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Relationship: 3116

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

Increase, Oxidative Stress leads to Increase, LPO

Upstream event

The causing Key Event (KE) in a Key Event Relationship (KER). More help

Increase, Oxidative Stress

Downstream event

The responding Key Event (KE) in a Key Event Relationship (KER). More help

Increase, LPO

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
Essential element imbalance leads to reproductive failure via oxidative stress	adjacent			Travis Karschnik (send email)	Under development: Not open for comment. Do not cite
Reactive oxygen species leading to growth inhibition via lipid peroxidation and cell death	adjacent	High	Moderate	You Song (send email)	Under development: Not open for comment. Do not cite
Reactive oxygen species leading to growth inhibition via lipid peroxidation and decreased cell proliferation	adjacent	High	Moderate	You Song (send email)	Under development: Not open for comment. Do not cite

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
humans	Homo sapiens	High	NCBI
mammals	mammals	High	NCBI
fish	fish	High	NCBI
crustaceans	Daphnia magna	High	NCBI
green algae	Ulva compressa	High	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

This KER describes the relationship by which an increase in oxidative stress leads to an increase in lipid peroxidation. Oxidative stress represents a shift toward a pro-oxidant state in which reactive oxygen species, reactive nitrogen species, redox-active intermediates, or weakened antioxidant defenses exceed the buffering capacity of the biological system. Lipid peroxidation is a chain reaction in which oxidants abstract hydrogen atoms from susceptible lipids, particularly polyunsaturated fatty acids, producing lipid radicals, lipid peroxyl radicals, lipid hydroperoxides and secondary reactive aldehydes such as malondialdehyde (MDA) and 4-hydroxy-2-nonenal (4-HNE) (Halliwell and Gutteridge, 2015; Ayala et al., 2014; Yin et al., 2011).

The relationship is biologically plausible because increased oxidative pressure raises the probability of radical initiation and propagation in lipid-rich compartments, especially biological membranes. Once initiated, lipid peroxidation can propagate through neighboring lipids and can be amplified by transition metals, oxygen availability, membrane composition and reduced antioxidant protection. The downstream KE therefore reflects a measurable chemical and biological consequence of upstream oxidative stress rather than a separate stressor-specific mechanism. The KER is modular and can be reused wherever oxidative stress is followed by measurable increases in lipid oxidation products.

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

Evidence for this KER was assembled from the ROS-growth AOP network literature review and data-mining workflow, targeted searches of primary literature, and mechanistic reviews of lipid peroxidation chemistry. The evidence-collection process followed the AOP-Wiki KER template structure, including taxonomic applicability, life stage and sex applicability, KER description, evidence collection strategy, evidence supporting the KER, modulating factors, quantitative understanding, domain of applicability and references.

The literature screening strategy focused on studies that measured oxidative stress and lipid peroxidation in the same biological system, or that provided strong mechanistic support for the transition from oxidative stress to lipid peroxidation. Search concepts included oxidative stress, lipid peroxidation, MDA, TBARS, 4-HNE, lipid hydroperoxides, antioxidant enzymes, glutathione, ROS, paraquat, copper, cadmium, thiram, hydrogen peroxide, hypoxia-reoxygenation, Daphnia, algae, fish, bivalves, and mammalian cells. Records were prioritized when they reported exposure concentration or dose, time of exposure, biological system, endpoints measured, and evidence relevant to dose-response or temporal concordance.

The final evidence set includes mechanistic reviews on lipid peroxidation chemistry and empirical studies from algae, Daphnia, fish, marine bivalves, mammalian cells and whole-organism models. Studies were extracted into the ROS-growth concordance table where they provided information on oxidative stress and lipid peroxidation endpoints. Greater weight was given to studies with paired measurement of upstream oxidative stress markers and downstream lipid peroxidation endpoints in the same exposure design.

