pattern is not seen in fish (Prindiville et al., 2011). The exact reason(s) why is not well understood. 

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 factors haven't been evaluated yet.

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

TAXONOMIC APPLICABILITY

The understanding of the effects of PPARα agonists on cholesterol primarily comes from studies on mice and humans to develop pharmaceuticals. However, lowered cholesterol in response to a PPARα agonist occurs in other mammals including rats, dogs, and guinea pigs at low, non-toxic doses (Meyer et al., 1999).

There are several studies showing that in fish PPARα agonism decreases cholesterol via the same mechanisms as in humans: 

  1. LPL is conserved in zebrafish (NCBI). It is increased in several fish species exposed to PPARα agonists (Prindiville et al., 2011; Teles et al., 2016; Guo et al., 2015)
  2. LDL is decreased in several fish species exposed to PPARα agonists (see Table 1)
  3. CETP is conserved in zebrafish (NCBI)
  4. APOA1 is conserved in zebrafish (NCBI). However, results are mixed on the effects of PPARα agonists on APOA1 (Corcoran et al., 2015; Teles et al., 2016) and HDL (see table 1) . In mice APOA1 is not regulated by PPARα (Staels & Auwerx, 1998), so this may be the case in fish.

SEX APPLICABILITY

Male and female mice show different effects in several endpoints, including total cholesterol, in response to fibrate administration. This is likely due to estrogen partially and indirectly inhibiting PPARα (Yoon, 2010; Jeong & Yoon, 2012). In fish, males and females often show differing effects on cholesterol (Lee et al., 2019; Runnalls et al., 2007).