Aop: 6

Title

Each AOP should be given a descriptive title that takes the form “MIE leading to AO”. For example, “Aromatase inhibition [MIE] leading to reproductive dysfunction [AO]” or “Thyroperoxidase inhibition [MIE] leading to decreased cognitive function [AO]”. In cases where the MIE is unknown or undefined, the earliest known KE in the chain (i.e., furthest upstream) should be used in lieu of the MIE and it should be made clear that the stated event is a KE and not the MIE. More help

Antagonist binding to PPARα leading to body-weight loss

Short name
A short name should also be provided that succinctly summarises the information from the title. This name should not exceed 90 characters. More help
PPARα antagonism leading to body-weight loss

Graphical Representation

A graphical summary of the AOP listing all the KEs in sequence, including the MIE (if known) and AO, and the pair-wise relationships (links or KERs) between those KEs should be provided. This is easily achieved using the standard box and arrow AOP diagram (see this page for example). The graphical summary is prepared and uploaded by the user (templates are available) and is often included as part of the proposal when AOP development projects are submitted to the OECD AOP Development Workplan. The graphical representation or AOP diagram provides a useful and concise overview of the KEs that are included in the AOP, and the sequence in which they are linked together. This can aid both the process of development, as well as review and use of the AOP (for more information please see page 19 of the Users' Handbook).If you already have a graphical representation of your AOP in electronic format, simple save it in a standard image format (e.g. jpeg, png) then click ‘Choose File’ under the “Graphical Representation” heading, which is part of the Summary of the AOP section, to select the file that you have just edited. Files must be in jpeg, jpg, gif, png, or bmp format. Click ‘Upload’ to upload the file. You should see the AOP page with the image displayed under the “Graphical Representation” heading. To remove a graphical representation file, click 'Remove' and then click 'OK.'  Your graphic should no longer be displayed on the AOP page. If you do not have a graphical representation of your AOP in electronic format, a template is available to assist you.  Under “Summary of the AOP”, under the “Graphical Representation” heading click on the link “Click to download template for graphical representation.” A Powerpoint template file should download via the default download mechanism for your browser. Click to open this file; it contains a Powerpoint template for an AOP diagram and instructions for editing and saving the diagram. Be sure to save the diagram as jpeg, jpg, gif, png, or bmp format. Once the diagram is edited to its final state, upload the image file as described above. More help

Authors

List the name and affiliation information of the individual(s)/organisation(s) that created/developed the AOP. In the context of the OECD AOP Development Workplan, this would typically be the individuals and organisation that submitted an AOP development proposal to the EAGMST. Significant contributors to the AOP should also be listed. A corresponding author with contact information may be provided here. This author does not need an account on the AOP-KB and can be distinct from the point of contact below. The list of authors will be included in any snapshot made from an AOP. More help

Kurt A. Gust1, Mitchell S. Wilbanks1, Zachary A. Collier1, Lyle D. Burgoon1, Edward J. Perkins1.

1Army Engineer Research and Development Center, Vicksburg, MS, 39180, Kurt.A.Gust@usace.army.mil; Mitchell.S.Wilbanks@usace.army.mil;

Point of Contact: Kurt A. Gust, Kurt.A.Gust@usace.army.mil

Point of Contact

Indicate the point of contact for the AOP-KB entry itself. This person is responsible for managing the AOP entry in the AOP-KB and controls write access to the page by defining the contributors as described below. Clicking on the name will allow any wiki user to correspond with the point of contact via the email address associated with their user profile in the AOP-KB. This person can be the same as the corresponding author listed in the authors section but isn’t required to be. In cases where the individuals are different, the corresponding author would be the appropriate person to contact for scientific issues whereas the point of contact would be the appropriate person to contact about technical issues with the AOP-KB entry itself. Corresponding authors and the point of contact are encouraged to monitor comments on their AOPs and develop or coordinate responses as appropriate.  More help
Agnes Aggy   (email point of contact)

Contributors

List user names of all  authors contributing to or revising pages in the AOP-KB that are linked to the AOP description. This information is mainly used to control write access to the AOP page and is controlled by the Point of Contact.  More help
  • Kurt A. Gust
  • Agnes Aggy

Status

The status section is used to provide AOP-KB users with information concerning how actively the AOP page is being developed, what type of use or input the authors feel comfortable with given the current level of development, and whether it is part of the OECD AOP Development Workplan and has been reviewed and/or endorsed. “Author Status” is an author defined field that is designated by selecting one of several options from a drop-down menu (Table 3). The “Author Status” field should be changed by the point of contact, as appropriate, as AOP development proceeds. See page 22 of the User Handbook for definitions of selection options. More help
Author status OECD status OECD project SAAOP status
Open for citation & comment TFHA/WNT Endorsed 2.3 Included in OECD Work Plan
This AOP was last modified on April 05, 2021 18:16
The date the AOP was last modified is automatically tracked by the AOP-KB. The date modified field can be used to evaluate how actively the page is under development and how recently the version within the AOP-Wiki has been updated compared to any snapshots that were generated. More help

