This Key Event Relationship is licensed under the Creative Commons BY-SA license. This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. If you remix, adapt, or build upon the material, you must license the modified material under identical terms.

Relationship: 3385

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

Generation of gluten-reactive T cell receptors leads to Co-localization of gluten reactive adaptive T-cells with APC

Upstream event

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

Generation of gluten-reactive T cell receptors

Downstream event

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

Co-localization of gluten reactive adaptive T-cells with APC

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
Gluten-driven immune activation leading to celiac disease in genetically predisposed individuals	adjacent	Moderate		Antonio Fernandez Dumont (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 Do not cite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
human	Homo sapiens	High	NCBI

Sex Applicability

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

Sex	Evidence
Unspecific	High

Life Stage Applicability

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

Term	Evidence
All life stages	High

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

A key concept within the field of immunology is the notion that adaptive responses are initiated in organized lymphoid structures (Alberts et al., 2002). TCRs specific for HLA-DQ2/8-gluten complexes are randomly synthesized during T cell development in the thymus. However, for these gluten-reactive T cells to participate in an adaptive immune response, they must encounter their specific antigen within the appropriate immune environment (Lundin et al., 1993; Arentz-Hansen et al., 2000; Janeway et al., 2001).

The generation of gluten-reactive T cell receptors (TCRs) is a prerequisite for the co-localization of gluten-reactive T cells with antigen-presenting cells (APCs) in organized lymphoid structures (Jabri & Sollid, 2017). For antigen recognition to occur, gluten peptides must be processed and presented by APCs in the gastrointestinal lymphoid tissues, and naïve T cells expressing gluten-reactive TCRs must migrate to these sites (Qiao et al., 2009). Without this migration and subsequent interaction with APCs, gluten-reactive T cells would remain functionally irrelevant.

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 was collected through a combination of literature searches and expert consultations. Experts contributed by reviewing drafted material asynchronously and participating in online discussions to refine the evidence base. Additionally, they provided key articles relevant to the topic, which served as a foundation for further literature searches in Scopus, PubMed, and Google Scholar. Keywords were tailored to each key event (KE) and key event relationship (KER) to ensure comprehensive coverage of relevant studies. The collected literature was systematically categorized in an Excel spreadsheet based on its relevance to specific KEs and KERs within the AOP. This approach facilitated the organization of data supporting different aspects of the pathway.

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

T cell development occurs in the thymus, where the generation of a highly diverse T cell receptor (TCR) repertoire is driven by a stochastic process (Alberts et al., 2002). This involves the rearrangement of TCR alpha and beta gene segments, enabling the production of a repertoire capable of recognizing a wide array of antigens presented by HLA molecules (Janeway et al., 2001). Within this process, TCRs with reactivity to both gluten and TG2 are also likely to arise. For gluten-specific T cell responses to be initiated, T cells expressing gluten-reactive TCRs must migrate to organized lymphoid structures, such as Peyer’s patches or mesenteric lymph nodes, where dendritic cells present the appropriate HLA-gluten complexes.

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

T cells specific for gluten peptides bound to HLA-DQ2 and/or HLA-DQ8 are readily detectable in individuals with celiac disease but are absent in healthy controls . This suggests that in celiac disease patients, naïve gluten-specific T cells must have encountered dendritic cells presenting gluten-antigen complexes in secondary lymphoid structures. Typically, T cells specific for immunodominant gluten peptides derived from alpha- and omega-gliadins are consistently found in patients (Christofersen et al., 2014). Furthermore, these T cells often express public T cell receptors, characterized by shared features across patients.

A hallmark of adaptive T cell responses is the clonal expansion of reactive T cells (Jabri & Sollid, 2017). The absence of detectable gluten-specific T cells in healthy controls may result from their low frequency compared to the expanded pool of such T cells in patients. Alternatively, because T cell repertoire generation is a stochastic process, it is possible that the public gluten-reactive T cell receptors were not produced in controls.

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

There are no known inconsistencies.

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 (MF)	MF Specification	Effect(s) on the KER	Reference(s)
Diet	Gluten load in the diet	Increased effect	Brottveit et al., 2011; Han et al., 2013; Raki et al., 2007

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

Response-response Relationship

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

Initiation of antigen-specific T cell responses requires interaction between naive T cells and activated antigen-loaded dendritic cells in secondary lymphoid structures. Therefore, co-localization of gluten-reactive adaptive T cells with APCs is an essential to initiate the development of celiac disease. Gluten exposure leads to T cell proliferation in celiac disease patients. Several studies have shown that reintroducing gluten in CD patients led to an increase of gluten-specific T cells (Brottveit et al., 2011; Han et al., 2013; Raki et al., 2007)

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

Adaptive immune responses develop over a timeframe of days, in which the migration of T cells to secondary lymphoid organs is a crucial first step, followed by encounter with gluten antigen-loaded dendritic cells (Qiao et al., 2012).

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

There are no known feedback loops.

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

Celiac disease, as it is currently understood, is a human-specific autoimmune disorder. Some animal models have been developed to reproduce aspects of the disease, but celiac disease is exclusive to humans. (Marietta et al., 2011).

