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Relationship: 23


The title of the KER should clearly define the two KEs being considered and the sequential relationship between them (i.e., which is upstream and which is downstream). Consequently all KER titles take the form “upstream KE leads to downstream KE”.  More help

Alkylation, DNA leads to Increase, Heritable mutations in offspring

Upstream event
Upstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help
Downstream event
Downstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes. Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

This table is automatically generated upon addition of a KER to an AOP. All of the AOPs that are linked to this KER will automatically be listed in this subsection. Clicking on the name of the AOP in the table will bring you to the individual page for that AOP. More help
AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Alkylation of DNA in male pre-meiotic germ cells leading to heritable mutations non-adjacent High Moderate Carole Yauk (send email) Open for citation & comment WPHA/WNT Endorsed

Taxonomic Applicability

Select one or more structured terms that help to define the biological applicability domain of the KER. In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER. Authors can indicate the relevant taxa for this KER in this subsection. The process is similar to what is described for KEs (see pages 30-31 and 37-38 of User Handbook) More help
Term Scientific Term Evidence Link
mouse Mus musculus High NCBI
Drosophila melanogaster Drosophila melanogaster Moderate NCBI

Sex Applicability

Authors can indicate the relevant sex for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of the User Handbook). More help

Life Stage Applicability

Authors can indicate the relevant life stage for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of User Handbook). More help

Key Event Relationship Description

Provide a brief, descriptive summation of the KER. While the title itself is fairly descriptive, this section can provide details that aren’t inherent in the description of the KEs themselves (see page 39 of the User Handbook). This description section can be viewed as providing the increased specificity in the nature of upstream perturbation (KEupstream) that leads to a particular downstream perturbation (KEdownstream), while allowing the KE descriptions to remain generalised so they can be linked to different AOPs. The description is also intended to provide a concise overview for readers who may want a brief summation, without needing to read through the detailed support for the relationship (covered below). Careful attention should be taken to avoid reference to other KEs that are not part of this KER, other KERs or other AOPs. This will ensure that the KER is modular and can be used by other AOPs. More help

Pre-meiotic male germ cells are outside of the blood-testis barrier and thus are exposed if there is systemic distribution. Exposure of pre-meiotic male germ cells to DNA alkylating agents results in DNA alkyl adducts. Replication of DNA with alkyl adducts thus can cause mutations in these cells. Fertilization of an egg by sperm containing mutations causes an increase in the number of mutations that are transmitted to their offspring.

Evidence Supporting this KER

Assembly and description of the scientific evidence supporting KERs in an AOP is an important step in the AOP development process that sets the stage for overall assessment of the AOP (see pages 49-56 of the User Handbook). To do this, biological plausibility, empirical support, and the current quantitative understanding of the KER are evaluated with regard to the predictive relationships/associations between defined pairs of KEs as a basis for considering WoE (page 55 of User Handbook). In addition, uncertainties and inconsistencies are considered. More help
Biological Plausibility
Define, in free text, the biological rationale for a connection between KEupstream and KEdownstream. What are the structural or functional relationships between the KEs? For example, there is a functional relationship between an enzyme’s activity and the product of a reaction it catalyses. Supporting references should be included. However, it is recognised that there may be cases where the biological relationship between two KEs is very well established, to the extent that it is widely accepted and consistently supported by so much literature that it is unnecessary and impractical to cite the relevant primary literature. Citation of review articles or other secondary sources, like text books, may be reasonable in such cases. The primary intent is to provide scientifically credible support for the structural and/or functional relationship between the pair of KEs if one is known. The description of biological plausibility can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured (see page 40 of the User Handbook for further information).   More help

Alkylating agents are prototypical mutagens in laboratory animals. It is established that these agents, especially those chemicals that preferentially cause O-alkylation in DNA, induce heritable mutations. ENU (N-ethyl-N-nitrosourea) is a prototypical agent used to derive offspring with de novo mutations inherited from exposed males (e.g., In fact, ENU mutagenicity is a standard bench tool for genetic screens used to identify new mutations associated with a phenotype of interest.

