Aop: 296


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

Oxidative DNA damage leading to chromosomal aberrations and mutations

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
Oxidative DNA damage, chromosomal aberrations and mutations

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


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

Eunnara Cho1,2, Ashley Allemang3, Marc Audebert4, Vinita Chauhan5, Stephen Dertinger6, Giel Hendriks7, Mirjam Luijten8, Francesco Marchetti1,2, Sheroy Minocherhomji9, Stefan Pfuhler3, Daniel J. Roberts10, Kristina Trenz11, Carole L. Yauk1, 12 *

1 Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada

2 Department of Biology, Carleton University, Ottawa, ON, Canada

3 The Procter & Gamble Company, Mason, OH, United States

4 Toxalim, INRAE, Toulouse, France

Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, ON, Canada

Litron Laboratories, Rochester, NY, United States

7 Toxys, Leiden, The Netherlands

Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands

Amgen, Thousand Oaks, CA, United States

10 Charles River Laboratories, Skokie, IL, United States

11 Boehringer-Ingelheim, Ingelheim, Germany

12 Department of Biology, University of Ottawa, Ottawa, ON, Canada

*Corresponding author: Carole Yauk (

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
Brendan Ferreri-Hanberry   (email point of contact)


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
  • Carole Yauk
  • Brendan Ferreri-Hanberry


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 comment. Do not cite EAGMST Under Review 1.76 Included in OECD Work Plan
This AOP was last modified on May 08, 2022 11:33
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
Increase, Oxidative damage to DNA November 03, 2021 04:31
Inadequate DNA repair October 26, 2021 08:25
Increase, DNA strand breaks August 22, 2021 22:57
Increase, Mutations August 16, 2021 14:41
Increase, Chromosomal aberrations August 16, 2021 14:34
Increase, Oxidative DNA damage leads to Inadequate DNA repair August 19, 2021 09:57
Increase, Oxidative DNA damage leads to Increase, DNA strand breaks October 01, 2021 12:19
Inadequate DNA repair leads to Increase, DNA strand breaks November 03, 2021 03:51
Increase, Oxidative DNA damage leads to Increase, Mutations August 06, 2021 14:11
Increase, DNA strand breaks leads to Inadequate DNA repair August 16, 2021 12:46
Increase, DNA strand breaks leads to Increase, Mutations October 29, 2019 14:41
Inadequate DNA repair leads to Increase, Mutations June 03, 2020 23:25
Inadequate DNA repair leads to Increase, Chromosomal aberrations November 03, 2021 01:46
Increase, DNA strand breaks leads to Increase, Chromosomal aberrations August 16, 2021 12:40
Hydrogen peroxide May 19, 2019 17:21
Potassium bromate May 19, 2019 17:21
Ionizing Radiation May 07, 2019 12:12
Cadmium chloride May 19, 2019 17:23
tert-Butyl hydroperoxide May 19, 2019 17:24
Reactive oxygen species August 15, 2017 10:43
Hydroquinone November 08, 2019 13:06
4-Nitroquinoline 1-oxide November 08, 2019 13:07


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

This adverse outcome pathway (AOP) network describes the linkage between oxidative DNA damage and irreversible genomic damage (chromosomal aberrations and mutations). Both endpoints are of regulatory interest because irreversible genomic damage is associated with various adverse health effects such as cancer and heritable disorders.

Mutagens are genotoxic substances that alter the DNA sequence and this includes single base substitutions, deletion or addition of a single base or multiple bases of DNA, and complex multi-site mutations. Mutations can occur in coding and non-coding regions of the genome and can be functional or silent. The site and type of mutation will determine its consequence. Clastogens are genotoxic substances that cause DNA single- and double-strand breaks that can result in deletion, addition, or rearrangement of sections in the chromosomes. As with mutagens, the type and extent of chromosome modification(s) determine cellular consequences.

The molecular initiating event (MIE) of this AOP is increase in oxidative DNA damage, indicated by increases in oxidative DNA lesions. DNA in any cell type is susceptible to oxidative damage due to endogenous (e.g., aerobic respiration) and exogenous (i.e., exposure to oxidants) oxidative insults. Although this is the MIE for this AOP network, we note that there are numerous upstream key events (KE) that can also lead to DNA oxidation. Thus, we expect this AOP to be expanded upstream, and to be incorporated into a variety of AOP networks. Generally, cells are able to tolerate and readily repair oxidative DNA lesions by basal repair mechanisms. However, excessive damage can override the basal repair capacity and lead to inadequate repair of oxidative damage (KE1). Mutations (AO1) can arise from incorrect repair following oxidative damage (KE1), where incorrect bases are inserted opposite lesions during DNA replication. Insufficiently or incompletely repaired oxidative DNA lesions can also lead to DNA strand breaks (KE2) that, if insufficiently repaired (KE1), may result in chromosome aberrations (AO2) and/or mutations (AO1) following DNA replication.

Support for this AOP is strong based on extensive understanding of the mechanisms involved in this pathway, evidence of essentiality of certain KE (i.e., studies using reactive oxidative species scavengers and modulating DNA repair enzymes), and a robust set of studies providing empirical support for many of the KERs.

We anticipate that this AOP will be of widespread use to the regulatory community as oxidative DNA damage is considered an important contributor to the adverse health effects of many environmental toxicants. Importantly, the AOP points to critical research gaps required to establish the quantitative associations and modulating factors that connect KEs across the AOP, and highlights the utility of novel test methods in understanding and evaluating the implications of oxidative DNA damage.

