API

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Relationship: 304

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

Up Regulation, TGFbeta1 expression leads to Activation, Stellate cells

Upstream event
The causing Key Event (KE) in a Key Event Relationship (KER). More help
Up Regulation, TGFbeta1 expression
Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER). More help
Activation, Stellate cells

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

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
Rattus norvegicus Rattus norvegicus High NCBI

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

Transforming growth factor beta 1 (TGF-β1) is the most potent fibrogenic factor for epatic stellate cells (HSCs). In response to TGF-β1, HSCs activate into myofibroblast-like cells, producing type I, III and IV collagen, proteoglycans like biglycan and decorin, glycoproteins like laminin, fibronectin, tenascin and glycosaminoglycan. [1] In the further course of events activated HSCs themselves express TGF-β1. TGF-β1 induces its own mRNA to sustain high levels in local sites of liver injury. The effects of TGF-β1 are mediated by intracellular signalling via Smad proteins. Smads 2 and 3 are stimulatory whereas Smad 7 is inhibitory. Smad1/5/8, MAP kinase and PI3 kinase are further signalling pathways in different cell types for TGF-β1 effects. [2] Concomitant with increased TGF-β production, HSC increase production of collagen. Connective tissue growth factor (CTGF) is a profibrogenic peptide induced by TGF-β, that stimulates the synthesis of collagen type I and fibronectin and may mediate some of the downstream effects of TGF-β. It is upregulated during activation of HSC, suggesting that its expression is another determinant of a fibrogenic response to TGF-β [3]. During fibrogenesis, tissue and blood levels of active TGF-β are elevated and overexpression of TGF-β1 in transgenic mice can induce fibrosis. Additionally, experimental fibrosis can be inhibited by anti-TGF-β treatments with neutralizing antibodies or soluble TbRs (TGF-β receptors) [4].

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

There is good understanding and broad acceptance of this KER. [1] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [2] [16] [17]

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 uncertainties that TGF-b1 activates HSCs.

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

Human: [6][8] Rat: [22]

References

List of the literature that was cited for this KER description. More help
  1. ↑ 1.0 1.1 Kisseleva, T. and Brenner, D.A. (2007), Role of hepatic stellate cells in fibrogenesis and the reversal of fibrosis, Journal of Gastroenterology and Hepatology, vol. 22, Suppl. 1; pp. S73–S78.
  2. ↑ 2.0 2.1 Parsons, C.J., M.Takashima and R.A. Rippe (2007), Molecular mechanisms of hepatic fibrogenesis. J Gastroenterol Hepatol, vol. 22, Suppl.1, pp. S79-S84.
  3. ↑ 3.0 3.1 Williams, E.J. et al. (2000), Increased expression of connective tissue growth factor in fibrotic human liver and in activated hepatic stellate cells, J Hepatol, vol. 32, no. 5, pp. 754-761.
  4. ↑ 4.0 4.1 Qi Z et al. (1999), Blockade of type beta transforming growth factor signaling prevents liver fibrosis and dysfunction in the rat, Proc Natl Acad Sci USA, vol. 96, no. 5, pp. 2345-2349.
  5. ↑ Gressner , A.M. et al. (2002), Roles of TGF-β in hepatic fibrosis. Front Biosci, vol. 7, pp. 793-807.
  6. ↑ 6.0 6.1 Kolios, G., V. Valatas and E. Kouroumalis (2006), Role of Kupffer cells in the pathogenesis of liver disease, World J.Gastroenterol, vol. 12, no. 46, pp. 7413-7420.
  7. ↑ Bataller, R. and D.A. Brenner (2005), Liver Fibrosis, J.Clin. Invest, vol. 115, no. 2, pp. 209-218.
  8. ↑ 8.0 8.1 Guo, J. and S. L. Friedman (2007), Hepatic fibrogenesis, Semin Liver Dis, vol. 27, no. 4, pp. 413-426.
  9. ↑ Brenner, D.A. (2009), Molecular Pathogenesis of Liver Fibrosis, Trans Am Clin Climatol Assoc, vol. 120, pp. 361–368.
  10. ↑ Kaimori, A. et al. (2007), Transforming growth factor-beta1 induces an epithelial-to-mesenchymal transition state in mouse hepatocytes in vitro, J Biol Chem, vol. 282, no. 30, pp. 22089-22101.
  11. ↑ Kershenobich Stalnikowitz, D. and A.B. Weisssbrod (2003), Liver Fibrosis and Inflammation. A Review, Annals of Hepatology, vol. 2, no. 4, pp.159-163.
  12. ↑ Li, Jing-Ting et al. (2008), Molecular mechanism of hepatic stellate cell activation and antifibrotic therapeutic strategies, J Gastroenterol, vol. 43, no. 6, pp. 419–428.
  13. ↑ Matsuoka, M. and H. Tsukamoto, (1990), Stimulation of hepatic lipocyte collagen production by Kupffer cell-derived transforming growth factor beta: implication for a pathogenetic role in alcoholic liver fibrogenesis, Hepatology, vol. 11, no. 4, pp. 599-605.
  14. ↑ Kisseleva T and Brenner DA, (2008), Mechanisms of Fibrogenesis, Exp Biol Med, vol. 233, no. 2, pp. 109-122.
  15. ↑ Poli, G. (2000), Pathogenesis of liver fibrosis: role of oxidative stress, Mol Aspects Med, vol. 21, no. 3, pp. 49 – 98.
  16. ↑ Friedman, S.L. (2008), Mechanisms of Hepatic Fibrogenesis, Gastroenterology, vol. 134, no. 6, pp. 1655–1669.
  17. ↑ Liu, Xingjun et al. (2006), Therapeutic strategies against TGF-beta signaling pathway in hepatic fibrosis. Liver Int, vol.26, no.1, pp. 8-22.
  18. ↑ Czaja, M.J. et al. (1989), In vitro and in vivo association of transforming growth factor-beta 1 with hepatic fibrosis, J Cell Biol, vol. 108, no. 6, pp. 2477-2482.
  19. ↑ Tan, A.B. et al. (2013), Cellular re- and de-programming by microenvironmental memory: why short TGF-β1 pulses can have long effects, Fibrogenesis Tissue Repair, vol. 6, no. 1, p. 12.
  20. ↑ Yin, C. et al. (2013), Hepatic stellate cells in liver development, regeneration, and cancer, J Clin Invest, vol. 123, no. 5, pp. 1902–1910.
  21. ↑ De Minicis, S. et al. (2007), Gene expression profiles during hepatic stellate cell activation in culture and in vivo, Gastroenterology, vol. 132, no. 5, pp. 1937-1946.
  22. ↑ Dooley, S. et al. (2000), Modulation of transforming growth factor b response and signaling during transdifferentiation of rat hepatic stellate cells to myofibroblasts,Hepatology, vol. 31, no. 5, pp. 1094-1106.