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Relationship: 1897


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, DNA Damage 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
Increased reactive oxygen and nitrogen species (RONS) leading to increased risk of breast cancer adjacent High Not Specified Jessica Helm (send email) Under development: Not open for comment. Do not cite Under Development
Increased DNA damage leading to increased risk of breast cancer adjacent High Not Specified Jessica Helm (send email) Under development: Not open for comment. Do not cite Under Development

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

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

Mutations occur in one of two major ways: incorporation of an incorrect nucleotide leading to a point mutation, and incorrect rejoining of a double strand break leading to a deletion or other sequence change, homozygosity, or chromosomal damage. Mutations in surviving cells are then propagated to daughter 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 is High. DNA damage in the form of nucleotide damage, single strand and double strand breaks, and complex damage can generate mutations, particularly when a damaged cell undergoes replication.

Empirical Support is High. It is generally accepted that DNA damage leads to mutations. Empirical support comes in part from the observation that agents which increase DNA damage also cause mutations, that DNA damage precedes the appearance of mutations, and that interventions that reduce DNA damage also reduce mutations. None of the identified studies measure both outcomes over the same range of time points. This constitutes a readily addressable data gap.

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

High. DNA damage in the form of nucleotide damage, single strand and double strand breaks, and complex damage can generate mutations, particularly when a damaged cell undergoes replication.

Nucleotide damage

Damage to single nucleotides can generate mutations. Oxidative damage and ionizing radiation can induce a range of base lesions, but guanine is particularly vulnerable because of its low redox potential (David, O'Shea et al. 2007). Repair is generally accurate, but generates single strand breaks. Repair processes can also insert an incorrect nucleotide where a lesion has been excised. If not corrected by mismatch repair processes before a replication cycle, an incorrect base is matched with its pair and is made permanent (Tubbs and Nussenzweig 2017). In a cell undergoing replication, the replication fork typically stalls at a lesion until repairs are complete, but translesion synthesis allows the replication fork to proceed at the cost of increased errors, or mutations (Abbotts and Wilson 2017). Different lesions vary in their frequency and ability to escape repair or be replicated and incorrectly paired by DNA polymerase, making some lesions more mutagenic than others. For example, guanine lesion 8-oxoguanine is very common, so although it is efficiently repaired it contributes to guanine mutations. Other guanine lesions including Fapy and hydantoins are less common but very mutagenic, so likely also contribute to guanine mutations (Neeley and Essigmann 2006; David, O'Shea et al. 2007). Thymine glycol is another common oxidative lesion formed from thymine that can also generate mutations.

Single strand breaks

Single strand breaks are generally repaired efficiently through a variant of the base excision repair pathway. However, replication fork collapse can occur when the replisome encounters an unrepaired single strand break, resulting in a double strand break (Kuzminov 2001).

Double strand breaks

Double strand breaks can generate mutations ranging from point mutations to inversions, deletions, duplications, and chromosomal gaps, breaks, and micronuclei. Double strand breaks can be repaired via two to three major pathways depending on damage type and cell stage among other conditions, and the mutation type and frequency depends on the repair mechanism employed.

Double strand breaks generated from the stalling or collapse of replication forks around lesions or single strand break are processed using homologous recombination (HR) (Rothkamm and Lobrich 2003; Ceccaldi, Rondinelli et al. 2016). Because these breaks happen during replication, an identical sister chromatid may be present to use as a template and repair can restore the original sequence. However, HR can also occur using a non-sister chromatid or in the case of repeated regions can use another stretch of DNA as a template, resulting in loss of homozygosity, inversions, deletions, and duplications (Saleh-Gohari, Bryant et al. 2005; Shrivastav, De Haro et al. 2008). HR may also increase point mutations (Shrivastav, De Haro et al. 2008).