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

This AOP network describes oxidative damage to DNA (MIE) leading to mutations (AO1) and chromosomal aberrations (AO2). The AOP summarizes the evidence supporting how increases in oxidative DNA lesions can overwhelm DNA repair mechanisms, causing an accumulation of unrepaired lesions and/or repair intermediates. Failure to resolve oxidative DNA damage can lead to permanent alterations to the genome. Increases in reactive oxygen and nitrogen species (RONS) that can lead to oxidative DNA lesions is a broad characteristic of many xenobiotics and indeed, is noted as one of the 'key characteristics of carcinogens' (Smith et al., 2016). Moreover, oxidative stress is often suspected to be the cause of DNA damage by substances whose mechanism of genotoxicity is uncertain [e.g., glyphosate (Kier and Kirkland, 2013; Benbrook, 2019), monosodium glutamate (Ataseven et al., 2016)]. Thus, this AOP network will serve as a key tool in mechanism-based genotoxic hazard identification and assessment.

Oxidative stress describes an imbalance of oxidants and antioxidants in the cell. Oxidative stress can occur when free radicals overwhelm the antioxidant capacity under certain physiological conditions, such as inflammation due to diseases, and also through exogenous stressors that are oxidants and/or induce ROS and other free radicals. Excess oxidants can occur following exposure to agents that: (a) generate free radicals and other RONS, (b) deplete cellular antioxidants, and/or (c) have oxidizing properties (Parke, 1982). Furthermore, there are substances that can induce inflammatory responses and in turn cause oxidative stress as a secondary effect (Gustafson et al., 2016). The effects of oxidative stress in the cell are broad; all biomolecules are susceptible to damage by oxidizing agents. Oxidative stress and associated damage to cellular components have been implicated in various diseases, including neurodegenerative diseases, cardiovascular diseases, diabetes, and different cancers (Liguori et al., 2018). 

Free radicals and other RONS are continuously generated as by-products of endogenous redox reactions (e.g., oxidative phosphorylation in the mitochondria, NADPH oxidation to NADP+ by NADPH oxidase) at steady state. The steady state concentration of oxidants is essential for cellular functions (e.g., as secondary signalling molecules) and is tightly regulated by endogenous antioxidants such as glutathione, and antioxidant enzymes such as superoxide dismutase and catalase. There are many protective barriers against oxidative damage to the genome within the cell. Compartmentalization is one of the ways in which DNA is protected from exposure to ROS and other free radicals generated by various biological processes that occur in different parts of the cell. Examples include CYP450 enzyme activity in the cytoplasmic endoplasmic reticulum and oxidative phosphorylation in the mitochondria (Dan Dunn et al., 2015; Veith and Moorthy, 2019).

Exogenous sources such as ionizing radiation, ultraviolet (UV) radiation, and certain compounds can directly or indirectly generate reactive species, causing oxidative stress. Oxidizing compounds can also directly cause oxidative damage to cellular components (Liguori et al., 2018). The nitrogenous bases of the DNA are susceptible to oxidation by both endogenous and exogenous oxidants (Berquist and Wilson III, 2012). Oxidizing agents cause a wide range of oxidative DNA lesions. In addition to strand breaks due to direct RONS attack on the phosphate backbone, the nitrogenous bases can be modified in various ways by free radicals and other reactive species. If these lesions are left unrepaired or the attempt at repair fails, mutations and strand breaks can occur, permanently altering the DNA sequence. All nitrogenous bases are susceptible to oxidative damage, however, to different extents. A variety of DNA lesions caused by RONS are described within this AOP (Cooke et al., 2003). Notably, guanine is most readily damaged by RONS and other oxidants due to its low reduction potential. Indeed, 8-oxoG is the most abundant oxidative DNA lesion and has been extensively studied. Consequently, chromosomal regions containing a higher GC content are more susceptible to oxidative base modifications. For example, human telomeres, which are constituted by TTAGGG repeats and a single-stranded G-rich 3' overhang, are known to be comparatively more sensitive to oxidative damage than other regions in the genome and accumulate 8-oxodG lesions that eventually lead to telomere shortening and genomic instability (Petersen et al., 1998; Bolzan, 2012; Fouquerel et al., 2019). The repair mechanisms and consequences of oxidative damage to telomeres are active areas of research. 

Within this AOP network, we mainly focus on 8-oxo-dG as oxidative DNA damage representing the MIE, for practicality. The fate of guanine lesions has been most extensively researched and well understood (Roszkowski et al., 2011; Whitaker et al., 2017; Cadet et al., 2017; Markkanen, 2017). Also, 8-oxodG is an accepted biomarker of oxidative stress and oxidative damage to DNA both in vitro and in vivo (Cooke et al., 2008; Roszkowski et al., 2011; P. Li et al., 2014; Guo et al., 2017). Several different detection methods for 8-oxo-dG are commercially available and, thus, are easy to access (e.g., immunodetection, comet assay). We note that 8-oxo-dG is not a terminal product of oxidative damage; 8-oxo-dG can be further oxidized to additional mutagenic lesions such as spiroiminodihydantoin and guanidinohydantoin (Jena and Mishra, 2012). However, as with many other oxidative lesions on pyrimidines and adenine, these guanine lesions are estimated to be small fractions compared to 8-oxo-dG (Yu et al., 2005; Cooke et al., 2008). 

The pathway to mutations (AO1) from oxidative DNA lesions can either proceed (a) directly to mutation through replication of unrepaired oxidized DNA bases (insertion of an incorrect nucleotide by a replicative or translesion polymerase), or (b) indirectly through the creation of strand breaks that can be misrepaired to introduce mutations (Taggart et al., 2014; Rodgers and McVey, 2016). Strand breaks can arise during attempted repair of oxidative DNA lesions. Oxidative base damage is predominantly repaired by base excision repair (BER), and by nucleotide excision repair (NER) to a lesser extent (Whitaker et al., 2017). In the excision repair pathways, single strand breaks (SSB) are transiently introduced as repair intermediates. With increasing oxidative lesions and more lesions in close proximity to each other, the quality and efficiency of repair may be compromised, resulting in persistent unrepaired lesions and repair intermediates. Accumulated repair intermediates such as SSBs, oxidized bases, and abasic sites can interfere with proximal excision repair and/or impede replication fork elongation, leading to double strand breaks (DSBs), which are more toxic and difficult to repair (Yang et al., 2006; Sedletska et al., 2013; Ensminger et al., 2014). Furthermore, if a SSB is introduced nearby another SSB on the opposite strand prior to or during excision repair, these SSBs may be converted to DSBs. Some studies suggest that multiple DNA lesions within one or two helical turns can increase the rate of DSB formation (Cannan and Pederson, 2017). Insufficiently repaired DSBs (incorrect or lack of rejoining) can permanently alter the DNA sequence (e.g., insertion, deletion, translocations), and cause both mutations (AO1) and structural chromosomal aberrations (AO2) (Rodgers and McVey, 2016). These processes are described in more detail within the AOP.   