Revision dates for related pages

Page Revision Date/Time
Decreased, PPARalpha transactivation of gene expression April 30, 2019 12:05
Decreased, Ketogenesis (production of ketone bodies) April 30, 2019 12:40
Not Increased, Circulating Ketone Bodies April 30, 2019 12:45
Decreased, Body Weight April 30, 2019 12:54
Increased, Catabolism of Muscle Protein April 30, 2019 12:48
Binding of antagonist, PPAR alpha September 16, 2017 10:14
stabilization, PPAR alpha co-repressor April 30, 2019 11:42
Fatty Acid Beta Oxidation, Decreased April 30, 2019 12:22
Binding of antagonist, PPAR alpha leads to stabilization, PPAR alpha co-repressor June 11, 2018 22:49
stabilization, PPAR alpha co-repressor leads to Decreased, PPARalpha transactivation of gene expression June 11, 2018 22:56
Decreased, PPARalpha transactivation of gene expression leads to Fatty Acid Beta Oxidation, Decreased June 11, 2018 23:05
Decreased, PPARalpha transactivation of gene expression leads to Decreased, Ketogenesis (production of ketone bodies) June 11, 2018 23:21
Fatty Acid Beta Oxidation, Decreased leads to Decreased, Ketogenesis (production of ketone bodies) June 11, 2018 23:14
Decreased, Ketogenesis (production of ketone bodies) leads to Not Increased, Circulating Ketone Bodies June 11, 2018 23:25
Not Increased, Circulating Ketone Bodies leads to Increased, Catabolism of Muscle Protein June 11, 2018 23:30
Increased, Catabolism of Muscle Protein leads to Decreased, Body Weight June 11, 2018 23:33
GW6471 January 30, 2017 16:02
Nitrotoluenes (hypothesized binding) January 30, 2017 16:26
PPARalpha antagonists June 02, 2017 14:46

Abstract

In the abstract section, authors should provide a concise and informative summation of the AOP under development that can stand-alone from the AOP page. Abstracts should typically be 200-400 words in length (similar to an abstract for a journal article). Suggested content for the abstract includes the following: The background/purpose for initiation of the AOP’s development (if there was a specific intent) A brief description of the MIE, AO, and/or major KEs that define the pathway A short summation of the overall WoE supporting the AOP and identification of major knowledge gaps (if any) If a brief statement about how the AOP may be applied (optional). The aim is to capture the highlights of the AOP and its potential scientific and regulatory relevance More help

The present AOP describes antagonistic chemical binding to the peroxisome proliferator-activated receptor α (PPARα) resulting in preferential binding a co-repressor to the overall PPARα signaling complex causing a chain of events that includes: antagonism of PPARα nuclear signaling, decreased transcriptional expression of PPARα-regulated genes that support energy metabolism, and inhibited metabolic energy production culminating with starvation-like weight loss. The AOP is likely to be synergized during fasting, starvation or malnutrition events.  The MIE for this AOP involves antagonistic PPARα binding. The antagonist-binding to the PPARα regulatory complex causes the KE1, stabilization of co-repressor (SMRT or N-CoR) to PPARalpha ligand binding domain suppressing PPARα nuclear signaling (Nagy et al 1999, Xu et al 2002). PPARα is a transcriptional regulator for a variety of genes that facilitate systemic energy homeostasis (Mirza et al 2019, Kersten 2014, Evans et al 2004, Desvergne and Wahli 1999). As a result of the MIE and then KE1, the KE2 occurs where PPARalpha transactivation is inhibited for genes involved in the next 2 key events of the AOP: (KE3) decreased fatty acid beta oxidation (Desvergne and Wahili 1999, Kersten 2014, Dreyer et al 1992, Lazarow 1978, Brandt et al 1998; Mascaro et al 1998, Aoyama et al 1998, Gulick et al 1994, Sanderson et al 2008) and (KE4) decreased ketogenesis (Cahil 2006, Kersten et al 2014, Sengupta et al 2010, Desvergne and Wahli 1999). The KE3 results in decreased catabolism of very long chain fatty acids in peroxisomes and reduced catabolism of long, medium and short chain fatty acids in mitochondria reducing acetyl-CoA availability for use in oxidative phosphorylation-based ATP production (Evans et al 2004).  KE2 (and also potentially KE3) can drive KE4 resulting in decreased potential to repackage energy substrates as ketone bodies to support systemic energy demands during periods where the systemic energy budget is negative (Badman et al 2007, Potthoff 2009; Muoio et al 2002). The KE5, no change or a decrease in circulating ketone bodies becomes critical during cellular energy deficit conditions, a state where ketogenesis is typically induced to increase circulating ketone bodies providing metabolic fuel to sustain energy homeostasis (Cahill 2006). Physiological studies of the progression of human starvation have demonstrated the critical importance of ketogenesis, especially production of β-hydroxybutyrate, for meeting systemic energy demands by supplementing glucose to sustain the energy requirements of the brain (Cahill 2006, Owen et al 2005). PPARα knock can inhibit ketogenesis from fatty acid substrates in fasted mice reducing β-hydroxybutyrate production causing hypoketonemia (Badman et al 2007, Le May et al 2000, Muoio et al 2002).  Sustained negative energy budgets lead to KE6, an increase in muscle protein catabolism, with glutamine and alanine recycled for gluconeogenesis (Felig et al 1970A, Kashiwaya et al 1994).  If ketogenesis from fatty acid substrates fails to meet cellular energy needs, gluconeogenesis from alternative substrates becomes necessary including (KE 6) muscle protein catabolism in situ supporting local muscle function and releasing glutamine (Marliss et al 1971) and alanine (Felig et al 1970A) for gluconeogenesis in kidney and liver to sustain systemic energy needs (Goodman et al 1966, Kashiwaya et al 1994, Cahill 2006).  Finally, the AO of body-weight loss occurs, which within the context of dynamic energy budget theory, decreases energy allocations to organismal maturation and reproduction (Nisbet et al 2000) and has been demonstrated to negatively affect ecological fitness (Martin et al 1987).

