Aop: 15

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

Alkylation of DNA in male pre-meiotic germ cells leading to heritable 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
Alkylation of DNA leading to heritable 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

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

Carole Yauk (1)*

Iain Lambert (2)

Francesco Marchetti (1)

George Douglas (1)

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

(2) Dept. of Biology, Carleton University, Ottawa, ON, Canada

  • Communicating author: carole.yauk@canada.ca

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
Carole Yauk   (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
  • Carole Yauk

Status

The status section is used to provide AOP-KB users with information concerning how actively the AOP page is being developed, what type of use or input the authors feel comfortable with given the current level of development, and whether it is part of the OECD AOP Development Workplan and has been reviewed and/or endorsed. “Author Status” is an author defined field that is designated by selecting one of several options from a drop-down menu (Table 3). The “Author Status” field should be changed by the point of contact, as appropriate, as AOP development proceeds. See page 22 of the User Handbook for definitions of selection options. More help
Author status OECD status OECD project SAAOP status
Open for citation & comment TFHA/WNT Endorsed 1.11 Included in OECD Work Plan
This AOP was last modified on April 07, 2020 08:56
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, Heritable mutations in offspring November 29, 2016 19:06
Alkylation, DNA September 16, 2017 10:14
Increase, Mutations October 25, 2019 13:12
N/A, Inadequate DNA repair October 30, 2019 10:07
Alkylation, DNA leads to N/A, Inadequate DNA repair December 10, 2019 10:43
N/A, Inadequate DNA repair leads to Increase, Mutations June 03, 2020 23:25
Alkylation, DNA leads to Increase, Mutations November 29, 2016 19:53
Alkylation, DNA leads to Increase, Heritable mutations in offspring November 29, 2016 19:53
Increase, Mutations leads to Increase, Heritable mutations in offspring November 29, 2016 19:59

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

Germ cell/heritable mutations are important regulatory endpoints for international agencies interested in protecting the health of future generations. However, germ cell mutation analysis has been hampered by a lack of efficient tools. With the publication of the OECD test guideline TG488 (rodent transgene mutation assay) and new technologies (including next generation sequencing) this field is experiencing renewed focus. Indeed, regulatory approaches to assess germ cell mutagenicity were the focus of an IWGT workshop (Yauk et al., 2013). Of particular concern is the inability to address this endpoint through high-throughput screening assays (because spermatogenesis cannot be carried out in culture), and mutagenesis is an important gap in existing high-throughput tests. The motivation for developing this AOP was to provide context for new assays in this field, identify research gaps and facilitate the development of new methods.

In this AOP, a compound capable of alkylating DNA is delivered to the testes causing germ cell mutations and subsequent mutations in the offspring of the exposed parents. The AOP requires uptake of the parent compound or metabolite in spermatogonia and interaction with DNA in those cells. DNA alkylation in male pre-meiotic germ cells is the molecular initiating event. A variety of different DNA adducts are formed that are subject to DNA repair; however, at high doses the repair machinery becomes saturated or overwhelmed. The fate of remaining adducts includes: (1) attempted DNA repair by alternative DNA repair machinery, or (2) no repair. Key event (KE) 1 is insufficient or incorrect DNA repair. Lack of repair can lead to replication of adducted DNA and ensuing mutations in male pre-meiotic germ cells (KE2). Mutations that do not impair spermatogenic processes will persist in these cells and eventually be present in the mature sperm. Thus, the mutations can be transmitted to the offspring (adverse outcome – inherited mutations). It is well documented that mice and other animals exposed to alkylating agents develop mutations in male pre-meiotic germ cells that are then found in sperm, resulting in the transmission of mutations to their offspring. There is a significant amount of empirical evidence supporting the AOP and the overall weight of evidence is strong. Although there are some gaps surrounding some mechanistic aspects of this AOP, the overarching AOP is widely accepted and applies broadly to any species that produces sperm.

