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Aop: 235

AOP Title

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Serotonin 1A Receptor Agonism leading to Anti-depressant Activity via K Channel Opening

Short name:

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Serotonin 1A Receptor Agonism to Anti-depressant Activity via K Channel

Authors

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Timothy E H Allen, University of Cambridge, teha2@cam.ac.uk

Point of Contact

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Timothy Allen

Contributors

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  • Timothy Allen

Status

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Author status OECD status OECD project SAAOP status
Under development: Not open for comment. Do not cite


This AOP was last modified on June 23, 2017 07:29

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Revision dates for related pages

Page Revision Date/Time
Serotonin 1A Receptor Agonism June 23, 2017 07:16
Release of G Proteins June 08, 2017 12:04
Anti-depressant Activity June 23, 2017 07:18
Opening of G protein gated inward rectifying K channels June 08, 2017 12:04
hyperpolarisation, neuron September 16, 2017 10:16
Serotonin 1A Receptor Agonism leads to Release of G Proteins June 23, 2017 07:18
Release of G Proteins leads to Opening of GIRK channels June 08, 2017 12:11
Opening of GIRK channels leads to hyperpolarisation, neuron June 08, 2017 12:12
hyperpolarisation, neuron leads to Anti-depressant Activity June 23, 2017 07:19

Abstract

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Serotonin receptors are well-understood GPCRs which trigger cellular signalling via G-proteins. The released G Proteins move to effectors in the cell to initiate their function. For the Gβγ, one of these is the K+ ion channel. The opening of the voltage-sensitive K+ channel allows K+ ions to flow out of the neuron, leading to a decrease in the concentration of K+ in the presynaptic neuron. An increase in the negative charge within the neuron is known as hyperpolarization. Hyperpolarization of a cell membrane inhibits action potentials by increasing the stimulus required to move the membrane potential to the action potential threshold. Serotonin 1A receptors are found in the brain explaining their link to emotional responses.

This putative AOP has been constructed using literature knowledge to provide qualitative information to link in silico predictions to adverse outcomes.


Background (optional)

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This optional section should be used to provide background information for AOP reviewers and users that is considered helpful in understanding the biology underlying the AOP and the motivation for its development. The background should NOT provide an overview of the AOP, its KEs or KERs, which are captured in more detail below.

Instructions

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Summary of the AOP

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Stressors

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Describes stressors known to trigger the MIE and provides evidence supporting that initiation. This will often be a list of prototypical compounds demonstrated to interact with the target molecule in the manner detailed in the MIE description to initiate a given pathway (e.g., 2,3,7,8-TCDD as a prototypical AhR agonist; 17α-ethynyl estradiol as a prototypical ER agonist). However, depending on the information available, this could also refer to chemical categories (i.e., groups of chemicals with defined structural features known to trigger the MIE). It can also include non-chemical stressors such as genetic or environmental factors. The evidence supporting the stressor will typically consist of a brief description and citation of literature showing that particular stressors can trigger the MIE.

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Molecular Initiating Event

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Title Short name
Serotonin 1A Receptor Agonism Serotonin 1A Receptor Agonism

Key Events

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Title Short name
Release of G Proteins Release of G Proteins
Opening of G protein gated inward rectifying K channels Opening of GIRK channels
hyperpolarisation, neuron hyperpolarisation, neuron

Adverse Outcome

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Title Short name
Anti-depressant Activity Anti-depressant Activity

Relationships Between Two Key Events (Including MIEs and AOs)

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Title Directness Evidence Quantitative Understanding
Serotonin 1A Receptor Agonism leads to Release of G Proteins Directly leads to Strong
Release of G Proteins leads to Opening of GIRK channels Directly leads to Strong
Opening of GIRK channels leads to hyperpolarisation, neuron Directly leads to Strong
hyperpolarisation, neuron leads to Anti-depressant Activity Indirectly leads to Strong

Network View

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Life Stage Applicability

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Is the AOP specific to certain tissues, life stages / age classes? Indicate if there are critical life stages, where exposure must occur, to results in the final adverse effect. Or specify if there are key events along the pathway which are dependent on the life stage although the AOP is known to be initiated regardless of life stage. Indicate also if the AOP is associated also with age- or sex-dependence.

