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AOP: 501

Title

A descriptive phrase which references both the Molecular Initiating Event and Adverse Outcome.It should take the form “MIE leading to AO”. For example, “Aromatase inhibition leading to reproductive dysfunction” where Aromatase inhibition is the MIE and reproductive dysfunction the AO. In cases where the MIE is unknown or undefined, the earliest known KE in the chain (i.e., furthest upstream) should be used in lieu of the MIE and it should be made clear that the stated event is a KE and not the MIE.  More help

Excessive iron accumulation leading to neurological disorders

Short name
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Excessive iron accumulation in Neuron, Neurological disorders
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Handbook Version v2.6

Graphical Representation

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Authors

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Young Jun Kim1 and Bongsuk Choi2

1 KIST Europe, Saarbruecken 66123, Germany

2. Hanpoong Pharm & Foods Co., Ltd.11 Guretdeul 3-gil, Deokjin-gu, Jeonju-si, Jeollabuk-do, 54843, Republic of Korea. email : bongsuk333@hanpoong.co.kr

Point of Contact

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Young Jun Kim   (email point of contact)

Contributors

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  • Young Jun Kim

Coaches

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OECD Information Table

Provides users with information concerning how actively the AOP page is being developed and whether it is part of the OECD Workplan and has been reviewed and/or endorsed. OECD Project: Assigned upon acceptance onto OECD workplan. This project ID is managed and updated (if needed) by the OECD. OECD Status: For AOPs included on the OECD workplan, ‘OECD status’ tracks the level of review/endorsement of the AOP . This designation is managed and updated by the OECD. Journal-format Article: The OECD is developing co-operation with Scientific Journals for the review and publication of AOPs, via the signature of a Memorandum of Understanding. When the scientific review of an AOP is conducted by these Journals, the journal review panel will review the content of the Wiki. In addition, the Journal may ask the AOP authors to develop a separate manuscript (i.e. Journal Format Article) using a format determined by the Journal for Journal publication. In that case, the journal review panel will be required to review both the Wiki content and the Journal Format Article. The Journal will publish the AOP reviewed through the Journal Format Article. OECD iLibrary published version: OECD iLibrary is the online library of the OECD. The version of the AOP that is published there has been endorsed by the OECD. The purpose of publication on iLibrary is to provide a stable version over time, i.e. the version which has been reviewed and revised based on the outcome of the review. AOPs are viewed as living documents and may continue to evolve on the AOP-Wiki after their OECD endorsement and publication.   More help
OECD Project # OECD Status Reviewer's Reports Journal-format Article OECD iLibrary Published Version
This AOP was last modified on November 05, 2025 10:16

Revision dates for related pages

Page Revision Date/Time
Increased intracelluar Iron accumulation June 15, 2023 04:38
Decrease of neuronal network function May 28, 2018 11:36
Neurological disorder June 15, 2023 04:43
Increase, Oxidative Stress February 11, 2026 07:05
Increased intracelluar Iron leads to Increase, Oxidative Stress July 23, 2024 22:32
Increase, Oxidative Stress leads to Neuronal network function, Decreased July 23, 2024 22:36
Neuronal network function, Decreased leads to Neurological disorder June 21, 2023 09:55