Background (optional)

This optional subsection should be used to provide background information for AOP reviewers and users that is considered helpful in understanding the biology underlying the AOP and the motivation for its development. The background should NOT provide an overview of the AOP, its KEs or KERs, which are captured in more detail below. Examples of potential uses of the optional background section are listed on pages 24-25 of the User Handbook. More help

Summary of the AOP

This section is for information that describes the overall AOP. The information described in section 1 is entered on the upper portion of an AOP page within the AOP-Wiki. This is where some background information may be provided, the structure of the AOP is described, and the KEs and KERs are listed. More help

Events:

Molecular Initiating Events (MIE)
An MIE is a specialised KE that represents the beginning (point of interaction between a stressor and the biological system) of an AOP. More help
Key Events (KE)
This table summarises all of the KEs of the AOP. This table is populated in the AOP-Wiki as KEs are added to the AOP. Each table entry acts as a link to the individual KE description page.  More help
Adverse Outcomes (AO)
An AO is a specialised KE that represents the end (an adverse outcome of regulatory significance) of an AOP.  More help
Sequence Type Event ID Title Short name
1 MIE 998 Binding of antagonist, PPAR alpha Binding of antagonist, PPAR alpha
2 KE 1000 stabilization, PPAR alpha co-repressor stabilization, PPAR alpha co-repressor
3 KE 858 Decreased, PPARalpha transactivation of gene expression Decreased, PPARalpha transactivation of gene expression
4 KE 1528 Fatty Acid Beta Oxidation, Decreased Fatty Acid Beta Oxidation, Decreased
5 KE 861 Decreased, Ketogenesis (production of ketone bodies) Decreased, Ketogenesis (production of ketone bodies)
6 KE 862 Not Increased, Circulating Ketone Bodies Not Increased, Circulating Ketone Bodies
7 KE 863 Increased, Catabolism of Muscle Protein Increased, Catabolism of Muscle Protein
8 AO 864 Decreased, Body Weight Decreased, Body Weight

Relationships Between Two Key Events (Including MIEs and AOs)

TESTINGThis table summarises all of the KERs of the AOP and is populated in the AOP-Wiki as KERs are added to the AOP. Each table entry acts as a link to the individual KER description page.To add a key event relationship click on either Add relationship: events adjacent in sequence or Add relationship: events non-adjacent in sequence.For example, if the intended sequence of KEs for the AOP is [KE1 > KE2 > KE3 > KE4]; relationships between KE1 and KE2; KE2 and KE3; and KE3 and KE4 would be defined using the add relationship: events adjacent in sequence button.  Relationships between KE1 and KE3; KE2 and KE4; or KE1 and KE4, for example, should be created using the add relationship: events non-adjacent button. This helps to both organize the table with regard to which KERs define the main sequence of KEs and those that provide additional supporting evidence and aids computational analysis of AOP networks, where non-adjacent KERs can result in artifacts (see Villeneuve et al. 2018; DOI: 10.1002/etc.4124).After clicking either option, the user will be brought to a new page entitled ‘Add Relationship to AOP.’ To create a new relationship, select an upstream event and a downstream event from the drop down menus. The KER will automatically be designated as either adjacent or non-adjacent depending on the button selected. The fields “Evidence” and “Quantitative understanding” can be selected from the drop-down options at the time of creation of the relationship, or can be added later. See the Users Handbook, page 52 (Assess Evidence Supporting All KERs for guiding questions, etc.).  Click ‘Create [adjacent/non-adjacent] relationship.’  The new relationship should be listed on the AOP page under the heading “Relationships Between Two Key Events (Including MIEs and AOs)”. To edit a key event relationship, click ‘Edit’ next to the name of the relationship you wish to edit. The user will be directed to an Editing Relationship page where they can edit the Evidence, and Quantitative Understanding fields using the drop down menus. Once finished editing, click ‘Update [adjacent/non-adjacent] relationship’ to update these fields and return to the AOP page.To remove a key event relationship to an AOP page, under Summary of the AOP, next to “Relationships Between Two Key Events (Including MIEs and AOs)” click ‘Remove’ The relationship should no longer be listed on the AOP page under the heading “Relationships Between Two Key Events (Including MIEs and AOs)”. More help

Network View

The AOP-Wiki automatically generates a network view of the AOP. This network graphic is based on the information provided in the MIE, KEs, AO, KERs and WoE summary tables. The width of the edges representing the KERs is determined by its WoE confidence level, with thicker lines representing higher degrees of confidence. This network view also shows which KEs are shared with other AOPs. More help

