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Aop: 17

AOP Title

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Binding of electrophilic chemicals to SH(thiol)-group of proteins and /or to seleno-proteins during brain development leads to impairment of learning and memory

Short name:

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Oxidative stress and Developmental Neurotoxicity

Graphical Representation

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Authors

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Florianne Tschudi-Monnet, Department of Physiology, University of Lausanne, Switzerland, and Swiss Center for Applied Human Toxicology (SCAHT), Florianne.Tschudi-Monnet@unil.ch

Marie-Gabrielle Zurich Fontanellaz, Department of Physiology, University of Lausanne and SCAHT, Switzerland, mzurich@unil.ch

Carolina Nunes, Department of Physiology, University of Lausanne, Switzerland, carolina.nunes@unil.ch

Jenny Sandström, SCAHT, Switzerland, jsm.sandstrom@gmail.com

Rex FitzGerald, SCAHT, Switzerland, rex.fitzgerald@unibas.ch

Michael Aschner, Albert Einstein College of Medecine, New York, USA, michael.aschner@einstein.yu.edu

Joao Rocha, Department of Biochemistry and Molecular Biology, Federal University of Santa Maria, jbtrocha@gmail.com

 

The authors of KEs AOPwiki ID 1392 (oxidative stress), 55 (Cell injury/death), 386 (Decrease network function), of the AO (Learning and memory, impairment), and of KER 359 (decrease network function leads to impairment in learning and memory) are greatly acknowledged.

 

Point of Contact

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Florianne Tschudi-Monnet   (email point of contact)

Contributors

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  • Florianne Tschudi-Monnet
  • Marie-Gabrielle Zurich

Status

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Author status OECD status OECD project SAAOP status
Under development: Not open for comment. Do not cite Under Development 1.13 Included in OECD Work Plan


This AOP was last modified on July 06, 2018 03:10

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Revision dates for related pages

Page Revision Date/Time
Binding, Thiol/seleno-proteins involved in protection against oxidative stress July 06, 2018 03:43
Oxidative Stress May 30, 2017 14:02
Glutamate dyshomeostasis February 01, 2018 06:23
N/A, Cell injury/death September 16, 2017 10:14
N/A, Neuroinflammation June 13, 2018 08:37
Decrease of neuronal network function May 28, 2018 11:36
Impairment, Learning and memory June 13, 2018 08:45
Tissue resident cell activation August 02, 2018 02:49
Increased Pro-inflammatory mediators August 02, 2018 02:47
Binding, SH/SeH proteins involved in protection against oxidative stress leads to Oxidative Stress February 07, 2018 09:55
Oxidative Stress leads to Glutamate dyshomeostasis February 21, 2018 04:31
Glutamate dyshomeostasis leads to N/A, Cell injury/death February 20, 2018 09:21
N/A, Cell injury/death leads to N/A, Neuroinflammation June 13, 2018 09:22
N/A, Cell injury/death leads to Tissue resident cell activation August 02, 2018 03:02
N/A, Neuroinflammation leads to N/A, Cell injury/death January 26, 2018 11:23
Increased pro-inflammatory mediators leads to N/A, Cell injury/death February 12, 2018 04:58
N/A, Cell injury/death leads to Neuronal network function, Decreased February 05, 2018 12:32
Neuronal network function, Decreased leads to Impairment, Learning and memory January 26, 2018 10:32
Oxidative Stress leads to N/A, Cell injury/death February 08, 2018 10:27
Methylmercuric(II) chloride November 29, 2016 18:42
Mercuric chloride November 29, 2016 18:42
Acrylamide November 08, 2017 11:15
Acrolein August 15, 2017 09:55
thiomersal February 01, 2018 05:57

Abstract

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This Adverse Outcome Pathway (AOP) describes the linkage between binding to sulfhydryl(SH)-/seleno-proteins and impairment of learning and memory, a deficit observed in autism spectrum disorders. Binding to SH-/ seleno-proteins has been defined as the Molecular Initiating Event (MIE). As the binding to the SH-/seleno-groups directly interferes with the function of the SH-/seleno-containing proteins, which are mainly located in mitochondria or are involved in the protection against oxidative stress, the MIE directly leads to the Key Event (KE), namely oxidative stress. In turn, oxidative stress, due either to increased ROS production or decreased anti-oxidant defenses leads to either cell injury/death or to glutamate dyshomeostasis. Glutamate dyshomeostasis, in turn, leads to cell injury/death via excitotoxicity due to overactivation of NMDA receptors, as described in AOP 48. Cell injury/death will affect the network formation and function, culminating in functional deficits such as impairment in learning and memory, defined as the Adverse Outcome (AO). Neuroinflammation is triggered secondary to cell injury/death and will exacerbate the neurotoxic pathway. According to the new AOP rules, neuroinflammation is defined by the two hub KEs: Tissue resident cell activation and increased pro-inflammatory mediators, which are common to all inflammatory processes across all tissues and permit connection with all AOPs where inflammation is an inherent mechanism. As an intermediary application of these new rules, the Key Events Relationships (KERs) linking these two hub KEs with cell injury/death are represented, but the description is found under the KERs linking neuroinflammation to cell injury/death. Two reasons account for it: (i) it allows to link this AOP with the other AOPs for neurotoxicity where neuroinflammation  is included as a KE; and (ii) there is not sufficient literature for the empirical support allowing to treat the two KEs separately. The weight-of-evidence supporting the relationships between the described KEs is based mainly on effects observed after exposure to mercury (methylmercury, mercury chloride, thiomersal, mercury metal vapor), and some scarce studies on the effects of acrylamide and acrolein. Essentiality of the KEs for this AOP is moderate to strong, since blocking, preventing or attenuating an upstream KE is mitigating the downstream KE. The domain of applicability of this AOP is mainly defined for brain development, but a similar sequence of KEs can occur in adult brain leading to the same AO, also associated with neurodegenerative diseases.