Abstract

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The Adverse Outcome Pathway (AOP) for Excessive Iron Accumulation Leading to Neurological Disorders describes a mechanistic sequence linking the Molecular Initiating Event (MIE)—brain iron overload with elevation of the labile iron pool (LIP)—to the adverse outcome (AO) of neurological disorder. Excess iron catalyzes Fenton/Fenton-like chemistry and impairs iron–sulfur protein function, producing oxidative stress (Key Event 1, KE1) characterized by reactive oxygen species (ROS), lipid peroxidation, and oxidative damage to proteins/DNA. Persistent oxidative stress perturbs synaptic homeostasis (glutamatergic/GABAergic balance), mitochondrial bioenergetics, and membrane excitability, driving decrease of neuronal network function (Key Event 2, KE2)—measured as reduced synaptic transmission, impaired long-term potentiation (LTP), diminished firing/synchrony on MEAs, and connectivity loss. These network-level deficits translate to neurological disorders (AO) including cognitive impairment, movement disorders, and neurobehavioral syndromes. The sequence is supported by strong biological plausibility (iron-catalyzed ROS; vulnerability of PUFA-rich neuronal membranes) and broad empirical evidence in cellular and in vivo models. Iron chelators (e.g., deferoxamine, deferiprone) and lipid peroxidation/ferroptosis inhibitors functionally rescue early and intermediate KEs, strengthening causality. Prototypical stressors include genetic iron-handling defects (e.g., HFE, ceruloplasmin, ferritin L-chain, SLC40A1), hemorrhagic/iatrogenic iron loading, chronic inflammation with hepcidin dysregulation, and environmental/occupational sources. This AOP supports hazard identification, disease-mechanism alignment (e.g., Parkinsonian phenotypes), and screening of neuroprotective strategies targeting iron–redox balance.

AOP Development Strategy

Context

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This AOP frames how excessive iron in the CNS elevates the labile iron pool, amplifies oxidative stress, and degrades neuronal network function, culminating in neurological disorders. Neurons and oligodendrocytes are rich in PUFA and iron-dependent enzymes; microglia/astrocytes modulate iron flux (transferrin, ferritin, ferroportin, DMT1, hepcidin). Dysregulation at this node perturbs redox homeostasis, synaptic plasticity, and circuit integrity—key determinants of cognitive and motor function. Applications span regulatory neurotoxicity, disease modeling (iron-accumulation syndromes), and therapeutic design (iron chelation, antioxidant/anti-ferroptotic strategies).

Strategy

Provides a description of the approaches to the identification, screening and quality assessment of the data relevant to identification of the key events and key event relationships included in the AOP or AOP network.This information is important as a basis to support the objective/envisaged application of the AOP by the regulatory community and to facilitate the reuse of its components.  Suggested content includes a rationale for and description of the scope and focus of the data search and identification strategy/ies including the nature of preliminary scoping and/or expert input, the overall literature screening strategy and more focused literature surveys to identify additional information (including e.g., key search terms, databases and time period searched, any tools used). More help

1. Identify and Characterize Key Events (KEs) 1.1 Molecular Initiating Event (MIE) Focus: Excessive iron accumulation / ↑Labile iron pool (LIP) in the brain. Approach:

  • Quantify LIP (calcein-AM quench; ferritinophagy markers), total iron (AAS/ICP-MS), and iron distribution (MRI-R2*, QSM; Perls’/DAB-enhanced).

  • Manipulate iron flux (hepcidin–ferroportin axis; DMT1) and verify directionality with iron chelators (DFO, DFP). Outcome: Define thresholds of LIP increase that trigger oxidative stress.

1.2 Downstream KEs Focus: KE1: Oxidative stress → KE2: Decrease of neuronal network function → AO: Neurological disorder. Approach:

  • KE1 metrics: ROS (DCFH-DA, MitoSOX), lipid peroxidation (BODIPY-C11, 4-HNE/MDA), protein/DNA oxidation (protein carbonyls, 8-oxo-dG).

  • KE2 metrics: synaptic proteins (PSD-95, synaptophysin), LTP/LTD (field EPSP), MEA (firing rate, burst index, synchrony), calcium imaging (ΔF/F), resting membrane/excitability.

  • AO metrics: behavioral/cognitive (Morris water maze/novel object recognition), motor (rotarod/open field), neurologic exam; imaging of atrophy/iron accumulation. Outcome: Establish temporal and quantitative links among KEs and AO; demonstrate rescue by chelation/antioxidants.

2. Define Key Event Relationships (KERs) 2.1 Biological Plausibility: Iron catalyzes ROS via Fenton chemistry; neurons are ROS-sensitive; oxidative damage impairs synaptic proteins/mitochondria → network failure. 2.2 Empirical Support: Dose–response/time-course (iron ↑ → ROS ↑ → synaptic/MEA ↓); reversibility with chelators and lipid-ROS scavengers. 2.3 Quantitative Understanding: Build response–response models (LIP vs BODIPY-C11; BODIPY-C11 vs LTP/MEA; MEA/LTP vs behavioral scores).

