API

Aop: 31

AOP Title

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Oxidation of iron in hemoglobin leading to hematotoxicity

Short name:

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Hemoglobin oxidation leading to hematotoxicity

Authors

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Mitchell Wilbanks, Kurt Gust, Youping Deng, Sharon Meyer, and Edward Perkins

Point of Contact: Mitchell Wilbanks, Mitchell.S.Wilbanks@usace.army.mil

Point of Contact

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Mitchell S. Wilbanks

Contributors

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  • Mitchell S. Wilbanks

Status

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Author status OECD status OECD project SAAOP status
Under development: Not open for comment. Do not cite Under Development 1.16 Included in OECD Work Plan


This AOP was last modified on December 03, 2016 16:37

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Revision dates for related pages

Page Revision Date/Time
N/A, Parent compound is converted to the reactive metabolite and forms free radicals leading to oxidation of heme iron(II) in hemoglobin to iron(III) December 03, 2016 16:37
Altered regulation, Alpha hemoglobin September 16, 2017 10:14
Propagation, Oxidative stress September 16, 2017 10:14
Damaging, Red blood cells; hemolysis September 16, 2017 10:14
Formation, Formation of hemoglobin adducts September 16, 2017 10:14
Down Regulation, Gulcose-6-phosphate dehydrogenase September 16, 2017 10:14
Increase, RBC congestion in liver September 16, 2017 10:14
Increase, Liver and splenic hemosiderosis September 16, 2017 10:14
N/A, Methemoglobinemia, decreased hemoglobin, hematocrit, red blood cell number September 16, 2017 10:14
N/A, Cyanosis occurs December 03, 2016 16:33
N/A, Parent compound is converted to the reactive metabolite and forms free radicals leadin leads to Propagation, Oxidative stress December 03, 2016 16:37
N/A, Parent compound is converted to the reactive metabolite and forms free radicals leadin leads to Damaging, Red blood cells; hemolysis December 03, 2016 16:37
N/A, Parent compound is converted to the reactive metabolite and forms free radicals leadin leads to Formation, Formation of hemoglobin adducts December 03, 2016 16:37
Damaging, Red blood cells; hemolysis leads to Increase, RBC congestion in liver December 03, 2016 16:37
Damaging, Red blood cells; hemolysis leads to N/A, Methemoglobinemia, decreased hemoglobin, hematocrit, red blood cell number December 03, 2016 16:37
Damaging, Red blood cells; hemolysis leads to Increase, Liver and splenic hemosiderosis December 03, 2016 16:37
Propagation, Oxidative stress leads to Down Regulation, Gulcose-6-phosphate dehydrogenase December 03, 2016 16:37
N/A, Parent compound is converted to the reactive metabolite and forms free radicals leadin leads to Altered regulation, Alpha hemoglobin December 03, 2016 16:37
N/A, Methemoglobinemia, decreased hemoglobin, hematocrit, red blood cell number leads to N/A, Cyanosis occurs December 03, 2016 16:37
Increase, RBC congestion in liver leads to N/A, Methemoglobinemia, decreased hemoglobin, hematocrit, red blood cell number December 03, 2016 16:37
Propagation, Oxidative stress leads to Damaging, Red blood cells; hemolysis December 03, 2016 16:37
Increase, Liver and splenic hemosiderosis leads to N/A, Methemoglobinemia, decreased hemoglobin, hematocrit, red blood cell number December 03, 2016 16:37

