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Relationship: 878

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

Decreased, PPARalpha transactivation of gene expression leads to Decreased, Peroxisomal Fatty Acid Beta Oxidation of Fatty Acids

Upstream event

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

Decreased, PPARalpha transactivation of gene expression

Downstream event

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

Decreased, Peroxisomal Fatty Acid Beta Oxidation of Fatty Acids

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
humans	Homo sapiens	High	NCBI
rat	Rattus norvegicus	High	NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help

Sex	Evidence
Male	High
Female	High

Life Stage Applicability

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

Term	Evidence
Not Otherwise Specified	Not Specified

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 transcriptional regulator for a variety of genes that facilitate systemic energy homeostasis (Kersten 2014, Evans et al 2004, Desvergne and Wahli 1999). Inhibition of PPARα transactivation (KE1) results in decreased transcriptional expression for genes that catalyze the peroxisomal fatty acid beta oxidation pathway (Desvergne and Wahili 1999, Kersten 2014, Dreyer et al. 1992, Lazarow 1978) by inhibiting expression of the enzymes involved in peroxisomal fatty acid metabolism. The processes of the KE, peroxisomal fatty acid beta-oxidation, are fairly well described in the literature including good coverage of the gene products that catalyze the metabolic reactions (Kersten 2014) with reasonable characterization of metabolic flux (Mannaerts and Van Veldhoven 1993, Desvergne and Wahli 1999), thus the WOE scores for KER were in the medium to medium-high range.

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

PPARα acts as a positive transcriptional regulator for many of the genes involved in peroxisomal fatty acid beta oxidation as well as genes involved in the pre- and post-processing of fatty acids in peroxisomal pathways (Desvergne and Wahili 1999, Kersten 2014), hence the KER for the KE, “decreased PPARα transactivation of gene expression” -> the KE “decreased peroxisomal fatty acid beta oxidation” received the score of “strong”. Peroxisomal fatty acid beta oxidation reactions shorten very long chain fatty acids from dietary sources releasing acetyl-CoA subunits (a primary metabolic fuel source) and shortened-chain fatty acids that can subsequently be catabolized in the downstream KE, “mitochondrial fatty acid beta-oxidation” (as reviewed in Kersten et al. 2014 and Desvergne and Wahli 1999).

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

Biological plausibility of this KER is strong given the supporting relationships cited in the literature described in the previous bullets above.

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

Include consideration of temporal concordance here

PPARα knock out nullifies downstream expression of transcripts for genes involved in peroxisomal beta-oxidation of fatty acids (Kersten et al 2014).

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

The KER relationship between the KE, “decreased PPARα transactivation of gene expression” and the KE, “decreased peroxisomal fatty acid beta oxidation” is well supported by the literature (see references above). Few uncertainties remain, and few inconsistencies have been reported.

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

Is it known how much change in the first event is needed to impact the second? Are there known modulators of the response-response relationships? Are there models or extrapolation approaches that help describe those relationships?

A large body of research demonstrated that PPARα nuclear signaling directly controls transcriptional expression for genes catalyzing peroxisomal beta-oxidation of very long chain fatty acids (>20C), mitochondrial beta-oxidation of short, medium and long chain fatty acids (<20C), and ketogenesis (as reviewed in Kersten 2014, Evans et al 2004, Desvergne and Wahli 1999, Sanderson et al 2010). The majority of the research described in these reviews was established using gene knock outs, so there is not much dose-response information available describing the KE, “decreased PPARα transactivation of gene expression” -> the KE, “decreased peroxisomal fatty acid beta oxidation”.

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

The relationships described herein have been primarily established in human and rodent models.

References

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. Evans RM, Barish GD, Wang YX: PPARs and the complex journey to obesity. Nat Med 2004, 10(4):355-361.

Dreyer C, Krey G, Keller H, Givel F, Helftenbein G, Wahli W (1992) Control of the peroxisomal beta-oxidation pathway by a novel family of nuclear hormone receptors. Cell 68(5):879-887.

Evans RM, Barish GD, Wang YX. 2004. Ppars and the complex journey to obesity. Nat Med 10:355-361.

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

Lazarow PB: Rat liver peroxisomes catalyze the beta oxidation of fatty acids. J Biol Chem 1978, 253(5):1522-1528.

Mannaerts GP, Van Veldhoven PP (1993) Metabolic role of mammalian peroxisomes. In: Gibson G, Lake B (eds.) Peroxisomes: Biology and Importance in Toxicology and Medicine. Taylor & Francis, London, pp 19–62.