Aop: 413

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

Oxidation and antagonism of reduced glutathione leading to mortality via acute renal failure

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
Oxidation of Reduced Glutathione Leading to Mortality

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

Zarin Hossain 

Under the supervision of Dr. Carmel Mothersill and Dr. Colin Seymour

Department of Biology, McMaster University

 

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
Zarin Hossain   (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
  • Zarin Hossain

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
This AOP was last modified on August 13, 2021 11:08
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
Oxidation, Glutathione (To be considered with MIE) November 09, 2017 06:40
Increased, Reactive oxygen species November 27, 2017 13:15
Increased, Kidney Failure January 16, 2019 08:57
Increase, Necrosis March 19, 2019 09:31
Increased Mortality September 08, 2021 07:07
Increase, Lipid peroxidation August 05, 2021 16:20
Oxidation, Glutathione leads to Increased, Reactive oxygen species August 05, 2021 14:37
Increased, Reactive oxygen species leads to Increase, LPO August 05, 2021 14:37
Increase, LPO leads to Increase, Necrosis August 11, 2021 15:34
Increase, Necrosis leads to Increased, Kidney Failure August 11, 2021 15:35
Increased, Kidney Failure leads to Increased Mortality August 11, 2021 15:35
Uranium August 05, 2021 14:28
Arsenic April 27, 2021 00:15
Bis(2,4,6-trimethylphenyl)-lambda~2~-germane--selenium (1/1) August 05, 2021 16:23

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

We are assiduously exploring mechanisms of toxicity of uranium to fish species in the context of uranium mining via an adverse outcome pathway (AOP). We have created an AOP that addresses the toxicity of aqueous concentrations of uranium. Our molecular initiating event is the oxidation of reduced glutathione, which occurs in the presence of reactive oxygen species (ROS) inducing materials such as uranium. Reduced glutathione is an antioxidant that helps cellular redox homeostasis. This oxidation prevents anti-oxidant function. The following key event - increase in ROS, is a result of both uranium promoting ROS and oxidizing glutathione, to perpetrate oxidative stress. An increase in ROS leaves major macromolecules such as DNA, proteins and membrane phospholipids susceptible to damage. Although there are multiple effects as a result of an increase in ROS, an AOP calls for one specific path. Thus, our following key event is lipid peroxidation, as it is widely observed in uranium-fish toxicity studies. Consequently, the increase in ROS is being investigated for its ability to damage lipids in the cell membranes, more specifically in the kidney for this AOP. Accordingly, our adverse outcome is the development of acute renal failure in fish species. This would be of regulatory significance as renal damage is an endpoint of concern to environmentalists and researchers in this field, as it is likely to lead to population decline.

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

The biology and chemistry of uranium effluent and its effects have been well explored, especially within fish species(Cooley et al. 2000; Kelly and Janz 2009; Goulet et al. 2011; Ma et al. 2020), however it has not been clearly presented. 

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 926 Oxidation, Glutathione (To be considered with MIE) Oxidation, Glutathione
2 KE 1115 Increased, Reactive oxygen species Increased, Reactive oxygen species
3 KE 1445 Increase, Lipid peroxidation Increase, LPO
4 KE 1607 Increase, Necrosis Increase, Necrosis
5 KE 759 Increased, Kidney Failure Increased, Kidney Failure
6 AO 351 Increased Mortality Increased Mortality

Relationships Between Two Key Events (Including MIEs and AOs)

This 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
Title Adjacency Evidence Quantitative Understanding

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

Life Stage Applicability

Identify the life stage for which the KE is known to be applicable. More help
Life stage Evidence
All life stages Moderate

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
fish fish High NCBI
mice Mus sp. Moderate 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
Unspecific High

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 overall assesment renders this AOP: Oxidation and antagonism of reduced glutathione leading to population decline via acute renal failure, moderately plausible and applicable. The domain of applicability applies to all organisms able to experience lipid peroxidation and/or kidney failure. Key events are deemed essential, as there are likely events between events that are not accounted for or as of the same importance. 