Abstract

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Studies have shown that aniline, 2,4,6-trinitrotoluene (TNT) and 2,4-dinitrotoluene (2,4-DNT) are converted to the reactive metabolite and form free radicals leading to oxidization of heme Iron(II) in hemoglobin to Iron(III), a molecular initiating event. Damage then occurs to red blood cells (RBCs) and methemoglobinemia ensues which is characterized by reduced RBCs, hemoglobin concentration, and Heinz body formation (Ellis et al. 1985, Lee et al. 1976, 1978, Hazleton Laboratories 1977, 1982, Kozuka et al. 1978, 1979, Bolt et al. 2006). The adverse outcome due to such hematological effects is cyanosis with possible death if methemoglobin levels become severe. Hemoglobin adducts are also formed by these chemicals (Sabbioni et al. 2006). Sinusoidal congestion was noted in animals who were exposed to 2,4-DNT or 2,6-DNT (Deng et al. 2011) while hemosiderosis was reported in another study involving DNT (Lee et al. 1978) and in aniline studies. A compensatory response to possible anemic effects has been observed in animals including increased peripheral reticulocytes (Deng et al. 2011) and induction of genes associated with heme biosynthesis (CPOX and UROS) (Rawat et al. 2010). Oxidative stress is also induced upon this interaction with the RBC which may lead to DNA damage and cell death to not only the RBC but other cells such as hepatocytes (Deng et al. 2011). Glucose-6-phosphate dehydrogenase (G6pd) was found to be significantly down-regulated in animals treated with 2,4-DNT for 14 d which leads to decreased levels of NADPH, a coenzyme used to properly maintain glutathione levels and therefore protect cells, especially RBC, from oxidative damage (Wilbanks, et al., unpublished observations). In response to increased oxidative stress, protective mechanisms such as the Nrf2 mediated oxidative stress response may be induced (Deng et al. 2011). While this AOP specifically shows effects of 2,4-DNT and 2,6-DNT, the principal adverse pathways of oxidation of Fe(II) to Fe(III) leading to methemoglobinemia and its downsteam effects and oxidative stress formation leading to its downstream effects are shared with the more well characterized structurally similar compound group of N-hydroxyl anilines.


Background (optional)

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Summary of the AOP

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Stressors

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Describes stressors known to trigger the MIE and provides evidence supporting that initiation. This will often be a list of prototypical compounds demonstrated to interact with the target molecule in the manner detailed in the MIE description to initiate a given pathway (e.g., 2,3,7,8-TCDD as a prototypical AhR agonist; 17α-ethynyl estradiol as a prototypical ER agonist). However, depending on the information available, this could also refer to chemical categories (i.e., groups of chemicals with defined structural features known to trigger the MIE). It can also include non-chemical stressors such as genetic or environmental factors. The evidence supporting the stressor will typically consist of a brief description and citation of literature showing that particular stressors can trigger the MIE.

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Molecular Initiating Event

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Title Short name
N/A, Parent compound is converted to the reactive metabolite and forms free radicals leading to oxidation of heme iron(II) in hemoglobin to iron(III) N/A, Parent compound is converted to the reactive metabolite and forms free radicals leadin

Key Events

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Title Short name
Altered regulation, Alpha hemoglobin Altered regulation, Alpha hemoglobin
Propagation, Oxidative stress Propagation, Oxidative stress
Damaging, Red blood cells; hemolysis Damaging, Red blood cells; hemolysis
Formation, Formation of hemoglobin adducts Formation, Formation of hemoglobin adducts
Down Regulation, Gulcose-6-phosphate dehydrogenase Down Regulation, Gulcose-6-phosphate dehydrogenase
Increase, RBC congestion in liver Increase, RBC congestion in liver
Increase, Liver and splenic hemosiderosis Increase, Liver and splenic hemosiderosis
N/A, Methemoglobinemia, decreased hemoglobin, hematocrit, red blood cell number N/A, Methemoglobinemia, decreased hemoglobin, hematocrit, red blood cell number

Adverse Outcome

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Title Short name
N/A, Cyanosis occurs N/A, Cyanosis occurs

Relationships Between Two Key Events (Including MIEs and AOs)

