AOP ID and Title:

Short Title: Deposition of energy leading to cataracts

Authors

Emma Carrothers¹, Meghan Appleby¹, Vita Lai¹, Tatiana Kozbenko¹, Dalya Alomar¹, Benjamin Smith¹, Robyn Hocking³, Carole Yauk², Ruth Wilkins¹, Vinita Chauhan¹ 

 

(1) Consumer and Clinical Radiation Protection Bureau, Environmental and Radiation Health Sciences Directorate, Health Canada, Ottawa, Ontario  

(2) Department of Biology, University of Ottawa, Ottawa, Ontario  

(3) Learning and Knowledge and Library Services, Health Canada, Ottawa, Ontario, Canada 

 

 

Consultants

Nobuyuki Hamada¹, Patricia Hinton², Elizabeth A. Ainsbury³

(1) Biology and Environmental Chemistry Division, Sustainable System Research Laboratory, Central Research Institute of Electric Power Industry (CRIEPI), Komae, Tokyo, Japan

(2) Canadian Forces Environmental Medicine Establishment, Toronto, Ontario, Canada  

(3) Radiation, Chemical and Environmental Hazards Division, UK Health Security Agency, United Kingdom.

Environmental Research Group within the School of Public Health, Faculty of Medicine at Imperial College of Science, Technology and Medicine, London, UK.

Status

Abstract

An AOP was developed describing a simplified path from “deposition of energy” (MIE; KE#1686) to cataracts (AO; KE#2083). The AOP is initiated by deposition of energy resulting in oxidative stress (KE#1392) within cells from increased free radical generation. If this exceeds antioxidant defence mechanisms, the oxidative stress, in turn, can damage molecules, the most well-studied include DNA and proteins.  Within the lens of the eye modified proteins (KE#2081) can aggregate, such as crystalline, and if not eliminated, can accumulate resulting in lens opacity. Concurrently, unmanaged oxidative stress can increase oxidative DNA damage (KE#1634) leading to DNA strand breaks (KE#1635). If these lesions are inadequately repaired (KE#155), an increase mutation frequency (KE#185) in critical genes and chromosomal aberrations (KE#1636) can occur. Mutations in genes associated with cell cycling can lead to uncontrolled cell proliferation (KE#870) of lens epithelial cells and the eventual AO, cataracts. The overall assessment of this AOP indicates high biological plausibility of the KERs as they are well established and understood; moderate levels of evidence support the essentiality and the Bradford-Hill empirical evidence criteria; low weight of evidence was identified for quantitative understanding across adjacent relationships, with some uncertainties and inconsistencies in mechanisms. Broadly, the information presented in this AOP can be used to support the review of radiation effects classification and broadly the system of radiological protection. 

Background

Cataracts, one of the leading causes of blindness, are a progressive condition in which the lens of the eye develops opacities and becomes cloudy, resulting in blurred vision as well as glare and haloes around lights (National Eye Institute, 2022). For this AOP, a cataract is defined when over 5% of the lens is opacified. Cataracts typically occur after the age of 50 in humans, as an age-related disease (Liu et al., 2017); however, progression of this disease can be initiated or accelerated after exposure to a variety of agents, one of which is radiation.  

For radiation induced cataracts, most research shows that the anatomical location is within the posterior sub capsular region of the eye with limited occurrence in the cortical and nuclear region. Available epidemiological evidence confirms a positive statistically significant association between radiation exposure and cataracts (Nakashima et al., 2006; Worgul et al., 2007; Chylack et al., 2012; Little et al., 2018). The data comes from Chernobyl workers, radiologic technologists, and patients exposed to radiation through medical procedures, with the most compelling evidence derived from atomic bomb survivors. Although there is concern for the role of long duration space flight missions in cataract formation, there is limited data from astronauts.  

In 2012, the International Commission on Radiological Protection (ICRP) recommended lowering the occupational eye lens dose limit from 150 mSv per year to an average of 20 mSv, with no single year exceeding 50 mSv. This revision was based on new evidence from both radiobiological studies and relevant epidemiological data. Assessment of the literature indicated a threshold dose for radiation induced cataracts of about 0.5 Gy (ICRP, 2012). This change in exposure limit has led to a need to further understand radiation-induced effects at lower doses and dose-rates. It is believed the progression of cataracts at high  doses and s higher dose-rates generally induce more damage than lower dose-rates (Brooks et al., 2016).

This AOP provides a summary of the relevant studies and endpoints that can inform future research designed to understand the role of radiation in causing cataracts. Assays and study designs spanning biological levels of organization across relevant models were identified, with the end goal to improve testing strategies and understanding in risk from low dose low dose-rate exposures. 

Summary of the AOP

Events

Molecular Initiating Events (MIE), Key Events (KE), Adverse Outcomes (AO)

Key Event Relationships

Stressors

Overall Assessment of the AOP

Summary of evidence (KE & KER relationships and evidence) 

This assessment provides an overview of the pathway. Further details and references can be found in the individual KEs and KERs and within the AOP report. 

Biological Plausibility 

This AOP begins with an MIE (deposition of energy) and then branches to cataract formation either from modified proteins or through DNA damage processes. Ionization events from deposition of energy interact directly or indirectly with the DNA. Indirect damage can also occur when water molecules dissociate producing radicals such as reactive oxygen species (ROS) that induce DNA breaks (Ahmadi et al., 2022). Moreover, a cascade of ionization events can cause the formation of clustered damage (Joiner and van der Kogel, 2009). Many studies use ultraviolet radiation as a stressor, and it is important to note that ionizing and non-ionizing radiation interact through  different mechanisms when inducing cataracts. Ionizing radiation can remove tightly bound electrons from atoms to create charged particles,  but also excite molecules without ionization. The absorption of non-ionizing radiation results in heat generation from molecular vibrations (Alcócer et al., 2020).

Deposition of energy can also lead to high levels of ROS and reactive nitrogen species (RNS) (collectively RONS) (Tangvarasittichai & Tangvarasittichai, 2019). There are several pathways leading to ROS, but radiolysis is the most prominent. Free radicals can combine to produce hydrogen peroxide, hydroxide, superoxide, and hydroxyl (Tian et al., 2017; Venkatesulu et al., 2018). Interactions with NO can also lead to RNS (Wang et al., 2019). Additionally, deposited energy can directly upregulate enzymes involved in reactive RONS production (de Jager et al., 2017). Activation of nicotinamide adenine dinucleotide phosphate (NADPH) oxidase (NOX) within mitochondria can generate more ROS (Soloviev & Kizub, 2019). Energy absorption by an unstable molecule, such as the chromophore NADPH (Jurja et al., 2014), is another route for radical production. Overwhelming amounts of free radicals can decrease antioxidant levels, causing oxidative stress (Wang et al., 2019). 

Protein damage leading to cataracts 

Alongside DNA as a target to energy deposition, other macromolecules can be damaged. In terms of cataracts, there is much evidence to show that protein modifications such as phosphorylation, deamidation, oxidation, disulfide bonds (Hanson et al., 2000), increased cross-linking, altered water-solubility, and increased protein aggregation are critical to disease progression (Fochler & Durchschlag, 1997; Reisz et al., 2014; Wang et al. 2020; Chandrasekher et al., 2004 ). ROS can also cause many alterations including conformational changes, protein cross-link formation, oxidation of amino acid side chains (Uwineza et al., 2019), and protein aggregation (Moreau et al., 2012). For example, alpha crystallin aggregation can be induced by free radicals oxidizing the thiol groups (Cabrera & Chihuailaf, 2011; Moreau & King 2012; Stohs, 1995). Finally, these modified proteins can lead directly to cataracts, the AO. Aggregated proteins cause improper lens epithelial cell (LEC) organization and increases light scattering, therefore resulting in lens opacity (Hamada et al., 2014). Additionally, modifications to connexin protein can lead to improper LEC layering, which has been linked to cataracts in humans (NCRP, 2016).  

DNA damage leading to cataracts 

Oxidative stress is also directly connected to increased DNA strand breaks. Cells under oxidative stress have excessive levels of ROS, molecules that can oxidize and remove nitrogenous bases, producing nicks in the DNA strand known as single strand breaks (SSB). Under circumstances when multiple SSBs are in close proximity, they may combine to form double strand breaks (DSB). Furthermore, these strand breaks and a combination of various DNA abnormalities occurring in close proximity can create complex lesions that are more difficult to repair (Nickoloff et al., 2020). The formation of SSBs induces base excision repair (BER), a DNA repair mechanism; however, cells are often unable to support multiple sites of repair in one area, leading to residual unrepaired SSBs that will increase the number of DSBs. It has been shown that radiation-generated ROS are more likely to produce clustered damage (Cannan & Pederson, 2016). Increased oxidative stress can also lead to increased oxidative DNA damage. In this case, ROS can induce DNA lesions, such as oxidized nucleotides or DNA breaks (Collins, 2014). 

DNA strand breaks can lead to inadequate DNA repair. DSBs, the most detrimental form of this damage (Iliakis et al., 2015), are often formed in the G1 phase of the cell cycle. Cells utilize various systems to repair DNA damage, the most error-prone pathway being non-homologous end-joining (NHEJ). Since NHEJ is an active pathway for DNA DSB repair in the G1 phase of the cell cycle, DSBs are repaired using this pathway, leading to decreased repair accuracy (Jeggo et al., 1998). Although NHEJ is predominantly the preferred repair mechanism throughout the cell cycle, homologous recombination (HR) and single-stranded annealing (SSA) are favored during the S and G2 phases in scenarios where the NHEJ repair pathway is inhibited. The absence of HR leading to an increase in SSA activity is still a matter to debate (Ceccaldi et al., 2016). Furthermore, clustered damage generated by high linear energy transfer radiation (Nikitaki et al., 2016), overwhelms the repair systems, leading to increased probability of inadequate repair (Tsao, 2007). 

Similarly, increased oxidative damage to DNA can also lead to inadequate repair. Repair systems are unable to deal with increased levels of lesions within a small area, resulting in decreased repair ability and therefore, inadequate repair (Georgakilas et al., 2013). Moreover, unrepaired oxidative lesions may be incorrectly bypassed during DNA replication, leading to the insertion of incorrect bases opposite unrepaired lesions (Shah et al., 2018). Imbalances between the level of oxidative DNA lesions and cellular repair capacity can also lead to inadequate repair (Brenerman et al., 2014). Non-DSB oxidative DNA damage can alter nuclease or glycosylase activity, resulting in decreased local DNA repair ability (Georgakilas et al., 2013). 

One of the possible outcomes of inadequate repair is increased mutations. DNA repair mechanisms, such as NHEJ (Sishc & Davis, 2017), break-induced replication (BIR), and microhomology-mediated break-induced replication (MMBIR) can be error-prone, leading to increased mutagenesis and genomic instability (Kramara et al., 2018). 

Inadequate repair can also lead to increased chromosomal aberrations (CA). The best-known model for this KER holds that unrepaired DSBs eventually lead to CAs (Schipler & Iliakis, 2013). Alternate models suggests that CAs occur when the enzymes responsible for binding DNA strands during the repair of enzyme-induced DNA breaks dysfunctions. Failure of different binding enzymes would lead to different forms of CAs (Bignold, 2009).  

Increased mutations and increased CAs are both linked to increased cell proliferation; however, as no lens-specific data was found, the existing relationships in the Wiki (KER: 1978 and 1979) have not been altered. This presents a possible focus for future research. 

Finally, increased cell proliferation of the metabolically active LECs can lead to cataracts. The lens is composed of several zones, with the germinative zone (GZ) being the only one that is mitotically active. In healthy lenses, cells in the GZ replicate and differentiate into lens fiber cells (LFCs). The LFCs are organelle-free, allowing light to pass through the lens. However, in cases of increased proliferation, cells are forced out of the GZ before forming fully differentiated LFCs. These improperly differentiated cells have not lost all of their organelles, resulting in reduced lens transparency (Ainsbury et al., 2016; Hamada, 2017; McCarron et al., 2022). As the lens is a closed system with little turnover, these cells are not removed, and their accumulation contributes to the cataractogenic load, a gradual lens opacification throughout life, which can eventually lead to cataracts (Ainsbury et al., 2016; Uwineza et al., 2019).  

Time- and dose- and incidence-concordance 

Overall evidence of time- and dose-concordance is moderate to low throughout the AOP. Certain relationships, particularly those directly connected with deposition of energy, are well supported with measurable changes in expression in a temporal and dose concordant manner. However, KEs at the cellular and organ level are generally supported by a weaker WOE with inconsistencies. The use of different models, time-points and radiation types across studies may be the reason for inconsistencies.  

Evidence of time concordance is demonstrated by the occurrence of upstream KEs at earlier timepoints than the downstream KEs. Time concordance involving deposition of energy is well supported by studies showing the deposition of energy followed by downstream changes later in a time course. Studies using in vitro and in vivo models have found downstream effects occurring within minutes to years of the MIE. For example, oxidative stress in human LECs can occur within an hour following 0.25 Gy γ-rays exposure (Ahmadi et al., 2022), while it may take months to years for cataract development under radiotherapy or space radiation exposure (Gragoudas et al., 1995; Cucinotta et al., 2001). However, cellular and organ level events are not well-studied to demonstrate consistent time concordance.  

Studies in the AOP provide evidence of upstream KEs observed at the same doses or lower doses as the downstream KEs. The KERs directly involving the deposition of energy contain  the most evidence for dose concordance. Downstream KERs have limited support for dose concordance in a lens model but are supported with evidence from other cell types.  

A few studies demonstrate greater changes produced by the upstream KE than the downstream KE following a stressor (incidence concordance). One KER showing incidence concordance is oxidative stress to DNA strand breaks. For example, there was a 5x increase of DNA strand breaks, while only a ~1.4-fold increase in oxidative stress marker in human LECs (Liu et al., 2013a).   

Domain of Applicability

Life Stage Applicability Taxonomic Applicability Sex Applicability

Overall, this AOP is applicable to all organisms with DNA that require a clear lens for vision. Of these, Homo sapiens (humans), Mus musculus (mice), and Rattus norvegicus (rats) had a moderate level of support, and Oryctolagus cuniculus (rabbits) had a low level of support throughout most of the pathway. However, portions of the pathway were also supported in Bos taurus (bovine), Sus scrofa (pigs), Cavia porcellus (guinea pigs), Sciurus linnaeus (squirrels), Macaca mulatta (monkeys) and Anura (frogs).  

This AOP is also applicable to all life stages, with a moderate level of support. However, it should also be noted that cataracts are primarily an age-related disease, generally occurring in humans after the age of 50 (Liu et al., 2017). As such, older organisms are at a higher risk of radiation-induced cataracts, as a gradual opacification of the lens may have already begun. 

Essentiality of the Key Events

The present AOP encompasses several notable uncertainties.  

1. There is no objective, universally acknowledged, definition for cataracts. A large variety of cataract scoring systems are used, with the major ones being the Lens Opacities Classification System I, II, and III (LOC I, II, and III), and the Merriam-Focht Cataract Scoring System. However, they are all subjective, relying partly on the examiner’s judgement.  

2. Many studies do not directly measure cataracts, instead measuring indirect indicators, such as minor opacities, that do not always progress into cataracts.  

3. Observation periods used in many studies may be too short to account for cataract development, leading to an apparent decrease in cataract prevalence.  

4. Certain KERs, such as increased oxidative stress to increased oxidative DNA damage, increased oxidative stress to increased DNA strand breaks, increased oxidative stress to modified proteins, modified proteins to cataracts, inadequate DNA repair to cataracts, increased oxidative stress to cataracts, and deposition of energy to increased cell proliferation are only weakly supported by empirical evidence.  

5. KERs describing increased oxidative DNA damage to inadequate DNA repair, inadequate DNA repair to increased mutations, inadequate DNA repair to increased chromosomal aberrations, and increased oxidative DNA damage to increased DNA strand breaks, while supported by non-lens evidence, are not supported by lens-based studies. 

6.  The use of different assays to assess KEs can result in diverse quantitative interpretations of data.

Essentiality of the Key Events 

Essentiality of the Deposition of Energy (MIE#1686) 

• Radiation exposure increases levels of DNA strand breaks (Reddy et al., 1998; Barnard et al., 2019; Barnard et al., 2021), modified proteins (Zigman et al., 1975; Abdelkawi et al., 2008; Anbaraki et al., 2016), oxidative stress (Zigman et al., 1995; Zigman et al., 2000; Kubo et al., 2010; Ahmadi et al., 2022), oxidative DNA damage (Pendergrass et al., 2010; Bahia et al., 2018), chromosomal aberrations (Dalke et al., 2018; Bains et al., 2019; Udroiu et al., 2020), cell proliferation (Pirie & Drance, 1959; Markiewicz et al., 2015; Bahia et al., 2018), and cataracts (Worgul et al., 1993; Jones et al., 2007; Kocer et al., 2007) above background levels. Removing/reducing the amount of radiation decreases the amount of damage to macromolecules found within the cell. 

Essentiality of Increased Oxidative Damage to DNA (KE#1634) 

• Depletion of antioxidant removing enzymes reduces oxidative DNA damage and initiate adequate repair mechanisms (Mesa & Bassnett, 2013) and increases DNA breaks (Domijan et al., 2006). 

Essentiality of Increased DNA Strand Breaks (KE#1635) 

• It is difficult to demonstrate the essentiality of increased DNA strand breaks as there are no modulators that can alter the KE and show effects to inadequate repair. However, it has been indirectly demonstrated that knock-out of mechanism related to repair processes can lead to increased strand breaks.  

Essentiality of Inadequate DNA Repair (KE#155) 

• The essentiality of inadequate DNA repair can be assessed through knock-out studies examining the effect of altering important repair genes on downstream KEs. In this way, inadequate DNA repair has been found to be essential in increasing mutations (Perera et al., 2016), chromosomal aberrations (Wilhelm et al., 2014), and cataracts (Kleiman et al., 2007) above background levels. For example, cataracts are up to 90% more common in ATM mutant mice, which have decreased DNA repair, compared to wild type mice (Worgul et al., 2002). 

Essentiality of Increased Mutations (KE#185) 

• The essentiality of this KE has been assessed as part of other AOPs, as described in the overall assessment of AOP #272. However, there was no available data from eye lens models to demonstrate the essentiality of this KE and show the effects on downstream KEs. 

Essentiality of Increased Chromosomal Aberrations (KE#1636) 

• The essentiality of this KE has been assessed as part of other AOPs, as described in the overall assessment of AOP #272. However, there was no available data from eye lens models to demonstrate the essentiality of this KE and show the effects on downstream KEs. 

Essentiality of Increased Cell Proliferation (KE#870) 

• There is a moderate level of evidence supporting the essentiality of increased cell proliferation. Mice with decreased cell proliferation (Ptch1) have lower lens opacity compared to wild-type mice (McCarron et al., 2021) and vice versa (De Stefano et al., 2021). 

Essentiality of Oxidative Stress (KE#1392) 

• Oxidative stress causes an increase in levels of DNA strand breaks (Li et al., 1998; Liu et al., 2013b; Cencer et al., 2018; Ahmadi et al., 2022) and cataract indicators (Karslioǧlu et al., 2005; Varma et al., 2011; Liu et al., 2013b; Qin et al., 2019) above background levels. Additionally, inhibition of oxidative stress reduces DNA strand breaks (Spector et al., 1997; Liu et al., 2013b) and cataract risk (Van Kuijk, 1991; Spector, 1995; Smith et al., 2016; Qin et al., 2019). 

Essentiality of Modified Proteins (KE#2081) 

• There is a low level of evidence supporting the essentiality of radiation in promoting modified proteins above a normal level. One study found that return of the lens protein solubility ratio to near control levels resulted in decreased lens opacity (Menard et al., 1986). 

Weight of Evidence Summary

1. Support for Biological Plausibility	Defining Question	High	Moderate	Low
	Is there a mechanistic relationship between KEup and KEdown consistent with established biological knowledge?	Extensive understanding of the KER based on extensive previous documentation and broad acceptance.	KER is plausible based on analogy to accepted biological relationships, but scientific understanding is incomplete	Empirical support for association between  KEs, but the structural or functional relationship between them is not understood.
MIE#1686→ KE#1635:  Deposition of energy → Increase DNA strand breaks	High  It is well established that deposition of energy can cause various types of DNA damage including SSBs and DSBs. Structural damage from the deposited energy can induce chemical modifications in the form of breaks to the phosphodiester backbone of both strands of the DNA. DSBs are also often formed by indirect interactions with radiation through water radiolysis and subsequent reactive oxygen species generation that can then damage the DNA.
MIE#1686→ KE#2081:   Deposition of Energy → Modified Proteins	High  It is well established that the deposition of energy leads to protein modifications. Energy deposited into cells, results in proteins undergoing post-translational modifications. These modifications culminate into larger protein changes such as high molecular weight aggregates and water-insolubility.
MIE#1686→ KE#1392:  Deposition of Energy → Oxidative Stress	High  When deposited energy reaches a cell it reacts with water and organic materials to produce free radicals such as ROS. If the ROS cannot be eliminated quickly and efficiently enough by the cell’s defense system, oxidative stress ensues.
KE#1392→ KE#1634: Oxidative Stress →Increase Oxidative DNA Damage	High  There is a large amount of evidence supporting the mechanistic relationship between increased oxidative stress and increased oxidative DNA damage. ROS react with DNA, causing changes such as DNA-protein cross-links, inter and intra-strand links, tandem base lesions, single and double strand breaks, abasic sites, and oxidized bases. The most common and best-studied lesion is 8-oxodG.
KE#1392→ KE#1635:   Oxidative Stress → Increase, DNA Strand Breaks	High  There is a strong understanding of the mechanistic relationship between increased oxidative stress leading to increased DNA strand breaks. ROS oxidize bases on the DNA strand, triggering base excision repair, which removes the altered bases. These altered bases are usually adenine and guanine, as they have the lowest oxidation potentials. When multiple bases in close proximity are removed, the repair efforts cause strain which can lead to strand breaks. Increased levels of ROS have also been linked to DNA strand fragmentation. Furthermore, decreased antioxidant levels have also been linked to increased DNA strand damage.
KE#1392→ KE#2081: Oxidative Stress → Modified Proteins	High  There is high evidence to support increased oxidative stress leading to modified proteins. Studies show that following increases in ROS, proteins undergo cross-linking, thiol group oxidation, increased disulfide bonds, and amino acid oxidation and carbonylation. The increased amount of inter-protein linkages leads to aggregation, insolubility, and reduced chaperone action.
KE#1634→ KE#155: Increase, Oxidative DNA Damage → Inadequate DNA Repair	High There is a risk of increased genomic instability and mutation potential associated with repairing the lesions. The high-risk area can become resistant to repair when non-DSB oxidative DNA damage results in altered nuclease or glycosylase activity. There are limited data from eye lens models to support this relationship. However, this KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #296.
KE#1635→ KE#155: Increase DNA strand breaks → Inadequate DNA repair	High It is well recognized that almost all types of DNA lesions will result in recruitment of repair enzymes and factors to the site of damage, and the pathway involved in the repair of DSBs has been well-documented in a number of reviews, many of which also discuss the error-prone nature of DNA repair. Error-prone repair processes are particularly important when DSBs are biologically induced and repaired during V(D)J recombination of developing lymphocytes and during meiotic divisions to generate gametes.
KE#155→ KE#185: Inadequate DNA Repair → Increase, Mutations	High This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #272.  However, there was no available data from eye lens models to support this relationship.
KE#155→ KE#1636: Inadequate DNA Repair → Increase, Chromosomal Aberrations	High There is low support for the biological plausibility of this relationship in lens cells; however, the relationship is well supported in other cell types. One of the repair mechanisms most commonly used for DSBs is NHEJ, which is error-prone and can lead to CAs.
MIE#1686→ KE#1634: Deposition of energy → Increase oxidative DNA damage	High  A large body of evidence supports the biological plausibility of this KER. The deposition of energy produces ROS, which then overwhelms the cell’s defense mechanisms and induces a state of oxidative stress, leading to increases in oxidative DNA damage. For energy such as  ultraviolet (UV), a form of electromagnetic radiation, this process occurs through the MAPK pathway.
MIE#1686→ KE#1636: Deposition of energy → Increase chromosomal aberrations	High Extensive and diverse data from human, animal and in vitro-based studies show ionizing radiation induces a rich variety of chromosomal aberrations. The mechanism leading from deposition of energy to chromosomal aberrations has been described in several reviews. Other evidence is derived from studies examining the mechanism of copy number variant formation and induction of radiation-induced chromothripsis.
MIE#1686→ KE#870: Deposition of Energy → Increase, Cell Proliferation	Moderate There is moderate available information to support the mechanistic relationship between energy deposition to increase cell proliferation. Energy deposited onto cells causes increased cell proliferation via the combined efforts of oncogene activation, tumor suppressor deactivation, and upregulated signaling pathways.
MIE#1686→ KE#2083: Deposition of Energy → Cataracts	High  It is well understood that the deposition of radiation energy leads to cataract development. It has been clearly shown that radiation affects lenses structurally. These structural changes can be characterized by the measurement of lens opacification. Opacification may be the result of uncontrolled cell proliferation due to overwhelming DNA damages and conformational alteration in lens crystallin proteins. However, the effect of radiation on the functionality of lenses is uncertain, since adverse effects of opacification on vision are largely dependent on the proportion and location of the opacification. Whether minor opacification progress into vision-impairing cataracts is also uncertain.
KE#2081→ KE#2083: Modified Proteins → Cataracts	High  It is well understood that the alteration of proteins leads to the development of cataracts/increased lens opacity. Changes in protein confirmation leads to aggregation, altering the ability of light to pass to the lens and leading to opaque regions within the eye. Protein alterations also result in the loss of protein functionality, which prevents repair and causes structural disorganization of lens proteins and loss of transparency and eventual cataracts.
KE#155→ KE#2083: Inadequate DNA Repair → Cataracts	Moderate   There is moderate evidence to support inadequate DNA repair leading to the development of cataracts. Poor DNA repair leads to aberrant lens fiber cell differentiation, contributing to light scattering and cataracts.
KE#1392→ KE#2083: Oxidative stress → Cataracts	High   There is a large amount of evidence for the biological plausibility of increases in oxidative stress leading to cataracts. This includes various different pathways such as protein oxidation, lipid peroxidation, increased calcium levels, DNA damage, apoptosis, and gap junction damage. The best-studied pathway, through increased protein oxidation, results in increased protein cross-linking, leading to decreased protein solubility, increased protein aggregation, increased light scattering, and therefore increased lens opacity and cataract occurrence.
KE#870→ KE#2083:   Increase, Cell Proliferation → Cataracts	Moderate  There is biological plausibility support for the relation between increased cell proliferation and cataracts. Since the lens is a closed system with little turnover, the increased proliferation of the metabolically active LECs can result in cataracts. Gradual lens opacification and eventual cataract development can result from the improperly differentiated and proliferating cells that are not removed from the system.
KE#1634→ KE#1635: Increase, Oxidative DNA Damage → Increase, DNA Strand Breaks	Moderate   There is moderate support for the biological plausibility of this relationship, the mechanism is generally understood. Findings include guanine and adenine being the most likely bases to be damaged, and clustered oxidized bases raise the risk of strand breaks.
2. Support for Essentiality of KEs	Defining Question	High	Moderate	Low
	Are downstream KEs and/or the AO prevented if an upstream KE is blocked?	Direct evidence from specifically designed experimental studies illustrating essentiality for at least one of the important KEs	Indirect evidence that sufficient modification of an expected modulating factor attenuates or augments a KE	No or contradictory experimental evidence of the essentiality of any of the KEs.
MIE#1686: Deposition of energy	High  Radiation exposure has been found to increase levels of DNA strand breaks, modified proteins, oxidative stress, oxidative DNA damage, chromosomal aberrations, cell proliferation, and cataracts above background levels. Removing the amount of radiation decreases the amount of damage to macromolecules found within the cell.
KE#1634: Increase, oxidative damage to DNA	Moderate  Depletion of antioxidant removing enzymes can reduce oxidative DNA damage and initiate adequate repair mechanisms and increased DNA breaks.
KE#1635: Increase, DNA strand breaks	Low  The essentiality of increased DNA strand breaks is difficult to demonstrate as there are no modulators that can alter the KE and show effects to inadequate repair.  However, indirectly, it has been shown that knock-out of mechanism related to repair processes can lead to increased strand breaks.
KE#155: Inadequate DNA repair	High  The essentiality of inadequate DNA repair can be assessed through knock-out studies examining the effect of altering important repair genes on downstream KEs. In this way, inadequate DNA repair has been found to be essential in increasing mutations, chromosomal aberrations, and cataracts above background levels.
KE#870: Increase, cell proliferation	Moderate  There is a moderate level of evidence supporting the essentiality of increased cell proliferation leading to cataracts.  Under homeostatic conditions, cells duplicate at a rate set by the speed of the cell cycle. Any disruption in regulators of the cell cycle can result in cellular transformation. Cell proliferation rates can be altered via deposited energy-induced genetic alterations, signaling pathway activation, and increased production of growth factors.
KE#1392: Oxidative stress	Moderate  Oxidative stress increases levels of DNA strand breaks above background levels. Inhibition of oxidative stress through the use of antioxidants reduces DNA strand breaks.
KE#2081: Modified proteins	Low  There is a low level of evidence supporting the essentiality of radiation in promoting modified proteins above a normal level.