Overall, we anticipate that this AOP network will provide a key sub-network that will be relevant to many future AOPs. However, we note that the AOs herein, increased mutations and chromosomal aberrations, are regulatory endpoints of concern in and of themselves. This AOP also provides a template for designing testing strategies for RONS-induced genetic effects. Despite the fact that this is a long-studied area in genetic toxicology, this work highlights notable gaps in the empirical evidence linking adjacent KEs. For example, the extent to which the levels of oxidative DNA damage must increase before DNA repair processes are overwhelmed leading to an AO is currently poorly understood, and may vary based on the test system. Hence, further data are needed to improve our ability to predict whether this pathway is relevant to a chemical’s toxicological effects..

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


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 1634 Increase, Oxidative damage to DNA Increase, Oxidative DNA damage
2 KE 155 Inadequate DNA repair Inadequate DNA repair
3 KE 1635 Increase, DNA strand breaks Increase, DNA strand breaks
4 AO 185 Increase, Mutations Increase, Mutations
5 AO 1636 Increase, Chromosomal aberrations Increase, Chromosomal aberrations

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

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


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

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
human Homo sapiens NCBI
mice Mus sp. NCBI
rat Rattus norvegicus 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

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

Biological plausibility:

Overall, the biological plausibility of this AOP network is strong. This network was developed by a team of experts within the Health and Environmental Sciences Institute’s Genetic Toxicology Technical Committee who have decades of experience in research on DNA repair and genetic toxicology.

Oxidative DNA lesions are primarily repaired by base excision repair (BER). BER is a multistep process that involves multiple enzymes including OGG1, which removes oxidized guanine bases and creates a nick 3’ to the damaged base, and APE1, which then removes the resulting abasic site by cleaving 5’ to the damaged base. It is known that BER glycosylases are constitutively expressed and that APE1 is an abundant enzyme (Tell et al., 2009). A spike in BER substrates could lead to an imbalance in the initiating steps of BER, causing an accumulation of abasic sites and other repair intermediates (e.g., SSBs) that can lead to the AOs described herein (Coquerelle et al., 1995; Yang et al., 2006; Nemec et al., 2010)Another suspected and biologically plausible mechanism by which oxidative DNA lesions can lead to clastogenic effects is through futile cycles of MUTY-initiated BER, which removes dA inserted opposite 8-oxodG during replication. MUTYH is readily available at the replication foci to initiate BER if needed but can initiate BER post-replication as well (Hayashi et al., 2002; Nakamura et al., 2021). During BER, following the removal of dA by MUTY and APE1, polymerases such as pol β and pol κ could re-insert dA opposite 8-oxodG, rendering the repair process futile. Such cyclical rounds of BER may cause an accumulation of repair intermediates such as SSBs in the newly synthesized strand (Hashimoto et al., 2004; Oka and Nakabeppu, 2011) SSBs can turn into DSBs if they occur in close proximity to each other on opposite strands (Iliakis et al., 2004; Fujita et al., 2013; Mehta and Haber, 2014). If DSBs are not repaired in a timely manner, the broken ends may diffuse away from their original position and result in genetic translocation where incorrect ends are joined, or loss of DNA segments, leading to structural aberrations (AO2) (Obe et al., 2010; Durante et al., 2013).

Error-prone repair of DSBs (KE1 Description section 3) can also lead to mutations, providing an alternate pathway to AO1, an increase in mutations (Sedletska et al., 2013). Non-homologous end joining (NHEJ), the error-prone joining of two broken ends, is a faster process compared to homologous recombination (HR), which uses the homologous sequence in the sister chromatid or homologous chromosome as a template to ensure fidelity of the reconstructed strands (Mao et al., 2008a; Mao et al., 2008b). The preference for the use of sister chromatids versus homologous chromosomes in HR depends on the stage of cell cycle in which the DSB occurs. NHEJ may be preferred over HR in many instances, especially under stress, leading to altered sequences at the site of repair (Rodgers and McVey, 2016). HR is mostly restricted to S and G2 phases of the cell cycle and, while NHEJ can occur at all stages of the cell cycle, it mostly occurs in G1, when the sister chromatids have not yet been synthesized (Brandsma and van Gent, 2012).

The structure of the site of a DSB and end resection can determine the repair pathway and the repair outcome. Typically, breaks with single stranded overhangs are processed by end resection and proceed to HR or error-prone homology-based annealing (i.e, single strand annealing and alternative end-joining). DSBs with blunt ends are more likely to be rejoined by NHEJ (Ceccaldi et al., 2016). The error-prone nature of DSB repair by NHEJ has been extensively studied and widely accepted. Under stress by exogenous or endogenous sources (e.g., xenobiotics), DSBs can also lead to mutagenic salvage DNA repair pathways such as break-induced replication (BIR) and microhomology-mediated break-induced replication (MMBIR) which are linked to mutagenesis, chromosomal rearrangemnts, and genomic instability (Sakofsky et al., 2015; Kramara et al., 2018).