Evidence Supporting this KER

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

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

Biological plausibility of this KER is high. The mechanistic basis is well established in chemistry and biology: oxidative stress increases reactive species capable of initiating lipid radical formation, and lipid radicals propagate chain reactions that generate lipid hydroperoxides and reactive aldehydes (Halliwell and Gutteridge, 2015; Ayala et al., 2014; Yin et al., 2011). Polyunsaturated fatty acids are particularly susceptible because bis-allylic hydrogens are readily abstracted, making membrane lipid composition a major determinant of sensitivity. Endogenous antioxidant systems, including glutathione peroxidases, peroxiredoxins, vitamin E, glutathione and other radical-scavenging systems, normally limit lipid peroxidation. When oxidative stress overwhelms these defenses, lipid peroxidation increases.

The structural and functional relationship between the two KEs is direct: the upstream KE increases the chemical conditions that initiate and propagate the downstream lipid oxidation process. This relationship is broadly accepted across toxicology, cell biology, physiology and environmental stress biology.

Empirical Evidence

Provides specific (citable) evidence that supports the idea of a change in the upstream KE (KEupstream) leading to, or being associated with, a subsequent change in the downstream KE (KEdownstream), assuming the perturbation of KEupstream is sufficient. More help

Biological system	Stressor / condition	Evidence supporting the KER	Concordance interpretation	Reference
Chlorella vulgaris	Paraquat, 24 h	Paraquat increased ROS and induced antioxidant enzymes; ROS and oxidative stress responses were observed at concentrations that support a pro-oxidant state leading to downstream oxidative damage.	Supports upstream oxidative-stress induction by a redox-cycling herbicide and provides context for lipid-damage progression in algae.	Qian et al. (2009).
Scenedesmus vacuolatus and Chlorella kessleri	Copper sulfate, 7 d	SOD/CAT induction occurred with increased MDA/TBARS, with MDA elevated at similar or higher concentrations than antioxidant-response markers.	Supports dose concordance between oxidative stress biomarkers and lipid peroxidation in freshwater green microalgae.	Knauert and Knauer (2008).
Chlamydomonas reinhardtii	Paraquat, 48 h	Significant TBARS/MDA increase occurred at >=0.5 uM paraquat, with associated mitochondrial depolarization at similar concentrations.	Supports oxidative-stress-driven lipid peroxidation following exposure to a superoxide-generating herbicide.	Esperanza et al. (2015).
Daphnia magna	Paraquat, 48 h	ROS induction was observed at lower concentrations, followed by antioxidant enzyme induction and TBARS responses at higher concentrations.	Supports expected dose sequence: ROS/oxidative stress precedes or coincides with lipid peroxidation.	Barata et al. (2005).
Daphnia magna	Thiram, 48 h	GSH depletion and increased MDA/TBARS were observed after thiram exposure.	Supports empirical linkage between redox imbalance and lipid peroxidation in a freshwater crustacean.	Belaid and Sbartai (2021).
Daphnia magna	High-PUFA diet, chronic	High-PUFA diet increased TBARS and reduced mitochondrial membrane potential.	Supports the role of lipid composition as a modulator and provides evidence that increased lipid susceptibility enhances peroxidation and downstream mitochondrial effects.	Moore et al. (2023).
Danio rerio	Dimethyl phthalate, 24-96 h	Antioxidant enzyme changes and MDA increases were observed after exposure.	Supports concordance between oxidative-stress biomarkers and lipid peroxidation in fish.	Cong et al. (2020).
Ruditapes philippinarum and Mytilus galloprovincialis	Hydrogen peroxide, 21 d or 48 h	Antioxidant enzyme activation was observed at lower concentrations than lipid peroxidation in digestive gland.	Supports dose concordance between direct oxidant exposure, oxidative-stress response and lipid peroxidation in bivalves.	Alam et al. (2022).
Marine bivalves	Chlorothalonil, 96 h	Antioxidant enzyme induction and MDA/TBARS increases occurred in bivalve tissues.	Supports oxidative stress and lipid peroxidation after antifoulant exposure.	Haque et al. (2019).
Human promyelocytic leukemia cells	Continuous H2O2 generation, 1 h	Sustained H2O2 production increased MDA at higher production rates.	Supports oxidant-driven lipid peroxidation in human cell systems.	Montserrat-Mesquida et al. (2024).

