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Relationship: 312


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

T4 in serum, Decreased leads to T4 in neuronal tissue, Decreased

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
Inhibition of Thyroperoxidase and Subsequent Adverse Neurodevelopmental Outcomes in Mammals adjacent Moderate Moderate Evgeniia Kazymova (send email) Open for citation & comment TFHA/WNT Endorsed
XX Inhibition of Sodium Iodide Symporter and Subsequent Adverse Neurodevelopmental Outcomes in Mammals adjacent Moderate Low Evgeniia Kazymova (send email) Not under active development
Sodium Iodide Symporter (NIS) Inhibition and Subsequent Adverse Neurodevelopmental Outcomes in Mammals adjacent High Low Evgeniia Kazymova (send email) Under Development: Contributions and Comments Welcome
Inhibition of Na+/I- symporter (NIS) leads to learning and memory impairment adjacent Moderate Low Arthur Author (send email) Open for citation & comment TFHA/WNT Endorsed

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
rat Rattus norvegicus Moderate NCBI
mouse Mus musculus Moderate NCBI
human Homo sapiens 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
Male Moderate
Female Moderate

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
During brain development High
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

In mammals, thyroxine (T4) in brain tissue is derived almost entirely from the circulating pool of T4 in blood. Transfer of free T4 (and to a lesser extent, T3) from serum binding proteins (thyroid binding globulin (TBG), transthyretin (TTR) and albumin; see McLean et al., 2017, for a recent review) into the brain requires transport across the blood brain barrier (BBB) and /or indirect transport from the cerebral spinal fluid (CSF) into the brain through the blood-CSF-barrier.  The blood vessels in rodents and humans expresses the main T4 transporter, MCT8, (Roberts et al. 2008), as does the choroid plexus which also expresses TTR and secretes the protein into the CSF (Alshehri et al. 2015).

T4 entering the brain through the BBB is taken up into astrocytes via cell membrane iodothyronine transporters (e.g., organic anion-transporting polypeptides OATP), monocarboxylate transporter 8 (MCT8) (Visser et al., 2011).  In astrocytes, T4 is then deiodinated by Type II deiodinase to triiodothyronine (T3) (St Germain and Galton, 1997), which is then transported via other iodothyronine transporters (MCT8) into neurons (Visser et al., 2011). While some circulating T3 may be taken up into brain tissue directly from blood (Dratman et al., 1991), the majority of neuronal T3 comes from deiodination of T4 in astrocytes. Decreases in circulating T4 will eventually result in decreased brain T3 tissue concentrations. It is also known that Type II deiodinase can be up-regulated in response to decreased T4 concentrations to maintain tissue concentrations of T3 (Pedraza et al., 2007; Lavado-Autric et al., 2013; Morse et al., 1986), except in tanycytes of the paraventricular nucleus (Fekete and Lechan, 2014).

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

The weight of evidence linking reductions in circulating serum TH and reduced brain concentrations of TH is moderate. Many studies support this basic linkage. However, there are compensatory mechanisms (e.g., upregulation of deiodinases, transporters) that may alter the relationship between hormones in the periphery and hormone concentrations in the brain. There is limited information available on the quantitative relationship between circulating levels of TH, these compensatory processes, and neuronal T4 concentrations, especially during development. Furthermore, in certain conditions, such as iodine deficiency, the decreases in circulating hormone might have greater impacts on tissue levels of TH (see for instance, Escobar del Rey, et al., 1989).

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

The biological relationship between these two KEs is strong as it is well accepted dogma within the scientific community. There is no doubt that decreased circulating T4 leads to declines in tissue concentrations of T4 and T3 in a variety of tissues, including brain. However, compensatory mechanisms (e.g., increased expression of Type 2 deiodinase) may differ during different lifestages and across different tissues, especially in different brain regions.  Similarly, the degree to which serum TH must drop to overwhelm these compensatory responses has not been established.

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

The fact that decreased serum TH results in lower brain TH concentrations is well accepted.  However, the ability of the developing brain to compensate for insuffiencies in serum TH has not been well studied.  Limited data is available that demonstrates that changes in local deiodination in the developing brain can compensate for chemical-induced alterations in TH concentrations (e.g., Calvo et al., 1990; Morse et al., 1996; Sharlin et al., 2010). And, there are likely different quantitative relationships between these two KEs depending on the compensatory ability based on both developmental stage and specific brain region (Sharlin et al., 2010). For these reasons, the empirical support for this linkage is rated as moderate

The role of cellular transporters represents an additional uncertainly. In addition, future work on cellular transport mechanisms and deiodinase activity is likley to inform addition of new KEs and KERs between serum and brain T4.

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

While it is well established that decreased in serum TH levels result in decreased brain TH concentrations, particularly fetal brain concentrations, a major gap is the lack of empirical data that allow direct quantification of this relationship (Hassan et al., 2018). Recently, serum TH and brain TH were measured in fetal cortex and postnatal day 14 offspring following graded degrees of hypothyroidism induced by PTU (O’Shaughnessy et al., 2018). Results showed that brain levels TH levels at both ages were quantitatively related to serum T4 levels. Additional dose-response information is necessary to confirm these findings, and standardization of analysis for the measurements in these distinct matrices is crucial to allow comparisons to be made between independent experiments.