Stressors

The stressor field is a structured data field that can be used to annotate an AOP with standardised terms identifying stressors known to trigger the MIE/AOP. Most often these are chemical names selected from established chemical ontologies. However, depending on the information available, this could also refer to chemical categories (i.e., groups of chemicals with defined structural features known to trigger the MIE). It can also include non-chemical stressors such as genetic or environmental factors. Although AOPs themselves are not chemical or stressor-specific, linking to stressor terms known to be relevant to different AOPs can aid users in searching for AOPs that may be relevant to a given stressor. More help
Name Evidence Term
GW6471 High
Nitrotoluenes (hypothesized binding) Moderate
PPARalpha antagonists High

Life Stage Applicability

Identify the life stage for which the KE is known to be applicable. More help
Life stage Evidence
Adult High

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) can be selected. 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
Mus musculus Mus musculus High NCBI
Colinus virginianus Colinus virginianus Moderate NCBI
Pimephales promelas Pimephales promelas Low NCBI
Rattus norvegicus Rattus norvegicus Moderate NCBI
Homo sapiens Homo sapiens High NCBI

Sex Applicability

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

Overall Assessment of the AOP

This section addresses the relevant biological domain of applicability (i.e., in terms of taxa, sex, life stage, etc.) and WoE for the overall AOP as a basis to consider appropriate regulatory application (e.g., priority setting, testing strategies or risk assessment). The goal of the overall assessment is to provide a high level synthesis and overview of the relative confidence in the AOP and where the significant gaps or weaknesses are (if they exist). Users or readers can drill down into the finer details captured in the KE and KER descriptions, and/or associated summary tables, as appropriate to their needs.Assessment of the AOP is organised into a number of steps. Guidance on pages 59-62 of the User Handbook is available to facilitate assignment of categories of high, moderate, or low confidence for each consideration. While it is not necessary to repeat lengthy text that appears elsewhere in the AOP description (or related KE and KER descriptions), a brief explanation or rationale for the selection of high, moderate, or low confidence should be made. More help

The majority of the evidence described in this AOP are derived for either human (mostly in vitro) or mice (in vivo and in vitro) studies.  There are recognized differences between mouse and human PPARα signaling and responses from the literature, however, for our specific KEs, the responses among species are relatively well conserved.  Therefore, we have reasonable confidence that the AOP provides reliable confidence for human health assessment.  The AOP also has the potential to support ecotoxicological assessment if there is reasonable confidence that the KEs are conserved in the species of interest.  The risk for this AOP is expected to be exacerbated during fasting, starvation and/or sub-optimal nutrition where interference with PPARα signaling is likely to contribute synergistically toward decreased exercise performance in the short-term and drive body-weight loss in long-term exposures.  The molecular responses from the MIE through KE4 are very well characterized in the literature for human and mouse.  KE5 and KE6 have fairly strong support from the literature, however the KER between them, especially stemming back to the MIE remains the largest data gap within the AOP.  Finally, the connection between KE6 and the AO is intuitive and well established in the literature.  Overall, the AOP is biologically plausible with logical order where AO is likely to be exacerbated when nutrition is suboptimal.

Regarding the use of the AOP for chemical safety assessment, the AOP should have relevance for any chemical observed to inhibit PPARα signaling.  Additionally, the manifestation and severity of the AO is expected to occur predominantly in chronic exposures, especially in nutritionally stressed populations.  There is much left to learn about what chemical structures are likely to antagonistically bind to PPARα before quantitative structure-activity relationships (QSARs) can be developed to predict binding / antagonistic effects.  

Domain of Applicability

The relevant biological domain(s) of applicability in terms of sex, life-stage, taxa, and other aspects of biological context are defined in this section. Biological domain of applicability is informed by the “Description” and “Biological Domain of Applicability” sections of each KE and KER description (see sections 2G and 3E for details). In essence the taxa/life-stage/sex applicability is defined based on the groups of organisms for which the measurements represented by the KEs can feasibly be measured and the functional and regulatory relationships represented by the KERs are operative.The relevant biological domain of applicability of the AOP as a whole will nearly always be defined based on the most narrowly restricted of its KEs and KERs. For example, if most of the KEs apply to either sex, but one is relevant to females only, the biological domain of applicability of the AOP as a whole would be limited to females. While much of the detail defining the domain of applicability may be found in the individual KE and KER descriptions, the rationale for defining the relevant biological domain of applicability of the overall AOP should be briefly summarised on the AOP page. More help

The majority of the evidence described in this AOP are derived for either human (mostly in vitro) or mice (in vivo and in vitro) studies.  There are recognized differences between mouse and human PPARα signaling and responses from the literature, however, for our specific KEs, the responses among species are relatively well conserved.  Therefore, we have reasonable confidence that the AOP provides reliable confidence for human health assessment.  The AOP also has the potential to support ecotoxicological assessment if there is reasonable confidence that the KEs are conserved in the species of interest.