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Taxonomic Applicability

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Indicate the relevant domain of applicability in terms of taxa.

Instructions

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To edit a taxonomic term on an AOP page, under “Taxonomic Applicability” click ‘Edit.’  User will be directed to a page entitled “Editing AOP Taxonomic Term” where they can edit the Evidence field using the drop down menu. Clicking ‘Update taxonomic term’ will update the Evidence field and redirect the user back to the AOP page.


Sex Applicability

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Graphical Representation

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Click to download graphical representation template

Overall Assessment of the AOP

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Below direct quotes from literature sources provide evidence for each KE and KER.

Serotonin 1A receptor agonism leading to release of G proteins

“there are five known subtypes (of 5HT receptors), all of which are highly conserved and signal through pertussis toxin (PTX)-sensitive Gi/Go proteins” PR Albert 2001

“The 5-HT1 receptors couple to Gi/Go proteins to mediate a range of actions that include classic inhibitory and cell-specific pathways” PR Albert 2001

“The heptahelical, serotonin 1A receptor couples mainly to pertussis toxin (PTX)-sensitive G proteins, such as Gi and Go” T Adayev 2003

“5-HT 1A receptors are coupled to the Gi family of G proteins, which include pertussis toxin-sensitive Gi 1, Gi 2, Gi3 and Go, and pertussis toxin-insensitive Gz proteins” JG Hensler 2003

“The  5-HT 1A   receptors  activate  G i /G o proteins” Z Chilmonczyk 2015

Release of G proteins leading to opening of G protein coupled inward rectifying K channel 

“activation of 5HT 1A receptors leads to…activation of hyperpolarizing K channels” SO Ogren 2007

“A ubiquitous pathway is…Gβγ-induced opening of K+ channels…mainly in neuroendocrine cells” PR Albert 2001

“5-HT 1A receptors are coupled via pertussis toxin-sensitive G proteins to the inhibition of adenylyl cyclase, or to the opening of potassium channels” JG Hensler 2003

“In neurons,  activation  of  the  5-HT 1A   receptor  activates  G  protein-coupled  inwardly-rectifying potassium channels (GIRKs) in the hippocampus and in the DRN, an action that profoundly hyperpolarizes neurons and decreases firing” Z Chilmonczyk 2015

Opening of G protein coupled inward rectifying K channel leading to hyperpolarization of presynapse

“Stimulation of the 5-HT1A subtype has been shown to induce neuronal hyperpolarization, most likely mediated by activation of G-protein coupled K+ channels, and consequent inhibition of neuronal activity” E Lacivita 2008

“In the dorsal raphe 5-HT 1A receptor activation opens potassium channels and inhibits cell firing” JG Hensler 2003

“The activation of 5-HT 1A receptors increases potassium conductance, thus hyperpolarizing the neuronal membrane and reducing the firing rate of serotonergic and pyramidal neurons in the cortex and hippocampus” P Celada 2004

Hyperpolarization of presynapse leading to anti-depressant activity

“These agents (5-HT 1A Agonists) comprise a class of psychoactive agents with both anxiolytic and antidepressant effects” JG Hensler 2003

“It should also be noted that the 5-HT 1A  receptor cooperates with other signal transduction systems (like the 5-HT 1B  or 5-HT 2A/2B/2C  receptors, the GABAergic and the glutaminergic systems), which also contribute to its antidepressant and/or anxiolytic activity” Z Chilmonczyk 2015

“The ability of 5-HT 1A  receptors to activate  GIRK-induced  hyperpolarizing  currents  allows  them  to  have  a  strong  effect  on  neuronal  firing  and  excitability,  a  physiological  process  that  may  be  linked  to  5-HT 1A   receptor-regulated behaviors” Z Chilmonczyk 2015

“5-HT 1A receptors are deeply involved in the mechanism of action of antidepressant drugs” P Celada 2004

