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Relationship: 295

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

Activation, Stellate cells leads to Accumulation, Collagen

Upstream event
The causing Key Event (KE) in a Key Event Relationship (KER). More help
Activation, Stellate cells
Downstream event
The responding Key Event (KE) in a Key Event Relationship (KER). More help
Accumulation, Collagen

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
Protein Alkylation leading to Liver Fibrosis adjacent High Brigitte Landesmann (send email) Open for citation & comment WPHA/WNT Endorsed
Endocytic lysosomal uptake leading to liver fibrosis adjacent High Marina Kuburic (send email) Under development: Not open for comment. Do not cite Under Review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
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
Sex Evidence
Unspecific

Life Stage Applicability

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

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

Up-regulation of collagen synthesis following hepatic stellate cell (HSC) activation is among the most striking molecular responses of HSCs to injury and is mediated by both transcriptional and post-transcriptional mechanisms. Activated HSCs do not only proliferate and increase cell number, but also increase collagen production per cell. Synthesis of type I collagen is initiated by expression of the col1a1 and col1a2 genes, giving rise to α 1(I) and α 2(I) procollagen mRNAs in a 2:1 ratio. Upon activation of HSCs and other myofibroblast precursors, there is a > 50-fold increase in α 1(I) procollagen mRNA levels. The half-life of collagen α1(I) mRNA increases 20-fold in activated HSCs compared with quiescent HSCs. Monocytes and macrophages are involved in inflammatory actions by producing large amounts of Nitric oxide (NO) and inflammatory cytokines such as TNF-α which have a direct stimulatory effect on HSC collagen synthesis. Synthesis of TGF-α and TGF-β promotes activation of neighbouring quiescent HSCs, whereas the release of HGF (hepatocyte growth factor) stimulates regeneration of adjacent hepatocytes.

The basement membrane-like matrix is normally comprised of collagens IV and VI, which is progressively replaced by collagens I and III and cellular fibronectin during fibrogenesis. Although multiple extracellular matrix (ECM) components are up-regulated, type I collagen is the most abundant protein. These changes in ECM composition initiate several positive feedback pathways that further amplify collagen production. Increasing matrix stiffness is a stimulus for HSC activation and matrix-provoked signals link to other growth factor receptors through integrin-linked kinase and transduce via membrane-bound guanosine triphosphate binding proteins, in particular Rho67 and Rac, signals to the actin cytoskeleton that promote migration and contraction.

The overall amount of collagen deposited by fibroblasts is a regulated balance between collagen synthesis and collagen catabolism. Down-regulated expression of degrading Matrix metalloproteinases (MMPs) and up-regulation of tissue inhibitors of metalloproteinases (TIMPs), MMP- inhibitors, lead to a net decrease in protease activity, and therefore, matrix accumulation. Chronic inflammation, hypoxia and oxidative stress reactivate epithelial-mesenchymal transition (EMT) developmental programmes that converge in the activation of NF-kB. Cells that may transdifferentiate into fibrogenic myofibroblasts are hepatocytes and cholangiocytes. Additional sources of ECM include bone marrow (which probably gives rise to circulating fibrocytes) and portal fibroblasts (Benyon and Arthur; 2001; Milani et al., 1994; Safadi and Friedman, 2002; Kolios et al.,2006; Bataller and Brenner, 2005; Lee und Friedman 2011; Guo and Friedman, 2007; Li, Jing-Ting et al., 2008;  Kershenobich Stalnikowitz and Weisssbrod , 2003; López-Novoa and Nieto, 2009; Friedman, 2010; 2008; Dalton et al., 2009; Leung, et al., 2008; Nan et al., 2013;  Hamdy and El-Demerdash, 2012;Li, Li et al., 2012; Natajaran et al., 2006; Luckey and Petersen, 2001;  Chen and Raghunath, 2009;Thompson et al., 2011; Henderson and Iredale, 2007).

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 general acceptance that HSCs are collagen producing cells and key actors in fibrogenesis. The functional relationship between these KEs is consistent with biological knowledge (Benyon and Arthur; 2001; Milani et al., 1994; Safadi and Friedman, 2002; Kolios et al.,2006; Bataller and Brenner, 2005; Lee und Friedman 2011; Guo and Friedman, 2007; Li, Jing-Ting et al., 2008;  Kershenobich Stalnikowitz and Weisssbrod , 2003; López-Novoa and Nieto, 2009).

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

no 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
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: Safadi and Friedman, 2002; Bataller and Brenner, 2005; Lee und Friedman 2011.

