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Relationship: 1709


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

Histone deacetylase inhibition leads to Histone acetylation, increase

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
Histone deacetylase inhibition leading to testicular atrophy adjacent High Moderate Shihori Tanabe (send email) Open for citation & comment WPHA/WNT Endorsed
Histone deacetylase inhibition leads to neural tube defects adjacent Not Specified Not Specified Marvin Martens (send email) Under Development: Contributions and Comments Welcome

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
Homo sapiens Homo sapiens High NCBI
Rattus norvegicus Rattus norvegicus High NCBI
Mus musculus Mus musculus High NCBI
Oryctolagus cuniculus Oryctolagus cuniculus Moderate NCBI
Brassica napus Brassica napus Moderate 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
Term Evidence
All life stages Moderate

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

The HDAC inhibitors (HDIs) inhibit deacetylation of the histone, leading to the increase in histone acetylation and gene transcription. HDACs deacetylate acetylated histone in epigenetic regulation [Falkenberg and Johnstone, 2014].

Histone acetylation is one of the major epigenetic mechanisms and belongs to the posttranslational modifications of histones. Histone acetyltransferase is setting the mark, and deacetylase (HDAC) is responsible for removing the acetyl group from specific lysine residues of the histones. It has been shown that the inhibition of HDACs leads to a hyperacetylation of histones and in general to an imbalance of other histone modifications.

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

HDACs are important proteins in the epigenetic regulation of gene transcription. Upon the inhibition of HDAC by HDIs, lysine in histone remains acetylated which leads to transcriptional activation or repression, changes in DNA replication, and DNA damage repair [Wade et al., 2008].

In all eukaryotes, the DNA containing the genetic information of an organism is organized in chromatin. The basic unit of chromatin is the nucleosome around which the naked DNA is wrapped. A nucleosome consists of two copies of each of the core histones H2A, H2B, H3, and H4 [Luger et al., 1997]. In order to dynamically regulate this highly complex structure several mechanisms are involved, including the posttranslational modifications of histones (reviewed in [Bannister and Kouzarides, 2011; Kouzarides, 2007]. For a long time, it is known that histones get acetylated and that this reaction is catalyzed by histone acetyltransferases (HAT) whereas the acetyl groups are removed by histone deacetylases (HDAC). Inhibition of HDACs by small-molecule compounds leads to hyperacetylation of the histones as the homeostasis of acetylation and deacetylation is disturbed (reviewed in [Gallinari et al., 2007]).

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

HDACs affect a large number of cellular proteins including histones, which reminds us the HDAC inhibition by HDIs hyperacetylates cellular proteins other than histones and exhibit additional biological effects. It is also noted that HDAC functions as the catalytic subunits of the large protein complex, which suggests that the inhibition of HDAC by HDIs affects the function of the large multiprotein complexes of HDAC [Falkenberg and Johnstone, 2014].  Related-analysis are usually indirect or in purified systems, therefore a direct cause-consequence relation is difficult to obtain.

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

SAHA or MS-275 treatment leads to an increase in acetylation of specific lysine residues on histones more than two-fold [Choudhary et al., 2009]. Acetylation of the variant histone H2AZ-a mark for DNA damage sites- was upregulated almost 20-fold by SAHA, whereas a number of sites on the core histones H3 and H4 are several times more highly regulated in response to SAHA than by MS-275 [Choudhary et al., 2009].

TSA (100 ng/ml) treatment leads to accumulation of the acetylated histones in a variety of mammalian cell lines, and the partially purified HDAC from wild-type FM3A cells was effectively inhibited by TSA (Ki = 3.4 nM) [Yoshida et al., 1990].

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
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
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

The relationship between HDAC inhibition and increase in histone acetylation is conceivably well conserved among various species including mammals.

