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Event: 864

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, Body Weight

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, Body Weight

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

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
weight loss 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 AdverseOutcome 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
Homo sapiens Homo sapiens Moderate NCBI
Mus musculus Mus musculus High NCBI
Colinus virginianus Colinus virginianus Moderate 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
Adults Moderate

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

If caloric intake is less than caloric use over time, an individual will lose body weight.  This is a basic principle in human dieting as well as an important principle related to individual health and ecological fitness of animal populations.   Dynamic energy budget theory has provided useful insights on how organisms take up, assimilate and then allocate energy to various fundamental biological processes including maintenance, growth, development and reproduction (Nisbet et al 2000).  Regarding energy allocation, somatic maintenance must first be met before then growth may occur, followed by maturation and then finally, surplus energy is dedicated to reproduction (Nisbet et al 2000).  As an example of the importance of energy allocation to ecological fitness, a review by Martin et al (1987) demonstrated that energy availability (availability of food) was the predominant limiting factor in reproductive success and survival for both young and parents in a broad life history review  for bird species.  This is a likely scenario for many organisms.

Various physiological processes act to maintain and prioritize energy allocations in individuals.  The influence of PPARalpha on systemic energy metabolism and energy homeostasis has been broadly established (see reviews by Kersten 2014, Evans et al 2004, Desvergne and Wahli 1999).  Inhibition of PPARalpha predominantly impairs lipid metabolism with respect to overall energy metabolism whereby energy release from fatty acid substrates is decreased.  PPARalpha has been demonstrated to play a critical role in stimulating fatty acid oxidation and ketogenesis during fasting resulting in increased ketone body levels in plasma (Badman et al 2007, Kersten 2014) a response that is eliminated in PPARalpha knockout mice (Badman et al 2007, Sanderson et al 2010).   Reviews by Cahill (2006) and Wang et al (2010) summarize the critical adaptive response of ketogenesis during fasting for maintaining systemic energy homeostasis by providing ketone bodies to energetically fuel a diverse range of tissues, especially the brain.   Not only does PPARalpha induce the upstream production of the raw materials for use in ketogenesis through fatty acid beta-oxidation, but also directly induces key enzymes in the ketogenesis pathway including Hmgcs2, Hmgcl and Acat1 (Kersten 2014).

Kersten et al (1999) and Badman et al (2007) demonstrated that PPARalpha-null mice were unable to actively mobilize fatty acid oxidation, and further, Kersten et al (1999) demonstrated that these mice were unable to meet energy demands during fasting and leading to hypoglycemia, hyperlipidemia, hypoketonemia and fatty liver.   Observations from toxicological and toxicogenomic research have implicated nitrotoluenes as potential PPAR antagonists in birds (Rawat et al 2010), rats (Deng et al 2011) and mice (Wilbanks et al 2014), an effect that additionally corresponded with weight loss in rats (Wilbanks et al 2014) and weight loss, loss of muscle mass and emaciation in birds (Quinn et al 2007).  These combined results indicate that inhibition of PPARalpha signaling and the resultant decrease in fatty acid oxidation and ketogenesis can detrimentally impair systemic energy budgets leading to starvation-like effects and resultant weight loss.  As reviewed in the introductory paragraph of this adverse outcome description, impaired energy availability leading to inability to meet somatic maintenance needs and causing negative growth are likely to have detrimental effects on survivorship, reproduction and ecological fitness. Such affects may adversely affect responses of regulatory concern including:  individual health, survival, and population sustainability.

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). ?

Methods that have been previously reviewed and approved by a recognized authority should be included in the Overview section above. All other methods, including those well established in the published literature, should be described here. Consider the following criteria when describing each method: 1. Is the assay fit for purpose? 2. Is the assay directly or indirectly (i.e. a surrogate) related to a key event relevant to the final adverse effect in question? 3. Is the assay repeatable? 4. Is the assay reproducible?

Dynamic energy budget model development and validation demonstrated against various parameter values and population studies (Nisbet et al 2000).  Food availability, animal weights, brood sizes, adult survival, and juvenile survival measured in Martin et al (1987).  Whole body animal weights were measured for mice in Wilbanks et al (2014).  Whole body weights, organ weights and breast muscle weights measured in Quinn et al (2007).  In vitro human PPARalpha nuclear-receptor activation/inhibition assays have been used to determine if chemicals interfere with PPARalpha nuclear signaling (Wilbanks et al 2014, Gust et al 2015).  Transcript Expression of PPARalpha as well as transcript expression for genes in which PPARalpha acts as a transcriptional regulator (Wilbanks et al 2014, Deng et al 2011, Rawat et al 2010, and studies reviewed in Kersten 2014).

