To the extent possible under law, AOP-Wiki has waived all copyright and related or neighboring rights to KER:353

Relationship: 353

Title

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

BDNF, Reduced leads to Cell injury/death

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
Chronic binding of antagonist to N-methyl-D-aspartate receptors (NMDARs) during brain development leads to neurodegeneration with impairment in learning and memory in aging adjacent Low Florianne Tschudi-Monnet (send email) Open for citation & comment WPHA/WNT Endorsed
Chronic binding of antagonist to N-methyl-D-aspartate receptors (NMDARs) during brain development induces impairment of learning and memory abilities adjacent Low Anna Price (send email) Open for citation & comment WPHA/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

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

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

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

BDNF influences the apoptosis occurring in developing neurons through two distinct mechanisms (Bernd, 2008). mBDNF can trigger prosurvival signaling after binding to TrkB receptor through inactivation of components of the cell death machinery and also through activation of the transcription factor cAMP-response element binding protein (CREB), which drives expression of the pro-survival gene Bcl-2 (West et al., 2001). On the other hand, proBDNF binds to the p75 neurotrophin receptor (p75NTR) and activates RhoA that regulates actin cytoskeleton polymerization resulting in apoptosis (Lee et al., 2001; Miller and Kaplan, 2001; Murray and Holmes, 2011). It is proved that reduced levels of BDNF can severely interfere with the survival of neurons in different brain regions, leading to cell death (Lee et al., 2001; Miller and Kaplan, 2001; Murray and Holmes, 2011).

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

BDNF mRNA levels dramatically increase between embryonic days 11 to 13 during rat development, playing important role in neuronal differentiation and survival (reviewed in Murray and Holmes, 2011). The latter has been supported by transgenic experiments where BNDF−/− mice demonstrated a dramatic increase in cell death among developing granule cells leading to impaired development of the layers of the cerebellar cortex (Schwartz et al., 1997). BDNF has also been shown to provide neuroprotection after hypoxic-ischemic brain injury in neonates (P7) but not in older (P21) animals (Cheng et al., 1997; Han and Holtzman, 2000). The neuroprotective role of BDNF has been further supported by the observed correlation between elevated BDNF protein levels and resistance to ischemic damage in hippocampus in vivo (Kokaia et al., 1996) and K+ rich medium-induced apoptosis in vitro (Kubo et al., 1995).

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

Pb2+: A number of studies demonstrate that deletion of BDNF does not lead to significant apoptotic cell death of neurons in the developing CNS (reviewed in Dekkers et al., 2013). In an in vivo Pb2+ exposure study, where female rats received 1,500 ppm prior, during breeding and lactation shows no changes at mRNA levels of BDNF in different hippocampus section derived from their pups (Guilarte et al., 2003). Regarding Pb2+, the pre- and neonatal exposure of rats to Pb2+ (Pb2+ blood levels below 10 μg/dL) show a decreased number of hippocampus neurons but no morphological or molecular features of severe apoptosis or necrosis have been detected in tested brains (Baranowska-Bosiacka et al., 2013). In contrast to the lack of apoptotic signs, reduced levels of BDNF concentration (pg/mg protein) of BDNF in brain homogenates has been recorded in forebrain cortex (39%) and hippocampus (29%) (Baranowska-Bosiacka et al., 2013). Pregnant rats have been exposed to lead acetate (0.2% in the drinking water) after giving birth until PND 20. At PND 20, blood Pb2+ levels in pups reached at 80 μg/dl. In these animals, the gene expression in different brain regions has been assessed and demonstrated that hippocampus is most sensitive with alterations beginning at PND 12 when caspase 3 mRNA increases after Pb2+ exposure (Chao et al., 2007). However, bcl-x and BDNF mRNA in the hippocampus have been significantly increased after caspase 3 increase, suggesting that the apoptotic signal activates a compensatory response by increasing survival factors like BDNF and that the temporality suggested in this AOP may not be accurate (Chao et al., 2007).

Some of the reported “inconsistencies” may be due to the lack of sufficient details in the reporting since publications vary in what they measure. Some of the referenced studies look at BDNF transcripts, others look at BDNF protein. BDNF processing is highly complex and different mRNA transcripts are known to be implicated in different cellular function.

Several studies addressing apoptosis mainly in the developing cerebral cortex have shown that more mechanism besides neurotrophic factors may be involved. Cytokines, as well as neurotransmitters can potentially activate a number of intracellular proteins that execute cell death (Henderson, 1996; Kroemer et al., 2009), meaning that further branches to this AOP might be added in the future.

