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Relationship: 2812

Title

A descriptive phrase which clearly defines the two KEs being considered and the sequential relationship between them (i.e., which is upstream, and which is downstream). More help

Oxidative Stress leads to Modified Proteins

Upstream event
The causing Key Event (KE) in a Key Event Relationship (KER). More help
Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER). More help

Key Event Relationship Overview

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

AOPs Referencing Relationship

AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Deposition of energy leading to occurrence of cataracts adjacent Moderate Low Vinita Chauhan (send email) Open for citation & comment Under Review

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KER.In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER.  More help
Term Scientific Term Evidence Link
human Homo sapiens Low NCBI
guinea pig Cavia porcellus Moderate NCBI
rabbit Oryctolagus cuniculus Low NCBI

Sex Applicability

An indication of the the relevant sex for this KER. More help
Sex Evidence
Unspecific Moderate

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER.  More help
Term Evidence
All life stages Moderate

Key Event Relationship Description

Provides a concise overview of the information given below as well as addressing details that aren’t inherent in the description of the KEs themselves. More help

Oxidative stress refers to production of reactive oxygen species (ROS) and reactive nitrogen species (RNS), and a reduction/insufficiency in radical-clearing enzymes (Brennan et al., 2012; Engwa et al., 2022; Cabrera & Chihuailaf, 2011). Under normal conditions, radicals are kept at a sustainable level by the body’s antioxidant defense system but if the radicals exceed the defense threshold, it can lead to protein oxidation (Taylor & Davies, 1987; Cabrera & Chihuailaf, 2011; Engwa et al., 2022).ROS and RNS, collectively known was RONS, have subdivisions of radicals and non-radicals, with the former being the more reactive (Cabrera & Chihuailaf, 2011; Engwa et al., 2022). The superoxide ion radical works to oxidize biological structures such as proteins and DNA, as well as helping to generate other types of radicals. Superoxide ion can oxidize the amino acids arginine into glutamic semialdehyde and methionine into disulphides. Ozone, another ROS, specifically oxidizes proteins by reacting with their alcohol, amine, and sulfhydryl functional groups (Engwa et al., 2022). Furthermore, H2O2 is able to travel further than other ROS as it is more stable (Spector, 1990), it can also interact with transition metal ions (Cu+ or Fe2+) that are often bound to proteins such as ferritin and ceruloplasmin. This interaction oxidizes the protein, converting H2O2 into a hydroxyl radical. (Engwa et al., 2022). Another example of non-radical oxidation of proteins is peroxynitrite’s action on tryptophan and methionine. These amino acids are oxidized, tryptophan into nitrotryptophan and methionine into methionine sulfoxide or ethylene (Engwa et al., 2022; Perrin & Koppenol, 2000). There is also evidence to support H2O2 leading to protein modifications, however singlet oxygen or hydroxyl radicals seem to not be involved (Hightower, 1995). Targets of free radicals can include lipids, DNA, and proteins (Engwa et al., 2022). 

Antioxidants stabilize radicals by facilitating an electron donation (Cabrera & Chihuailaf, 2011). This reduces the number of radicals available to oxidize other macromolecules like proteins, thus reducing the number of molecules sustaining modifications (Engwa et al., 2022). Proteins are particularly good targets of free radicals because of their abundance of amino acids containing sulfur and aromatics, as well as the fact that following proline oxidation, peptide bonds are at risk of free radical attack (Cabrera & Chihuailaf, 2011). Free radicals have an affinity for sulfur-containing amino acids, such as cysteine and methionine, due to their ability to readily react with most ROS, making the proteins containing them the most susceptible to oxidative modifications. This quality of the amino acids makes them act in an antioxidant capacity for the other structures in the area (Bin et al., 2017). 