Essentiality of the Key Events

An important aspect of assessing an AOP is evaluating the essentiality of its KEs. The essentiality of KEs can only be assessed relative to the impact of manipulation of a given KE (e.g., experimentally blocking or exacerbating the event) on the downstream sequence of KEs defined for the AOP. Consequently evidence supporting essentiality is assembled on the AOP page, rather than on the independent KE pages that are meant to stand-alone as modular units without reference to other KEs in the sequence.The nature of experimental evidence that is relevant to assessing essentiality relates to the impact on downstream KEs and the AO if upstream KEs are prevented or modified. This includes: Direct evidence: directly measured experimental support that blocking or preventing a KE prevents or impacts downstream KEs in the pathway in the expected fashion. Indirect evidence: evidence that modulation or attenuation in the magnitude of impact on a specific KE (increased effect or decreased effect) is associated with corresponding changes (increases or decreases) in the magnitude or frequency of one or more downstream KEs.When assembling the support for essentiality of the KEs, authors should organise relevant data in a tabular format. The objective is to summarise briefly the nature and numbers of investigations in which the essentiality of KEs has been experimentally explored either directly or indirectly. See pages 50-51 in the User Handbook for further definitions and clarifications.  More help

Rationale for essentiality calls:

  • MIE:  PPARα, Binding of antagonist:  Regarding the present MIE, molecules can bind to the PPARα regulatory complex affecting the binding of co-activators and co-repressors. Specifically designed molecules such as the PPARα antagonists GW6471 can bind to PPARα selectively recruiting binding of co-repressors to the PPARα nuclear signaling complex (Xu et al 2002).
  • Key Event 1:  PPAR alpha co-repressor, Increased - The binding of co-repressors to the PPARα signaling complex suppresses nuclear signaling and thus downstream transcription of PPARα-regulated genes (Liu et al 2008).  GW6471 binding to the co-repressor is reversible thus allowing the co-repressor to leave the ligand binding domain of PPARα, restoring normal function (Xu et al 2002).
  • Key Event 2:  PPARalpha transactivation of gene expression, Decreased - As described in a variety of reviews, PPARalpha represents a master regulator of energy metabolism which specifically promotes fatty oxidation for energy production & distribution (Evans et al 2004, Kersten 2014, Lefebvre et al 2006, Desvergne and Wahili 1999, Mirza et al 2019).  Both PPARalpha knock outs and PPARalpha antagonism decreased transcriptional expression of gene targets involved in peroxisomal fatty acid beta oxidation (Kersten et al 1999, Desvergne and Wahili 1999, Janssen et al 2015), mitochondrial fatty acid beta oxidation (Brandt et al 1998; Mascaro et al 1998, Kersten  2014), and ketogenesis (Sengupta et al 2010, Desvergne and Wahli 1999, Kersten 2014).
  • Key Event 3: Fatty Acid Beta Oxidation, Decreased – This key event is essential for deriving metabolic energy from fatty acid substrates thus supporting a large component of overall organismal energy demands (Evans et al 2004, Kersten 2014, Desvergne and Wahili 1999).  Very long chain fatty acids (>C20) are metabolized in the peroxisome and short, medium and long chain fatty acids (<C20) are catabolized by mitochondrial beta-oxidation.  PPARalpha regulates nearly every enzymatic step in the uptake as well as the oxidative breakdown of acyl-CoAs to acetyl-CoA (Kersten 2014).  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).  PPARalpha knockout studies have demonstrated impaired mitochondrial fatty acid oxidation leading to fatty acid accumulation in the liver (Badmann et al 2007) as well as an inability to meet systemic energy demands (Kersten et al, 1999).
  • Key Event 4: Ketogenesis (production of ketone bodies), decreased - The liver represents a key organ involved in systemic energy distribution given its ability to synthesize glucose (an ability shared only with the kidney, Gerich et al 2001) as well as its exclusive role in the generation of ketone bodies (Cahill 2006, Sengupta et al 2010, Kersten 2014).  This is especially important for the metabolic energy needs of the brain which can only use glucose and the ketone body, β-hydroxybutyrate for cellular energy production (Cahill 2006, Owen 2005, Kersten 2014).  Therefore, ketogenesis is critical to supporting general systemic energy homeostasis in fasting events (Cahill 2006, Evans et al 2004, Sengupta et al 2010).  Interference with ketogenesis, for example by PPARα inhibition, has been demonstrated to inhibit β-hydroxybutyrate production (measured in serum) during fasting events in mice (Le May et al 2000, Badman et al 2007, Potthoff 2009, Sengupta et al 2010) and cause hypoketonemia (Muoio et al 2002).  The Badman et al (2007) study indicated that metabolism of fatty acid substrates (measured as liver triglycerides) that would otherwise contribute to β-hydroxybutyrate production was additionally inhibited under PPARα knockout.  
  • Key Event 5: Circulating Ketone Bodies, Not Increased - Physiological studies of the progression of human starvation have identified that the preferred metabolic fuel is glucose in the fed state and progressing through two days of fasting, afterward ketone bodies become increasingly important for meeting energy demands (Cahill 2006, Owen et al 2005).  Substrates derived from carbohydrates, fats and protein can contribute to gluconeogenesis (Cahill 2006, Gerich et al 2001) whereas substrates derived from fatty acids are the primary contributors to ketogenesis (Desvergne and Wahli 1999).  Cahill (2006) and colleagues have demonstrated the importance of ketone body production, especially β-hydroxybutyrate, for maintaining energy homeostasis during starvation by serving as an alternative substrate to glucose for providing energy to the brain in the starvation state (Cahill 2006).  Interference with ketogenesis, for example by PPARα inhibition, has been demonstrated to inhibit β-hydroxybutyrate production (measured in serum) during fasting events in mice (Badman et al 2007, Potthoff 2009).  Related to this observation, PPARα-knockout mice reached exhaustion sooner than wild types in an exercise challenge which corresponded with significantly decreased β-hydroxybutyrate in serum indicating hypoketonemia in PPARα-knockout mice versus wild types (Muoio et al 2002).  Under normal conditions, activated ketogenesis occurring during fasting events is rapidly deactivated when blood glucose concentrations increase to normal levels and resultant elevated circulating ketone bodies are reduced correspondingly (Cahill 2006).
  • Key Event 6: Catabolism of Muscle Protein, Increased  - After two to three days of fasting in humans, dietary glucose has been long-since expended and contribution to blood glucose from glycogen metabolism is reduced to zero (Cahill 2006).  At this point, about two fifths of fatty acid metabolism in the whole body is dedicated to hepatic ketogenesis, largely in support of the energy demands of the brain, however the brain is still significantly supported by glucose derived from gluconeogenesis (Cahill 2006).  As fatty acid stores are depleted, gluconeogenesis from other substrates becomes increasingly important including muscle protein catabolism in situ for supporting muscle function as well as releasing glutamine (Marliss et al 1971) and alanine (Felig et al 1970A) which can be recycled to glucose by gluconeogenesis in the kidney (Goodman et al 1966, Kashiwaya et al 1994, Cahill 2006). In prolonged starvation events, the catabolism of muscle protein for gluconeogenesis in order to support systemic energy needs results in loss of muscle mass which contributes to loss of overall body weight.  This loss is rapidly reversible upon input of alternative metabolic fuel for example by nutrient assimilation from feeding.
  • Adverse Outcome:  Loss of body weight - If caloric intake is less than caloric use over time, an individual will lose body weight.  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).  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).  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).   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 body 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.  In the absence of PPARalpha knockout, and upon removal of PPARalpha antagonist dosing, normal bioenergetic physiology can potentially be attained.

