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Relationship: 1705

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

Loss of alveolar capillary membrane integrity leads to Activation of Th2 cells

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
Substance interaction with the lung resident cell membrane components leading to lung fibrosis adjacent Moderate Low Cataia Ives (send email) Under development: Not open for comment. Do not cite EAGMST Under Review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

Sex Applicability

An indication of the the relevant sex for this KER. More help

Life Stage Applicability

An indication of the the relevant life stage(s) for this KER.  More help

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

During the tissue injury-mediated immune response, naïve CD4+ Th cells differentiate into two major functional subsets: Th1 and Th2 type. Both Th1 and Th2 secrete distinct cytokines that promote proliferation and differentiation of their respective T cell population and inhibit proliferation and differentiation of the opposing subset. Th2 cytokines including pro-inflammatory and fibrotic mediators such as GATA-3, IL-13 and Arg-1 are increased in lung-irradiation induced fibrosis (Wynn, 2004; Brush et al., 2007; Han et al., 2011). Th2 immune response is implicated in allergen-mediated lung fibrosis. Meta-analysis of gene expression data collected from lungs of mice exposed to various fibrogenic substances including MWCNTs, showed that the expression and function of Th2 response associated genes and pathways are altered in fibrotic lungs (Nikota et al., 2016). Exposure of mice lacking STAT6 transcription factor to MWCNTs resulted in abrogated expression of Th2 genes and reduced lung fibrosis (Nikota et al., 2017). IL-4, the archetypal Th2 cytokine is a pro-fibrotic cytokine and is elevated in IPF and lung fibrosis. Overexpression of pro-fibrotic Th2 cytokine IL-13 results in sub-epithelial fibrosis with eosinophilic inflammation (Wilson and Wynn, 2009). In silica-induced pulmonary fibrosis in mice, T regulatory lymphocytes are recruited to the lungs where they increase expression of platelet-derived growth factor (PDGF) and TGF-β (Maggi et al., 2005). Chemokines associated with the Th2 response in airway epithelial cells include CCL1, CCL17, CCL20, and CCL22 (Lekkerkerker et al., 2012).

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 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

The biological plasubility of this KER is high as there is a mechanistic relationship between ACM injury (tissue damage), and the induction of a Th2 response (responsible for wound healing) (Gieseck et al., 2018; Wynn, 2004).

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

Exogenous delivery of TNFα to mouse lungs with established fibrosis, reduced the fibrotic burden. Exogenous treatment with TNFα slowed the M2 macrophage polarisation. TNFα deficient mice showed prolonged pro-fibrotic response and M2 polarisation following bleomycin treatment (Redente et al., 2014).

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
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

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

References

List of the literature that was cited for this KER description. More help
  1. Brush, J., Lipnick, S., Phillips, T., Sitko, J., McDonald, J. and McBride, W. (2007). Molecular Mechanisms of Late Normal Tissue Injury. Seminars in Radiation Oncology, 17(2), pp.121-130.
  2. Caldwell, C. C., Chen, Y., Goetzmann, H. S., Hao, Y., Borchers, M. T., Hassett, D. J., Young, L. R., Mavrodi, D., Thomashow, L., & Lau, G. W. (2009). Pseudomonas aeruginosa exotoxin pyocyanin causes cystic fibrosis airway pathogenesis. The American journal of pathology, 175(6), 2473–2488.
  3. Chang, X., Zhu, A., Liu, F., Zou, L., Su, L., Li, S., & Sun, Y. (2017). Role of NF-κB activation and Th1/Th2 imbalance in pulmonary toxicity induced by nano NiO. Environmental toxicology, 32(4), 1354–1362.
  4. Gieseck, R. L., 3rd, Wilson, M. S., & Wynn, T. A. (2018). Type 2 immunity in tissue repair and fibrosis. Nature reviews. Immunology, 18(1), 62–76.
  5. Haczku, A., Cao, Y., Vass, G., Kierstein, S., Nath, P., Atochina-Vasserman, E. N., Scanlon, S. T., Li, L., Griswold, D. E., Chung, K. F., Poulain, F. R., Hawgood, S., Beers, M. F., & Crouch, E. C. (2006). IL-4 and IL-13 form a negative feedback circuit with surfactant protein-D in the allergic airway response. Journal of immunology (Baltimore, Md. : 1950), 176(6), 3557–3565.
  6. Han, G., Zhang, H., Xie, C. H., & Zhou, Y. F. (2011). Th2-like immune response in radiation-induced lung fibrosis. Oncology reports26(2), 383–388.

