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Relationship: 2649


The title of the KER should clearly define the two KEs being considered and the sequential relationship between them (i.e., which is upstream and which is downstream). Consequently all KER titles take the form “upstream KE leads to downstream KE”.  More help

Covalent Binding, Protein leads to Increased proinflammatory mediators

Upstream event
Upstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help
Downstream event
Downstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. 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

This table is automatically generated upon addition of a KER to an AOP. All of the AOPs that are linked to this KER will automatically be listed in this subsection. Clicking on the name of the AOP in the table will bring you to the individual page for that AOP. More help
AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Covalent Binding of Low Molecular Weight Organic Chemicals to Proteins leads to Sensitisation (Sensitization) of the Respiratory Tract adjacent High Not Specified Arthur Author (send email) Under Development: Contributions and Comments Welcome Under Development

Taxonomic Applicability

Select one or more structured terms 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. Authors can indicate the relevant taxa for this KER in this subsection. The process is similar to what is described for KEs (see pages 30-31 and 37-38 of User Handbook) More help
Term Scientific Term Evidence Link
human Homo sapiens High NCBI

Sex Applicability

Authors can indicate the relevant sex for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of the User Handbook). More help
Sex Evidence
Unspecific High

Life Stage Applicability

Authors can indicate the relevant life stage for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of User Handbook). More help

Key Event Relationship Description

Provide a brief, descriptive summation of the KER. While the title itself is fairly descriptive, this section can provide details that aren’t inherent in the description of the KEs themselves (see page 39 of the User Handbook). This description section can be viewed as providing the increased specificity in the nature of upstream perturbation (KEupstream) that leads to a particular downstream perturbation (KEdownstream), while allowing the KE descriptions to remain generalised so they can be linked to different AOPs. The description is also intended to provide a concise overview for readers who may want a brief summation, without needing to read through the detailed support for the relationship (covered below). Careful attention should be taken to avoid reference to other KEs that are not part of this KER, other KERs or other AOPs. This will ensure that the KER is modular and can be used by other AOPs. More help

Covalent binding to proteins by electrophiles generates haptenated proteins which result in measurable increases in . As such, the induction and/or activation of a variety of proinflammatory mediators is a measurable result of stressors that covalently bind proteins.

Evidence Supporting this KER

Assembly and description of the scientific evidence supporting KERs in an AOP is an important step in the AOP development process that sets the stage for overall assessment of the AOP (see pages 49-56 of the User Handbook). To do this, biological plausibility, empirical support, and the current quantitative understanding of the KER are evaluated with regard to the predictive relationships/associations between defined pairs of KEs as a basis for considering WoE (page 55 of User Handbook). In addition, uncertainties and inconsistencies are considered. More help
Biological Plausibility
Define, in free text, the biological rationale for a connection between KEupstream and KEdownstream. What are the structural or functional relationships between the KEs? For example, there is a functional relationship between an enzyme’s activity and the product of a reaction it catalyses. Supporting references should be included. However, it is recognised that there may be cases where the biological relationship between two KEs is very well established, to the extent that it is widely accepted and consistently supported by so much literature that it is unnecessary and impractical to cite the relevant primary literature. Citation of review articles or other secondary sources, like text books, may be reasonable in such cases. The primary intent is to provide scientifically credible support for the structural and/or functional relationship between the pair of KEs if one is known. The description of biological plausibility 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 (see page 40 of the User Handbook for further information).   More help
Uncertainties and Inconsistencies
In addition to outlining the evidence supporting a particular linkage, it is also important to identify inconsistencies or uncertainties in the relationship. Additionally, while there are expected patterns of concordance that support a causal linkage between the KEs in the pair, it is also helpful to identify experimental details that may explain apparent deviations from the expected patterns of concordance. Identification of uncertainties and inconsistencies contribute to evaluation of the overall WoE supporting the AOPs that contain a given KER and to the identification of research gaps that warrant investigation (seep pages 41-42 of the User Handbook).Given that AOPs are intended to support regulatory applications, AOP developers should focus on those inconsistencies or gaps that would have a direct bearing or impact on the confidence in the KER and its use as a basis for inference or extrapolation in a regulatory setting. Uncertainties that may be of academic interest but would have little impact on regulatory application don’t need to be described. In general, this section details evidence that may raise questions regarding the overall validity and predictive utility of the KER (including consideration of both biological plausibility and empirical support). It also contributes along with several other elements to the overall evaluation of the WoE for the KER (see Section 4 of the User Handbook).  More help