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

This AOP is applicable to all life stages and all organisms that produce reactive oxygen species and/or experience lipid peroxidation, and/or experience kidney failure, unless otherwise stated. It is important to note that there is evidence for this AOP primarily in fish studies, however there is no indication that this AOP would not be applicable to other species or life stages. Biological plausibility is high, as much of this AOP is dependant on studies observing uranium toxicity in fish species. There is moderate emperical support, as there are studies available on these KER's but there is a lack of information on dose-response relationships in this AOP. Overall, this AOP should be considered for regulatory significance, especially for fish species exposed to uranium (possible from uranium milling effluent) because this AOP has been observed from these studies. 

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

Support for Essentiality of KEs

Defining Question

Are downstream KEs and/or the AO prevented if an upstream KE is blocked?

High (Strong)

Moderate

Low (Weak)

Direct evidence from specifically designed experimental studies illustrating essentiality for at least one of the important KEs (e.g. stop/reversibility studies, antagonism, knock out models, etc.)

Indirect evidence that sufficient modification of an expected modulating factor attenuates or augments a KE leading to increase in KE down or AO

No or contradictory experimental evidence of the essentiality of any of the KEs

Oxidation,  Glutathione (MIE) High 
  • Binding to redued glutathione converts reduced glutathione to oxidized glutathione. In ordinary situations, oxidized glutathione is able to again be reduced (via glutathione reductase), however when this process is irreguarly disrupted, it can cause oxidative stress manifestations. (Pizzorno 2014; Kalinina et al. 2014)
  • It has been shown that low dose exposure to uranium had significantly higher oxidized glutathione compared to reduced glutathione in exposed fish (Kelly and Janz 2009). 
  • Genes that play a role in glutathione homeostasis are upregulated as a response to an imbalance in oxidized and reduced glutathione, indicating preturbation (Lerebours et al. 2009; Barillet et al. 2011; Song et al. 2012.) 

Increase,  ROS 

Increase, Lipid  Peroxidation

High 
  • Lipid peroxidation if often used as a measure of an increase in reactive oxygen species (ROS) 
  • In a study observing juvenile northern pike, an increase in lipid peroxidation that was attributed to an increase in ROS, in the kidneys of those fish exposed to uranium milling effluent tcompared to a control lake (Kelly and Janz 2009). 
  • Cooley et al., (2000) also saw an increase in lipid peroxidation attributed to ROS increase as a result of uranium milling effluent. 
  • The studies listed above have implied that there is a dose dependancy between an increase in ROS and the manifestation of lipid peroxidation. It is well-accepted that lipid perxidation is a result of imbalanced and increased ROS. 
Increase,  Necrosis High
  • Since necrosis is a common response to trauma, the greater the increase in ROS and oxidative stress, the likelihood for cell death increases (Proskuryakov et al. 2003) - well accepted. 
  • Lipid peroxidation is a common liability for necrotic cell death (Kehrer 1993). 
  • Hepatocyte necrosis has been observed in fish species as a result of increased lipid peroxidation. Necrosis was dependant on exposure to stressor (Cooley et al. 2000). 
  • Rat studies have shown an increase in cellular damage and necrosis as a result of increase in ROS (Ma et al. 2020). 
Increase, Kidney Failure  Moderate
  • It is hypothesized that kidney failure observed in fish species as a result of uranium exposure is a consequence of necrotic lesions commonly seen. 
  • Necrotic lesions have been especially observed in the kidney of fish species as a result of exposure to uranium exhibiting the KE's listed above, including in the the proximal and distal convoluted tubes (Kelly and Janz 2009). 
  • Necrotic lesions leading to kidney failure is a logical explanation that has been suggested, although research is not prominent. There is no evidence that suggests against this phenomenon. 