3. Address Modulating Factors Iron status (systemic and CNS), age, sex hormones, diet (PUFA), antioxidant capacity (GSH/NADPH), neuroinflammation (microglial activation), co-exposures (pesticides, solvents), and genetics (iron handling variants).

4. Expand Domain of Applicability Taxonomic: Human, rodent, zebrafish; Life Stage: adult/aged > juvenile; Sex: threshold shifts via iron stores/hormones.

Summary of the AOP

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Events:

Molecular Initiating Events (MIE)
An MIE is a specialised KE that represents the beginning (point of interaction between a prototypical stressor and the biological system) of an AOP. More help
Key Events (KE)
A measurable event within a specific biological level of organisation. More help
Adverse Outcomes (AO)
An AO is a specialized KE that represents the end (an adverse outcome of regulatory significance) of an AOP. More help
Type Event ID Title Short name
MIE 2149 Increased intracelluar Iron accumulation Increased intracelluar Iron
KE 1392 Increase, Oxidative Stress Increase, Oxidative Stress
KE 386 Decrease of neuronal network function Neuronal network function, Decreased
AO 2150 Neurological disorder Neurological disorder

Relationships Between Two Key Events (Including MIEs and AOs)

This table summarizes all of the KERs of the AOP and is populated in the AOP-Wiki as KERs are added to the AOP.Each table entry acts as a link to the individual KER description page. More help
Title Adjacency Evidence Quantitative Understanding
Increased intracelluar Iron leads to Increase, Oxidative Stress adjacent Moderate Not Specified
Increase, Oxidative Stress leads to Neuronal network function, Decreased adjacent High Not Specified
Neuronal network function, Decreased leads to Neurological disorder adjacent High Not Specified

Network View

This network graphic is automatically generated based on the information provided in the MIE(s), KEs, AO(s), KERs and Weight of Evidence (WoE) summary tables. The width of the edges representing the KERs is determined by its WoE confidence level, with thicker lines representing higher degrees of confidence. This network view also shows which KEs are shared with other AOPs. More help

Prototypical Stressors

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Life Stage Applicability

The life stage for which the AOP is known to be applicable. More help
Life stage Evidence
Old Age High

Taxonomic Applicability

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Term Scientific Term Evidence Link
Homo sapiens Homo sapiens High NCBI

Sex Applicability

The sex for which the AOP is known to be applicable. More help
Sex Evidence
Mixed High

Overall Assessment of the AOP

Addressess the relevant biological domain of applicability (i.e., in terms of taxa, sex, life stage, etc.) and Weight of Evidence (WoE) for the overall AOP as a basis to consider appropriate regulatory application (e.g., priority setting, testing strategies or risk assessment). More help

This AOP links brain iron overload to neurological disorders via well-established chemistry (iron-driven ROS) and neurophysiology (synaptic/circuit degradation). Biological plausibility is high; empirical support is strong for early KEs (oxidative stress) and moderate–strong for network impairment. Quantitative mapping from network metrics to complex clinical phenotypes remains to be refined.

Domain of Applicability

Addressess the relevant biological domain(s) of applicability in terms of sex, life-stage, taxa, and other aspects of biological context. More help
Domain Relevance Evidence
Taxonomic Humans, rodents (primary) Conserved iron homeostasis and redox pathways
Life Stage Adults/elderly Age-related iron accumulation; antioxidant decline
Sex Both Differences mainly shift thresholds (iron burden, hormones)
Molecular/Cellular Neurons, astrocytes, microglia, oligodendrocytes Iron transporters (DMT1, TfR, ferroportin), ferritin, antioxidant/ferroptosis machinery
Stressors Genetic, acquired iron loading Align with clinical and preclinical observations