Rat: Li, Li et al., 2012; Luckey and Petersen, 2001;  Rockey et al., 1992

References

List of the literature that was cited for this KER description. More help
  • Benyon, R.C. and M.J. Arthur (2001), Extracellular matrix degradation and the role of stellate cells, Semin Liver Dis, vol. 21, no. 3, pp. 373-384.
  • Milani, S. et al. (1994), Differential expression of matrix-metalloproteinase-1 and -2 genes in normal and fibrotic human liver, Am J Pathol, vol. 144, no. 3, pp. 528-537.
  • ↑Safadi, R. and S.L. Friedman (2002), Hepatic fibrosis--role of hepatic stellate cell activation, MedGenMed, vol 4, no. 3, p. 27.
  • 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.
  • Bataller, R. and D.A. Brenner (2005), Liver Fibrosis, J.Clin. Invest, vol. 115, no. 2, pp. 209-218.
  • Lee, U.E. and S.L. Friedman (2011), Mechanisms of Hepatic Fibrogenesis, Best Pract Res Clin Gastroenterol, vol. 25, no. 2, pp. 195-206.
  • Guo, J. and S. L. Friedman (2007), Hepatic fibrogenesis, Semin Liver Dis, vol. 27, no. 4, pp. 413-426.
  • Brenner, D.A. (2009), Molecular Pathogenesis of Liver Fibrosis, Trans Am Clin Climatol Assoc, vol. 120, pp. 361–368.
  • 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.
  • Kershenobich Stalnikowitz, D. and A.B. Weisssbrod (2003), Liver Fibrosis and Inflammation. A Review, Annals of Hepatology, vol. 2, no. 4, pp.159-163.
  • López-Novoa, J.M. and M.A. Nieto (2009), Inflammation and EMT: an alliance towards organ fibrosis and cancer progression, EMBO Mol Med, vol. 1. no. 6-7, pp. 303–314.
  • Friedman, S.L (2010), Evolving challenges in hepatic fibrosis, Nat. Rev. Gastroenterol. Hepatol, vol. 7, no. 8, pp. 425–436.
  • Friedman, S.L. (2008), Mechanisms of Hepatic Fibrogenesis, Gastroenterology, vol. 134, no. 6, pp. 1655–1669.
  • Dalton, S.R. et al. (2009), Carbon tetrachloride-induced liver damage in asialoglycoprotein receptor-deficient mice, Biochem Pharmacol, vol. 77, no. 7, pp. 1283-1290.
  • Leung, T.M. et al. (2008), Endothelial nitric oxide synthase is a critical factor in experimental liver fibrosis, Int J Exp Pathol, vol. 89, no. 4, pp. 241-250.
  • Nan, Y.M. et al. (2013), Activation of peroxisome proliferator activated receptor alpha ameliorates ethanol mediated liver fibrosis in mice, Lipids in Health and Disease, vol. 12, p. 11.
  • Hamdy, N. and E. El-Demerdash. (2012), New therapeutic aspect for carvedilol: antifibrotic effects of carvedilol in chronic carbon tetrachloride-induced liver damage, Toxicol Appl Pharmacol, vol. 261, no. 3, pp. 292-299.
  • Li, Li et al. (2012), Establishment of a standardized liver fibrosis model with different pathological stages in rats, Gastroenterol Res Pract; vol. 2012, Article ID 560345.
  • Natajaran, S.K. et al. (2006), Oxidative stress in the development of liver cirrhosis: a comparison of two different experimental models, J Gastroenterol Hepatol, vol. 21, no. 6, pp. 947-957.
  • Luckey, S.W., and D.R. Petersen (2001), Activation of Kupffer cells during the course of carbon tetrachloride-induced liver injury and fibrosis in rats, Exp Mol Pathol, vol. 71, no. 3, pp. 226-240.
  • Chen, C. and M. Raghunath (2009), Focus on collagen: in vitro systems to study fibrogenesis and antifibrosis state of the art, Fibrogenesis Tissue Repair, vol. 15, no. 2, p. 7.
  • Thompson, K.J., I.H. McKillop and L.W. Schrum (2011), Targeting collagen expression in alcoholic liver disease, World J Gastroenterol, vol. 17, no. 20, pp. 2473-2481.
  • Henderson, N.C. and J.P. Iredale (2007), Liver fibrosis: cellular mechanisms of progression and resolution, Clin Sci (Lond), vol. 112, no. 5, pp. 265-280.
  • Rockey, D.C. et al. (1992), Rat hepatic lipocytes express smooth muscle actin upon activation in vivo and in culture, J Submicrosc Cytol Pathol, vol. 24, no. 2, pp. 193-203.