 

 

3. Empirical Support for KERs	Defining Question	High	Moderate	Low
	Does empirical evidence support that a change in KEup leads to an appropriate change in KEdown?     Does KEup occur at lower doses and earlier time points than KE down and is the incidence of KEup> than that for KEdown?     Inconsistencies?	Multiple studies showing dependent change in both events following exposure to a wide range of specific stressors.     No or few critical data gaps or conflicting data	Demonstrated dependent change in both events following exposure to a small number of stressors.     Some inconsistencies with expected pattern that can be explained by various factors.	Limited or no studies reporting dependent change in both events following exposure to a specific stressor; and/or significant inconsistencies in empirical support across taxa and species that don’t align with hypothesized AOP
MIE#1686→ KE#1635:  Deposition of energy → Increase DNA strand breaks	High   There is a high level of empirical evidence to support the relationship between energy deposition and increased DNA strand breaks. The evidence collected to support this relationship was gathered from various in vitro and in vivo studies. Various stressors were applied, including X-rays, gamma rays, protons and photons. The studies supported a dose and time concordance between the deposition of energy and DNA strand breaks.
MIE#1686→ KE#2081:   Deposition of Energy → Modified Proteins	Low   There are a number of studies to support a dose response between energy deposition and protein modification, but no time response data. Evidence suggests that in vitro and in vivo model exposure to higher (>2 Gy) doses and long UV exposures can initiate protein modification.
MIE#1686→ KE#1392:  Deposition of Energy → Oxidative Stress	High  There is a large body of evidence supporting a time and dose relationship from the deposition of energy to oxidative stress. Various studies using in vitro and in vivo rat, mice, rabbit, squirrel, bovine and human models provided evidence for this KER. A wide range of stressors were applied, including UV light (UV-B and UV-A) and ionizing radiation (gamma rays, X-rays, protons, photons, neutrons, and heavy ions). A dose-dependent increase in oxidative stress was observed in studies that examined a range of ionizing radiation doses (0-10 Gy).
KE#1392→ KE#1634: Oxidative Stress →Increase Oxidative DNA Damage	Low  There is very limited evidence supporting time and dose concordance for this KER. In vivo rodent studies informed a dose concordance following O2 exposure as a stressor and a time concordance following 11 Gy X-rays.
KE#1392→ KE#1635:   Oxidative Stress → Increase, DNA Strand Breaks	Moderate  There is evidence supporting the dose and incidence concordance of this relationship. There is limited evidence to support a time concordance. A limited variety of stressors are used as evidence supporting this KER. Most studies informing this relationship come from in vitro human models.
KE#1392→ KE#2081: Oxidative Stress → Modified Proteins	Low  Limited evidence supports dose and incidence concordance for this relationship. No evidence found supporting time concordance. Stressor types are limited to UVA radiation or H2O2 exposure.
KE#1634→ KE#155: Increase, Oxidative DNA Damage → Inadequate DNA Repair	Moderate  There is limited available data from eye lens models to support this relationship This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #296.
KE#1635→ KE#155: Increase DNA strand breaks → Inadequate DNA repair	Moderate   There is limited available data from eye lens models to support this relationship. This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #272.
KE#155→ KE#185: Inadequate DNA Repair → Increase, Mutations	Moderate  This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #272. However, there was no available data from eye lens models to support this relationship.
KE#155→ KE#1636: Inadequate DNA Repair → Increase, Chromosomal Aberrations	Moderate  This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #296.  However, there was no available data from eye lens models to support this relationship.
MIE#1686→ KE#1634: Deposition of energy → Increase oxidative DNA damage	Low  There is limited evidence to support this KER. No incidence concordance evidence is available. Low variety of stressors (X-rays and UVB) inform this relationship. In vitro human lens epithelial cells exposed to X-rays or UVB lead to a dose concordant increase in oxidative DNA damage. In vivo mice models exposed to X-rays showed a time concordant increase in oxidative DNA damage.
MIE#1686→ KE#1636: Deposition of energy → Increase chromosomal aberrations	High   There is a high level of empirical evidence to support this KER. Various studies demonstrate dose and time concordance between the deposition of energy and increased frequency of chromosomal aberrations. The evidence collected to support this relationship was gathered from various in vitro and in vivo studies. Various stressors were applied, including X-rays, gamma rays, and heavy ions. Chromosomal aberrations were detected as early as 30 minutes post-irradiation.
MIE#1686→ KE#870: Deposition of Energy → Increase, Cell Proliferation	High  There is high evidence to support dose and time concordance between energy deposition and cell proliferation, but no evidence for incidence concordance. Various in vivo and in vitro studies on rodents, rabbits, or human models inform this relationship. A variety of stressor types such as gamma rays, UV, or X-rays were used as evidence for this KER.
MIE#1686→ KE#2083: Deposition of Energy → Cataracts	High  There is high evidence to support dose and time concordance between energy deposition and cataract development. Various in vivo and in vitro studies and a variety of stressor types inform this relationship.
KE#2081→ KE#2083: Modified Proteins → Cataracts	Low  There is a small pool of evidence to support the time and incidence concordance between modified proteins and cataracts. Limited in vivo rodent studies and stressor types (gamma rays, X-rays) provide support for incidence and time concordance.
KE#155→ KE#2083: Inadequate DNA Repair → Cataracts	Low  There is a low amount of empirical evidence to support the relationship. The only available studies involve mice genetically predisposed towards inadequate DNA repair. Time concordance is supported by the in vivo studies, but no evidence is available for dose and incidence concordance. Mice irradiated with X-rays show cataract development 1-3 weeks sooner than wild type animals.
KE#1392→ KE#2083: Oxidative stress → Cataracts	Low  There is a limited amount of empirical support for this KER. No available studies support incidence concordance. Dose and time concordance are supported by a low amount of empirical evidence from in vitro and in vivo studies exposed to gamma rays or H2O2.
KE#870→ KE#2083:   Cell Proliferation → Cataracts	Low  There is no confident empirical evidence to accurately demonstrate a dependant relationship between the two events. Limited studies support time and dose concordance using relevant stressors and models.
KE#1634→ KE#1635: Increase, Oxidative DNA Damage → Increase, DNA Strand Breaks	Moderate  This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #296.  However, there was no available data from eye lens models to support this relationship.
KE#1636 → KE#870: Increase, chromosomal aberrations → Increase, Cell Proliferation	Moderate  This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #272.  However, there was no available data from eye lens models to support this relationship.
KE#185 → KE#870: Increase, Mutations → Increase, Cell Proliferation	Moderate  This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #272.  However, there was no available data from eye lens models to support this relationship.
MIE#1686→ KE#185: Deposition of energy → Increase, Mutations	High  This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #272.  However, there was no available data from eye lens models to support this relationship.

Quantitative Consideration

Quantitative understanding of the KERs in this AOP was rated as low. While certain KERs, such as MIE to AO, are well understood quantitatively with the literature, the understanding of other KERs is limited. For example, the quantitative understanding regarding the amount of DNA strand breaks and oxidative DNA lesions that would exceed cellular repair capacities to predict downstream effects require further investigation. Furthermore, studies often examined different endpoints at various time-points, using different stressors, doses, dose-rates, and models within each KER, causing difficulty in accurately comparing studies and deriving a quantitative understanding of the relationship, including precisely predicting the downstream KEs from the upstream KEs. As such, the areas with low quantitative understanding could be the focus of future experimental work using a more co-ordinated approach to experimental design, data collection and analysis. This would allow for more informative quantitative data that could be combined to understand the quantitative concordance of direct relationships and better support risk modeling and understanding of minimal risk dose estimates. 

Review of the Quantitative Understanding for each KER	Defining Question	High	Moderate	Low
	To what extent can a change in KEdownstream be predicted from KEupstream? With what precision can the uncertainty in the prediction of KEdownstream be quantified? To what extent are the known modulating factors of feedback mechanisms accounted for? To what extent can the relationships described be reliably generalized across the applicability domain of the KER?	Change in KEdownstream can be precisely predicted based on a relevant measure of KEupstream; uncertainty in the quantitative prediction can be precisely estimated from the variability in the relevant KEupstream measure. Known modulating factors and feedback/feedforward mechanisms are accounted for in the quantitative description. Evidence that the quantitative relationship between the KEs generalizes across the relevant applicability domain of the KER.	Change in KEdownstream can be precisely predicted based on a relevant measure of KEupstream; uncertainty in the quantitative prediction is influenced by factors other than the variability in the relevant KEupstream measure. Quantitative description does not account for all known modulating factors and/or known feedback/feedforward mechanisms. The quantitative relationship has only been demonstrated for a subset of the overall applicability domain of the KER.	Only a qualitative or semi-quantitative prediction of the change in KEdown can be determined from a measure of KEup. Known modulating factors and feedback/feedforward mechanisms are not accounted for. Quantitative relationship has only been demonstrated for a narrow subset of the overall applicability domain of the KER.
MIE#1686→ KE#1635:  Deposition of energy → Increase DNA strand breaks	High   The vast majority of studies examining energy deposition and incidence of DSBs suggest a positive, linear relationship between these two events. Predicting the exact number of DSBs from the deposition of energy, however, appears to be highly dependent on the biological model, the type of radiation and the radiation dose range, as evidenced by the differing calculated DSB rates across studies.
MIE#1686→ KE#2081:   Deposition of Energy → Modified Proteins	Moderate   There is a large amount of quantitative evidence supporting an increased amount of modified proteins following the deposition of energy; however, no trend emerged that could reliably predict the changes. There is a large variety of protein alterations that are possible and measurable. This makes finding connections between studies difficult, especially due to the wide range of doses used with inconsistencies as to the minimum dose needed to see effect.
MIE#1686→ KE#1392:  Deposition of Energy → Oxidative Stress	High  There is a large body of evidence supporting a quantitative understanding of the change in the deposition of energy needed to produce a change in the level of elements of oxidative stress. Oxidative stress can be represented by several different endpoints, including catalase, glutathione (GSH), superoxide dismutase, glutathione peroxidase (GSH-Px), malondialdehyde (MDA), and ROS levels. Measurements have also been made over a large range of doses and dose rates
KE#1392→ KE#1634: Oxidative Stress →Increase Oxidative DNA Damage	Low  There are a small number of studies that provide quantitative evidence for this KER.
KE#1392→ KE#1635:   Oxidative Stress → Increase, DNA Strand Breaks	Low  There is a considerable amount of evidence supporting dose concordance for an increased amount of DNA strand breaks following exposure to increased oxidative stress, however no trend has emerged that could reliably predict the changes. Measurements of oxidative stress are quite varied across studies. There is a clear association between the two events, positive changes in oxidative stress indicators increase DSB.
KE#1392→ KE#2081: Oxidative Stress → Modified Proteins	Low  There is a moderate amount of quantitative evidence supporting an increased the number of modified proteins following exposure to increased oxidative stress; however, no trend has emerged that could reliably predict the changes.
KE#1634→ KE#155: Increase, Oxidative DNA Damage → Inadequate DNA Repair	Low  This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #296. However, there was no available data from eye lens models to support this relationship.
KE#1635→ KE#155: Increase DNA strand breaks → Inadequate DNA repair	Moderate   According to studies examining DSBs and DNA repair after exposure to radiation, a positive linear relationship between DSBs and radiation dose has been observed, and a linear-quadratic relationship between the number of misrejoined DSBs and radiation dose which varied according to LET and dose-rate of the radiation. Overall, 1 Gy of radiation may induce between 35 and 70 DSBs, with 10 - 15% being misrepaired at 10 Gy and 50 - 60% being misrepaired at 80 Gy. This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #272.
KE#155→ KE#185: Inadequate DNA Repair → Increase, Mutations	Moderate  This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #272. However, there was no available data from eye lens models to support this relationship.
KE#155→ KE#1636: Inadequate DNA Repair → Increase, Chromosomal Aberrations	Low  This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #296.  However, there was no available data from eye lens models to support this relationship.
MIE#1686→ KE#1634: Deposition of energy → Increase oxidative DNA damage	Moderate   There is a moderate amount of quantitative understanding for this KER. The majority of the data investigates different indicators of oxidative DNA damage, namely 8-OH-DG, 8-OH G, cyclobutane pyrimidine dimers, and multiple chromophores such as NADH.
MIE#1686→ KE#1636: Deposition of energy → Increase chromosomal aberrations	High  Most studies indicate a positive, linear-quadratic relationship between the deposition of energy by ionizing radiation and the frequency of chromosomal aberrations. Equations describing this relationship were provided in a number of studies. In terms of time scale predictions, this may still be difficult owing to the often-lengthy cell cultures required to assess chromosomal aberrations post-irradiation, as well as the potential inapplicability of long-term cultures in predicting events in vivo.
MIE#1686→ KE#870: Deposition of Energy → Increase, Cell Proliferation	Moderate   There is a large amount of quantitative evidence supporting an increased amount of cell proliferation following the deposition of energy, however no trend can reliably predict the changes.
MIE#1686→ KE#2083: Deposition of Energy → Cataracts	High  The levels of cataract prevalence and severity generally can be predicted quantitatively from the level of radiation exposure. Many studies show that cataract development is dose dependent. The prediction of cataract development can be made more reliably with higher-dose exposures than with lower-dose exposures. Low-dose exposures typically show long lag periods for the onset of cataractogenesis, that coupled with the short observation periods frequently used make the prediction of cataract severity or prevalence less reliable. There are many known modulating factors that influence cataract development such as quality and dose of the radiation, gender, age at exposure, and genetic predispositions. These factors all affect the onset timing, prevalence, and severity of cataract development. Radiation-induced cataracts have been observed consistently across several mammalian species.
KE#2081→ KE#2083: Modified Proteins → Cataracts	Low  There is limited quantitative understanding of increased lens opacity/cataracts from protein alteration. Age is a known modulator of this relationship; protein aggregation increases naturally as the individual ages.
KE#155→ KE#2083: Inadequate DNA Repair → Cataracts	Low  There is limited quantitative evidence supporting the development of cataracts following inadequate DNA repair, and as such, there is not enough information to observe a trend that could reliably predict the changes.
KE#1392→ KE#2083: Oxidative stress → Cataracts	Low  There is limited quantitative understanding for this KER. Most of the data has been obtained using H2O2 to induce oxidative stress, and cataracts are assessed indirectly.
KE#870→ KE#2083:   Cell Proliferation → Cataracts	Low  The quantitative understanding of this KER is weak. There is no confident empirical evidence to accurately demonstrate a dependant relationship between the two events.
KE#1634→ KE#1635: Increase, Oxidative DNA Damage → Increase, DNA Strand Breaks	Low  This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #296. However, there was no available data from eye lens models to support this relationship.
KE#1636 → KE#870: Increase, chromosomal aberrations → Increase, Cell Proliferation	Low  This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #272. However, there was no available data from eye lens models to support this relationship.
KE#185 → KE#870: Increase, Mutations → Increase, Cell Proliferation	Low  This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #272. However, there was no available data from eye lens models to support this relationship.
MIE#1686→ KE#185: Deposition of energy → Increase, Mutations	High   This KER has been assessed as part of other AOPs, as described in the overall assessment of AOP #272. However, there was no available data from eye lens models to support this relationship.

Considerations for Potential Applications of the AOP (optional)

As the International Commission on Radiological Protection works to review literature on health effects from radiation exposure, the collected knowledge presented in this AOP will provide a structured approach to guide future recommendations. With better designed experiments that cross biological levels of organization, more informative quantitative data will be generated that can then inform risk assessment strategies. A stronger evidence base can provide better justification to support guidelines and standards for future space missions and settings related to occupational, environmental, and medical exposures, where cataracts are of concern.

References

Abdelkawi, S., M. Abo-Elmagd and H. Soliman. (2008), “Development of cataract and corneal opacity in mice due to radon exposure”, Radiation Effects and Defects in Solids, Vol.163/7, Taylor & Francis, Oxfordshire, https://doi.org/10.1080/10420150701249603.  

Ahmadi, M. et al. (2022), “Early responses to low-dose ionizing radiation in cellular lens epithelial models”, Radiation Research, Vol. 197/1, Radiation Research Society, United States, https://doi.org/10.1667/RADE-20-00284.1    

Ainsbury, E. A. et al. (2016), “Ionizing radiation induced cataracts: recent biological and mechanistic developments and perspectives for future research”, Mutation research. Reviews in mutation research, Vol. 770, Elsevier B.V., https://doi.org/10.1016/j.mrrev.2016.07.010   

Anbaraki, A. et al. (2016), “Preventive role of lens antioxidant defense mechanism against riboflavin-mediated sunlight damaging of lens crystallin”, International Journal of Biological Macromolecules, Vol.91, Elsevier, Amsterdam, https://doi.org/10.1016/j.ijbiomac.2016.06.047.  

Bahia, S. et al. (2018), “Oxidative and nitrative stress-related changes in human lens epithelial cells following exposure to X-rays”, International journal of radiation biology, Vol. 94/4, England, https://doi.org/10.1080/09553002.2018.1439194   

Bains, S. K. et al. (2019), “Effects of ionizing radiation on telomere length and telomerase activity in cultured human lens epithelium cells”, International journal of radiation biology, Vol. 95/1, Taylor & Francis, Abingdon, https://doi.org/10.1080/09553002.2018.1466066  

Barnard, S. et al. (2021), “Lens epithelial cell proliferation in response to ionizing radiation”, Radiation Research, Vol. 197/1, Radiation Research Society, https://doi.org/10.1667/RADE-20-00294.1   

Barnard, S. G. R. et al. (2019), “Inverse dose-rate effect of ionising radiation on residual 53BP1 foci in the eye lens”, Scientific Reports, Vol. 9/1, Nature Publishing Group, England, https://doi.org/10.1038/s41598-019-46893-3  

Bignold, L.P. (2009), "Mechanisms of clastogen-induced chromosomal aberrations : A critical review and description of a model based on failures of tethering of DNA strand ends to strand-breaking enzymes.", Mutation Research, Vol. 681/2-3, Elsevier, Amsterdam https://doi.org/10.1016/j.mrrev.2008.11.004.    

Brenerman, B., J. Illuzzi, and D. Wilson III (2014), “Base excision repair capacity in informing healthspan”, Carcinogenesis, Vol. 35/12, Oxford Academic, https://doi.org/10.1093/carcin/bgu225.   

Brooks, A. L., Hoel, D. G., Preston, R. J. (2016), “The role of dose rate in radiation cancer risk: evaluating the effect of dose rate at the molecular, cellular and tissue levels using key events in critical pathways following exposure to low LET radiation.” International journal of radiation biology, Vol. 92/8, Informa, London, https://doi.org/10.1080/09553002.2016.118630 

Cabrera, M. and R. Chihuailaf. (2011), “Antioxidants and the integrity of ocular tissues”, Veterinary Medicine International, Vol. 2011, Hindawi Limited, London, https://doi.org/10.4061/2011/905153.   

Cannan, W. and D. Pederson. (2016), “Mechanisms and consequences of double-strand DNA break formation in chromatin”, Journal of Cell Physiology, Vol.231/1, Wiley, Hoboken, https://doi.org/10.1002/jcp.25048.   

Ceccaldi, R., Rondinelli B., D’Andrea A. D. (2016), “Repair Pathway Choices and Consequences at the Double-Strand Break.” Trends in cell biology, Vol. 26/1, Elsevier, Amsterdam, https://doi.org/10.1016/j.tcb.2015.07.009 

Cencer, C. et al. (2018), “PARP-1/PAR Activity in Cultured Human Lens Epithelial Cells Exposed to Two Levels of UVB Light”, Photochemistry and Photobiology, Vol.94/1, Wiley-Blackwell, Hoboken, https://doi.org/10.1111/php.12814.   

Chandrasekher, G., & Sailaja, D. (2004),. Alterations in lens protein tyrosine phosphorylation and phosphatidylinositol 3-kinase signaling during selenite cataract formation,. Current eye research, Vol.28(2),. https://doi.org/10.1076/ceyr.28.2.135.26232 https://doi.org/10.1076/ceyr.28.2.135.26232 

Chylack, L.T. Jr et al. (2012), “NASCA Report 2: Longitudinal Study of Relationship of Exposure to Space Radiation and Risk of Lens Opacity”, Radiation Research, Vol.178/1, Radiation Research Society, Indianapolis, htps://doi.org/10.1667/RR2876.1.   

Collins, A. R. (2014), “Measuring oxidative damage to DNA and its repair with the comet assay”, Biochimica et biophysica acta. General subjects, Vol. 1840/2, Elsevier, Amsterdam, https://doi.org/10.1016/j.bbagen.2013.04.022   

Cucinotta, F.A. et al. (2001), “Space Radiation and Cataracts in Astronauts”, Radiation Research, Vol.156/5 Pt 1, Radiation Research Society, Indianapolis, https://doi.org/10.1667/0033-7587(2001)156[0460:SRACIA]2.0.CO;2. 

Dalke, C. et al. (2018), “Lifetime study in mice after acute low-dose ionizing radiation: a multifactorial study with special focus on cataract risk”, Radiation and environmental biophysics, Vol. 57/2, Springer Berlin Heidelberg, Berling/Heidelberg, https://doi.org/10.1007/s00411-017-0728-z. 

de Jager, T. L., A. E. Cockrell, S. S. Du Plessis (2017), “Ultraviolet Light Induced Generation of Reactive Oxygen Species”, in: Ultraviolet Light in Human Health, Diseases and Environment, vol 996. Springer Cham, https://doi.org/10.1007/978-3-319-56017-5_2.

De Stefano, I. et al. (2021), “Contribution of genetic background to the radiation risk for cancer and non-cancer diseases in Ptch1+/- mice”, Radiation Research, Vol. 197/1, Radiation Research Society, https://doi.org/10.1667/RADE-20-00247.1  

Domijan, A., Zeljezic, D., Kopjar, D., Peraica, M. (2006), “Standard and Fpg-modified comet assay in kidney cells of ochratoxin A- and fumonisin B(1)-treated rats”, Toxciology, Vol. 222/1-2, Elsevier, Amsterdam, https://doi.org/10.1016/j.tox.2006.01.024. 

Fochler, C. and H. Durchschlag. (1997), “Investigation of irradiated eye-lens proteins by analytical ultracentrifugation and other techniques”, Progress in Colloid and Polymer Science, Vol.107, Springer, Berlin, https://doi.org/10.1007/BFb0118020.   

Georgakilas, A. G et al. (2013), “Induction and repair of clustered DNA lesions: what do we know so far?”, Radiation Research, Vol. 180/1, The Radiation Research Society, United States, https://doi.org/10.1667/RR3041.1. 

Gragoudas, E.S. et al. (1995), “Lens Changes after Proton Beam Irradiation for Uveal Melanoma”, American Journal of Ophthalmology, Vol.119/2, Elsevier, Amsterdam, https://doi.org/10.1016/S0002-9394(14)73868-1. 

Hamada, N. (2014), “What Are the Intracellular Targets and Intratissue Target Cells for Radiation Effects?”, Radiation Research, Vol.181/1, Radiation Research Society, Indianapolis, https://doi.org/10.1667/RR13505.1.   

Hamada, N. (2017), “Ionizing radiation sensitivity of the ocular lens and its dose rate dependence”, International journal of radiation biology, Vol. 93/10, Taylor & Francis, England, https://doi.org/10.1080/09553002.2016.1266407   

Hanson, S. et al. (2000), “The major in vivo modifications of the human water-insoluble lens crystallins are disulfide bonds, deamidation, methionine oxidation and backbone cleavage”, Experimental Eye Research, Vol.71/2, Academic Press Inc, Cambridge, https://doi.org/10.1006/EXER.2000.0868.   

ICRP (2012), “ICRP Publication #118: ICRP Statement on Tissue Reactions and Early and Late Effects of Radiation in Normal Tissues and Organs - Threshold Doses for Tissue Reactions in a Radiation Protection Context”, Annals of the ICRP, Vol.41/1-2, Elsevier, Amsterdam, https://doi.org/10.1016/j.icrp.2012.02.001.   

Iliakis, G., T. Murmann & A. Soni (2015), "Alternative end-joining repair pathways are the ultimate backup for abrogated classical non-homologous end-joining and homologous recombination repair: Implications for the formation of chromosome translocations", Mutation research. Genetic toxicology and environmental mutagenesis, Vol. 793, https://doi.org/10.1016/j.mrgentox.2015.07.001. 

Jeggo, P.A. (1998) “DNA breakage and repair”, Advances in genetics, Vol. 38, Elsevier, Amsterdam, https://doi.org/10.1016/s0065-2660(08)60144-3 

Joiner, M. and A. van der Kogel (2009), "Basic Clinical Radiobiology", 4th ed., CRC Press, https://doi.org/10.1201/b15450.   

Jones, J.A. et al. (2007), “Cataract Formation Mechanisms and Risk in Aviation and Space Crews”, Aviation, Space and Environmental Medicine, Vol.78/4 Suppl, Aerospace Medical Association, A56-66.    

Jurja, S. et al. (2014), “Ocular cells and light: harmony or conflict?”, Romanian Journal of Morphology & Embryology, Vol. 55/2, Romanian Academy Publishing House, Bucharest, pp. 257–261.   

Karslioǧlu, I. et al. (2005), “Radioprotective effects of melatonin on radiation-induced cataract”, Journal of radiation research, Vol. 46/2, The Japan Radiation Research Society, England, https://doi.org/10.1269/jrr.46.277  

Kleiman, N. J. et al. (2007), “Mrad9 and Atm haplinsufficiency enhance spontaneous and X-ray-induced cataractogenesis in mice”, Radiation research, Vol. 168/5, Radiation Research Society, United States, https://doi.org/10.1667/rr1122.1  

Kocer, I. et al. (2007), “The effect of L-carnitine in the prevention of ionizing radiation-induced cataracts: A rat model”, Graefe’s Archive for Clinical and Experimental Ophthalmology, Vol. 245/4, Springer, Germany, https://doi.org/10.1007/s00417-005-0097-1  

Kozbenko, T. et al. (2022), “Deploying elements of scoping review methods for adverse outcome pathway development: a space travel case example”, International Journal of Radiation Biology, Vol. 98/12, Taylor & Francis, London, https://doi.org/10.1080/09553002.2022.2110306  

Kramara, J., B. Osia, and A. Malkova (2018), "Break-Induced Replication: The Where, The Why, and The How", Trends Genet, Vol. 34/7, Elsevier, Amsterdam, https://doi.org/10.1016/j.tig.2018.04.002.   

Kubo, E. et al. (2010), “Protein expression profiling of lens epithelial cells from Prdx6-depleted mice and their vulnerability to UV radiation exposure”, American Journal of Physiology, Vol. 298/2, American Physiological Society, Rockville, https://doi.org/10.1152/ajpcell.00336.2009.   

Li, Y. et al. (1998), “Response of lens epithelial cells to hydrogen peroxide stress and the protective effect of caloric restriction”, Experimental Cell Research, Vol.239/2, Elsevier, Amsterdam, https://doi.org/10.1006/excr.1997.3870.   

Little, M. P. et al. (2018), “Occupational radiation exposure and risk of cataract incidence in a cohort of US radiologic technologists”, European Journal of Epidemiology, Vol. 33/12, Springer, https://doi.org/10.1007/s10654-018-0435-3.   

Liu, H. et al. (2013a), “Sulforaphane can protect lens cells against oxidative stress: Implications for cataract prevention”, Investigative Ophthalmology and Visual Science, Vol.54/8, Association for Research in Vision and Ophthalmology, Rockville, https://doi.org/10.1167/iovs.13-11664.  

Liu B. et al. (2013b). “Computational methods for detecting copy number variations in cancer genome using next generation sequencing: principles and challenges”, Oncotarget. 4(11):1868-81. Doi: 10.18632/oncotarget.1537.   

Liu, Y. et al. (2017), “Cataracts”, The Lancet (British edition), Vol. 390/10094, Elsevier Ltd, England, https://doi.org/10.1016/S0140-6736(17)30544-5   

Markiewicz, E. et al. (2015), “Nonlinear ionizing radiation-induced changes in eye lens cell proliferation, cyclin D1 expression and lens shape”, Open Biology, Vol.5/4, Royal Society, London, https://doi.org/10.1098/rsob.150011.   

McCarron, R. et al. (2022), “Radiation-Induced Lens Opacity and Cataractogenesis: A Lifetime Study Using Mice of Varying Genetic Backgrounds”, Radiation Research, Vol.196, Radiation Research Society, Indianapolis, https://doi.org/10.1667/RADE-20-00266.1.   

Menard, T. et al. (1986), “Radioprotection against cataract formation by WR-77913 in gamma-irradiated rats”, International Journal of Radiation Oncology Biology Physics, Vol.12, Elsevier, Amsterdam, https://doi.org/10.1016/0360-3016(86)90199-9.   

Mesa, R. and S. Bassnett (2013), “UV-B induced DNA damage and repair in the mouse lens”, Investigative ophthalmology & visual science, Vol. 54/10, the Association for Research in Vision and Ophthalmology, United States, https://doi.org/10.1167/iovs.13-12644   

Moreau, K. and J. King. (2012), “Protein misfolding and aggregation in cataract disease and prospects for prevention”, Trends in Molecular Medicine, Vol.18/5, Elsevier Ltd, London, https://doi.org/10.1016/j.molmed.2012.03.005.   

Nakashima, E., K. Neriishi and A. Minamoto. (2006), “A Reanalysis of Atomic-Bomb Cataract Data, 2000-2002: A Threshold Analysis”, Health Physics, Vol.90/2, Lippincott Williams & Wilkins, Philadelphia, https://doi.org/10.1097/01.HP.0000175442.03596.63.   

National Eye Institute (2022), Cataracts, https://www.nei.nih.gov/learn-about-eye-health/eye-conditions-and-diseases/cataracts (accessed November 29, 2022).  

NCRP (2016), “Guidance on radiation dose limits for the lens of the eye”, NCRP Commentary, Vol.26, National Council on Radiation Protection and Measurements Publications, Bethesda.   

Nickoloff, J. A., Sharma N., and Taylor L. (2020) “Clustered DNA Double-Strand Breaks: Biological Effects and Relevance to Cancer Radiotherapy.” Genes, Vol. 11/1, MDPI, Basel, https://doi.org/10.3390/genes11010099 

Nikitaki, Z. et al. (2016), "Measurement of complex DNA damage induction and repair in human cellular systems after exposure to ionizing radiations of varying linear energy transfer (LET)", Free Radiacal Research, Vol. 50/sup1, Taylor & Francis, London, https://doi.org/10.1080/10715762.2016.1232484.   

Pendergrass, W. et al. (2010), “X-ray induced cataract is preceded by LEC loss, and coincident with accumulation of cortical DNA, and ROS; similarities with age-related cataracts”, Molecular Vision, Vol. 16, Emory University, Atlanta, pp. 1496-513.    

Perera, D. et al. (2016), "Differential DNA repair underlies mutation hotspots at active promoters in cancer genomes", Nature, Vol. 532/7598, Springer Nature, https://doi.org/10.1038/nature17437.  

Pirie, A. and S. M. Drance (1959), “Modification of X-ray damage to the lens by partial shielding”, International Journal of Radiation Biology and Related Studies in Physics, Chemistry and Medicine, Vol. 1/3, Taylor & Francis, London, https://doi.org/10.1080/09553005914550391. 

Qin, Z. et al. (2019), “Opacification of lentoid bodies derived from human induced pluripotent stem cells is accelerated by hydrogen peroxide and involves protein aggregation”, Journal of cellular physiology, Vol. 234/12, Wiley Subscriptions, United States, https://doi.org/10.1002/jcp.28943. 

Reddy, V. N. et al. (1998), “The effect of aqueous humor ascorbate on ultraviolet-B-induced DNA damage in lens epithelium”, Investigative ophthalmology & visual science, Vol. 39/2, Arvo, pp. 344-350.  

Reisz, J. et al. (2014), “Effects of ionizing radiation on biological molecules - mechanisms of damage and emerging methods of detection”, Antioxidants and Redox Signaling, Vol.21(2), Mary Ann Liebert Inc, Larchmont, https://doi.org/10.1089/ars.2013.5489.    

Schipler, A. & 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, Vol. 41/165, http://doi.org/10.1093/nar/gkt556.   

Shah, A. et al. (2018), “Defective Base Excision Repair of Oxidative DNA Damage in Vascular Smooth Muscle Cells Promotes Atherosclerosis”, Circulation, Vol. 138/14, https://doi.org/10.1161/CIRCULATIONAHA.117.033249.   

Sishc, B.J. & A.J. Davis (2017), "The Role of the Core Non-Homologous End Joining Factors in Carcinogenesis and Cancer.", Cancers, Vol. 9/7, Basel, http://doi.org/10.3390/cancers9070081.   

Smith, A. J. O. et al. (2016), “PARP-1 inhibition influences the oxidative stress response of the human lens”, Redox biology, Vol. 8/C, Elsevier, Netherlands, https://doi.org/10.1016/j.redox.2016.03.003. 

Soloviev, A. I. and I.V. Kizub (2019), “Mechanisms of vascular dysfunction evoked by ionizing radiation and possible targets for its pharmacological correction”, Biochemical pharmacology, Vol. 159, Elsevier, Amsterdam, https://doi.org/10.1016/j.bcp.2018.11.019.    

Spector, A. et al. (1997), “Microperoxidases catalytically degrade reactive oxygen species and may be anti-cataract agents”, Experimental Eye Research, Vol.65/4, Academic Press Inc, Cambridge, https://doi.org/10.1006/exer.1997.0336.   

Spector, A. (1995), “Oxidative stress‐induced cataract: mechanism of action”, The FASEB Journal, Vol.9/12, Federation of American Societies for Experimental Biology, Bethesda, https://doi.org/10.1096/fasebj.9.12.7672510.  

Stohs, S. (1995), “The role of free radicals in toxicity and disease”, Journal of Basic and Clinical Physiology and Pharmacology, Vol. 6/3-4, Walter de Gruyter GmbH, Berlin, pp. 205-228.    

Tangvarasittichai, O and S. Tangvarasittichai (2019), “Oxidative stress, ocular disease, and diabetes retinopathy”, Current Pharmaceutical Design, Vol. 24/40, Bentham Science Publishers, https://doi.org/10.2174/1381612825666190115121531. 

Tian, Y. et al. (2017), “The Impact of Oxidative Stress on the Bone System in Response to the Space Special Environment”, International Journal of Molecular Sciences, Vol. 18/10, Multidisciplinary Digital Publishing Institute, Basel, https://doi.org/10.3390/ijms18102132.    

Tsao, D. et al. (2007), “Induction and processing of oxidative clustered DNA lesions in 56Fe-ion-irradiated human monocytes”, Radiation Research, Vol.168/1, United States, https://doi.org/10.1667/RR0865.1   

Tuieng, R. J., Cartmell, S. H., Kirwan, C. C., & Sherratt, M. J. (2021). The Effects of Ionising and Non-Ionising Electromagnetic Radiation on Extracellular Matrix Proteins, Cells, Vol. 10(11), MDPI, Basel, https://doi.org/10.3390/cells10113041 

Udroiu, I. et al. (2020), “DNA damage in lens epithelial cells exposed to occupationally-relevant X-ray doses and role in cataract formation”, Scientific reports, Vol. 10/1, Nature Research, Berlin, https://doi.org/10.1038/s41598-020-78383-2  

Uwineza, A. et al. (2019), “Cataractogenic load – A concept to study the contribution of ionizing radiation to accelerated aging in the eye lens”, Mutation Research - Reviews in Mutation Research, Vol.779, Elsevier, Amsterdam, https://doi.org/10.1016/j.mrrev.2019.02.004.   

van Kuijk, F. J. (1991), “Effects of ultraviolet light on the eye: role of protective glasses”, Environmental health perspectives, Vol. 96, National Institute of Environmental Health Sciences, Unites States, https://doi.org/10.1289/ehp.9196177. 