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Title Directness Evidence Quantitative Understanding
N/A, Parent compound is converted to the reactive metabolite and forms free radicals leadin leads to Propagation, Oxidative stress Directly leads to Moderate
N/A, Parent compound is converted to the reactive metabolite and forms free radicals leadin leads to Damaging, Red blood cells; hemolysis Directly leads to Strong
N/A, Parent compound is converted to the reactive metabolite and forms free radicals leadin leads to Formation, Formation of hemoglobin adducts Directly leads to Strong
Damaging, Red blood cells; hemolysis leads to Increase, RBC congestion in liver Directly leads to Moderate
Damaging, Red blood cells; hemolysis leads to N/A, Methemoglobinemia, decreased hemoglobin, hematocrit, red blood cell number Directly leads to Strong
Damaging, Red blood cells; hemolysis leads to Increase, Liver and splenic hemosiderosis Directly leads to Strong
Propagation, Oxidative stress leads to Down Regulation, Gulcose-6-phosphate dehydrogenase Directly leads to Weak
N/A, Parent compound is converted to the reactive metabolite and forms free radicals leadin leads to Altered regulation, Alpha hemoglobin Indirectly leads to Weak
N/A, Methemoglobinemia, decreased hemoglobin, hematocrit, red blood cell number leads to N/A, Cyanosis occurs Directly leads to Strong
Increase, RBC congestion in liver leads to N/A, Methemoglobinemia, decreased hemoglobin, hematocrit, red blood cell number Directly leads to Moderate
Propagation, Oxidative stress leads to Damaging, Red blood cells; hemolysis Directly leads to Strong
Increase, Liver and splenic hemosiderosis leads to N/A, Methemoglobinemia, decreased hemoglobin, hematocrit, red blood cell number Directly leads to Moderate

Network View

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Life Stage Applicability

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Is the AOP specific to certain tissues, life stages / age classes? Indicate if there are critical life stages, where exposure must occur, to results in the final adverse effect. Or specify if there are key events along the pathway which are dependent on the life stage although the AOP is known to be initiated regardless of life stage. Indicate also if the AOP is associated also with age- or sex-dependence.

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Taxonomic Applicability

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Term Scientific Term Evidence Link
Mus musculus Mus musculus Strong NCBI
Rattus norvegicus Rattus norvegicus Strong NCBI

Sex Applicability

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Graphical Representation

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Click to download graphical representation template

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Overall Assessment of the AOP

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This AOP is constructed using data from human, rat, mouse, avian, and fish based studies.

Domain of Applicability

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The relevant domain(s) of applicability in terms of sex, life-stage, taxa, and other aspects of biological context are defined in this section. Domain of applicability is informed by the “Description” and “Taxonomic Relevance” section of each KE description and the “Description of the KER” section of each KER description. The relevant domain of applicability of the AOP as a whole will most often be defined based on the most narrowly restricted of its KEs. For example, if most of the KEs apply to either sex, but one is relevant to females only, the domain of applicability of the AOP as a whole would generally be limited to females. While much of the detail defining the domain of applicability may be found in the individual KE descriptions, the rationale for defining the relevant domain of applicability of the overall AOP should be briefly summarised on the AOP page.

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Essentiality of the Key Events

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The essentiality of various of the KEs is influential in considering confidence in an overall hypothesised AOP for potential regulatory application being secondary only to biological plausibility of KERs (Meek et al., 2014; 2014a). The defining question for determining essentiality (included in Annex 1) relates to whether or not downstream KEs and/or the AO is prevented if an upstream event is experimentally blocked. It is assessed, generally, then, on the basis of direct experimental evidence of the absence/reduction of downstream KEs when an upstream KE is blocked or diminished (e.g., in null animal models or reversibility studies). Weight of evidence for essentiality of KEs would be considered high if there is direct evidence from specifically designed experimental studies illustrating essentiality for at least one of the important key events [e.g., stop/reversibility studies, antagonism, knock out models, etc.) moderate if there is indirect 25 evidence that experimentally induced change of an expected modulating factor attenuates or augments a key event (e.g., augmentation of proliferative response (KEupstream) leading to increase in tumour formation (KEdownstream or AO)) and weak if there is no or contradictory experimental evidence of the essentiality of any of the KEs (Annex 1).