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

The overall evidence for this KER is strong, but several uncertainties influence interpretation. First, lipid peroxidation biomarkers can be nonspecific or method-dependent. TBARS is widely used but can overestimate MDA or respond to non-lipid-derived substances; more specific methods such as HPLC, LC-MS/MS or measurement of 4-HNE and lipid hydroperoxides provide stronger evidence (Ayala et al., 2014; Yin et al., 2011). Second, oxidative stress is often inferred from antioxidant enzyme induction or glutathione perturbation rather than directly measured ROS flux. Third, lipid peroxidation depends strongly on membrane lipid composition, antioxidant status, metal availability and exposure duration, so the same oxidative-stress magnitude may not produce the same lipid peroxidation response in all systems. Finally, adaptive antioxidant responses may delay or suppress lipid peroxidation after mild oxidative stress, creating apparent temporal or dose-response discordance in some studies.

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	Details	Effect on the KER	Supporting evidence
Membrane lipid composition / PUFA content	Higher abundance of polyunsaturated fatty acids increases susceptibility to radical chain peroxidation.	Increases the probability and magnitude of lipid peroxidation for a given oxidative-stress level.	Ayala et al. (2014); Yin et al. (2011); Moore et al. (2023).
Antioxidant capacity	Includes glutathione, glutathione peroxidases, catalase, peroxiredoxins, vitamin E and other lipid-soluble antioxidants.	Higher antioxidant capacity buffers oxidative stress and decreases lipid peroxidation; depletion or inhibition increases sensitivity.	Halliwell and Gutteridge (2015); Sies et al. (2017); Belaid and Sbartai (2021).
Transition metals	Iron, copper and other redox-active metals catalyze radical generation and lipid peroxide decomposition.	Enhances initiation and propagation of lipid peroxidation, often lowering the threshold for the downstream KE.	Halliwell and Gutteridge (2015); Knauert and Knauer (2008); Regoli and Giuliani (2014).
Oxygen availability and hypoxia/reoxygenation	Oxygen tension and reoxygenation influence radical formation and lipid peroxide propagation.	Can increase oxidative stress and lipid peroxidation during reoxygenation or variable oxygen regimes.	Ouillon et al. (2021); Sokolova et al. (2019).
Temperature and metabolic rate	Thermal stress changes metabolism, oxygen flux and membrane properties.	May increase ROS production and alter membrane susceptibility to lipid peroxidation.	Tseng et al. (2011); Almaida-Pagán et al. (2014).
Assay method and sampling time	TBARS, MDA, 4-HNE and lipid hydroperoxide methods differ in specificity and kinetics.	Influences apparent magnitude, timing and detectability of lipid peroxidation.	Ayala et al. (2014); Yin et al. (2011).

Quantitative Understanding of the Linkage

Captures information that helps to define how much change in the upstream KE, and/or for how long, is needed to elicit a detectable and defined change in the downstream KE. More help

Quantitative understanding of this KER is moderate. The qualitative and mechanistic relationship is well established, but a universal quantitative threshold for oxidative stress leading to lipid peroxidation cannot be defined because the response depends on lipid composition, antioxidant capacity, oxygen availability, transition metals, exposure duration, stressor chemistry and assay method (Ayala et al., 2014; Yin et al., 2011; Sies et al., 2017).

Response-response Relationship

Provides sources of data that define the response-response relationships between the KEs. More help

Response-response evidence exists in specific systems. In green microalgae exposed to copper, antioxidant enzyme induction and MDA/TBARS increases occurred over the same concentration range, supporting dose concordance (Knauert and Knauer, 2008). In Daphnia magna exposed to paraquat, ROS induction occurred at lower concentrations than antioxidant enzyme and TBARS responses, suggesting that increased ROS and oxidative stress precede lipid peroxidation (Barata et al., 2005). In bivalves exposed to hydrogen peroxide, antioxidant enzyme activation occurred at lower concentrations than lipid peroxidation in digestive gland, also supporting a staged relationship (Alam et al., 2022).