Essentiality of the Key Events

The essentiality of KEs can only be assessed relative to the impact of manipulation of a given KE (e.g., experimentally blocking or exacerbating the event) on the downstream sequence of KEs defined for the AOP. Consequently, evidence supporting essentiality is assembled on the AOP page, rather than on the independent KE pages that are meant to stand-alone as modular units without reference to other KEs in the sequence. The nature of experimental evidence that is relevant to assessing essentiality relates to the impact on downstream KEs and the AO if upstream KEs are prevented or modified. This includes: Direct evidence: directly measured experimental support that blocking or preventing a KE prevents or impacts downstream KEs in the pathway in the expected fashion. Indirect evidence: evidence that modulation or attenuation in the magnitude of impact on a specific KE (increased effect or decreased effect) is associated with corresponding changes (increases or decreases) in the magnitude or frequency of one or more downstream KEs. More help
Key Event (KE) Essentiality Rationale and Evidence
MIE: Brain iron overload (↑LIP) Strong Necessary driver of iron-catalyzed ROS; chelation reduces KE1.
KE1: Oxidative stress Strong Required for lipid/protein/DNA damage; antioxidants/iron chelators prevent KE2.
KE2: Network function decrease Strong Central determinant of cognition/motor control; synaptic/circuit rescue improves outcomes.
AO: Neurological disorder Outcome Emerges from cumulative network failure across regions (e.g., cortex, basal ganglia).

Evidence Assessment

Addressess the biological plausibility, empirical support, and quantitative understanding from each KER in an AOP. More help

1. MIE: Brain iron overload → Oxidative stress Biological Plausibility: Strong (Fenton chemistry; iron–sulfur protein disruption). Empirical Support: Strong (LIP↑ precedes ROS/lipid-ROS↑; reversed by chelation).

2. KE1: Oxidative stress → KE2: Network function decrease Biological Plausibility: Strong (oxidative damage to synapses/mitochondria/ion channels). Empirical Support: Strong (BODIPY-C11/4-HNE↑ correlates with ↓LTP, ↓MEA spiking/synchrony; antioxidant rescue).

3. KE2 → AO: Neurological disorder Biological Plausibility: Moderate–Strong (network integrity underlies behavior). Empirical Support: Moderate (improvements in LTP/MEA associate with behavioral rescue in models).

Known Modulating Factors

Modulating factors (MFs) may alter the shape of the response-response function that describes the quantitative relationship between two KES, thus having an impact on the progression of the pathway or the severity of the AO.The evidence supporting the influence of various modulating factors is assembled within the individual KERs. More help
Modulating Factor Influence/Outcome KER(s) involved
Labile iron pool (↑) Lowers threshold for KE1/KE2 MIE→KE1; KE1→KE2
PUFA/ACSL4 (↑) Amplifies lipid peroxidation KE1→KE2
Antioxidant capacity (GSH/NADPH) (↓) Worsens ROS handling MIE→KE1; KE1→KE2
Neuroinflammation Microglial ROS/RNS amplify damage KE1→KE2
Mitochondrial dysfunction Increases mtROS; network fragility KE1→KE2
Age/sex/hormones Shift thresholds via iron/hormonal milieu All

Quantitative Understanding

Optional field to provide quantitative weight of evidence descriptors.  More help
Key Event / Relationship Quantitative Evidence Thresholds Temporal Concordance
MIE (LIP↑) % calcein-quench loss vs ROS indices LIP ≥120–150% baseline → ROS↑ Minutes–hours
KE1 (Oxidative stress) BODIPY-C11/4-HNE vs LTP/MEA BODIPY ≥150–200% & 4-HNE↑ predict LTP↓ ≥20–30% Hours–days
KE1→KE2 ROS/lipid-ROS vs network metrics ≥30% LTP decline or ≥25% MEA firing↓ indicates KE2 Hours–days
KE2→AO Network composite vs behavior Region-specific; composite drop associates with cognitive/motor deficits Days–weeks

Considerations for Potential Applications of the AOP (optional)

Addressess potential applications of an AOP to support regulatory decision-making.This may include, for example, possible utility for test guideline development or refinement, development of integrated testing and assessment approaches, development of (Q)SARs / or chemical profilers to facilitate the grouping of chemicals for subsequent read-across, screening level hazard assessments or even risk assessment. More help

  • Screening: Prioritize compounds that raise LIP or lipid-ROS in neuron–glia co-cultures/brain organoids; apply MEA/LTP readouts.

