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Relationship: 25


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, Mutations

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 Evgeniia Kazymova (send email) Open for citation & comment TFHA/WNT Endorsed
Alkylation of DNA leading to cancer 1 non-adjacent High Moderate Arthur Author (send email) Open for adoption

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
medaka Oryzias latipes 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

Alkylated DNA may be ‘misread’ during DNA replication, leading to insertion of incorrect nucleotides. Upon replication, these changes become fixed as mutations. Subsequent replication propagates these mutations to daughter cells. Mutations in stem cells are of the greatest concern, as these will persist throughout the organism’s lifetime. Thus, increased mutations will be found in the cells of organisms that possess alkylated DNA.

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 can cause a variety of adducts and DNA damage (e.g., alkali labile sites, DNA strand breaks, etc.) that are potentially mutagenic and clastogenic. This KER focuses on the probability that an alkyl DNA adduct will lead to a mutation.

Not all adducts are equally mutagenic. Very generally, chemicals that preferentially cause O-alkylation in DNA induce DNA sequence changes, whereas chemicals that cause N-alkylation of DNA are more efficient inducers of structural chromosomal aberrations (reviewed in Beranek 1990). Indeed, a review of the biological significance of N7 alkyl-guanine adducts concluded that these adducts simply be used to confirm exposure to target tissue (Boysen et al., 2009), because the vast majority of studies shows that these adducts do not cause mispairing. A variety of work has demonstrated that N7-alkylguanine adducts can be bypassed essentially error free (e.g., Philippin et al., 2014; Shrivastav et al., 2010). Moreover, alkylation can involve modification with different sizes of alkylation groups (e.g., methyl, ethyl, propyl). Although response to these is qualitatively similar with respect to the key events, in general, larger alkylating groups tend to be more mutagenic (Beranek, 1990). It is widely known that chemicals that preferentially cause O-alkylation in DNA induce mutations. ENU (N-ethyl-N-nitrosourea) is a prototypical O-alkylating agent and the most studied male germ cell mutagen.

Alkylating agents are prototypical somatic and male germ cell mutagens.

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 alkyl adducts are mutagenic. The proportion of oxygen-alkylation and the type of mutation (with ethylation > methylation) will govern mutagenicity, but there are few empirical data to support this. There are no inconsistencies or uncertainties for ENU or iPMS; other alkylating agents (EMS, MMS) have yielded some discrepancies in the transgenic rodent mutation assay. However, the experimental protocols applied were sub-standard (the OECD TG for this analysis was revised and published in 2013). Overall, more work is needed on alkylating agents other than ENU to fill important data gaps.

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

Alkylating agents are well-established to cause mutation in virtually any cell type in any organism.


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

Beranek, D.T. (1990), "Distribution of methyl and ethyl adducts following alkylation with monofunctional alkylating agents", Mutation Research, 231(1): 11-30.

Boysena, G., B.F. Pachkowski, J. Nakamura and J.A. Swenberg (2009), "The formation and biological significance of N7-guanine adducts", Mutation Research, 678: 76–94.

Brooks, T.M. and S.W. Dean (1997), "The detection of gene mutation in the tubular sperm of Muta Mice following a single intraperitoneal treatment with methyl methanesulphonate or ethylnitrosourea", Mutat. Res., 388(2-3): 219-222.

Douglas, G.R., J. Jiao, J.D. Gingerich, J.A. Gossen and L.M. Soper (1995), "Temporal and molecular characteristics of mutations induced by ethylnitrosourea in germ cells isolated from seminiferous tubules and in spermatozoa of lacZ transgenic mice", Proc. Natl. Acad. Sci. USA, 92(16): 7485-7489.

Katoh, M., N. Horiya and R.P. Valdivia (1997), "Mutations induced in male germ cells after treatment of transgenic mice with ethylnitrosourea", Mutat Res. 1997 Feb 14;388(2-3):229-37.

Katoh, M., T. Inomata, N. Horiya, F. Suzuki, T. Shida, K. Ishioka and T. Shibuya (1997), "Studies on mutations in male germ cells of transgenic mice following exposure to isopropyl methanesulfonate, ethylnitrosourea or X-ray", Mutat. Res., 388(2-3):213-8.

Liegibel, U.M. and P. Schmezer (1994), "Detection of the two germ cell mutagens ENU and iPMS using the LacZ/transgenic mouse mutation assay" Mutat. Res., 341(1):17-28.

Mattison, J.D., L.B. Penrose and B. Burlinson (1997), "Preliminary results of ethylnitrosourea, isopropyl methanesulphonate and methyl methanesulphonate activity in the testis and epididymal spermatozoa of Muta Mice", Mutat. Res. 388(2-3): 123-7.

Mientjes, E.J., K. Hochleitner, A. Luiten-Schuite, J.H. van Delft, J. Thomale, F. Berends, M.F. Rajewsky, P.H. Lohman and R.A. Baan (1996), "Formation and persistence of O6-ethylguanine in genomic and transgene DNA in liver and brain of lambda(lacZ) transgenic mice treated with N-ethyl-N-nitrosourea", Carcinogenesis, 17(11): 2449-2454.