Background (optional)

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This AOP was originally started in a workshop report entitled: Adverse Outcome Pathways (AOP) relevant to Neurotoxicity and published in Critical Review in Toxicol: Bal-Price, A., Crofton, K.M., Sachana, M., Shafer, T.J., Behl, M., Forsby, A., Hargreaves, A., Landesmann, B., Lein, P.J., Louisse, J., Monnet-Tschudi, F., Paini, A., Rolaki, A., Schrattenholz, A., Sunol, C., van Thriel, C., Whelan, M., Fritsche, E., 2015. Putative adverse outcome pathways relevant to neurotoxicity. Crit Rev Toxicol 45(1), 83-91.


Summary of the AOP

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Events: Molecular Initiating Events (MIE)

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Key Events (KE)

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Adverse Outcomes (AO)

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Sequence Type Event ID Title Short name
1 MIE 1487 Binding, Thiol/seleno-proteins involved in protection against oxidative stress Binding, SH/SeH proteins involved in protection against oxidative stress
2 KE 1392 Oxidative Stress Oxidative Stress
3 KE 1488 Glutamate dyshomeostasis Glutamate dyshomeostasis
4 KE 55 N/A, Cell injury/death N/A, Cell injury/death
5 KE 188 N/A, Neuroinflammation N/A, Neuroinflammation
6 KE 1492 Tissue resident cell activation Tissue resident cell activation
7 KE 1493 Increased Pro-inflammatory mediators Increased pro-inflammatory mediators
8 KE 386 Decrease of neuronal network function Neuronal network function, Decreased
9 AO 341 Impairment, Learning and memory Impairment, Learning and memory

Relationships Between Two Key Events
(Including MIEs and AOs)

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Title Adjacency Evidence Quantitative Understanding
Binding, SH/SeH proteins involved in protection against oxidative stress leads to Oxidative Stress adjacent High
Oxidative Stress leads to Glutamate dyshomeostasis adjacent Moderate
Glutamate dyshomeostasis leads to N/A, Cell injury/death adjacent High
N/A, Cell injury/death leads to N/A, Neuroinflammation adjacent Moderate
N/A, Cell injury/death leads to Tissue resident cell activation adjacent Moderate
N/A, Neuroinflammation leads to N/A, Cell injury/death adjacent Moderate
Increased pro-inflammatory mediators leads to N/A, Cell injury/death adjacent Moderate
N/A, Cell injury/death leads to Neuronal network function, Decreased adjacent High
Neuronal network function, Decreased leads to Impairment, Learning and memory adjacent High
Oxidative Stress leads to N/A, Cell injury/death non-adjacent High

Network View

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Stressors

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Name Evidence Term
Methylmercuric(II) chloride High
Mercuric chloride High
Acrylamide Moderate
Acrolein Low
thiomersal Low

Life Stage Applicability

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Life stage Evidence
During brain development

Taxonomic Applicability

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Term Scientific Term Evidence Link
rat Rattus norvegicus High NCBI
mouse Mus musculus High NCBI
human Homo sapiens Moderate NCBI

Sex Applicability

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Sex Evidence
Unspecific Moderate

Overall Assessment of the AOP

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Experimental and epidemiological evidences indicate that compared to the adult central nervous system (CNS), the developing CNS is generally more susceptible to toxicant exposure (Costa et al., 2004; Grandjean and Landrigan, 2006). Pre-natal and post-natal exposure may have long-term consequences, i.e. not detected immediately at the end of the exposure period. Such effects have been described on child development in communities with chronic low level mercury exposure (Castoldi et al., 2008; Debes et al., 2006; Grandjean et al., 2014; Lam et al., 2013).

The aim of this AOP is to capture the KEs and the KERs that occur after binding to thiol- and selenol groups of proteins, the MIE and the known molecular target of chemical initiators such as mercury, acrylamide and acrolein, and impairment in learning and memory, the AO, which is a neurotoxicity marker belonging to the OECD regulatory tool box. Data are most extensive for mercury as stressor during development; data for other stressors such as acrylamide and acrolein are much more limited. Chronic, low-dose prenatal MeHg exposure from maternal consumption of fish has been associated with endpoints of neurotoxicity in children, including poor performance on neurobehavioral tests, particularly on tests of attention, fine-motor function, language, visual-spatial abilities (e.g., drawing), and verbal memory (NRC, 2000). Some –SH- or –SeH-containing proteins have been demonstrated to be inhibited by MeHg either in vitro or in vivo, but a causal relationship has not been established between these inhibitory effects and the final pathological events (Oliveira, 2017). The analysis of the essentiality of the KEs and of the weight of evidence for the KERs supports a plausible mechanistic link between the MIE and the AO.

Domain of Applicability

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As autism spectrum disorder (ASD) is a neurodevelopmental illness, this AOP is mainly focused on the developmental period, although it cannot be excluded that long-term exposure in adult may trigger a similar cascade of KEs leading also to impairment in learning and memory, as observed in neurodegenerative diseases such as Alzheimer's disease (Mutter et al., 2010). Regarding sex differences, ASD has a higher prevalence in male (4:1) (Fombonne, 2005). While no specific sex differences have been analyzed/described for most KEs, Curtis and coworkers (2011) observed a higher level of TNF-a in hippocampus of male prairie wolf than in female, both treated for 10 weeks with inorganic mercury, in the form of HgCl2; whereas Zhang and coworkers (2013) found a higher neuroinflammatory response associated with altered social behavior in female mice offspring than in male, following gestational exposure to HgCl2. However, after developmental methylmercury exposure, long-lasting behavioral alterations were more prominent in males (Ceccatelli et al., 2013; Castoldi et al., 2008). These discrepancies may be due to sex differences in kinetics or susceptibility (Vahter et al., 2006).


Essentiality of the Key Events

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Support for Essentiality of KEs

Defining Question

Are downstream KEs and/or the AO prevented if an upstream KE is blocked ?

High (Strong)

Moderate

Low (Weak)

Direct evidence from specifically designed experimental studies illustrating essentiality for at least one of the important KEs (e.g. stop/reversibility studies, antagonism, knock out models, etc.)