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

De novo germ cell mutations are changes in the DNA sequence of sperm or egg that can be inherited by offspring. De novo mutations contribute to a wide range of human disorders including cancer, infertility, autism, schizophrenia, intellectual disability, and epilepsy (Girirajan et al. 2010; Hoischen et al. 2010; Ku et al. 2012; Lupski 2010; Morrow 2010; Vissers et al. 2010). Each child inherits, on average, approximately one de novo mutation per 100 million nucleotides delivered via the parental egg and sperm (Conrad et al. 2011; Kong et al. 2012; O'Roak et al. 2012; Roach et al. 2010). The precise locations and types of mutations in the genomic DNA sequence govern the outcome of these mutations (e.g., protein coding versus intergenic sequences, conserved versus non-conserved mutations, etc.). Although a large portion of human DNA is of unknown function, recent literature suggests that at least 80% of the genome is transcribed, and most DNA is expected to have a biological function (Bernstein et al. 2012). It has been estimated that the proportion of coding and splice-site base substitutions that result in truncating mutations is ~5% (Kryukov et al. 2007), and that as many as 30% of missense mutations are also likely to be highly deleterious due to loss of function (Boyko et al. 2008). When they occur in functional sites, de novo mutations can cause embryonic or fetal lethality, or if viable, can produce a broad spectrum of inherited genetic disorders. Recent estimates suggest that a human genome contains approximately 100 loss-of-function variants, with as many as 20 exhibiting complete loss of gene function (McLaughlin et al. 2010). Therefore, de novo mutations contribute to the overall population genetic disease burden. The present AOP focuses on DNA alkylation in spermatogonia that causes inherited mutation transmitted via sperm, arguably one of the most well characterized modes of action in genetic toxicology. Humans are exposed to alkylating agents from external (e.g., abiotic plant materials, tobacco smoke, combustion products, chemotherapeutic agents) and internal (e.g., byproducts of oxidative damage and cellular methyl donors) sources.

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 97 Alkylation, DNA Alkylation, DNA
2 KE 155 N/A, Inadequate DNA repair N/A, Inadequate DNA repair
3 KE 185 Increase, Mutations Increase, Mutations
4 AO 336 Increase, Heritable mutations in offspring Increase, Heritable mutations in offspring

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 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

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
Adult High

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) can be selected. In many cases, individual species identified in these structured fields will be those for which the strongest evidence used in constructing the AOP was available in relation to this KE. More help
Term Scientific Term Evidence Link
Mus musculus Mus musculus High NCBI
Drosophila melanogaster Drosophila melanogaster High NCBI
Oryzias latipes Oryzias latipes Low NCBI
Syrian golden hamster Mesocricetus auratus Low 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
Male 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
Attached file: Revisedassessmentsummaryaop 15

Before developing this AOP a review of the literature was undertaken to identify studies in which male germ cells were exposed to alkylating agents and measures of DNA adducts, DNA repair and mutations, as well as mutations in offspring, were evaluated. The focus of this AOP (as described in the KERs) is on O-alkylating agents, which are signficantly more mutagenic than N-alkylation chemicals. Studies where sufficient information relating to the chemicals used, dose, tissue, time-point, animal model, experimental procedures and experimental results were available were considered to assess empirical data in germ cells for each of the KEs and KERs in the AOP. The germ cell database on which the AOP was based is found in Supplementary Table I (SupplementalTablesFigures) and is comprised of 32 studies. No study measured multiple KEs within it; however, for each KE there were at least two dose-response and time-series analyses for at least one alkylating agent. We consider this overall number of high quality studies to be fairly extensive evidence of the ability of O-alkylating agents to cause adducts and mutations in germ cells, and mutations in offspring, although no studies were ideally suited to establish the empirical linkages between the KERs. We thus compared results across studies where possible to attempt to do this. All of the studies either used ENU as the primary study compound, or applied ENU as one of the positive controls to assess other alkylating agents. Strong dose-response data for mutations occurring in exposed pre-meiotic germ cells and mutations in offspring are only available for ENU. The other alkylating agents show varying degrees mutagenicity, but single doses were used in most studies. Thus, the evaluation of concordance of the dose-response could only be undertaken with ENU for in vivo germ cell and heritable effects. However, where possible we used information from research on somatic cells to provide additional support for the KERs. In particular, experiments in somatic cells were necessary to assess the involvement of DNA repair in removing adducts and preventing mutations. Overall, we note that the rationale for claiming high confidence in this AOP and its KERs is based primarily on the more influential Bradford Hill consideration of biological plausibility, with decades of research having been done in somatic and germ cells on DNA damage, repair and mutation. Much of the data, then, supporting AOP evaluation derives from historical studies from the 1990’s, with less recent evidence. As noted, a primary motivation for developing this AOP was the recent release of TG 488, and newly available whole generation sequencing methods, which we expect to be increasingly applied. Thus, additional well-designed experiments that dissect the relationships between alkyl adducts, mutations in sperm, and mutations in offspring to assess essentiality and empirical support are expected in the future through application of these improved approaches. Below we describe each KE and KER in detail, using the wiki entries as a guide to the order of presentation and the content described.

