API

Aop: 97

AOP Title

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Short name:

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5-HTT block to population decline

Authors

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Kellie Fay

Point of Contact

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Kellie Fay

Contributors

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• Kellie Fay

Status

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This AOP was last modified on January 13, 2017 10:53

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Revision dates for related pages

Page	Revision Date/Time
Inhibition, 5-hydroxytryptamine transporter (5-HTT; SERT)	September 16, 2017 10:15
Increase, predation	December 03, 2016 16:37
Increased, muscular waves in foot	September 16, 2017 10:15
Increased, water retention in foot	December 03, 2016 16:37
Decline, Population	December 03, 2016 16:33
Increased, valve movement	December 03, 2016 16:37
Depletion, energy reserves	December 03, 2016 16:37
Increased, foot detachment	December 03, 2016 16:37
Increased, locomotion	December 03, 2016 16:37
Increased, serotonin (5-HT)	September 16, 2017 10:15
Depletion, energy reserves leads to Increase, predation	December 03, 2016 16:38
Increased, locomotion leads to Increase, predation	December 03, 2016 16:37
Increased, water retention in foot leads to Increased, valve movement	December 03, 2016 16:38
Increased, valve movement leads to Increase, predation	December 03, 2016 16:38
Inhibition, 5-hydroxytryptamine transporter (5-HTT; SERT) leads to Increased, muscular waves in foot	January 13, 2017 11:17
Inhibition, 5-hydroxytryptamine transporter (5-HTT; SERT) leads to Increased, valve movement	January 13, 2017 11:18
Increased, valve movement leads to Increased, water retention in foot	December 03, 2016 16:38
Increased, muscular waves in foot leads to Increased, foot detachment	December 03, 2016 16:37
Increased, water retention in foot leads to Increased, foot detachment	December 03, 2016 16:38
Increased, muscular waves in foot leads to Increased, locomotion	December 03, 2016 16:37
Increased, valve movement leads to Depletion, energy reserves	December 03, 2016 16:38
Increased, locomotion leads to Depletion, energy reserves	December 03, 2016 16:38
Increase, predation leads to Decline, Population	December 03, 2016 16:38
Increased, foot detachment leads to Depletion, energy reserves	December 03, 2016 16:38
Increased, serotonin (5-HT) leads to Increased, valve movement	January 17, 2017 01:02
Inhibition, 5-hydroxytryptamine transporter (5-HTT; SERT) leads to Increased, serotonin (5-HT)	December 03, 2016 16:37
Increased, serotonin (5-HT) leads to Increased, muscular waves in foot	January 30, 2017 11:17
Fluoxetine	November 29, 2016 18:42

Abstract

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Anti-depressants such as fluoxetine and sertraline inhibit the reuptake of 5-hydroxytryptamine (5-HT; serotonin)  by blocking the 5-HT transporter (5-HTT), causing an increase in serotonin levels at neural junctions. In molluscs, serotonergic neurons are responsible for the termination of the catch state of muscle contraction (Muneoka and Twarog, 1983). During catch, muscles contract and are resistant to stretch well after excitation by acetylcholine has stopped and intracellular Ca2+ stores return to normal. Importantly, this prolonged contraction is accomplished with minimal (or no) use of energy. While additional phyla may also be able to undergo catch contraction, the role of serotonin in releasing the contraction state appears to be unique to mollusks (Muneoka and Twarog, 1983). In bivalves, catch is used to maintain valve (shell) closure and the presence of serotonin promotes the transition from the passive state to active valve movement; exposure to 5-HTT inhibitors has been observed to cause increased valve movement in swan mussels (Cunha and Machado, 2001). Increased valve movement not only depletes the organism’s energy reserves,but can cause excess water retention in the foot. This water retention is speculated to cause the foot detachment observed in mussels exposed to 5-HTT inhibitors (Cunha and Machado, 2001), although terrestrial gastropods also experience foot detachement (Pavlova 2001). Mussels in the unattached state expend greater energy [54] and are more susceptibility to predation than those attached to a substrate and clumped together (Casey and Chattopadhyay, 2008).

Serotonin has also been identified as a primary neurotransmitter used to control both ciliary and pedal foot locomotion in land and aquatic mollusks (Muneoka et al 1983, Pavlova 2001 , Gosselin 1961, Longley 2010). The specific impacts on locomotion, as well as the concentration-dependence, varies among molluscs because of differing physiology and life history strategies (Fong, 2014). In various bivalves, movement alterations may take the form of increased valve movement, locomotion and mantle display, and/or increased burrowing or burrowing (inappropriately) during daylight hours. The untimely and excessive movement of molluscs due to amplified serotonergic activity could feasibly enhance their visibility and/or diminish their energy reserves, making them more susceptible to predation. Recently, prolonged, low-dose (30-300 ng/L) exposures of mussels to fluoxetine were reported to cause decreases in filter feeding rates, energy reserves and growth (Peters 2016). Foot detachment mentioned above has also been attributed to disrupted coordination of pedal muscle cells and ciliated epithelium of the foot (Pavlova 2001).

 

Background (optional)

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Instructions

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Summary of the AOP

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Stressors

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Molecular Initiating Event

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Key Events

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Adverse Outcome

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Relationships Between Two Key Events (Including MIEs and AOs)

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Network View

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Life Stage Applicability

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Taxonomic Applicability

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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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This putative AOP should be considered preliminary only.

Domain of Applicability

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Life Stage Applicability Movement-related and energy depletion are also specific to juvenile and adult mussels. Taxonomic Applicability To relate the MIE for aquatic species, an assessment of the conservation of this target across taxa was a primary step in establishing biological plausibility. Because pharmaceuticals present in aquatic environments have known activity to human targets, the human 5-HTT was used as the query protein in a SeqAPASS analysis. The results indicated substantial conservation across a broad spectrum of major animal classes for which there were data. Within the scope of potentially exposed aquatic taxa (fish, turtles, crustaceans, bivalves, etc), the high degree of conservation at the levels of the primary amino acid sequence and functional domain (solute-binding domain) suggests exposure to drugs which interact with the human transporter would likewise inhibit orthologous transporters in these taxa. Within the phylum molluska, this aop was developed with specific focus on bivalves although several key events are likely applicable to other taxa. Some key events may be unique to specific bivalve taxa due to different life history strategies.  An attempt to distinguish between relevant taxa for each key event has been made within each event page. Sex Applicability

 

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).

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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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List the bibliographic references to original papers, books or other documents used to support the AOP.

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