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Relationship: 202

Title

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

Increase, Mutations 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 adjacent High Moderate Evgeniia Kazymova (send email) Open for citation & comment TFHA/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
human Homo sapiens High 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

If a mutation arises in spermatogonial stem cells and does not influence cellular function, the mutation can become fixed and/or propagated within the stem cell population. Mutations that do not affect sperm maturation will persist through the succeeding stages of spermatogenesis and will be found in the mature sperm of the organism throughout its reproductive lifespan. Mutations can also occur in differentiating spermatogonia; however, once the sperm generated by these dividing spermatogonia are ejaculated there will be no ‘record’ of the induced mutation. Mutations that impair spermatogenesis or the viability of the cell will be lost via apoptosis and cell death, potentially contributing to decreased fertility. Mutations that do not impact sperm motility, morphology or ability to penetrate the zona pellucida (or other important sperm parameters), and that are present in mature sperm, may be transmitted to the egg resulting in the development of an offspring with a mutation. Thus, increased incidence of mutations in germ cells leads to increased incidence of mutations in the offspring. There is a great deal of evidence demonstrating that exposure to a variety of DNA alkylating agents induces mutations in male spermatogenic cells.

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

Evolution requires heritable mutations that are transmitted to offspring via parental gametes. This is the primary mechanism by which an offspring would have a sequence variant in every single one of its cells that is not found in its parents. Indeed, as stated in a recent review in Science by Shendura and Aikey "Germline mutations are the principal cause of heritable disease and the ultimate source of evolutionary change." Thus, this KER is supported by substantive understanding of genetics and evolution, with heritable germ cell mutations forming the basis for the selective evolution of species.

In addition, in toxicology, a large body of literature demonstrates that exposure to specific genotoxic chemicals during pre-meiotic stages of spermatogenesis leads to mutations in both the sperm and the offspring, supporting that mutations occurring in sperm fertilize the egg and result in offspring with mutations (reviewed in Demarini 2012; Marchetti and Wyrobek 2005; Yauk et al. 2012). Indeed, ENU is used as a tool in genetics to create offspring carrying mutations for the purposes of understanding gene function ( e.g., http://www.riken.jp/en/research/labs/brc/mutagen_genom). In these studies, male mice are mutagenized by exposure to ENU and mated to females. The offspring of these males have a much higher incidence of mutation; the function of new mutations occurring in genes in these offspring is used to study gene function.

Thus, overall this KER is biologically plausible and widely understood.

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

There are no inconsistencies in the data for this KER, although the data are limited. There is a possibility that mutations can arise in the early embryo instead of in the spermatogenic cells. However, given the study designs for this type of work (where > 42 days pass prior to sperm collection or mating – see OECD TG488 for the time-series required for transgene mutation analysis in sperm), it is unlikely that this contributes significantly. Limitations in technology currently prevent the analyses required to describe the incidence of mutations in sperm versus offspring, but this is a future research direction. It should be noted that the locations and types of mutations would influence the probably of transmission; this relationship has not been confirmed empirically and limits extrapolation across studies applying different endpoints.

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
Time-scale
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

Mutation is the underlying source of evolution and occurs in every species. Theoretically, any sexually reproducing organism (i.e., producing gametes) can acquire mutations in their gametes and transmit these to descendants. Thus, the present KER is relevant to any species producing sperm.

References

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

Barnett, L.B., R.W. Tyl, B.S. Shane, M.D. Shelby and S.E. Lewis (2002), "Transmission of mutations in the lacI transgene to the offspring of ENU-treated Big Blue male mice", Environ. Mol. Mutagen., 40(4): 251-257.

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.

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.

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 K. (2012), "Rate of de novo mutations and the importance of father's age to disease risk", Nature, 488(7412): 471-475.

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.

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.

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.

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.

O'Brien, J.M., A. Williams, J. Gingerich, G.R. Douglas, F. Marchetti and C.L. Yauk (2013), "No evidence for transgenerational genomic instability in the F1 or F2 descendants of Muta™Mouse males exposed to N-ethyl-N-nitrosourea", Mutat Res., 741-742:11-7

Paul,C. and B. Robaire (2013), "Ageing of the male germ line", Nat. Rev. Urol., 10(4): 227-234.

Shendura, J. and M. Akey (2015), "The origins, determinants, and consequences of human mutations", Science, 349(6255): 1478-1483.

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", Nat. Genet., 44(10): 1161-1165.

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.

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.

Yauk, C.L., Y.E. Dubrova, G.R. Grant and A.J. Jeffreys (2002), "A novel single molecule analysis of spontaneous and radiation-induced mutation at a mouse tandem repeat locus", Mutat Res., 500(1-2): 147-156.

Yauk, C.L., L.J. Argueso, S.S. Auerbach, P. Awadalla, S.R. Davis, D.M. Demarini, G.R. Douglas, Y.E. Dubrova, R.K. Elespuru, T.M. Glover, B.F. Hales , M.E. Hurles, C.B. Klein, J.R. Lupski, D.K. Manchester, F. Marchetti, A. Montpetit, J.J. Mulvihill, B. Robaire, W.A. Robbins, G.A. Rouleau, D.T. Shaughnessy, C.M. Somers, J.G. Taylor 6th, J. Trasler, M.D. Waters, T.E. Wilson, K.L. Witt and J.B. Bishop (2013), "Harnessing genomics to identify environmental determinants of heritable disease" Mutation Research, 752(1): 6-9.