  7. Jackson, J., Friberg, I., Little, S. and Bradley, J. (2009). Review series on helminths, immune modulation and the hygiene hypothesis: Immunity against helminths and immunological phenomena in modern human populations: coevolutionary legacies?. Immunology, 126(1), pp.18-27
  8. Kikuchi, N., Ishii, Y., Morishima, Y., Yageta, Y., Haraguchi, N., Itoh, K., Yamamoto, M., & Hizawa, N. (2010). Nrf2 protects against pulmonary fibrosis by regulating the lung oxidant level and Th1/Th2 balance. Respiratory research, 11(1), 31.
  9. Kolb, M., Margetts, P., Anthony, D., Pitossi, F. and Gauldie, J. (2001). Transient expression of IL-1β induces acute lung injury and chronic repair leading to pulmonary fibrosis. Journal of Clinical Investigation, 107(12), pp.1529-1536.
  10. N. Lekkerkerker, A., Aarbiou, J., van Es, T. and A.J. Janssen, R. (2012). Cellular Players in Lung Fibrosis. Current Pharmaceutical Design, 18(27), pp.4093-4102
  11. Li, J., Zhao, L., Zhang, Y., Li, W., Duan, X., Chen, J., Guo, Y., Yang, S., Sun, G., & Li, B. (2017). Imbalanced immune responses involving inflammatory molecules and immune-related pathways in the lung of acute and subchronic arsenic-exposed mice. Environmental research, 159, 381–393.
  12. Maggi, E., Cosmi, L., Liotta, F., Romagnani, P., Romagnani, S. and Annunziato, F. (2005). Thymic regulatory T cells. Autoimmunity Reviews, 4(8), pp.579-586.
  13. Miyazaki, Y., Araki, K., Vesin, C., Garcia, I., Kapanci, Y., Whitsett, J., Piguet, P. and Vassalli, P. (1995). Expression of a tumor necrosis factor-alpha transgene in murine lung causes lymphocytic and fibrosing alveolitis. A mouse model of progressive pulmonary fibrosis. Journal of Clinical Investigation, 96(1), pp.250-25
  14. Nikota, J., Williams, A., Yauk, C. L., Wallin, H., Vogel, U., & Halappanavar, S. (2016). Meta-analysis of transcriptomic responses as a means to identify pulmonary disease outcomes for engineered nanomaterials. Particle and fibre toxicology, 13(1), 25. https://doi.org/10.1186/s12989-016-0137-5
  15. Nikota J, Banville A, Goodwin LR, Wu D, Williams A, Yauk CL, Wallin H, Vogel U, Halappanavar S. Stat-6 signaling pathway and not Interleukin-1 mediates multi-walled carbon nanotube-induced lung fibrosis in mice: insights from an adverse outcome pathway framework. Part Fibre Toxicol. 2017 Sep 13;14(1):37.
  16. Ortiz, L., Lasky, J., Hamilton, R., Holian, A., Hoyle, G., Banks, W., Peschon, J., Brody, A., Lungarella, G. and Friedman, M. (1998). Expression of TNF and the Necessity of TNF Receptors in Bleomycin-Induced Lung Injury in Mice. Experimental Lung Research, 24(6), pp.721-743
  17. Piguet, P. (1989). Tumor necrosis factor/cachectin plays a key role in bleomycin-induced pneumopathy and fibrosis. Journal of Experimental Medicine, 170(3), pp.655-663
  18. Redente, E., Keith, R., Janssen, W., Henson, P., Ortiz, L., Downey, G., Bratton, D. and Riches, D. (2014). Tumor Necrosis Factor-α Accelerates the Resolution of Established Pulmonary Fibrosis in Mice by Targeting Profibrotic Lung Macrophages. American Journal of Respiratory Cell and Molecular Biology, 50(4), pp.825-837
  19. Venosa, A., Malaviya, R., Choi, H., Gow, A. J., Laskin, J. D., & Laskin, D. L. (2016). Characterization of Distinct Macrophage Subpopulations during Nitrogen Mustard-Induced Lung Injury and Fibrosis. American journal of respiratory cell and molecular biology, 54(3), 436–446.
  20. Wilson, M. and Wynn, T. (2009). Pulmonary fibrosis: pathogenesis, etiology and regulation. Mucosal Immunology, 2(2), pp.103-121
  21. Wynn, T. (2004). Fibrotic disease and the TH1/TH2 paradigm. Nature Reviews Immunology, 4(8), pp.583-594.
  22. Zhang K. (1994). Myofibroblasts and Their Role in Lung Collagen Gene Expression during Pulmonary Fibrosis. American Journal of Pathology, Vol. 145, No. 1.