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Event: 858

Key Event Title

The KE title should describe a discrete biological change that can be measured. It should generally define the biological object or process being measured and whether it is increased, decreased, or otherwise definably altered relative to a control state. For example “enzyme activity, decreased”, “hormone concentration, increased”, or “growth rate, decreased”, where the specific enzyme or hormone being measured is defined. More help

Decreased, PPARalpha transactivation of gene expression

Short name
The KE short name should be a reasonable abbreviation of the KE title and is used in labelling this object throughout the AOP-Wiki. The short name should be less than 80 characters in length. More help
Decreased, PPARalpha transactivation of gene expression

Biological Context

Structured terms, selected from a drop-down menu, are used to identify the level of biological organization for each KE. Note, KEs should be defined within a particular level of biological organization. Only KERs should be used to transition from one level of organization to another. Selection of the level of biological organization defines which structured terms will be available to select when defining the Event Components (below). More help
Level of Biological Organization

Cell term

Further information on Event Components and Biological Context may be viewed on the attached pdf.The biological context describes the location/biological environment in which the event takes place.  For molecular/cellular events this would include the cellular context (if known), organ context, and species/life stage/sex for which the event is relevant. For tissue/organ events cellular context is not applicable.  For individual/population events, the organ context is not applicable. More help
Cell term
eukaryotic cell

Organ term

Further information on Event Components and Biological Context may be viewed on the attached pdf.The biological context describes the location/biological environment in which the event takes place.  For molecular/cellular events this would include the cellular context (if known), organ context, and species/life stage/sex for which the event is relevant. For tissue/organ events cellular context is not applicable.  For individual/population events, the organ context is not applicable. More help

Key Event Components

Further information on Event Components and Biological Context may be viewed on the attached pdf.Because one of the aims of the AOP-KB is to facilitate de facto construction of AOP networks through the use of shared KE and KER elements, authors are also asked to define their KEs using a set of structured ontology terms (Event Components). In the absence of structured terms, the same KE can readily be defined using a number of synonymous titles (read by a computer as character strings). In order to make these synonymous KEs more machine-readable, KEs should also be defined by one or more “event components” consisting of a biological process, object, and action with each term originating from one of 22 biological ontologies (Ives, et al., 2017; See List). Biological process describes dynamics of the underlying biological system (e.g., receptor signalling). The biological object is the subject of the perturbation (e.g., a specific biological receptor that is activated or inhibited). Action represents the direction of perturbation of this system (generally increased or decreased; e.g., ‘decreased’ in the case of a receptor that is inhibited to indicate a decrease in the signalling by that receptor).Note that when editing Event Components, clicking an existing Event Component from the Suggestions menu will autopopulate these fields, along with their source ID and description. To clear any fields before submitting the event component, use the 'Clear process,' 'Clear object,' or 'Clear action' buttons. If a desired term does not exist, a new term request may be made via Term Requests. Event components may not be edited; to edit an event component, remove the existing event component and create a new one using the terms that you wish to add. More help
Process Object Action
receptor transactivation peroxisome proliferator-activated receptor alpha decreased

Key Event Overview

AOPs Including This Key Event

All of the AOPs that are linked to this KE will automatically be listed in this subsection. This table can be particularly useful for derivation of AOP networks including the KE. Clicking on the name of the AOP will bring you to the individual page for that AOP. More help
AOP Name Role of event in AOP Point of Contact Author Status OECD Status
PPARα antagonism leading to body-weight loss KeyEvent Agnes Aggy (send email) Open for citation & comment TFHA/WNT Endorsed


This is a structured field used to identify specific agents (generally chemicals) that can trigger the KE. Stressors identified in this field will be linked to the KE in a machine-readable manner, such that, for example, a stressor search would identify this as an event the stressor can trigger. NOTE: intermediate or downstream KEs in one AOP may function as MIEs in other AOPs, meaning that stressor information may be added to the KE description, even if it is a downstream KE in the pathway currently under development.Information concerning the stressors that may trigger an MIE can be defined using a combination of structured and unstructured (free-text) fields. For example, structured fields may be used to indicate specific chemicals for which there is evidence of an interaction relevant to this MIE. By linking the KE description to a structured chemical name, it will be increasingly possible to link the MIE to other sources of chemical data and information, enhancing searchability and inter-operability among different data-sources and knowledgebases. The free-text section “Evidence for perturbation of this MIE by stressor” can be used both to identify the supporting evidence for specific stressors triggering the MIE as well as to define broad chemical categories or other properties that classify the stressors able to trigger the MIE for which specific structured terms may not exist. More help