Evidence Assessment

The biological plausibility, empirical support, and quantitative understanding from each KER in an AOP are assessed together.  Biological plausibility of each of the KERs in the AOP is the most influential consideration in assessing WoE or degree of confidence in an overall hypothesised AOP for potential regulatory application (Meek et al., 2014; 2014a). Empirical support entails consideration of experimental data in terms of the associations between KEs – namely dose-response concordance and temporal relationships between and across multiple KEs. It is examined most often in studies of dose-response/incidence and temporal relationships for stressors that impact the pathway. While less influential than biological plausibility of the KERs and essentiality of the KEs, empirical support can increase confidence in the relationships included in an AOP. For clarification on how to rate the given empirical support for a KER, as well as examples, see pages 53- 55 of the User Handbook.  More help

"'Biological Plausibility"'

Binding of molecules to peroxisome proliferator-activated receptor α (PPARα) can cause either agonistic (i.e. GW409544) or antagonistic (i.e. GW6471) signaling depending on molecular structure (Xu et al 2001, Xu et al 2002).  A well described mode of antatonistic binding by GW6471 demonstrates that the molecule can bind to the PPARα ligand binding domain causing conformational changes that induce increased affinity to co-repressors which decrease PPARα nuclear signaling (Xu et al 2002) representing the MIE for this AOP.  

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 KE1, the binding of co-repressors such as the SMRT and N-CoR to PPARα is reinforced by the MIE, which blocks the AF-2 helix from adopting the active conformation, as demonstrated in x-ray crystallography results presented in Xu et al (2002).  Thus, molecules that bind to PPARα that can enhance co-repressor binding act as PPARα antagonists.

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).  In fact, 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, 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 (Kersten 2014, Desvergne and Wahli 1999, Evans et al 2004, Sengupta et al 2010). 

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, McMullen et al 2014, Rakhshandehroo et al 2009).

Peroxisomal 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 by mitochondrial fatty acid beta oxidation reaction (as reviewed in Kersten et al 2014 and Desvergne and Wahli 1999).  Fatty acids shortened via peroxisomal beta-oxidation as well as fatty acids released from adipose tissue stores can be catabolized in mitochondrial beta-oxidation reactions to acetyl-CoA, NADH and ATP (Aoyama et al 1998).  Within the mitochondria, the acetyl-CoA substrates can be used to maximize ATP production through full substrate oxidation via the citric acid cycle followed by oxidative phosphorylation by the electron transport chain (Nelson and Cox 2000A, Desvergne and Wahli 1999).  This demonstrates the importance of PPARα signaling for inducing cellular energy release from fatty acids.

Blocking PPARα signaling has been shown to inhibit expression of transcripts / enzymes involved in both peroxisomal and mitochondrial beta-oxidation causing impaired fatty acid catabolism, fatty acid accumulation in the liver and impaired cellular energy state during fasting events (Badman et al 2007, Kersten et al 1999). 

During periods of fasting, acetyl-CoA generated during either peroxisomal or mitochondrial beta-oxidation of fatty acids in the liver can each contribute to ketogenesis (Kersten 2014, Sengupta 2010).  The liver represents a key organ involved in systemic energy distribution given its ability to synthesize glucose and catalyze the formation of ketone bodies, especially β-hydroxybutyrate, via ketogenesis (Cahil 2006, Kersten 2014).  β-hydroxybutyrate is especially important for the metabolic energy needs of the brain which is unable to utilize fatty acids for cellular energy production (Owen 2005, Kersten 2014) as well as supporting general systemic energy homeostasis in fasting events (Cahil 2006, Evans et al 2004).