A variety of alkylating agents are positive in the mouse specific locus test demonstrating that they cause heritable mutations in offspring as a result of exposure of pre-meiotic male germ cells. These agents include ENU, methyl nitrosourea (MNU), procarbazine and melphalan. This has been thoroughly reviewed by Marchetti and Wyrobek (2005) and Witt and Bishop (1996). It should be noted that procarbazine and melphalan predominantly cause N-alkyl adducts and yield a weaker response in the specific locus test assay in male pre-meiotic germs (these agents yield higher responses in post-meiotic stages of spermatogenesis).

Uncertainties and Inconsistencies
In addition to outlining the evidence supporting a particular linkage, it is also important to identify inconsistencies or uncertainties in the relationship. Additionally, while there are expected patterns of concordance that support a causal linkage between the KEs in the pair, it is also helpful to identify experimental details that may explain apparent deviations from the expected patterns of concordance. Identification of uncertainties and inconsistencies contribute to evaluation of the overall WoE supporting the AOPs that contain a given KER and to the identification of research gaps that warrant investigation (seep pages 41-42 of the User Handbook).Given that AOPs are intended to support regulatory applications, AOP developers should focus on those inconsistencies or gaps that would have a direct bearing or impact on the confidence in the KER and its use as a basis for inference or extrapolation in a regulatory setting. Uncertainties that may be of academic interest but would have little impact on regulatory application don’t need to be described. In general, this section details evidence that may raise questions regarding the overall validity and predictive utility of the KER (including consideration of both biological plausibility and empirical support). It also contributes along with several other elements to the overall evaluation of the WoE for the KER (see Section 4 of the User Handbook).  More help

As described above, not all alkylating agents cause heritable mutations as a result of mutations arising in spermatogonia. O-alkylation is critical, and the size of the alkyl group is important, with ENU exhibiting an order of magnitude greater response than MNU. Although there are no inconsistencies based on knowledge of the spectrum of adducts expected for specific alkylating agents, the database on which this KER is assessed is nearly exclusively centered on ENU. Moreover, a key data gap includes evidence of the effect of alkylating agents in the offspring of exposed humans.

Very little data are available on exposed humans despite the fact that humans may be exposed to high doses of alkylating agents during chemotherapy. Thus far the evidence has not supported that the cancer treatments pose heritable mutagenic hazards based on assessment of cancer (Madanat-Harjuoja et al., 2011), minisatellite mutations (Tawn et al., 2013) and congenital anomalies (Signorello et al., 2012) in offspring, or minisatellite mutation analysis in sperm ( Zheng et al., 2000; Armour et al., 199). However, cancer therapies are complex combinations of drugs that include agents that generally induce N-alkylation rather than O-alkylation. It has been suggested that the search for human germ cell mutagens has been flawed by lack of appropriate power, focus on the wrong agents, and using the wrong tools (DeMarini, 2012).