Mientjes, E.J., A. Luiten-Schuite, E. van der Wolf, Y. Borsboom, A. Bergmans, F. Berends, P.H. Lohman, R.A. Baan RA, J.H. van Delft (1998), "DNA adducts, mutant frequencies, and mutation spectra in various organs of lambda lacZ mice exposed to ethylating agents", Environ. Mol. Mutagen., 31(1): 18-31

Norris, M.B. and R.N. Winn (2010), "Isolated spermatozoa as indicators of mutations transmitted to progeny", Mutat. Res., 688(1-2): 36–40.

Labib, S., C. Yauk, A. Williams, V.M. Arlt, D.H. Phillips, P.A. White and S. Halappanavar (2012)," Subchronic oral exposure to benzo(a)pyrene leads to distinct transcriptomic changes in the lungs that are related to carcinogenesis. Toxicol Sci 129(1):213-224.

Malik, A.I., A. Williams, C.L. Lemieux, P.A. White and C.L. Yauk (2012), "Hepatic mRNA, microRNA, and miR-34a-target responses in mice after 28 days exposure to doses of benzo(a)pyrene that elicit DNA damage and mutation", Environ. Mol. Mutagen., 53(1): 10-21.

Malik, A.I., A. Rowan-Carroll, A. Williams, C.L. Lemieux, A.S. Long, V.M. Arlt, D.H. Phillips, P.A. White and C.L. Yauk (2013), "Hepatic genotoxicity and toxicogenomic responses in MutaMouse males treated with dibenz[a,h]anthracene", Mutagenesis, 28(5): 543-554.

O'Brien, J.M., M.A. Beal, J.D. Gingerich, L. Soper L, G.R. Douglas, C.L. Yauk and F. Marchetti (2014), "Transgenic rodent assay for quantifying male germ cell mutant frequency", J. Vis. Exp., (90): e51576.

O’Brien, J.M., M. Walker, A. Sivathayalan, G.R. Douglas, C.L. Yauk and F. Marchetti (2015), "Sublinear response in lacZ mutant frequency of Muta™ Mouse spermatogonial stem cells after low dose subchronic exposure to N-ethyl-N-nitrosourea", Environ. Mol. Mutagen., 56(4): 347-55.

Renault, D., D. Brault and V. Thybaud (1997), "Effect of ethylnitrosourea and methyl methanesulfonate on mutation frequency in MutaMouse germ cells (seminiferous tubule cells and epididymis spermatozoa)", Mutat. Res., 388(2-3): 145-153.

Shrivastav, N., D. Li and J.M. Essigmann (2010), "Chemical biology of mutagenesis and DNA repair: cellular responses to DNA alkylation", Carcinogenesis, 31(1): 59-70.

Skopek, T.R., K.L. Kort, D.R. Marino, L.V. Mittal, D.R. Umbenhauer, G.M. Laws and S.P. Adams (1996), "Mutagenic response of the endogenous hprt gene and lacI transgene in benzo[a]pyrene-treated Big Blue B6C3F1 mice", Environ. Mol. Mutagen., 28(4): 376-384.

Suzuki, T., S. Itoh, N. Takemoto, N. Yajima, M. Miura, M. Hayashi, H. Shimada and T. Sofuni (1997), "Ethyl nitrosourea and methyl methanesulfonate mutagenicity in sperm and testicular germ cells of lacZ transgenic mice (Muta Mouse)", Mutat. Res., 388(2-3): 155-163.

Swenberg, J.A., E. Fryar-Tita, Y. Jeong, G. Boysen, T. Starr, V.E. Walker and R.J. Albertini (2008), "Biomarkers in toxicology and risk assessment: informing critical dose-response relationships", Chem. Res. Toxicol., 21(1): 253-265.

Swayne, B.G., A. Kawata, N.A. Behan, A. Williams, M.G. Wade, A.J. Macfarlane and C.L. Yauk (2012), "Investigating the effects of dietary folic acid on sperm count, DNA damage and mutation in Balb/c mice", Mutat. Res., 737(1-2): 1-7.

Tinwell, H., P. Lefevre, C.V. Williams and J. Ashby (1997), "The activity of ENU, iPMS and MMS in male mouse germ cells using the Muta Mouse positive selection transgenic mutation assay", Mutat. Res., 388(2-3): 179-185.

van Delft J.H., A. Bergmans and R.A. Baan RA (1997), "Germ-cell mutagenesis in lambda lacZ transgenic mice treated with ethylating and methylating agents: comparison with specific-locus test", Mutat. Res., 388(2-3): 165-173.

van Delft, J.H. and R.A. Baan (1995), "Germ cell mutagenesis in lambda lacZ transgenic mice treated with ethylnitrosourea; comparison with specific-locus test", Mutagenesis, 10(3): 209-214.

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