Double strand breaks occurring in all parts of the cell cycle may be processed by non-homologous end joining (NHEJ) (Rothkamm and Lobrich 2003), which can alter the nucleotide sequence of the two broken ends to achieve a fusible template leading to point mutations, deletions, and insertions (Ceccaldi, Rondinelli et al. 2016). NHEJ can fuse incorrect ends within or between chromosomes, resulting in major changes including translocations, deletions, inversions, and duplications. Compared with HR, NHEJ is considered to be more likely to generate mutations, particular the resection dependent classical or alternative end joining pathways (Ceccaldi, Rondinelli et al. 2016).

Complex damage

Complex damage delays repair and increases double strand breaks, increasing the likelihood of mutation. Clustered lesions or single strand breaks are processed more slowly than non-clustered lesions, increasing the number of lesions that will undergo replication and potentially generate mutations in daughter cells (Dianov, Timchenko et al. 1991; Eccles, O'Neill et al. 2011). Clustered damage made of closely opposed lesions and/or single strand breaks can also create double strand breaks (Chaudhry and Weinfeld 1997; Vispe and Satoh 2000; Yang, Galick et al. 2004; Schipler and Iliakis 2013; Sharma, Collins et al. 2016; Shiraishi, Shikazono et al. 2017). Complex damage involving double strand breaks is also repaired more slowly (Stenerlow, Hoglund et al. 2000; Schipler and Iliakis 2013; Lorat, Timm et al. 2016), and undergoes a form of NHEJ with excision that leads to increased translocations and deletions (Eccles, O'Neill et al. 2011; Sharma, Collins et al. 2016; Watts 2016).

Genomic Instability/Long term effects

Genomic instability is the prolonged appearance of DNA damage, chromosomal damage, and mutations. It is sometimes seen following agents that induce DNA damage including ionizing radiation, RONS, and NMU (Goepfert, Moreno-Smith et al. 2007; Kadhim, Salomaa et al. 2013; Stanicka, Russell et al. 2015). DNA damage occurring during genomic instability is associated with the appearance of mutations including deletions, inversions, and duplications (Murnane 2012; Kadhim, Salomaa et al. 2013; Sishc, Nelson et al. 2015).

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

Despite the generally accepted relationship between DNA damage and mutations, few studies uncovered in the literature for RONS or ionizing radiation measure both DNA damage and mutations in the same study (Denissova, Nasello et al. 2012; Sharma, Collins et al. 2016; Biehs, Steinlage et al. 2017) and none measure both key events at the same time points.

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

Mutations generally increase linearly with dose of DNA damaging agents (Sandhu and Birnboim 1997; Sharma, Collins et al. 2016), but multiple factors including DNA repair, bystander effects, and genomic instability can affect the shape of the dose-response. IR promotion of DNA repair mechanisms decrease major mutations (lethal recessive changes) at lower IR doses/dose rates in flies (0.2 Gy at 0.05 Gy/min gamma) (Koana and Tsujimura 2010). In contrast, non-targeted effects of IR contribute to supralinear responses at lower doses (Sandhu and Birnboim 1997; Hall and Hei 2003; Yang, Anzenberg et al. 2007). At higher doses (10-80 Gy) rearrangements from misrejoining (joining together of non-sequential DNA) increase linearly with dose for high LET IR, but supralinearly for low LET IR, attributed to the increase in the concentration and complexity of double strand breaks with LET  (Rydberg, Cooper et al. 2005).

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


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

Abbotts, R. and D. M. Wilson, 3rd (2017). "Coordination of DNA single strand break repair." Free radical biology & medicine 107: 228-244.

Biehs, R., M. Steinlage, et al. (2017). "DNA Double-Strand Break Resection Occurs during Non-homologous End Joining in G1 but Is Distinct from Resection during Homologous Recombination." Molecular cell 65(4): 671-684 e675.

Buonanno, M., S. M. de Toledo, et al. (2011). "Long-term consequences of radiation-induced bystander effects depend on radiation quality and dose and correlate with oxidative stress." Radiation research 175(4): 405-415.

Ceccaldi, R., B. Rondinelli, et al. (2016). "Repair Pathway Choices and Consequences at the Double-Strand Break." Trends in cell biology 26(1): 52-64.