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 relevant exclusively to mature males and their pre-meiotic germ cells. Although not considered in this AOP, progenitor germ cells from earlier life stages may also be susceptible to induced mutations from alkylating agents, which could then be transmitted to offspring after sexual maturity. Relevant endpoints have been characterized across different taxa: (1) alkyl adduct levels in this AOP were from hamsters, mice and rats; (2) repair of alkylated DNA has been studied in prokaryotes to higher eukaryotes, including human cells in culture (while there are differences across taxa, all species have some DNA repair systems in place and it is common to extrapolate conclusions across eukaryotic species); (3) mutations in male germ cells were measured in mice and fish; and (4) mutations in offspring were measured in Drosophila, Japanese Medaka and mice. Quite generally, the AOP applies to any species that produces sperm. The similarity in spermatogenesis and in DNA repair of alkyl adducts is well documented across rodents and humans (Adler 1996). Heritable mutations are the basis of evolution and occur in every species. That mutations in sperm are transmitted to offspring in humans is best demonstrated by studies exploring the effects of ageing. Significant increases are observed in the amount of DNA damage and mutation as human males age (reviewed in Paul and Robaire 2013). Similarly, increased incidence of single nucleotide mutations and microsatellite mutation in the offspring of ageing fathers has recently been measured by advanced genomics technologies (Kong et al. 2012; Sun et al. 2012). Lifestyle factors including smoking and lower income brackets in human fathers in associated with increased minisatellite mutations in their offspring (LinSchooten et al., 2013).

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

Essentiality was not directly tested for all of the KEs. The MIE cannot be ‘blocked’ in any way to our knowledge (e.g., as you might block a receptor-binding MIE). However, as described in the KERs, enhanced DNA repair of alkylated DNA reduces mutation frequencies and reduction in repair increases mutation frequencies, supporting the essentiality of KE1 (i.e., moderate support). Correct repair of the alkylated DNA (i.e., a block of KE1) will not lead to mutation. For example, MGMT overexpression protects mgt1 mutant yeast against alkylation-induced mutation (Xiao and Fontanie 1995). In addition, Big Blue® mice over-expressing human AGT exhibit greatly reduced O6-methylguanine-mediated lacI and K-ras mutations in the thymus following treatment with MNU (Allay et al. 1999) relative to wild type Big Blue® mice. Insufficient DNA repair is well-established to lead to mutations. In addition, inactivation of MGMT sensitizes cells to alkylation-induced mutagenesis resulting in an increased number of mutations per adduct (Thomas et al. 2013).

The remainder of the AOP requires transmission of mutations in sperm to offspring. There are no means to study the essentiality of mutations in sperm. Once mutations occur in male pre-meiotic germ cells, they cannot be removed to observe whether occurrence in offspring is decreased. In addition, mutations that occur in stem cells are propagated clonally and can become fixed in the spermatogonial cell population. Thus, waiting a longer period of time, or removing the exposure, is not effective in causing a decline in the mutation frequency. Therefore, the essentiality of this KE is inferred by the biology of the pathway and cannot be addressed directly with experimental evidence.

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 of the KERs: Strong. There is extensive understanding of the ability of alkylating agents to cause DNA adducts, the requirement for overcoming DNA repair, and the resulting mutations that arise in both somatic and germ cells. It is established that exposure to alkylating agents produced mutations in germ cells – ENU is used in genetic screening to produce mutations to derive new phenotypes for research.

