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Event: 1528

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

Fatty Acid Beta Oxidation, Decreased

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
Fatty Acid Beta Oxidation, Decreased

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

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

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
fatty acid beta-oxidation 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 Kurt A. Gust (send email) Open for citation & comment TFHA/WNT Endorsed

Stressors

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
human Homo sapiens High NCBI
mouse 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
Adult, reproductively mature High

Sex Applicability

No help message 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 positive transcriptional regulator for many of the genes involved in peroxisomal and mitochondrial 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).  Thus, decreased PPARα nuclear signaling results in decreased transcriptional expression of genes that are regulated by PPARα, and subsequently, decreased expression of the coded proteins and enzymes that ultimately decreased fatty acid metabolism within peroxisomes and mitochondria.  In PPARα knock-out mice, fatty acid oxidation capacity was decreased in well fed, rested mice and the reduced fatty acid oxidation capacity was greatly exacerbated during exercise challenge or 24h starvation (Muoio et al 2002).

Genes Involved:  The first gene target identified for PPARα was Acyl-CoA oxidase (Acox1, Dreyer et al 1992) which represents the first enzyme in peroxisomal long-chain fatty acid oxidation (Kersten 2014) and is also the rate-limiting enzyme in this pathway (Desvergne and Wahili 1999).  In addition to Acox1, a variety of additional enzymes involved in peroxisomal fatty acid metabolism are under transcriptional control of PPARα transactivation including enzymes that facilitate fatty acid uptake into the peroxisome (Abcd1, Abcd2 and Abcd 3), conversion of acyl-CoA/acetyl-CoA to acyl-carnitine/acetyl-carnitine (Crot/Crat), and conversion of acyl-CoAs back to fatty acids via thioesterases (Acots, as reviewed in Kersten 2014).  PPARalpha also has transcriptional control over enzymes downstream of Acox1 in the peroxisomal beta-oxidation of acyl-CoA pathway including L-bifunctional enzyme (Ehhadh), D-bifunctional enzyme (Hsd17b4), and peroxisomal 3-ketoacyl-CoA thiolase activity (Acaa1a, Acaa1b, as reviewed in Kersten 2014).  All of these genes are potential targets for screening affects within this KE.

As reviewed in Kersten (2014), the genes (and associated functions) regulated by PPARα in the mitochondrial processing of fatty acids include the following:  (1) Import of acyl-CoAs into the mitochondria is facilitated by PPARα-induced increases in expression of carnitine palmitoyl-transferases 1a, 1b, and 1 (Cpt1a, Cpt1b, Cpt2) and acyl-carnitine translocase (Slc25a20; Brandt et al 1998, Mascaro et al 1998, Feige et al 2010).  (2) The first step of mitochondrial beta-oxidation is catalyzed by length-specific acyl-CoA hydrogenases (Acadvl, Acadl, Acadm, Acads; Aoyama et al 1998, Gulick et al 1994).  (3) The three subsequent steps in mitochondrial beta-oxidation that successively release acetyl-CoAs from the hydrocarbon chain are catalyzed by the mitochondrial trifunctional enzyme (Hadha and Hadhb).  These enzymes are replaced upon progressive chain shortening by Hadh and Acaa2.  (4) the final PPARalpha targets include Eci1, Eci2, Decr1, and Hsd17b10 which convert unsaturated and 2-methlylated aclyl-CoAs into intermediates of beta-oxidation (Sanderson et al 2008, Aoyama et al 1998). 

Metabolism Affected:  Peroxisomes participate in a variety of lipid metabolic pathways including the beta-oxidation of very long-straight chain (<20 C in length) or branched –chain acyl-CoAs (Lazarow 1978, Kersten 2014).  The peroxisomal beta-oxidation pathway is not directly coupled to the electron transport chain and oxidative phosporylation, therefore the first oxidation reaction transforms energy to heat (H2O2 production) while in the second step, energy is captured in the metabolically accessible form of high-energy electrons in NADH (Mannaerts and Van Veldhoven 1993, Desvergne and Wahli 1999).  The peroxisomal beta-oxidation pathway provides fatty acid chain shortening where two carbons are removed in each round of oxidation in the form of acetyl-CoA (Desvergne and Wahli 1999).  The acetyl-CoA monomers serve as fundamental units for metabolic energy production (ATP)  via the citric acid cycle followed by electron-transport chain mediated oxidative phosphorylation (Nelson and Cox, 2000A) as well as serve as the fundamental units for energy storage via gluconeogenesis (Nelson and Cox, 2000B) and lipogenesis (Nelson and Cox, 2000C).  The shortened chain fatty acids (<20C) can then be transported to the mitochondria to undergo mitochondrial beta-oxidation for complete metabolism of the carbon substrate for cellular energy production (Desvergne and Wahli 1999).