Increase, Mortality (AO)

High
  • Kidney failure is an indiciator for mortality. In 2017, 1.2 million people died at the cuase of kidney disease (Persaud, 2020)
  • The detrimental effects outlined above are reason for an impairement for survivability, especially when they are experienced by the organism at higher/worse degrees.
  • Stressors responsible for inducing this AOP (such as uranium) have been observed to decrease egg hatchability and reproductive success, decrease survivability, hinder growth and increase mortality overall (Pyle et al. 2002; Kelly and Janz 2009; Goertzen et al. 2011; Simon et al. 2011).  

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.

The biological plausibility for this AOP is overall moderate. It is biologically possible for each step to perpetrate one after the other and for all key events, it is well accepted that one insigates the other. However, the mechanisms and relationships between key events are not fully established or understood. It is assumed that these processes are dynamic and complicated. 

 Support for Biological Plausibility of KERs

Defining Question

High (Strong) 

Moderate Low (Weak)

Is there a mechanistic (i.e. structural or functional) relationship between KEup and KE down consistent with established biological knowledge?

Extensive understanding of the KER based on extensive previous documentation and broad acceptance.

The KER is plausible based on analogy to accepted biological relationship, but scientific understanding is not completely established. There is empirical support for a statistical association between KES but the structural or functional relationship between them is not understood.

MIE to KE1

Glutathione Oxidation leads to Increase in ROS 

MODERATE

Rationale: 

The oxidation of reduced glutathione is (at least partially) resposible for the increase in ROS. Reduced glutathione is an anti-oxidant that plays a role in homeostasis of cellular redox and eliminating free radicals/reactive oxygen species (Pizzorno 2014; Kalinina et al. 2014). When a oxidative stressor is able to bind to reduced glutathione, it is inhibited and becomes its oxidized form (oxidized glutathione). Significantly, inhibiting an anti-oxidant would increase ROS. Not only this, an imbalance between reduced and oxidized glutathione itself, is also a reason for increase in ROS and susceptibility to oxidative stress. 

KE1 to KE2 

Increase in ROS leads to Increase in Lipid Peroxidation

STRONG

Rationale: 

Oxidative stress is often manifested as lipid peroxidation, thus lipid peroxidation is often used to measure oxidative stress. Lipid peroxidation occurs when reactive oxygen species attack and damage the poly unsaturated fatty acids of cellular and subcellular phospholipid membranes. This can cause structural disorder, and damage important ezymes and proteins (Ayala et al. 2014). Therefore, it was quite obvious how an increase in ROS would increase lipid peroxidation, as there are more reactive species able to attack the double-bond lipid membranes. 

KE2 to KE3

Increase in Lipid Peroxidation leads to Increase in Necrosis

MODERATE

Rationale:

Necrosis is a common response to trauma to cells. As mentioned, lipid peroxidation can damage the structural integrity and function of phopholipid membranes; a form of trauma (Ayala et al. 2014). An increase in ROS and lipid peroxidation is commonly cited as an instgator of necrotic cell death (Kehrer 1993). Built-up damage from lipid peroxidation can cause cell and/or organ membranes to break and malfunction. Therefor, an increase in necrosis can be expected as a result of an increase in ROS and lipid peroxidation. 

KE3 to KE4

Increase in Necrosis leads to Kidney Failure

MODERATE

Rationale: 

Again, damage to lipid membranes can affects the viability/survivability of cells and organs. Necrosis and cellular damage have been primarily seen in the liver and kidneys when observing fish species exposed to uranium. There is most definitely other manifestations of an increase in necrosis, however for this AOP, kidney failure was chosen. Kidney failure is characterized by both loss of function and integrity (Lameire 2005; Hilton 2011), which can result from an increase in pathological lesions arising via necrosis. It is biologically very plausible for kidney damage to arise (partially) because of necrosis in kidney tissue, however, it is likely that several other factors regarding kidney survivability also play a role to perpetrate significant kidney failure. 

KE4 to AO

Kidney Failure leads to Increase in Mortality 

HIGH 

Rationale: 

Significant kidney failure can lead to death (Cooley et al. 2000). This has been seen in humans, and many other species. It is well accepted. It is likely that kidney failure may not be the only reason for mortality from this pathway, however it is positive that the drecreased function of the kidney plays a role in survivability. Therefore, it is logical to hypothesize that kindey failure can lead to death in this AOP. 