To elucidate which pathways respiratory sensitizers regulate, in vitro DNA microarray studies were performed in different human lung cell lines exposed to a limited set of respiratory sensitizers. These studies were not able to identify specific molecular pathways that were regulated by respiratory sensitizers. They could identify activation of genes, related to innate immune response. In human alveolar epithelial cells (A549 cell line), for example, genes encoding for TLR2, TNF-a, IL-1 receptor, and cytokine signaling pathways were upregulated by hexamethylene diisocyanate (HDI) and TMA. (Verstraelen et al., 2009) NLRP3 has been demonstrated to be important in respiratory sensitization by proteins, (Besnard et al., 2012) but the involvement in the induction of respiratory sensitization by low-molecular-weight chemicals is unknown. In human keratinocytes, the respiratory sensitizers MDI and TMA failed to elevate intracellular proinflammatory IL-18 levels. (Corsini et al., 2009) Conflicting reports as to whether IL-18 is associated with a Th1 or Th2 immune response hamper interpretation of this result.

Additionally, the canonical phosphatase and tensin homolog (PTEN)-signaling pathway might be relevant for respiratory sensitization. (Verstraelen et al., 2009) This pathway regulates cell survival signaling pathways and plays a protective role in the pathogenesis of asthma. (Kwak et al., 2003) In a mouse model of TDI-induced asthma, the PTEN pathway was shown to play a protective role in asthma pathogenesis, because it was involved in the regulation of IL-17 induction and NF-kB activation. (Kim et al., 2007) A more recent in vitro study showed that the PTEN pathway was not consistently induced by all respiratory sensitizers, since maleic anhydride and 7-aminocephalosporanic acid failed to induce this pathway but another diisocyanate, HDI, did. (Remy et al., 2014)

Response-response Relationship
This subsection should be used to define sources of data that define the response-response relationships between the KEs. In particular, information regarding the general form of the relationship (e.g., linear, exponential, sigmoidal, threshold, etc.) should be captured if possible. If there are specific mathematical functions or computational models relevant to the KER in question that have been defined, those should also be cited and/or described where possible, along with information concerning the approximate range of certainty with which the state of the KEdownstream can be predicted based on the measured state of the KEupstream (i.e., can it be predicted within a factor of two, or within three orders of magnitude?). For example, a regression equation may reasonably describe the response-response relationship between the two KERs, but that relationship may have only been validated/tested in a single species under steady state exposure conditions. Those types of details would be useful to capture.  More help
This sub-section should be used to provide 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?). This can be useful information both in terms of modelling the KER, as well as for analyzing the critical or dominant paths through an AOP network (e.g., identification of an AO that could kill an organism in a matter of hours will generally be of higher priority than other potential AOs that take weeks or months to develop). Identification of time-scale can also aid the assessment of temporal concordance. For example, for a KER that operates on a time-scale of days, measurement of both KEs after just hours of exposure in a short-term experiment could lead to incorrect conclusions regarding dose-response or temporal concordance if the time-scale of the upstream to downstream transition was not considered. More help

Haptenation is essentially instantaneous, and inflammatory responses to haptenated proteins are rapid. As a result, in vitro cytokine/chemokine secretion and redox responses may be quantifiable within minutes to a few hours, but sensitivity and precision vary based on the assay detection method. Haptenated peptides generated in vitro can be quantified after 15 minutes. (Hettick, et al., 2009) Most in vitro cellular assay protocols quantify inflammatory readouts after 24 – 48 hours of exposure.