Indirect evidence that sufficient modification of an expected modulating factor attenuates or augments a KE leading to increase in KE down or AO

No or contradictory experimental evidence on the essentiality of any of the KEs

MIE

Binding to SH-/seleno-proteins

HIGH

RATIONALE: Strong affinity binding (or exchange reaction) of mercury to SH- and seleno-proteins is well known. Such binding can directly inactivate the protein function or can indirectly facilitate protein denaturation. SH-containing proteins are more abundant than seleno-containing proteins. (For review: Farina et al., 2011). Carvalho et al  (2011) reported inhibition of activity of NADPH-reduced seleno-enzyme thioredoxin reductase (TrxR) by inorganic and organic mercury compounds, consistent with binding of mercury also to the active site selenol/thiol. On treatment with 5 µM selenite and NADPH, TrxR inactivated by HgCl2 displayed almost full recovery of activity. Similarly, recovery of TrxR activity and cell viability by selenite was observed in HgCl2-treated HEK 293 cells.

KE1

Oxidative stress

HIGH

RATIONALE: The deleterious consequences of oxidative stress are well accepted in various animal models. Oxygen radical scavengers, such as glutathione, catalase, selenium and cysteine blocked the methylmercury neurotoxicity in cerebral neuron culture (Park et al., 1996). In mouse primary cerebral cortical cultures, MeHg 5 μM depleted mono- and disulfide glutathione in neuronal, glial and mixed cultures. Supplementation with exogenous glutathione (glutathione monoethyl ester, GSHME) protected against MeHg-induced increased reactive oxygen species (ROS) formation and neuronal death (Rush, 2012). In brain mitochondrial-enriched fractions from adult male Swiss mice dosed with 40 mg MeHg/L drinking water for 21 days (this dose induces rotarod and open-field locomotor deficits; brain concentration ca 10 μM Hg), in vitro incubation with the antioxidant enzyme SOD, a superoxide scavenger, as well as catalase and GPx, which are peroxide detoxifying enzymes, blocked MeHg-induced increase in ROS formation (Franco, 2009). In mitochondrial-enriched fractions from whole brain minus cerebellum of adult male Swiss mice, 10-100 µM MeHg increased lipid peroxidation end-products and disrupted mitochondrial activity. Co-incubation with diphenyl diselenide (100 μM) completely prevented these effects (Meinerz, 2011).

A strong exacerbation of methylmercury neurotoxicity was observed in 3D cultures treated simultaneously with promoters of hydroxyl radical formation (10 mM copper sulphate plus 100 mM ascorbate), showing that in pro-oxidant conditions when anti-oxidant defense mechanisms are overwhelmed, low, non-cytotoxic concentrations of mercury became potently neurotoxic. This indirectly suggests that ROS production is an important mechanism in mercury neurotoxicity (Sorg et al., 1998).

KE2

Glutamate dyshomeostasis

HIGH

RATIONALE: There is an abundant literature showing that mercury interferes with glutamate uptake/transport, metabolism in astrocytes and neurons (see relative KERs) and as glutamate is the main excitatory transmitter, and is involved in memory processes, it is well accepted that perturbation of glutamate homeostasis has deleterious functional consequences. The use of microdialysis probes demonstrate that 10 or 100 mM of methylmercury induced a significant elevation of extracellular glutamate level in the frontal cortex of adult awake rats (Juarez et al., 2002). In addition, antagonists of NMDA receptors, such as MK-801 (non-competitive antagonist), D-2-amino-5-phosphonovaleric acid (APV, competitive antagonist) and 7-chlorokynurenic acid (antagonist of glycine site associated to NMDAR) blocked methylmercury-induced neurotoxicity in cerebral neuron cultures (Park et al., 1996).

KE3

Cell Injury/death, increased

HIGH

RATIONALE: Cell injury/death is a highly converging node in AOPs. Decrease in synaptic connectivity or cell loss will in turn induce perturbations in the establishment of neuronal connections and trigger inflammatory responses, which through a feedback loop can exacerbate this KE.

KE4

Neuroinflammation

 

KE4' Tissue resident cell activation

 

KE4'' Pro-inflammatory mediators, increased

MODERATE

RATIONALE: It is widely accepted in different experimental animal models that the use of minocycline, an antibiotic, which blocks microglial reactivity has protective effects, as have other interferences with any inflammatory mediators. However, we rate the essentiality of this KE as moderate (i) given the complexity of the neuroinflammatory response, having either reparative or neurodegenerative consequences, (ii) since few reported studies exist where adverse effects of mercury and acrylamide are decreased when the neuroinflammatory process is modulated (see below), and (iii) because the reported studies were not performed during the developmental exposure period (see below).

Adult rats exposed to MeHg (5mg/kg bw) for 12 consecutive days exhibited piknotic nuclei in cerebellar granule cells, what was reverted by a co-administration of CA074 an inhibitor of cathepsin released by activated microglia. These observations strongly suggest that the mercury–induced neuropathological changes are secondary to microglial activation (Sakamoto et al., 2008).

Farnesol (a sequiterpene) reduced astrogliosis (decreased GFAP) and microgliosis (decreased Iba1) and TNF-a, Il-1b and i-NOS in cortex, hippocampus and striatum of rats exposed to acrylamide (20 mg/kg bw for 4 weeks). This was associated with a marked improvement in motor coordination (Santhanasabapathy et al., 2015). (Santhanasabapathy et al., 2015).

KE5

Decreased network formation and function

HIGH

RATIONALE: Mercury interferes strongly with glutamate neurotransmission, which is an important mechanism underlying memory function (for review: Featherstone, 2010). In addition, during brain development, glutamate has also trophic effects, by stimulating BDNF production or through the activation of the different glutamate receptors. The trophic effect of glutamate receptor activation is developmental stage-dependent and may play an important role in determining the selective survival of neurons that made proper connections (Balazs, 2006).

 AO

Impairment of learning and memory

HIGH

RATIONALE: The neurocognitive domain, in particular dentate gyrus, hippocampus and cortex are particularly susceptible to the neurotoxicity of mercury in the developing brain (Morris et al., 2017; Sobolowski et al., 2011, 2013; Ceccatelli et al., 2013). Chronic, low-dose prenatal MeHg exposure from maternal consumption of fish has been associated with endpoints of neurotoxicity in children, including poor performance on neurobehavioral tests, particularly on tests of attention, fine-motor function, language, visual-spatial abilities (e.g., drawing), and verbal memory (NRC, 2000). Prenatal MeHg exposure is associated with childhood memory and learning deficits, particularly visual memory performance (Orenstein, 2017).