It is established and accepted that unrepaired oxidative DNA lesions, especially 8-oxodG and FapydG, are mutagenic (AO1). During DNA replication, the presence of these unrepaired adducts (KE1: Inadequate repair) on nucleotides leads to incorrect base pairing with incoming nucleosides. This occurs without causing structural disturbance leading to evasion of mismatch repair (Cooke et al., 2003). It is well-understood that both 8-oxodG and FapydG readily base pair with adenine, giving rise to G to T transversions, which are the predominant base substitutions caused by oxidative stress (Cadet and Wagner, 2013; Poetsch et al., 2018)

The underlying biology of the KERs leading to chromosomal aberrations (AO2) is more complex. There are a variety of biologically plausible mechanisms that link inadequate repair of oxidative DNA lesions (KE1; see section 2) of KE Description) to DNA strand breaks (KE2), which, if insufficiently repaired (KE1; see section 3) of KE Description), can cause chromosomal aberrations. Mechanistically, these pathways are well understood (Yang et al., 2006; Nemec et al., 2010; Markkanen, 2017). However, empirical evidence supporting the occurrence of these events is limited in the current literature.

Telomeres, which are rich in GC, are especially susceptible to oxidative damage. 8-oxodG in telomeres causes the replicative DNA polymerase δ to stall because pol δ is not proficient in extending past dC inserted opposite 8-oxodG (Markkanen et al. 2012). Thus, an accumulation of 8-oxodG in telomeres can increase the risk of replication fork collapsing due to stalling (Fouquerel et al. 2019). Furthermore, oxidized dNTPs such as 8-oxoGTPs inserted in the telomere by the telomerase terminates the elongation process as the telomerase is incapable of extending past an 8-oxodG (Fouquerel et al. 2016). Both scenarios can result in the loss and shortening of telomeres. Damage to telomeres can trigger the DNA damage response and be treated in the same manner as DSBs, in which unprotected ends are fused with other available ends leading to structural aberrations (i.e., chromosomal fusions, bridges, micronuclei) (Barnes et al., 2019; Fouquerel et al., 2019).  

Time- and dose-response concordance:

The WOE supporting the time- and dose-response concordance of KEs leading to the AOs is between moderate and strong.

The MIE (increase in oxidative DNA lesions) can be measured shortly following exposure to stressors. In cell-free systems and cell-based in vitro models, 8-oxodG has been quantified as early as 15 minutes following chemical exposure (Ballmaier and Epe, 2006). Oxidative lesion formation and induction of strand breaks have been demonstrated by time course experiments, where increases in oxidative lesions were detected at earlier time points and at lower concentrations than strand breaks following exposure to various oxidative stress-inducing chemicals [e.g., Ballmaier and Epe (2006), Deferme et al. (2013)]. Mutations (AO1) and chromosomal aberrations (AO2) must be measured after replication and cell division; therefore, these endpoints are only detected at much later time points than the MIE and KEs. Due to the vastly different sensitivities and dynamic ranges of the methodologies detecting the events in these AOPs, it is difficult to demonstrate concordance in concentration-response between the upstream events and AO.

Uncertainties, inconsistencies, and data gaps:

Currently, quantitative understanding of the amount of oxidative lesions that lead to the two AOs of this AOP network, mutations and chromosomal aberrations, is very limited. Very few studies have specifically investigated the extent of chromosomal aberrations induced by different levels of oxidative DNA lesions. Quantitative studies of different oxidative DNA lesions corresponding to mutation frequencies are also very limited. In order to increase the quantitative understanding of the KERs and to facilitate predictive toxicology, studies are needed to investigate the quantity of 8-oxodG in addition to the endogenous levels required to overwhelm DNA repair and lead to chromosomal aberrations and mutations. We note that the mutagenicity of 8-oxodG has been most extensively studied, while other oxidative DNA lesions have been studied to a lesser extent. In addition, oxidative DNA base modifications such as 8-oxoG also appear to play a role in modulating gene expression and serve as epigenetic markers (Ba and Boldogh, 2018; Bordin et al. 2021). Thus, the interplay of the regulatory roles of oxidized DNA bases and DNA damage response, and its influence on the toxicity of oxidative DNA lesions must be considered.             

Quantitative understanding of the relationships comes primarily from studies that modulate levels of oxidative DNA damage through manipulation of repair enzyme activity. In these studies, conflicting observations have been made following modulation of OGG1, the primary repair enzyme for 8-oxodG lesions. While OGG1 protected against DSB formation and cytotoxicity of certain compounds (e.g., methyl mercury, bleomycin, hydrogen peroxide), DSBs were exacerbated by the presence of OGG1 in some other cases (e.g., ionizing radiation, conflicting results for hydrogen peroxide) (Ondovcik et al., 2012; Wang et al., 2018). Available literature indicate that the effect of inadequate repair of oxidative lesions manifests differently for different stressors; it has been suggested that these discrepancies may be due to the difference in proximity of lesions to each other (clustered lesions vs. single lesions) (Yang et al., 2004; Yang et al., 2006). 

This AOP network primarily describes oxidative damage to the nuclear DNA (nDNA). However, we must acknowledge that oxidative damage occurs also in the deoxynucleotide triphosphate (dNTP) pool and mitochondrial DNA (mtDNA). Due to mtDNA's location, it is more susceptible to oxidative damage than nDNA. Indeed, crosstalk exists between the nucleus and mitochondria during oxidative stress (Cha et al., 2015; Saki and Prakash, 2017). BER maintains both mitochondrial and nuclear genomic integrity (Cha et al., 2015). Oxidized dNTPs, especially 8-oxodGMP, can be inserted into both genomes during replication and excision repair, resulting in mismatches and impediment of the repair of existing damage, respectively; both scenarios can directly lead to inadequate DNA repair, contributing to the progression of the AOP network (Colussi et al., 2002; Russo et al., 2004; Caglayan et al., 2017). Moving forward, KEs addressing oxidative damage to the dNTP pool and mtDNA are necessary to build a more complete map of oxidative stress-related genotoxicity and to expand the AOP network to other related AOs.  