Response-response Relationship
This subsection should be used to define sources of data that define the response-response relationships between the KEs. In particular, information regarding the general form of the relationship (e.g., linear, exponential, sigmoidal, threshold, etc.) should be captured if possible. If there are specific mathematical functions or computational models relevant to the KER in question that have been defined, those should also be cited and/or described where possible, along with information concerning the approximate range of certainty with which the state of the KEdownstream can be predicted based on the measured state of the KEupstream (i.e., can it be predicted within a factor of two, or within three orders of magnitude?). For example, a regression equation may reasonably describe the response-response relationship between the two KERs, but that relationship may have only been validated/tested in a single species under steady state exposure conditions. Those types of details would be useful to capture.  More help
This sub-section should be used to provide information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). This can be useful information both in terms of modelling the KER, as well as for analyzing the critical or dominant paths through an AOP network (e.g., identification of an AO that could kill an organism in a matter of hours will generally be of higher priority than other potential AOs that take weeks or months to develop). Identification of time-scale can also aid the assessment of temporal concordance. For example, for a KER that operates on a time-scale of days, measurement of both KEs after just hours of exposure in a short-term experiment could lead to incorrect conclusions regarding dose-response or temporal concordance if the time-scale of the upstream to downstream transition was not considered. More help
Known modulating factors
This sub-section presents information regarding modulating factors/variables known to alter the shape of the response-response function that describes the quantitative relationship between the two KEs (for example, an iodine deficient diet causes a significant increase in the slope of the relationship; a particular genotype doubles the sensitivity of KEdownstream to changes in KEupstream). Information on these known modulating factors should be listed in this subsection, along with relevant information regarding the manner in which the modulating factor can be expected to alter the relationship (if known). Note, this section should focus on those modulating factors for which solid evidence supported by relevant data and literature is available. It should NOT list all possible/plausible modulating factors. In this regard, it is useful to bear in mind that many risk assessments conducted through conventional apical guideline testing-based approaches generally consider few if any modulating factors. More help
Known Feedforward/Feedback loops influencing this KER
This subsection should define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits? In some cases where feedback processes are measurable and causally linked to the outcome, they should be represented as KEs. However, in most cases these features are expected to predominantly influence the shape of the response-response, time-course, behaviours between selected KEs. For example, if a feedback loop acts as compensatory mechanism that aims to restore homeostasis following initial perturbation of a KE, the feedback loop will directly shape the response-response relationship between the KERs. Given interest in formally identifying these positive or negative feedback, it is recommended that a graphical annotation (page 44) indicating a positive or negative feedback loop is involved in a particular upstream to downstream KE transition (KER) be added to the graphical representation, and that details be provided in this subsection of the KER description (see pages 44-45 of the User Handbook).  More help

Domain of Applicability

As for the KEs, there is also a free-text section of the KER description that the developer can use to explain his/her rationale for the structured terms selected with regard to taxonomic, life stage, or sex applicability, or provide a more generalizable or nuanced description of the applicability domain than may be feasible using standardized terms. More help

That alkylation of DNA causes heritable mutations has been demonstrated specifically in flies, fish, and rodents. However, it is assumed that alkylating agents would act broadly on virtually any DNA sequence, in any organism, in any cell type. Thus, as long as the species has male germ cells, this KER would be relevant to that species.


List of the literature that was cited for this KER description using the appropriate format. Ideally, the list of references should conform, to the extent possible, with the OECD Style Guide (OECD, 2015). More help

Armour, J.A., M.H. Brinkworth and A. Kamischke (1999), "Direct analysis by small-pool PCR of MS205 minisatellite mutation rates in sperm after mutagenic therapies", Mutat. Res., 445(1): 73-80.

Demarini, D.M. (2012), "Declaring the existence of human germ-cell mutagens", Environ. Mol. Mutagen., 53(3): 166-172.

Dubrova, Y.E., P. Hickenbotham, C.D. Glen, K. Monger, H.P. Wong and R.C. Barber (2008), "Paternal exposure to ethylnitrosourea results in transgenerational genomic instability in mice", Environ. Mol. Mutagen., 49(4): 308-311.

Ehling, U.H. and A. Neuhäuser-Klaus (1991), "Induction of specific-locus and dominant lethal mutations in male mice by 1-methyl-1-nitrosourea (MNU)", Mutat. Res., 250(1-2): 447-456.

Favor, J. (1986), "The frequency of dominant cataract and recessive specific-locus mutations in mice derived from 80 or 160 mg ethylnitrosourea per kg body weight treated spermatogonia." 'Mutat. Res., 162(1): 69-80.

Favor, J., M. Sund, A. Neuhauser-Klaus and U.H. Ehling (1990), "A dose-response analysis of ethylnitrosourea-induced recessive specific-locus mutations in treated spermatogonia of the mouse", 'Mutat. Res., 231(1): 47-54.

Favor, J., A. Neuhäuser-Klaus, U.H. Ehling, A. Wulff and A.A. van Zeeland (1997), "The effect of the interval between dose applications on the observed specific-locus mutation rate in the mouse following fractionated treatments of spermatogonia with ethylnitrosourea", 'Mutat. Res., 374(2): 193-199.

Lewis, S.E., L.B. Barnett, B.M. Sadler and M.D. Shelby (1991), "ENU mutagenesis in the mouse electrophoretic specific-locus test, 1. Dose-response relationship of electrophoretically-detected mutations arising from mouse spermatogonia treated with ethylnitrosourea", 'Mutat. Res., 249(2): 311-315.