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 majority of the information on this KER comes from in vivo studies with rodents (mainly MCT8 knock-out mice and thyroidectomized rats) and histopathological analyses of human brain tissues derived from patients affected by AHDS (Allan-Herndon-Dudley syndrome). The evoluationary conservation of the transport of TH from circulation to the developing brain suggests, with some uncertainty, that this KER is also applicable to other mammalian species.


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

Alshehri B, D'Souza DG, Lee JY, Petratos S, Richardson SJ.  The diversity of mechanisms influenced by transthyretin in neurobiology: development, disease and endocrine disruption. J Neuroendocrinol. 2015 May;27(5):303- 23.

Bárez-López S, Obregon MJ, Martínez-de-Mena R, Bernal J, Guadaño-Ferraz A, Morte B.  Effect of Triiodothyroacetic Acid Treatment in Mct8 Deficiency: A Word of Caution. Thyroid. 2016 May;26(5):618-26.

Bastian TW, Anderson JA, Fretham SJ, Prohaska JR, Georgieff MK, Anderson GW (2012), Fetal and neonatal iron deficiency reduces thyroid hormone-responsive gene mRNA levels in the neonatal rat hippocampus and cerebral cortex. Endocrinology 153:5668-5680.

Bastian TW, Prohaska JR, Georgieff MK, Anderson GW (2014) Fetal and neonatal iron deficiency exacerbates mild thyroid hormone insufficiency effects on male thyroid hormone levels and brain thyroid hormone-responsive gene expression. Endocrinology 55:1157-1167.

Broedel, O., Eravci, M., Fuxius, S., Smolarz, T., Jeitner, A., Grau, H., Stoltenburg-Didinger, G., Plueckhan, H., Meinhold, H., and Baumgartner, A. (2003). Effects of hyper and hypothyroidism on thyroid hormone concentrations in regions of the rat brain. Am. J. Physiol. Endocrinol. Metab. 285:E470–480.

Calvo, R., Obregon, M.J., Escobar del Rey, F., and Morreale de Escobar, G. (1992). The rat placenta and the transfer of thyroid hormones from the mother to the fetus. Effects of maternal thyroid status. Endocrinology 131:357–365.

Calvo R, Obregon MJ, Ruiz de Ona C, Escobar del Rey F, Morreale de Escobar G 1990 Congenital hypothyroidism, as studied in rats. Crucial role of maternal thyroxine but not of 3,5,3’-triiodothyronine in the protection of the fetal brain. J Clin Invest 86:889–899.

Denver, RJ. (1998). The molecular basis of thyroid hormone-dependent central nervous system remodeling during amphibian metamorphosis. Comparative Biochemistry and Physiology Part C: Pharmacology, Toxicology and Endocrinology, 119:219-228.

Dratman MB, Crutchfield FL, Schoenhoff MB. Transport of iodothyronines from bloodstream to brain: contributions by blood:brain and choroid plexus:cerebrospinal fluid barriers.  Brain Res. 1991 Jul 19;554(1-2):229-36.

Gilbert ME, Hedge JM, Valentin-Blasini L, Blount BC, Kannan K, Tietge J, Zoeller RT, Crofton KM, Jarrett JM, Fisher JW (2013) An animal model of marginal iodine deficiency during development: the thyroid axis and neurodevelopmental outcome. Toxicol Sci 132:177-195.

Escobar del Rey F, Ruiz de Oña C, Bernal J, Obregón MJ, Morreale de Escobar G. Generalized deficiency of 3,5,3'-triiodo-L-thyronine (T3) in tissues from rats on a low iodine intake, despite normal circulating T3 levels. Acta Endocrinol (Copenh). 1989 Apr;120(4):490-8.

Escobar-Morreale HF, Obregón MJ, Escobar del Rey F, Morreale de Escobar G. Replacement therapy for hypothyroidism with thyroxine alone does not ensure euthyroidism in all tissues, as studied in thyroidectomized rats. J Clin Invest. 1995 Dec;96(6):2828-38.

Escobar-Morreale HF1, Obregón MJ, Hernandez A, Escobar del Rey F, Morreale de Escobar G. Regulation of iodothyronine deiodinase activity as studied in thyroidectomized rats infused with thyroxine or triiodothyronine. Endocrinology. 1997 Jun;138(6):2559-68.

Fekete C, Lechan RM.  Central regulation of hypothalamic-pituitary-thyroid axis under physiological and pathophysiological conditions.  Endocr Rev. 2014 Apr;35(2):159-94

Lavado-Autric R, Calvo RM, de Mena RM, de Escobar GM, Obregon MJ. Deiodinase activities in thyroids and tissues of iodine-deficient female rats. Endocrinology. 2013 Jan;154(1):529-36.