Known modulating factors
This sub-section presents information regarding modulating factors/variables known to alter the shape of the response-response function that describes the quantitative relationship between the two KEs (for example, an iodine deficient diet causes a significant increase in the slope of the relationship; a particular genotype doubles the sensitivity of KEdownstream to changes in KEupstream). Information on these known modulating factors should be listed in this subsection, along with relevant information regarding the manner in which the modulating factor can be expected to alter the relationship (if known). Note, this section should focus on those modulating factors for which solid evidence supported by relevant data and literature is available. It should NOT list all possible/plausible modulating factors. In this regard, it is useful to bear in mind that many risk assessments conducted through conventional apical guideline testing-based approaches generally consider few if any modulating factors. More help

Respiratory sensitizers without intrinsic electrophilic activity have been observed, and this is attributed to in situ generation of electrophilic activity. Pre-haptens and pro-haptens are converted from inactive molecules into active electrophiles by UV light and metabolic enzymes, respectively. (Aptula et al., 2007)

(Taylor et al;, 2020) found that single nucleotide polymorphisms (SNPs) in genese regulating inflammation, calcium regulation and endothelial function, and serine/threonine protein kinsase signaling were associated with differences in plasma and urine levels of 1,6-hexamethylene diisocyanate monomer and 1,6-hexamethylene diisocyanate isocyanurate following occupational exposure. 

Known Feedforward/Feedback loops influencing this KER
This subsection should define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits? In some cases where feedback processes are measurable and causally linked to the outcome, they should be represented as KEs. However, in most cases these features are expected to predominantly influence the shape of the response-response, time-course, behaviours between selected KEs. For example, if a feedback loop acts as compensatory mechanism that aims to restore homeostasis following initial perturbation of a KE, the feedback loop will directly shape the response-response relationship between the KERs. Given interest in formally identifying these positive or negative feedback, it is recommended that a graphical annotation (page 44) indicating a positive or negative feedback loop is involved in a particular upstream to downstream KE transition (KER) be added to the graphical representation, and that details be provided in this subsection of the KER description (see pages 44-45 of the User Handbook).  More help

Domain of Applicability

As for the KEs, there is also a free-text section of the KER description that the developer can use to explain his/her rationale for the structured terms selected with regard to taxonomic, life stage, or sex applicability, or provide a more generalizable or nuanced description of the applicability domain than may be feasible using standardized terms. More help


List of the literature that was cited for this KER description using the appropriate format. Ideally, the list of references should conform, to the extent possible, with the OECD Style Guide (OECD, 2015). More help

AGIUS, R. M., ELTON, R. A., SAWYER, L. & TAYLOR, P. 1994. Occupational asthma and the chemical properties of low molecular weight organic substances. Occup Med (Lond), 44, 34-6.

AGIUS, R. M., NEE, J., MCGOVERN, B. & ROBERTSON, A. 1991. Structure activity hypotheses in occupational asthma caused by low molecular weight substances. Ann Occup Hyg, 35, 129-37.

APTULA, A. O., ROBERTS, D. W. & PEASE, C. K. 2007. Haptens, prohaptens and prehaptens, or electrophiles and proelectrophiles. Contact Dermatitis, 56, 54-56.

BESNARD, A. G., TOGBE, D., COUILLIN, I., TAN, Z., ZHENG, S. G., ERARD, F., LE BERT, M., QUESNIAUX, V. & RYFFEL, B. 2012. Inflammasome-IL-1-Th17 response in allergic lung inflammation. J Mol Cell Biol, 4, 3-10.

CORSINI, E., MITJANS, M., GALBIATI, V., LUCCHI, L., GALLI, C. L. & MARINOVICH, M. 2009. Use of IL-18 production in a human keratinocyte cell line to discriminate contact sensitizers from irritants and low molecular weight respiratory allergens. Toxicol In Vitro, 23, 789-96.

EMTER, R., ELLIS, G. & NATSCH, A. 2010. Performance of a novel keratinocyte-based reporter cell line to screen skin sensitizers in vitro. Toxicol Appl Pharmacol, 245, 281-90.

ENOCH, S. J., ROBERTS, D. W. & CRONIN, M. T. 2010. Mechanistic category formation for the prediction of respiratory sensitization. Chem Res Toxicol, 23, 1547-55.

HETTICK, J.M., RUWONA, T.B. & SIEGEL, P.D. 2009.  Structural elucidation of isocyanate-peptide adducts using tandem mass spectrometry. J Am Soc Mass Spectrom 20, 1567–1575.

HUANG, S., WISZNIEWSKI, L., CONSTANT, S. & ROGGEN, E. 2013. Potential of in vitro reconstituted 3D human airway epithelia (MucilAir™) to assess respiratory sensitizers. Toxicol In Vitro, 27, 1151-6.