Not only does PPARα signaling stimulate the release of cellular energy from fatty acids, it also regulates the transcription of enzymes that catalyze the repackaging of that cellular energy to ketone bodies via ketogenesis (Sengupta et al 2010, Desvergne and Wahli 1999).  Inhibition of PPARα signaling has been demonstrated to inhibit transcriptional expression of genes that catalyze ketogenesis as well as ketone body production (Badman et al 2007, Potthoff 2009, Sengupta 2010) affecting circulating levels of ketone bodies for systemic use.

Kersten et al (1999) demonstrated that PPARα is induced in fasted mice mobilizing the oxidation of fatty acids for energy production.  In that study, PPARα-null mice did not actively induce fatty acid oxidation or ketogenesis leaving the mice unable to meet energy demands during fasting and leading to hypoglycemia, hyperlipidemia, hypoketonemia and fatty liver.  In such energy deficits, muscle protein catabolism is induced where the amino acids glutamine and alanine serve as substrates for gluconeogenesis in the kidney to supplement cellular energy production / distribution (Cahill 2006, Marliss et al 1971, Felig et al 1970A, Goodman et al 1966, Kashiwaya et al 1994).

PPARα knockout resulted in important organism-level responses including quicker onset of exhaustion compared to wild type mice in exercise trials where PPARα-K/Os exhibited hypoketonemia (Muoio et al 2002).   Additionally, animals exposed to pollutants (nitrotoluenes) that act as partial PPARα antagonists had decreased exercise endurance (Wilbanks et al 2014), showed body weight loss (Wilbanks et al 2014, Quinn et al 2007) and displayed loss of muscle mass (Quinn et al 2007). 

In general, 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.

"'Concordance of dose-response relationships:"'

Dose-response relationships have been developed for GW6471 and the relative binding of PPARα co-repressors and co-activators to the PPARα nuclear signaling complex where the proportion of co-repressors increases dramatically with increasing GW6471 concentration (Xu et al 2002).  Correspondingly, the relative activity of PPARα decreased to zero with increasing GW6471 concentrations (Xu et al 2002).  Additionally, recent observations of PPARα antagonism by nitrotoluenes have demonstrated dose-response relationships for PPARα nuclear signaling inhibition in human in vitro investigations which corresponded with dose-responsive decreases in transcriptional expression of genes involved in lipid metabolism pathways (Wilbanks et al 2014, Gust et al 2015).  These results corresponded with a dose-responsive relationship where increasing nitrotoluene dose caused decreased muscle mass, decreased body weight and increased emaciation in chronic dosing studies (Quinn et al 2007).

"'Temporal concordance among the key events and adverse effect:"'

Co-repressor binding was observed prior to inhibition of PPARα signaling (Xu et al 2002).  PPARα knock out nullifies downstream expression of transcripts for genes involved in peroxisomal beta-oxidation of fatty acids, mitochondrial beta-oxidation of fatty acids, and ketogenesis pathways relative to wild types (Kersten et al 2014).  Peroxisomal beta-oxidation of very long chain fatty acids into long chain fatty acids occurs prior to import into mitochondria and progression of mitochondrial beta-oxidation (Lazarow 1978, Kersten 2014).  Mitochondrial beta-oxidation of long chain fatty acids occurs prior to generation of ketone bodies via ketogenesis (Sengupta et al 2010, Badman et al 2007).  Ketogenesis occurs prior to increases in circulating ketone bodies (Sengupta et al 2010, Badman et al 2007, Cahill 2006).  Increases in circulating ketone bodies can be observed prior to loss of muscle mass to muscle-protein catabolism given that this linkage is not directly connected.  Muscle protein catabolism derives amino acids that are recycled to glucose via renal gluconeogenesis (Goodman et al 1966, Kashiwaya et al 1994, Cahill 2006).  Catabolism of muscle protein occurs prior to body weight loss (Quinn et al 2007).

"'Consistency:"'

The transcription co-repressors, silencing mediator for retinoid and thyroid hormone receptors (SMRT) and nuclear receptor co-repressor (N-CoR) competition with transcriptional co-activators for binding to nuclear receptors (including PPARα) has been observed in humans as well as yeast (Nagy et al 1999) suggesting broad taxonomic applicability for this MIE.  The evidence of PPARα as a regulator of fatty acid metabolism is well described in the literature (for example, Kersten 2014, Evans 2004, Desvergne and Wahili 1999), and is consistent across many species including human, mouse, rat, Northern bobwhite, fathead minnow and carp (Kersten et al 1999, Kersten 2014, Wintz et al 2006, Gust et al 2015, Deng et al 2011, Wilbanks et al 2014, Xu and Jing, 2012).  Inhibition of PPARα via gene knockout or treatment with PPARα antagonist consistently results in deceased fatty acid metabolism with indicators of increased serum triglycerides, fatty livers and steatosis (Kersten 2014, Evans 2004, Desvergne and Wahili 1999, Kersten et al 1999, Wintz et al 2006, Deng et al 2011).  Given PPARα’s central role in systemic energy metabolism, studies of PPARα antagonism have shown decreased potential for sustaining energy needs of the organism (Kersten et al 1999) leading to decreased exercise performance (Muoio et al 2002, Wilbanks et al 2014) and weight loss (Wilbanks et al 2014, Quinn et al 2007).  Research thus far suggest that the PPARα transcriptional regulation pathway as well as the metabolic pathways for which PPARα acts as a regulator indicates that the progression of key events through to the adverse outcome will tend to be evolutionarily conserved for within mammals and likely across animal phyla.