Mitochondrial processing of fatty acids involves:  (1) Import of short, medium and long chain fatty acids (<C20) acyl-CoAs into the mitochondria by carnitine palmitoyl-transferases 1a, 1b, and 1 (Cpt1a, Cpt1b, Cpt2) and acyl-carnitine translocase (Slc25a20, Brandt et al 1998; Mascaro et al 1998, Kersten et al 2014).  (2) The first step of beta-oxidation catalyzed by the length-specific acyl-CoA hydrogenases (Acadvl, Acadl, Acadm, Acads; Aoyama et al 1998, Gulick et al 1994, Kersten et al 2014).  (3) The three subsequent steps in mitochondrial beta-oxidation that successively release acetyl-CoAs from the hydrocarbon chain are catalyzed by the mitochondrial trifunctional enzyme (Hadha and Hadhb, Kersten et al 2014).  These enzymes are replaced upon progressive chain shortening by Hadh and Acaa2 (Kersten et al 2014).  (4) The conversion of unsaturated and 2-methylated acetyl-CoAs into intermediates of beta-oxidation are catalyzed by Eci1, Eci2, Decr1, and Hsd17b10 (Sanderson et al 2008, Aoyama et al 1998, Kersten et al 2014).  Interestingly, tissue-specific differences in sensitivity to PPARα knock out have been observed in mice where fatty acid oxidation was markedly impaired in liver and heart tissues whereas skeletal muscle was largely unaffected due to seven-fold increased abundance of PPARδ in skeletal muscle tissue (Muoio et al 2007).  Redundancy in regulation of genes involved in fatty acid metabolism across PPARα, PPARβ, PPARδ, and PPARγ are known in canonical signaling pathways (KEGG Pathway map03320) where metabolic responses are coordinated across the iso-types with whole-organism-level effects on insulin sensitivity, body fat, and body weight (Harrington et al 2007). 

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). ?

Beta oxidation of fatty acids in mitochondria was measured using mouse liver homogenates where a radio-labeled fatty acid substrate was reacted for 30 minutes and then centrifuged to separate reaction products for fractional radioactivity measurements in Aoyama et al (1998).  Comparative measures of reaction products were also performed where potassium cyanide was added to the reaction mixture to inhibit mitochondrial beta oxidation activity to normalize the contribution of mitochondrial enzymatic reactions to the overall reaction product (Aoyama et al 1998).  In Muoio et al (2002), capacity for beta oxidation of fatty acids in serum was determined by measuring the nonesterified fatty acids and transcript expression was quantified using RT-qPCR.  Harrington et al (2007) administered agonists for the various PPARs and PPARpan (affecting all PPARs simultaneously) used ex vivo quantification of PPAR-induced fatty acid oxidation of 14C-labeled fatty acids to CO2.

A variety of transcript expression assays have been used to demonstrate the effect of PPARα signaling inhibition on downstream transcript expression (see literature cited above for specific methods within each investigation).  Investigation of PPARα transcriptional targets (especially those involved in fatty acid metabolism) have been conducted via variety of methods, with RT-qPCR being the benchmark standard (Kersten 2014 and Feige et al 2010).  Spectroscopic analysis of the characteristic absorption bands for fatty acid substrates and fatty acid beta oxidation products were examined for peroxisomal fractions purified from rat livers by differential and of equilibrium density centrifugation (Lazarow 1978).  Additionally, NAD reduction assays were conducted for acyl-CoA substrates with varying chain lengths where increased oxidation was observed for substrates with long chain length relative to short chain acyl-CoAs (Lazarow 1978).

Brandt et al (1998) investigated concentration response effects of Oleate, Decanoate and Hexanoate fatty acid chains on mitochondrial carnitine palmitoyl-transferases I (M-CPT I) expression using promoter-reporter plasmid MCPT.Luc.1025 reporter transfected into rat neonate cardiac myocytes.  Human M-CPT I was investigate using an analogous method (Brandt et al 1998).  Expression of human medium chain acyl-CoA dehydrogenase (MCAD) was investigated using a MCAD.luc.1054 reporter transfected into HepG2 cells in response to fatty acids with various chain lengths (Gulick et al 1994).  Investigation of various enzymes involved in hepatic fatty acid metabolism described in Aoyama et al (1998) were investigated using Western immunoblot quantitiation.