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) can be selected from an ontology. In many cases, individual species identified in these structured fields will be those for which the strongest evidence used in constructing the AOP was available in relation to this KE. More help
Term Scientific Term Evidence Link
Homo sapiens Homo sapiens High NCBI
Mus musculus Mus musculus High NCBI

Life Stages

The structured ontology terms for life-stage are more comprehensive than those for taxa, but may still require further description/development and explanation in the free text section. More help
Life stage Evidence
Not Otherwise Specified Not Specified

Sex Applicability

The authors must select from one of the following: Male, female, mixed, asexual, third gender, hermaphrodite, or unspecific. More help
Term Evidence
Male High
Female High

Key Event Description

A description of the biological state being observed or measured, the biological compartment in which it is measured, and its general role in the biology should be provided. For example, the biological state being measured could be the activity of an enzyme, the expression of a gene or abundance of an mRNA transcript, the concentration of a hormone or protein, neuronal activity, heart rate, etc. The biological compartment may be a particular cell type, tissue, organ, fluid (e.g., plasma, cerebrospinal fluid), etc. The role in the biology could describe the reaction that an enzyme catalyses and the role of that reaction within a given metabolic pathway; the protein that a gene or mRNA transcript codes for and the function of that protein; the function of a hormone in a given target tissue, physiological function of an organ, etc. Careful attention should be taken to avoid reference to other KEs, KERs or AOPs. Only describe this KE as a single isolated measurable event/state. This will ensure that the KE is modular and can be used by other AOPs, thereby facilitating construction of AOP networks. More help

PPARα acts as a nuclear signaling element that controls the transcription of a variety of genes involved in lipid catabolism and energy production pathways (Desvergne and Wahli 1999, Kersten 2014). Fatty acids serve as the natural ligands that stimulate PPARα nuclear signaling where the fatty acids (likely in association with fatty acid binding proteins) bind to the ligand binding domain of PPARα along with co-activators to the PPARα regulatory complex at promoter regions of PPARα-regulated genes (termed PPAR response elements, PPREs) initiating the transcription of genes that metabolize the fatty acids (Ahmed et al 2007, Wolfrum et al. 2001, Desvergne and Wahli 1999, Kersten 2014, Xu et al 2001, Janssen et al 2015). 

Specifically, PPARα contains both a ligand-binding domain that binds fatty acids and a DNA-binding domain that initiates binding to PPREs in the promoter regions of PPARα-regulated genes (Ahmed et al 2007, Hihi et al 2002).  Binding of the fatty acid ligands to PPARα facilitates heterodimeric binding with another ligand-activated nuclear receptor, the retinoid X receptor (RXR), forming an activated PPAR-RXR transcriptional regulator complex (DiRenzo et al 1997, Ahmed et al 2007).  PPAR competes for binding to RXR with retinoic acid receptors (RARs) where the RAR/RXR heterodimer inhibits transcription of genes downstream of PPREs (DiRenzo et al 1997).  Transcriptional regulation activity of the PPAR/RXR complex is also influenced by the binding and release of accessory molecules that act as coactivators such as steroid receptor co-activator 1 (SRC-1) or as corepressors such as nuclear receptor corepressor (N-CoR, DiRenzo et al 1997, Ahmed et al 2007, Xu et al 2002, Liu et al 2008).  Such binding of the co-repressor N-CoR to the PPARα/RXRα complex has been demonstrated to inhibit transcriptional transactivation (Xu et al 2002, Liu et al 2008).  The exact mechanisms by which the PPAR/RXR complex facilitate transcription are still not well understood.  It has been observed that RXR contains a highly conserved motif at the C-terminal end of the ligand-binding domain known as activating function 2 (AF2) which undergoes conformational changes allowing interaction with coactivators / corepressors, the former of which is hypothesized to recruit the components of the transcriptional machinery necessary to transcribe the downstream gene (DiRenzo et al 1997).  Even the basal transcriptional machinery itself is recognized to vary across cell types and the prototypical preinitiation complex (PIC) is inherently highly flexible, confirmationally diverse including multi-faceted interactions of activators, core promotion factors, the RNA polymerase II enzyme, elongation factors, and chromatin remodeling complexes all combined at the promoter to facilitate gene transcription (Levine et al 2014).  Additionally, recent transcriptomic research coupling transcriptomic expression and chromatin immunoprecipitation (ChIP) sequencing to identify PPARα binding to PPREs suggests PPARα may exert transcriptional regulation beyond its direct genomic targets via secondary signaling networks including various kinases (McMullen et al 2014).  Given the current KE (KE2, PPARalpha transactivation of gene expression, Decreased), a variety of upstream influences may impair the function of the PPARα-RXRα heterodimer and/or affect coactivator / corepressor binding leading to decreased PIC competence resulting in impaired transcription of downstream genes as well as secondary signaling networks.