Evidence Assessment

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Dose-response and temporal concordance of KEs

There is no study where all KEs are measured simultaneously after exposure to several doses, impeding a dose-response and concordance analysis. In one single study (in blue in the table), three downstream KEs were measured following pre-natal exposure to methylmercury. Comparisons of all animal studies show that doses used are ranging from 0.5 - 5 mg/kg; but dose-response was seldom performed. In these studies, the time (pre-natal, post-natal, lactation,...) and duration of exposure are quite diverse and no analysis of brain mercury content was made, so it is not possible to compare doses between studies. Therefore, based on the present data, it is impossible to define whether KEs up occur at lower doses and earlier time points than KEs down.

For in vitro studies, KEs up are often measured after acute exposure to high concentrations.

The following table summarizes concentrations/doses, time, and duration of exposure for the various test systems and KEs.

MIE

KE1

KE2

KE3

KE4

KE5

AO

Binding to SH-/seleno-proteins

Oxidative stress

Glutamate dyshomeostasis

Cell injury/death

Neuroinflammation

Decreased network formation and function

Impairment in learning and memory

In vivo

In vivo

In vivo

In vivo

In vivo

In vivo

In vivo

C57BL/6J mice dosed with 5 mg MeHg/L in drinking water during gestation and lactation

Cytoplasmic and nuclear TrxR and Cytoplasmic Gpx were reduced in cerebral and cerebellar cortex of 22 days-old offspring (Ruszkiewicz, 2016)

 

Male C57BL/6NJcl mice dosed with 30 ppm methylmercury in drinking water   for 6-weeks

(Fujimura, 2017)

 

Adult male Sprague-Dawley rats exposed to methylmercury (1 mg/kg orally for 6 months) (Joshi, 2014)

 

Zebra fish brain exposed to Hg2+, MeHg 1.8 molar (measured in brain tissue), for 28 days.

(Branco, 2012)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Male C57BL/6NJcl mice exposed to methylmercury (1.5 mg/kg/day

for 6-weeks)

(Fujimura, 2017)

 

Adult male Sprague-Dawley rats exposed to methylmercury (1 mg/kg orally for 6 months) (Joshi, 2014)

 

 

Zebra fish brain exposed to Hg2+, MeHg 1.8 molar (measured in brain tissue), for 28 days.

(Branco, 2012)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Rat Young (3-4 weeks) dosed with acrylamide by gavage (5, 15, 30 mg/kg, 5 applications per week during 4 weeks)

(Tian, 2018)

 

Microdialysis probe in adult Wistar rats showed that acute exposure to methylmercury (10, 100 mM) induced an increase release of extracellular glutamate (9.8 fold at 10 mM and 2.4 fold at 100 mM). This extracellular glutamate level remained elevated at least 90 min.

(Juarez et al., 2002)

 

 

 

Rat, perinatal exposure to methylmercury (GD7-PD21, i.e. 35 days)

0.5 mg/kg bw/day in drinking water

(Roda et al., 2008)

 

 

Rat Young (3-4 weeks) exposed to acrylamide by gavage (5, 15, 30 mg/kg, 5 applications per week during 4 weeks)

(Tian, 2018)

 

 

Rat pregnant exposed to methylmercury (1.5 mg/kg orally) from GD5 till parturition                (Jacob, 2017)

 

 

 

Rat, perinatal exposure to methylmercury (GD7-PD21, i.e. 35 days)

0.5 mg/kg bw/day in drinking water

(Roda et al., 2008)

 

 

Monkeys, 6,12,18 months oral exposure

50 mg/kg bw

(Charleston et al., 1996)

 

 

 

 

 

 

 

 

 

 

 

 

 

Mice dosed during postnatal week 1-3 with subcutaneous 2-5 mg mercury chloride/kg/once per week  (Eddins et al., 2008)

Pregnant rat dosed on GD 15 with 8 mg/kg of methylmercury by gavage. Offsprings were tested at day 16, 21 and 60. (Cagiano et al., 1990)

Rat pregnant exposed to methylmercury (1.5 mg/kg orally) from GD5 till parturition               (Jacob, 2017)

 

Mice dosed during postnatal week 1-3 with subcutaneous 2-5 mg mercury chloride/kg/once per week (Eddins et al., 2008)

Pregnant rat dosed on GD 15 with 8 mg/kg of methylmercury by gavage. Offsprings were tested at day 16, 21 and 60.     (Cagiano et al., 1990)

Rat pregnant exposed to methylmercury (1.5 mg/kg orally) from GD5 till parturition                (Jacob, 2017)

Pregnant mice received 0.5 mg methylmercury/kg/day in drinking water from gestational day 7 until day 7 after delivery. Offspring behavior was monitored at 5-15 and 26-36 weeks of age.                (Onishchenko et al., 2007)

Balb mice exposed to methylmercury in diet (low dose: 1.5 mg/kg; high dose: 4.5 mg/kg) during 11 weeks (6 weeks prior mating, 3 weeks during gestation and 2 weeks post-partum). Offsprings tested at PD 15 showed an accumulation of Hg in brain (0.08 mg/kg for low dose and 0.25 mg/kg for the high dose)                (Glover et al., 2009)

In vitro

In vitro

In vitro

In vitro

In vitro

 

 

 

Mouse primary cortical cultures exposed to 5 mM of methylmercury for 24h

(Rush, 2012)

 

MeHg inhibits ex vivo rat thioredoxin reductase; IC50 0.158 μM (cerebral),

(Wagner et al., 2010)

 

 

Mouse primary cortical cultures exposed to 5 mM of methylmercury for 24h

(Rush, 2012)

 

 

Methylmercury (2-10 µM) in synaptic vesicles isolated from rat brain (with LD50 at 50 µM ).

(Porciuncula et al., 2003)

 

 

Mouse astrocytes, neurons in mono- or co-cultures exposed to methylmercury 1-50 µM for 24h                  (Morken, 2005)

 

Methylmercury (2-10 µM) in synaptic vesicles isolated from rat brain (with LD50 at 50 µM).