Madanat-Harjuoja, L.M., N. Malila, P. Lähteenmäki, E. Pukkala, J.J. Mulvihill, J.D. Boice Jr and R. Sankila (2010), "Risk of cancer among children of cancer patients - a nationwide study in Finland," Int. J. Cancer, 126(5): 1196-1205.

Marchetti, F. and A.J. Wyrobek (2005), "Mechanisms and consequences of paternally-transmitted chromosomal abnormalities", Birth Defects Res C Embryo Today, 75(2): 112-129.

Nagao, T. (1987), "Frequency of congenital defects and dominant lethals in the offspring of male mice treated with methylnitrosourea", 'Mutat. Res., 177(1): 171-178.

Russell, W.L., E.M. Kelly, P.R. Hunsicker, J.W. Bangham, S.C. Maddux and E.L. Phipps (1979), "Specific-locus test shows ethylnitrosourea to be the most potent mutagen in the mouse", Proc. Natl. Acad. Sci. USA, 76(11): 5818-5819.

Russell, W.L., P.R. Hunsicker, G.D. Raymer, M.H. Steele, K.F. Stelzner and H.M. Thompson HM (1982), "Dose-response curve for ethylnitrosourea-induced specific-locus mutations in mouse spermatogonia", Proc. Natl. Acad. Sci. USA, 79(11): 3589-3591.

Russell, L.B. (2004), "Effects of male germ-cell stage on the frequency, nature, and spectrum of induced specific-locus mutations in the mouse", Genetica, 122(1): 25-36.

Russell, L.B., P.R. Hunsicker and W.L. Russell (2007), "Comparison of the genetic effects of equimolar doses of ENU and MNU: while the chemicals differ dramatically in their mutagenicity in stem-cell spermatogonia, both elicit very high mutation rates in differentiating spermatogonia", 'Mutat. Res., 616(1-2): 181-195.

Selby, P.B., V.S. Earhart, E.M. Garrison and G. Douglas Raymer (2004), "Tests of induction in mice by acute and chronic ionizing radiation and ethylnitrosourea of dominant mutations that cause the more common skeletal anomalies", 'Mutat. Res., 545(1-2): 81-107.

Signorello, L.B., J.J. Mulvihill, D.M. Green, H.M. Munro, M. Stovall, R.E. Weathers, A.C. Mertens, J.A. Whitton, L.L. Robison and J.D. Boice Jr. (2012), "Congenital anomalies in the children of cancer survivors: a report from the childhood cancer survivor study", J. Clin. Oncol., 30(3): 239-245.

Shima, A. and A. Shimada (1994), "The Japanese medaka, Oryzias latipes, as a new model organism for studying environmental germ-cell mutagenesis", Environ. Health Perspect., 102 Suppl 12: 33-35.

Tosal, L., M.A. Comendador and L.M. Sierra (1998), "N-ethyl-N-nitrosourea predominantly induces mutations at AT base pairs in pre-meiotic germ cells of Drosophila males", Mutagenesis, 13(4): 375-380.

Van Zeeland, A.A., A. de Groot and A. Neuhauser-Klaus (1990), "DNA adduct formation in mouse testis by ethylating agents: a comparison with germ cell mutagenesis", 'Mutat. Res., 231(1): 55-62.

Vilarino-Guell, C., A.G. Smith and Y.E. Dubrova (2003), "Germline mutation induction at mouse repeat DNA loci by chemical mutagens", 'Mutat. Res., 526(1-2): 63-73.

Witt, K.L. and J.B. Bishop (1996), "Mutagenicity of anticancer drugs in mammalian germ cells", 'Mutat. Res., 355(1-2): 209-234.

Zheng, N., D.G. Monckton, G. Wilson, F. Hagemeister, R. Chakraborty, T.H. Connor, M.J. Siciliano, M.L. Meistrich (2000), "Frequency of minisatellite repeat number changes at the MS205 locus in human sperm before and after cancer chemotherapy", Environ. Mol. Mutagen., 36(2): 134-145.