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

Evidence was provided for humans in Kersten (2014), Evans et al (2004), and Desvergne and Wahli (1999).  Evidence was provided for mice in Badman et al (2007), Sanderson et al (2010), Wilbanks et al (2014), Xu et al (2012), and Kersten et al (1999).  Evidence was provided for birds in Martin et al (1987).

Regulatory Significance of the Adverse Outcome

An AO is a specialised KE that represents the end (an adverse outcome of regulatory significance) of an AOP. For KEs that are designated as an AO, one additional field of information (regulatory significance of the AO) should be completed, to the extent feasible. If the KE is being described is not an AO, simply indicate “not an AO” in this section.A key criterion for defining an AO is its relevance for regulatory decision-making (i.e., it corresponds to an accepted protection goal or common apical endpoint in an established regulatory guideline study). For example, in humans this may constitute increased risk of disease-related pathology in a particular organ or organ system in an individual or in either the entire or a specified subset of the population. In wildlife, this will most often be an outcome of demographic significance that has meaning in terms of estimates of population sustainability. Given this consideration, in addition to describing the biological state associated with the AO, how it can be measured, and its taxonomic, life stage, and sex applicability, it is useful to describe regulatory examples using this AO. More help

WWeight loss in wild populations has direct implications on fitness as demonstrated dynamic energy budget modeling (Nisbet et al 2000).  Thus weight loss can be used as a metric for populations sustainability.  For individuals, rapid weight loss of greater than 20% total body weight is considered indicative of a moribund condition in laboratory animals for many Institutional Animal Care and Use Committees as established by American Association for Laboratory Animal Science (https://www.aalas.org/iacuc#.ViZzMSvaFs).

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

Badman MK, Pissios P, Kennedy AR, Koukos G, Flier JS, Maratos-Flier E: Hepatic fibroblast growth factor 21 is regulated by PPARalpha and is a key mediator of hepatic lipid metabolism in ketotic states. Cell metabolism 2007, 5(6):426-437.

Cahill GF, Jr.: Fuel metabolism in starvation. Annu Rev Nutr 2006, 26:1-22.

Deng Y, Meyer SA, Guan X, Escalon BL, Ai J, Wilbanks MS, Welti R, Garcia-Reyero N, Perkins EJ (2011) Analysis of common and specific mechanisms of liver function affected by nitrotoluene compounds. PLoS One 6(2): e14662.

 

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.

 

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

Kersten S, Seydoux J, Peters JM, Gonzalez FJ, Desvergne B, Wahli W: Peroxisome proliferator-activated receptor alpha mediates the adaptive response to fasting. J Clin Invest 1999, 103(11):1489-1498.

 

Martin TE: Food as a limit on breeding birds: a life-history perspective. Annu Rev Ecol Syst 1987:453-487.

Nisbet R, Muller E, Lika K, Kooijman S: From molecules to ecosystems through dynamic energy budget models. J Anim Ecol 2000, 69(6):913-926.

Quinn MJ Jr, Bazar MA, McFarland CA, Perkins EJ, Gust KA, Gogal Jr RM, Johnson MS (2007) Effects of subchronic exposure to 2,6-dinitrotoluene in the northern bobwhite (Colinus virginianus). Environmental Toxicology and Chemistry 26(10):2202-2207.

Rawat A, Gust KA, Deng Y, Garcia-Reyero N, Quinn MJ, Jr., Johnson MS, Indest KJ, Elasri MO, Perkins EJ (2010) From raw materials to validated system: the construction of a genomic library and microarray to interpret systemic perturbations in Northern bobwhite. Physiological Genomics 42(2):219-235.

Sanderson, L.M., Boekschoten, M.V., Desvergne, B., Muller, M., Kersten, S., 2010. Transcriptional profiling reveals divergent roles of PPARalpha and PPARbeta/delta in regulation of gene expression in mouse liver. Physiological Genomics 41:42e52.

Wang YX: PPARs: diverse regulators in energy metabolism and metabolic diseases. Cell Res 2010, 20(2):124-137.

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.