Empirical Support

The empirical support available for this AOP is moderate. Clear evidence between dose response relationships is not present. However, there are several in-vivo and in-vitro experiments showing these key events respectively causing each other. Only one stressor, uranium, is considered for the empirical support.

Empirical support for KERs

Defining Question

Does the empirical evidence support that a change in the KEup leads to an appropriate change in the KE down? Does KEup occur at lower doses and earlier time points than KE down and is the incidence of KEup higher than that for KE down?

Are inconsistencies in empirical support cross taxa, species and stressors that don’t align with expected pattern of hypothesized AOP?

High (Strong)

Moderate

Low(Weak)

Multiple studies showing dependent change in both exposure to a wide range of specific stressors (extensive evidence for temporal, dose-response and incidence concordance) and no or few critical data gaps or conflicting data.

Demonstrated dependent change in both events following exposure to a small number of specific stressors and some evidence inconsistent with expected pattern that can be explained by factors such as experimental design, technical considerations, differences among laboratories, etc.

Limited or no studies reporting dependent change in both events following exposure to a specific stressor (ie endpoints never measured in the same study or not at all); and/or significant inconsistencies in empirical support across taxa and species that don’t align with expected pattern for hypothesized AOP

MIE to KE1

Glutathione Oxidationleads to Increase in ROS 

MODERATE

Rationale:

Kelly and Janz (2009) demonstrated that low exposure of uranium had significantly increased oxidized glutathione overall and compared to reduced glutathione. Uranium exposure has also shown an increase in genes playing a role in glutathione homeostasis (Lerebours et al. 2009; Barillet et al. 2011; Song et al. 2012.). 

KE1 to KE2 

Increase in ROS leads to Increase in Lipid Peroxidation

MODERATE

Rationale: 

An increase in ROS was determined as the cause of significant lipid peroxidation in juvenile northern pike inhabiting lakes downstream of uranium milling facilities, compared to a control (Kelly and Janz 2009). 

KE2 to KE3

Increase in Lipid Peroxidation leads to Increase in Necrosis

MODERATE

Rationale: 

In whitefish exposed to uranium via diet, damaged lesions were observed the most in the liver where necrotic cell death was also highly observed. This necrotic cell death was accredited to oxidative stress and an increase in lipid peroxidation. The authors also suggested that the increase in necrosis was dose-dependant on uranium exposure (Cooley et al. 2000). 

KE3 to KE4

Increase in Necrosis leads to Kidney Failure

LOW

Rationale: 

lesions have been especially observed in the kidney of fish species as a result of exposure to uranium exhibiting the KE's listed above, including in the the proximal and distal convoluted tubes (Kelly and Janz 2009). There is no/little quantitative analysis confirming this KER. However, no evidence suggests against necrotic lesions instigating kidney damage or failure. It is biologically plausible and thus appropriate. 

KE4 to AO

Kidney Failure leads to Increase in Mortality 

HIGH

Rationale:

Stressors responsible for inducing this AOP (such as uranium) have been observed to decrease egg hatchability and reproductive success, decrease survivability, hinder growth and increase mortality overall (Pyle et al. 2002; Kelly and Janz 2009; Goertzen et al. 2011; Simon et al. 2011). There is little quantitative data available for direct evidence showing that kidney failure will lead to mortality, however it is widely accepted that severe cases have high probability of death. Again, there are additional manifestations of uranium toxicity (not outlined in this AOP) that can contribute to death. It is therefore, very difficult to measure and conclude the "dose"-response relationship between these key events ie. how much kidney failure causes mortality. Though, because this phenomenon is widely accepted (in it's inconclusive form), we suggest the emperical support is high. 