PPARα regulates expression of genes encoding nearly every enzymatic step of fatty acid catabolism including fatty acid uptake into cells, fatty acid activation to acyl-CoAs, and the release of cellular energy from fatty acids through the oxidative breakdown of acyl-CoAs to acetyl-CoA, and in starvation conditions, the repackaging of Acetyl-CoA substrates into ketone bodies via ketogenesis pathways (Kersten 2014, Desvergne and Wahli 1999, Evans et al 2004).  A pathway-level schematic for PPARα transactivation is illustrated in KEGG Pathway map03320 providing the specific gene targets and associated functional responses that are transcriptionally regulated by PPARα. It should be noted that there are species-specific differences in PPARα transactivation of gene expression among mice and humans which are explained in the “Evidence Supporting Taxonomic Applicability” section, below.

How It Is Measured or Detected

One of the primary considerations in evaluating AOPs is the relevance and reliability of the methods with which the KEs can be measured. The aim of this section of the KE description is not to provide detailed protocols, but rather to capture, in a sentence or two, per method, the type(s) of measurements that can be employed to evaluate the KE and the relative level of scientific confidence in those measurements. Methods that can be used to detect or measure the biological state represented in the KE should be briefly described and/or cited. These can range from citation of specific validated test guidelines, citation of specific methods published in the peer reviewed literature, or outlines of a general protocol or approach (e.g., a protein may be measured by ELISA).Key considerations regarding scientific confidence in the measurement approach include whether the assay is fit for purpose, whether it provides a direct or indirect measure of the biological state in question, whether it is repeatable and reproducible, and the extent to which it is accepted in the scientific and/or regulatory community. Information can be obtained from the OECD Test Guidelines website and the EURL ECVAM Database Service on Alternative Methods to Animal Experimentation (DB-ALM). ?

X-ray crystallography was used to describe the ligand binding domain (fatty acid binding domain) of PPARα and demonstrate the binding complex of PPARα, the artificial ligand (GW6471), and the co-repressor silencing mediator for retinoid and thyroid hormone receptors (SMRT, Xu et al 2001, 2002).  Fold activation of the PPARα-GW6471-SMRT transcriptional regulatory complex was measured in mammalian two-hybrid assays (Xu et al 2001).  PPAR-RXR and RAR-RXR heterodimerization and activity were quantified using expression vectors for murine PPARα, RAR and RXR in CV-1 cells transfected with 1ug of reporter plasmid and 50-200ng of expression plasmid (DiRenzo et al 1997).  DNA-dependent radioligand binding assays were conducted to quantify ligand binding in the assays described in DiRenzo et al (1997).  X-ray crystallography has been used with limited success to describe the PIC while high-resolution electron microscopy is providing additional insights into the fully functionalized PIC when bound to the promotor and including all accessory molecules (Levine et al 2014).  Effects of PPARα transactivation on expression of downstream genes been examined by a variety of methods, especially RT-qPCR (Kersten et al 2014).  As a recommendation for investigating specific genes regulated by PPARα, as part of this KE, see the KEGG pathway for PPAR Signaling (map03320).  In McMullen et al (2014), transcriptomic expression was investigated in human primary hepatocytes in time and dose series exposures to the PPARα agonist GW7647 where transcriptomic expression was measured using Affimetrix microarrays and ChIPseq was conducted after completing immunoprecipitation and quantified using Illumina HiSeq 2000 sequencing to find binding to PPRE within 50K bp of differentially expressed genes.

Domain of Applicability

This free text section should be used to elaborate on the scientific basis for the indicated domains of applicability and the WoE calls (if provided). While structured terms may be selected to define the taxonomic, life stage and sex applicability (see structured applicability terms, above) of the KE, the structured terms may not adequately reflect or capture the overall biological applicability domain (particularly with regard to taxa). Likewise, the structured terms do not provide an explanation or rationale for the selection. The free-text section on evidence for taxonomic, life stage, and sex applicability can be used to elaborate on why the specific structured terms were selected, and provide supporting references and background information.  More help