Varma, S. D., S. Kovtun and K. R. Hegde (2011), “Role of ultraviolet irradiation and oxidative stress in cataract formation – medical prevention by nutritional antioxidants and metabolic agonists”, Eye & contact lens, Vol. 37/4, Lippincott Willians & Wilkins Inc, United States, https://doi.org/10.1097/ICL.0b013e31821ec4f2. 

Venkatesulu, B. P. et al. (2018), “Radiation-Induced Endothelial Vascular Injury: A Review of Possible Mechanisms”, JACC: Basic to Translational Science, Vol. 3/4, Elsevier, Amsterdam, https://doi.org/10.1016/j.jacbts.2018.01.014. 

Wang, H. et al. (2019), “Radiation-induced heart disease: a review of classification, mechanism and prevention”, International Journal of Biological Sciences, Vol. 15/10, Ivyspring International Publisher, Sydney, https://doi.org/10.7150/ijbs.35460.   

Wang, Z. et al. (2020). MDM2 phosphorylation mediates H2O2-induced lens epithelial cells apoptosis and age-related cataract,. Biochemical and biophysical research communications, Vol. (1), . https://doi.org/10.1016/j.bbrc.2020.05.060  

Wilhelm, T. et al. (2014), "Spontaneous slow replication fork progression elicits mitosis alterations in homologous recombination-deficient mammalian cells.", Proceedings of the National Academy of Sciences of the United States of America, Vol. 111/2, https://doi.org/10.1073/pnas.1311520111. 

Worgul, B. V et al. (2002), “Atm heterozygous mice are more sensitive to radiation-induced cataracts than are their wild-type counterparts,” Proceedings of the National Academy of Sciences, Vol. 99/15, National Academy of Sciences, https://doi.org/10.1073/pnas.162349699. 

Worgul, B. V. et al. (1993), “Accelerated heavy particles and the lens VII: The cataractogenic potential of 450 MeV/amu iron ions”, Investigative Ophthalmology and Visual Science, Vol. 34/1, pp. 184–193.  

Worgul, B. V. et al. (2007), “Cataracts among Chernobyl Clean-up Workers: Implications Regarding Permissible Eye Exposures”, Radiation Research, Vol.167/2, Radiation Research Society, Indianapolis, https://doi.org/10.1667/RR0298.1.   

Zigman, S. et al. (1975), “The response of mouse ocular tissues to continuous near-UV light exposure”, Investigative Ophthalmology, Vol.14/September, Association for Research in Vision and Ophthalmology, Rockville, pp.710-713.  

Zigman, S. et al. (1995), “Damage to cultured lens epithelial cells of squirrels and rabbits by UV-A (99.9%) plus UV-B (0.1%) radiation and alpha tocopherol protection”, Molecular and cellular biochemistry, Vol. 143, Springer, London, https://doi.org/10.1007/BF00925924

Zigman, S. et al. (2000), “Effects of intermittent UVA exposure on cultured lens epithelial cells”, Current Eye Research, Vol. 20/2, Informa UK Limited, London, https://doi.org/10.1076/0271-3683(200002)2021-DFT095

Appendix 1

List of MIEs in this AOP

Event: 1686: Deposition of Energy

Short Name: Energy Deposition

Key Event Component

AOPs Including This Key Event

Stressors

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Energy can be deposited into any substrate, both living and non-living; it is independent of age, taxa, sex, or life-stage. 

Taxonomic applicability: This MIE is not taxonomically specific. 

Life stage applicability: This MIE is not life stage specific. 

Sex applicability: This MIE is not sex specific. 

Key Event Description

Deposition of energy refers to events where energetic subatomic particles, nuclei, or electromagnetic radiation deposit energy in the media through which they transverse. The energy may either be sufficient (e.g. ionizing radiation) or insufficient (e.g. non-ionizing radiation) to ionize atoms or molecules (Beir et al.,1999). 

Ionizing radiation can cause the ejection of electrons from atoms and molecules, thereby resulting in their ionization and the breakage of chemical bonds.  The excitation of molecules can also occur without ionization. These events are stochastic and unpredictable. The energy of these subatomic particles or electromagnetic waves ranges from 124 keV to 5.4 MeV and is dependent on the source and type of radiation (Zyla et al., 2020). Not all electromagnetic radiation is ionizing; as the incident radiation must have sufficient energy to free electrons from the electron orbitals of the atom or molecule. The energy deposited can induce direct and indirect ionization events and can result from internal (injections, inhalation, ingestion) or external exposure. 

Direct ionization is the principal path where charged particles interact with biological structures such as DNA, proteins or  membranes to cause biological damage. Photons, which are electromagnetic waves can also deposit energy to cause direct which themselves can indirectly damage critical targets such as DNA (Beir et al., 1999; Balagamwala et al., 2013) or alter cellular processes. Given the fundamental nature of energy deposition by radioactive/unstable nuclei, nucleons or elementary particles in material, this process is universal to all biological contexts. 

The spatial structure of ionizing energy deposition along the resulting particle track is represented as linear energy transfer (LET) (Hall and Giaccia, 2018 UNSCEAR, 2020). High LET refers to energy mostly above 10 keV μm-1 which produces more complex, dense structural damage than low LET radiation (below 10 keV μm-1). Low-LET particles produce sparse ionization events such as photons (X- and gamma rays), as well as high-energy protons. Low LET radiation travels farther into tissue but deposits smaller amounts of energy, whereas high LET radiation, which includes heavy ions, alpha particles and high-energy neutrons, does not travel as far but deposits larger amounts of energy into tissue at the same absorbed dose. The biological effect of the deposition of energy can be modulated by varying dose and dose rate of exposure, such as acute, chronic, or fractionated exposures (Hall and Giaccia, 2018). 

Non-ionizing radiation is electromagnetic waves that does not have enough energy to break bonds and induce ion formation but it can cause molecules to excite and vibrate faster resulting in biological effects. Examples of non-ionizing radiation include radio waves (wavelength: 100 km-1m), microwaves (wavelength: 1m-1mm), infrared radiation (wavelength: 1mm- 1 um), visible light (wavelengths: 400-700 nm), and ultraviolet radiation of longer wavelengths such as UVB (wavelengths: 315-400nm) and UVA (wavelengths: 280-315 nm). 

How it is Measured or Detected

Radiation type	Assay Name	References	Description	OECD Approved Assay
Ionizing radiation	Monte Carlo Simulations (eg. Geant4)	Douglass et al., 2013; Douglass et al., 2012; Zyla et al., 2020	Monte Carlo simulations are based on a computational algorithm that mathematically models the deposition of energy into materials.	No
Ionizing radiation	Fluorescent Nuclear Track Detector (FNTD)	Sawakuchi, 2016; Niklas, 2013; Kodaira & Konishi, 2015	FNTDs are biocompatible chips with crystals of aluminum oxide doped with carbon and magnesium; used in conjunction with fluorescent microscopy, these FNTDs allow for the visualization and the linear energy transfer (LET) quantification of tracks produced by the deposition of energy into a material.	No
Ionizing radiation	Tissue equivalent proportional counter (TEPC)	Straume et al, 2015	Measure the LET spectrum and calculate the equivalent dose	No
Ionizing radiation	alanine dosimeters/NanoDots	Lind et al. 2019  Xie et al., 2022	Alanine dosimeters use the amino acid alanine to detect radiation-induced changes, and nanodots leverage nano-scale technology to provide high precision and sensitivity in radiation dose measurements	No
Non-ionizing radiation	UV meters or radiometers	Xie et al., 2020	UVA/UVB (irradiance intensity), UV dosimeters (accumulated irradiance over time), Spectrophotometer (absorption of UV by a substance or material)	No

 

References

Balagamwala, E. H. et al. (2013), “Introduction to radiotherapy and standard teletherapy techniques”, Dev Ophthalmol, Vol. 52, Karger, Basel, https://doi.org/10.1159/000351045 

Beir, V. et al. (1999), “The Mechanistic Basis of Radon-Induced Lung Cancer”, in Health Risks of Exposure to Radon: BEIR VI, National Academy Press, Washington, D.C., https://doi.org/10.17226/5499 

Douglass, M. et al. (2013), “Monte Carlo investigation of the increased radiation deposition due to gold nanoparticles using kilovoltage and megavoltage photons in a 3D randomized cell model”, Medical Physics, Vol. 40/7, American Institute of Physics, College Park, https://doi.org/10.1118/1.4808150 

Douglass, M. et al. (2012), “Development of a randomized 3D cell model for Monte Carlo microdosimetry simulations.”, Medical Physics, Vol. 39/6, American Institute of Physics, College Park, https://doi.org/10.1118/1.4719963 

Hall, E. J. and Giaccia, A.J. (2018), Radiobiology for the Radiologist, 8th edition, Wolters Kluwer, Philadelphia. 

Kodaira, S. and Konishi, T. (2015), “Co-visualization of DNA damage and ion traversals in live mammalian cells using a fluorescent nuclear track detector.”, Journal of Radiation Research, Vol. 56/2, Oxford University Press, Oxford, https://doi.org/10.1093/jrr/rru091 

Lind, O.C., D.H. Oughton and Salbu B. (2019), "The NMBU FIGARO low dose irradiation facility", International Journal of Radiation Biology, Vol. 95/1, Taylor & Francis, London, https://doi.org/10.1080/09553002.2018.1516906. 

Sawakuchi, G.O. and Akselrod, M.S. (2016), “Nanoscale measurements of proton tracks using fluorescent nuclear track detectors.”, Medical Physics, Vol. 43/5, American Institute of Physics, College Park, https://doi.org/10.1118/1.4947128 

Straume, T. et al. (2015), “Compact Tissue-equivalent Proportional Counter for Deep Space Human Missions.”, Health physics, Vol. 109/4, Lippincott Williams & Wilkins, Philadelphia, https://doi.org/10.1097/HP.0000000000000334  

Niklas, M. et al. (2013), “Engineering cell-fluorescent ion track hybrid detectors.”, Radiation Oncology, Vol. 8/104, BioMed Central, London, https://doi.org/10.1186/1748- 717X-8-141 

UNSCEAR (2020), Sources, effects and risks of ionizing radiation, United Nations. 

 Xie, Li. et al. (2022), "Ultraviolet B Modulates Gamma Radiation-Induced Stress Responses in Lemna Minor at Multiple Levels of Biological Organisation", SSRN, Elsevier, Amsterdam, http://dx.doi.org/10.2139/ssrn.4081705 . 

Zyla, P.A. et al. (2020), Review of particle physics: Progress of Theoretical and Experimental Physics, 2020 Edition, Oxford University Press, Oxford. 

 

 

List of Key Events in the AOP

Event: 2081: Increased Modified Proteins

Short Name: Modified Proteins

Key Event Component

AOPs Including This Key Event

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability: Modified proteins are applicable to all animals as proteins exist in some form in the cells of all animals (Cray, 2012).  

Life stage applicability: This key event is not life stage specific as individuals in all life stages have proteins that can be modified (Dalle-Donne et al., 2006; Krisko & Radman, 2019). However, older individuals have naturally higher baseline levels of modified proteins, and those levels can even be used to determine an individual’s age (Krisko & Radman, 2019). 

Sex applicability: This key event is not sex specific as both sexes have proteins that can be modified. Evidence shows that males have a slightly higher level of protein carbonylation than their age-matched female counterparts (Barreiro et al., 2006). 

Evidence for perturbation by a stressor: There is evidence to demonstrate that protein modification can occur as a result of multiple stressor types including oxidizing agents and ionizing & non-ionizing radiation (Hightower, 1995, Hamada et al., 2014; Lipman et al., 1988; Reisz et al., 2014).  

Key Event Description

Proteins are considered to be modified following any change in structural components, as well as protein levels. Modifications to proteins can occur at any one of the structural levels of proteins, primary structure (amino acid or polypeptide sequence), the secondary structure (alpha helix or beta sheet structures), or the tertiary structure (globular protein forms) (Alberts et al., 2002). Protein modifications can include post-translational modifications such as deamidation, oxidation, phosphorylation and carbonylation. Protein structure specificity can be crucial to their ability to execute their functional duties within a cell. Protein modifications can in turn affect protein-protein interactions, potentially hindering the ability to perform those functions (Dalle-Donne et al., 2006; Krisko & Radman, 2019). These affected protein interactions can result in unfolding, aggregation, insolubility, and increased molecular weight (Toyoma et al., 2013; Young, 1994). This can lead to the development of various age-related diseases, such as cataracts. As an example, modification of the tertiary structure of lens crystallin proteins can cause protein aggregation, increased lens opacity, and eventually cataracts (Moreau & King, 2012).  

Modified proteins also refers to changes in protein levels which can result from changes in how proteins are synthesized (through transcription and translation), modified, and regulated in cells (Krisko & Radman, 2019). These processes are governed spatially and temporally by transcriptional and translational regulators as well as other signaling moieties and are tightly linked to the functional needs of cells, which can change depending on the presence of stressors or other external signaling factors (Reisz et al., 2014. Misregulation of protein expression can trigger a cascade of changes in downstream intracellular activities, which can then cause abnormal cellular dynamics. This misregulation can include abnormally high or low levels of particular proteins or even abnormalities in their breakdown (Hamada et al., 2014.

How it is Measured or Detected

Listed below are common methods for detecting the KE, however there may be other comparable methods that are not listed. 

Method of Measurement	References	Description	OECD-Approved Assay
Mass Spectrometry	(Noble & Bailey, 2009)	Technique involves measuring the mass-to-charge ratio of ions to identify and quantify molecules and architectural changes such as the post-translational modifications of proteins	No
Proximity Ligation Assay	(Noble & Bailey, 2009)	An immunohistochemical tool that can help perform in situ detection of endogenous proteins, protein modifications, and protein interactions with high specificity and sensitivity	No
Western Blot	(Noble & Bailey, 2009)	Immunoblotting technique using antibody to detect its antigen and can be used for measuring protein levels.	No
Bicinchoninic Acid Assay (BCA)	(Noble & Bailey, 2009)	Can assist in quantification of total protein in a sample with colorimetric changes propagated through proteins mediated reduction of Cu+2 to Cu+1.	No
A280(Spectroscopy)	(Noble & Bailey, 2009)	Direct assay method for protein concentration determination in solution through measuring absorbance at 280 nm.	No
Lowry Assay	(Noble & Bailey, 2009)	Binding of administered agents to proteins causes measurable spectral shift to the blue form of the dye which can be used to quantify protein-levels.	No
Protein Mass Spectrometry	(Noble & Bailey, 2009)	Proteins initially digested various recombinant proteases, most often trypsin and are then subsequently observed at the tandem mass spectrometer (MS1) as a series of peaks, each with a different mass-to-charge ratio.	No
ELISA	(Alomari et al. 2018)	Carbonyl content on proteins detected using a plate reader following chromogenic reaction	No

References

Alberts B. et al. (2002), “The Shape and Structure of Proteins”, Molecular Biology of the Cell, 4, New York: Garland Science.   

Alomari, E. et al. (2018), “Protein carbonylation detection methods: A comparison”, Data in Brief, Vol.19, Elsevier, Amsterdam, https://doi.org/10.1016/j.dib.2018.06.088. 

Barreiro, E. et al. (2006), “Aging, sex differences, and oxidative stress in human respiratory and limb muscles”, Free Radical Biology & Medicine, Vol.41/5, Elsevier, Amsterdam, https://doi.org/10.1016/j.freeradbiomed.2006.05.027. 

Cray, C. (2012), “Chapter 5 - Acute Phase Proteins in Animals”, Progress in Molecular Biology and Translational Science, Vol.105, Elsevier, Amsterdam, https://doi.org/10.1016/B978-0-12-394596-9.00005-6. 

Dalle-Donne, I. et al. (2006), “Protein carbonylation, cellular dysfunction, and disease progression”, Journal of Cellular and Molecular Medicine, Vol.10/2, Wiley-Blackwell, Hoboken, https://doi.org/10.1111/j.1582-4934.2006.tb00407.x. 

Hamada, N. et al. (2014), “Emerging issues in radiogenic cataracts and cardiovascular disease”, Journal of Radiation Research, Vol.55/5, Oxford University Press, Oxford, https://doi.org/10.1093/jrr/rru036.  

Hightower, K. (1995), “The role of the Lens epithelium in development of UV cataract”, Current Eye Research, Vol.14/1, Taylor & Francis, Oxfordshire, https://doi.org/10.3109/02713689508999916. 

Krisko, A. and M. Radman. (2019), “Protein damage, ageing and age-related diseases”, Open Biology, 9/3, The Royal Society, London, https://doi.org/10.1098/rsob.180249. 

Lipman, R., B. Tripathi and R. Tripathi. (1988), “Cataracts induced by microwave and ionizing radiation”, Survey of Ophthalmology, Vol.33/3, Elsevier, Amsterdam, https://doi.org/10.1016/0039-6257(88)90088-4. 

Moreau, K. L. and J. A. King (2012), “Protein misfolding and aggregation in cataract disease and prospects for prevention”, Trends in Molecular Medicine, Vol. 18/5, Elsevier Ltd, England, https://doi.org/10.1016/j.molmed.2012.03.005 

Reisz, J. et al. (2014), “Effects of ionizing radiation on biological molecules - mechanisms of damage and emerging methods of detection”, Antioxidants and Redox Signaling, Vol.21(2), Mary Ann Liebert Inc, Larchmont, https://doi.org/10.1089/ars.2013.5489.  

Noble, J. E., & Bailey, M. J. A. (2009). Chapter 8 Quantitation of Protein. In Methods in Enzymology (Vol. 463, Issue C, pp. 73–95). Academic Press Inc.  

Toyama, B., & Hetzer, M. (2013). Protein homeostasis: Live long, won't prosper. Nature Reviews Molecular Cell Biology, 14(1), pp.55-61. 

Young, R. (1994). The family of sunlight-related eye diseases. Optometry and Vision Science, 71(2), pp.125-144. 

Event: 1634: Increase, Oxidative DNA damage

Short Name: Increase, Oxidative DNA damage

Key Event Component

AOPs Including This Key Event

Stressors

Biological Context

Cell term

Organ term

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability: Theoretically, DNA oxidation can occur in any cell type, in any organism. Oxidative DNA lesions have been measured in mammalian cells (human, mouse, calf, rat) in vitro and in vivo, and in prokaryotes.

Life stage applicability: This key event is not life stage specific (Mesa & Bassnett, 2013; Suman et al., 2019). 

Sex applicability: This key event is not sex specific (Mesa & Bassnett, 2013). 

Evidence for Perturbation by Prototypic Stressor: H₂O₂ and KBrO₃ – A concentration-dependent increase in oxidative lesions was observed in both Fpg- and hOGG1-modified comet assays of TK6 cells treated with increasing concentrations of glucose oxidase (an enzyme that generates H₂O₂) and potassium bromate for 4 h (Platel et al., 2011).  

Evidence indicates that oxidative DNA damage is also induced by X-rays (Bahia et al., 2018), ⁶⁰Co γ-rays, ¹²C ions, α particles, electrons (Georgakilas, 2013), UVB (Mesa and Bassnett, 2013), γ-rays, ⁵⁶Fe ions (Datta et al., 2012), and protons (Suman et al., 2019).  

Key Event Description

The nitrogenous bases of DNA are susceptible to oxidation in the presence of oxidizing agents. Oxidative adducts form mainly on C5 and to a lesser degree on C6 of thymine and cytosine, and on C8 of guanine and adenine. Guanine is most prone to oxidation due to its low oxidation potential (Jovanovic and Simic, 1986). Indeed, 8-oxo-2’-deoxyguanosine (8-oxodG)/8-hydroxy-2’-deoxyguanosine (8-OHdG) is the most abundant and well-studied oxidative DNA lesion in the cell (Swenberg et al., 2011). It causes an A(anti):8-oxo-G(syn) mispair instead of the normal C(anti):8-oxo-G(syn) pair. This pairing does not cause large structural changes to the DNA backbone, and therefore remains undetected by the polymerase’s proofreading mechanism. Consequently, one of the daughter strands will have an AT pair instead of the correct GC pair after replication (Markkanen, 2017). 

Formamidopyrimidine lesions on guanine and adenine (FaPyG and FaPyA), 8-hydroxy-2'-deoxyadenine (8-oxodA), and thymidine glycol (Tg) are other common oxidative lesions. We refer the reader to reviews on this topic to see the full set of potential oxidative DNA lesions (Whitaker et al., 2017). Oxidative DNA lesions are present in the cell at a steady state due to endogenous redox processes (Swenberg et al., 2010). Under normal conditions, cells are able to withstand the baseline level of oxidized bases through efficient repair and regulation of free radicals in the cell. However, direct chemical insult from specific compounds, exposure to various forms of radiation, or induction of reactive oxygen species (ROS) from the reduction of endogenous molecules, as well as through the release of inflammatory cell-derived oxidants, can lead to increased DNA oxidation, a state known as oxidative stress (Turner et al., 2002; Schoenfeld et al., 2012; Tangvarasittichai and Tangvarasittichai, 2019). It is worth noting that ROS must be generated near the DNA to cause damage, otherwise, if ROS was produced more distantly, then it can be removed by the cell (Nilsson & Liu, 2020). Furthermore, although cells do possess repair mechanisms to deal with oxidative DNA damage, sometimes the repair intermediates can interfere with genome function or decrease stability of the genome. This creates a balancing act between when it is best to repair damage and when it is best to leave it (Poetsch, 2020a). 

This KE describes an increase in oxidative lesions of a broad spectrum (ie. superoxide radical (O2•−), hydroxyl radical (OH), peroxyl radical (RO22), single oxygen (1O2 ) in the nuclear DNA above the steady-state level. Oxidative DNA damage can occur in any cell type with nuclear DNA under oxidative stress.

How it is Measured or Detected

Relative Quantification of Oxidative DNA Lesions

• Comet assay (single cell gel electrophoresis) with Fpg and hOGG1 modifications (Smith et al., 2006; Platel et al., 2011)
  • Oxoguanine glycosylase (hOGG1) and formamidopyrimidine-DNA glycosylase (Fpg) are base excision repair (BER) enzymes in eukaryotic and prokaryotic cells, respectively
  • Both enzymes are bi-functional; the glycosylase function cleaves the glycosidic bond between the ribose and the oxidized base, giving rise to an abasic site, and the apurinic/apymidinic (AP) site lyase function cleaves the phosphodiester bond via β-elimination reaction and creates a single strand break
  • Treatment of DNA with either enzyme prior to performing the electrophoresis step of the comet assay allows detection of oxidative lesions by measuring the increase in comet tail length when compared against untreated samples.
• Enzyme-linked immunosorbant assay (ELISA) (Dizdaroglu et al., 2002; Breton et al., 2003; Xu et al., 2008; Zhao et al. 2017)
  • 8-oxodG can be detected using immunoassays, such as ELISA, that use antibodies against 8-oxodG lesions. It has been noted that immunodetection of 8-oxodG can be interfered by certain compounds in biological samples.

Absolute Quantification of Oxidative DNA Lesions

• Quantification of 8-oxodG using HPLC-EC  (Breton et al., 2003; Chepelev et al., 2015)
  • 8-oxodG can be separated from digested DNA and precisely quantified using high performance liquid chromatography (HPLC) with electrochemical detection
• Mass spectrometry LC-MRM/MS (Mangal et al., 2009)
  • Liquid chromatography can also be coupled with multiple reaction monitoring/ mass spectrometry to detect and quantify oxidative lesions. Correlation between lesions measured by hOGG1-modified comet assay and LC-MS has been reported

Gas chromatography-mass spectrometry (GC-MS) 

• DNA is hydrolyzed to release either free bases or nucleosides and then undergoes derivatization in order to increase their volatility. Finally, samples run through a gas chromatograph and then a mass spectrometer. The mass spectrometer results are used to determine oxidative DNA damage by identifying modified bases or nucleosides (Dizdaroglu, 1994). 

Sequencing assays 

• Various markers are used to detect and highlight sites of DNA damage; the result is then processed and sequenced. This category encompasses a wide range of assays such as snAP-seq, OGG1-AP-seq, oxiDIP-seq, OG-seq, and click-code-seq (Yun et al., 2017; Wu et al., 2018; Amente et al., 2019; Poetsch, 2020b). 
• We note that other types of oxidative lesions can be quantified using the methods described above.

References

Amente, S. et al. (2019), “Genome-wide mapping of 8-oxo-7,8-dihydro-2’-deoxyguanosine reveals accumulation of oxidatively-generated damage at DNA replication origins within transcribed long genes of mammalian cells”, Nucleic Acids Research 2019, Vol. 47/1, Oxford University Press, England, https://doi.org/10.1093/nar/gky1152 

Bahia, S. et al. (2018), “Oxidative and nitrative stress-related changes in human lens epithelial cells following exposure to X-rays”, International journal of radiation biology, Vol. 94/4, England, https://doi.org/10.1080/09553002.2018.1439194 

Breton J, Sichel F, Bainchini F, Prevost V. (2003). Measurement of 8-Hydroxy-2′-Deoxyguanosine by a Commercially Available ELISA Test: Comparison with HPLC/Electrochemical Detection in Calf Thymus DNA and Determination in Human Serum. Anal Lett 36:123-134.

Cabrera, M. P., R. Chihuailaf and F. Wittwer Menge (2011), “Antioxidants and the integrity of ocular tissues”, Veterinary medicine international, Vol. 2011, SAGE-Hindawi Access to Research, United States, https://doi.org/10.4061/2011/905153 

Cadet, J. et al. (2012), “Oxidatively generated complex DNA damage: tandem and clustered lesions”, Cancer letters, Vol. 327/1, Elsevier Ireland Ltd, Ireland. https://doi.org/10.1016/j.canlet.2012.04.005 

Chepelev N, Kennedy D, Gagne R, White T, Long A, Yauk C, White P. (2015). HPLC Measurement of the DNA Oxidation Biomarker, 8-oxo-7,8-dihydro-2'-deoxyguanosine, in Cultured Cells and Animal Tissues. Journal of Visualized Experiments 102:e52697.

Collins, A. R. (2014), “Measuring oxidative damage to DNA and its repair with the comet assay”, Biochimica et biophysica acta. General subjects, Vol. 1840/2, Elsevier B.V., https://doi.org/10.1016/j.bbagen.2013.04.022 

Datta, K. et al. (2012), “Exposure to heavy ion radiation induces persistent oxidative stress in mouse intestive”, PloS One, Vol. 7/8, Public Library of Science, United States, https://doi.org/10.1371/journal.pone.0042224 

Dizdaroglu, M. (1994), “Chemical determination of oxidative DNA damage by gas chromatography-mass spectrometry”, Methods in Enzymology, Vol. 234, Elsevier Science & Technology, United States, https://doi.org/ 10.1016/0076-6879(94)34072-2 

Dizdaroglu, M. et al. (2002), “Free radical-induced damage to DNA : mechanisms and measurement”, Free radical biology & medicine, Vol. 32/11, United States, pp. 1102-1115 

Eaton, J. W. (1995), “UV-mediated cataractogenesis: a radical perspective”, Documenta ophthalmologica, Vol. 88/3-4, Springer, Dordrecht, https://doi.org/10.1007/BF01203677 

Fletcher, A. E. (2010), “Free radicals, antioxidants and eye diseases: evidence from epidemiological studies on cataract and age-related macular degeneration”, Ophthalmic Research, Vol. 44/3, Karger international, Basel, https://doi.org/10.1159/000316476 

Georgakilas, A. G et al. (2013), “Induction and repair of clustered DNA lesions: what do we know so far?”, Radiation Research, Vol. 180/1, The Radiation Research Society, United States, https://doi.org/10.1667/RR3041.1 

Jose, D. et al. (2009). “Spectroscopic studies of position-specific DNA “breathing” fluctuations at replication forks and primer-template junctions”, Proceedings of the National Academy of Sciences of the United States of America, Vol. 106/11, https://doi.org/10.1073/pnas.0900803106 

Jovanovic S, Simic M. (1986). One-electron redox potential of purines and pyrimidines. J Phys Chem 90:974-978.

Kruk, J., K. Kubasik-Kladna and H. Y. Aboul-Enein (2015), “The role oxidative stress in the pathogenesis of eye diseases: current status and a dual role of physical activity”, Mini-reviews in medicinal chemistry, Vol. 16/3, Bentham Science Publishers Ltd, Netherlands, https://doi.org/10.2174/1389557516666151120114605 

Lee, J. et al. (2004), “Reactive oxygen species, aging, and antioxidative nutraceuticals”, Comprehensive reviews in food science and food safety, Vol. 3/1, Blackwell Publishing Ltd, Oxford, https://doi.org/10.1111/j.1541-4337.2004.tb00058.x 

Mangal D, Vudathala D, Park J, Lee S, Penning T, Blair I. (2009). Analysis of 7,8-Dihydro-8-oxo-2′-deoxyguanosine in Cellular DNA during Oxidative Stress. Chem Res Toxicol 22:788-797.

Markkanen, E. (2017), “Not breathing is not an option: How to deal with oxidative DNA damage”, DNA repair, Vol. 59, Elsevier B.V., Netherlands, https://doi.org/10.1016/j.dnarep.2017.09.007 

Mesa, R. and S. Bassnett (2013), “UV-B induced DNA damage and repair in the mouse lens”, Investigative ophthalmology & visual science, Vol. 54/10, the Association for Research in Vision and Ophthalmology, United States, https://doi.org/10.1167/iovs.13-12644 

Nilsson R. and Liu N. (2020), “Nuclear DNA damages generated by reactive oxygen molecules (ROS) under oxidative stress and their relevance to human cancers, including ionizing radiation-induced neoplasia part I: Physical, chemical and molecular biology aspects”, Radiation Medicine and Protection, Vol. 1/3(3), https://doi.org/10.1016/j.radmp.2020.09.002 

Pendergrass, W. et al. (2010), “X-ray induced cataract is preceded by LEC loss, and coincident with accumulation of cortical DNA, and ROS; similarities with age-related cataracts”, Molecular vision, Vol. 16, Molecular Vision, United States, pp. 1496-1513 

Platel A, Nesslany F, Gervais V, Claude N, Marzin D. (2011). Study of oxidative DNA damage in TK6 human lymphoblastoid cells by use of the thymidine kinase gene-mutation assay and the in vitro modified comet assay: Determination of No-Observed-Genotoxic-Effect-Levels. Mutat Res 726:151-159.

Poetsch, Anna R. (2020a), “The genomics of oxidative DNA damage, repair, and resulting mutagenesis”, Computational and structural biotechnology journal 2020, Vol. 18, Elsevier B.V., Netherlands https://doi.org/10.1016/j.csbj.2019.12.013 

Poetsch, A. R. (2020b), “AP-Seq: A method to measure apurinic sites and small base adducts genome-wide”, The Nucleus, Springer US, New York, Sacca, S. C. et al. (2009), “Gene-environment interactions in ocular diseases”, Mutation research – fundamental and molecular mechanisms of mutagenesis, Vol. 667/1-2, Elsevier, Amsterdam, https://doi.org/10.1016/j.mrfmmm.2008.11.002 

Schoenfeld, M. P. et al. (2012), “A hypothesis on biological protection from space radiation through the use of new therapeutic gases as medical counter measures”, Medical gas research, Vol. 2/1, BioMed Central Ltd, India, https://doi.org/10.1186/2045-9912-2-8 

Smith C, O'Donovan M, Martin E. (2006). hOGG1 recognizes oxidative damage using the comet assay with greater specificity than FPG or ENDOIII. Mutagenesis 21:185-190.