Uncertainties and Inconsistencies 

There are a few uncertainties for consideration: 

  1. The increase in reactive oxygen species could be the molecular initiating event - while this is true and an increase is ROS is a major contributor and key event to this AOP, proceeding is the event of oxidation of glutathione. The increase is ROS is at least partially due to the oxidation of glutathione but is also be at the cause of other events not mentioned in this AOP. ROS production occurs in multiple ways and is quite complex, however the oxidation of glutathione was pertinent when looking at fish species in which this AOP was based. 
  2. At high concentrations of the stressor, it may be expected that reduced glutathione is found at a higher concentration in exposed subjects compared to a control (Kelly and Janz 2009). This is confusing at first, but may be appropriate. Because there is an increase in ROS, a feedback loop exists where the increase in ROS causes an increase in production of reduced glutathione to combat the increased ROS production. There is still oxidation of glutathione occuring, however, an increase in reduced glutathione may also be an indicator or an increase in ROS. At low concentrations, the expected result can be seen where there is a decrease in reduced glutathione or increase in oxidized glutathione compared to a control (Song et al. 2012). Theoretically, in propagating this AOP, oxidized glutathione should typically be in a higher ratio compared to reduced glutathione. Yet, these processes are quite complex and also may very from species to species or organism to organism. They key indicator is an imabalance in the anti-oxidant mechanisms existing with (reduced/oxidized) glutathione. 

Acknowledging these inconcistencies is important to understand the decisions made in this AOP. Although these inconcistencies are present, they do not hinder the validity of the AOP in its biological plausibility or empirical analsysis. Please take these notes into consideration when evaluating the AOP. 

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

The WOE analysis indicates that many KEs and KERs lack some experimental evidence, especially that showing that without one KE, the following KE will be affected or non-existent. However, the overall analysis supports the AOP. Because there is a lack of experimentation on dose-response relationships within this AOP, we propose that it is a qualitative AOP. This is appropritate because the overall pathway is partially based on several studies observing uranium toxicity in fish species. This provides strong evidence and biological plausability in the development of this AOP. There is a large degree of biological plausibility as many of these phenomenons are widly accepted and are logically presented in regards to the sequence of key events. The lack of specific experimental data and uncertainty in quantitative experimentation is difficult for this AOP, as many factors can simultaneously cause key events (such as an increase in ROS or kidney failure). Especially when regarding fish studies, there are several external factors to consider in the environment that may affect these key events. To some degree, many studies have assumed the relationship between exposure and toxic response is dose dependant, however it is yet to be quantified and accepted. In-vitro studies may provide more insight on the dose-response relationship between the stressor and key events, thus providing a better quantitative understanding. A future need for this AOP is a vigorous and thorough experiment model system to evaluate dose-response relationships, conentration-response relationships and exposure-effect relationships within the framework of this 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 establishment of this AOP will allow for the understanding of uranium toxicity to fish species and predictive toxicology with stressors inducing glutathione oxidation. This may especially play a part in understanding the environmental toxicity of heavy metals. It is possible to expand this AOP and explore tritium as another toxic metal that is potentially of threat to fish species. With the prospective overlap of key events between the two stressors, this connection may be the beginning of an AOP web.

References

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

Ayala A, Muñoz MF, Argüelles S. 2014. Lipid Peroxidation: Production, Metabolism, and Signaling Mechanisms of Malondialdehyde and 4-Hydroxy-2-Nonenal. Oxid Med Cell Longev. 2014:360438. https://doi.org/10.1155/2014/360438

Barillet S, Adam-Guillermin C, Palluel O, Porcher J-M, Devaux A. 2011. Uranium bioaccumulation and biological disorders induced in zebrafish (Danio rerio) after a depleted uranium waterborne exposure. Environ Pollut. 159(2):495–502. https://doi.org/10.1016/j.envpol.2010.10.013

Cooley HM, Evans RE, Klaverkamp JF. 2000. Toxicology of dietary uranium in lake whitefish (Coregonus clupeaformis). Aquatic Toxicology. 48(4):495–515. https://doi.org/10.1016/S0166-445X(99)00057-0

Cooley HM, Klaverkamp JF. 2000. Accumulation and distribution of dietary uranium in lake whitefish (Coregonus clupeaformis). Aquatic Toxicology. 48(4):477–494. https://doi.org/10.1016/S0166-445X(99)00058-2

Goertzen MM, Driessnack MK, Janz DM, Weber LP. 2011. Swimming performance and energy homeostasis in juvenile laboratory raised fathead minnow (Pimephales promelas) exposed to uranium mill effluent. Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology. 154(4):420–426. https://doi.org/10.1016/j.cbpc.2011.07.012

Goulet RR, Fortin C, J. Spry D. 2011. Fish Physiology: Homeostasis and Toxicology of Non-Essential Metals. [place unknown]: Academic Press.