Neuronal Location

“5-HT1A receptors are deeply involved in the mechanism of action of antidepressant drugs. They occur in mammalian brain in 2 different populations: on 5-HT neurons of the midbrain raphe nuclei (autoreceptors) and on neurons postsynaptic to 5-HT nerve terminals, mainly in cortico-limbic areas. In both regions, 5-HT1A receptors have a somatodendritic location. The activation of 5-HT1A receptors increases potassium conductance, thus hyperpolarizing the neuronal membrane and reducing the firing rate of serotonergic and pyramidal neurons in the cortex and hippocampus” P Celada 2004

Domain of Applicability

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The relevant domain(s) of applicability in terms of sex, life-stage, taxa, and other aspects of biological context are defined in this section. Domain of applicability is informed by the “Description” and “Taxonomic Relevance” section of each KE description and the “Description of the KER” section of each KER description. The relevant domain of applicability of the AOP as a whole will most often be defined based on the most narrowly restricted of its KEs. For example, if most of the KEs apply to either sex, but one is relevant to females only, the domain of applicability of the AOP as a whole would generally be limited to females. While much of the detail defining the domain of applicability may be found in the individual KE descriptions, the rationale for defining the relevant domain of applicability of the overall AOP should be briefly summarised on the AOP page.

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Essentiality of the Key Events

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The essentiality of various of the KEs is influential in considering confidence in an overall hypothesised AOP for potential regulatory application being secondary only to biological plausibility of KERs (Meek et al., 2014; 2014a). The defining question for determining essentiality (included in Annex 1) relates to whether or not downstream KEs and/or the AO is prevented if an upstream event is experimentally blocked. It is assessed, generally, then, on the basis of direct experimental evidence of the absence/reduction of downstream KEs when an upstream KE is blocked or diminished (e.g., in null animal models or reversibility studies). Weight of evidence for essentiality of KEs would be considered high if there is direct evidence from specifically designed experimental studies illustrating essentiality for at least one of the important key events [e.g., stop/reversibility studies, antagonism, knock out models, etc.) moderate if there is indirect 25 evidence that experimentally induced change of an expected modulating factor attenuates or augments a key event (e.g., augmentation of proliferative response (KEupstream) leading to increase in tumour formation (KEdownstream or AO)) and weak if there is no or contradictory experimental evidence of the essentiality of any of the KEs (Annex 1).

Instructions

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Weight of Evidence Summary

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This involves evaluation of the Overall AOP based on Relative Level of Confidence in the KERs, Essentiality of the KEs and Degree of Quantitative Understanding based on Annexes 1 and 2. Annex 1 (“Guidance for assessing relative level of confidence in the Overall AOP”) guides consideration of the weight of evidence or degree of confidence in the predictive relationship between pairs of KEs based on KER descriptions and support for essentiality of KEs. It is designed to facilitate assignment of categories of high, moderate or low against specific considerations for each a series of defined element based on current experience in assessing MOAs/AOPs. In addition to increasing consistency through delineation of defining questions for the elements and the nature of evidence associated with assignment to each of the categories, importantly, the objective of completion of Annex 1 is to transparently delineate the rationales for the assignment based on the specified considerations. While it is not necessary to repeat lengthy text which appears in earlier parts of the document, the entries for the rationales should explicitly express the reasoning for assignment to the categories, based on the considerations for high, moderate or low weight of evidence included in the columns for each of the relevant elements. 24 While the elements can be addressed separately for each of the KERs, the essentiality of the KEs within the AOP is considered collectively since their interdependence is often illustrated through prevention or augmentation of an earlier or later key event. Where it is not possible to experimentally assess the essentiality of the KEs within the AOP (i.e., there is no experimental model to prevent or augment the key events in the pathway), this should be noted. Identified limitations of the database to address the biological plausibility of the KERs, the essentiality of the KEs and empirical support for the KERs are influential in assigning the categories for degree of confidence (i.e., high, moderate or low). Consideration of the confidence in the overall AOP is based, then, on the extent of available experimental data on the essentiality of KEs and the collective consideration of the qualitative weight of evidence for each of the KERs, in the context of their interdependence leading to adverse effect in the overall AOP. Assessment of the overall AOP is summarized in the Network View, which represents the degree of confidence in the weight of evidence both for the rank ordered elements of essentiality of the key events and biological plausibility and empirical support for the interrelationships between KEs. The AOP-Wiki provides such a network graphic based on the information provided in the MIE, KE, AO, and KER tables. The Key Event Essentiality calls are used to determine the size of each key event node with larger sizes representing higher confidence for essentiality. The Weight of Evidence summary in the KER table is used to determine the width of the lines connecting the key events with thicker lines representing higher confidence.