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

The time scale of the linkage can range from minutes to days. Chemical initiation of lipid radicals can occur rapidly when reactive species are present, but commonly measured endpoints such as MDA, TBARS, 4-HNE or lipid hydroperoxides often become detectable over hours to days depending on exposure intensity and tissue antioxidant capacity. Quantitative prediction of lipid peroxidation from oxidative-stress measurements therefore remains system-specific and is best supported when both KEs are measured in the same biological context and time course.

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

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 broadly applicable to aerobic biological systems containing oxidizable lipids. It is particularly relevant to membranes and lipid-rich tissues or compartments, including plasma membranes, mitochondrial membranes, chloroplast membranes, digestive gland, liver, nervous tissue and reproductive tissues. The relationship is expected to be conserved across taxa because it is based on fundamental redox chemistry and lipid radical chain reactions rather than on a taxon-specific receptor pathway.

The KER should be applied most confidently when both upstream oxidative stress and downstream lipid peroxidation are measured under the same exposure conditions. Applicability is strongest when oxidative stress is assessed by redox imbalance or antioxidant-response endpoints and lipid peroxidation is measured using specific markers such as MDA, 4-HNE or lipid hydroperoxides. Applicability is weaker when lipid peroxidation is inferred solely from nonspecific TBARS responses without supporting oxidative-stress biomarkers or when the exposure context is dominated by physical membrane disruption rather than redox-mediated chemistry.

References

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

Alam MR, Ehiguese FO, Vitale D, Martín-Díaz ML. 2022. Oxidative stress response to hydrogen peroxide exposure of Mytilus galloprovincialis and Ruditapes philippinarum: reduced embryogenesis success and altered biochemical response of sentinel marine bivalve species. Environmental Chemistry and Ecotoxicology 4:97-105. https://doi.org/10.1016/j.enceco.2022.01.002.

Almaida-Pagán PF, Lucas-Sánchez A, Tocher DR. 2014. Changes in mitochondrial membrane composition and oxidative status during rapid growth, maturation and aging in zebrafish, Danio rerio. Biochimica et Biophysica Acta - Molecular and Cell Biology of Lipids 1841(7):1003-1011. https://doi.org/10.1016/j.bbalip.2014.04.004.

Ayala A, Munoz MF, Arguelles S. 2014. Lipid peroxidation: production, metabolism, and signaling mechanisms of malondialdehyde and 4-hydroxy-2-nonenal. Oxidative Medicine and Cellular Longevity 2014:360438. https://doi.org/10.1155/2014/360438.

Barata C, Varo I, Navarro JC, Arun S, Porte C. 2005. Antioxidant enzyme activities and lipid peroxidation in the freshwater cladoceran Daphnia magna exposed to redox cycling compounds. Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology 140(2):175-186. https://doi.org/10.1016/j.cca.2005.01.013.

Belaid C, Sbartai I. 2021. Assessing the effects of thiram to oxidative stress responses in a freshwater bioindicator cladoceran (Daphnia magna). Chemosphere 268:128808. https://doi.org/10.1016/j.chemosphere.2020.128808.

Cong B, Liu C, Wang L, Chai Y. 2020. The impact on antioxidant enzyme activity and related gene expression following adult zebrafish (Danio rerio) exposure to dimethyl phthalate. Animals 10(4):717. https://doi.org/10.3390/ani10040717.

Esperanza M, Cid A, Herrero C, Rioboo C. 2015. Acute effects of a prooxidant herbicide on the microalga Chlamydomonas reinhardtii: screening cytotoxicity and genotoxicity endpoints. Aquatic Toxicology 165:210-221. https://doi.org/10.1016/j.aquatox.2015.06.004.