Proteins that interact with RONS will undergo bond alterations that can lead to aggregation. Free radicals can modify proteins in both reversible and irreversible ways. Redox-response proteins get oxidized as part of the protective mechanism against oxidizing radicals but will be repaired once the threat is over. In this instance, modifications are reversible, and homeostasis is maintained via antioxidative action. These proteins function as buffer, reducing free radicals before that can oxidize other proteins. Irreversible oxidation, on the other hand, occurs when there is oxidation on important functional or structural sites (Chen et al., 2013). These sites are important to a certain function of a protein or help maintain its specific structural configuration. This damage can result in loss of function and/or misfolding of proteins. The amino acids of proteins are very susceptible to ROS attacks, with methionine, tryptophan, histidine, and cysteine residues being the most at risk (Chen et al., 2013; Balasubramanian, 2000). Once the amino acids get oxidized by the ROS, they become oxidation products and are no longer useful for the originally intended function within the protein (Engwa et al., 2022).  

Protein carbonyl level is changed by ROS exposure through the post-translational modification called carbonylation, where carbonyl groups are added to the protein (Grimsrud et al., 2008). ROS accomplishes this by interacting with amino acids such as proline and lysine, on the protein side chains, which tend to create carbonyl derivatives (Engwa et al., 2022). In proteins attacked by radicals, there is also a tendency to form cross-links between the proteins. These connections affect water solubility of the proteins. Normal proteins have a balance of protein-protein and protein-water interactions that maintain structure and solubility, however following the oxidation of the amino side chains of the proteins, they become thermodynamically preferred to have more protein-protein interactions. This causes an increase in cross-linking and aggregation, which leads to decreased water solubility (Xiong, 2000). 

Evidence Collection Strategy

Include a description of the approach for identification and assembly of the evidence base for the KER. For evidence identification, include, for example, a description of the sources and dates of information consulted including expert knowledge, databases searched and associated search terms/strings.  Include also a description of study screening criteria and methodology, study quality assessment considerations, the data extraction strategy and links to any repositories/databases of relevant references.Tabular summaries and links to relevant supporting documentation are encouraged, wherever possible. More help

The strategy for collating the evidence to support the relationship is described in Kozbenko et al 2022. Briefly, a scoping review methodology was used to prioritize studies based on a population, exposure, outcome, endpoint statement.

Evidence Supporting this KER

Addresses the scientific evidence supporting KERs in an AOP setting the stage for overall assessment of the AOP. More help

Overall Weight of Evidence: Moderate 

Biological Plausibility
Addresses the biological rationale for a connection between KEupstream and KEdownstream.  This field can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured.   More help

The biological plausibility of the relationship between increased oxidative stress leading to modified proteins is strongly supported by the literature. Studies show that increase of oxidative stress, leads to protein modifications (Uwineza et al., 2019; Taylor & Davies, 1987; Truscott, 2005; Brennan et al., 2012; Davies & Truscott, 2001). This relationship has been observed in rabbit and guinea pig models (Shang et al., 2001; Giblin et al., 2002). Excessive ROS generation can lead to oxidization of amino acid side chains, cross-link formation, and conformational changes (Uwineza et al., 2019). Radical oxygen species can modify protein molecules chemically, and act to increase proteolytic activity of cellular enzymes by inactivating proteolytic enzyme inhibitors (Balasubramanian, 2000; Stohs, 1995). Oxidation via radical species-protein interactions can also lead to increased insolubility of the proteins due to their modified structure and inability to interact with unmodified proteins (Kim et al., 2015).  

Proteins aggregation can be exacerbated by protein oxidation. For example, in lens cells, the presence of free radicals can attack abundant proteins such as alpha crystalline. The thiol groups on the crystallin proteins then become oxidized and increase the number of disulfide adducts, increasing protein aggregates (Cabrera & Chihuailaf, 2011; Moreau et al., 2012). Amino acid side chains are particularly susceptible to damage from oxidative stress, resulting in cross-linking and conformational changes which can culminate in protein accumulation. The accumulation is a result of the cells being denucleated and therefore, unable to reverse the sustained damage via protein turnover (Uwineza et al., 2019). Oxidative conditions can contribute to the loss of protein function leading to the generation of high molecular weight aggregates. This change is hypothesised to be a result of methionine oxidation, which is more likely to happen when GSH levels are low resulting in an increase in hydroxyl radical formation (Brennan et al., 2012; Truscott, 2005). The hydroxyl radical also results in covalently bound protein aggregates, and alongside superoxide ion it leads to protein fragmentation (Stohs, 1995).  