Stohs, S. J. (1995), “The role of free radicals in toxicity and disease”, Journal of Basic and Clinical Physiology and Pharmacology, Vol. 6/3-4, Freund Publishing House Ltd, https://doi.org/10.1515/JBCPP.1995.6.3-4.205 

Suman, S. et al. (2019), “Fractionated and acute proton radiation show differential intestinal tumorigenesis and DNA damage and repair pathway response in ApcMin/+ mice”, International Journal of Radiation Oncology, Biology, Physics, Vol. 105/3, Elsevier Inc, https://doi.org/10.1016/j.ijrobp.2019.06.2532 

Swenberg J. et al. (2011). "Endogenous versus Exogenous DNA Adducts: Their Role in Carcinogenesis, Epidemiology, and Risk Assessment." Toxicol Sci 120:S130-S145.

Tangvarasittichai, O and S. Tangvarasittichai (2018), “Oxidative stress, ocular disease, and diabetes retinopathy”, Current Pharmaceutical Design, Vol. 24/40, Bentham Science Publishers, https://doi.org/10.2174/1381612825666190115121531 

Turner, N. D. et al. (2002), “Opportunities for nutritional amelioration of radiation-induced cellular damage”, Nutrition, Vol. 18/10, Elsevier Inc, New York, https://doi.org/10.1016/S0899-9007(02)00945-0 

Whitaker A, Schaich M, Smith MS, Flynn T, Freudenthal B. (2017). Base excision repair of oxidative DNA damage: from mechanism to disease. Front Biosci 22:1493-1522.

Wu, J. (2018), “Nucleotide-resolution genome-wide mapping of oxidative DNA damage by click-code-seq”, Journal of the American Chemical Society 2018, American Chemical Society, United States https://doi-org.proxy.bib.uottawa.ca/10.1021/jacs.8b03715 

Xu, X. et al. (2008). “Fluorescence recovery assay for the detection of protein-DNA binding”, Analytical Chemistry, Vol. 80/14, https://doi.org/10.1021/ac8007016 

Zhao M, Howard E, Guo Z, Parris A, Yang X. (2017). p53 pathway determines the cellular response to alcohol-induced DNA damage in MCF-7 breast cancer cells. PLoS One 12:e0175121.

Event: 1635: Increase, DNA strand breaks

Short Name: Increase, DNA strand breaks

Key Event Component

AOPs Including This Key Event

Stressors

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability: DNA strand breaks are relevant to all species, including vertebrates such as humans, that contain DNA (Cannan & Pederson, 2016).  

Life stage applicability: This key event is not life stage specific as all life stages display strand breaks. However, there is an increase in baseline levels of DNA strand breaks seen in older individuals though it is unknown whether this change due to increased break induction or a greater retention of breaks due to poor repair (White & Vijg, 2016). 

Sex applicability: This key event is not sex specific as both sexes display evidence of strand breaks. In some cell types, such as peripheral blood mononuclear cells, males show higher levels of single strand breaks than females (Garm et al., 2012). 

Evidence for perturbation by a stressor: There are studies demonstrating that increased DNA strand breaks can result from exposure to multiple stressor types including ionizing & non-ionizing radiation, chemical agents, and oxidizing agents (EPRI, 2014; Hamada, 2014; Cencer et al., 2018; Cannan & Pederson, 2016; Yang et al., 1998).  

Key Event Description

DNA strand breaks are a type of damage resulting from the hydrolysis of phosphodiester groups in the backbone of DNA molecules (Gates, 2009) and can occur on a single strand (single strand breaks; SSBs) or both strands (double strand breaks; DSBs). SSBs arise when the sugar phosphate backbones connecting adjacent nucleotides in DNA are simultaneously hydrolyzed such that the hydrogen bonds between complementary bases are not able to hold the two strands together. DSBs are generated when both strands are simultaneously broken at sites that are sufficiently close to one another that base-pairing and chromatin structure are insufficient to keep the two DNA ends juxtaposed. As a consequence, the two DNA ends generated by a DSB can physically dissociate from one another, becoming difficult to repair and increasing the chance of inappropriate recombination with other sites in the genome (Jackson, 2002). SSB can turn into DSB if the replication fork stalls at the lesion leading to fork collapse. Strand breaks are intermediates in various biological events, including DNA repair (e.g., excision repair), as well as other normal cellular processes where DSBs act as genetic shufflers to generate genetic diversity for V(D)J recombination in lymphoid cells, and chromatin remodeling in both somatic cells and germ cells, and meiotic recombination in gametes. 

Strand breaks are intermediates in various biological events, including DNA repair (e.g., excision repair), V(D)J recombination in developing lymphoid cells and chromatin remodeling in both somatic cells and germ cells. The spectrum of damage can be complex, particularily if the stressor is from large amounts of deposited energy which can result in complex lesions and clustered damage defined as two or more oxidized bases, abasic sites or starnd breaks on opposing DNA strands within a few helical turns. These lesions are more difficult to repair and have been studied in many types of models (Barbieri et al., 2019 and Asaithamby et al., 2011). DSBs and complex lesions are of particular concern, as they are considered the most lethal and deleterious type of DNA lesion. If misrepaired or left unrepaired, DSBs may drive the cell towards genomic instability, apoptosis or tumorigenesis (Beir, 1999). 

How it is Measured or Detected

Please refer to the table below for details regarding these and other methodologies for detecting DNA DSBs. 

Method of Measurement	References	Description	OECD Approved Method?
Comet Assay (Single Cell Gel Eletrophoresis - Alkaline)	Collins, 2004; Olive and Banath, 2006; Platel et al., 2011; Nikolova et al., 2017	To detect SSBs or DSBs, single cells are encapsulated in agarose on a slide, lysed, and subjected to gel electrophoresis at an alkaline pH (pH >13); DNA fragments are forced to move, forming a "comet"-like appearance	Yes
γ-H2AX Foci Quantification - Flow Cytometry	Rothkamm and Horn, 2009; Bryce et al., 2016	Measurement of γ-H2AX immunostaining in cells by flow cytometry, normalized to total levels of H2AX	No
γ-H2AX Foci Quantification - Western Blot	Burma et al., 2001; Revet et al., 2011	Measurement of γ-H2AX immunostaining in cells by Western blotting, normalized to total levels of H2AX	No
γ-H2AX Foci Quantification - Microscopy	Redon et al., 2010; Mah et al., 2010; Garcia-Canton et al., 2013	Quantification of γ-H2AX immunostaining by counting γ-H2AX foci visualized with a microscope	No
γ-H2AX Foci Quantification - ELISA	Ji et al., 2017	Measurement of γ-H2AX in cells by ELISA, normalized to total levels of H2AX	No
Pulsed Field Gel Electrophoresis (PFGE)	Ager et al., 1990; Gardiner et al., 1985; Herschleb et al., 2007; Kawashima et al., 2017	To detect DSBs, cells are embedded and lysed in agarose, and the released DNA undergoes gel electrophoresis in which the direction of the voltage is periodically alternated; Large DNA fragments are thus able to be separated by size	No
The TUNEL (Terminal Deoxynucleotidyl Transferase dUTP Nick End Labeling) Assay	Loo, 2011	To detect strand breaks, dUTPs added to the 3’OH end of a strand break by the DNA polymerase terminal deoxynucleotidyl transferase (TdT) are tagged with a fluorescent dye or a reporter enzyme to allow visualization	No
In Vitro DNA Cleavage Assays using Topoisomerase	Nitiss, 2012	Cleavage of DNA can be achieved using purified topoisomerase; DNA strand breaks can then be separated and quantified using gel electrophoresis	No
PCR assay	Figueroa‑González & Pérez‑Plasencia, 2017	Assay of strand breaks through the observation of DNA amplification prevention. Breaks block Taq polymerase, reducing the number of DNA templates, preventing amplification	No
Sucrose density gradient centrifuge	Raschke et al. 2009	Division of DNA pieces by density, increased fractionation leads to lower density pieces, with the use of a sucrose cushion	No
Alkaline Elution Assay	Kohn, 1991	Cells lysed with detergent-solution, filtered through membrane to remove all but intact DNA	No
Unwinding Assay	Nacci et al. 1992	DNA is stored in alkaline solutions with DNA-specific dye and allowed to unwind following removal from tissue, increased strand damage associated with increased unwinding	Yes
STRIDE assay	Zilio and Ulrich, 2021	STRIDE (SensiTive Recognition of Individual DNA Ends) combines in situ nick translation with the proximity ligation assay (PLA) to detect single-strand breaks (sSTRIDE) or double-strand breaks (dSTRIDE). In this process, lesions labeled through nick translation with biotinylated nucleotides are identified by a PLA signal, which arises from the interaction of two anti-biotin antibodies from different species.	No
sBLISS	Bouwmann et al. 2020	sBLISS (in-suspension breaks labeling in situ and sequencing)  labels double-strand breaks (DSBs) in cells immobilized on glass coverslips, using double-stranded oligonucleotide adaptors that facilitate selective linear amplification through T7-mediated in vitro transcription (IVT), followed by next-generation sequencing (NGS) library preparation	No

References

Ager, D. D., et al. (1990). Measurement of radiation-induced DNA double-strand breaks by pulsed-field gel electrophoresis. Radiation research, 122/(2), 181–187. 

Anderson, D. & Laubenthal J. (2013), “Analysis of DNA Damage via Single-Cell Electrophoresis. In: Makovets S, editor. DNA Electrophoresis. Totowa.”, NJ: Humana Press. p 209-218. 

Asaithamby, A., B. Hu and D.J. Chen. (2011) “Unrepaired clustered DNA lesions induce chromosome breakage in human cells.” Proc Natl Acad Sci U S A 108(20): 8293-8298 . 

Barbieri, S., G. Babini, J. Morini et a l (2019). . Predicting DNA damage foci and their experimental readout with 2D microscopy: a unified approach applied to photon and neutron exposures. Scientific Reports 9(1): 14019 

Bouwman, B. et al. (2020), “Genome-wide detection of DNA double-strand breaks by in-suspension BLISS”, Nature protocols,.15/12, Springer Nature, London, https://doi.org/10.1038/s41596-020-0397-2  

Bryce, S. et al. (2016), “Genotoxic mode of action predictions from a multiplexed flow cytometric assay and a machine learning approach.”, Environ Mol Mutagen. 57:171-189. Doi: 10.1002/em.21996. 

Burma, S. et al. (2001), “ATM phosphorylates histone H2AX in response to DNA double-strand breaks.”, J Biol Chem, 276(45): 42462-42467. doi:10.1074/jbc.C100466200 

Cannan, W.J. and D.S. Pederson (2016), "Mechanisms and Consequences of Double-Strand DNA Break Formation in Chromatin.", Journal of Cellular Physiology, Vol.231(/1), Wiley, New York, https://doi.org/10.1002/jcp.25048.  

Cencer, C. et al. (2018), “PARP-1/PAR Activity in Cultured Human Lens Epithelial Cells Exposed to Two Levels of UVB Light”, Photochemistry and Photobiology, Vol.(94/1), Wiley-Blackwell, Hoboken, https://doi.org/10.1111/php.12814.  

Charlton, E. D. et al. (1989), “Calculation of Initial Yields of Single and Double Stranded Breaks in Cell Nuclei from Electrons, Protons, and Alpha Particles.”, Int. J. Radiat. Biol. 56(1): 1-19. doi: 10.1080/09553008914551141. 

Collins, R. A. (2004), “The Comet Assay for DNA Damage and Repair. Molecular Biotechnology.”, Mol Biotechnol. 26(3): 249-61. doi:10.1385/MB:26:3:249 

EPRI (2014), Epidemiology and mechanistic effects of radiation on the lens of the eye: Review and scientific appraisal of the literature, EPRI, California. 

Figueroa‑González, G. and C. Pérez‑Plasencia. (2017), “Strategies for the evaluation of DNA damage and repair mechanisms in cancer”, Oncology Letters, Vol.133(/6), Spandidos Publications, Athens, https://doi.org/10.3892/ol.2017.6002. 

Garcia-Canton, C. et al. (2013), “Assessment of the in vitro p-H2AX assay by High Content Screening asa novel genotoxicity test.”, Mutat Res. 757:158-166. Doi: 10.1016/j.mrgentox.2013.08.002 

Gardiner, K. et al. (1986), “Fractionation of Large Mammalian DNA Restriction Fragments Using Vertical Pulsed-Field Gradient Gel Electrophoresis.”, Somatic Cell and Molecular Genetics. 12(2): 185-95.Doi: 10.1007/bf01560665. 

Garm, C. et al. (2012), “Age and gender effects on DNA strand break repair in peripheral blood mononuclear cells”, Aging Cell, Vol.12/1, Blackwell Publishing Ltd, Oxford, https://doi.org/10.1111/acel.12019. 

Hamada, N. (2014), “What are the intracellular targets and intratissue target cells for radiation effects?”, Radiation research, Vol. 181/1, The Radiation Research Society, Indianapolis, https://doi.org/10.1667/RR13505.1. 

Herschleb, J. et al. (2007), “Pulsed-field gel electrophoresis.”, Nat Protoc. 2(3): 677-684. doi:10.1038/nprot.2007.94 

Iliakis, G. et al. (2015), “Alternative End-Joining Repair Pathways Are the Ultimate Backup for Abrogated Classical Non-Homologous End-Joining and Homologous Recombination Repair: Implications for the Formation of Chromosome Translocations.”, Mutation Research/Genetic Toxicology and Environmental Mutagenesis. 2(3): 677-84. doi: 10.1038/nprot.2007.94 

Jackson, S. (2002). “Sensing and repairing DNA double-strand breaks.”, Carcinogenesis. 23:687-696. Doi:10.1093/carcin/23.5.687. 

Ji, J. et al. (2017), “Phosphorylated fraction of H2AX as a measurement for DNA damage in cancer cells and potential applications of a novel assay.”, PLoS One. 12(2): e0171582. doi:10.1371/journal.pone.0171582 

Kawashima, Y.(2017), “Detection of DNA double-strand breaks by pulsed-field gel electrophoresis.”, Genes Cells 22:84-93. Doi: 10.1111/gtc.12457. 

Khoury, L. et al. (2013), “Validation of high-throughput genotoxicity assay screening using cH2AX in-cell Western assay on HepG2 cells.”, Environ Mol Mutagen, 54:737-746. Doi: 10.1002/em.21817. 

Khoury, L. et al. (2016), “Evaluation of four human cell lines with distinct biotransformation properties for genotoxic screening.”, Mutagenesis, 31:83-96. Doi: 10.1093/mutage/gev058. 

Kohn, K.W. (1991), “Principles and practice of DNA filter elution”, Pharmacology & Therapeutics, Vol.49(/1), Elsevier, Amsterdam, https://doi.org/10.1016/0163-7258(91)90022-E. 

Loo, DT. (2011), “In Situ Detection of Apoptosis by the TUNEL Assay: An Overview of Techniques. In: Didenko V, editor. DNA Damage Detection In Situ, Ex Vivo, and In Vivo. Totowa.”, NJ: Humana Press. p 3-13.doi: 10.1007/978-1-60327-409-8_1. 

Mah, L. J. et al. (2010), “Quantification of gammaH2AX foci in response to ionising radiation.”, J Vis Exp(38). doi:10.3791/1957. 

Nacci, D. et al. (1992), “Application of the DNA alkaline unwinding assay to detect DNA strand breaks in marine bivalves”, Marine Environmental Research, Vol.33(/2), Elsevier BV, Amsterdam, https://doi.org/10.1016/0141-1136(92)90134-8. 

Nikolova, T., F. et al. (2017), “Genotoxicity testing: Comparison of the γH2AX focus assay with the alkaline and neutral comet assays.”, Mutat Res 822:10-18. Doi: 10.1016/j.mrgentox.2017.07.004. 

Nitiss, J. L. et al. (2012), “Topoisomerase assays. ”, Curr Protoc Pharmacol. Chapter 3: Unit 3 3. 

OECD. (2014). Test No. 489: “In vivo mammalian alkaline comet assay.” OECD Guideline for the Testing of Chemicals, Section 4 . 

Olive, P. L., & Banáth, J. P. (2006), “The comet assay: a method to measure DNA damage in individual cells.”, Nature Protocols. 1(1): 23-29. doi:10.1038/nprot.2006.5. 

Platel A. et al. (2011), “Study of oxidative DNA damage in TK6 human lymphoblastoid cells by use of the thymidine kinase gene-mutation assay and the in vitro modified comet assay: Determination of No-Observed-Genotoxic-Effect-Levels.”, Mutat Res 726:151-159. Doi: 10.1016/j.mrgentox.2011.09.003. 

Raschke, S., J. Guan and G. Iliakis. (2009), “Application of alkaline sucrose gradient centrifugation in the analysis of DNA replication after DNA damage”, Methods in Molecular Biology, Vol.521, Humana Press, Totowa, https://doi.org/10.1007/978-1-60327-815-7_18. 

Redon, C. et al. (2010), “The use of gamma-H2AX as a biodosimeter for total-body radiation exposure in non-human primates.”, PLoS One. 5(11): e15544. doi:10.1371/journal.pone.0015544 

Revet, I. et al. (2011), “Functional relevance of the histone γH2Ax in the response to DNA damaging agents.” Proc Natl Acad Sci USA.108:8663-8667. Doi: 10.1073/pnas.1105866108 

Rogakou, E.P. et al. (1998), “DNA Double-stranded Breaks Induce Histone H2AX Phosphorylation on Serine 139.” , J Biol Chem, 273:5858-5868. Doi: 10.1074/jbc.273.10.5858 

Rothkamm, K. & Horn, S. (2009), “γ-H2AX as protein biomarker for radiation exposure.”, Ann Ist Super Sanità, 45(3): 265-71. 

White, R.R. and J. Vijg. (2016), “Do DNA Double-Strand Breaks Drive Aging?”, Molecular Cell, Vol.63, Elsevier, Amsterdam, http://doi.org/10.1016/j.molcel.2016.08.004. 

Yang, Y. et al. (1998), “The effect of catalase amplification on immortal lens epithelial cell lines”, Experimental Eye Research, Vol.67(/6), Academic Press Inc, Cambridge, https://doi.org/10.1006/exer.1998.0560.  

Zilio, N. and H. D. Ulrich (2021), “Exploring the SSBreakome: genome-wide mapping of DNA single-strand breaks by next-generation sequencing”, The FEBS journal, 288(13), Wiley, Hoboken, https://doi.org/10.1111/febs.15568 

 

Event: 155: Inadequate DNA repair

Short Name: Inadequate DNA repair

Key Event Component

AOPs Including This Key Event

Stressors

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

The retention of adducts has been directly measured in many different types of eukaryotic somatic cells (in vitro and in vivo). In male germ cells, work has been done on hamsters, rats and mice. The accumulation of mutation and changes in mutation spectrum has been measured in mice and human cells in culture. Theoretically, saturation of DNA repair occurs in every species (prokaryotic and eukaryotic). The principles of this work were established in prokaryotic models. Nagel et al. (2014) have produced an assay that directly measures DNA repair in human cells in culture.

NHEJ is primarily used by vertebrate multicellular eukaryotes, but it also been observed in plants. Furthermore, it has recently been discovered that some bacteria (Matthews et al., 2014) and yeast (Emerson et al., 2016) also use NHEJ. In terms of invertebrates, most lack the core DNA-PK_cs and Artemis proteins; they accomplish end joining by using the RA50:MRE11:NBS1 complex (Chen et al., 2001).  HR occurs naturally in eukaryotes, bacteria, and some viruses (Bhatti et al., 2016).

Taxonomic applicability: Inadequate DNA repair is applicable to all species, as they all contain DNA (White & Vijg, 2016).  

Life stage applicability: This key event is not life stage specific as any life stage can have poor repair, though as individuals age their repair process become less effective (Gorbunova & Seluanov, 2016). 

Sex applicability: There is no evidence of sex-specificity for this key event, with initial rate of DNA repair not significantly different between sexes (Trzeciak et al., 2008). 

Evidence for perturbation by a stressor: Multiple studies demonstrate that inadequate DNA repair can occur as a result of stressors such as ionizing and non-ionizing radiation, as well as chemical agents (Kuhne et al., 2005; Rydberg et al., 2005; Dahle et al., 2008; Seager et al., 2012; Wilhelm, 2014; O’Brien et al., 2015).  

Key Event Description

DNA lesions may result from the formation of DNA adducts (i.e., covalent modification of DNA by chemicals), or by the action of agents such as radiation that may produce strand breaks or modified nucleotides within the DNA molecule. These DNA lesions are repaired through several mechanistically distinct pathways that can be categorized as follows:

1. Damage reversal acts to reverse the damage without breaking any bonds within the sugar phosphate backbone of the DNA. The most prominent enzymes associated with damage reversal are photolyases (Sancar, 2003) that can repair UV dimers in some organisms, and O6-alkylguanine-DNA alkyltransferase (AGT) (Pegg 2011) and oxidative demethylases (Sundheim et al., 2008), which can repair some types of alkylated bases.
2. Excision repair involves the removal of a damaged nucleotide(s) through cleavage of the sugar phosphate backbone followed by re-synthesis of DNA within the resultant gap. Excision repair of DNA lesions can be mechanistically divided into: 

   a) Base excision repair (BER) (Dianov and Hübscher, 2013), in which the damaged base is removed by a damage-specific glycosylase prior to incision of the phosphodiester backbone at the resulting abasic site. This leads to an intermediate that contains a DNA strand break, whereby DNA ligase is then recruited to seal the ends of the DNA.

   b) Nucleotide excision repair (NER) (Schärer, 2013), in which the DNA strand containing the damaged nucleotide is incised at sites several nucleotides 5’ and 3’ to the site of damage, and a polynucleotide containing the damaged nucleotide is removed prior to DNA resynthesis within the resultant gap and sealing of the ends by DNA ligase.  

   c) Mismatch repair (MMR) (Li et al., 2016)  which does not act on DNA lesions but does recognize mispaired bases resulting from replication errors. In MMR the strand containing the misincorporated base is removed prior to DNA resynthesis.

   The major pathway that removes oxidative DNA damage is base excision repair (BER), which can be either monofunctional or bifunctional; in mammals, a specific DNA glycosylase (OGG1: 8-Oxoguanine glycosylase) is responsible for excision of 8-oxoguanine (8-oxoG) and other oxidative lesions (Hu et al., 2005; Scott et al., 2014; Whitaker et al., 2017). We note that long-patch BER is used for the repair of clustered oxidative lesions, which uses several enzymes from DNA replication pathways (Klungland and Lindahl, 1997). These pathways are described in detail in various reviews e.g., (Whitaker et al., 2017). 

3. Single strand break repair (SSBR) involves different proteins and enzymes depending on the origin of the SSB (e.g., produced as an intermediate in excision repair or due to direct chemical insult) but the same general steps of repair are taken for all SSBs: detection, DNA end processing, synthesis, and ligation (Caldecott, 2014). Poly-ADP-ribose polymerase1 (PARP1) detects and binds unscheduled SSBs (i.e., not deliberately induced during excision repair) and synthesizes PAR as a signal to the downstream factors in repair. PARP1 is not required to initiate SSBR of BER intermediates. The XRCC1 protein complex is then recruited to the site of damage where a common DNA intermediate as BER was generated, and acts as a scaffold for proteins and enzymes required for repair. Depending on the nature of the damaged termini of the DNA strand, different enzymes are required for end processing to generate the substrates that DNA polymerase β (Polβ; short patch repair) or Pol δ/ε (long patch repair) can bind to synthesize over the gap, although end processing is generally done by polynucleotide kinase. Synthesis in long-patch repair displaces a single stranded flap which is excised by flap endonuclease 1 (FEN1). In short-patch repair, the XRCC1/Lig3α complex joins the two ends after synthesis. In long-patch repair, the PCNA/Lig1 complex ligates the ends. (Caldecott, 2014). 
4. Double strand break repair (DSBR) is necessary to preserve genomic integrity when breaks occur in both strands of a DNA molecule. There are two major pathways for DSBR: homologous recombination (HR), which operates primarily during the S phase of dividing cell types, and nonhomologous end joining (NHEJ), which can function in both dividing and non-dividing cell types. No repair occurs in the M phase (Teruaki Iyama and David M. Wilson III, 2013). DNA repair in mitosis is controversial (Mladenov et al., 2023).

Complex lesions can be created by a single mutagen and can be more difficult to repair, as the mechanism behind how different repair pathways cooperate to address this is still unclear (Aleksandrov et al., 2018). In higher eukaryotes such as mammals, NHEJ is usually the preferred pathway for DNA DSBR. Its use, however, is dependent on the cell type, the gene locus, and the nuclease platform (Miyaoka et al., 2016). The use of NHEJ is also dependent on the cell cycle; NHEJ is generally not the pathway of choice when the cell is in the late S or G2 phase of the cell cycle, or in mitotic cells when the sister chromatid is directly adjacent to the double-strand break (DSB) (Lieber et al., 2003). In these cases, the HR pathway is commonly used for repair of DSBs. Despite this, NHEJ is still used more commonly than HR in human cells. Classical NHEJ (C-NHEJ) is the most common NHEJ repair mechanism, but alternative NHEJ (alt-NHEJ) can also occur, especially in the absence of C-NHEJ and HR.

The process of C-NHEJ in humans requires at least seven core proteins: Ku70, Ku86, DNA-dependent protein kinase complex (DNA-PK_cs ), Artemis, X-ray cross-complementing protein 4 (XRCC4), XRCC4-like factor (XLF), and DNA ligase IV (Boboila et al., 2012). When DSBs occur, the Ku proteins, which have a high affinity for DNA ends, will bind to the break site and form a heterodimer. This protects the DNA from exonucleolytic attack and acts to recruit DNA-PK_cs, the catalytic subunit, thus forming a trimeric complex on the ends of the DNA strands. Alternative NHEJ, or alt NHEJ, uses small similar sequences in two broken DNA ends to join them together. Unlike the usual repair method (cNHEJ), aNHEJ doesn't need specific proteins like LIG4 and KU. Instead, it relies on the MRN complex to process the breaks. However, alt NHEJ tends to cause mutations by adding or removing bits of DNA during the repair (Chaudhuri and Nussenzweig, 2017). The kinase activity of DNA-PK_cs is then triggered, causing DNA-PK_cs to auto-phosphorylate and thereby lose its kinase activity; the now phosphorylated DNA-PK_cs dissociates from the DNA-bound Ku proteins. The free DNA-PK_cs phosphorylates Artemis, an enzyme that possesses 5’-3’ exonuclease and endonuclease activity in the presence of DNA-PK_cs and ATP. Artemis is responsible for ‘cleaning up’ the ends of the DNA. For 5’ overhangs, Artemis nicks the overhang, generally leaving a blunt duplex end. For 3’ overhangs, Artemis will often leave a four- or five-nucleotide single stranded overhang (Pardo et al., 2009; Fattah et al., 2010; Lieber et al., 2010). Next, the XLF and XRCC4 proteins form a complex which makes a channel to bind DNA and aligns the ends for efficient ligation via DNA ligase IV (Hammel et al., 2011).

The process of alt-NHEJ is less well understood than C-NHEJ and is a lower fidelity mechanism.  Alt-NHEJ is known to involve slightly different core proteins than C-NHEJ and required microhomology repeats, but the steps of the pathway are essentially the same between the two processes (reviewed in Chiruvella et al., 2013). It is established, however, that alt-NHEJ is more error-prone in nature than C-NHEJ, which contributes to incorrect DNA repair. Alt-NHEJ is thus considered primarily to be a backup repair mechanism (reviewed in Chiruvella et al., 2013). 

In contrast to NHEJ, HR takes advantage of similar or identical DNA sequences to repair DSBs and is not error-prone (Sung and Klein, 2006). The initiating step of HR is the creation of a 3’ single strand DNA (ss-DNA) overhang. Combinases such as RecA and Rad51 then bind to the ss-DNA overhang, and other accessory factors, including Rad54, help recognize and invade the homologous region on another DNA strand. From there, DNA polymerases are able to elongate the 3’ invading single strand and resynthesize the broken DNA strand using the corresponding sequence on the homologous strand.

 

Fidelity of DNA Repair

Most DNA repair pathways are extremely efficient. However, in principal, all DNA repair pathways can be overwhelmed when the DNA lesion burden exceeds the capacity of a given DNA repair pathway to recognize and remove the lesion. Exceeded repair capacity may lead to toxicity or mutagenesis following DNA damage. Apart from extremely high DNA lesion burden, inadequate repair may arise through several different specific mechanisms. For example, during repair of DNA containing O6-alkylguanine adducts, AGT irreversibly binds a single O6-alkylguanine lesion and as a result is inactivated (this is termed suicide inactivation, as its own action causes it to become inactivated). Thus, the capacity of AGT to carry out alkylation repair can become rapidly saturated when the DNA repair rate exceeds the de novo synthesis of AGT (Pegg, 2011).

A second mechanism relates to cell specific differences in the cellular levels or activity of some DNA repair proteins. For example, XPA is an essential component of the NER complex. The level of XPA that is active in NER is low in the testes, which may reduce the efficiency of NER in testes as compared to other tissues (Köberle et al., 1999). Likewise, both NER and BER have been reported to be deficient in cells lacking functional p53 (Adimoolam and Ford, 2003; Hanawalt et al., 2003; Seo and Jung, 2004). A third mechanism relates to the importance of the DNA sequence context of a lesion in its recognition by DNA repair enzymes. For example, 8-oxoguanine (8-oxoG) is repaired primarily by BER; the lesion is initially acted upon by a bifunctional glycosylase, OGG1, which carries out the initial damage recognition and excision steps of 8-oxoG repair. However, the rate of excision of 8-oxoG is modulated strongly by both chromatin components (Menoni et al., 2012) and DNA sequence context (Allgayer et al., 2013) leading to significant differences in the repair of lesions situated in different chromosomal locations.

DNA repair is also remarkably error-free. However, misrepair can arise during repair under some circumstances. DSBR is notably error prone, particularly when breaks are processed through NHEJ, during which partial loss of genome information is common at the site of the double strand break (Iyama and Wilson, 2013). This is because NHEJ rejoins broken DNA ends without the use of extensive homology; instead, it uses the microhomology present between the two ends of the DNA strand break to ligate the strand back into one. When the overhangs are not compatible, however, indels (insertion or deletion events), duplications, translocations, and inversions in the DNA can occur. These changes in the DNA may lead to significant issues within the cell, including alterations in the gene determinants for cellular fatality (Moore et al., 1996).

Activation of mutagenic DNA repair pathways to withstand cellular or replication stress either from endogenous or exogenous sources can promote cellular viability, albeit at a cost of increased genome instability and mutagenesis (Fitzgerald et al., 2017). These salvage DNA repair pathways including, Break-induced Replication (BIR) and Microhomology-mediated Break-induced Replication (MMBIR). BIR repairs one-ended DSBs and has been extensively studied in yeast as well as in mammalian systems. BIR and MMBIR are linked with heightened levels of mutagenesis, chromosomal rearrangements and ensuing genome instability (Deem et al., 2011; Sakofsky et al., 2015; Saini et al., 2017; Kramara et al., 2018). In mammalian genomes BIR-like synthesis has been proposed to be involved in late stage Mitotic DNA Synthesis (MiDAS) that predominantly occurs at so-called Common Fragile Sites (CFSs) and maintains telomere length under s conditions of replication stress that serve to promote cell viability (Minocherhomji et al., 2015; Bhowmick et al., 2016; Dilley et al., 2016).       

Misrepair may also occur through other repair pathways. Excision repair pathways require the resynthesis of DNA and rare DNA polymerase errors during gap resynthesis will result in mutations (Brown et al., 2011). Errors may also arise during gap resynthesis when the strand that is being used as a template for DNA synthesis contains DNA lesions (Kozmin and Jinks-Robertson, 2013). In addition, it has been shown that sequences that contain tandemly repeated sequences, such as CAG triplet repeats, are subject to expansion during gap resynthesis that occurs during BER of 8-oxoG damage (Liu et al., 2009).

How it is Measured or Detected

There is no test guideline for this event. The event is usually inferred from measuring the retention of DNA adducts or the creation of mutations as a measure of lack of repair or incorrect repair. These ‘indirect’ measures of its occurrence are crucial to determining the mechanisms of genotoxic chemicals and for regulatory applications (i.e., determining the best approach for deriving a point of departure). More recently, a fluorescence-based multiplex flow-cytometric host cell reactivation assay (FM-HCR) has been developed to directly measure the ability of human cells to repair plasmid reporters (Nagel et al., 2014).