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

The domain of applicability includes human (as reviewed in Brandt et al 1998, Evans et al 2004, Gulick et al 1994, Kersten 2014 and Desvergne and Wahli 1999; various product labels for fibrate drugs available at the US FDA), rat (as measured by Lazarow 1978) and  mouse (as reviewed in Kersten 2014 and Desvergne and Wahli 1999). Fatty acid oxidation in response to various PPAR agonists administered in mouse and human skeletal muscle tissues using in vitro assays showed the same response profiles among species (Muoio et al 2002).  Results from Rakshanderhroo et al (2009) showed that PPARα transactivation caused unique transcriptional expression profiles between human and mouse, however expression for genes 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.)  Interestingly, PPARα-humanized mice exposed to the PPARα agonist Wy-14643 showed no hepatocellular proliferation compared to wild type mice, but both humanized and wild types showed the same capacity for induction of peroxisomal and mitochondrial fatty acid metabolizing enzymes and resultant decreases of blood-serum trigycerides (Cheung et al 2004).  (IMPORTANT NOTE:  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

References

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 (https://www.oecd.org/about/publishing/OECD-Style-Guide-Third-Edition.pdf) (OECD, 2015). More help

Aoyama, T., Peters, J.M., Iritani, N., Nakajima, T., Furihata, K., Hashimoto, T., et al., 1998. Altered constitutive expression of fatty acid-metabolizing enzymes in mice lacking the peroxisome proliferator-activated receptor alpha (PPARalpha). Journal of Biological Chemistry 273:5678e5684.

Brandt, J.M., Djouadi, F., Kelly, D.P., 1998. Fatty acids activate transcription of the muscle carnitine palmitoyltransferase I gene in cardiac myocytes via the peroxisome proliferator-activated receptor alpha. Journal of Biological Chemistry 273:23786e23792.

Cheung, C., Akiyama, T.E., Ward, J.M., Nicol, C.J., Feigenbaum, L., Vinson, C., Gonzalez, F.J., 2004. Diminished hepatocellular proliferation in mice humanized for the nuclear receptor peroxisome proliferator-activated receptor alpha. Cancer Res. 64, 3849-3854.

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

Gulick, T., Cresci, S., Caira, T., Moore, D.D., Kelly, D.P., 1994. The peroxisome proliferator-activated receptor regulates mitochondrial fatty acid oxidative enzyme gene expression. Proceedings of the National Academy of Sciences of the United States of America 91:11012e11016.

Harrington, W.W., C, S.B., J, G.W., N, O.M., J, G.B., D, C.L., W, R.O., M, C.L., D, M.I., 2007. The Effect of PPARalpha, PPARdelta, PPARgamma, and PPARpan Agonists on Body Weight, Body Mass, and Serum Lipid Profiles in Diet-Induced Obese AKR/J Mice. PPAR research 2007, 97125.

Kersten S.  2014. Integrated physiology and systems biology of PPARα. 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.

Mascaro, C., Acosta, E., Ortiz, J.A., Marrero, P.F., Hegardt, F.G., Haro, D., 1998. Control of human muscle-type carnitine palmitoyltransferase I gene transcription by peroxisome proliferator-activated receptor. Journal of Biological Chemistry 273:8560e8563.

Muoio, D.M., MacLean, P.S., Lang, D.B., Li, S., Houmard, J.A., Way, J.M., Winegar, D.A., Corton, J.C., Dohm, G.L., Kraus, W.E., 2002. Fatty acid homeostasis and induction of lipid regulatory genes in skeletal muscles of peroxisome proliferator-activated receptor (PPAR) alpha knock-out mice. Evidence for compensatory regulation by PPAR delta. J. Biol. Chem. 277, 26089-26097.

Nelson DL, Cox MM 2000A.  The Citric Acid Cycle. Lehninger Principles of Biochemistry. 3rd Edition.  Worth Publishers.  New York, NY. p567-592.

Nelson DL, Cox MM 2000B.  Carbohydrate Biosynthesis. Lehninger Principles of Biochemistry. 3rd Edition.  Worth Publishers.  New York, NY. p722-764.

Nelson DL, Cox MM 2000C.  Lipid Biosynthesis. Lehninger Principles of Biochemistry. 3rd Edition.  Worth Publishers.  New York, NY. p770-814.

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.

Sanderson, L.M., de Groot, P.J., Hooiveld, G.J., Koppen, A., Kalkhoven, E., Muller, M., et al., 2008. Effect of synthetic dietary triglycerides: a novel research paradigm for nutrigenomics. PLoS One 3:e1681.