Halliwell B, Gutteridge JMC. 2015. Free Radicals in Biology and Medicine. 5th ed. Oxford: Oxford University Press.

Haque MN, Eom HJ, Nam SE, Shin YK, Rhee JS. 2019. Chlorothalonil induces oxidative stress and reduces enzymatic activities of Na+/K+-ATPase and acetylcholinesterase in gill tissues of marine bivalves. PLoS ONE 14(4):e0214236. https://doi.org/10.1371/journal.pone.0214236.

Knauert S, Knauer K. 2008. The role of reactive oxygen species in copper toxicity to two freshwater green algae. Journal of Phycology 44(2):311-321. https://doi.org/10.1111/j.1529-8817.2008.00471.x.

Montserrat-Mesquida M, Ferrer MD, Pons A, Sureda A, Capó X. 2024. Effects of chronic hydrogen peroxide exposure on mitochondrial oxidative stress genes, ROS production and lipid peroxidation in HL60 cells. Mitochondrion 76:101869. https://doi.org/10.1016/j.mito.2024.101869.

Moore TD, Martin-Creuzburg D, Yampolsky LY. 2023. Diet effects on longevity, heat tolerance, lipid peroxidation and mitochondrial membrane potential in Daphnia. Oecologia 202(1):151-163. https://doi.org/10.1007/s00442-023-05382-1.

Ouillon N, Sokolov EP, Otto S, Rehder G, Sokolova IM. 2021. Effects of variable oxygen regimes on mitochondrial bioenergetics and reactive oxygen species production in a marine bivalve, Mya arenaria. Journal of Experimental Biology 224(4):jeb237156. https://doi.org/10.1242/jeb.237156.

Pan YX, Luo Z, Zhuo MQ, Wei CC, Chen GH, Song YF. 2018. Oxidative stress and mitochondrial dysfunction mediated Cd-induced hepatic lipid accumulation in zebrafish Danio rerio. Aquatic Toxicology 199:12-20. https://doi.org/10.1016/j.aquatox.2018.03.017.

Qian H, Chen W, Sun L, Jin Y, Liu W, Fu Z. 2009. Inhibitory effects of paraquat on photosynthesis and the response to oxidative stress in Chlorella vulgaris. Ecotoxicology 18(5):537-543. https://doi.org/10.1007/s10646-009-0311-8.

Regoli F, Giuliani ME. 2014. Oxidative pathways of chemical toxicity and oxidative stress biomarkers in marine organisms. Marine Environmental Research 93:106-117. https://doi.org/10.1016/j.marenvres.2013.07.006.

Schieber M, Chandel NS. 2014. ROS function in redox signaling and oxidative stress. Current Biology 24(10):R453-R462. https://doi.org/10.1016/j.cub.2014.03.034.

Sies H, Berndt C, Jones DP. 2017. Oxidative stress. Annual Review of Biochemistry 86:715-748. https://doi.org/10.1146/annurev-biochem-061516-045037.

Sokolov EP, Markert S, Hinzke T, Hirschfeld C, Becher D, Ponsuksili S, Sokolova IM. 2019. Effects of hypoxia-reoxygenation stress on mitochondrial proteome and bioenergetics of the hypoxia-tolerant marine bivalve Crassostrea gigas. Journal of Proteomics 194:99-111. https://doi.org/10.1016/j.jprot.2018.12.009.

Tseng YC, Chen RD, Lucassen M, Schmidt MM, Dringen R, Abele D, Hwang PP. 2011. Exploring uncoupling proteins and antioxidant mechanisms under acute cold exposure in brains of fish. PLoS ONE 6(3):e18180. https://doi.org/10.1371/journal.pone.0018180.

Yin H, Xu L, Porter NA. 2011. Free radical lipid peroxidation: mechanisms and analysis. Chemical Reviews 111(10):5944-5972. https://doi.org/10.1021/cr200084z.