Indirect Measurement

In somatic and spermatogenic cells, measurement of DNA repair is usually inferred by measuring DNA adduct formation/removal. Insufficient repair is inferred from the retention of adducts and from increasing adduct formation with dose. Insufficient DNA repair is also measured by the formation of increased numbers of mutations and alterations in mutation spectrum. The methods will be specific to the type of DNA adduct that is under study.

Some EXAMPLES are given below for alkylated DNA.

DOSE-RESPONSE CURVE FOR ALKYL ADDUCTS/MUTATIONS: It is important to consider that some adducts are not mutagenic at all because they are very effectively repaired. Others are effectively repaired, but if these repair processes become overwhelmed mutations begin to occur. The relationship (shape of dose-response curve) between exposure to mutagenic agents and mutations provide an indication of whether the removal of adducts occurs, and whether it is more efficient at low doses. Sub-linear dose-response curves (hockey stick or j-shape curves) for mutation induction indicates that adducts are not converted to mutations at low doses. This suggests the effective repair of adducts at low doses, followed by saturation of repair at higher doses (Clewell et al., 2019). Thus, measurement of a clear point of inflection in the dose-response curve for mutations suggests that repair does occur, at least to some extent, at low dosees but that reduced repair efficiency arises above the inflection point. A lack of increase in mutation frequencies (i.e., flat line for dose-response) for a compound showing a dose-dependent increase in adducts would imply that the adducts formed are either not mutagenic or are effectively repaired.

RETENTION OF ALKYL ADDUCTS: Alkylated DNA can be found in cells long after exposure has occurred. This indicates that repair has not effectively removed the adducts. For example, DNA adducts have been measured in hamster and rat spermatogonia several days following exposure to alkylating agents, indicating lack of repair (Seiler et al., 1997; Scherer et al., 1987).

MUTATION SPECTRUM: Shifts in mutation spectrum (i.e., the specific changes in the DNA sequence) following a chemical exposure (relative to non-exposed mutation spectrum) indicates that repair was not operating effectively to remove specific types of lesions. The shift in mutation spectrum is indicative of the types of DNA lesions (target nucleotides and DNA sequence context) that were not repaired. For example, if a greater proportion of mutations occur at guanine nucleotides in exposed cells, it can be assumed that the chemical causes DNA adducts on guanine that are not effectively repaired.

Direct Measurement

Nagel et al. (2014) we developed a fluorescence-based multiplex flow-cytometric host cell reactivation assay (FM-HCR) to measures the ability of human cells to repair plasmid reporters. These reporters contain different types and amounts of DNA damage and can be used to measure repair through by NER, MMR, BER, NHEJ, HR and MGMT.

Please refer to the table below for additional details and methodologies for detecting DNA damage and repair.

Assay Name	References	Description	DNA Damage/Repair Being Measured	OECD Approved Assay
Dose-Response Curve for Alkyl Adducts/ Mutations	Lutz 1991   Clewell 2016	Creation of a curve plotting the stressor dose and the abundance of adducts/mutations; Characteristics of the resulting curve can provide information on the efficiency of DNA repair	Alkylation, oxidative damage, or DSBs	N/A
Retention of Alkyl Adducts	Seiler 1997   Scherer 1987	Examination of DNA for alkylation after exposure to an alkylating agent; Presence of alkylation suggests a lack of repair	Alkylation	N/A
Mutation Spectrum	Wyrick 2015	Shifts in the mutation spectrum after exposure to a chemical/mutagen relative to an unexposed subject can provide an indication of DNA repair efficiency, and can inform as to the type of DNA lesions present	Alkylation, oxidative damage, or DSBs	N/A
DSB Repair Assay (Reporter constructs)	Mao et al., 2011	Transfection of a GFP reporter construct (and DsRed control) where the GFP signal is only detected if the DSB is repaired; GFP signal  is quantified using fluorescence microscopy or flow cytometry	DSBs	N/A
Primary Rat Hepatocyte DNA Repair Assay	Jeffrey and Williams, 2000   Butterworth et al., 1987	Rat primary hepatocytes are cultured with a 3H-thymidine solution in order to measure DNA synthesis in response to a stressor in non-replicating cells; Autoradiography is used to measure the amount of 3H incorporated in the DNA post-repair	Unscheduled DNA synthesis in response to DNA damage	N/A
Repair synthesis measurement by 3H-thymine incorporation	Iyama and Wilson, 2013	Measure DNA synthesis in non-dividing cells as indication of gap filling during excision repair	Excision repair	N/A
Comet Assay with Time-Course	Olive et al., 1990   Trucco et al., 1998 - Dunkenberger et al., 2022	Comet assay is performed with a time-course under alkaline conditions to detect SSBs and DSBs. Quantity of DNA in the tail should decrease as DNA repair progresses	DSBs	Yes (No. 489)
Flow Cytometry	Corneo et al., 2007	The alt-NHEJ flow cytometer method involves utilizing an extrachromosomal substrate. Green fluorescent protein (GFP) expression is indicative of successful alt-NHEJ activity, contingent on the removal of 10 nucleotides from each end of the DNA and subsequent rejoining within a 9-nucleotide microhomology region. This approach provides a quantitative and visual means to measure the efficiency of alternative non-homologous end joining in cellular processes.	Alt NHEJ	No
Pulsed Field Gel Electro-phoresis (PFGE) with Time-Course	Biedermann et al., 1991	PFGE assay with a time-course; Quantity of small DNA fragments should decrease as DNA repair  progresses	DSBs	N/A
Fluorescence -Based Multiplex Flow-Cytometric Host Reactivation Assay (FM-HCR)	Nagel et al., 2014	Measures the ability of human cells to repair plasma reporters, which contain different types and amounts of DNA damage; Used to measure repair processes including HR, NHEJ, BER, NER, MMR, and MGMT	HR, NHEJ, BER, NER, MMR, or MGMT	N/A
Alkaline Unwinding Assay with Time Course	Nacci et al. 1991	DNA is stored in alkaline solutions with DNA-specific dye and allowed to unwind following removal from tissue, increased strand damage associated with increased unwinding. Samples analyzed at different time points to compare remaining damage following repair opportunities	DSBs	Yes (No. 489)
Sucrose Density Gradient Centrifugation with Time Course	Larsen et al. 1982	Strand breaks alter the molecular weight of the DNA piece. DNA in alkaline solution centrifuged into sugar density gradient, repeated set time apart. The less DNA breaks identified in the assay repeats, the more repair occurred	SSBs	N/A
y-H2AX Foci Staining with Time Course	Mariotti et al. 2013  Penninckx et al. 2021	Histone H2AX is phosphorylated in the presence of DNA strand breaks, the rate of its disappearance over time is used as a measure of DNA repair	DSBs	N/A
Alkaline Elution Assay with Time Course	Larsen et al. 1982	DNA with strand breaks elute faster than DNA without, plotted against time intervals to determine the rate at which strand breaks repair	SSBs	N/A
53BP1 foci Detection with Time Course	Penninckx et al. 2021	53BP1 is recruited to the site of DNA damage, the rate at which its level decreases over time is used to measure DNA repair	DSBs	N/A

 

References

Adimoolam, S. & J.M. Ford (2003), "p53 and regulation of DNA damage recognition during nucleotide excision repair" DNA Repair (Amst), 2(9): 947-54.

Aleksandrov, Radoslav et al. (2018), “Protein Dynamics in Complex DNA Lesions.” Molecular cell,69(6): 1046-1061.e5. doi:10.1016/j.molcel.2018.02.016 

Allgayer, J. et al. (2013), "Modulation of base excision repair of 8-oxoguanine by the nucleotide sequence", Nucleic Acids Res, 41(18): 8559-8571. Doi: 10.1093/nar/gkt620.

Beranek, D.T. (1990), "Distribution of methyl and ethyl adducts following alkylation with monofunctional alkylating agents", Mutation Research, 231(1): 11-30. Doi: 10.1016/0027-5107(90)90173-2.

Bhatti, A. et al., (2016), “Homologous Recombination Biology.”, Encyclopedia Britannica.

Bhowmick, R., S. et al. (2016), "RAD52 Facilitates Mitotic DNA Synthesis Following Replication Stress", Mol Cell, 64:1117-1126. Doi: 10.1016/j.molcel.2016.10.037.

Biedermann, A. K. et al. (1991), “SCID mutation in mice confers hypersensitivity to ionizing radiation and a deficiency in DNA double-strand break repair”, Cell Biology, 88(4): 1394-7. Doi: 10.1073/pnas.88.4.1394.

Boboila, C., F. W. Alt & B. Schwer. (2012), “Classical and alternative end-joining pathways for repair of lymphocyte-specific and general DNA double-strand breaks.” Adv Immunol, 116, 1-49. doi:10.1016/B978-0-12-394300-2.00001-6

Bronstein, S.M. et al. (1991), "Toxicity, mutagenicity, and mutational spectra of N-ethyl-N-nitrosourea in human cell lines with different DNA repair phenotypes", Cancer Research, 51(19): 5188-5197.

Bronstein, S.M. et al. (1992), "Efficient repair of O6-ethylguanine, but not O4-ethylthymine or O2-ethylthymine, is dependent upon O6-alkylguanine-DNA alkyltransferase and nucleotide excision repair activities in human cells", Cancer Research, 52(7): 2008-2011. 

Brown, J.A. et al. (2011), "Efficiency and fidelity of human DNA polymerases λ and β during gap-filling DNA synthesis", DNA Repair (Amst)., 10(1):24-33.

Butterworth, E. B. et al., (1987), A protocol and guide for the in vitro rat hepatocyte DNA-repair assay. Mutation Research. 189, 113-21. Doi: 10.1016/0165-1218(87)90017-6.

Caldecott, K. W. (2014), "DNA single-strand break repair", Exp Cell Res, 329(1): 2-8.

Chaudhuri, R.A. and Nussenzweig, A. (2017), “The multifaceted roles of PARP1 in DNA repair and chromatin remodelling”. Nat Rev Mol Cell Biol 18, 610–621. https://doi.org/10.1038/nrm.2017.53   

Chen, L. et al., (2001), Promotion of DNA ligase IV-catalyzed DNA end-joining by the Rad50/Mre11/Xrs2 and Hdf1/Hdf2 complexes. Mol Cell. 8(5), 1105-15.

Chiruvella, K. K., Z. Liang & T. E. Wilson, (2013), Repair of Double-Strand Breaks by End Joining. Cold Spring Harbor Perspectives in Biology, 5(5):127-57. Doi: 10.1101/cshperspect.a012757.

Clewell, R. A. et al. (2019). “Dose-dependence of chemical carcinogenicity: Biological mechanisms for thresholds and implications for risk assessment”. Chem Biol Interact. 2019 Mar 1;301:112-127. doi: 10.1016/j.cbi.2019.01.025. 

Corneo, B. et al., 2007, "Rag mutations reveal robust alternative end joining”. Nature 449, 483–486 (2007). https://doi.org/10.1038/nature06168   

Dahle, J., et al. (2008), “Overexpression of human OGG1 in mammalian cells decreases ultraviolet A induced mutagenesis”, Cancer Letters, Vol.267, Elsevier, Amsterdam, https://doi.org/10.1016/j.canlet.2008.03.002. 

Deem, A. et al. (2011), "Break-Induced Replication Is Highly Inaccurate.", PLoS Biol.  9:e1000594. Doi: 10.1371/journal.pbio.1000594.

Dianov, G.L. & U. Hübscher (2013), "Mammalian base excision repair: the forgotten archangel", Nucleic Acids Res., 41(6):3483-90. Doi: 10.1093/nar/gkt076.

Dilley, R.L. et al.  Greenberg (2016), "Break-induced telomere synthesis underlies alternative telomere maintenance", Nature, 539:54-58. Doi: 10.1038/nature20099.

Douglas, G.R. et al.  (1995), "Temporal and molecular characteristics of mutations induced by ethylnitrosourea in germ cells isolated from seminiferous tubules and in spermatozoa of lacZ transgenic mice", Proceedings of the National Academy of Sciences of the United States of America, 92(16):7485-7489. Doi: 10.1073/pnas.92.16.7485.

Dunkenberger, Logan et al. (2022), “Comet Assay for the Detection of Single and Double-Strand DNA Breaks.” Methods in molecular biology (Clifton, N.J.), 2422: 263-269. doi:10.1007/978-1-0716-1948-3_18 

Fattah, F. et al., (2010), Ku regulates the non-homologous end joining pathway choice of DNA double-strand break repair in human somatic cells. PLoS Genet, 6(2), doi:10.1371/journal.pgen.1000855

Fitzgerald, D.M., P.J. Hastings, and S.M. Rosenberg (2017), "Stress-Induced Mutagenesis: Implications in Cancer and Drug Resistance", Ann Rev Cancer Biol, 1:119-140. Doi: 10.1146/annurev-cancerbio-050216-121919.

Gorbunova, V. and A. Seluanov. (2016), “DNA double strand break repair, aging and the chromatin connection”, Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis, Vol.788/1-2, Elsevier, Amsterdam, http://dx.doi.org/10.1016/j.mrfmmm.2016.02.004. 

Hammel, M. et al., (2011), XRCC4 protein interactions with XRCC4-like factor (XLF) create an extended grooved scaffold for DNA ligation and double strand break repair. J Biol Chem, 286(37), 32638-32650. doi:10.1074/jbc.M111.272641.

Hanawalt, P.C., J.M. Ford and D.R. Lloyd (2003), "Functional characterization of global genomic DNA repair and its implications for cancer", Mutation Research, 544(2-3): 107–114.

Harbach, P. R. et al., (1989), “The in vitro unscheduled DNA synthesis (UDS) assay in rat primary hepatocytes”, Mutation Research, 216(2):101-10. Doi:10.1016/0165-1161(89)90010-1.

Iyama, T. and D.M. Wilson III (2013), "DNA repair mechanisms in dividing and non-dividing cells", DNA Repair, 12(8): 620– 636.

Jeffrey, M. A.& M. G. Williams, (2000), “Lack of DNA-damaging Activity of Five Non-nutritive Sweeteners in the Rat Hepatocyte/DNA Repair Assay”,  Food and Chemical Toxicology, 38: 335-338. Doi: 10.1016/S0278-6915(99)00163-5.

Köberle, B. et al. (1999), "Defective repair of cisplatin-induced DNA damage caused by reduced XPA protein in testicular germ cell tumours", Curr. Biol., 9(5):273-6. Doi: 10.1016/s0960-9822(99)80118-3.

Kozmin, S.G. & S. Jinks-Robertson S. (2013), “The mechanism of nucleotide excision repair-mediated UV-induced mutagenesis in nonproliferating cells”, Genetics, 193(3): 803-17. Doi: 10.1534/genetics.112.147421.

Kramara, J., B. Osia, and A. Malkova (2018), "Break-Induced Replication: The Where, The Why, and The How", Trends Genet, 34:518-531. Doi: 10.1016/j.tig.2018.04.002.

Kuhne, M., G. Urban and M. Lo (2005), "DNA Double-Strand Break Misrejoining after Exposure of Primary Human Fibroblasts to CK Characteristic X Rays, 29 kVp X Rays and 60Co γ Rays", Radiation. Research, Vol.164/5, Radiation Research Society, Indianapolis, https://doi.org/10.1667/RR3461.1. 

Larsen, K.H. et al. (1982), “DNA repair assays as tests for environmental mutagens: A report of the U.S. EPA gene-tox program”, Mutation Research, Vol.98/3, Elsevier, Amsterdam, https://doi.org/10.1016/0165-1110(82)90037-9. 

Li Z, A. H. Pearlman, and P. Hsieh (2016), "DNA mismatch repair and the DNA damage response", DNA Repair (Amst), 38:94-101.

Lieber, M. R., (2010), “The mechanism of double-strand DNA break repair by the nonhomologous DNA end-joining pathway.” Annu Rev Biochem. 79:181-211. doi:10.1146/annurev.biochem.052308.093131.

Lieber, M. R. et al., (2003), “Mechanism and regulation of human non-homologous DNA end-joining”, Nat Rev Mol Cell Biol. 4(9):712-720. doi:10.1038/nrm1202.

Liu, Y. et al. (2009), "Coordination between polymerase beta and FEN1 can modulate CAG repeat expansion", J. Biol. Chem., 284(41): 28352-28366. Doi: 10.1074/jbc.M109.050286.

Mao, Z. et al., (2011), “SIRT6 promotes DNA repair under stress by activating PARP1”, Science. 332(6036): 1443-1446. doi:10.1126/science.1202723.

Mariotti, L.G. et al. (2013), “Use of the γ-H2AX Assay to Investigate DNA Repair Dynamics Following Multiple Radiation Exposures”, PLoS ONE, Vol.8/11, PLoS, San Francisco, https://doi.org/10.1371/journal.pone.0079541. 

Matthews, L. A., & L. A. Simmons, (2014), “Bacterial nonhomologous end joining requires teamwork”, J Bacteriol. 196(19): 3363-3365. doi:10.1128/JB.02042-14.

Menoni, H. et al. (2012), "Base excision repair of 8-oxoG in dinucleosomes", Nucleic Acids Res. ,40(2): 692-700. Doi: 10.1093/nar/gkr761.

Minocherhomji, S. et al. (2015), "Replication stress activates DNA repair synthesis in mitosis", Nature, 528:286-290. Doi: 10.1038/nature16139.

Miyaoka, Y. et al., (2016), “Systematic quantification of HDR and NHEJ reveals effects of locus, nuclease, and cell type on genome-editing”, Sci Rep, 6, 23549. doi:10.1038/srep23549/.

Mladenov. et al.  (2023), . “New Facets of DNA Double Strand Break Repair: Radiation Dose as Key Determinant of HR versus c-NHEJ Engagement”. International journal of molecular sciences, 24(19), 14956. https://doi.org/10.3390/ijms241914956 

Moore, J. K., & J. E. Haber, (1996), “Cell cycle and genetic requirements of two pathways of nonhomologous end-joining repair of double-strand breaks in Saccharomyces cerevisiae”, Molecular and Cellular Biology, 16(5), 2164–73.  Doi: 10.1128/MCB.16.5.2164.

Nacci, D. et al. (1992), “Application of the DNA alkaline unwinding assay to detect DNA strand breaks in marine bivalves”, Marine Environmental Research, Vol.33/2, Elsevier BV, Amsterdam, https://doi.org/10.1016/0141-1136(92)90134-8. 

Nagel, Z.D. et al. (2014), "Multiplexed DNA repair assays for multiple lesions and multiple doses via transcription inhibition and transcriptional mutagenesis", Proc. Natl. Acad. Sci. USA, 111(18):E1823-32. Doi: 10.1073/pnas.1401182111.

O’Brien, J.M. et al. (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. Doi: 10.1002/em.21932.

Olive, L. P., J. P. Bnath & E. R. Durand, (1990), “Heterogeneity in Radiation-Induced DNA Damage and Repairing Tumor and Normal Cells Measured Using the "Comet" Assay”, Radiation Research. 122: 86-94. Doi: 10.1667/rrav04.1.

Pardo, B., B. Gomez-Gonzalez & A. Aguilera, (2009), “DNA repair in mammalian cells: DNA double-strand break repair: how to fix a broken relationship”, Cell Mol Life Sci, 66(6), 1039-1056. doi:10.1007/s00018-009-8740-3.

Pegg, A.E. (2011), "Multifaceted roles of alkyltransferase and related proteins in DNA repair, DNA damage, resistance to chemotherapy, and research tools", Chem. Res. Toxicol., 4(5): 618-39. Doi: 10.1021/tx200031q.

Penninckx, S. et al. (2021), “Quantification of radiation-induced DNA double strand break repair foci to evaluate and predict biological responses to ionizing radiation”, NAR Cancer, Vol.3/4, Oxford University Press, Oxford, https://doi.org/10.1093/narcan/zcab046. 

Rydberg, B. 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, Vol.163/5, Radiation Research Society, Indianapolis, https://doi.org/10.1667/RR3346.  

Sancar, A. (2003), "Structure and function of DNA photolyase and cryptochrome blue-light photoreceptors", Chem Rev., 103(6): 2203-37. Doi: 10.1021/cr0204348.

Saini, N. et al. (2017), "Migrating bubble during break-induced replication drives conservative DNA synthesis", Nature, 502:389-392. Doi: 10.1038/nature12584.

Sakofsky, C.J. et al. (2015), "Translesion Polymerases Drive Microhomology-Mediated Break-Induced Replication Leading to Complex Chromosomal Rearrangements", Mol Cell, 60:860-872. Doi: 10.1016/j.molcel.2015.10.041.

Schärer, O.D. (2013), "Nucleotide excision repair in eukaryotes", Cold Spring Harb. Perspect. Biol., 5(10): a012609. Doi: 10.1101/cshperspect.a012609.

Scherer, E., A.A. Jenner and L. den Engelse (1987), "Immunocytochemical studies on the formation and repair of O6-alkylguanine in rat tissues", IARC Sci Publ., 84: 55-8.

Seiler, F., K. Kamino, M. Emura, U. Mohr and J. Thomale (1997), "Formation and persistence of the miscoding DNA alkylation product O6-ethylguanine in male germ cells of the hamster", Mutat Res., 385(3): 205-211. Doi: 10.1016/s0921-8777(97)00043-8.

Shelby, M.D. and K.R. Tindall (1997), "Mammalian germ cell mutagenicity of ENU, IPMS and MMS, chemicals selected for a transgenic mouse collaborative study", Mutation Research, 388(2-3): 99-109. Doi: 10.1016/s1383-5718(96)00106-4.

Seo, Y.R. and H.J. Jung (2004), "The potential roles of p53 tumor suppressor in nucleotide excision repair (NER) and base excision repair (BER)", Exp. Mol. Med., 36(6): 505-509. Doi: 10.1038/emm.2004.64.

Sundheim, O. et al. (2008), "AlkB demethylases flip out in different ways", DNA Repair (Amst)., 7(11): 1916-1923. Doi: 10.1016/j.dnarep.2008.07.015.

Sung, P., & H. Klein, (2006), “Mechanism of homologous recombination: mediators and helicases take on regulatory functions”,  Nat Rev Mol Cell Biol, 7(10), 739-750. Doi:10. 1038/nrm2008.

Trucco, C., et al., (1998), “DNA repair defect i poly(ADP-ribose) polymerase-deficient cell lines”, Nucleic Acids Research. 26(11): 2644–2649. Doi: 10.1093/nar/26.11.2644.

Trzeciak, A.R. et al. (2008), “Age, sex, and race influence single-strand break repair capacity in a human population”, Free Radical Biology & Medicine, Vol. 45, Elsevier, Amsterdam, https://doi.org/10.1016/j.freeradbiomed.2008.08.031. 

White, R.R. and J. Vijg. (2016), “Do DNA Double-Strand Breaks Drive Aging?”, Molecular Cell, Vol.63, Elsevier, Amsterdam, http://doi.org/10.1016/j.molcel.2016.08.004. 

Wyrick, J.J. & S. A. Roberts, (2015), “Genomic approaches to DNA repair and mutagenesis”, DNA Repair (Amst). 36:146-155. doi: 10.1016/j.dnarep.2015.09.018.

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.

Event: 185: Increase, Mutations

Short Name: Increase, Mutations

Key Event Component

AOPs Including This Key Event

Stressors

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability: Mutations can occur in any organism and in any cell type, and are the fundamental material of evolution. The test guidelines described above range from analysis from prokaryotes, to rodents, to human cells in vitro. Mutations have been measured in virtually every human tissue sampled in vivo.

Life stage applicability: This key event is not life stage specific as all stages of life have DNA that can be mutated; however, baseline levels of mutations are seen to increase with age (Slebos et al., 2004; Kirkwood, 1989). 

Sex applicability: This key event is not sex specific as both sexes undergo mutations. Males have a higher mutation rate than females (Hedrick, 2007). 

Evidence for perturbation by a stressor: Many studies demonstrate that increased mutations can occur as a result of ionizing radiation (Sankaranarayanan & Nikjoo, 2015; Russell et al., 1957; Winegar et al., 1994; Gossen et al., 1995).  

Key Event Description

A mutation is a change in DNA sequence. Mutations can thus alter the coding sequence of genes, potentially leading to malformed or truncated proteins. Mutations can also occur in promoter regions, splice junctions, non-coding RNA, DNA segments, and other functional locations in the genome. These mutations can lead to various downstream consequences, including alterations in gene expression. There are several different types of mutations including missense, nonsense, insertion, deletion, duplication, and frameshift mutations, all of which can impact the genome and its expression in unique ways.

Missense mutations are the substitution of one base in the codon with another. This change is significant because the three bases in a codon code for a specific amino acid and the new combination may signal for a different amino acid to be formed. Nonsense mutations also result from changes to the codon bases, but in this case, they cause the generation of a stop codon in the DNA strand where there previously was not one. This stop codon takes the place of a normal coding triplet, preventing its translation into an amino acid. This will cause the translation of the strand to prematurely stop. Both missense and nonsense mutations can result from substitutions, insertions, or deletions of bases (Chakarov et al. 2014).  

Insertion and deletion mutations are the addition and removal of bases from the strand, respectively. These often accompany a frameshift mutation, as the alteration in the number of bases in the strand causes the frame of the base reader to shift by the added or reduced number, altering the amino acids that are produced if that number is not devisable by three. Codons come in specific orders, sectioned into groups of three. When the boundaries of which three bases are included in one group are changed, this can change the whole transcriptional output of the strand (Chakaroy et al. 2014). 

Mutations can be propagated to daughter cells upon cellular replication. Mutations in stem cells (versus terminally differentiated non-replicating cells) are the most concerning, as these will persist in the organism. The consequence of the mutation, and thus the fate of the cell, depends on the location (e.g., coding versus non-coding) and the type (e.g., nonsense versus silent) of mutation.

Mutations can occur in somatic cells or germ cells (sperm or egg).

How it is Measured or Detected

Mutations can be measured using a variety of both OECD and non-OECD mutagenicity tests. Listed below are common methods for detecting the KE, however there may be other comparable methods that are not listed.

Somatic cells: The Salmonella mutagenicity test (Ames Test) is generally used as part of a first tier screen to determine if a chemical can cause gene mutations. This well-established test has an OECD test guideline (OECD TG 471, 2020). A variety of bacterial strains are used, in the presence and absence of a metabolic activation system (e.g., rat liver microsomal S9 fraction), to determine the mutagenic potency of chemicals by dose-response analysis. A full description is found in Test No. 471: Bacterial Reverse Mutation Test (OECD, 2016).

A variety of in vitro mammalian cell gene mutation tests are described in OECD’s Test Guidelines 476 (2016) and 490 (2015). TG 476 (2016) is used to identify substances that induce gene mutations at the hprt (hypoxanthine-guanine phosphoribosyl transferase) gene, or the transgenic xprt (xanthine-guanine phosphoribosyl transferase) reporter locus. The most commonly used cells for the HPRT test include the CHO, CHL and V79 lines of Chinese hamster cells, L5178Y mouse lymphoma cells, and TK6 human lymphoblastoid cells. The only cells suitable for the XPRT test are AS52 cells containing the bacterial xprt (or gpt) transgene (from which the hprt gene was deleted).

The new OECD TG 490 (2015) describes two distinct in vitro mammalian gene mutation assays using the thymidine kinase (tk) locus and requiring two specific tk heterozygous cells lines: L5178Y tk+/-3.7.2C cells for the mouse lymphoma assay (MLA) and TK6 tk+/- cells for the TK6 assay. The autosomal and heterozygous nature of the thymidine kinase gene in the two cell lines enables the detection of cells deficient in the enzyme thymidine kinase following mutation from tk+/- to tk-/-.

It is important to consider that different mutation spectra are detected by the different mutation endpoints assessed. The non-autosomal location of the hprt gene (X-chromosome) means that the types of mutations detected in this assay are point mutations, including base pair substitutions and frameshift mutations resulting from small insertions and deletions. Whereas, the autosomal location of the transgenic xprt, tk, or gpt locus allows the detection of large deletions not readily detected at the hemizygous hprt locus on X-chromosomes. Genetic events detected using the tk locus include both gene mutations (point mutations, frameshift mutations, small deletions) and large deletions.

The transgenic rodent mutation assay (OECD TG 488, 2020) is the only assay capable of measuring gene mutation in virtually all tissues in vivo. Specific details on the rodent transgenic mutation reporter assays are reviewed in Lambert et al. (2005, 2009). The transgenic reporter genes are used for detection of gene mutations and/or chromosomal deletions and rearrangements resulting in DNA size changes (the latter specifically in the lacZ plasmid and Spi- test models) induced in vivo by test substances (OECD, 2009, OECD, 2011; Lambert et al., 2005). Briefly, transgenic rodents (mouse or rat) are exposed to the chemical agent sub-chronically. Following a manifestation period, genomic DNA is extracted from tissues, transgenes are rescued from genomic DNA, and transfected into bacteria where the mutant frequency is measured using specific selection systems.

The Pig-a (phosphatidylinositol glycan, Class A) gene on the X chromosome codes for a catalytic subunit of the N-acetylglucosamine transferase complex that is involved in glycosylphosphatidyl inositol (GPI) cell surface anchor synthesis. Cells lacking GPI anchors, or GPI-anchored cell surface proteins are predominantly due to mutations in the Pig-a gene. Thus, flow cytometry of red blood cells expressing or not expressing the Pig-a gene has been developed for mutation analysis in blood cells from humans, rats, mice, and monkeys. The assay is described in detail in Dobrovolsky et al. (2010). Development of an OECD guideline for the Pig-a assay is underway. In addition, experiments determining precisely what proportion of cells expressing the Pig-a mutant phenotype have mutations in the Pig-a gene are in progress (e.g., Nicklas et al., 2015, Drobovolsky et al., 2015). A recent paper indicates that the majority of CD48 deficient cells from 7,12-dimethylbenz[a]anthracene-treated rats (78%) are indeed due to mutation in Pig-a (Drobovolsky et al., 2015).

Germ cells: Tandem repeat mutations can be measured in bone marrow, sperm, and other tissues using single-molecule PCR. This approach has been applied most frequently to measure repeat mutations occurring in sperm DNA. Isolation of sperm DNA is as described above for the transgenic rodent mutation assay, and analysis of tandem repeats is done using electrophoresis for size analysis of allele length using single-molecule PCR. For expanded simple tandem repeat this involved agarose gel electrophoresis and Southern blotting, whereas for microsatellites sizing is done by capillary electrophoresis. Detailed methodologies for this approach are found in Yauk et al. (2002) and Beal et al. (2015).

Mutations in rodent sperm can also be measured using the transgenic reporter model (OECD TG 488, 2020). A description of the approach is found within this published TG. Further modifications to this protocol have been made as of 2022 for the analysis of germ cells. Detailed methodology for detecting mutant frequency arising in spermatogonia is described in Douglas et al. (1995), O'Brien et al. (2013); and O'Brien et al. (2014). Briefly, male mice are exposed to the mutagen and killed at varying times post-exposure to evaluate effects on different phases of spermatogenesis. Sperm are collected from the vas deferens or caudal epididymis (the latter preferred). Modified protocols have been developed for extraction of DNA from sperm.

A similar transgenic assay can be used in transgenic medaka (Norris and Winn, 2010).

Please note, gene mutations that occur in somatic cells in vivo (OECD Test. No. 488, 2020) or in vitro (OECD Test No. 476: In vitro Mammalian Cell Gene Mutation Test, 2016), or in bacterial cells (i.e., OECD Test No. 471, 2020) can be used as an indicator that mutations in male pre-meiotic germ cells may occur for a particular agent (sensitivity and specificity of other assays for male germ cell effects is given in Waters et al., 1994). However, given the very unique biological features of spermatogenesis relative to other cell types, known exceptions to this rule, and the small database on which this is based, inferring results from somatic cell or bacterial tests to male pre-meiotic germ cells must be done with caution. That mutational assays in somatic cells may predict mutations in germ cells has not been rigorously tested empirically (Singer and Yauk, 2010). The IWGT working group on germ cells specifically addressed this gap in knowledge in their report (Yauk et al., 2015) and recommended that additional research address this issue. Mutations can be directly measured in humans (and other species) through the application of next-generation sequencing. Although single-molecule approaches are growing in prevalence, the most robust approach to measure mutation using next-generation sequencing today requires clonal expansion of the mutation to a sizable proportion (e.g., sequencing tumours; Shen et al., 2015), or analysis of families to identify germline derived mutations (reviewed in Campbell and Eichler, 2013; Adewoye et al., 2015).