HUR, G. Y., KIM, S. H., PARK, S. M., YE, Y. M., KIM, C. W., JANG, A. S., PARK, C. S., HONG, C. S. & PARK, H. S. 2009. Tissue transglutaminase can be involved in airway inflammation of toluene diisocyanate-induced occupational asthma. J Clin Immunol, 29, 786-94.

JOHANNESSON, G., ROSQVIST, S., LINDH, C. H., WELINDER, H. & JÖNSSON, B. A. 2001. Serum albumins are the major site for in vivo formation of hapten-carrier protein adducts in plasma from humans and guinea-pigs exposed to type-1 allergy inducing hexahydrophthalic anhydride. Clin Exp Allergy, 31, 1021-30.

KIM, S. R., LEE, K. S., PARK, S. J., MIN, K. H., LEE, K. Y., CHOE, Y. H., LEE, Y. R., KIM, J. S., HONG, S. J. & LEE, Y. C. 2007. PTEN down-regulates IL-17 expression in a murine model of toluene diisocyanate-induced airway disease. J Immunol, 179, 6820-9.

KIMBER, I., POOLE, A. & BASKETTER, D. A. 2018. Skin and respiratory chemical allergy: confluence and divergence in a hybrid adverse outcome pathway. Toxicol Res (Camb), 7, 586-605.

KWAK, Y. G., SONG, C. H., YI, H. K., HWANG, P. H., KIM, J. S., LEE, K. S. & LEE, Y. C. 2003. Involvement of PTEN in airway hyperresponsiveness and inflammation in bronchial asthma. J Clin Invest, 111, 1083-92.

LALKO, J. F., KIMBER, I., DEARMAN, R. J., API, A. M. & GERBERICK, G. F. 2013. The selective peptide reactivity of chemical respiratory allergens under competitive and non-competitive conditions. J Immunotoxicol, 10, 292-301.

LALKO, J. F., KIMBER, I., DEARMAN, R. J., GERBERICK, G. F., SARLO, K. & API, A. M. 2011. Chemical reactivity measurements: potential for characterization of respiratory chemical allergens. Toxicol In Vitro, 25, 433-45.

LAUENSTEIN, L., SWITALLA, S., PRENZLER, F., SEEHASE, S., PFENNIG, O., FÖRSTER, C., FIEGUTH, H., BRAUN, A. & SEWALD, K. 2014. Assessment of immunotoxicity induced by chemicals in human precision-cut lung slices (PCLS). Toxicol In Vitro, 28, 588-99.

NATSCH, A., RYAN, C. A., FOERTSCH, L., EMTER, R., JAWORSKA, J., GERBERICK, F. & KERN, P. 2013. A dataset on 145 chemicals tested in alternative assays for skin sensitization undergoing prevalidation. J Appl Toxicol, 33, 1337-52.

REMY, S., VERSTRAELEN, S., VAN DEN HEUVEL, R., NELISSEN, I., LAMBRECHTS, N., HOOYBERGHS, J. & SCHOETERS, G. 2014. Gene expressions changes in bronchial epithelial cells: markers for respiratory sensitizers and exploration of the NRF2 pathway. Toxicol In Vitro, 28, 209-17.

SEED, M. & AGIUS, R. 2010. Further validation of computer-based prediction of chemical asthma hazard. Occup Med (Lond), 60, 115-20.

SEED, M. J. & AGIUS, R. M. 2017. Progress with Structure-Activity Relationship modelling of occupational chemical respiratory sensitizers. Curr Opin Allergy Clin Immunol, 17, 64-71.

TAYLOR, L. W., FRENCH, J. E., ROBBINS, Z. G., BOYER, J. C. & NYLANDER-FRENCH, L. A. 2020. Influence of Genetic Variance on Biomarker Levels After Occupational Exposure to 1,6-Hexamethylene Diisocyanate Monomer and 1,6-Hexamethylene Diisocyanate Isocyanurate. Front Genet, 11, 836.

VERSTRAELEN, S., NELISSEN, I., HOOYBERGHS, J., WITTERS, H., SCHOETERS, G., VAN CAUWENBERGE, P. & VAN DEN HEUVEL, R. 2009. Gene profiles of a human alveolar epithelial cell line after in vitro exposure to respiratory (non-)sensitizing chemicals: identification of discriminating genetic markers and pathway analysis. Toxicol Lett, 185, 16-22.