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

Theoretically, this AOP is relevant to any cell type in any organism at any life stage. Regardless of the type of cell or organism, DNA is susceptible to oxidative damage and repair mechanisms exist to protect the cell against permanent chromosomal damage. Generally, DNA repair pathways are highly conserved among eukaryotic organisms (Wirth et al., 2016). Base excision repair (BER), the primary repair mechanism for oxidative DNA lesions, and associated glycosylases are highly conserved across eukaryotes (Jacobs and Schar, 2012). DNA strand break repair pathways such as homologous recombination (HR) and non-homologous end joining (NHEJ) are shared among eukaryotes as well. Induction of chromosomal aberrations and mutations following oxidative DNA damage has been studied in both eukaryotic and prokaryotic cells. Notably, the KEs of this AOP have been measured in rodent models (i.e., rat and mouse) and mammalian cells in culture (e.g., TK6 human lymphoblastoid cells, HepG2 human hepatic cells, Chinese hamster ovary cells) (Klungland et al., 1999; Arai et al., 2002; Platel et al., 2009; Platel et al., 2011; Deferme et al., 2013).

The occurrence of oxidative DNA damage and chromosomal aberrations are well-established events in humans. Micronucleus and 8-oxodG have been quantified in various tissues and fluids as part of occupational health and biomonitoring studies. Detection of 8-oxodG is typically used as a measure of oxidiative DNA damage to link exposure and/or diseases to oxidative stress [e.g., urinary 8-oxodG (Hanchi et al., 2017); 8-oxodG in tumour samples (Mazlumoglu et al., 2017)]. Micronuclei (MN) are also regularly quantified as a biomarker of genotoxicant exposure or genotoxic stress in humans. Numerous examples of detecting MN in different human tissues (e.g., lymphocytes, buccal cells, urothelial cells) are available in the current literature (Li et al., 2014; Dong et al., 2019; Alpire et al., 2019). Mutations also have been measured in human samples of diverse cell types (Ojha et al., 2018; Zhu et al., 2019; Liljedahl et al., 2019). As such, observations of the MIE and the two AOs of this AOP have been extensively documented in humans.

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

A large number of studies have been published that explore the effects of KE modulation on downstream effects. These studies broadly provide strong support to the essentiality of the events within the AOP. Below are examples demonstrating the effects of KE modulation on downstream events.

Essentiality of Increase, oxidative DNA damage (MIE)

  • GSH depletion increases 8-oxo-dG (MIE), and DNA strand breaks (KE2)
    • HepG2 human hepatocytes were treated with 1 mM buthionine sulphoximine (BSO), a GSH-depleting agent, for 4, 8, and 24 hours. Time-dependent statistically significant reduction in GSH was observed at all time points when compared to baseline. The level of 8-oxo-dG lesions was measured 6 and 24 hours after BSO exposure and, at both time points, there was a statistically significant increase in oxidative DNA lesions. A higher magnitude of lesions were present at 24 hours and with statistically significant increases in strand breaks (measured via comet assay) as compared to control (p<0.01) (Beddowes et al., 2003).
  • Antioxidant treatment reduces oxidative lesions, downstream strand breaks, and MN induction (AO2)
    • A 3 hour exposure of HepG2 cells to increasing concentrations of tetrachlorohydroquinone (TCHQ) with N-acetylcysteine (NAC: a radical scanvenger and precursor to glutathione) pre-treatment reduced the amount of cellular ROS (measured by DCFH-DA assay), 8-oxodG, and strand breaks induced by TCHQ measured immediately following exposure. The MN assay at 24 hours indicated a statistically significant decrease in MN at the highest concentration (Dong et al., 2014).
    • Reduction of 8-oxo-dG levels following NAC treatment was also observed in embryos isolated from C57BL/6Jpun/pun mice treated with NAC via drinking water; NAC significantly reduced the number of 8-oxo-dG in the treatment group (Reliene et al., 2004). In human blood mononuclear cells collected in clinical studies, 72-hour NAC treatment significantly reduced the number of MN in the cells. Together, these data support the correlation between the levels of ROS, 8-oxo-dG, and MN frequency (Federici et al., 2015).

Essentiality of Inadequate DNA repair (KE1)

  • The effect of inadequate DNA repair on lesion accumulation and strand breaks (KE2)
    • Nth1 knock-out in vivo - FapyG and FapyA lesions were measured in liver nuclear extracts from wild type and Nth1-/- mice. Statistically significant increases in FapyG and FapyA were observed in Nth1-/- mice. These results demonstrate insufficient repair leading to accumulation of unrepaired oxidative lesions (Hu et al., 2005).
    • Ogg1 knock-out in vitro - In Ogg1-/- mouse embryonic fibroblasts (MEF) treated with 400 µM hydrogen peroxide for 30 minutes, there were significantly fewer strand breaks measured by alkaline comet assay, compared to Ogg1+/+ MEFs. Time series (5 – 90 minutes) immunoblotting of the genomic DNA using anti-8-oxo-dG antibodies indicated a larger magnitude of oxidative lesions in Ogg1-/- cells compared to wild type.  Overall, these results demonstrate the role of Ogg1 in the generation of strand breaks during BER following oxidative DNA damage (Wang et al., 2018).    
  • The effect of inadequate DNA repair on MN induction (AO2)
    • Ogg1 knock-out in vivo - In Ogg1-deficient mice exposed to silver nanoparticles (AgNPs) for seven days, a significant increase (compared to Ogg1+/+) in double strand breaks (indicated by % γ-H2AX positive cells) and 8-oxo-dG lesions were observed at the end of treatment and after 7 days of recovery. The magnitude of increase in DSBs after the 7-day recovery was smaller in wild type. Levels of MN were measured in erythrocytes at the same time points. Increases in MN frequency were significant in wild type (compared to untreated control) on day 7, but not after 7 and 14 days of recovery. In Ogg1-/- mice, the increase in MN was significantly higher on day 7 compared to Ogg1+/+ mice and untreated Ogg1-/- mice and remained significant 7 and 14 days after the exposure (Nallanthighal et al., 2017). Thus, the DNA damage was retained in repair deficient mice leading to persistent clastogenic effects.
  • The effect of inadequate DNA repair on mutations (AO1)
    • Suzuki et al. (2010) knocked-down BER-initiating glycosylases (OGG1, NEIL1, MYH, NTH1) in HEK293T human embryonic kidney cells transfected with plasmids that were either positive or negative for 8-oxodG. The resulting changes in mutant frequencies were measured. Compared to the negative control, all knock-downs caused the mutant frequency to increase in 8-oxodG plasmid-containing cells. Moreover, G:C to T:A transversion frequency increased in all analyzed cells. MYH knock-down decreased A:T to C:G transversion frequency of A paired to 8-oxo-dG; the latter result supports the futile MYH-initiated BER model for the repair of 8-oxo-dG opposite A (Suzuki et al., 2010). Overall, these findings support the essential role of DNA repair in mitigating the mutagenic effects of oxidative DNA lesions.