(Porciuncula et al., 2003

 

Mouse astrocytes, neurons in mono- or co-cultures exposed to methylmercury 1-50 µM for 24h              (Morken, 2005)

 

3D rat brain cell cultures 10 day treatment

HgCl2 10-9-10-6M

MeHgCl 10-9-3x10-7M

(Monnet-Tschudi et al., 1996; Eskes et al., 2002)

 

 

In human in vitro

In human in vitro

 

 

 

 

In human

 

Human neuroblastoma cells (SH-SY5Y)exposed to 1 µM of methylmercury

(Branco, 2017; Franco, 2009)

 

 

 

Human neuroblastoma cells (SH-SY5Y)exposed to 1 µM of methylmercury

(Branco, 2017; Franco, 2009)

 

 

 

 

 

 

Maternal peripartum hair mercury level was measured to assess prenatal mercury exposure. The concentrations of mercury was found in the range of 0.3-5.1 µg/g, similar to fish-eating population in US. Statistical analyses revealed that each ug/g increase in hair Hg was associated with a decrement in visual memory, learning and verbal memory.   (Orenstein et al., 2014)

 

 

Summary Table for Weight of evidence of KERs (Biological Plausability, Empirical support, Uncertainties)

Support for Biological Plausibility of KERs

Defining Question

Is there a mechanistic (i.e. structural or functional) relationship between KEup and KEdown consistent with established biological knowledge?

High (Strong)

Moderate

Low (Weak)

Extensive understanding of the KER based on extensive previous documentation and broad acceptance

The KER is plausible based on analogy to accept biological relationship but scientific understanding is not completely established

There is empirical support for a statistical association between KEs but the structural or functional relationship between them is not understood

MIE to KE Oxidative stress

HIGH

RATIONALE: Thiol- and selenol containing proteins, which mainly belong to the anti-oxidant protections, have a high affinity for binding soft metals such as mercury (Farina, 2011). Binding to these thiol/sulfhydryl/SH/SeH groups results in structural modifications affecting the catalytic capacity, and thereby reducing the capacity to neutralize ROS. Extensive empirical support of interfering with MIE or using anti-oxidant compounds is available. Limited conflicted data.

KE Oxidative stress to KE Glutamate (Glu) dyshomeostasis

MODERATE

RATIONALE: Due to the tight coupling of glutamate transporters with energy production, and to the important role of glutamate transporters in glutamate homeostasis, perturbations of energy metabolism such as mitochondrial dysfunction and increased production of ROS lead to glutamate dyshomeostasis  (Boron and Boulpaep, 2003). Methylmercury was shown to inhibit both the H+-ATPase activity and vesicular glutamate uptake (Porciuncula et al., 2003). As, on one hand, ROS production can interfere with glutamate uptake, and on the other hand, glutamate accumulation leads to excitotoxicity and ROS production, the exact sequence of the KER is difficult to assess. But the fact that both KEs are involved in mercury-induced neurotoxicity is broadly accepted (Farina et al., 2011; Antunes dos Santos et al., 2016; Morris et al., 2017; Kern et al., 2012).

KE Glutamate dyshomeostasis to KE Cell injury/death

HIGH

RATIONALE: Glutamate dyshomeostasis, in particular excess of glutamate in the synaptic cleft, leads to overactivation of ionotropic glutamate receptors, referred to as excitotoxicity. This, in turn, will cause cell injury/death via ROS production (see AOP 48). This KER is also inherent to the developing brain, where glutamate ionotropic receptors are expressed early in various neural cells and when NMDA receptors are expressed in neurons. There is empirical support for all three chemical initiators (mercury, acrylamide, acrolein). In addition, several experiments aiming at blocking glutamate excitotoxicity and the resulting ROS production are protective for cell injury/death. Limited conflicting data.

KE Cell injury/death to KE Neuroinflammation

MODERATE

RATIONALE: It is widely accepted that cell/neuronal injury and death lead to neuroinflammation (microglial and astrocyte reactivities) in adult brain, and in the developing brain, where neuroinflammation was observed after cell injury/death induced by excitotoxic lesions (Acarin et al., 1997; Dommergues et al., 2003). Empirical support is available for all three chemical initiators (mercury, acrylamide, acrolein).  Few experiments, showing a protection when blocking any feature of neuroinflammation have been described. There are some contradicting data showing an absence of neuroinflammatory response despite the occurrence of mercury-induced apotosis and slight behavioral alterations.

KE Neuroinflammation to KE Cell injury/death

MODERATE

RATIONALE: In vitro co-culture experiments have demonstrated that reactive glial cells (microglia and astrocytes) can kill neurons via the release of pro-inflammatory cytokines, such as TNF-a, IL-1b and IL-6 and/or ROS/RNS (Chao et al., 1995; Brown and Bal-Price, 2003; Kraft and Harry, 2011; Taetzsch and Block, 2013) and that interventions aiming at blocking these inflammatory biomolecules can rescue the neurons (Yadav et al., 2012; Brzozowski et al., 2015). Several reports showed that modulating mercury or acrylamide-induced neuroinflammation was protective for neurons. Because of the complexity of the neuroinflammatory response, that can have neuroprotective or neurodegenerative consequences depending on the duration, local environment or still unknown factors, the rating of this KER was kept as moderate. The vicious cycle between cell injury/death and neuroinflammation is well known and was described in other AOPs. Neuroinflammation could be considered as a modulating factor, but because of the numerous inhibiting experiments, it is considered as an essential KE. Some conflicting data due to the dual role of some inflammatory mediators have been reported.

KE Cell injury/death to KE Decreased network formation and function

HIGH

RATIONALE: Neuronal network formation and functional crosstalk are established via synaptogenesis. It was shown that under physiological conditions components of the apoptotic machinery in the developing brain regulate synapse formation and neuronal connectivity (Dekkers et al., 2013). The brain’s electrical activity dependence on synapse formation is critical for proper neuronal communication. Glial cells are also involved in the establishment and stabilization of the neuronal network. Extensive experimental support for the adverse effects of mercury on synaptogenesis exist, establishing a strong link between mercury-induced apoptosis and/or neuronal loss and perturbations in a number of neurotransmitter systems (Jacob, 2017; Bridges, 2017) and perturbations of functionality (Falluel-Morel, 2007; Ferraro, 2009; Teixera, 2014; Onishchenko, 2007). Limited protective experiments and conflicting data reported.