Empirical support for the KERs: Across the KERs the degree of support ranges from weak to strong (File:AssessmentSummaryAop-15.pdf - Table II). Support from somatic cells in culture contributes to moderate calls for the relationships between adduct formation, insufficient DNA repair and mutation. The weak call is based on lack of empirical data to support that mutations in germ cells are transmitted to offspring. However, increased mutation frequencies in germ cells occur following exposure to the same types of chemicals that cause increased mutations in the offspring. It should be noted that biological plausibility for this KER is strong as it is based on understanding of molecular biology and evolution. The strongest support is associated with the indirect KER linking alkylation of DNA to mutation in germ cells (KER4). This is primarily based on extensive evidence in both somatic and germ cells demonstrating that chemicals that alkylate DNA cause mutations, that alkyl adducts occur at a greater incidence than mutations at matching doses, and that alkyl adducts precede mutations. In somatic cells, work has been done on many different chemicals, whereas the germ cell data were primarily for the chemical ENU (but data were also available for a few select other chemicals) (File:AssessmentSummaryAop-15.pdf - Table I, Figure 2). In addition, data are available for multiple species to support this indirect KER. There is a large degree of consistency in the germ cell literature to show that a variety of O-alkylating agents cause male germ cell mutations in many species (Drosophila, fish and rodent) and that these effects occur at many mutational loci (e.g., mutations in genes that are inherited measured with the Specific Locus Test, sperm mutations in tandem repeat DNA sequences, tandem repeat mutations in offspring, transgene mutations in sperm). Many alkylating agents have been tested to show that they create adducts in male rodent germ cells (e.g., DEN, ENU, EMS, DES), mutations in male mouse germ cells (ENU, IPMS and MNU) and mutations in the offspring of exposed male mice (ENU, MNU and IPMS). In summary, we consider the overall empirical data supporting the AOP to be MODERATE (the median call). Rank order (provided in the overall assessment Table - File:AssessmentSummaryAop-15.pdf):

Rank order of the KERs and the weight of evidence for the essentiality all point to the overall weight of evidence for this AOP as strong. Biological plausibility is strong for all KERs, with primarily moderate evidence for KER linkages and relatively few uncertainties or inconsistencies.

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

As described above, it is established that alkyl adducts, mutations in spermatogonia and mutations in offspring all increase with dose in a manner that is consistent with the AOP. Alkylation must exceed a threshold (determined by saturation of the relevant DNA repair pathways) before alkyl DNA lesions persist, and mutations subsequently begin to occur. However, the precise quantitative relationship has not been modeled. Existing data published in the literature could be mined to do this and thresholds for specific adduct types (i.e., estimates of how many adducts are needed to cause a mutation in a gene on average) have been published for certain cell types, which should theoretically correlate with germ cell mutagenicity for ENU and other alkylating agents.

The quantitative relationship between mutations in sperm and mutations in the offspring has not been determined and will be locus- and mutation-type specific (e.g., stronger selection against coding mutations than non-coding mutations, which will influence transmission probability); however, although many mutations will lead to embryonic loss, a large subset of mutations is expected to be heritable and viable. It is expected that quantitative understanding of this relationship will increase as advanced single cell sequencing technologies are more developed to query mutations in sperm versus offspring. For non-coding sites (e.g., transgenic reporter genes and non-coding DNA like tandem repeats), the relationship is expected to approach 1:1.

Overall, the variables that could be used to predict whether a heritable mutation is probable following exposure to an alkylating agent are the number and types of adducts per nucleotide (and knowledge of their repair efficiency). Generally, the probability of a mutation occurring is highly dependent on the type of adduct formed (mutagenicity of the adduct is based on repair efficiency and probability of error-free replication over the lesion) and abundance of the adducts, and could be modeled using existing published data.

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 information provided in this AOP will provide context for understanding how to interpret new data produced from the rodent transgene mutation assay applied to sperm (OECD TG 488) [OECD 2013], which is being increasingly applied, as well as data produced using tandem repeat mutation assays. In addition, it is envisioned that next generation sequencing technologies will enable the analysis of germ cell mutations in human populations and the eventual discovery of human germ cell mutagens. It is important to note that the regulation of chemicals that can induce heritable effects has, to date, been based heavily on extrapolation from somatic cell data. Although regulatory agencies around the world have policies in place for germ cell mutagens, risk management based on an agent that is classified as a germ cell mutagen has not yet occurred because of lack of solid evidence that these exist. This AOP demonstrates strong evidence to support the existence of male rodent germ cell mutagens, supported by data in other species (fish, flies, birds), and strongly implies that such mutagens will also affect human germ cells.