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Weight of Evidence Summary

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This involves evaluation of the Overall AOP based on Relative Level of Confidence in the KERs, Essentiality of the KEs and Degree of Quantitative Understanding based on Annexes 1 and 2. Annex 1 (“Guidance for assessing relative level of confidence in the Overall AOP”) guides consideration of the weight of evidence or degree of confidence in the predictive relationship between pairs of KEs based on KER descriptions and support for essentiality of KEs. It is designed to facilitate assignment of categories of high, moderate or low against specific considerations for each a series of defined element based on current experience in assessing MOAs/AOPs. In addition to increasing consistency through delineation of defining questions for the elements and the nature of evidence associated with assignment to each of the categories, importantly, the objective of completion of Annex 1 is to transparently delineate the rationales for the assignment based on the specified considerations. While it is not necessary to repeat lengthy text which appears in earlier parts of the document, the entries for the rationales should explicitly express the reasoning for assignment to the categories, based on the considerations for high, moderate or low weight of evidence included in the columns for each of the relevant elements. 24 While the elements can be addressed separately for each of the KERs, the essentiality of the KEs within the AOP is considered collectively since their interdependence is often illustrated through prevention or augmentation of an earlier or later key event. Where it is not possible to experimentally assess the essentiality of the KEs within the AOP (i.e., there is no experimental model to prevent or augment the key events in the pathway), this should be noted. Identified limitations of the database to address the biological plausibility of the KERs, the essentiality of the KEs and empirical support for the KERs are influential in assigning the categories for degree of confidence (i.e., high, moderate or low). Consideration of the confidence in the overall AOP is based, then, on the extent of available experimental data on the essentiality of KEs and the collective consideration of the qualitative weight of evidence for each of the KERs, in the context of their interdependence leading to adverse effect in the overall AOP. Assessment of the overall AOP is summarized in the Network View, which represents the degree of confidence in the weight of evidence both for the rank ordered elements of essentiality of the key events and biological plausibility and empirical support for the interrelationships between KEs. The AOP-Wiki provides such a network graphic based on the information provided in the MIE, KE, AO, and KER tables. The Key Event Essentiality calls are used to determine the size of each key event node with larger sizes representing higher confidence for essentiality. The Weight of Evidence summary in the KER table is used to determine the width of the lines connecting the key events with thicker lines representing higher confidence.

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Quantitative Considerations

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The extent of quantitative understanding of the various KERs in the overall hypothesised AOP is also critical in consideration of potential regulatory application. For some applications (e.g. doseresponse analysis in in depth risk assessment), quantitative characterisation of downstream KERs may be essential while for others, quantitative understanding of upstream KERs may be important (e.g., QSAR modelling for category formation for testing). Because evidence that contributes to quantitative understanding of the KER is generally not mutually exclusive with the empirical support for the KER, evidence that contributes to quantitative understanding should generally be considered as part of the evaluation of the weight of evidence supporting the KER (see Annex 1, footnote b). General guidance on the degree of quantitative understanding that would be characterised as weak, moderate, or strong is provided in Annex 2.

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Considerations for Potential Applications of the AOP (optional)

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At their discretion, the developer may include in this section discussion of the 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. While it is challenging to foresee all potential regulatory application of AOPs and any application will ultimately lie within the purview of regulatory agencies, potential applications may be apparent as the AOP is being developed, particularly if it was initiated with a particular application in mind. This optional section is intended to provide the developer with an opportunity to suggest potential regulatory applications and describe his or her rationale. Detailing such considerations can aid the process of transforming narrative descriptions of AOPs into practical tools. In this context, it is necessarily beneficial to involve members of the regulatory risk assessment community on the development and assessment team. The Network view which is generated based on assessment of weight of evidence/degree of confidence in the hypothesized AOP taking into account the elements described in Section 7 provides a useful summary of relevant information as a basis to consider appropriate application in a regulatory context. Consideration of application needs then, to take into consideration the following rank ordered qualitative elements: Confidence in biological plausibility for each of the KERs Confidence in essentiality of the KEs Empirical support for each of the KERs and overall AOP The extent of weight of evidence/confidence in both these qualitative elements and that of the quantitative understanding for each of the KERs (e.g., is the MIE known, is quantitative understanding restricted to early or late key events) is also critical in determining appropriate application. For example, if the confidence and quantitative understanding of each KER in a hypothesised AOP are low and or low/moderate and the evidence for essentiality of KEs weak (Section 7), it might be considered as appropriate only for applications with less potential for impact (e.g., prioritisation, category formation for testing) versus those that have immediate implications potentially for risk management (e.g., in depth assessment). If confidence in quantitative understanding of late key events is high, this might be sufficient for an in depth assessment. The analysis supporting the Network view is also essential in identifying critical data gaps based on envisaged regulatory application.

