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Relationship: 877


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

Binding as antagonist, Antagonist binding to PPARalpha ligand binding domain leads to Decreased, PPARalpha transactivation of gene expression

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

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
Homo sapiens Homo sapiens High NCBI
Rattus rattus Rattus rattus High NCBI
yeast Saccharomyces cerevisiae Moderate NCBI

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

The transcription co-repressors, silencing mediator for retinoid and thyroid hormone receptors (SMRT) and nuclear receptor co-repressor (N-CoR) have been observed to compete with transcriptional co-activators for binding to nuclear receptors (including PPARα) thus suppressing basal transcriptional activity (Nagy et al 1999, Xu et al 2002). Regarding the present MIE, PPARα antagonists such as GW6471 stabilize the binding of co-repressors to the PPARα signaling complex suppressing nuclear signaling and thus downstream transactivation-transcription of PPARα-regulated genes. Given that PPARα trans-activation induces catabolism of fatty acids, this signaling pathway has been broadly demonstrated to play a key role in energy homeostasis (Kersten 2014, Evans et al 2004, Desvergne and Wahli 1999).

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

Specific Weight of Evidence scoring for all KEs and KERs in this AOP are provided in Collier et al (2016). PPARα antagonists such as GW6471 stabilize the binding of co-repressors to the PPARα signaling complex suppressing nuclear signaling (Xu et al. 2002) and thus downstream transcription of PPARα-regulated genes which is supported by a vast array of studies (see for literature review), thus the KER for the MIE  KE1 received the score of “strong”.

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

The biological plausibility is high given the lock-and-key mechanism identified for the binding of GW6471 to the co-repressor of PPARα signaling complex which inhibits PPARα transactivation (Xu et al 2002).

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

Regarding the present MIE, GW6471 has highly specific binding to the SMRT and N-CoR binding domains (Nagy et al 1999, Xu et al 2002). The degree to which other chemicals cause PPARα antagonism by this specific MIE needs to be explored. For example, Wilbanks et al. (2014) and Gust et al (2015) demonstrated inhibition of human PPARα nuclear signaling in in vitro nuclear signaling bioassays in response to 2,4-dinitrotoluene(2,4-DNT) and 2-amino-4,6-dinitrotoluene (2A-DNT), respectively. However, it is unknown if this response was manifested through the co-repressor binding stabilization that was identified in (Xu et al 2002).

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
Response-response Relationship
Provides sources of data that define the response-response relationships between the KEs.  More help
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

The majority of the studies cited herein provide evidence for human and rat, however much of the signaling architecture is also present in yeast (Krogsdam et al 2002).


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

Desvergne B, Wahli W (1999) Peroxisome proliferator-activated receptors: nuclear control of metabolism. Endocrine Reviews 20(5): 649-688.

Gust KA, Nanduri B, Rawat A, Wilbanks MS, Ang CY, Johnson DR, Pendarvis K, Chen X, Quinn Jr. MJ, Johnson MS, Burgess SC, Perkins EJ (2015) Systems Toxicology Identifies Mechanistic Impacts of 2-amino-4,6-dinitrotoluene (2A-DNT) Exposure in Northern Bobwhite. BMC Genomics. In Press.

Evans RM, Barish GD, Wang YX: PPARs and the complex journey to obesity. Nat Med 2004, 10(4):355-3

Kersten S. 2014. Integrated physiology and systems biology of PPARalpha. Molecular Metabolism 2014, 3(4):354-371.

Krogsdam AM, Nielsen CA, Neve S, Holst D, Helledie T, Thomsen B, et al. 2002. Nuclear receptor corepressor-dependent repression of peroxisome-proliferator-activated receptor delta-mediated transactivation. Biochem J 363:157-165.

Nagy L, Kao H-Y, Love JD, Li C, Banayo E, Gooch JT, Krishna V, Chatterjee K, Evans RM, Schwabe JWR: Mechanism of corepressor binding and release from nuclear hormone receptors. Genes Dev 1999, 13(24):3209-3216.

Wilbanks, M., Gust, K.A., Atwa, S., Sunesara, I., Johnson, D., Ang, C.Y., Meyer., S.A., and Perkins, E.J. 2014. Validation of a genomics-based hypothetical adverse outcome pathway: 2,4-dinitrotoluene perturbs PPAR signaling thus impairing energy metabolism and exercise endurance. Toxicological Sciences. 141(1):44-58.

Xu HE, Lambert MH, Montana VG, Plunket KD, Moore LB, Collins JL, et al. 2001. Structural determinants of ligand binding selectivity between the peroxisome proliferator-activated receptors. Proceedings of the National Academy of Sciences 98:13919-13924.

Xu HE, Stanley TB, Montana VG, Lambert MH, Shearer BG, Cobb JE, McKee DD, Galardi CM, Plunket KD, Nolte RT et al: Structural basis for antagonist-mediated recruitment of nuclear co-repressors by PPAR[alpha]. Nature 2002, 415(6873):813-817.