Essentiality of Increase, DNA strand breaks (KE2)

  • Double strand breaks leading to mutations (AO1)
    • Tatsumi-Miyajima et al. (1993) analyzed different mutations arising from the repair of DSBs induced by a restriction endonuclease, AvaI, in five different human fibroblast cell lines transfected with plasmids containing the AvaI restriction site in the supF gene. Cells containing non-digested plasmids (negative control) produced spontaneous supF mutation frequencies between 0.197 and 2.49 x10-3. In cells containing Ava1-digested plasmids, the number of supF mutants increased, indicated by the rejoining fidelity ((total colonies-supF mutants)/total colonies) between 0.50-0.86. Hence, up to 50% of the colonies were mutated at the AvaI restriction site due to erroneous repair of DSBs induced by the endonuclease.(Tatsumi-Miyajima et al., 1993).
  • Reduction in strand breaks leads to decreases in MN frequency (AO2)
    • Differentiated rat thyroid cells (PCCL3) were internally irradiated by 131I treatment and externally irradiated by 5 Gy X-rays, with or without NAC pre-treatment. Cellular ROS and strand breaks were measured at different time points after irradiation. NAC pre-treatment abrogated ROS induced by both internal and external irradiation at 30 min. The level of ROS was also significantly lower in the NAC-treated cells compared to the non-treated cells at later time points (2, 24, and 48 hours). Moreover, the induction of strand breaks at 30 min was also prevented by NAC pre-treatment and there was a reduction in strand breaks compared to the non-treated cells at later time points as well. Finally, the induction of MN measured 24 and 48 hours after irradiation was significantly lower in NAC-treated cells compared to non-treated cells (Kurashige et al., 2017).

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

1. Support for biological plausibility

Defining Question

High (Strong)


Low (Weak)

Is there a mechanistic relationship between KEup and KEdown consistent with established biological knowledge?

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

KER is plausible based on analogy to accepted biological relationships, but scientific understanding is incomplete

Empirical support for association between

KEs, but the structural or functional relationship between them is not understood.

MIE → KE1: Increase, oxidative DNA damage leads to inadequate repair


The repair mechanisms for oxidative DNA damage have been extensively studied and are well-understood. It is generally accepted that limits exist on the amount of oxidative DNA damage that can be managed by these repair mechanisms.

KE1 → KE2: Inadequate repair leads to Increase, DNA strand breaks


It is well-established that failed attempts to repair of accumulated oxidative lesions and replication fork stalling by both unrepaired and incompletely repaired DNA lesions (e.g., repair intermediates such as abasic sites and SSBs) lead to increase in DNA strand breaks.

KE2 →KE1:

Increase, DNA strand breaks leads to Inadequate repair


It is well recognized that the pathways involved in the repair of DSBs is error-prone. In addition to errors induced by NHEJ, all repair mechanisms have a capacity limit; if the number of strand breaks exceed the repair capacity of the cell, unrepaired  SSBs and DSBs may accumulate.

KE1 → AO1: Inadequate repair leads to Increase, mutations


Numerous studies (cell-based and in vivo) have demonstrated increases in mutation due to unrepaired oxidative DNA lesions (insufficient repair) and incorrect repair (e.g., non-homologous end joining and error-prone lesion bypass). The mechanisms by which these events occur are well-understood.

KE1 → AO2: Inadequate repair leads to Increase, chromosomal aberrations


Chromosomal aberrations may result if DNA repair is inadequate, meaning that the double-strand breaks are misrepaired or not repaired at all. A multitude of different chromosomal aberrations can occur, depending on the timing (i.e., cell cycle) and type of inadequate repair. Examples include copy number variants, deletions, translocations, inversions, dicentric chromosomes, nucleoplasmic bridges, nuclear buds, micronuclei, centric rings, and acentric fragments. A multitude of publications are available that provide details on how these various chromosomal aberrations are formed in the context of inadequate repair.


KE2 →AO1: Increase, DNA strand breaks leads to Increase, mutations


Mechanisms of DNA strand break repair have been extensively studied. It is accepted that non-homologous end joining of DSBs can introduce deletions, insertions, translocations, or base substitution.   


MIE → KE2: Oxidative DNA lesions leads to Increase, DNA strand breaks


Increase in strand breaks due to failed repair of oxidative DNA lesions is an accepted mechanism for the clastogenic effects of oxidative damage. Concurrent increases in the two KEs have been observed in previous studies. However, data that demonstrate a causal relationship, in accordance with the Bradford-Hill criteria for causality, are limited.


MIE → AO1: Oxidative DNA lesions leads to Increase, mutations


Strong empirical evidence exists in literature demonstrating increases in mutation frequency due to increase in oxidative DNA lesions. Notably, mutagenicity of 8-oxodG, the most abundant oxidative DNA lesion, has been extensively studied and is well-known to cause G to T transversions.