KE Decreased network formation and function to AO Impairment in learning and memory

HIGH

RATIONALE: A review on the Morris water maze (MWM), as an investigative tool of spatial learning and memory in laboratory rats pointed out that perturbed neuronal networks rather than neuronal death per se in certain regions is responsible for the impairment in MWM performance. Functional integrated neural networks that involve the coordination action of different brain regions are consequently important for spatial learning and memory performance (D'Hooge and De Deyn, 2001). Broad empirical support showing mercury-induced effects on learning and memory as consequence of network disruption (Sokolowski et al. 2013; Eddins et al., 2008; Glover et al., 2009). Similar observations were made in humans (Orenstein et al., 2014; Yorifuji et al., 2011).  Interestingly, behavioral alterations were detected long time after exposure (delayed effects). Few conflicting data have been reported, but other behavioral deficits, such as alterations in motor activity and increased anxiety suggest that systems other than hippocampus-related learning and memory are also affected.

KE oxidative stress to KE Cell injury/death

HIGH

RATIONALE: The central nervous system is especially vulnerable to free radical damage since it has a high oxygen consumption rate, an abundant lipid content and reduced levels of antioxidant enzymes (Coyle and Puttfarcken, 1993; Markesbery, 1997). The developing nervous system is particularly vulnerable to chemical insults (Grandjean & Landrigan, 2014). One reason for this higher vulnerability is the incapacity of immature neural cells to cope with oxidative stress by increasing glutathione (GSH) production (Sandström et al., 2017). Broad empirical support for mercury and acrylamide showing an association between increased ROS production and/or decreased protection against oxidative stress and apoptosis and/or necrosis (Lu et al., 2011; Sarafian et al., 1994; Allam et al., 2011; Lakshmi et al., 2012). Anti-oxidant treatments proved to be protective. Few conflicting data, except a mercury-induced upregulation of GSH level and GR activity as an adaptive mechanism following lactational exposure to methylmercury (10 mg/L in drinking water) associated with motor deficit, suggesting neuronal impairment (Franco et al., 2006).


Quantitative Understanding

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Some quantitative relationships have been described between the upstream early KEs (MIE to KE oxidative stress, Oxidative stress to Cell injury/death), although the diversity of test systems and posology (dosing/exposure amount and duration) hampers comparison between studies. It is more difficult to evaluate quantitative relationships between later downstream KEs, such as Neuroinflammation and Decreased Network Function. Neuroinflammation is a complex adaptive mechanism which is not yet completely understood; it can have neuroprotective or neurodegenerative consequences, depending on triggering signals, duration, microenvironment or other unknown influences, which may determine the outcome of the neuroinflammatory process. Decreased network function is currently difficult to quantify because quantitative technologies for mapping and understanding of brain networks (and their plasticity) are still under development.

Optimally, we would like data from a single type of test system showing that exposure to stressor, e.g. mercury, is correlated with changes in all KEs. Such models are emerging, using cells of human origin (Pamies et al., 2016; Sandström et al., 2016; Fritsche et al., 2017) or non-mammalian models, such as zebrafish (Geier et al., 2018; Padilla et al., 2018) and will allow in the future generation of quantitative data which may be used for in silico hazard prediction.


Considerations for Potential Applications of the AOP (optional)

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  • Contribution to the network of KEs/AOPs on Developmental Neurotoxicity (DNT)
  • Establishing thiol/selenol binding as a MIE to enable its use in in silico modeling for prediction and in vitro hazard identification screening
  • Generating quantitative data by measuring all KEs in a single model after repeated/long term exposure to a wide concentration range of the chemical initiators to facilitate the development of computational predictive approaches

References

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Acarin, L., B. González, B. Castellano and A. J. Castro (1997). "Quantitative analysis of microglial reaction to a cortical excitotoxic lesion in the early postnatal brain." Exp.Neurol. 147: 410-417.

Allam,  a et al. (2011) ‘Prenatal and perinatal acrylamide disrupts the development of cerebellum in rat: Biochemical and morphological studies.’, Toxicology and industrial health, 27, pp. 291–306. doi: 10.1177/0748233710386412.

Antunes Dos Santos, A., M. Appel Hort, M. Culbreth, C. Lopez-Granero, M. Farina, J. B. Rocha and M. Aschner (2016). "Methylmercury and brain development: A review of recent literature." J Trace Elem Med Biol 38: 99-107.

Balazs, R. (2006). "Trophic effect of glutamate." Curr Top Med Chem 6(10): 961-968.

Branco, V., J. Canario, J. Lu, A. Holmgren and C. Carvalho (2012). "Mercury and selenium interaction in vivo: effects on thioredoxin reductase and glutathione peroxidase." Free Radic Biol Med 52(4): 781-793.

Branco, V., L. Coppo, S. Sola, J. Lu, C. M. P. Rodrigues, A. Holmgren and C. Carvalho (2017). "Impaired cross-talk between the thioredoxin and glutathione systems is related to ASK-1 mediated apoptosis in neuronal cells exposed to mercury." Redox Biol 13: 278-287.

Bridges, K., Venables, B., Roberts, A., 2017. Effects of dietary methylmercury on the dopaminergic system of adult fathead minnows and their offspring. Environ Toxicol Chem 36, 1077-1084.

Brown, G. C. and A. Bal-Price (2003). "Inflammatory neurodegeneration mediated by nitric oxide, glutamate, and mitochondria." Mol Neurobiol 27(3): 325-355.

Brzozowski, M. J., P. Jenner and S. Rose (2015). "Inhibition of i-NOS but not n-NOS protects rat primary cell cultures against MPP(+)-induced neuronal toxicity." J Neural Transm 122(6): 779-788.

Cagiano, R., et al. (1990). "Evidence that exposure to methyl mercury during gestation induces behavioral and neurochemical changes in offspring of rats." Neurotoxicol Teratol 12(1): 23-28.

Carvalho, C.M.L., Lu, J., Zhang, X., Arnér, E.S.J., Holmgren, A. Effects of selenite and chelating agents on mammalian thioredoxin reductase inhibited by mercury: Implications for treatment of mercury poisoning (2011) FASEB Journal, 25 (1), pp. 370-381.