Please refer to the table below for additional details and methodologies for measuring mutations.

Assay Name	References	Description	OECD Approved Assay
Assorted Gene Loci Mutation Assays	Tindall et al., 1989; Kruger et al., 2015	After exposure to a chemical/mutagen, mutations can be measured by the ability of exposed cells to form colonies in the presence of specific compounds that would normally inhibit colony growth; Usually only cells -/- for the gene of interest are able to form colonies	N/A
TK Mutation Assay	Yamamoto et al., 2017; Liber et al., 1982; Lloyd and Kidd, 2012	After exposure to a chemical/mutagen, mutations are detected at the thymidine kinase (TK) loci of L5178Y wild-type mouse lymphoma TK (+/-) cells by measuring resistance to lethaltriflurothymidine (TFT); Only TK-/- cells are able to form colonies	Yes (No. 490)
HPRT Mutation Assay	Ayres et al., 2006; Parry and Parry, 2012	Similar to TK Mutation Assay above, X-linked HPRT mutations produced in response to chemical/mutagen exposure can be measured through colony formation in the presence of 6-TG or 8-azoguanine; Only HPRT-/- cells are able to form colonies	Yes (No. 476)
Salmonella Mutagenicity Test (Ames Test)	OECD, 1997	After exposure to a chemical/mutagen, point mutations are detected by analyzing the growth capacity of different bacterial strains in the presence and absence of various metabolic activation systems	Yes (No. 471)
PIG-A / PIG-O Assay	Kruger et al., 2015; Nakamura, 2012; Chikura, 2019	After exposure to a chemical/mutagen, mutations  in PIG-A or PIG-O (which decrease the biosynthesis of the glycosylphosphatidylinositol (GPI) anchor protein) are assessed by the colony-forming capabilities of cells after in vitro exposure, or by flow cytometry of blood samples after in vivo exposure	N/A
Single Molecule PCR	Kraytsberg & Khrapko, 2005; Yauk, 2002	This PCR technique uses a single DNA template, and is often employed for detection of mutations in microsatellites, recombination studies, and generation of polonies	N/A
ACB-PCR	Myers et al., 2014 (Textbook, pg 345-363); Banda et al.,  2013; Banda et al.,  2015; Parsons et al., 2017	Using this PCR technique, single base pair substitution mutations within oncogenes or tumour suppressor genes can be detected by selectively amplifying specific point mutations within an allele and selectively blocking amplification of the wild-type allele	N/A
Transgenic Rodent Mutation Assay	OECD 2013; Lambert 2005; Lambert 2009	This in vivo test detects gene mutations using transgenic rodents that possess transgenes and reporter genes; After in vivo exposure to a chemical/mutagen, the transgenes are analyzed by transfecting bacteria with the reporter gene and examining the resulting phenotype	Yes (No. 488)
Conditionally inducible transgenic mouse models	Parsons 2018 (Review)	Inducible mutations linked to fluorescent tags are introduced into transgenic mice; Upon exposure of the transgenic mice to an inducing agent, the presence and functional assessment of the mutations can be easily ascertained due to expression of the linked fluorescent tags	N/A
Error-Corrected Next Generation Sequencing (NGS)	Salk 2018 (Review)	This technique detects rare subclonal mutations within a pool of heterogeneous DNA samples through the application of new error-correction strategies to NGS; At present, few laboratories in the world are capable of doing this, but commercial services are becoming available (e.g., Duplex sequencing at TwinStrand BioSciences)	N/A

 

References

Adewoye, A.B. et al. (2015), "The genome-wide effects of ionizing radiation on mutation induction in the mammalian germline", Nat. Commu., 6:6684. Doi: 10.1038/ncomms7684.

Ayres, M. F. et al. (2006),  “Low doses of gamma ionizing radiation increase hprt mutant frequencies of TK6 cells without triggering the mutator phenotype pathway”,  Genetics and Molecular Biology. 2(3): 558-561. Doi:10.1590/S1415-4757200600030002.

Banda M, Recio L, and Parsons BL. (2013), “ACB-PCR measurement of spontaneous and furan-induced H-ras codon 61 CAA to CTA and CAA to AAA mutation in B6C3F1 mouse liver”, Environ Mol Mutagen. 54(8):659-67. Doi:10.1002/em.21808.

Banda,  M. et al. (2015), “Quantification of Kras mutant fraction in the lung DNA of mice exposed to aerosolized particulate vanadium pentoxide by inhalation”,  Mutat Res Genet Toxicol Environ Mutagen. 789-790:53-60. Doi: 10.1016/j.mrgentox.2015.07.003

Campbell, C.D. & E.E. Eichler (2013), "Properties and rates of germline mutations in humans", Trends Genet., 29(10): 575-84. Doi:  10.1016/j.tig.2013.04.005

Chakarov, S. et al. (2014), “DNA damage and mutation. Types of DNA damage”, BioDiscovery, Vol.11, Pensoft Publishers, Sofia, https://doi.org/10.7750/BIODISCOVERY.2014.11.1.

Chikura, S. et al. (2019), “Standard protocol for the total red blood cell Pig-a assay used in the interlaboratory trial organized by the Mammalian Mutagenicity Study Group of the Japanese Environmental Mutagen Society”,  Genes Environ.  27:41-5. Doi: 10.1186/s41021-019-0121-z.

Dobrovolsky, V.N. et al. (2015), "CD48-deficient T-lymphocytes from DMBA-treated rats have de novo mutations in the endogenous Pig-a gene. CD48-Deficient T-Lymphocytes from DMBA-Treated Rats Have De Novo Mutations in the Endogenous Pig-a Gene", Environ. Mol. Mutagen., (6): 674-683. Doi: 10.1002/em.21959.

Douglas, G.R. et al. (1995), "Temporal and molecular characteristics of mutations induced by ethylnitrosourea in germ cells isolated from seminiferous tubules and in spermatozoa of lacZ transgenic mice", Proceedings of the National Academy of Sciences of the United States of America, 92(16): 7485-7489. Doi: 10.1073/pnas.92.16.7485.

Gossen, J.A. et al. (1995), "Spontaneous and X-ray-induced deletion mutations in a LacZ plasmid-based transgenic mouse model", Mutation Research, 331/1, Elsevier, Amsterdam, https://doi.org/10.1016/0027-5107(95)00055-N. 

Hedrick, P.W. (2007), “Sex: Differences In Mutation, Recombination, Selection, Gene Flow, And Genetic Drift”, Evolution, Vol.61/12, Wiley, Hoboken, https://doi.org/10.1111/j.1558-5646.2007.00250.x. 

Kirkwood, T.B.L. (1989), “DNA, mutations and aging”, Mutation Research, Vol.219/1, Elsevier B.V., Amsterdam, https://doi.org/10.1016/0921-8734(89)90035-0

Kraytsberg,Y. &  Khrapko, K. (2005),  “Single-molecule PCR: an artifact-free PCR approach for the analysis of somatic mutations”,  Expert Rev Mol Diagn. 5(5):809-15. Doi: 10.1586/14737159.5.5.809.

Krüger, T. C., Hofmann, M., & Hartwig, A. (2015), “The in vitro PIG-A gene mutation assay: mutagenicity testing via flow cytometry based on the glycosylphosphatidylinositol (GPI) status of TK6 cells”, Arch Toxicol. 89(12), 2429-43. Doi: 10.1007/s00204-014-1413-5.

Lambert, I.B. et al. (2005), "Detailed review of transgenic rodent mutation assays", Mutat Res., 590(1-3):1-280. Doi: 10.1016/j.mrrev.2005.04.002.

Liber, L. H., & Thilly, G. W. (1982),  “Mutation assay at the thymidine kinase locus in diploid human lymphoblasts”,  Mutation Research. 94: 467-485. Doi:10.1016/0027-5107(82)90308-6.

Lloyd, M., & Kidd, D. (2012), “The Mouse Lymphoma Assay. In: Parry J., Parry E. (eds) Genetic Toxicology, Methods in Molecular Biology (Methods and Protocols), 817. Springer, New York, NY.

Myers, M. B. et al., (2014), “ACB-PCR Quantification of Somatic Oncomutation”,  Molecular Toxicology Protocols, Methods in Molecular Biology. DOI: 10.1007/978-1-62703-739-6_27

Nakamura, J. et al., (2012), “Detection of PIGO-deficient cells using proaerolysin: a valuable tool to investigate mechanisms of mutagenesis in the DT40 cell system”, PLoS One.7(3): e33563. Doi:10.1371/journal.pone.0033563.

Nicklas, J.A., E.W. Carter and R.J. Albertini (2015), "Both PIGA and PIGL mutations cause GPI-a deficient isolates in the Tk6 cell line", Environ. Mol. Mutagen., 6(8):663-73. Doi: 10.1002/em.21953.

Norris, M.B. and R.N. Winn (2010), "Isolated spermatozoa as indicators of mutations transmitted to progeny", Mutat Res., 688(1-2): 36–40. Doi: 10.1016/j.mrfmmm.2010.02.008.

O'Brien, J.M. et al.(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. Doi: 10.1016/j.mrfmmm.2013.02.004.

O'Brien, J.M. et al. (2014), "Transgenic rodent assay for quanitifying male germ cell mutation frequency", Journal of Visual Experimentation, Aug 6;(90). Doi: 10.3791/51576.

O’Brien, J.M. et al. (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., 6(4): 347-355. Doi: 10.1002/em.21932.

OECD (2020), Test No. 471: Bacterial Reverse Mutation Test, OECD Guidelines for the Testing of Chemicals, Section 4, OECD Publishing, Paris.

OECD (2016), Test No. 476: In vitro Mammalian Cell Gene Mutation Test, OECD Guidelines for the Testing of Chemicals, Section 4, OECD Publishing, Paris.

OECD (2009), Detailed Review Paper on Transgenic Rodent Mutation Assays, Series on Testing and Assessment, N° 103, ENV/JM/MONO 7, OECD, Paris.

OECD (2020), Test No. 488: Transgenic Rodent Somatic and Germ Cell Gene Mutation Assays, OECD Guidelines for the Testing of Chemicals, Section 4, OECD Publishing, Paris.

OECD (2016), Test. No. 490: In vitro mammalian cell gene mutation mutation tests using the thymidine kinase gene, OECD Guidelines for the Testing of Chemicals, Section 4, OECD Publishing, Paris.

OECD Guidelines for the Testing of Chemicals, Section 4, OECD Publishing, Paris.

Parry MJ, & Parry ME. 2012. Genetic Toxicology Principles and Methods. Humana Press. Springer Protocols.

Parsons BL, McKim KL, Myers MB. 2017. Variation in organ-specific PIK3CA and KRAS mutant levels in normal human tissues correlates with mutation prevalence in corresponding carcinomas. Environ Mol Mutagen. 58(7):466-476. Doi: 10.1002/em.22110.

Parsons BL. Multiclonal tumor origin: Evidence and implications. Mutat Res. 2018. 777:1-18. doi: 10.1016/j.mrrev.2018.05.001.

Russell, W.L. et al. (1957), "Radiation Dose Rate and Mutation Frequency.", Science, Vol.128/3338, American Association for the Advancement of Science, Washington, https://doi.org/10.1126/science.128.3338.1546.

Salk JJ, Schmitt MW, &Loeb LA. (2018), “Enhancing the accuracy of next-generation sequencing for detecting rare and subclonal mutations”, Nat Rev Genet. 19(5):269-285. Doi: 10.1038/nrg.2017.117.

Sankaranarayanan, K. & H. Nikjoo (2015), "Genome-based, mechanism-driven computational modeling of risks of ionizing radiation: The next frontier in genetic risk estimation?", Mutation Research, Vol.764, Elsevier, Amsterdam, https://doi.org/10.1016/j.mrrev.2014.12.003. 

Shen, T., S.H. Pajaro-Van de Stadt, N.C. Yeat and J.C. Lin (2015), "Clinical applications of next generation sequencing in cancer: from panels, to exomes, to genomes" Front. Genet., 6: 215. Doi: 10.3389/fgene.2015.00215.

Singer, T.M. and C.L. Yauk CL (2010), "Germ cell mutagens: risk assessment challenges in the 21st century", Environ. Mol. Mutagen., 51(8-9): 919-928. Doi: 10.1002/em.20613.

Slebos, R.J.C. et al. (2004), “Mini-and microsatellite mutations in children from Chernobyl accident cleanup workers”, Mutation Research/Genetic Toxicology and Environmental Mutagenesis, Vol.559/1-2, Elsevier, Amsterdam, https://doi.org/10.1016/j.mrgentox.2004.01.003. 

Tindall, R. K., & Stankowski Jr., F. L. (1989),  “Molecular analysis of spontaneous mutations at the GPT locus in Chinese hamster ovary (AS52) cells”, Mutation Research, 220, 241-53. Doi: 10.1016/0165-1110(89)90028-6.

Waters, M.D. et al. (1994), "The performance of short-term tests in identifying potential germ cell mutagens: a qualitative and quantitative analysis", Mutat. Res., 341(2): 109-31. Doi: 10.1016/0165-1218(94)90093-0.

Winegar, R.A. et al. (1994), "Radiation-induced point mutations, deletions and micronuclei in lacI transgenic mice", Mutation Research, Vol.307/2, Elsevier, Amsterdam, https://doi.org/10.1016/0027-5107(94)90258-5. 

Yamamoto, A. et al. (2017), “Radioprotective activity of blackcurrant extract evaluated by in vitro micronucleus and gene mutation assays in TK6 human lymphoblastoid cells”, Genes and Environment. 39: 22. Doi: 10.1186/s41021-017-0082-z.

Yauk, C.L. et al. (2002), "A novel single molecule analysis of spontaneous and radiation-induced mutation at a mouse tandem repeat locus", Mutat. Res., 500(1-2): 147-56. Doi: 10.1016/s0027-5107(02)00005-2.

Yauk, C.L. et al. (2015), "Approaches for Identifying Germ Cell Mutagens: Report of the 2013 IWGT Workshop on Germ Cell Assays", Mutat. Res. Genet. Toxicol. Environ. Mutagen., 783: 36-54. Doi: 10.1016/j.mrgentox.2015.01.008.

Yeat and J.C. Lin. 2015. Clinical applications of next generation sequencing in cancer: from panels, to exomes, to genomes. Front. Genet., 6: 215. Doi: 10.3389/fgene.2015.00215.

Event: 1636: Increase, Chromosomal aberrations

Short Name: Increase, Chromosomal aberrations

Key Event Component

AOPs Including This Key Event

Stressors

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability: CAs are possible in nucleated cells of any species (Ferguson-Smith, 2015).  

Life stage applicability: This key event is not life stage specific as subjects of all ages have chromosomes that can be improperly structured. However, older individuals have naturally higher baseline levels of CAs (Vick et al., 2017). Individuals born with stable type aberrations will retain them throughout their lifetime (Gardner et al., 2011). 

Sex applicability: This key event is not sex specific, with both sexes experiencing CAs at comparable rates (Kašuba et al., 1995). 

Evidence for perturbation by a stressor: Many studies have provided evidence to support increased CAs occurring as a result of exposure to ionizing radiation (Franken et al., 2012; Cornforth et al., 2002; Loucas et al., 2013).  

Key Event Description

Structural chromosomal aberrations describe the damage to chromosomes that results from breaks along the DNA and may lead to deletion, addition, or rearrangement of sections in the chromosome. Chromosomal aberrations can be divided in two major categories: chromatid-type or chromosome-type depending on whether one or both chromatids are involved, respectively. They can be further classified as rejoined or non-rejoined aberrations. Rejoined aberrations include translocations, insertions, dicentrics and rings, while unrejoined aberrations include acentric fragments and breaks (Savage, 1976). Some of these aberrations are stable (i.e., reciprocal translocations) and can persist for many years (Tucker and Preston, 1996). Others are unstable (i.e., dicentrics, acentric fragments) and decline at each cell division because of clonogenic inactivation (Boei et al., 1996). These events may be detectable after cell division and such damage to DNA is irreversible. Chromosomal aberrations are associated with  clonogenic inactivation and carcinogenicity (Mitelman, 1982).

Chromosomal aberrations (CA) refer to a missing, extra or irregular portion of chromosomal DNA. These DNA changes in the chromosome structure may be produced by different double strand break (DSB) repair mechanisms (Obe et al., 2002).

There are 4 main types of CAs: deletions, duplications, translocations, and inversions. Deletions happen when a portion of the genetic material from a chromosome is lost. Terminal deletions occur when an end piece of the chromosome is cleaved. Interstitial deletions arise when a chromosome breaks in two separate locations and rejoins incorrectly, with the center piece being omitted. Duplications transpire when there is any addition or rearrangement of excess genetic material; types of duplications include transpositions, tandem duplications, reverse duplications, and displaced duplications (Griffiths et al., 2000). Translocations result from a section of one chromosome being transferred to a non-homologous chromosome (Bunting and Nussenzweig, 2013). When there is an exchange of segments on two non-homologous chromosomes, it is called a reciprocal translocation. Inversions occur in a single chromosome and involve both of the ends breaking and being ligated on the opposite ends, effectively inverting the DNA sequence.    
 

A fifth type of CA that can occur in the genome is the copy number variant (CNV). CNVs, which may comprise greater than 10% of the human genome (Shlien et al., 2009; Zhang et al., 2016; Hastings et al., 2009),  are deletions or duplications that can vary in size from 50 base pairs (Arlt et al., 2012; Arlt et al., 2014; Liu et al., 2013) up into the megabase pair range (Arlt et al., 2012; Wilson et al., 2015; Arlt et al., 2014; Zhang et al., 2016). CNV regions are especially enriched in large genes and large active transcription units (Wilson et al., 2015), and are of particular concern when they cause deletions in tumour suppressor genes or duplications in oncogenes (Liu et al., 2013; Curtis et al., 2012). There are two types of CNVs: recurrent and non-recurrent. Recurrent CNVs are thought to be produced through a recombination process during meiosis known as non-allelic homologous recombination (NAHR) (Arlt et al., 2012; Hastings et al., 2009). These recurrent CNVs, also called germline CNVs, could be inherited and are thus common across different individuals (Shlien et al., 2009; Liu et al., 2013). Non-recurrent CNVs are believed to be produced in mitotic cells during the process of replication. Although the mechanism is not well studied, it has been suggested that stress during replication, in particular stalling replication forks, prompt microhomology-mediated mechanisms to overcome the replication stall, which often results in duplications or deletions. Two models that have been proposed to explain this mechanism include the Fork Stalling and Template Switching (FoSTeS) model, and the Microhomology-Mediated Break-Induced Replication (MMBIR) model (Arlt et al., 2012; Wilson et al., 2015; Lee et al., 2007; Hastings et al., 2009).

 

CAs can be classified according to whether the chromosome or chromatid is affected by the aberration. Chromosome-type aberrations (CSAs) include chromosome-type breaks, ring chromosomes, marker chromosomes, and dicentric chromosomes; chromatid-type aberrations (CTAs) refer to chromatid breaks and chromatid exchanges (Bonassi et al., 2008; Hagmar et al., 2004). When cells are blocked at the cytokinesis step, When cells are blocked at the cytokinesis step, micronuclei (MN; small nucleus-like structures that contain a chromosome or a piece of a chromosome that was lost during mitosis) can appear in the cytoplasm of binucleated cells. These micronuclei are an indication of CAs and are often related to dicentric chromosomes. Dicentric chromosomes can also cause nucleoplasmic bridges (NPBs; physical connections that exist between the two nuclei) (El-Zein et al., 2014). Other CAs can be assessed by examining the DNA sequence, as is the case when detecting copy number variants (CNVs) (Liu et al., 2013).

OECD defines clastogens as ‘any substance that causes structural chromosomal aberrations in populations of cells or organisms’.

How it is Measured or Detected

CAs can be detected before and after cell division. Widely used assays are described in the table below, however there may be other comparable methods that are not listed. 

Assay	References	Description	OECD-approved assay
Premature Chromosome Condensation (PCC)	Prasanna et al., 2000; Okayasu et al., 2019	Cells are exposed to mitosis-promoting factors (MPF) following cell fusion, causing the chromosomes to condense prematurely. In another approach, cells are exposed to protein phosphatase inhibitors, such as type 1 and 2A protein phosphatases, also causing premature chromosome condensation.	N/A
Chromosomal G-banding	Schwatz, 1990	Use of Giesma dye to stain chromosomal bands, abnormalities determined by the presence of altered morphology	N/A
Fluorescent In Situ  Hybridization (FISH)	Beaton et al., 2013; Pathak et al., 2017	Fluorescent assay of metaphase chromosomes that can detect CAs through chromosome painting and microscopic analysis	N/A
Micronuclei (MN) Assay via Microscopy in vitro	OECD, 2016a	Micronuclei are scored in vitro using microscopy	Yes (No. 487)
Cytokinesis Block Micronucleus (CBMN) Assay with Microscopy in vitro	Fenech, 2000; OECD, 2016a	Cells are cultured with cytokinesis blocking agent, fixed to slides, and undergo MN quantification using microscopy.	Yes (No.487)
Micronucleus (MN) Assay by Microscopy in vivo	OECD, 2016b	Cells are fixed on slides and MN are scored using microscopy. Red blood cells can also be scored for MN using flow cytometry (see below)	Yes (No. 474)
CBMN with Imaging Flow Cytometry	Rodrigues et al., 2015	Cells are cultured with cytokinesis blocking agent, fixed in solution, and imaged with flow cytometry to quantify MN	N/A
Flow cytometry detection of MN	Dertinger et al., 2004; Bryce et al., 2007; OECD 2016a, 2016b	In vivo and in vitro flow cytometry-based, automated micronuclei measurements are also done without cytokinesis block. MN analysis in vivo is performed in peripheral blood cells to detect MN in erythrocytes and reticulocytes.	Yes (No.487; No. 474)
High-throughput biomarker assays (indirect measures to confirm clastogenicity)	Bryce et al. 2014, 2016, 2018   Khoury et al., 2013, Khoury et al., 2016)     Hendriks et al., 2012, 2016; Wink et al., 2014	Multiplexed biomarkers can be measured by flow cytometry are used to discern clastogenic and aneugenic mechanisms for MN induction. Flow cytometry-based quantification of γH2AX foci and p53 protein expression (Bryce et al., 2016).   Prediscreen Assay– In-Cell Western -based quantification of γH2AX   Green fluorescent protein reporter assay to detect the activation of stress signaling pathways, including DNA damage signaling including a reporter porter that is associated with DNA double strand breaks.	N/A
Dicentric Chromosome Assay (DCA)	Abe et al., 2018	Cells are fixed on microscope slides, chromosomes are stained, and the number of dicentric chromosomes are quantified	N/A
High content imaging	Shahane et al., 2016	DNA can be stained using fluorescent dyes and micronuclei can be scored high-throughput microscopy image analysis.	N/A
Chromosomal aberration test	OECD, 2016c; 2016d; 20l16e	In vitro, the cell cycle is arrested at metaphase after 1.5 cell cycle following 3-6 hour exposure   In vivo, the test chemical is administered as a single treatment and bone marrow is collected 18-24 hrs later (TG 475), while testis is collected 24-48 hrs later (TG 483). The cell cycle is arrested with a metaphase-arresting chemical (e.g., colchicine) 2-5 hours before cell collection. Once cells are fixed and stained on microscope slides, chromosomal aberrations are scored	Yes. In vitro (No. 473) In vivo (No. 475 and No. 483)
Array Comparative Genomic Hybridization (aCGH) or SNP Microarray	Adewoye et al., 2015; Wilson et al., 2015; Arlt et al., 2014; Redon et al., 2006; Keren, 2014; Mukherjee, 2017	CNVs are most commonly detected using global DNA microarray technologies; This method, however, is unable to detect balanced CAs, such as inversions	N/A
Next Generation Sequencing (NGS): Whole Genome Sequencing (WGS) or Whole Exome Sequencing (WES)	Liu, 2013; Shen, 2016; Mukherjee, 2017	CNVs are detected by fragmenting the genome and using NGS to sequence either the entire genome (WGS), or only the exome (WES); Challenges with this methodology include only being able to detect CNVs in exon-rich areas if using WES, the computational investment required for the storage and analysis of these large datasets, and the lack of computational algorithms available for effectively detecting somatic CNVs	N/A

 

References

Abe, Y et al. (2018), “Dose-response curves for analyzing of dicentric chromosomes and chromosome translocations following doses of 1000 mGy or less, based on irradiated peripheral blood samples from five healthy individuals”,  J Radiat Res. 59(1), 35-42. doi:10.1093/jrr/rrx052

Adewoye, A.B.et al. (2015), “The genome-wide effects of ionizing radiation on mutation induction in the mammalian germline”, Nat. Commun. 6:66-84. doi: 10.1038/ncomms7684.

Arlt MF, Wilson TE, Glover TW. (2012), “Replication stress and mechanisms of CNV formation”, Curr Opin Genet Dev. 22(3):204-10. doi: 10.1016/j.gde.2012.01.009.

Arlt, MF. Et al. (2014), “Copy number variants are produced in response to low-dose ionizing radiation in cultured cells”, Environ Mol Mutagen. 55(2):103-13. doi: 10.1002/em.21840.

Beaton, L. A. et al. (2013), “Investigating chromosome damage using fluorescent in situ hybridization to identify biomarkers of radiosensitivity in prostate cancer patients”, Int J Radiat Biol. 89(12): 1087-1093. doi:10.3109/09553002.2013.825060

Boei, J.J., Vermeulen, S., Natarajan, A.T. (1996), “Detection of chromosomal aberrations by fluorescence in situ hybridization in the first three postirradiation divisions of human lymphocytes”, Mutat Res, 349:127-135. Doi: 10.1016/0027-5107(95)00171-9.

Bonassi, S.  (2008),”Chromosomal aberration frequency in lymphocytes predicts the risk of cancer: results from a pooled cohort study of 22 358 subjects in 11 countries”, Carcinogenesis. 29(6):1178-83. doi: 10.1093/carcin/bgn075.

Bryce SM, Bemis JC, Avlasevich SL, Dertinger SD. In vitro micronucleus assay scored by flow cytometry provides a comprehensive evaluation of cytogenetic damage and cytotoxicity. Mutat Res. 2007 Jun 15;630(1-2):78-91. doi: 10.1016/j.mrgentox.2007.03.002. Epub 2007 Mar 19. PMID: 17434794; PMCID: PMC1950716.

Bryce, S. et al. (2014), “Interpreting In VitroMicronucleus Positive Results: Simple Biomarker Matrix Discriminates Clastogens, Aneugens, and Misleading Positive Agents”, Environ Mol Mutagen, 55:542-555. Doi:10.1002/em.21868.

Bryce, S. et al.(2016), “Genotoxic mode of action predictions from a multiplexed flow cytometric assay and a machine learning approach”, Environ Mol Mutagen, 57:171-189. Doi: 10.1002/em.21996.

Bryce SM, Bernacki DT, Smith-Roe SL, Witt KL, Bemis JC, Dertinger SD. Investigating the Generalizability of the MultiFlow ® DNA Damage Assay and Several Companion Machine Learning Models With a Set of 103 Diverse Test Chemicals. Toxicol Sci. 2018 Mar 1;162(1):146-166. doi: 10.1093/toxsci/kfx235. PMID: 29106658; PMCID: PMC6059150.

Bunting, S. F., & Nussenzweig, A. (2013), “End-joining, translocations and cancer”, Nature Reviews Cancer.13 (7): 443-454. doi:10.1038/nrc3537

Cornforth, M.N., S.M. Bailey, and E.H. Goodwin. (2002), “Dose Responses for Chromosome Aberrations Produced in Noncycling Primary Human Fibroblasts by Alpha Particles, and by Gamma Rays Delivered at Sublimating Low Dose Rates”, Radiation Research, Vol.158, Radiation Research Society, Indianapolis, https://doi.org/10.1667/0033-7587(2002)158[0043:DRFCAP]2.0.CO;2.  

Curtis, C. et al. (2012), “The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups”, Nature. 486(7403):346-52. doi: 10.1038/nature10983.

Dertinger, S.D. et al.(2004), “Three-color labeling method for flow cytometric measurement of cytogenetic damage in rodent and human blood”, Environ Mol Mutagen, 44:427-435. Doi: 10.1002/em.20075.

El-Zein, RA. Et al. (2014), “The cytokinesis-blocked micronucleus assay as a strong predictor of lung cancer: extension of a lung cancer risk prediction model”,  Cancer Epidemiol Biomarkers Prev. 23(11):2462-70. doi: 10.1158/1055-9965.EPI-14-0462.

Fenech, M. (2000), “The in vitro micronucleus technique”, Mutation Research. 455(1-2), 81-95. Doi: 10.1016/s0027-5107(00)00065-8

Ferguson-Smith, M.A. (2015), “History and evolution of cytogenetics”, Molecular Cytogenetics, Vol.8/19, Biomed Central, London, https://doi.org/10.1186/s13039-015-0125-8. 

Franken, N.A.P. et al. (2012), “Relative biological effectiveness of high linear energy transfer alpha-particles for the induction of DNA-double-strand breaks, chromosome aberrations and reproductive cell death in SW-1573 lung tumour cells”, Oncology Reports, Vol.27, Spandidos Publications, Athens, https://doi.org/10.3892/or.2011.1604. 

Gardner, R.M., G.R. Sutherland, and L.G. Shaffer. (2011), “Chapter 1: Elements in Medical Cytogenetics” in Chromosome abnormalities and genetic counseling (No. 61), Oxford University Press, USA, pp.7-15. 

Griffiths, A. J. F., Miller, J. H., & Suzuki, D. T. (2000), “An Introduction to Genetic Analysis”, 7th edition. New York: W. H. Freeman. Available from: https://www.ncbi.nlm.nih.gov/books/NBK21766/

Hagmar, L. et al. (2004), “Impact of types of lymphocyte chromosomal aberrations on human cancer risk: results from Nordic and Italian cohorts”, Cancer Res. 64(6):2258-63.

Hastings PJ, Ira G & Lupski JR. (2009), “A microhomology-mediated break-induced replication model for the origin of human copy number variation”. PLoS Genet. 2009 Jan;5(1): e1000327. doi: 10.1371/journal.pgen.1000327.

Hendriks, G. et al. (2012), “The ToxTracker assay: novel GFP reporter systems that provide mechanistic insight into the genotoxic properties of chemicals”, Toxicol Sci, 125:285-298. Doi: 10.1093/toxsci/kfr281.

Hendriks, G. et al. (2016), “The Extended ToxTracker Assay Discriminates Between Induction of DNA Damage, Oxidative Stress, and Protein Misfolding”, Toxicol Sci, 150:190-203. Doi: 10.1093/toxsci/kfv323.

Kašuba, V., et al. (1995), “Chromosome aberrations in peripheral blood lymphocytes from control individuals”, Mutation Research Letters, Vol.346/4, Elsevier, Amsterdam, https://doi.org/10.1016/0165-7992(95)90034-9. 

Keren, B. (2014),”The advantages of SNP arrays over CGH arrays”, Molecular Cytogenetics.7( 1):I31. Doi: 10.1186/1755-8166-7-S1-I31.

Khoury, L., Zalko, D., Audebert, M. (2016), “Evaluation of four human cell lines with distinct biotransformation properties for genotoxic screening”, Mutagenesis. 31:83-96. Doi: 10.1093/mutage/gev058.

Khoury, L., Zalko, D., Audebert, M. (2013), “Validation of high-throughput genotoxicity assay screening using cH2AX in-cell Western assay on HepG2 cells”, Environ Mol Mutagen, 54:737-746. Doi: 10.1002/em.21817.

Lee JA, Carvalho CM, Lupski JR. (2007). “Replication mechanism for generating nonrecurrent rearrangements associated with genomic disorders”, Cell. 131(7):1235-47. Doi: 10.1016/j.cell.2007.11.037.

Liu B. et al. (2013). “Computational methods for detecting copy number variations in cancer genome using next generation sequencing: principles and challenges”, Oncotarget. 4(11):1868-81. Doi: 10.18632/oncotarget.1537.

Loucas, B.D., et al. (2013), “Chromosome Damage in Human Cells by Gamma Rays, Alpha Particles and Heavy Ions: Track Interactions in Basic Dose-Response Relationships”, Radiation Research, Vol.179/1, Radiation Research Society, Indianapolis, https://doi.org/10.1667/RR3089.1. 