Uncertainties and Inconsistencies
Addresses inconsistencies or uncertainties in the relationship including the identification of experimental details that may explain apparent deviations from the expected patterns of concordance. More help

N/A

Known modulating factors

This table captures specific information on the MF, its properties, how it affects the KER and respective references.1.) What is the modulating factor? Name the factor for which solid evidence exists that it influences this KER. Examples: age, sex, genotype, diet 2.) Details of this modulating factor. Specify which features of this MF are relevant for this KER. Examples: a specific age range or a specific biological age (defined by...); a specific gene mutation or variant, a specific nutrient (deficit or surplus); a sex-specific homone; a certain threshold value (e.g. serum levels of a chemical above...) 3.) Description of how this modulating factor affects this KER. Describe the provable modification of the KER (also quantitatively, if known). Examples: increase or decrease of the magnitude of effect (by a factor of...); change of the time-course of the effect (onset delay by...); alteration of the probability of the effect; increase or decrease of the sensitivity of the downstream effect (by a factor of...) 4.) Provision of supporting scientific evidence for an effect of this MF on this KER. Give a list of references.  More help
Modulating Factor (MF) MF Specification Effect(s) on the KER Reference(s)
Free Radical Scavengers  Antioxidant supplementation has been linked to reduced oxidative damage. The scavengers work to reduce the reactivity of ROS in the cell by donating one of their own electrons, resulting in a matching pair on the radical.  Lower levels of free radical scavengers would result in a limited ability to reduce RONS-mediated damage. Reduced GSH levels are associated with protein modifications, including changes to water-solubility (29% decrease GSH ≥ 20% decrease soluble proteins) and protein carbonyl concentration (84% decrease GSH ≥ 367% increase carbonyl concentration).  Taylor & Davies, 1987; Cabrera & Chihuailaf, 2011; Giblin et al., 2002; Shang et al., 2001 
Age  Older lenses have reduced antioxidant capacities (in humans >30 years old). This is due in part to the development of a chemical barrier between the cortex and the nucleus of the lens that prevents GSH from protecting the oldest lens cells from oxidative damage.  Antioxidants function to prevent RONS-mediated damage, so proteins in older lenses, with reduced antioxidant capacities, will be more likely to undergo oxidative modifications.  Taylor & Davies, 1987; Cabrera & Chihuailaf, 2011; Quinlan & Hogg, 2018; Sweeney & Truscott, 1998 
Response-response Relationship
Provides sources of data that define the response-response relationships between the KEs.  More help
Time-scale
Information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). More help
Known Feedforward/Feedback loops influencing this KER
Define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits. More help

N/A

Domain of Applicability

A free-text section of the KER description that the developers can use to explain their rationale for the taxonomic, life stage, or sex applicability structured terms. More help

This KER is plausible in all life stages, sexes, and organisms. The majority of the evidence is from in vivo male adult guinea pigs and rabbit in vitro models that do not specify sex. 

References

List of the literature that was cited for this KER description. More help

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. 

Bin, P., R. Huang and X. Zhou. (2017). “Oxidation Resistance of the Sulfur Amino Acids: Methionine and Cysteine”, BioMed Research International, Vol.2017, Hindawi Limited, London, https://doi.org/10.1155/2017/9584932. 

Brennan, L., R. McGreal and M. Kantorow. (2012), “Oxidative stress defense and repair systems of the ocular lens”, Frontiers in Bioscience – Elite, Vol.4/E(1), Frontiers in Bioscience, Singapore, https://doi.org/10.2741/365. 

Cabrera, M., & 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. 

Chen, Y. et al. (2013), “Ocular aldehyde dehydrogenases: Protection against ultraviolet damage and maintenance of transparency for vision”, Progress in Retinal and Eye Research, Vol.33/1, Elsevier Ltd, London, https://doi.org/10.1016/j.preteyeres.2012.10.001. 