References

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

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Kong, A., M.L. Frigge, G. Masson, S. Besenbacher, P. Sulem, G. Magnusson, S.A. Gudjonsson, A. Sigurdsson, A. Jonasdottir, W.S. Wong, G. Sigurdsson, G.B. Walters, S. Steinberg, H. Helgason, G. Thorleifsson, D.F. Gudbjartsson, A. Helgason, O.T. Magnusson, U. Thorsteinsdottir and K. Stefansson (2012), "Rate of de novo mutations and the importance of father's age to disease risk", Nature, 488(7412): 471-475.

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Linschooten, J.O., N. Verhofstad, K. Gutzkow, A.K. Olsen, C. Yauk, Y. Oligschläger, G. Brunborg, F.J. van Schooten and R.W. Godschalk (2013), “Paternal lifestyle as a potential source of germline mutations transmitted to offspring”, FASEB J, 27: 2873-28749. Paul C, Robaire B. 2013. Ageing of the male germ line. Nat Rev Urol 10(4):227-234.

McLaughlin, H.M., R. Sakaguchi, C. Liu, T. Igarashi, D. Pehlivan, K. Chu, R. Iyer, P. Cruz, P.F. Cherukuri, N.F. Hansen, J.C. Mullikin, Program NCS, L.G. Biesecker, T.E. Wilson, V. Ionasescu, G. Nicholson, C. Searby, K. Talbot, J.M. Vance, S. Zuchner, K. Szigeti, J.R. Lupski, Y.M. Hou, E.D. Green and A. Antonellis (2010), "Compound heterozygosity for loss-of-function lysyl-tRNA synthetase mutations in a patient with peripheral neuropathy", Am. J. Hum. Genet., 87(4): 560-566.

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O'Roak, B.J., L. Vives, S. Girirajan, E. Karakoc, N. Krumm, B.P. Coe, R. Levy, A. Ko, C. Lee, J.D. Smith, E.H. Turner, I.B. Stanaway, B. Vernot, M. Malig, C. Baker, B. Reilly, J.M. Akey, E. Borenstein, M.J. Rieder, D.A. Nickerson, R. Bernier, J. Shendure and E.E. Eichler (2012), "Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations", Nature, 485(7397): 246-250.

Roach, J.C., G. Glusman, A.F. Smit, C.D. Huff, R. Hubley, P.T. Shannon, L. Rowen, K.P. Pant, N. Goodman, M. Bamshad, J. Shendure, R. Drmanac, L.B. Jorde, L. Hood, D.J. Galas (2010), "Analysis of genetic inheritance in a family quartet by whole-genome sequencing", Science, 328(5978): 636-639.

Sun, J.X., A. Helgason, G. Masson, S.S. Ebenesersdottir, H. Li, S. Mallick, S. Gnerre, N. Patterson, A. Kong, D. Reich and K. Stefansson (2012), "A direct characterization of human mutation based on microsatellites", Nature Genetics, 44(10): 1161-1165.

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Vissers, L.E., J. de Ligt, C. Gilissen, I. Janssen, M. Steehouwer, P. de Vries, B. van Lier, P. Arts, N. Wieskamp, M. del Rosario, B.W. van Bon, A. Hoischen, B.B. de Vries, H.G. Brunner, J.A. Veltman (2010), "A de novo paradigm for mental retardation", Nature Genetics, 42(12): 1109-1112.

Yauk C.L., Aardema, M.J., Benthem, J., Bishop, J.B., Dearfield, K.L., DeMarini, D.M., Dubrova, Y.E., Honma, M., Lupski, J.R., Marchetti, F., Meistrich, M.L., Pacchierotti, F., Stewart, J., Waters, M.D., Douglas, G.R. (2013), "Approaches for identifying germ cell mutagens: Report of the 2013 IWGT workshop on germ cell assays", "Mutation Research Genetic Toxicolology and Environmental Mutagenesis", 783: 36-54.

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