While this KER applies to both sexes, it is important to note that females are more likely to be affected by celiac disease, and sex-based differences in immune response can influence clinical outcomes (Janson-Knodell et al., 2019; Klein and Fanagan, 2016).

References

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

Alberts B, Johnson A, Lewis J, et al. Molecular Biology of the Cell. 4th edition. New York: Garland Science; 2002. Chapter 24, The Adaptive Immune System.
Arentz-Hansen H, Körner R, Molberg Ø, Quarsten H, Vader W, Kooy YMC, Lundin KEA, Koning F, Roepstorff P, Sollid LM, McAdam S. (2000). The intestinal T cell response to α-gliadin in adult celiac disease is focused on a single deamidated glutamine targeted by tissue transglutaminase. J Exp Med. 191:603-612.
Brottveit M, Ráki M, Bergseng E, Fallang LE, Simonsen B, Løvik A, Larsen S, Løberg EM, Jahnsen FL, Sollid LM, Lundin KE. Assessing possible celiac disease by an HLA-DQ2-gliadin Tetramer Test. Am J Gastroenterol. 2011 Jul;106(7):1318-24. doi: 10.1038/ajg.2011.23. Epub 2011 Mar 1. Erratum in: Am J Gastroenterol. 2012 Apr;107(4):638. PMID: 21364548.
Christophersen A, Ráki M, Bergseng E, Lundin KE, Jahnsen J, Sollid LM, Qiao SW. Tetramer-visualized gluten-specific CD4+ T cells in blood as a potential diagnostic marker for coeliac disease without oral gluten challenge. United European Gastroenterol J. 2014 Aug;2(4):268-78. doi: 10.1177/2050640614540154. Erratum in: United European Gastroenterol J. 2014 Dec;2(6):550. doi: 10.1177/2050640614553383. PMID: 25083284; PMCID: PMC4114117.
Han A, Newell EW, Glanville J, Fernandez-Becker N, Khosla C, Chien YH, Davis MM. Dietary gluten triggers concomitant activation of CD4+ and CD8+ αβ T cells and γδ T cells in celiac disease. Proc Natl Acad Sci U S A. 2013 Aug 6;110(32):13073-8. doi: 10.1073/pnas.1311861110. Epub 2013 Jul 22. PMID: 23878218; PMCID: PMC3740842.
Jabri B, Sollid LM. T Cells in Celiac Disease. J Immunol. 2017 Apr 15;198(8):3005-3014. doi: 10.4049/jimmunol.1601693. PMID: 28373482; PMCID: PMC5426360.
Janeway CA Jr, Travers P, Walport M, et al. Immunobiology: The Immune System in Health and Disease. 5th edition. New York: Garland Science; 2001. Generation of lymphocytes in bone marrow and thymus.
Jansson-Knodell CL, Hujoel IA, West CP, Taneja V, Prokop LJ, Rubio-Tapia A, Murray JA. Sex Difference in Celiac Disease in Undiagnosed Populations: A Systematic Review and Meta-analysis. Clin Gastroenterol Hepatol. 2019 Sep;17(10):1954-1968.e13. doi: 10.1016/j.cgh.2018.11.013. Epub 2018 Nov 16. PMID: 30448593.
Klein SL, Flanagan KL. Sex differences in immune responses. Nat Rev Immunol. 2016 Oct;16(10):626-38. doi: 10.1038/nri.2016.90. Epub 2016 Aug 22. PMID: 27546235.
Lundin KE, Scott H, Hansen T, Paulsen G, Halstensen TS, Fausa O, Thorsby E, Sollid LM. (1993). Gliadin-specific, HLA-DQ(alpha 10501,beta 10201) restricted T cells isolated from the small intestinal mucosa of celiac disease patients. J Exp Med. 178:187-196.
Marietta, E., David, C., & Murray, J. (2011). Important Lessons Derived From Animal Models of Celiac Disease. International Reviews of Immunology, 30(4), 197. https://doi.org/10.3109/08830185.2011.598978
Qiao SW, Sollid LM, Blumberg RS. Antigen presentation in celiac disease. Curr Opin Immunol. 2009 Feb;21(1):111-7. doi: 10.1016/j.coi.2009.03.004. Epub 2009 Apr 1. PMID: 19342211; PMCID: PMC3901576.
Qiao SW, Iversen R, Ráki M, Sollid LM. The adaptive immune response in celiac disease. Semin Immunopathol. 2012 Jul;34(4):523-40. doi: 10.1007/s00281-012-0314-z. Epub 2012 Apr 26. PMID: 22535446.
Ráki M, Fallang LE, Brottveit M, Bergseng E, Quarsten H, Lundin KE, Sollid LM. Tetramer visualization of gut-homing gluten-specific T cells in the peripheral blood of celiac disease patients. Proc Natl Acad Sci U S A. 2007 Feb 20;104(8):2831-6. doi: 10.1073/pnas.0608610104. Epub 2007 Feb 16. PMID: 17307878; PMCID: PMC1800789.