"'Uncertainties, inconsistencies, and data gaps:"'

A critical data gap regarding this AOP is an absence of studies that have investigated the effects null mutants for ketogenesis on the physiology and individual performance during long term starvation relative to wild type individuals.  Additionally, knowledge about feedback mechanisms between ketogenesis vs gluconeogenesis would be beneficial for interpreting systemic energy metabolism.  Regarding the antagonistic action of nitrotoluenes on PPARalpha nuclear signaling (Wilbanks et al 2014, Gust et al 2015), receptor-binding assays would be beneficial to determine if this class of chemicals is binding the SMRT and N-CoR co-repressors, similar to the antagonistic action of GW6471 (Xu et al 2002).

Quantitative Understanding

Some proof of concept examples to address the WoE considerations for AOPs quantitatively have recently been developed, based on the rank ordering of the relevant Bradford Hill considerations (i.e., biological plausibility, essentiality and empirical support) (Becker et al., 2017; Becker et al, 2015; Collier et al., 2016). Suggested quantitation of the various elements is expert derived, without collective consideration currently of appropriate reporting templates or formal expert engagement. Though not essential, developers may wish to assign comparative quantitative values to the extent of the supporting data based on the three critical Bradford Hill considerations for AOPs, as a basis to contribute to collective experience.Specific attention is also given to how precisely and accurately one can potentially predict an impact on KEdownstream based on some measurement of KEupstream. This is captured in the form of quantitative understanding calls for each KER. See pages 55-56 of the User Handbook for a review of quantitative understanding for KER's. More help

Given the complex nature of PPARalpha’s functioning within a multi-subunit transcription factor regulating the transcriptional expression of a multitude of genes that facilitate lipid metabolism, to our knowledge, the relationship between PPARalpha signaling and individual gene expression has not yet been quantitatively modeled.  However, the gene regulatory networks structure is well established (KEGG Pathway, map03320) and numerous empirical observations of the positive relationship between PPARalpha signaling with transcript expression and downstream metabolic pathways (Kersten 2014, Desvergne and Wahli 1999), there is opportunity to develop a quantitative gene signaling model for this system.  For peroxisomal and mitochondrial fatty acid beta-oxidation pathways and ketogenesis, a variety of enzyme kinetics information is available for modeling (see reviews by Kersten 2014, Desvergne and Wahli 1999) as well as basic knowledge of the reaction stoichiometry of each metabolic reactions that can contribute to metabolic energy substrates for systemic use.  Resultant models should be integrated with the work of Kashiwaya et al (1994) who have developed a detailed quantitative model for the metabolic flux of glucose including the influence of ketone bodies and insulin action on the dynamics of glycolysis versus gluconeogenesis.  Dynamic energy budget (DEB) models (Nisbet et al 2000) have strong utility for integrating the dynamics of energy input and allocation to organismal processes of importance for characterizing/predicting the condition of the individual (ie. growth and maturation) as well as population-level responses (ie. allocation of energy to reproduction).  DEB modeling has great potential for integrating suborganismal processes into individual and population level outcomes (Ananthasubramaniam et al 2015) and could serve to integrate data from dose-responsive relationships among PPARalpha antagonistic nitrotoluenes and fatty acid metabolism, muscle loss and body weight loss (Rawat et al 2010, Deng et al 2011, Wilbanks et al 2014, Quinn et al 2007, Xu and Jin 2012) thus supporting development of a semi-quantitative or quantitative AOP.

Considerations for Potential Applications of the AOP (optional)

At their discretion, the developer may include in this section discussion of the potential applications of an AOP to support regulatory decision-making. This may include, for example, possible utility for test guideline development or refinement, development of integrated testing and assessment approaches, development of (Q)SARs / or chemical profilers to facilitate the grouping of chemicals for subsequent read-across, screening level hazard assessments or even risk assessment. While it is challenging to foresee all potential regulatory application of AOPs and any application will ultimately lie within the purview of regulatory agencies, potential applications may be apparent as the AOP is being developed, particularly if it was initiated with a particular application in mind. This optional section is intended to provide the developer with an opportunity to suggest potential regulatory applications and describe his or her rationale.To edit the “Considerations for Potential Applications of the AOP” section, on an AOP page, in the upper right hand menu, click ‘Edit.’ This brings you to a page entitled, “Editing AOP.” Scroll down to the “Considerations for Potential Applications of the AOP” section, where a text entry box allows you to submit text. In the upper right hand menu, click ‘Update AOP’ to save your changes and return to the AOP page or 'Update and continue' to continue editing AOP text sections.  The new text should appear under the “Considerations for Potential Applications of the AOP” section on the AOP page. More help

The present AOP may require additional conditions to be fully manifested.    The risk for this AOP is expected to be exacerbated during fasting, starvation and/or sub-optimal nutrition where interference with PPARα signaling is likely to contribute synergistically toward decreased exercise performance and increased body-weight loss. 

References

List the bibliographic references to original papers, books or other documents used to support the AOP. More help

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