Increase, DNA strand breaks leads to Increase, chromosomal aberrations


DNA strands breaks must occur for chromosomal aberrations to occur. Increase in strand breaks, especially DSBs, may increase the risk of inadequate repair (lack of repair or misrepair) of the damage, leading to translocations, inversions, insertions, and deletions.

2. Support for Essentiality of KEs

Defining Question

High (Strong)


Low (Weak)

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

Direct evidence from specifically designed experimental studies illustrating essentiality for at least one of the important KEs

Indirect evidence that sufficient modification of an expected modulating factor attenuates or augments a KE

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

MIE: Increase, oxidative DNA damage


Studies have demonstrated that indirectly reducing or increasing the amount of oxidative DNA lesions by modulating cellular ROS levels (via antioxidant addition or depletion) causes concordant changes in the levels of strand breaks and MN.

KE1: Inadequate repair


Numerous studies have investigated inadequate BER of oxidative DNA lesions by disrupting BER through generating gene KO rodent or mammalian cell models. Modulation of the downstream KEs (i.e., DNA strand breaks, mutation, MN induction) by dysfunctional BER has been demonstrated in these studies.

KE2: DNA strand breaks


Theoretically, chromosomal aberrations (AO2) cannot occur unless DNA strand breaks occur. Predominantly, indirect evidence exists that support the essentiality of KE2 in leading to mutations (AO1).

3. Empirical Support for KERs

Defining Question

High (Strong)


Low (Weak)

Does empirical evidence support that a change in KEup leads to an appropriate change in KEdown?

Does KEup occur at lower doses and earlier time points than KE down and is the incidence of KEup> than that for KEdown?


Multiple studies showing dependent change in both events following exposure to a wide range of specific stressors.

No or few critical data gaps or conflicting data

Demonstrated dependent change in both events following exposure to a small number of stressors.

Some inconsistencies with expected pattern that can be explained by various factors.

Limited or no studies reporting dependent change in both events following exposure to a specific stressor; and/or significant inconsistencies in empirical support across taxa and species that don’t align with hypothesized AOP

MIE → KE1: Increase, oxidative DNA damage leads to inadequate repair


Empirical in vitro and in vivo data demonstrate that increases in oxidative DNA lesions leads to indications of inadequate repair (i.e., increases in mutation, retention of adducts, increases in lesions despite upregulation of repair enzymes).

KE1 → KE2: Inadequate repair leads to Increase, DNA strand breaks


Limited in vivo data are available. A few In vitro studies have demonstrated a larger increase in DNA strand breaks in BER-defective cells compared to wildtype cells, following various oxidative stresse-inducing chemical exposures. 

In certain cases, as demonstrated by Wang et al. (2018), knock-down of OGG1 (BER-initiating glycosylase) reduced the amount of  DNA strand breaks that formed after exposure to hydrogen peroxide - mostly likely due to the reduction in the incidences of incomplete repair. As such, deficiency in different DNA repair proteins can have varying effects on downstream strand breaks; inadequate repair may manifest differently for different stressors.

KE2 →KE1:

Increase, DNA strand breaks leads to Inadequate repair


Results from many studies indicate dose/incidence and temporal concordance between the frequency of double-strand breaks and the rate of inadequate repair. As DNA damage accumulates in cells, the incidence of inadequate DNA repair activity (in the form of non-repaired or misrepaired DSBs) also increases.

 Uncertainties in this KER include controversy surrounding the error rate of NHEJ, differences in responses depending on genotoxicant exposure levels and confounding clinical factors (such as smoking) that affect double-strand break repair fidelity.

KE1 → AO1: Inadequate repair leads to Increase, mutations


Repair deficiency causing increases in mutations has been extensively demonstrated in both in vitro and in vivo. Overexpression of repair enzymes has been shown to reduce mutation frequency following chemical exposure in vitro, which further supports the causal relationship between these two KEs.

KE1 → AO2: Inadequate repair leads to Increase, chromosomal aberrations


There is little empirical evidence available that directly examines the dose and incidence concordance between DNA repair and CAs within the same study. Similarly, there is not clear evidence of a temporal concordance between these two events. More research is required to establish empirical evidence for this KER.


KE2 →AO1: Increase, DNA strand breaks leads to Increase, mutations


Evidence from in vitro and in vivo studies demonstrating dose and temporal concordance of the two KEs are available. These investigations utilized various stressors such as chemicals and ionizing radiation.


MIE → KE2: Oxidative DNA lesions leads to Increase, DNA strand breaks


Both in vitro and in vivo data are available that the demonstrate dose-response concordance of oxidative DNA lesions formation and strand breakage following exposure to various stressors. However, the temporal concordance between the KEs is not strong; there are discrepancies in the temporal sequence of events that appear to be dependent on the endpoint used to measure the KE (i.e., Fpg comet assay vs. 8-oxodG immunodetection, comet assay vs. ɣ-H2AX immunodetection). 


MIE → AO1: Increase, oxidative DNA lesions leads to Increase, mutations


This KER was demonstrated by knocking out oxidative DNA damage repair protein (OGG1) and exposure to different ROS-inducing chemicals in vitro and in vivo. It is clear that an increase in oxidative DNA lesions is followed by an increase in mutant frequency or G to T transversions. 



Increase, DNA strand breaks leads to Increase, chromosomal aberrations


Temporal concordance is clear in both in vitro and in vivo data. However, due to the differences in the methods used to measure strand breaks and chromosomal aberrations, the concentration-response of these events often appear to be discordant.  

The text in blue were copied and pasted from AOP #272: Direct deposition of ionizing energy onto DNA leading to lung cancer.