Mayerl S, Müller J, Bauer R, Richert S, Kassmann CM, Darras VM, Buder K, Boelen A, Visser TJ, Heuer H. Transporters MCT8 and OATP1C1 maintain murine brain thyroid hormone homeostasis.  J Clin Invest. 2014 May;124(5):1987-99.

McLean TR, Rank MM, Smooker PM, Richardson SJ.  Evolution of thyroid hormone distributor proteins. Mol Cell Endocrinol. 2017 Feb 27. pii: S0303-7207(17)30151-X. doi: 10.1016/j.mce.2017.02.038. [Epub ahead of print]

Morreale de Escobar, G., Obregon, M.J., and Escobar del Ray, F. (1987). Fetal and maternal thyroid hormones. Hormone Res. 26:12–27.

Morreale de Escobar, G., Calvo, R., Obregon, M.J., and Escobar del Rey, F. (1990). Contribution of maternal thyroxine to fetal thyroxine pools in normal rats near term. Endocrinology 126:2765–2767.

Morse DC, Wehler EK, Wesseling W, Koeman JH, Brouwer A. Alterations in rat brain thyroid hormone status following pre- and postnatal exposure to polychlorinated biphenyls (Aroclor 1254). Toxicol Appl Pharmacol. 1996 Feb;136(2):269-79

Obregon MJ, Ruiz de Ona C, Calvo R, Escobar del Rey F, Morreale de Escobar G 1991 Outer ring iodothyronine deiodinases and thyroid hormone economy: Responses to iodine deficiency in the rat fetus and neonate. Endocrinology 129:2663–2673.

Oppenheimer, J.H. (1983). The nuclear Receptor-triiodothyronine complex: Relationship to thyroid hormone distribution, metabolism, and biological action. In: Molecular Basis of Thyroid Hormone Action, eds. J.H. Oppenheimer and H.H. Samuels, pp. 1–35. New York: Academic Press.

O'Shaughnessy KL, Wood, C, Ford RL, Kosian, PA, Hotchkiss, MG, Degitz SJ, Gilbert ME. Thyroid hormone disruption in the fetal and neonatal rat: Predictive hormone measures and bioindicators of hormone action in the developing cortex. Toxicol Sci. 2018 Aug 6. doi: 10.1093/toxsci/kfy190.  [Epub ahead of print]

Pedraza PE, Obregon MJ, Escobar-Morreale HF, del Rey FE, de Escobar GM (2006) Mechanisms of adaptation to iodine deficiency in rats: thyroid status is tissue specific. Its relevance for man. Endocrinology 147:2098-2108.

Porterfield, S.P. and Hendrich, C.E. (1992). Tissue iodothyronine levels in fetuses of control and hypothyroid rats at 13 and 16 days gestation. Endocrinology 131:195–200.

Porterfield, S.P. and Hendrich, C.E. (1993). The role of thyroid hormones in prenatal neonatal neurological development-current perspectives. Endocrine Rev. 14:94–106.

Power DM, Llewellyn L, Faustino M, Nowell MA, Björnsson BT, Einarsdottir IE, Canario AV, Sweeney GE. (2001). Thyroid hormones in growth and development of fish. Comp Biochem Physiol C Toxicol Pharmacol. Dec;130(4):447-59.

Roberts LM, Woodford K, Zhou M, Black DS, Haggerty JE, Tate EH, Grindstaff KK, Mengesha W, Raman C, Zerangue N.  Expression of the thyroid hormone transporters monocarboxylate transporter-8 (SLC16A2) and organic ion transporter-14 (SLCO1C1) at the blood-brain barrier. Endocrinology. 2008 Dec;149(12):6251-61.

Seed J, Carney EW, Corley RA, Crofton KM, DeSesso JM, Foster PM, Kavlock R, Kimmel G, Klaunig J, Meek ME, Preston RJ, Slikker W Jr, Tabacova S, Williams GM, Wiltse J, Zoeller RT, Fenner-Crisp P, Patton DE.  Overview: Using mode of action and life stage information to evaluate the human relevance of animal toxicity data. Crit Rev Toxicol. 2005 35:664-72.

Sharlin DS, Gilbert ME, Taylor MA, Ferguson DC, Zoeller RT. (2010).The nature of the compensatory response to low thyroid hormone in the developing brain. J Neuroendocrinol.  Mar;22(3):153-65.

St. Germain, D.L. and Galton, V.A. (1997). The deiodinase family of selenoproteins. Thyroid 7:655–668.

Taylor MA, Swant J, Wagner JJ, Fisher JW, Ferguson DC (2008) Lower thyroid compensatory reserve of rat pups after maternal hypothyroidism: correlation of thyroid, hepatic, and cerebrocortical biomarkers with hippocampal neurophysiology. Endocrinology 149:3521-3530.

Van Herck SL, Geysens S, Delbaere J, Darras VM. (2013). Regulators of thyroid hormone availability and action in embryonic chicken brain development. Gen Comp Endocrinol.190:96-104.

Visser WE, Friesema EC, Visser TJ.  Minireview: thyroid hormone transporters: the knowns and the unknowns.  Mol Endocrinol. 2011 Jan;25(1):1-14.