  • Risk management: Incorporate iron chelation and anti-ferroptotic strategies in mitigation studies.

  • Translational markers: MRI-QSM/R2* for brain iron; plasma/CSF 4-HNE/MDA; electrophysiological network metrics.

References

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

  1. Levi S, et al. "Iron imbalance in neurodegeneration." Molecular Psychiatry, 2024.​

  2. Ward RJ, et al. "The role of iron in brain ageing and neurodegenerative disorders." PMC, 2014.​

  3. Stankiewicz J, et al. "Iron in Chronic Brain Disorders." Neurobiology of Disease, 2007.​

  4. Mohammadi S, et al. "Iron accumulation/overload and Alzheimer's disease risk." Alzheimer's & Dementia, 2024.​

  5. Daglas M, et al. "The Involvement of Iron in Traumatic Brain Injury and Neurodegeneration." Frontiers in Neuroscience, 2018.​

  6. Levi S, et al. "Neurodegeneration with brain iron accumulation." Frontiers in Pharmacology, 2014.​

  7. Gao G, et al. "Brain Iron Metabolism, Redox Balance and Neurological Diseases." PMC, 2023.​

  8. Gao Q, et al. "Role of iron in brain development, aging, and neurodegeneration." Annals of Medicine, 2025.​

  9. Medlink Editors. "Neurodegeneration with brain iron accumulation." Medlink Neurology, 2025.​

  10. Loughnan R, et al. "Hemochromatosis neural archetype reveals iron disruption in the brain." Science Advances, 2024.​

  11. Riederer P, et al. "Iron in neurodegeneration - cause or consequence?", Journal of Neural Transmission, 2021.

  12. Rouault TA. "Iron metabolism in the CNS: implications for neurodegenerative diseases." Nature Reviews Neuroscience, 2013.

  13. Papanikolaou G, et al. "Iron metabolism and toxicity in Parkinson's disease." Acta Neurologica Scandinavica, 2020.

  14. Ayton S, et al. "Brain iron accumulation and its impact on neurodegenerative diseases." Trends in Neurosciences, 2017.

  15. Hare D, et al. "Iron in Alzheimer's disease: from pathogenesis to therapeutic approaches." Lancet Neurology, 2013.

  16. Que EL, et al. "Iron Homeostasis: Mechanisms and Disease." Annual Review of Biochemistry, 2018.

  17. Zecca L, et al. "Iron, brain ageing and neurodegenerative disorders." Nature Reviews Neuroscience, 2004.

  18. Forni GL, et al. "Neurological complications in hereditary hemochromatosis." Hematology and Therapy, 2019.

  19. Bush AI. "Metals and neurodegeneration." Current Opinion in Chemical Biology, 2017.

  20. Kaur D, et al. "Iron in Parkinson's disease: causes and consequences." Neurochemical Research, 2015.

  21. Walker Z, et al. "Neuroferritinopathy: clinical features and genetics." Neurology, 2019.

  22. Miyajima H, et al. "Aceruloplasminemia as a genetic iron overload disorder." Nature Genetics, 1987.

  23. Möller HE, et al. "Brain iron mapping using MRI: clinical relevance." Radiology, 2020.

  24. You LH, et al. "Ferroptosis and neurodegeneration: iron toxicity mechanisms." Free Radical Biology & Medicine, 2022.

  25. Zimmermann MB. "Iron deficiency and excess: neurological effects." Annals of Nutrition & Metabolism, 2017.

  26. Gregory A, et al. "Neurodegeneration with brain iron accumulation syndromes." Brain, 2009.

  27. Pandolfo M, et al. "Friedreich ataxia and iron toxicity." Annals of Neurology, 2012.

  28. Morey TM, et al. "Iron overload and cognitive decline." Neuropsychopharmacology, 2018.

  29. Langkammer C, et al. "Quantitative MR imaging of brain iron." Radiology, 2010.

  30. Cossu G, et al. "Pantothenate kinase-associated neurodegeneration: A clinical review." Movement Disorders Clinical Practice, 2020.