Instructions

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Quantitative Considerations

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The extent of quantitative understanding of the various KERs in the overall hypothesised AOP is also critical in consideration of potential regulatory application. For some applications (e.g. doseresponse analysis in in depth risk assessment), quantitative characterisation of downstream KERs may be essential while for others, quantitative understanding of upstream KERs may be important (e.g., QSAR modelling for category formation for testing). Because evidence that contributes to quantitative understanding of the KER is generally not mutually exclusive with the empirical support for the KER, evidence that contributes to quantitative understanding should generally be considered as part of the evaluation of the weight of evidence supporting the KER (see Annex 1, footnote b). General guidance on the degree of quantitative understanding that would be characterised as weak, moderate, or strong is provided in Annex 2.

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Considerations for Potential Applications of the AOP (optional)

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At their discretion, the developer may include in this section discussion of the potential applications of an AOP to support regulatory decision-making. This may include, for example, possible utility for test guideline development or refinement, development of integrated testing and assessment approaches, development of (Q)SARs / or chemical profilers to facilitate the grouping of chemicals for subsequent read-across, screening level hazard assessments or even risk assessment. While it is challenging to foresee all potential regulatory application of AOPs and any application will ultimately lie within the purview of regulatory agencies, potential applications may be apparent as the AOP is being developed, particularly if it was initiated with a particular application in mind. This optional section is intended to provide the developer with an opportunity to suggest potential regulatory applications and describe his or her rationale. Detailing such considerations can aid the process of transforming narrative descriptions of AOPs into practical tools. In this context, it is necessarily beneficial to involve members of the regulatory risk assessment community on the development and assessment team. The Network view which is generated based on assessment of weight of evidence/degree of confidence in the hypothesized AOP taking into account the elements described in Section 7 provides a useful summary of relevant information as a basis to consider appropriate application in a regulatory context. Consideration of application needs then, to take into consideration the following rank ordered qualitative elements: Confidence in biological plausibility for each of the KERs Confidence in essentiality of the KEs Empirical support for each of the KERs and overall AOP The extent of weight of evidence/confidence in both these qualitative elements and that of the quantitative understanding for each of the KERs (e.g., is the MIE known, is quantitative understanding restricted to early or late key events) is also critical in determining appropriate application. For example, if the confidence and quantitative understanding of each KER in a hypothesised AOP are low and or low/moderate and the evidence for essentiality of KEs weak (Section 7), it might be considered as appropriate only for applications with less potential for impact (e.g., prioritisation, category formation for testing) versus those that have immediate implications potentially for risk management (e.g., in depth assessment). If confidence in quantitative understanding of late key events is high, this might be sufficient for an in depth assessment. The analysis supporting the Network view is also essential in identifying critical data gaps based on envisaged regulatory application.

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References

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Adayev T., Ray I., Sondhi R., Sobocki T., Banerjee P. (2003Biochim. Biophys. Acta-Molecular Cell Res. 1640, 8.

Albert P.R., Tiberi M. (2001Trends Endocrinol. Metab. 12, 453.

Celada P., Puig M.V., Amargós-Bosch M., Adell A., Artigas F. (2004) J. Psychiatry Neurosci. 29, 252.

Chilmonczyk Z., Bojarski A.J., Pilc, A., and Sylte, I. (2015Int. J. Mol. Sci. 16, 18474.

Hensler J.G. (2003Life Sci. 72, 1665.

Lacivita E., Leopoldo M., Berardi F., Perrone R. (2008) Curr. Top. Med. Chem. 8, 1024.

Ögren S.O., Razani H., Elvander-Tottie E., Kehr J. (2007Physiol. Behav. 92, 172.