Chaudhry, M. A. and M. Weinfeld (1997). "Reactivity of human apurinic/apyrimidinic endonuclease and Escherichia coli exonuclease III with bistranded abasic sites in DNA." The Journal of biological chemistry 272(25): 15650-15655.

Choi, K. M., C. M. Kang, et al. (2007). "Ionizing radiation-induced micronucleus formation is mediated by reactive oxygen species that are produced in a manner dependent on mitochondria, Nox1, and JNK." Oncol Rep 17(5): 1183-1188.

David, S. S., V. L. O'Shea, et al. (2007). "Base-excision repair of oxidative DNA damage." Nature 447(7147): 941-950.

Dayal, D., S. M. Martin, et al. (2008). "Hydrogen peroxide mediates the radiation-induced mutator phenotype in mammalian cells." Biochem J 413(1): 185-191.

Denissova, N. G., C. M. Nasello, et al. (2012). "Resveratrol protects mouse embryonic stem cells from ionizing radiation by accelerating recovery from DNA strand breakage." Carcinogenesis 33(1): 149-155.

Dianov, G. L., T. V. Timchenko, et al. (1991). "Repair of uracil residues closely spaced on the opposite strands of plasmid DNA results in double-strand break and deletion formation." Molecular & general genetics : MGG 225(3): 448-452.

Du, C., Z. Gao, et al. (2009). "Mitochondrial ROS and radiation induced transformation in mouse embryonic fibroblasts." Cancer Biol Ther 8(20): 1962-1971.

Eccles, L. J., P. O'Neill, et al. (2011). "Delayed repair of radiation induced clustered DNA damage: friend or foe?" Mutation research 711(1-2): 134-141.

Fetisova, E. K., M. M. Antoschina, et al. (2015). "Radioprotective effects of mitochondria-targeted antioxidant SkQR1." Radiation research 183(1): 64-71.

Goepfert, T. M., M. Moreno-Smith, et al. (2007). "Loss of chromosomal integrity drives rat mammary tumorigenesis." Int J Cancer 120(5): 985-994.

Hall, E. J. and T. K. Hei (2003). "Genomic instability and bystander effects induced by high-LET radiation." Oncogene 22(45): 7034-7042.

Jones, J. A., P. K. Riggs, et al. (2007). "Ionizing radiation-induced bioeffects in space and strategies to reduce cellular injury and carcinogenesis." Aviat Space Environ Med 78(4 Suppl): A67-78.

Kadhim, M., S. Salomaa, et al. (2013). "Non-targeted effects of ionising radiation--implications for low dose risk." Mutation research 752(2): 84-98.

Koana, T. and H. Tsujimura (2010). "A U-shaped dose-response relationship between x radiation and sex-linked recessive lethal mutation in male germ cells of Drosophila." Radiation research 174(1): 46-51.

Kuhne, M., K. Rothkamm, et al. (2000). "No dose-dependence of DNA double-strand break misrejoining following alpha-particle irradiation." International journal of radiation biology 76(7): 891-900.

Kuzminov, A. (2001). "Single-strand interruptions in replicating chromosomes cause double-strand breaks." Proceedings of the National Academy of Sciences of the United States of America 98(15): 8241-8246.

Lorat, Y., S. Timm, et al. (2016). "Clustered double-strand breaks in heterochromatin perturb DNA repair after high linear energy transfer irradiation." Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology 121(1): 154-161.

Murnane, J. P. (2012). "Telomere dysfunction and chromosome instability." Mutation research 730(1-2): 28-36.

Neeley, W. L. and J. M. Essigmann (2006). "Mechanisms of formation, genotoxicity, and mutation of guanine oxidation products." Chemical research in toxicology 19(4): 491-505.

Padula, G., M. V. Ponzinibbio, et al. (2016). "Possible radioprotective effect of folic acid supplementation on low dose ionizing radiation-induced genomic instability in vitro." Indian J Exp Biol 54(8): 537-543.

Patil, S. L., N. B. Rao, et al. (2014). "Antigenotoxic potential of rutin and quercetin in Swiss mice exposed to gamma radiation." Biomed J 37(5): 305-313.