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References

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Bolt HM, Degen GH, Dorn SB, Plöttner S, Harth V (2006) Genotoxicity and potential carcinogenicity of 2,4,6-TNT trinitrotoluene: structural and toxicological considerations. Reviews on environmental health. Oct-Dec; 21(4):217-28.

Deng Y, Meyer SA, Guan X, Escalon BL, Ai J, et al. (2011) Analysis of Common and Specific Mechanisms of Liver Function Affected by Nitrotoluene Compounds. PLoS ONE. 6(2): e14662.

Ellis HV, Hong CB, Lee CC, et al. 1985. Subchronic and chronic toxicity studies of 2,4-dinitrotoluene. Part I. Beagle dog. J Am Co11 Toxicol. 4:233-242.

Jones, C.R., Liu, Y., Sepai, O., Yan, H., and Sabbioni, G. (2005). Hemoglobin adducts in workers exposed to nitrotoluenes. Carcinogenesis. 26(1):133-143.

Kozuka H, Mori M., Katayama K, Matsuhashi T, Miyahara T, Mori Y, and Nagahara S. 1978. Studies on the metabolism and toxicity of dinitrotoluenes-Metabolism of dinitrotoluenes by Rhodotorula glutinis and rat liver homogenate. Eisei Kagaku, 24: 252-259.

Kozuka H, Mori M, and Yoshifumi, N. 1979. Studies on the metabolism and toxicity of dinitrotoluenes: Toxicological study of 2,4-dinitrotoluene (2,4-DNT) in rats in long term feeding. The Journal of Toxicological Sciences. 4:221-228.

La, D.K. and Froines, J.R. (1992). Comparison of DNA adduct formation between 2,4 and 2,6-dintirotoluene by 32P-postlabelling analysis. Archives of Toxicology. 66(9):633-640.

Lee CC, Ellis HV, Kowalski JJ, et al. 1976. Mammalian toxicity of munitions compounds. Phase II: Effects of multiple doses. Part IIh 2,6-Dinitrotoluene. Progress report no. 4. Midwest Research Institute Project no. 3900-B. Contract no. DAMD-17-74-C-4073. From ASTDR.

Lee CC, Ellis HV, Kowalski JJ, et al. 1978. Mammalian toxicity of munitions compounds. Phase II: Effects of multiple doses. Part Il: 2,4-Dinitrotoluene. Progress report No. 3. Midwest Research Institute, Kansas City, MO. Contract no. DAMD 17-74-C-4073. From ASTDR.

Hazleton Laboratories. 1977. A thirty-day toxicology study in Fischer-344 rats given dinitrotoluene, technical grade. Full report. Submitted to Chemical Industry Institute of Toxicology, Research Triangle Park, NC.

Hazleton Laboratories. 1982. 104-week chronic study in rats. Dinitrotoluene. Final report Volume I of II. Submitted to Chemical Industry Institute of Toxicology, Research Triangle Park, NC.

Rawat A, Gust KA, Deng Y, Garcia-Reyero N, Quinn MJ Jr, Johnson MS, Indest KJ, Elasri MO, Perkins EJ. From raw materials to validated system: the construction of a genomic library and microarray to interpret systemic perturbations in Northern bobwhite. Physiol Genomics. 42: 219–235, 2010.

Sabbioni G, Jones CR, Sepai O, et al. 2006. Biomarkers of exposure, effect, and susceptibility in workers exposed to nitrotoluenes. Cancer Epidemiol Biomarkers. Prev 15(3):559-66.

Wintz H, Yoo LJ, Loguinov A, Wu Y, Steevens JA, Holland RD, Beger RD, Perkins EJ, Hughes O, Vulpe CD. Gene expression profiles in fathead minnow exposed to 2,4-DNT: correlation with toxicity in mammals. Toxicol Sci. 94: 71–82, 2006.