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
Time-scale
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 survival and antiapoptotic role of BDNF has been investigated not only in rodents but also in developing chicken neurons (Hallbook et al., 1995; Frade et al., 1997; Reinprecht et al., 1998). In invertebrates, only recently a protein with possible neurotrophic role has been identified but its influence and function in neuronal cell death of developing neurons has not been investigated yet (Zhu et al., 2008).

References

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

Baranowska-Bosiacka, Strużyńska L, Gutowska I, Machalińska A, Kolasa A, Kłos P, Czapski GA, Kurzawski M, Prokopowicz A, Marchlewicz M, Safranow K, Machaliński B, Wiszniewska B, Chlubek D. (2013) Perinatal exposure to lead induces morphological, ultrastructural and molecular alterations in the hippocampus. Toxicology. 303: 187-200.

Bernd P. (2008) The role of neurotrophins during early development. Gene Expr. 14: 241-250.

Chao SL, Moss JM, Harry GJ. (2007) Lead-induced Alterations of Apoptosis and Neurotrophic Factor mRNA in the Developing Rat Cortex, Hippocampus, and Cerebellum. J Biochem Mol Toxicol. 21: 265-272.

Cheng Y, Gidday JM, Yan Q et al (1997) Marked age-dependent neuroprotection by brain-derived neurotrophic factor against neonatal hypoxic-ischemic brain injury. Ann Neurol 41: 521-529.

Dekkers MP, Nikoletopoulou V, Barde YA. (2013) Cell biology in neuroscience: Death of developing neurons: new insights and implications for connectivity. J Cell Biol. 203: 385-393.

Dikranian K, Ishimaru MJ, Tenkova T, Labruyere J, Qin YQ, Ikonomidou C, Olney JW. (2001) Apoptosis in the in vivo mammalian forebrain. Neurobiol Dis. 8: 359-379.

Dribben WH, Creeley CE, Farber N. (2011) Low-level lead exposure triggers neuronal apoptosis in the developing mouse brain. Neurotoxicol Teratol. 33: 473-480.

Farber NB, Creeley CE, Olney JW. (2010) Alcohol-induced neuroapoptosis in the fetal macaque brain. Neurobiol Dis. 40:200-206.

Frade JM, Bovolenta P, Martínez-Morales JR, Arribas A, Barbas JA, Rodríguez-Tébar A. (1997) Control of early cell death by BDNF in the chick retina. Development. 124: 3313-3320.

Guilarte TR, Toscano CD, McGlothan JL, Weaver SA. (2003) Environmental enrichment reverses cognitive and molecular deficits induced by developmental lead exposure. Ann Neurol. 53: 50-56.

Hallbook F, Bäckström A, Kullander K, Kylberg A, Williams R, Ebendal T (1995). Neurotrophins and their receptors in chicken neuronal development. Int J Dev Biol. 39: 855-868.

Han BH, Holtzman DM (2000) BDNF protects the neonatal brain from hypoxic-ischemic injury in vivo via the ERK pathway. J Neurosci. 20: 5775-57811.

Hansen HH, Briem T, Dzietko M, Sifringer M, Voss A, Rzeski W, Zdzisinska B, Thor F, Heumann R, Stepulak A, Bittigau P, Ikonomidou C. (2004). Mechanisms leading to disseminated apoptosis following NMDA receptor blockade in the developing rat brain. Neurobiol Dis. 16: 440-453.

He L, Poblenz AT, Medrano CJ, Fox DA. Lead and calcium produce rod photoreceptor cell apoptosis by opening the mitochondrial permeability transition pore. J Biol Chem. 2000 Apr 21;275(16):12175-84.

Henderson CE. (1996). Programmed cell death in the developing nervous system. Neuron 17: 579-585.

Huang F, Schneider JS. (2004) Effects of lead exposure on proliferation and differentiation of neural stem cells derived from different regions of embryonic rat brain. Neurotoxicology 25: 1001–1012.

Ikonomidou C, Bosch F, Miksa M, Bittigau P, Vöckler J, Dikranian K, Tenkova TI, Stefovska V, Turski L, Olney JW. (1999) Blockade of NMDA receptors and apoptotic neurodegeneration in the developing brain. Science 283: 70-74.

Kokaia Z, Nawa H, Uchino H, Elmer E, Kokaia M, Carnahan J, Smith ML, Siesjo BK & Lindvall O. (1996) Regional brain-derived neurotrophic factor mRNA and protein levels following transient forebrain ischemia in the rat. Brain Res Mol Brain Res. 38: 139-144.