Davies, M. and R. Truscott. (2001), “Photo-oxidation of proteins and its role in cataractogenesis”, Journal of Photochemistry and Photobiology B: Biology, Vol.63/1-3, Elsevier, Amsterdam, https://doi.org/10.1016/s1011-1344(01)00208-1. 

Engwa, G.A., F.N. Nweke and B.N. Nkeh-Chungag. (2022), “Free Radicals, Oxidative Stress-Related Diseases and Antioxidant Supplementation”, Alternative therapies in health and medicine, Vol.28/1, InnoVision Health Media, Eagan, pp.114-128. 

Giblin, F. et al. (2002), “UVA Light In vivo Reaches the Nucleus of the Guinea Pig Lens and Produces Deleterious, Oxidative Effects”, Experimental Eye Research, Vol.75/4, Academic Press Inc, Cambridge, https://doi.org/10.1006/exer.2002.2039. 

Grimsrud, P.A. et al. (2008), “Oxidative Stress and Covalent Modification of Protein with Bioactive Aldehydes”, Journal of Biological Chemistry, Vol.283/32, American Society for Biochemistry and Molecular Biology, Rockville, https://doi.org/10.1074/jbc.R700019200. 

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. 

Kim, I. et al. (2015), “Site specific oxidation of amino acid residues in rat lens γ-crystallin induced by low-dose γ-irradiation”, Biochemical and Biophysical Research Communications, Vol.466/4, Elsevier, Amsterdam, https://doi.org/10.1016/j.bbrc.2015.09.075. 

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, 1–12. https://doi.org/10.1080/09553002.2022.2110306 

Perrin, D. and W.H. Koppenol. (2000), “The Quantitative Oxidation of Methionine to Methionine Sulfoxide by Peroxynitrite”, Archives of Biochemistry and Biophysics, Vol.377/2, Elsevier, Amsterdam, https://doi.org/10.1006/abbi.2000.1787. 

Quinlan, R.A., and P.J. Hogg. (2018), “γ-Crystallin redox–detox in the lens”, Journal of Biological Chemistry, Vol.293/46, American Society for Biochemistry and Molecular Biology, Rockville, https://doi.org/10.1074/jbc.H118.006240. 

Shang, F., T. Nowell and A. Taylor. (2001), “Removal of oxidatively damaged proteins from lens cells by the ubiquitin-proteasome pathway”, Experimental Eye Research, Vol.73/2, Academic Press Inc, Cambridge, https://doi.org/10.1006/exer.2001.1029. 

Spector, A. (1990), “Oxidation and Aspects of Ocular Pathology”. CLAO Journal, Vol.16/1, Lippincott, Williams and Wilkins Ltd, Philadelphia, S8-S10. 

Stohs, S. (1995), “The role of free radicals in toxicity and disease”, Journal of Basic Clinical Physiology and Pharmacology, Vol.6/3-4, Walter de Gruyter GmbH, Berlin, https://doi.org/10.1515/jbcpp.1995.6.3-4.205. 

Sweeney, M.H.J. and R.J.W. Truscott. (1998), “An Impediment to Glutathione Diffusion in Older Normal Human Lenses: a Possible Precondition for Nuclear Cataract”, Experimental Eye Research, Vol.67, Academic Press Inc, Cambridge, https://doi.org/10.1006/exer.1998.0549. 

Taylor, A. and K. Davies. (1987), “Protein oxidation and loss of protease activity may lead to cataract formation in the aged lens”, Free Radical Biology and Medicine, Vol.3/6, Elsevier, Amsterdam, https://doi.org/10.1016/0891-5849(87)90015-3. 

Truscott, R. (2005), “Age-related nuclear cataract - Oxidation is the key”, Experimental Eye Research, Vol.80/5, Academic Press Inc, Cambridge, https://doi.org/10.1016/j.exer.2004.12.007. 

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. 

Xiong, Y.L. (2000), “Chapter 4: Protein Oxidation and Implications for Muscle Food Quality”, in Antioxidants in Muscle Foods: Nutritional Strategies to Improve Quality, Wiley, Hoboken, pp.85-111.