Aspects of PPARα signaling have been observed to differ comparing human and rodent responses as described for Mus musculus (Kersten 2014) and Homo sapiens in clinical observations (Kersten 2014) and in in vitro assays (reviewed in Kersten 2014).  Microarray-based comparative transcriptomic expression among mouse and human primary hepatocyte samples exposed to the PPARα agonist Wy14643 showed minor overlap in individual gene-level expression, however substantial overlap was observed at the pathway level (Rakshanderhroo et al 2009).  In that study, most of the genes that were differentially expressed in common among human and mouse were involved in lipid metabolism, including CPT1A, HMGCS2, FABP1, ACSL1 and ADFP.  Thus, in Rakshanderhroo et al (2009), evaluation of PPARα transactivation differences among human and mouse suggest expression for gene-transcripts involved in lipid metabolism tended to be the most conserved among species.  (IMPORTANT NOTE:  The results from Rakshanderhroo et al (2009) should be viewed with caution given that primary hepatocytes were obtained from 1 mouse per strain, only.)  Feige et al (2010) found that mice with humanized PPARα were insensitive to the PPARα agonist pollutant, diethylhexyl phthalate (DEHP), where mRNA expression (measured by reverse transcriptase-qPCR) for genes involved in fatty-acid metabolism were not induced relative to wild type mice.  (IMPORTANT NOTE:  the results from Fiege et al (2010) show that DEHP is a weak partial agonist of PPARα.  Additionally, the use of wild type versus mice with humanized PPARα for extrapolating species-to-species differences should be viewed with caution.  Humanized receptor is not likely to interact with the same cofactors in mice relative to humans and the regulatory grammars may differ between among species that may further complicate the biochemistry.)

Evidence for Perturbation by Stressor


List of the literature that was cited for this KE description. Ideally, the list of references, should conform, to the extent possible, with the OECD Style Guide ( (OECD, 2015). More help

Ahmed, W., Ziouzenkova, O., Brown, J., Devchand, P., Francis, S., Kadakia, M., Kanda, T., Orasanu, G., Sharlach, M., Zandbergen, F., Plutzky, J., 2007. PPARs and their metabolic modulation: new mechanisms for transcriptional regulation? J. Intern. Med. 262, 184-198.

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

DiRenzo, J., Soderstrom, M., Kurokawa, R., Ogliastro, M.H., Ricote, M., Ingrey, S., Horlein, A., Rosenfeld, M.G., Glass, C.K., 1997. Peroxisome proliferator-activated receptors and retinoic acid receptors differentially control the interactions of retinoid X receptor heterodimers with ligands, coactivators, and corepressors. Mol. Cell. Biol. 17, 2166-2176.

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

Feige, J.N., Gerber, A., Casals-Casas, C., Yang, Q., Winkler, C., Bedu, E., Bueno, M., Gelman, L., Auwerx, J., Gonzalez, F.J., Desvergne, B., 2010. The pollutant diethylhexyl phthalate regulates hepatic energy metabolism via species-specific PPARalpha-dependent mechanisms. Environ. Health Perspect. 118, 234-241.

Hihi, A.K., Michalik, L., Wahli, W., 2002. PPARs: transcriptional effectors of fatty acids and their derivatives. Cell Molec Life Sci 59, 790-798.

Janssen, A.W., Betzel, B., Stoopen, G., Berends, F.J., Janssen, I.M., Peijnenburg, A.A., Kersten, S., 2015. The impact of PPARalpha activation on whole genome gene expression in human precision cut liver slices. BMC Genomics 16, 760.

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

Levine, M., Cattoglio, C., Tjian, R., 2014. Looping Back to Leap Forward: Transcription Enters a New Era. Cell 157, 13-25.

Liu, M.H., Li, J., Shen, P., Husna, B., Tai, E.S., Yong, E.L., 2008. A natural polymorphism in peroxisome proliferator-activated receptor-alpha hinge region attenuates transcription due to defective release of nuclear receptor corepressor from chromatin. Mol. Endocrinol. 22, 1078-1092.

McMullen, P.D., Bhattacharya, S., Woods, C.G., Sun, B., Yarborough, K., Ross, S.M., Miller, M.E., McBride, M.T., LeCluyse, E.L., Clewell, R.A., Andersen, M.E., 2014. A map of the PPARalpha transcription regulatory network for primary human hepatocytes. Chem. Biol. Interact. 209, 14-24.

Rakhshandehroo, M., Hooiveld, G., Muller, M., Kersten, S., 2009. Comparative analysis of gene regulation by the transcription factor PPARalpha between mouse and human. PLoS One 4, e6796.

Wolfrum C, Borrmann CM, Borchers T, Spener F (2001) Fatty acids and hypolipidemic drugs regulate peroxisome proliferator-activated receptors alpha - and gamma-mediated gene expression via liver fatty acid binding protein: a signaling path to the nucleus. Proc Natl Acad Sci USA 98(5):2323-2328.

Xu HE, Lambert MH, Montana VG, Plunket KD, Moore LB, Collins JL, Oplinger JA, Kliewer SA, Gampe RT, McKee DD et al: Structural determinants of ligand binding selectivity between the peroxisome proliferator-activated receptors. Proceedings of the National Academy of Sciences 2001, 98(24):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.