  • Hyperacetylation by HDIs such as SAHA and Cpd-60 are observed in mice (Mus musculus) [Schroeder et al., 2013].
  • TSA induces acetylation of histone H4 in a time-dependent manner in mouse cell lines (Mus musculus) [Alberts et al., 1998].
  • AR-42, a novel HDI, induces hyperacetylation in human pancreatic cancer cells (Homo sapiens) [Henderson et al., 2016].
  • SAHA and MS-275 lead to the hyperacetylation of lysine residues of histones in human cell lines of epithelial (A549) and lymphoid origin (Jurkat) (Homo sapiens) [Choudhary et al., 2009].
  • SAHA treatment induces the H3 and H4 histone acetylation in human corneal fibroblasts and conjunctiva from rabbits after glaucoma filtration surgery (Homo sapiens, Oryctolagus cuniculus) [Sharma et al., 2016].
  • TSA induces the acetylation of histones H3 and H4 in Brassica napus microspore cultures (Brassica napu) [Li et al., 2014].


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

Alberts, A.S. et al. (1998), "Activation of SRF-regulated chromosomal templates by Rho-family GTPases requires a signal that also induces H4 hyperacetylation", Cell 92:475-487

Bannister, A. J. and Kouzarides, T. (2011), "Regulation of chromatin by histone modifications", Cell Res 21:381-395

Chen, S. et al. (2018), "Valproic acid attenuates traumatic spinal cord injury-induced inflammation via STAT1 and NF-kB pathway dependent of HDAC3", J Neuroinflammation 15:150

Choudhary, C. et al. (2009), "Lysine acetylation targets protein complexes and co-regulates major cellular functions", Science 325:834-840

Cousens, L. S. et al. (1979), "Different accessibilities in chromatin to histone acetylase", J Biol Chem 254:1716-1723

Dayan, C. and Hales, B.F. (2014), "Effects of ethylene glycol monomethyl ether and its metabolite, 2-methoxyacetic acid, on organogenesis stage mouse limbs in vitro", Birth Defects Res (Part B) 101:254-261

Eikel, D. et al. (2006), "Teratogenic effects mediated by inhibition of histone deacetylases: evidence from quantitative structure activity relationships of 20 valproic acid derivatives", Chem Res Toxicol 19:272-278

Falkenberg, K.J. and Johnstone, R.W. (2014), "Histone deacetylases and their inhibitors in cancer, neurological disease and immune disorders", Nat Rev Drug Discov 13:673-691

Gallinari, P. et al. (2007), "HDACs, histone deacetylation and gene transcription: From molecular biology to cancer therapeutics", Cell Res 17:195-211

Gottlicher, M. et al. (2001), "Valproic acid defines a novel class of HDAC inhibitors inducing differentiation of transformed cells", EMBO J 20:6969-6978

Henderson, S.E. et al. (2016), "Suppression of tumor growth and muscle wasting in a transgenic mouse model of pancreatic cancer by the novel histone deacetylase inhibitor AR-42", Neoplasia 18:765-774

Kouzarides, T. (2007), "Chromatin modifications and their function", Cell 128:693-705

Lagger, G. et al. (2002), "Essential function of histone deacetylase 1 in proliferation control and CDK inhibitor repression", EMBO J 21:2672-2681

Li, H. et al. (2014), "The histone deacetylase inhibitor trichostatin A promotes totipotentcy in the male gametophyte", Plant Cell 26:195-209

Luger, K. et al. (1997), "Crystal structure of the nucleosome core particle at 2.8 a resolution", Nature 389:251-260

Menegola, E. et al. (2005), "Inhibition of histone deacetylase activity on specific embryonic tissues as a new mechanism for teratogenicity", Birth Defects Res B Dev Reprod Toxicol 74:392-398

Riggs, M.G. et al. (1977), "N-butyrate causes histone modification in HeLa and friend erythroleukaemia cells", Nature 268:462-464

Schroeder, F.A. et al. (2013), "A selective HDAC 1/2 inhibitor modulates chromatin and gene expression in brain and alters mouse behavior in two mood-related tests", PLoS One 8:e71323

Sharma, A. et al. (2016), "Epigenetic modification prevents excessive wound healing and scar formation after glaucoma filtration surgery", Invest Ophthalmol Vis Sci 57:3381-3389

Wade, M.G. et al. (2008), "Methoxyacetic acid-induced spermatocyte death is associated with histone hyperacetylation in rats", Biol Reprod 78:822-831

Yoshida, M. et al. (1990), "Potent and specific inhibition of mammalian histone deacetylase both in vivo and in vitro by trichostatin A", J Biol Chem 265:17174-17179