Rothkamm, K. and M. Lobrich (2003). "Evidence for a lack of DNA double-strand break repair in human cells exposed to very low x-ray doses." Proceedings of the National Academy of Sciences of the United States of America 100(9): 5057-5062.

Rydberg, B., B. Cooper, et al. (2005). "Dose-dependent misrejoining of radiation-induced DNA double-strand breaks in human fibroblasts: experimental and theoretical study for high- and low-LET radiation." Radiation research 163(5): 526-534.

Saleh-Gohari, N., H. E. Bryant, et al. (2005). "Spontaneous homologous recombination is induced by collapsed replication forks that are caused by endogenous DNA single-strand breaks." Molecular and cellular biology 25(16): 7158-7169.

Sandhu, J. K. and H. C. Birnboim (1997). "Mutagenicity and cytotoxicity of reactive oxygen and nitrogen species in the MN-11 murine tumor cell line." Mutation research 379(2): 241-252.

Schiestl, R. H., F. Khogali, et al. (1994). "Reversion of the mouse pink-eyed unstable mutation induced by low doses of x-rays." Science 266(5190): 1573-1576.

Schipler, A. and G. Iliakis (2013). "DNA double-strand-break complexity levels and their possible contributions to the probability for error-prone processing and repair pathway choice." Nucleic acids research 41(16): 7589-7605.

Seager, A. L., U. K. Shah, et al. (2012). "Pro-oxidant induced DNA damage in human lymphoblastoid cells: homeostatic mechanisms of genotoxic tolerance." Toxicological sciences : an official journal of the Society of Toxicology 128(2): 387-397.

Sharma, V., L. B. Collins, et al. (2016). "Oxidative stress at low levels can induce clustered DNA lesions leading to NHEJ mediated mutations." Oncotarget 7(18): 25377-25390.

Shiraishi, I., N. Shikazono, et al. (2017). "Efficiency of radiation-induced base lesion excision and the order of enzymatic treatment." International journal of radiation biology 93(3): 295-302.

Shrivastav, M., L. P. De Haro, et al. (2008). "Regulation of DNA double-strand break repair pathway choice." Cell Res 18(1): 134-147.

Sishc, B. J., C. B. Nelson, et al. (2015). "Telomeres and Telomerase in the Radiation Response: Implications for Instability, Reprograming, and Carcinogenesis." Front Oncol 5: 257.

Stanicka, J., E. G. Russell, et al. (2015). "NADPH oxidase-generated hydrogen peroxide induces DNA damage in mutant FLT3-expressing leukemia cells." The Journal of biological chemistry 290(15): 9348-9361.

Stenerlow, B., E. Hoglund, et al. (2000). "Rejoining of DNA fragments produced by radiations of different linear energy transfer." International journal of radiation biology 76(4): 549-557.

Suzuki, K., G. Kashino, et al. (2009). "Long-term persistence of X-ray-induced genomic instability in quiescent normal human diploid cells." Mutation research 671(1-2): 33-39.

Tubbs, A. and A. Nussenzweig (2017). "Endogenous DNA Damage as a Source of Genomic Instability in Cancer." Cell 168(4): 644-656.

Vispe, S. and M. S. Satoh (2000). "DNA repair patch-mediated double strand DNA break formation in human cells." The Journal of biological chemistry 275(35): 27386-27392.

Watts, F. Z. (2016). "Repair of DNA Double-Strand Breaks in Heterochromatin." Biomolecules 6(4).

Yang, H., V. Anzenberg, et al. (2007). "The time dependence of bystander responses induced by iron-ion radiation in normal human skin fibroblasts." Radiation research 168(3): 292-298.

Yang, H., N. Asaad, et al. (2005). "Medium-mediated intercellular communication is involved in bystander responses of X-ray-irradiated normal human fibroblasts." Oncogene 24(12): 2096-2103.

Yang, N., H. Galick, et al. (2004). "Attempted base excision repair of ionizing radiation damage in human lymphoblastoid cells produces lethal and mutagenic double strand breaks." DNA repair 3(10): 1323-1334.