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 quantitative understanding of the KERs in this AOP is overall weak. Different cell types have different baseline levels of antioxidants and antioxidant enzymes, as well as different oxidative DNA lesion repair capacity. For example, Nishioka et al. (1999) demonstrated difference in the expression level of OGG1 mRNA across different human tissues (Nishioka et al., 1999). Thus, the quantity of oxidative DNA lesions required to overwhelm the repair mechanisms and lead to chromosomal damage or mutations differ by cell type. Furthermore, antioxidant and DNA repair capacities differ by individual in vivo and are influenced by factors such as age and the disease state of the individual; for example, DNA repair ability and antioxidant enzyme activities are known to decline with age in humans (Liguori et al., 2018; Kozakiewicz et al., 2019; Chen et al., 2020). Such are modulating factors for the AOP progression. Thus, we note that different thresholds exist for the amount of oxidative DNA damage that leads to the AO, depending on the individual and the modulating factors affecting the individual. 

Modulating Factors

As discussed above, there are various modulating factors for this AOP, including genetic polymorphisms in DNA repair and antioxidant response-associated genes in individuals and the metabolic competency (i.e., phase 2 xenobiotic metabolism) of the cell line used. For in vitro experiments, a critical consideration is the  concentration at which genomic effects are measured, as ROS production is expected to be highly elevated at overtly cytotoxic concentrations (i.e., generally >50% cytotoxicity in the context of genotoxicity testing). Mutations and chromosomal aberrations occurring above certain levels of cytotoxicity are not considered relevant to in vivo outcomes. As such, in vitro genotoxicity testing guidelines should be consulted for specific recommendations for selecting the top chemical exposure concentrations.

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

Genotoxicity testing is a fundamental requirement for all chemical and pharmaceutical safety assessments. Although there are established guidelines for in vitro tests, the current standard in vitro genotoxicity assays provide limited mechanistic information and suffer from high sensitivity and low specificity, potentially leading to unnecessary follow up work. The field is moving towards the use of more  biologically relevant in vitro models and tests that inform on mechanisms that cause the observed apical outcome (Whitwell et al., 2015). There is also a movement away from the notion that genotoxicity testing is only valuable to inform potential hazards and identify genotoxic mechanisms of carcinogenesis, as many mechanisms of genotoxicity only operate once a critical exposure threshold is satisfied. Indeed, there is increasing use of genotoxicity data in deriving points of departure to inform risk assessments (Klapacz and Gollapudi, 2020; Luijten et al., 2020; White et al., 2020). Overall, understanding the biological mechanisms (i.e., the MIEs and KEs) that lead to genotoxic outcomes is essential to the risk assessment process (Dearfield et al., 2017), especially if the mechanism is not biologically active at clinically relevant exposures . This AOP network provides a framework for assembling information from different mechanism-based tests to determine the probability that an agent induces oxidative DNA damage, which can be used to demonstrate that the agent itself is not DNA reactive. For example, analysis of a chemical using the Bradford-Hill criteria aligned against this AOP network could be used to determine if the chemical’s primary mode of action is via ROS-induction, rather than an artefact of over-exposure (e.g., cytotoxicity). In the case of a true ROS-driven mechanism, levels of oxidative DNA damage and likely cell cycle delay should occur at concentrations below those that induce chromosomal aberrations and mutations.  

Oxidative DNA damage is a long established mechanism of inducing genotoxicity and, thus, a useful endpoint in assessing genotoxicity risk. From a human health perspective, there is an increasing understanding (and acceptance) of the fact that genomic damage such as mutations, in and of themselves, are adverse (e.g., germ cell mutations) (Heflich et al., 2020). However, a chemical that induces oxidative DNA damage will demonstrate a threshold concentration, below which it does not induce measurable genotoxicity. This is due to the various pathways of endogenous DNA repair and enzymatic reductions that prevent progression of oxidative lesions to adverse genotoxicity outcomes, facilitating quantification of safe permissible exposures. Hence, once it is demonstrated for a chemical that this AOP is operable, a quantitative assessment of in vivo genotoxicity data (e.g., micronuclei or mutations) could be used to assess risk, provided the study design is appropriate (White and Johnson, 2016; Dearfield et al., 2017; White et al., 2020). 

Overall, AOP networks (such as this one) can inform how different testing methods, including fit-for-purpose mechanistic assays, should be used to quantitatively relate KEs to specific adverse genotoxic outcomes. Presently, this AOP network documents clear gaps in the quantitative understanding of genomic damage induced by oxidative DNA lesions that when filled, will enhance risk assessment and predictive toxicology for chemicals that induce oxidative DNA lesions. In conclusion, AOPs like this can be applied in regulatory assessment of chemicals to (a) facilitate mode of action analysis of chemicals to hypothesize potential molecular initiating events; (b) identify test methods and strategies for use with untested chemicals to link them to the appropriate AOP(s); (c) highlight knowledge gaps and uncertainties in genotoxic MOAs; (d) facilitate the development of new ‘all-in-one’ testing strategies, where MOA and apical endpoints are measured concomitantly; and (e) support a non-linear risk assessment when direct DNA-reactivity is not empirically supported.  


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

Alpire, M., C. Cardoso, C. Seabra Pereira, and D. Ribeiro (2019), "Genomic instability in Buccal mucosal cells of children living in abnormal conditions from Santos-Sao Vicente Estuary", Int J Environ Health Res, 1:1-7.

Arai, T., V.P. Kelly, O. Minowa, T. Noda, and S. Nishimura (2002), "High accumulation of oxidative DNA damage, 8-hydroxyguanine, in Mmh/Ogg1 deficient mice by chronic oxidative stress", Carcinogenesis, 23:2005-2010.

Ataseven, N., C. Yuzbasioglu A., and F. Unal (2016), "Genotoxicity of monosodium glutamate", Food Chem Toxicol, 91:8-18.

Ba, X., and I. Boldogh (2018), "8-Oxoguanine DNA glycosylase 1: Beyond repair of the oxidatively modified base lesions", Redox Biol,14:669-678. . 

Ballmaier, D. and B. Epe (2006), "DNA damage by bromate: Mechanism and consequences", Toxicol, 221:166-171.

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