Hilton R. 2011. Defining acute renal failure. CMAJ. 183(10):1167–1169. https://doi.org/10.1503/cmaj.081170

Kalinina EV, Chernov NN, Novichkova MD. 2014. Role of glutathione, glutathione transferase, and glutaredoxin in regulation of redox-dependent processes. Biochemistry (Mosc). 79(13):1562–1583. https://doi.org/10.1134/S0006297914130082

Kehrer JP. 1993. Free radicals as mediators of tissue injury and disease. Crit Rev Toxicol. 23(1):21–48. https://doi.org/10.3109/10408449309104073

Kelly JM, Janz DM. 2009. Assessment of oxidative stress and histopathology in juvenile northern pike (Esox lucius) inhabiting lakes downstream of a uranium mill. Aquatic Toxicology. 92(4):240–249. https://doi.org/10.1016/j.aquatox.2009.02.007

Lameire N. 2005. The Pathophysiology of Acute Renal Failure. Critical Care Clinics. 21(2):197–210. https://doi.org/10.1016/j.ccc.2005.01.001

Lerebours A, Gonzalez P, Adam C, Camilleri V, Bourdineaud J-P, Garnier-Laplace J. 2009. Comparative analysis of gene expression in brain, liver, skeletal muscles, and gills of zebrafish (Danio rerio) exposed to environmentally relevant waterborne uranium concentrations. Environmental Toxicology and Chemistry. 28(6):1271–1278. https://doi.org/10.1897/08-357.1

Ma M, Wang R, Xu L, Xu M, Liu S. 2020. Emerging health risks and underlying toxicological mechanisms of uranium contamination: Lessons from the past two decades. Environment International. 145:106107. https://doi.org/10.1016/j.envint.2020.106107

Pizzorno J. 2014. Glutathione! Integr Med (Encinitas). 13(1):8–12.

Proskuryakov SY a, Konoplyannikov AG, Gabai VL. 2003. Necrosis: a specific form of programmed cell death? Experimental Cell Research. 283(1):1–16. https://doi.org/10.1016/S0014-4827(02)00027-7

Pyle GG, Swanson SM, Lehmkuhl DM. 2002. Toxicity of uranium mine receiving waters to early life stage fathead minnows (Pimephales promelas) in the laboratory. Environmental Pollution. 116(2):243–255. https://doi.org/10.1016/S0269-7491(01)00130-0

Simon O, Mottin E, Geffroy B, Hinton T. 2011. Effects of dietary uranium on reproductive endpoints—fecundity, survival, reproductive success—of the fish Danio rerio. Environmental Toxicology and Chemistry. 30(1):220–225. https://doi.org/10.1002/etc.381

Song Y, Salbu B, Heier LS, Teien H-C, Lind O-C, Oughton D, Petersen K, Rosseland BO, Skipperud L, Tollefsen KE. 2012. Early stress responses in Atlantic salmon (Salmo salar) exposed to environmentally relevant concentrations of uranium. Aquatic Toxicology. 112–113:62–71. https://doi.org/10.1016/j.aquatox.2012.01.019

Song Y, Salbu B, Teien H-C, Sørlie Heier L, Olav Rosseland B, Høgåsen T, Erik Tollefsen K. 2014. Hepatic transcriptomic profiling reveals early toxicological mechanisms of uranium in Atlantic salmon (Salmo salar). BMC Genomics. 15(1):694. https://doi.org/10.1186/1471-2164-15-694