Kroemer G, Galluzzi L, Vandenabeele P, Abrams J, Alnemri ES, Baehrecke EH, Blagosklonny MV, El-Deiry WS., Golstein P, Green DR, Hengartner M, Knight RA, Kumar S, Lipton SA, Malorni W, Nuñez G, Peter ME, Tschopp J, Yuan J, Piacentini M, Zhivotovsky B, Melino G. Nomenclature Committee on Cell Death (2009). Classification of cell death: recommendations of the Nomenclature Committee on Cell Death 2009. Cell Death Differ. 16: 3-11.

Kubo T, Nonomura T, Enokido Y, Hatanaka H. (1995) Brain-derived neurotrophic factor (BDNF) can prevent apoptosis of rat cerebellar granule neurons in culture. Brain Res Dev Brain Res. 85: 249-258.

Lee R, Kermani P, Teng KK, Hempstead BL. (2001) Regulation of cell survival by secreted proneurotrophins. Science 294: 1945-1948.

Liu J, Han D, Li Y, Zheng L, Gu C, Piao Z, Au WW, Xu X, Huo X. (2010) Lead affects apoptosis and related gene XIAP and Smac expression in the hippocampus of developing rats. Neurochem Res. 35: 473-479.

Miller FD, Kaplan DR. (2001) Neurotrophin signalling pathways regulating neuronal apoptosis. Cell Mol Life Sci. 58: 1045-1053.

Murray PS, Holmes PV. (2011) An Overview of Brain-Derived Neurotrophic Factor and Implications for Excitotoxic Vulnerability in the Hippocampus nternational. J Pept. Volume 2011 (2011), Article ID 654085, 12 pages.

Neal AP, Stansfield KH, Worley PF, Thompson RE, Guilarte TR. (2010) Lead exposure during synaptogenesis alters vesicular proteins and impairs vesicular release: Potential role of NMDA receptor-dependent BDNF signaling. Toxicol Sci. 116: 249-263.

Niu Y, Zhang R, Cheng Y, Sun X, Tian J. (2002) Effect of lead acetate on the apoptosis and the expression of bcl-2 and bax genes in rat brain cells. Zhonghua Yu Fang Yi Xue Za Zhi. 36: 30-33.

Oberto A, Marks N, Evans HL, Guidotti A. (1996) Lead (Pb + 2) promotes apoptosis in newborn rat cerebellar neurons: pathological implications. J Pharmacol Exp Ther. 279: 435-442.

Reinprecht K, Hutter-Paier B, Crailsheim K, Windisch M. (1998) Influence of BDNF and FCS on viability and programmed cell death (PCD) of developing cortical chicken neurons in vitro. J Neural Transm Suppl. 53: 373-384.

Schwartz PM, Borghesani PR, Levy RL, Pomeroy SL, Segal RA. (1997) Abnormal cerebellar development and foliation in BDNF(-/-) mice reveals a role for neurotrophins in CNS patterning. Neuron 19: 269-281.

Sharifi AM, Baniasadi S, Jorjani M, Rahimi F, Bakhshayesh M. (2002) Investigation of acute lead poisoning on apoptosis in rat hippocampus in vivo. Neurosci Lett. 329: 45-48.

Sharifi AM, Mousavi SH. (2008) Studying the effects of lead on DNA fragmentation and proapoptotic bax and antiapoptotic bcl-2 protein expression in PC12 cells. Toxicol. Mech. Methods 18: 75-79.

Stansfield KH, Pilsner JR, Lu Q, Wright RO, Guilarte TR. (2012) Dysregulation of BDNF-TrkB signaling in developing hippocampal neurons by Pb(2+): implications for an environmental basis of neurodevelopmental disorders. Toxicol Sci. 127: 277-295.

West AE, Chen WG, Dalva MB, Dolmetsch RE, Kornhauser JM, Shaywitz AJ, Takasu MA, Tao X, Greenberg ME. (2001) Calcium regulation of neuronal gene expression. Proc Natl Acad Sci U S A. 98: 11024-11031.

Xu J, Ji LD, Xu LH. (2006) Lead-induced apoptosis in PC 12 cells: involvement of p53, Bcl-2 family and caspase-3. Toxicol Lett. 166: 160-167.

Yoon WJ, Won SJ, Ryu BR, Gwag BJ. (2003). Blockade of ionotropic glutamate receptors produces neuronal apoptosis through the Bax- cytochrome C-caspase pathway: the causative role of Ca2+deficiency. J Neurochem. 85: 525-533.

Zhu B, Pennack JA, McQuilton P, Forero MG, Mizuguchi K, Sutcliffe B, Gu CJ, Fenton JC, Hidalgo A. (2008) Drosophila neurotrophins reveal a common mechanism for nervous system formation. PLoS Biol. 18;6(11):e284.