Castoldi, A. F., C. Johansson, N. Onishchenko, T. Coccini, E. Roda, M. Vahter, S. Ceccatelli and L. Manzo (2008). "Human developmental neurotoxicity of methylmercury: impact of variables and risk modifiers." Regul Toxicol Pharmacol 51(2): 201-214.

Castoldi, A. F., N. Onishchenko, C. Johansson, T. Coccini, E. Roda, M. Vahter, S. Ceccatelli and L. Manzo (2008). "Neurodevelopmental toxicity of methylmercury: Laboratory animal data and their contribution to human risk assessment." Regul Toxicol Pharmacol 51(2): 215-229.

Ceccatelli, S., R. Bose, K. Edoff, N. Onishchenko and S. Spulber (2013). "Long-lasting neurotoxic effects of exposure to methylmercury during development." J Intern Med 273(5): 490-497.

Charleston, J. S., R. L. Body, R. P. Bolender, N. K. Mottet, M. E. Vahter and T. M. Burbacher (1996). "Changes in the number of astrocytes and microglia in the thalamus of the monkey Macaca fascicularis following long-term subclinical methylmercury exposure." NeuroToxicology 17: 127-138.

Chao, C. C., S. Hu and P. K. Peterson (1995). "Glia, cytokines, and neurotoxicity." Crit.Rev.Neurobiol. 9: 189-205.

Coyle, J. and Puttfarcken, P. (1993) ‘Glutamate Toxicity’, Science, 262, pp. 689–95.

Curtis, J. T., A. N. Hood, Y. Chen, G. P. Cobb and D. R. Wallace (2010). "Chronic metals ingestion by prairie voles produces sex-specific deficits in social behavior: an animal model of autism." Behav Brain Res 213(1): 42-49.

Debes, F., E. Budtz-Jorgensen, P. Weihe, R. F. White and P. Grandjean (2006). "Impact of prenatal methylmercury exposure on neurobehavioral function at age 14 years." Neurotoxicol Teratol 28(5): 536-547.

Dekkers, M.P., Nikoletopoulou, V., Barde, Y.A., 2013. Cell biology in neuroscience: Death of developing neurons: new insights and implications for connectivity. J Cell Biol 203, 385-393.

D'Hooge R, De Deyn PP. (2001). Applications of the Morris water maze in the study of learning and memory. Brain Res Brain Res Rev. 36: 60-90.

Dommergues, M. A., F. Plaisant, C. Verney and P. Gressens (2003). "Early microglial activation following neonatal excitotoxic brain damage in mice: a potential target for neuroprotection." Neuroscience 121(3): 619-628.

Eddins, D., et al. (2008). "Mercury-induced cognitive impairment in metallothionein-1/2 null mice." Neurotoxicol Teratol 30(2): 88-95.

Eskes, C., P. Honegger, L. Juillerat-Jeanneret and F. Monnet-Tschudi (2002). "Microglial reaction induced by noncytotoxic methylmercury treatment leads to neuroprotection via interactions with astrocytes and IL-6 release." Glia 37(1): 43-52.

Falluel-Morel, A., Sokolowski, K., Sisti, H.M., Zhou, X., Shors, T.J., Dicicco-Bloom, E., 2007. Developmental mercury exposure elicits acute hippocampal cell death, reductions in neurogenesis, and severe learning deficits during puberty. J Neurochem 103, 1968-1981.

Farina, M., J. B. Rocha and M. Aschner (2011). "Mechanisms of methylmercury-induced neurotoxicity: evidence from experimental studies." Life Sci 89(15-16): 555-563.

Ferraro, L., Tomasini, M.C., Tanganelli, S., Mazza, R., Coluccia, A., Carratu, M.R., Gaetani, S., Cuomo, V., Antonelli, T., 2009. Developmental exposure to methylmercury elicits early cell death in the cerebral cortex and long-term memory deficits in the rat. Int J Dev Neurosci 27, 165-174.

Featherstone, D. E. (2010). "Intercellular glutamate signaling in the nervous system and beyond." ACS Chem Neurosci 1(1): 4-12.

Fombonne, E. (2005). "Epidemiology of autistic disorder and other pervasive developmental disorders." J Clin Psychiatry 66 Suppl 10: 3-8.

Franco, J. L. et al. (2006) ‘Cerebellar thiol status and motor deficit after lactational exposure to methylmercury’, Environmental Research, 102(1), pp. 22–28. doi: 10.1016/j.envres.2006.02.003.

Franco, J. L., T. Posser, P. R. Dunkley, P. W. Dickson, J. J. Mattos, R. Martins, A. C. Bainy, M. R. Marques, A. L. Dafre and M. Farina (2009). "Methylmercury neurotoxicity is associated with inhibition of the antioxidant enzyme glutathione peroxidase." Free Radic Biol Med 47(4): 449-457.

Fritsche, E., Crofton, K.M., Hernandez, A.F., Hougaard Bennekou, S., Leist, M., Bal-Price, A., Reaves, E., Wilks, M.F., Terron, A., Solecki, R., Sachana, M.,Gourmelon, A., 2017b. OECD/EFSA workshop on developmental neurotoxicity (DNT): The use of non-animal test methods for regulatory purposes. ALTEX 34, 311-315.

Fujimura, M. and F. Usuki (2017). "In situ different antioxidative systems contribute to the site-specific methylmercury neurotoxicity in mice." Toxicology 392: 55-63.

Geier, M.C., Minick, D. J., Truong, L., Tilton, S., Anderson, K.A., Tanguay, R.L., 2018. Systematic developmental neurotoxicity assessment of a representative PAH Superfund mixture using zebrafish. TAAP DNT Special Issue (Submitted).

Gilbert, J. and H. Y. Man (2017). "Fundamental Elements in Autism: From Neurogenesis and Neurite Growth to Synaptic Plasticity." Front Cell Neurosci 11: 359.

Glover, C. N., et al. (2009). "Methylmercury speciation influences brain gene expression and behavior in gestationally-exposed mice pups." Toxicol Sci 110(2): 389-400.

Grandjean, P. and P. J. Landrigan (2006). "Developmental neurotoxicity of industrial chemicals." Lancet 368(9553): 2167-2178.

Grandjean, P. and Landrigan, P. J. (2014) ‘Neurobehavioural effects of developmental toxicity’, The Lancet Neurology, 13(3), pp. 330–338. doi: 10.1016/S1474-4422(13)70278-3.