Mitelman, F. (1982), “Application of cytogenetic methods to analysis of etiologic factors in carcinogenesis”, IARC Sci Publ, 39:481-496.

Mukherjee. S. et al. (2017), “Addition of chromosomal microarray and next generation sequencing to FISH and classical cytogenetics enhances genomic profiling of myeloid malignancies, Cancer Genet. 216-217:128-141. doi: 10.1016/j.cancergen.2017.07.010.

Obe, G. et al. (2002), “Chromosomal Aberrations: formation, Identification, and Distribution”, Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis. 504(1-2), 17-36. Doi: 10.1016/s0027-5107(02)00076-3.

Savage, J.R. (1976), “Classification and relationships of induced chromosomal structual changes”, J Med Genet, 13:103-122. Doi: 10.1136/jmg.13.2.103.

Shahane SA, Nishihara K, Xia M. High-Throughput and High-Content Micronucleus Assay in CHO-K1 Cells. Methods Mol Biol. 2016;1473:77-85. doi: 10.1007/978-1-4939-6346-1_9. PMID: 27518626.

OECD (2016a), Test No. 487: In Vitro Mammalian Cell Micronucleus Test, OECD Guidelines for the Testing of Chemicals, Section 4, OECD Publishing, Paris, https://doi.org/10.1787/9789264264861-en.

OECD (2016a), Test No. 487: In Vitro Mammalian Cell Micronucleus Test, OECD Guidelines for the Testing of Chemicals, Section 4, OECD Publishing, Paris, https://doi.org/10.1787/9789264264861-en. 

OECD. (2016b), “Test No. 474: Mammalian Erythrocyte Micronucleus Test. OECD Guideline for the Testing of Chemicals, Section 4.”Paris: OECD Publishing.

OECD. (2016c), “In Vitro Mammalian Chromosomal Aberration Test 473.”

OECD. (2016d). Test No. 475: Mammalian Bone Marrow Chromosomal Aberration Test. OECD Guideline for the Testing of Chemicals, Section 4. Paris: OECD Publishing.

OECD. (2016e). Test No. 483: Mammalian Spermatogonial Chromosomal Aberration Test. Paris: OECD Publishing.

Okayasu, R. and C. Liu. (2019), “G1 premature chromosome condensation (PCC) assay”, Methods in molecular biology, Humana Press, Totowa, https://doi.org/10.1007/978-1-4939-9432-8_4.  

Pathak, R., Koturbash, I., & Hauer-Jensen, M. (2017), “Detection of Inter-chromosomal Stable Aberrations by Multiple Fluorescence In Situ Hybridization (mFISH) and Spectral Karyotyping (SKY) in Irradiated Mice”, J Vis Exp(119). doi:10.3791/55162.

Prasanna, P. G. S., N. D. Escalada and W. F. Blakely (2000), “Induction of premature chromosome condensation by a phosphatase inhibitor and a protein kinase in unstimulated human peripheral blood lymphocytes: a simple and rapid technique to study chromosome aberrations using specific whole-chromosome DNA hybridization probes for biological dosimetry”, Mutation Research, Vol. 466/2, Elsevier B.V., Amsterdam, https://doi/org/10.1016/S1383-5718(00)00011-5 

Redon, R. et al. (2006), “Global variation in copy number in the human genome”, Nature. 444(7118):444-54. 10.1038/nature05329.

Rodrigues, M. A., Beaton-Green, L. A., & Wilkins, R. C. (2016), “Validation of the Cytokinesis-block Micronucleus Assay Using Imaging Flow Cytometry for High Throughput Radiation Biodosimetry”, Health Phys. 110(1): 29-36. doi:10.1097/HP.0000000000000371

Schwartz, G. G. (1990), “Chromosome aberrations. Biological Markers in Epidemiology (BS Hulka, TC Wlwosky, and JD Griffith, Eds.)”, Oxford University Press, Oxford, pp.147-172.  

Shahane S, Nishihara K, Xia M. (2016), “High-Throughput and High-Content Micronucleus Assay in CHO-K1 Cells”, In: Zhu H, Xia M, editors. High-Throughput Screening Assays in Toxicology. New York, NY: Humana Press. p 77-85.

Shen.TW,  (2016),”Concurrent detection of targeted copy number variants and mutations using a myeloid malignancy next generation sequencing panel allows comprehensive genetic analysis using a single testing strategy”, Br J Haematol. 173(1):49-58. doi: 10.1111/bjh.13921.

Shlien A, Malkin D. (2009), “Copy number variations and cancer”, Genome Med. 1(6):62. doi: 10.1186/gm62.

Tucker, J.D., Preston, R.J. (1996), “Chromosome aberrations, micronuclei, aneuploidy, sister chromatid exchanges, and cancer risk assessment”, Mutat Res, 365:147-159.

Vick, E. et al. (2017), Age-related chromosomal aberrations in patients with diffuse large B-cell lymphoma, American Society of Hematology, https://doi.org/10.1182/blood.V130.Suppl_1.1571.1571 

Wilson, TE. et al.  (2015), “Large transcription units unify copy number variants and common fragile sites arising under replication stress”, Genome Res. 25(2):189-200. doi: 10.1101/gr.177121.114.

Wink, S. et al. (2014), “Quantitative high content imaging of cellular adaptive stress response pathways in toxicity for chemical safety assessment”, Chem Res Toxicol, 27:338-355.

Zhang N, Wang M, Zhang P, Huang T. 2016. Classification of cancers based on copy number variation landscapes. Biochim Biophys Acta.  1860(11 Pt B):2750-5. doi: 10.1016/j.bbagen.2016.06.003.

Event: 870: Increase, Cell Proliferation

Short Name: Increase, Cell Proliferation

Key Event Component

AOPs Including This Key Event

Stressors

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

 Cell proliferation is a central process supporting development, tissue homeostasis and carcinogenesis, each of which occur in all vertebrates. This key event has been observed nasal tissues of rats exposed to the chemical initiator vinyl acetate. In general, cell proliferation is necessary in the biological development and reproduction of most organisms. This KE is thus relevant and applicable to all multicellular cell types, tissue types, and taxa.

Life stage applicability: This key event is not life stage specific (Fujimichi and Hamada, 2014; Barnard et al., 2022).

Sex applicability: This key event is not sex specific (Markiewicz et al., 2015).

Evidence for perturbation by a stressor: There is a large body of evidence supporting the effectiveness of ionizing radiation, UV, and mechanical wounding as stressors for increased cell proliferation. These stressors can be subdivided into X-rays (van Sallmann, 1951; Ramsell and Berry, 1966; Richards, 1966; Riley et al., 1988; Riley et al., 1989; Kleiman et al., 2007; Pendergrass et al., 2010; Fujimichi and Hamada, 2014, Markiewicz et al., 2015; Bahia et al., 2018), 60Co γ-rays (Hanna and O’Brien, 1963; Barnard et al., 2022; McCarron et al., 2021), 137Cs γ-rays (Andley and Spector, 2005), neutrons (Richards, 1966; Riley et al., 1988; Riley et al., 1989), 40Ar (Worgul et al., 1986), 56Fe (Riley et al., 1989), UVB (Söderberg et al., 1986; Andley et al., 1994; Cheng et al., 2019), UVC (Trenton and Courtois, 1981), and mechanical wounding (Riley et al., 1989).

Key Event Description

Throughout their life, cells replicate their organelles and genetic information before dividing to form two new daughter cells, in a process known as cellular proliferation. This replicative process is known as the cell cycle and is subdivided into various stages notably, G1, S, G2, and M in mammals. G1 and G2 are gap phases, separating mitosis and DNA synthesis. Differentiated cells typically remain in G1; however, quiescent cells reside in an optional phase just before G1, known as G0.  

Progression through the cycle is dependent on sufficient nutrient availability to provide optimal nucleic acid, protein, and lipid levels, as well as sufficient cell mass. To this end, the cell cycle is mediated by three major checkpoints: the restriction (R) point, or G1/S checkpoint, controlling entry into S phase, the G2/M checkpoint, controlling entry into mitosis, and one more controlling entry into cytokinesis. If conditions are ideal for division, cells will pass the restriction point (G1/S) and begin the activation and expression of genes used for duplicating centrosomes and DNA, eventually leading to proliferation (Cuyàs et al., 2014).  

Various protein complexes, known as cyclins, cyclin-dependent kinases (CDKs), and cyclin-dependent kinase inhibitors (CKIs) regulate passage through each phase by activating and inhibiting specific processes (Lovicu et al., 2014). The CDKs are responsible for controlling progression through the cell cycle. They promote DNA synthesis and mitosis, and therefore cell division (Barnum & O’Connell, 2014). Furthermore, growth factors are required to stimulate cell division, but after passing through the restriction point at G1 they are no longer necessary (Lovicu et al., 2014).  

In the context of cancer, one hallmark is the sustained and uncontrolled cell proliferation (Hanahan et al., 2011, Portt et al., 2011). When cells obtain a growth advantage due to mutations in critical genes that regulate cell cycle progression, they may begin to proliferate excessively, resulting in hyperplasia and potentially leading to the development of a tumor. This is often achieved through oncogene activation and inactivation of tumor suppressor genes (Hanahan et al., 2011). Cell inactivation and the replacement of these cells can initiate clonal expansion (Heidenreich adn Paretzke et al., 2008). 

Sustained atrophy/degeneration olfactory epithelium under the influence of a cytotoxic agent leads to adaptive tissue remodeling. Cell types unique to olfactory epithelium, e.g. olfactory neurons, sustentacular cells and Bowmans glands, are replaced by cell types comprising respiratory epithelium or squamous epithelium.

How it is Measured or Detected

Two common methods of measuring cell proliferation in vivo are the use of Bromodeoxyuridine (5-bromo-2'-deoxyuridine, BrdU) labeling (Pera, 1977), and Ki67 immunostaining (Grogan, 1988). BrdU is a synthetic analogue of the nucleoside Thymidine. BrDu is incorporated into DNA synthesized during the S1 phase of cell replication and is stable for long periods. Labeling of dividing cells by BrdU is accomplished by infusion, bolus injection, or implantation of osmotic pumps containing BrdU for a period of time sufficient to generate measureable numbers of labeled cells. Tissue sections are stained immunhistochemically with antibodies for BrdU and labeled cells are counted as dividing cells. Similarly, 5-iodo-2'-deoxyuridine (IdU) is another analogue of thymidine used to measure cell proliferation as it is also incorporated into DNA during its synthesis (Devine & Behbehani, 2021). Ki67 is a cellular marker of replication not found in quiescent cells (Roche, 2015). Direct immunohistochemical staining of cells for protein Ki67 using antibodies is an alternative to the use of BrdU, with the benefit of not requiring a separate treatment (injection for pulse-labeling). Cells positive for Ki67 are counted as replicating cells. Replicating cell number is reported per unit tissue area or per cell nuclei (Bogdanffy, 1997). Listed below are common methods for detecting the KE, however there may be other comparable methods that are not listed.

Assay Name	References	Description	OECD Approved Assay
CyQuant Cell Proliferation Assay	Jones et al., 2001	DNA-binding dye is added to cell cultures, and the dye signal is measured directly to provide a cell count and thus an indication of cellular proliferation	N/A
Nucleotide Analog Incorporation Assays (e.g. BrdU, EdU)	Romar et al., 2016, Roche; 2013	Nucleoside analogs are added to cells in culture or injected into animals and become incorporated into the DNA at different rates, depending on the level of cellular proliferation; Antibodies conjugated to a peroxidase or fluorescent tag are used for quantification of the incorporated nucleoside analogs using techniques such as ELISA, flow cytometry, or microscopy	Yes (No. 442B)
Cytoplasmic Proliferation Dye Assays	Quah & Parish, 2012	Cells are incubated with a cytoplasmic dye of a certain fluorescent intensity; Cell divisions decrease the intensity in such a way that the number of divisions can be calculated using flow cytometry measurements	N/A
Colourimetric Dye Assays	Vega-Avila & Pugsley, 2011; American Type Culture Collection	Cells are incubated with a dye that changes colour following metabolism; Colour change can be measured and extrapolated to cell number and thus provide an indication of cellular proliferation rates	N/A
BrdU, Ki67, IdU Quantification - Flow Cytometry	Ligasová et al., 2017; Devine & Behehani, 2021; Kim & Sederstrom, 2015	Measurement of cell proliferation biomarkers by flow cytometry, normalized to total levels of BrdU, Ki67 or IdU.	No

 

References

Andley, U. P. et al. (1994), “Modulation of lens epithelial cell proliferation by enhanced prostaglandin synthesis after UVB exposure”, Investigative Ophthalmology & Visual Science, Vol. 35/2, Rockville, pp. 374-381  

Andley, U. and A. Spector (2005), “Peroxide resistance in human and mouse lens epithelial cell lines is related to long-term changes in cell biology and architecture”, Free Radical Biology & Medicine, Vol. 39/6, Elsevier B.V, United States, https://doi.org/10.1016/j.freeradbiomed.2005.04.028 

Bahia, S. et al. (2018), “Oxidative and nitrative stress-related changes in human lens epithelial cells following exposure to X-rays”, International journal of radiation biology, Vol. 94/4, England, https://doi.org/10.1080/09553002.2018.1439194 

Barnard, S. et al. (2022), “Lens Epithelial Cell Proliferation in Response to Ionizing Radiation.”, Radiation Research, Vol. 197/1, Radiation Research Society, United States, https://doi.org/10.1667/RADE-20-00294.1 

Barnum, K. and M. O’Connell (2014), “Cell cycle regulation by checkpoints”, in Cell cycle control, Springer, New York, http://doi.org/ 10.1007/978-1-4939-0888-2 

Bogdanffy. et al. (1997). “FOUR-WEEK INHALATION CELL PROLIFERATION STUDY OF THE EFFECTS OF VINYL ACETATE ON RAT NASAL EPITHELIUM”, Inhalation Toxicology, Taylor & Francis. 9: 331-350.

Cheng, T. et al. (2019), “lncRNA H19 contributes to oxidative damage repair in the early age-related cataract by regulating miR-29a/TDG axis”, Journal of cellular and molecular medicine, Vol. 23/9, Wiley Subscription Services, Inc. England, https://doi.org/10.1111/jcmm.14489 

Cuyàs, E. et al. (2014), “Cell cycle regulation by the nutrient-sensing mammalian target of rapamycin (mTOR) pathway”, in Cell cycle control, Springer, New York, http://dx.doi.org/ 10.1007/978-1-4939-0888-2 

Devine,R. D, and G. K. Behbehani (2021), “Use of the Pyrimidine Analog, 5-Iodo-2'-Deoxyuridine (IdU) with Cell Cycle Markers to establish Cell Cycle Phases in a Mass Cytometry Platform”, Journal of visualized experiments. (176). doi:10.3791/60556  

Fujimichi, Y. and N. Hamada (2014), “Ionizing irradiation not only inactivates clonogenic potential in primary normal human diploid lens epithelial cells but also stimulates cell proliferation in a subset of this population”, PloS one, Vol. 9/5, e98154, Public Library of Science, United States, https://doi.org/10.1371/journal.pone.0098154 

Grogan. et al. (1988). “Independent prognostic significance of a nuclear proliferation antigen in diffuse large cell lymphomas as determined by the monoclonal antibody Ki-67”, Blood. 71: 1157-1160.

Hanna, C. and J. E. O’Brien (1963), “Lens epithelial cell proliferation and migration in radiation cataracts”, Radiation research, Academic Press, Inc, United States, https://doi.org/10.2307/3571405 

Hanahan, D. & R. A. Weinberg, (2011),” Hallmarks of cancer: the next generation”, Cell. 144(5):646-74. doi: 10.1016/j.cell.2011.02.013.

Heidenreich WF, Paretzke HG. (2008) Promotion of initiated cells by radiation-induced cell inactivation. Radiat Res. Nov;170(5):613-7. doi: 10.1667/RR0957.1. PMID: 18959457.

Jones, J. L. et al. (2001), Sensitive determination of cell number using the CyQUANT cell proliferation assay. Journal of Immunological Methods. 254(1-2), 85-98. Doi:10.1016/s0022-1759(01)00404-5.

Kim, K. H. and Sederstrom J. M. (2015), “Assaying Cell Cycle Status Using Flow Cytometry.” Current protocols in molecular biology, 111:28.6.1-28.6.11., doi:10.1002/0471142727.mb2806s111  

Kleiman, N. J. et al. (2007), “Mrad9 and Atm haplinsufficiency enhance spontaneous and X-ray-induced cataractogenesis in mice”, Radiation research, Vol. 168/5, Radiation Research Society, United States, https://doi.org/10.1667/rr1122.1 

Ligasová, A. et al. (2017), “Cell cycle profiling by image and flow cytometry: The optimised protocol for the detection of replicational activity using 5-Bromo-2'-deoxyuridine, low concentration of hydrochloric acid and exonuclease III.” PloS one, 12(4): e0175880, doi:10.1371/journal.pone.0175880  

Lovicu, J. et al (2014), “Lens epithelial cell proliferation”, in Lens epithelium and posterior capsular opacification, Springer, Tokyo, http://dx.doi.org/ 10.1007/978-4-431-54300-8_4 

Markiewicz, E. et al. (2015), “Nonlinear ionizing radiation-induced changes in eye lens cell proliferation, cyclin K1 expression and lens shape”, Open biology, Vol. 5/4, The Royal Society, England, https://doi.org/10.1098/rsob.150011 

McCarron, R. A. et al. (2021), “Radiation-induced lens opacity and cataractogenesis: a lifetime study using mice of varying genetic backgrounds”, Radiation research, Vol. 197/1, Radiation Research Society, United States, https://doi.org/10.1667/RADE-20-00266.1 

Pendergrass, W. et al. (2010), “X-ray induced cataract is preceded by LEC loss, and coincident with accumulation of cortical DNA, and ROS; similarities with age-related cataracts”, Molecular vision, Vol. 16, Molecular Vision, United States, pp. 1496-1513 

Pera, Mattias and Detzer (1977). “Methods for determining the proliferation kinetics of cells by means of 5-bromodeoxyuridine”, Cell Tissue Kinet.10: 255-264. Doi: 10.1111/j.1365-2184.1977.tb00293.x.

Portt, L. et al. (2011), “Anti-apoptosis and cell survival: a review”, Biochim Biophys Acta. 21813(1):238-59. doi: 10.1016/j.bbamcr.2010.10.010.

Quah, J. C. B. & R. C. Parish (2012), “New and improved methods for measuring lymphocyte proliferation in vitro and in vivo using CFSE-like fluorescent dyes”, Journal of Immunological Methods. 379(1-2), 1-14. doi: 10.1016/j.jim.2012.02.012.

Ramsell, T. G. and R. J. Berry (1966), “Recovery from X-ray damage to the lens. The effects of fractionated X-ray doses observed in rabbit lens epithelium irradiated in vivo”, British Journal of Radiology, Vol. 39/467, England, pp. 853-858 

Riley, E. F. et al. (1988), “Recovery of murine lens epithelial cells from single and fractionated doses of X rays and neutrons”, Radiation Research, Vol. 114/3, Academic Press Inc, Oak Brook, https://doi.org/10.2307/3577127 

Riley, E. F. et al. (1989), “Comparison of recovery from potential mitotic abnormality in mitotically quiescent lens cells after X, neutron, and 56Fe irradiations”, Radiation Research, Vol. 119/2, United States, pp. 232-254 

Richards, R. D. (1966), “Changes in lens epithelium after X-ray or neutron irradiation (mouse and rabbit)”, Transactions of the American Ophthalmological Society, Vol. 64, United States, pp. 700-734 

Roche Applied Science, (2013), “Cell Proliferation Elisa, BrdU (Colourmetric) ». Version 16

Romar, A. G., S. T. Kupper & J. S. Divito (2015), “Research Techniques Made Simple: Techniques to Assess Cell Proliferation”,  Journal of Investigative Dermatology. 136(1), e1-7. doi: 10.1016/j.jid.2015.11.020.

Söderberg, P. G. et al. (1986), “Unscheduled DNA synthesis in lens epithelium after in vivo exposure to UV radiation in the 300 nm wavelength region”, Acta Ophthalmologica, Vol. 64/2, Blackwell Publishing Ltd, Oxford, UK, https://doi.org/10.1111/j.1755-3768.1986.tb06894.x 

Trenton, J. A. and Y. Courtois (1981), “Evolution of the distribution, proliferation and ultraviolet repair capacity of rat lens epithelial cells as a function of maturation and aging”, Mechanisms of Ageing and Development, Vol. 15/3, Elsevier, Ireland, https://doi.org/1016/0047-6374(81)90134-2 

Vega-Avila, E. & K. M. Pugsley (2011), “An Overview of Colorimetric Assay Methods Used to Assess Survival or Proliferation of Mammalian Cells”, Proc. West. Pharmacol. Soc. 54, 10-4.

von Sallmann, L. (1951), “Experimental studies on early lens changes after x-ray irradiation III. Effect of X-radiation on mitotic activity and nuclear fragmentation of lens epithelium in normal and cysteine-treated rabbits”, Transactions of the American Ophthalmological Society, Vol. 48, United States, pp. 228-242 

Worgul, B. V. et al. (1986), “Accelerated heavy particles and the lens II. Cytopathological changes”, Investigative Ophthalmology and Visual Science, Vol 27/1, pp. 108-114 

Event: 1392: Oxidative Stress

Short Name: Oxidative Stress

Key Event Component

AOPs Including This Key Event

Stressors

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability: Occurrence of oxidative stress is not species specific.  

Life stage applicability: Occurrence of oxidative stress is not life stage specific. 

Sex applicability: Occurrence of oxidative stress is not sex specific. 

Evidence for perturbation by prototypic stressor: There is evidence of the increase of oxidative stress following perturbation from a variety of stressors including exposure to ionizing radiation and altered gravity (Bai et al., 2020; Ungvari et al., 2013; Zhang et al., 2009).  

Key Event Description

Oxidative stress is defined as an imbalance in the production of reactive oxygen species (ROS) and antioxidant defenses. High levels of oxidizing free radicals can be very damaging to cells and molecules within the cell.  As a result, the cell has important defense mechanisms to protect itself from ROS. For example, Nrf2 is a transcription factor and master regulator of the oxidative stress response. During periods of oxidative stress, Nrf2-dependent changes in gene expression are important in regaining cellular homeostasis (Nguyen, et al., 2009) and can be used as indicators of the presence of oxidative stress in the cell. 

In addition to the directly damaging actions of ROS, cellular oxidative stress also changes cellular activities on a molecular level. Redox sensitive proteins have altered physiology in the presence and absence of ROS, which is caused by the oxidation of sulfhydryls to disulfides on neighboring amino acids (Antelmann & Helmann 2011). Importantly Keap1, the negative regulator of Nrf2, is regulated in this manner (Itoh, et al. 2010). 

ROS also undermine the mitochondrial defense system from oxidative damage. The antioxidant systems consist of superoxide dismutase, catalase, glutathione peroxidase and glutathione reductase, as well as antioxidants such as α-tocopherol and ubiquinol, or antioxidant vitamins and minerals including vitamin E, C, carotene, lutein, zeaxanthin, selenium, and zinc (Fletcher, 2010). The enzymes, vitamins and minerals catalyze the conversion of ROS to non-toxic molecules such as water and O2. However, these antioxidant systems are not perfect and endogenous metabolic processes and/or exogenous oxidative influences can trigger cumulative oxidative injuries to the mitochondria, causing a decline in their functionality and efficiency, which further promotes cellular oxidative stress (Balasubramanian, 2000; Ganea & Harding, 2006; Guo et al., 2013; Karimi et al., 2017).  

However, an emerging viewpoint suggests that ROS-induced modifications may not be as detrimental as previously thought, but rather contribute to signaling processes (Foyer et al., 2017). 

 

Sources of ROS Production 

Direct Sources: Direct sources involve the deposition of energy onto water molecules, breaking them into active radical species. When ionizing radiation hits water, it breaks it into hydrogen (H*) and hydroxyl (OH*) radicals by destroying its bonds. The hydrogen will create hydroxyperoxyl free radicals (HO2*) if oxygen is available, which can then react with another of itself to form hydrogen peroxide (H2O2) and more O2 (Elgazzar and Kazem, 2015). Antioxidant mechanisms are also affected by radiation, with catalase (CAT) and peroxidase (POD) levels rising as a result of exposure (Seen et al. 2018; Ahmad et al. 2021).  

Indirect Sources: An indirect source of ROS is the mitochondria, which is one of the primary producers in eukaryotic cells (Powers et al., 2008).  As much as 2% of the electrons that should be going through the electron transport chain in the mitochondria escape, allowing them an opportunity to interact with surrounding structures. Electron-oxygen reactions result in free radical production, including the formation of hydrogen peroxide (H2O2) (Zhao et al., 2019). The electron transport chain, which also creates ROS, is activated by free adenosine diphosphate (ADP), O2, and inorganic phosphate (Pi) (Hargreaves et al. 2020; Raimondi et al. 2020; Vargas-Mendoza et al. 2021). The first and third complexes of the transport chain are the most relevant to mammalian ROS production (Raimondi et al., 2020). The mitochondria has its own set of DNA and it is a prime target of oxidative damage (Guo et al., 2013). ROS is also produced through nicotinamide adenine dinucleotide phosphate oxidase (Nox) stimulation, an event commenced by angiotensin II, a product/effector of the renin-angiotensin system (Nguyen Dinh Cat et al. 2013; Forrester et al. 2018). Other ROS producers include xanthine oxidase, immune cells (macrophage, neutrophils, monocytes, and eosinophils), phospholipase A2 (PLA2), monoamine oxidase (MAO), and carbon-based nanomaterials (Powers et al. 2008; Jacobsen et al. 2008; Vargas-Mendoza et al. 2021). 

How it is Measured or Detected

Oxidative Stress: Direct measurement of ROS is difficult because ROS are unstable. The presence of ROS can be assayed indirectly by measurement of cellular antioxidants, or by ROS-dependent cellular damage. Listed below are common methods for detecting the KE, however there may be other comparable methods that are not listed 

• Detection of ROS by chemiluminescence (https://www.sciencedirect.com/science/article/abs/pii/S0165993606001683) 
• Detection of ROS by chemiluminescence is also described in OECD TG 495 to assess phototoxic potential. 
• Glutathione (GSH) depletion. GSH can be measured by assaying the ratio of reduced to oxidized glutathione (GSH:GSSG) using a commercially available kit (e.g., http://www.abcam.com/gshgssg-ratio-detection-assay-kit-fluorometric-green- ab138881.html). 
• TBARS. Oxidative damage to lipids can be measured by assaying for lipid peroxidation using TBARS (thiobarbituric acid reactive substances) using a commercially available kit. 
• 8-oxo-dG. Oxidative damage to nucleic acids can be assayed by measuring 8-oxo-dG adducts (for which there are a number of ELISA based commercially available kits),or HPLC, described in Chepelev et al. (Chepelev, et al. 2015). 

  

Molecular Biology: Nrf2. Nrf2’s transcriptional activity is controlled post-translationally by oxidation of Keap1. Assay for Nrf2 activity include: 

• Immunohistochemistry for increases in Nrf2 protein levels and translocation into the nucleus Western blot for increased Nrf2 protein levels 
• Western blot of cytoplasmic and nuclear fractions to observe translocation of Nrf2 protein from the cytoplasm to the nucleus qPCR of Nrf2 target genes (e.g., Nqo1, Hmox-1, Gcl, Gst, Prx, TrxR, Srxn), or by commercially available pathway-based qPCR array (e.g., oxidative stress array from SABiosciences) 
• Whole transcriptome profiling by microarray or RNA-seq followed by pathway analysis (in IPA, DAVID, metacore, etc.) for enrichment of the Nrf2 oxidative stress response pathway (e.g., Jackson et al. 2014) 
• OECD TG422D describes an ARE-Nrf2 Luciferase test method 

In general, there are a variety of commercially available colorimetric or fluorescent kits for detecting Nrf2 activationOxidative Stress. Direct measurement of ROS is difficult because ROS are unstable. The presence of ROS can be assayed indirectly by measurement of cellular antioxidants, or by ROS-dependent cellular damage. Listed below are common methods for detecting the KE, however there may be other comparable methods that are not listed 

 

• Detection of ROS by chemiluminescence (https://www.sciencedirect.com/science/article/abs/pii/S0165993606001683) 

• Detection of ROS by chemiluminescence is also described in OECD TG 495 to assess phototoxic potential. 

• Glutathione (GSH) depletion. GSH can be measured by assaying the ratio of reduced to oxidized glutathione (GSH:GSSG) using a commercially available kit (e.g., http://www.abcam.com/gshgssg-ratio-detection-assay-kit-fluorometric-green- ab138881.html). 

• TBARS. Oxidative damage to lipids can be measured by assaying for lipid peroxidation using TBARS (thiobarbituric acid reactive substances) using a commercially available kit. 

• 8-oxo-dG. Oxidative damage to nucleic acids can be assayed by measuring 8-oxo-dG adducts (for which there are a number of ELISA based commercially available kits),or HPLC, described in Chepelev et al. (Chepelev, et al. 2015). 

  

Molecular Biology: Nrf2. Nrf2’s transcriptional activity is controlled post-translationally by oxidation of Keap1. Assay for Nrf2 activity include: 

  

• Immunohistochemistry for increases in Nrf2 protein levels and translocation into the nucleus Western blot for increased Nrf2 protein levels 

• Western blot of cytoplasmic and nuclear fractions to observe translocation of Nrf2 protein from the cytoplasm to the nucleus qPCR of Nrf2 target genes (e.g., Nqo1, Hmox-1, Gcl, Gst, Prx, TrxR, Srxn), or by commercially available pathway-based qPCR array (e.g., oxidative stress array from SABiosciences) 

• Whole transcriptome profiling by microarray or RNA-seq followed by pathway analysis (in IPA, DAVID, metacore, etc.) for enrichment of the Nrf2 oxidative stress response pathway (e.g., Jackson et al. 2014) 

• OECD TG422D describes an ARE-Nrf2 Luciferase test method 

In general, there are a variety of commercially available colorimetric or fluorescent kits for detecting Nrf2 activation 

Assay Type & Measured Content	Description	Dose Range Studied	Assay Characteristics (Length/Ease of use/Accuracy)
ROS  Formation in the Mitochondria assay (Shaki et al., 2012)	“The mitochondrial ROS measurement was performed flow cytometry using DCFH-DA. Briefly, isolated kidney mitochondria were incubated with UA (0, 50, 100 and 200 µM) in respiration buffer containing (0.32 mM sucrose, 10mM Tris, 20 mM Mops, 50 µM EGTA, 0.5 mM MgCl2, 0.1 mM KH2PO4 and 5 mM sodium succinate) [32]. In the interval times of 5, 30 and 60 min following the UA addition, a sample was taken and DCFH-DA was added (final concentration, 10 µM) to mitochondria and was then incubated for 10 min.Uranyl acetate-induced ROS generation in isolated kidney mitochondria were determined through the flow cytometry (Partec, Deutschland) equipped with a 488-nm argon ion laser and supplied with the Flomax software and the signals were obtained using a 530-nm bandpass filter (FL-1 channel). Each determination is based on the mean fluorescence intensity of 15,000 counts.”	0, 50,100 and 200 µM of Uranyl Acetate	Long/ Easy High accuracy
Mitochondrial Antioxidant Content Assay Measuring GSH content (Shaki et al., 2012)	“GSH content was determined using DTNB as the indicator and spectrophotometer method for the isolated mitochondria. The mitochondrial fractions (0.5 mg protein/ml) were incubated with various concentrations of uranyl acetate for 1 h at 30 °C and then 0.1 ml of mitochondrial fractions was added into 0.1 mol/l of phosphate buffers and 0.04% DTNB in a total volume of 3.0 ml (pH 7.4). The developed yellow color was read at 412 nm on a spectrophotometer (UV-1601 PC, Shimadzu, Japan). GSH content was expressed as µg/mg protein.”	0, 50,  100, or  200 µM  Uranyl Acetate
H2O2 Production Assay Measuring H2O2 Production in isolated mitochondria (Heyno et al., 2008)	“Effect of CdCl2 and antimycin A (AA) on H2O2 production in isolated mitochondria from potato. H2O2 production was measured as scopoletin oxidation. Mitochondria were incubated for 30 min in the measuring buffer  (see the Materials and Methods) containing 0.5 mM succinate as an electron donor and 0.2 µM mesoxalonitrile 3‐chlorophenylhydrazone (CCCP) as an uncoupler, 10 U horseradish peroxidase and 5 µM scopoletin.”	0, 10, 30  µM Cd2+     2 µM antimycin A
Flow Cytometry ROS & Cell Viability (Kruiderig et al., 1997)	“For determination of ROS, samples taken at the indicated time points were directly transferred to FACScan tubes. Dih123 (10 mM, final concentration) was added and cells were incubated at 37°C in a humidified atmosphere (95% air/5% CO2) for 10 min. At t 5 9, propidium iodide (10 mM, final concentration) was added, and cells were analyzed by flow cytometry at 60 ml/min. Nonfluorescent Dih123 is cleaved by ROS to fluorescent R123 and detected by the FL1 detector as described above for Dc (Van de Water 1995)”“For determination of ROS, samples taken at the indicated time points were directly transferred to FACScan tubes. Dih123 (10 mM, final concentration) was added and cells were incubated at 37°C in a humidified atmosphere (95% air/5% CO2) for 10 min. At t 5 9, propidium iodide (10 mM, final concentration) was added, and cells were analyzed by flow cytometry at 60 ml/min. Nonfluorescent Dih123 is cleaved by ROS to fluorescent R123 and detected by the FL1 detector as described above for Dc (Van de Water 1995)”		Strong/easy medium
DCFH-DA  Assay Detection of hydrogen peroxide production (Yuan et al.,  2016)	Intracellular ROS production was measured using DCFH-DA as a probe. Hydrogen peroxide oxidizes DCFH to DCF. The probe is hydrolyzed intracellularly to DCFH carboxylate anion. No direct reaction with H2O2 to form fluorescent production.	0-400  µM	Long/ Easy High accuracy
H2-DCF-DAAssay Detection of superoxide production (Thiebault etal., 2007)	This dye is a stable nonpolar compound which diffuses readily into the cells and yields H2-DCF. Intracellular OH or ONOO- react with H2-DCF when cells contain peroxides, to form the highly fluorescent compound DCF, which effluxes the cell. Fluorescence intensity of DCF is measured using a fluorescence spectrophotometer.	0–600  µM	Long/ Easy High accuracy
CM-H2DCFDA  Assay (Eruslanov  & Kusmartsev, 2009)	The dye (CM-H2DCFDA) diffuses into the cell and is cleaved by esterases, the thiol reactive chlormethyl group reacts with intracellular glutathione which can be detected using flow cytometry.		Long/Easy/ High Accuracy

 

Method of Measurement	References	Description	OECD-Approved Assay
Chemiluminescence	(Lu, C. et al., 2006;   Griendling, K. K., et al., 2016)	ROS can induce electron transitions in molecules, leading to electronically excited products. When the electrons transition back to ground state, chemiluminescence is emitted and can be measured. Reagents such as luminol and lucigenin are commonly used to amplify the signal.	No
Spectrophotometry	(Griendling, K. K., et al., 2016)	NO has a short half-life. However, if it has been reduced to nitrite (NO2-), stable azocompounds can be formed via the Griess Reaction, and further measured by spectrophotometry.	No
Direct or Spin Trapping-Based electron paramagnetic resonance (EPR) Spectroscopy	(Griendling, K. K., et al., 2016)	The unpaired electrons (free radicals) found in ROS can be detected with EPR and is known as electron paramagnetic resonance. A variety of spin traps can be used.	No
Nitroblue Tetrazolium Assay	(Griendling, K. K., et al., 2016)	The Nitroblue Tetrazolium assay is used to measure O2.− levels. O2.− reduces nitroblue tetrazolium (a yellow dye) to formazan (a blue dye), and can be measured at 620 nm.	No
Fluorescence analysis of dihydroethidium (DHE) or Hydrocyans	(Griendling, K. K., et al., 2016)	Fluorescence analysis of DHE is used to measure O2.− levels.  O2.− is reduced to O2 as DHE is oxidized to 2-hydroxyethidium, and this reaction can be measured by fluorescence. Similarly, hydrocyans can be oxidized by any ROS, and measured via fluorescence.	No
Amplex Red Assay	(Griendling, K. K., et al., 2016)	Fluorescence analysis to measure extramitochondrial or extracellular H2O2 levels. In the presence of horseradish peroxidase and H2O2, Amplex Red is oxidized to resorufin, a fluorescent molecule measurable by plate reader.	No
Dichlorodihydrofluorescein Diacetate (DCFH-DA)	(Griendling, K. K., et al., 2016)	An indirect fluorescence analysis to measure intracellular H2O2 levels.  H2O2 interacts with peroxidase or heme proteins, which further react with DCFH, oxidizing it to dichlorofluorescein (DCF), a fluorescent product.	No
HyPer Probe	(Griendling, K. K., et al., 2016)	Fluorescent measurement of intracellular H2O2 levels. HyPer is a genetically encoded fluorescent sensor that can be used for in vivo and in situ imaging.	No
Cytochrome c Reduction Assay	(Griendling, K. K., et al., 2016)	The cytochrome c reduction assay is used to measure O2.− levels. O O2.− is reduced to O2 as ferricytochrome c is oxidized to ferrocytochrome c, and this reaction can be measured by an absorbance increase at 550 nm.	No
Proton-electron double-resonance imaging (PEDRI)	(Griendling, K. K., et al., 2016)	The redox state of tissue is detected through nuclear magnetic resonance/magnetic resonance imaging, with the use of a nitroxide spin probe or biradical molecule.	No
Glutathione (GSH) depletion	(Biesemann, N. et al., 2018)	A downstream target of the Nrf2 pathway is involved in GSH synthesis. As an indication of oxidation status, GSH can be measured by assaying the ratio of reduced to oxidized glutathione (GSH:GSSG) using a commercially available kit (e.g., http://www.abcam.com/gshgssg-ratio-detection-assay-kit-fluorometric-green-ab138881.html).	No
Thiobarbituric acid reactive substances (TBARS)	(Griendling, K. K., et al., 2016)	Oxidative damage to lipids can be measured by assaying for lipid peroxidation with TBARS using a commercially available kit.	No
Protein oxidation (carbonylation)	(Azimzadeh et al., 2017; Azimzadeh et al., 2015; Ping et al., 2020)	Can be determined with ELISA or a commercial assay kit. Protein oxidation can indicate the level of oxidative stress.	No
Seahorse XFp Analyzer	Leung et al. 2018	The Seahorse XFp Analyzer provides information on mitochondrial function, oxidative stress, and metabolic dysfunction of viable cells by measuring respiration (oxygen consumption rate; OCR) and extracellular pH (extracellular acidification rate; ECAR).	No

 

Molecular Biology: Nrf2. Nrf2’s transcriptional activity is controlled post-translationally by oxidation of Keap1. Assays for Nrf2 activity include:  

Method of Measurement	References	Description	OECD-Approved Assay
Immunohistochemistry	(Amsen, D., de Visser, K. E., and Town, T., 2009)	Immunohistochemistry for increases in Nrf2 protein levels and translocation into the nucleus	No
qPCR	(Forlenza et al., 2012)	qPCR of Nrf2 target genes (e.g., Nqo1, Hmox-1, Gcl, Gst, Prx, TrxR, Srxn), or by commercially available pathway-based qPCR array (e.g., oxidative stress array from SABiosciences)	No
Whole transcriptome profiling via microarray or via RNA-seq followed by a pathway analysis	(Jackson, A. F. et al., 2014)	Whole transcriptome profiling by microarray or RNA-seq followed by pathway analysis (in IPA, DAVID, metacore, etc.) for enrichment of the Nrf2 oxidative stress response pathway	No

 

References

Ahmad, S. et al. (2021), “60Co-γ Radiation Alters Developmental Stages of Zeugodacus cucurbitae (Diptera: Tephritidae) Through Apoptosis Pathways Gene Expression”, Journal Insect Science, Vol. 21/5, Oxford University Press, Oxford, https://doi.org/10.1093/jisesa/ieab080 

Antelmann, H. and J. D. Helmann (2011), “Thiol-based redox switches and gene regulation.”, Antioxidants & Redox Signaling, Vol. 14/6, Mary Ann Leibert Inc., Larchmont, https://doi.org/10.1089/ars.2010.3400 

Amsen, D., de Visser, K. E., and Town, T. (2009), “Approaches to determine expression of inflammatory cytokines”, in Inflammation and Cancer, Humana Press, Totowa, https://doi.org/10.1007/978-1-59745-447-6_5  

Azimzadeh, O. et al. (2015), “Integrative Proteomics and Targeted Transcriptomics Analyses in Cardiac Endothelial Cells Unravel Mechanisms of Long-Term Radiation-Induced Vascular Dysfunction”, Journal of Proteome Research, Vol. 14/2, American Chemical Society, Washington, https://doi.org/10.1021/pr501141b 

Azimzadeh, O. et al. (2017), “Proteome analysis of irradiated endothelial cells reveals persistent alteration in protein degradation and the RhoGDI and NO signalling pathways”, International Journal of Radiation Biology, Vol. 93/9, Informa, London, https://doi.org/10.1080/09553002.2017.1339332 

Azzam, E. I. et al. (2012), “Ionizing radiation-induced metabolic oxidative stress and prolonged cell injury”, Cancer Letters, Vol. 327/1-2, Elsevier, Ireland, https://doi.org/10.1016/j.canlet.2011.12.012 

Bai, J. et al. (2020), “Irradiation-induced senescence of bone marrow mesenchymal stem cells aggravates osteogenic differentiation dysfunction via paracrine signaling”, American Journal of Physiology - Cell Physiology, Vol. 318/5, American Physiological Society, Rockville, https://doi.org/10.1152/ajpcell.00520.2019. 

Balasubramanian, D (2000), “Ultraviolet radiation and cataract”, Journal of ocular pharmacology and therapeutics, Vol. 16/3, Mary Ann Liebert Inc., Larchmont, https://doi.org/10.1089/jop.2000.16.285.   

Biesemann, N. et al., (2018), “High Throughput Screening of Mitochondrial Bioenergetics in Human Differentiated Myotubes Identifies Novel Enhancers of Muscle Performance in Aged Mice”, Scientific Reports, Vol. 8/1, Nature Portfolio, London, https://doi.org/10.1038/s41598-018-27614-8.  

Elgazzar, A. and N. Kazem. (2015), “Chapter 23: Biological effects of ionizing radiation” in The Pathophysiologic Basis of Nuclear Medicine, Springer, New York, pp. 540-548 

Eruslanov, E., & Kusmartsev, S. (2010). Identification of ROS using oxidized DCFDA and flow-cytometry. Methods in molecular biology ,N.J.,  Vol. 594,  https://doi.org/10.1007/978-1-60761-411-1_4 

Fletcher, A. E (2010), “Free radicals, antioxidants and eye diseases: evidence from epidemiological studies on cataract and age-related macular degeneration”, Ophthalmic Research, Vol. 44, Karger International, Basel, https://doi.org/10.1159/000316476.  

Forlenza, M. et al. (2012), “The use of real-time quantitative PCR for the analysis of cytokine mRNA levels” in Cytokine Protocols, Springer, New York, https://doi.org/10.1007/978-1-61779-439-1_2  

Forrester, S.J. et al. (2018), “Angiotensin II Signal Transduction: An Update on Mechanisms of Physiology and Pathophysiology”, Physiological Reviews, Vol. 98/3, American Physiological Society, Rockville, https://doi.org/10.1152/physrev.00038.201 

Foyer, C. H., A. V. Ruban, and G. Noctor (2017), “Viewing oxidative stress through the lens of oxidative signalling rather than damage”, Biochemical Journal, Vol. 474/6, Portland Press, England, https://doi.org/10.1042/BCJ20160814 

Ganea, E. and J. J. Harding (2006), “Glutathione-related enzymes and the eye”, Current eye research, Vol. 31/1, Informa, London, https://doi.org/10.1080/02713680500477347.  

Griendling, K. K. et al. (2016), “Measurement of reactive oxygen species, reactive nitrogen species, and redox-dependent signaling in the cardiovascular system: a scientific statement from the American Heart Association”, Circulation research, Vol. 119/5, Lippincott Williams & Wilkins, Philadelphia, https://doi.org/10.1161/RES.0000000000000110  

Guo, C. et al. (2013), “Oxidative stress, mitochondrial damage and neurodegenerative diseases”, Neural regeneration research, Vol. 8/21, Publishing House of Neural Regeneration Research, China, https://doi.org/10.3969/j.issn.1673-5374.2013.21.009 

Hargreaves, M., and L. L. Spriet (2020), “Skeletal muscle energy metabolism during exercise.”, Nature Metabolism, Vol. 2, Nature Portfolio, London, https://doi.org/10.1038/s42255-020-0251-4 

Hladik, D. and S. Tapio (2016), “Effects of ionizing radiation on the mammalian brain”, Mutation Research/Reviews in Mutation Research, Vol. 770, Elsevier, Amsterdam, https://doi.org/10.1016/j.mrrev.2016.08.003 

Itoh, K., J. Mimura and M. Yamamoto (2010), “Discovery of the negative regulator of Nrf2, Keap1: a historical overview”, Antioxidants & Redox Signaling, Vol. 13/11, Mary Ann Leibert Inc., Larchmont, https://doi.org/10.1089/ars.2010.3222  

Jackson, A.F. et al. (2014), “Case study on the utility of hepatic global gene expression profiling in the risk assessment of the carcinogen furan.”, Toxicology and Applied Pharmacology, Vol. 274/11, Elsevier, Amsterdam, https://doi.org/10.1016/j.taap.2013.10.019 

Jacobsen, N.R. et al. (2008), “Genotoxicity, cytotoxicity, and reactive oxygen species induced by single-walled carbon nanotubes and C60 fullerenes in the FE1-MutaTM Mouse lung epithelial cells”, Environmental and Molecular Mutagenesis, Vol. 49/6, John Wiley & Sons, Inc., Hoboken, https://doi.org/10.1002/em.20406 

Karimi, N. et al. (2017), “Radioprotective effect of hesperidin on reducing oxidative stress in the lens tissue of rats”, International Journal of Pharmaceutical Investigation, Vol. 7/3, Phcog Net, Bengaluru, https://doi.org/10.4103/jphi.JPHI_60_17.  

Leung, D.T.H., and Chu, S. (2018), “Measurement of Oxidative Stress: Mitochondrial Function Using the Seahorse System” In: Murthi, P., Vaillancourt, C. (eds) Preeclampsia. Methods in Molecular Biology, vol 1710. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7498-6_22 

Lu, C., G. Song, and J. Lin (2006), “Reactive oxygen species and their chemiluminescence-detection methods”, TrAC Trends in Analytical Chemistry, Vol. 25/10, Elsevier, Amsterdam, https://doi.org/10.1016/j.trac.2006.07.007 

Nguyen Dinh Cat, A. et al. (2013), “Angiotensin II, NADPH oxidase, and redox signaling in the vasculature”, Antioxidants & redox signaling, Vol. 19/10, Mary Ann Liebert, Larchmont, https://doi.org/10.1089/ars.2012.4641 

Ping, Z. et al. (2020), “Oxidative Stress in Radiation-Induced Cardiotoxicity”, Oxidative Medicine and Cellular Longevity, Vol. 2020, Hindawi, https://doi.org/10.1155/2020/3579143 

Powers, S.K. and M.J. Jackson. (2008), “Exercise-Induced Oxidative Stress: Cellular Mechanisms and Impact on Muscle Force Production”, Physiological Reviews, Vol. 88/4, American Physiological Society, Rockville, https://doi.org/10.1152/physrev.00031.2007 

Raimondi, V., F. Ciccarese and V. Ciminale. (2020), “Oncogenic pathways and the electron transport chain: a dangeROS liason”, British Journal of Cancer, Vol. 122/2, Nature Portfolio, London, https://doi.org/10.1038/s41416-019-0651-y 

Seen, S. and L. Tong. (2018), “Dry eye disease and oxidative stress”, Acta Ophthalmologica, Vol. 96/4, John Wiley & Sons, Inc., Hoboken, https://doi.org/10.1111/aos.13526 

Ungvari, Z. et al. (2013), “Ionizing Radiation Promotes the Acquisition of a Senescence-Associated Secretory Phenotype and Impairs Angiogenic Capacity in Cerebromicrovascular Endothelial Cells: Role of Increased DNA Damage and Decreased DNA Repair Capacity in Microvascular Radiosensitivity”, The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, Vol. 68/12, Oxford University Press, Oxford, https://doi.org/10.1093/gerona/glt057.  

 

Vargas-Mendoza, N. et al. (2021), “Oxidative Stress, Mitochondrial Function and Adaptation to Exercise: New Perspectives in Nutrition”, Life, Vol. 11/11, Multidisciplinary Digital Publishing Institute, Basel, https://doi.org/10.3390/life11111269 

Wang, H. et al. (2019), “Radiation-induced heart disease: a review of classification, mechanism and prevention”, International Journal of Biological Sciences, Vol. 15/10, Ivyspring International Publisher, Sydney, https://doi.org/10.7150/ijbs.35460  

Zhang, R. et al. (2009), “Blockade of AT1 receptor partially restores vasoreactivity, NOS expression, and superoxide levels in cerebral and carotid arteries of hindlimb unweighting rats”, Journal of applied physiology, Vol. 106/1, American Physiological Society, Rockville, https://doi.org/10.1152/japplphysiol.01278.2007. 

Zhao, R. Z. et al. (2019), “Mitochondrial electron transport chain, ROS generation and uncoupling”, International journal of molecular medicine, Vol. 44/1, Spandidos Publishing Ltd., Athens, https://doi.org/10.3892/ijmm.2019.4188 

List of Adverse Outcomes in this AOP

Event: 2083: Occurrence of Cataracts

Short Name: Cataracts

Key Event Component

AOPs Including This Key Event

Biological Context

Domain of Applicability

Taxonomic Applicability Life Stage Applicability Sex Applicability

Taxonomic applicability: This KE is relevant to any species requiring a clear lens for vision. 

Life stage applicability: This key event can occur at any life stage; however, it is most common in older adults. Among humans, cataract changes usually begin after the age of 50 and become increasingly prevalent with age.  

Sex applicability: The adverse outcome can develop in both sexes and is not sex-specific. Females, however, have a small increased background risk of cataracts (Ainsbury et al., 2016). They also have a higher risk for radiation-induced cataracts including PSC, cortical and nuclear cataracts (Choshi et al., 1983, Nakashima et al., 2006; Henderson et al., 2010; Dynlacht et al., 2011; Azizova et al. 2018; Little et al., 2018; Garrett et al., 2020).  

Evidence for perturbation by prototypic stressors: A large body of evidence supports cataract induction via both ionizing and non-ionizing radiation. This includes X-rays, γ-rays, UV, neutrons, protons, β particles, and various heavy ions (⁵⁶Fe, ⁴⁰Ar, ¹²C, ²⁰Ne, ²²⁴Ra, and He). Of these, X-rays and γ-rays are the best supported (Yang & Ainsworth, 1987; Chmelevsky, 1988l; Brenner et al., 1991; Fedorenko, 1995; Char et al., 1998; Nakashima et al., 2006; Worgul et al., 2007; Davis et al., 2010; Karatasakis et al., 2018; Garrett et al., 2020; Kang et al., 2020; McCarron et al., 2021).  

Key Event Description

Cataracts are a progressive condition in which the lens of the eye develops opacities and becomes cloudy, resulting in blurred vision as well as glare and haloes around lights (National Eye Institute, 2022). For this AOP, a cataract is defined when over 5% of the lens is opacified. It is one of the leading causes of blindness around the world (Raj et al., 2009; Liu et al., 2017), and surgery is currently the only cure.  

The lens is a transparent, biconvex tissue located at the front of the eye. It is responsible for focusing light onto the retina, producing a clear image. However, under certain conditions, sections of the lens may develop small opacities, losing their transparency and resulting in blurred vision (Hildreth et al., 2009). As the lens has low metabolic and mitotic activity, there is very little tissue turnover. Therefore, damaged proteins that are not removed can acucmulate over time contributing to opacities and formation of cataracts (Hamada, 2017).  

A variety of factors are essential for maintaining the transparency of the lens, and therefore preventing cataracts. These include proper organization, development and balance of proteins such as crystallins (Hildreth et al., 2009; Ainsbury et al., 2016; Hamada, 2017; Wu et al., 2018), no organelles within the mature lens fiber cells (Pendergrass, 2010; Fujimichi et al., 2014; Hamada, 2017; Heitmancik & Shiels, 2015), and a low water content in the lens (Ainsbury et al., 2016). Genetic factors can also play a role, such as mutations in genes coding for molecular chaperones, growth factors, gap-junction proteins, intermediated filament proteins, membrane proteins, and RNA binding proteins (Hamada & Fujimichi, 2015; Lachke, 2022). When any of these factors are affected, it causes light scattering, which increases lens opacity, contributing to cataract formation and density.  

In general, there are three main categories of cataract: pediatric, age-related and those secondary to other causes. Age-related cataracts are the most common and can be subdivided into nuclear, cortical, or posterior subcapsular cataracts (PSC) based on which portion of the lens becomes opaque. In nuclear cataracts the opacities are in the nucleus of the lens, in cortical cataracts they are in the cortex, and in posterior subcapsular cataracts they are located beneath the posterior capsule (Van Kuijk, 1991).  Research has shown that posterior subcapsular (PSC) cataracts are a subtype of cataract that are most often found with ionizing radiation exposure. This may be due to radiation exposure causing the improperly differentiated lens epithelial cells (LECs) to leave the germinative zone (GZ) and migrate along the posterior capsule towards the center of the lens. As atypical lens fiber cells (LFCs), and atypical LECs accumulate in this area, they may cause the development of a PSC cataract (Loganovsky et al., 2020).

Cataracts can be diagnosed through several different methods and there is no universally accepted grading system. The most common grading systems are the Lens Opacities Classification System I, II, or III (LOC I, II, or III), the Modified Merriam-Focht Cataract Scoring System, and the slit lamp grading system. They classify cataracts on a scale of severity, which is often subjective, relying upon the examiner’s judgement. However, there are some methods such as Scheimpflug imaging which are less subjective as they measure lens density (Barraquer et al., 2017; Singh Grewal & Singh Grewal, 2012). 

How it is Measured or Detected

Listed below are common methods for detecting the KE, however there may be other comparable methods that are not listed. 

Assay	Reference	Description	OECD Approved Assay
Lens opacification grading systems	Barraquer et al., 2017	Systems used to classify the severity of cataracts. There are multiple types including: the Modified Merriam-Focht Cataract Scoring System, Lens Opacities Classification System III (LOC III), Word Health Organization Cataract Grading System, Lens Opacities Classification System I (LOCI), Lens Opacities Classification System II (LOC II), Wisconsin Clinical and Photographic Cataract Grading System, Wilmer Clinical and Photographic Grading System, Oxford Clinical Cataract Grading System, Age-Related Eye Disease Study, National Eye Institute Clinical Cataract Grading System, Japanese Cooperative Cataract Research Group Cataract Grading System	No
Slit Lamp Grading System	Barraquer et al., 2017; Robert & Alastair, 2017	Measures the light intensity reflected from opacities in nuclear cataracts. This also includes various techniques such as retroillumination.	No
Microscopy Examination	Stirling and Griffiths, 1991	Tests can help to examine interlocking processes and membrane architecture of lens.	No
Histological staining	Singh et al., 2003	Uses dyes such as trypan blue to differentiate different parts of the lens.	No
Optical coherence tomography (OCT)	Sharma, 2016	Optical signals are sent towards a tissue, where they either pass through or are reflected. These signals are then interpreted to build a spatial image of the tissue.	No
Scheimpflug imaging	Singh Grewal & Singh Grewal, 2012	This technique allows for the photography of obliquely tilted specimens without losing focus. Cataract grading systems that utilize this principle include the Oxford Scheimpflug System, the Nidek EAS-1000, and the Zeiss Schfeimpflug video camera.	No

References

Ainsbury, E. A. et al. (2016), “Ionizing radiation induced cataracts: recent biological and mechanistic developments and perspectives for future research”, Mutation research. Reviews in mutation research, Vol. 770, Elsevier B.V., https://doi.org/10.1016/j.mrrev.2016.07.010  

Barraquer, R. I. et al. (2017), “Validation of the nuclear cataract grading system BCN 10”, Ophthalmic Research, Vol. 57/4, Karger, https://doi.org/10.1159/000456720  

Brenner, D. J. et al. (1991), “Accelerated heavy particles and the lens: VI. RBE studies at low doses”, Radiation Research, Vol. 128/1, Academic Press, Inc, United States, https://doi.org/10.2307/3578069  

Char, D. H., S. M. Kroll, and J. Castro (1998), “Ten-year follow-up of helium ion therapy for uveal melanoma”, American Journal of Ophthalmology, Vol. 125/1, Elsevier Inc, New York, https://doi.org/10.1016/S0002-9394(99)80238-4  

Chmelevsky, D et al. (1988), “An epidemiological assessment of lens opacifications that impaired vision in patients injected with radium-224”, Radiation Research, Vol. 115/2, Academic Press, Oak Brook, https://doi.org/10.2307/3577161  

Choshi, K et al. (1983), “Ophthalmologic changes related to radiation exposure and age in adult health study sample, Hiroshima and Nagasaki”, Radiation Research, Vol. 96/3, Academic Press, Oak Brook, https://doi.org/10.2307/3576122  

Davis, J. G et al. (2010), “Dietary supplements reduce the cataractogenic potential of proton and HZE-particle radiation in mice”, Radiation Research, Vol. 173/3, The Radiation Research Society, United States, https://doi.org/10.1667/RR1398.1  

Dynlacht, J. R et al. (2011), “Age and hormonal status as determinants of cataractogenesis induced by ionizing radiation. I. Densely ionizing (high-LET) radiation”, Radiation Research, Vol. 175/1, The Radiation Research Society, United States, https://doi.org/10.1667/RR2319.1  

Fujimichi, Y., N. Hamada and M. Duncan (2014), “Ionizing irradiation not only inactivates clonogenic potential in primary normal human diploid lens epithelial cells but also stimulates cell proliferation in a subset of this population”, PloS one, Vol. 9/5, Public Library of Science, United States, https://doi.org/10.1371/journal.pone.0098154  

Garrett, J et al. (2020), “The protective effect of estrogen against radiation cataractogenesis is dependent upon the type of radiation”, Radiation Research, Vol. 194/5, Radiation Research Society, United States, https://doi.org/10.1667/RADE-20-00015.1  

Hamada, N. (2015), “Role of carcinogenesis related mechanisms in cataractogenesis and its implications for ionizing radiation cataractogenesis.” Cancer letters, Vol. 368,2 . https://doi.org/10.1016/j.canlet.2015.02.017  

Hamada, N. (2017), “Ionizing radiation sensitivity of the ocular lens and its dose rate dependence”, International journal of radiation biology, Vol. 93/10, Taylor & Francis, England, https://doi.org/10.1080/09553002.2016.1266407  

Hausmann, J. C. et al. (2020), “Ophthalmic examination findings and intraocular pressure measurements in six species of Anura”, Journal of Zoo and Wildlife Medicine, Vol. 50/4, American Association of Zoo Veterinarians, United States, https://doi.org/10.1638/2019-0115  

Henderson, M. A. et al. (2010), “Effects of estrogen and gender on cataractogenesis induced by high-let radiation” Radiation Research, Vol. 173/2, The Radiation Research Society, United States, https://doi.org/10.1667/RR1917.1  

Hildreth, C. J., A. E. Burke, and R. M. Glass (2009), “Cataracts”, JAMA: the journal of the American Medical Association, Vol. 301/19, https://doi.org/10.1001/jama.301.19.2060  

Kang, L. H. et al. (2020), “Ganoderic acid A protects lens epithelial cells from UVB irradiation and delays lens opacity”, Chinese Journal of Natural Medicines, Vol. 18/12, Elsevier B. V., China, https://doi.org/10.1016/S1875-5364(20)60037-1  

Karatasakis, A. et al. (2018), “Radiation-associated lens changes in the cardiac catheterization laboratory: Results from the IC-CATARACT (CATaracts Attributed to Radiation in the CaTh lab) study”, Catheterization and Cardiovascular Interventions, Vol. 91/4, Wiley Subscription Services, United States, https://doi.org/10.1002/ccd.27173  

Lachke, S. A. (2022), “RNA-binding proteins and post-transcriptional regulation in lens biology and cataract: mediating spatiotemporal expression of key factors that control the cell cycle, transcription, cytoskeleton and transparency”, Experimental Eye Research, Vol. 214, Elsevier Ltd, England, https://doi.org/10.1016/j.exer.2021.108889  

Little, M. P. et al. (2018), “Occupational radiation exposure and risk of cataract incidence in a cohort of US radiologic technologists”, European Journal of Epidemiology, Vol. 33/12, Springer, https://doi.org/10.1007/s10654-018-0435-3.  

Liu, Y. et al. (2017), “Cataracts”, The Lancet (British edition), Vol. 390/10094, Elsevier Ltd, England, https://doi.org/10.1016/S0140-6736(17)30544-5  

Loganovsky. et al (2020),. “Radiation-Induced Cerebro-Ophthalmic Effects in Humans”,. Life (Basel, Switzerland), Vol10(4). https://doi.org/10.3390/life10040041  

Loganovsky. eEt al (2021),. “Radiation-associated brain-ophthalmic effects in long-duration space missions”,. Revista Brasileira de Oftalmologia. Vol. 80. 10.37039/1982.8551.20210058. 

McCarron, R. A. et al. (2021), “Radiation-induced lens opacity and cataractogenesis: a lifetime study using mice of varying genetic backgrounds”, Radiation research, Vol. 197/1, Radiation Research Society, United States, https://doi.org/10.1667/RADE-20-00266.1  

Nakashima, E. et al. (2006), “A reanalysis of atomic-bomb cataract data, 2000-2002: A threshold analysis”, Health Physics, Vol. 90/2, Health Physics Society, Philadelphia, https://doi.org/10.1097/01.HP.0000175442.03596.63  

National Eye Institute (2022), Cataracts, https://www.nei.nih.gov/learn-about-eye-health/eye-conditions-and-diseases/cataractshttps://www.nei.nih.gov/learn-about-eye-health/eye-conditions-and-diseases/cataracts (accessed November 29, 2022) 

Pendergrass, W. et al. (2010), “X-ray induced cataract is preceded by LEC loss, and coincident with accumulation of cortical DNA, and ROS; similarities with age-related cataracts”, Molecular vision, Vol. 16, Molecular Vision, United States, pp. 1496-1513  

Raj et al. (2009), “Post-operative capsular opacification”, Nepalese journal of ophthalmology, Nepal, https://doi.org/10.3126/nepjoph.v1i1.3673  

Singh, A. J. et al. (2003), “A histological analysis of lens capsules stained with trypan blue doe capsulorrhexis in phacoemulsification cataract surgery”, Eye, Vol. 17/5, Springer Nature, London, https://doi.org/10.1038/sj.eye.6700440  

Sing Grewal, D. and S. P. Singh Grewal (2012), “Clinical applications of Scheimpflug imaging in cataract surgery”, Saudi Journal of Ophthalmology, Vol. 26, Elsevier, pp. 25-32  

Stirling, R.J. and P. G. Griffiths (1991), “Scanning EM studies of normal human lens fibres and fibres from nuclear cataracts”, Eye, Vol. 5/1, Springer Nature, London, https://doi.org/10.1038/eye.1991.17  

Worgul, B. V et al. (2007), “Cataracts among Chernobyl clean-up workers: Implications regarding permissible eye exposures”, Radiation Research, Vol. 167/2, Radiation Research Society, Lawrence, https://doi.org/10.1667/RR0298.1  

Wu, Shu-Yu et al. (2018), “Transgenic zebrafish models reveal distinct molecular mechanisms for cataract-linked αA-crystallin mutants”, PloS One, Vol. 13/11, Public Library of Science, United States, https://doi.org/10.1371/journal.pone.0207540  

Yang, V. C. and E. J. Ainsworth (1987), “A histological study on the cataractogenic effects of heavy charged particles”, Vol. 11/1, National Science Council of the Republic of China, pp. 18-28 

 

Appendix 2

List of Key Event Relationships in the AOP