Hallmayer, J., S. Cleveland, A. Torres, J. Phillips, B. Cohen, T. Torigoe, J. Miller, A. Fedele, J. Collins, K. Smith, L. Lotspeich, L. A. Croen, S. Ozonoff, C. Lajonchere, J. K. Grether and N. Risch (2011). "Genetic heritability and shared environmental factors among twin pairs with autism." Arch Gen Psychiatry 68(11): 1095-1102.

Jacob, S., Thangarajan, S., 2017. Effect of Gestational Intake of Fisetin (3,3',4',7-Tetrahydroxyflavone) on Developmental Methyl Mercury Neurotoxicity in F1 Generation Rats. Biol Trace Elem Res 177, 297-315.

Jafari, T., N. Rostampour, A. A. Fallah and A. Hesami (2017). "The association between mercury levels and autism spectrum disorders: A systematic review and meta-analysis." J Trace Elem Med Biol 44: 289-297.

Joshi, D., M. D. Kumar, S. A. Kumar and S. Sangeeta (2014). "Reversal of methylmercury-induced oxidative stress, lipid peroxidation, and DNA damage by the treatment of N-acetyl cysteine: a protective approach." J Environ Pathol Toxicol Oncol 33(2): 167-182.

Juarez, B. I., M. L. Martinez, M. Montante, L. Dufour, E. Garcia and M. E. Jimenez-Capdeville (2002). "Methylmercury increases glutamate extracellular levels in frontal cortex of awake rats." Neurotoxicol Teratol 24(6): 767-771.

Kern, J. K., D. A. Geier, L. K. Sykes, B. E. Haley and M. R. Geier (2016). "The relationship between mercury and autism: A comprehensive review and discussion." J Trace Elem Med Biol 37: 8-24.

Kraft, A. D. and G. J. Harry (2011). "Features of microglia and neuroinflammation relevant to environmental exposure and neurotoxicity." Int J Environ Res Public Health 8(7): 2980-3018.

Lakshmi, D. et al. (2012) ‘Ameliorating effect of fish oil on acrylamide induced oxidative stress and neuronal apoptosis in cerebral cortex’, Neurochemical Research, 37(9), pp. 1859–1867. doi: 10.1007/s11064-012-0794-1.

Lam, H. S., K. M. Kwok, P. H. Chan, H. K. So, A. M. Li, P. C. Ng and T. F. Fok (2013). "Long term neurocognitive impact of low dose prenatal methylmercury exposure in Hong Kong." Environ Int 54: 59-64.

Landa, R. J. (2008). "Diagnosis of autism spectrum disorders in the first 3 years of life." Nat Clin Pract Neurol 4(3): 138-147.

Li, D., H. O. Karnath and X. Xu (2017). "Candidate Biomarkers in Children with Autism Spectrum Disorder: A Review of MRI Studies." Neurosci Bull 33(2): 219-237.

Li, H., H. Li, Y. Li, Y. Liu and Z. Zhao (2018). "Blood Mercury, Arsenic, Cadmium, and Lead in Children with Autism Spectrum Disorder." Biol Trace Elem Res 181(1): 31-37.

Loke, Y. J., A. J. Hannan and J. M. Craig (2015). "The Role of Epigenetic Change in Autism Spectrum Disorders." Front Neurol 6: 107.

Lu, T. H. et al. (2011) ‘Involvement of oxidative stress-mediated ERK1/2 and p38 activation regulated mitochondria-dependent apoptotic signals in methylmercury-induced neuronal cell injury’, Toxicology Letters. Elsevier Ireland Ltd, 204(1), pp. 71–80. doi: 10.1016/j.toxlet.2011.04.013.

Markesbery, W. R. (1997) ‘Oxidative stress hypothesis in Alzheimer’s disease’, Free Radical Biology and Medicine, 23(1), pp. 134–147. doi: 10.1016/S0891-5849(96)00629-6.

Meinerz, D. F., M. T. de Paula, B. Comparsi, M. U. Silva, A. E. Schmitz, H. C. Braga, P. S. Taube, A. L. Braga, J. B. Rocha, A. L. Dafre, M. Farina, J. L. Franco and T. Posser (2011). "Protective effects of organoselenium compounds against methylmercury-induced oxidative stress in mouse brain mitochondrial-enriched fractions." Braz J Med Biol Res 44(11): 1156-1163.

Monnet-Tschudi, F., M. G. Zurich and P. Honegger (1996). "Comparison of the developmental effects of two mercury compounds on glial cells and neurons in aggregate cultures of rat telencephalon." Brain Res 741(1-2): 52-59.

Morken, T.S., Sonnewald, U., Aschner, M., Syversen, T., 2005. Effects of methylmercury on primary brain cells in mono- and co-culture. Toxicol Sci 87, 169-175.

Morris, G., B. K. Puri, R. E. Frye and M. Maes (2017). "The Putative Role of Environmental Mercury in the Pathogenesis and Pathophysiology of Autism Spectrum Disorders and Subtypes." Mol Neurobiol.

Mostafa, G. A., G. Bjorklund, M. A. Urbina and L. Y. Al-Ayadhi (2016). "The levels of blood mercury and inflammatory-related neuropeptides in the serum are correlated in children with autism spectrum disorder." Metab Brain Dis 31(3): 593-599.

Mutter, J., J. Naumann, C. Sadaghiani, R. Schneider and H. Walach (2004). "Alzheimer disease: mercury as pathogenetic factor and apolipoprotein E as a moderator." Neuro Endocrinol Lett 25(5): 331-339.

National Research Council. 2000. Toxicological Effects of Methylmercury. Washington, DC: The National Academies Press. https://doi.org/10.17226/9899.

Oliveira, C. S., B. C. Piccoli, M. Aschner and J. B. T. Rocha (2017). "Chemical Speciation of Selenium and Mercury as Determinant of Their Neurotoxicity." Adv Neurobiol 18: 53-83.

Onishchenko, N., Tamm, C., Vahter, M., Hokfelt, T., Johnson, J.A., Johnson, D.A., Ceccatelli, S., 2007. Developmental exposure to methylmercury alters learning and induces depression-like behavior in male mice. Toxicol Sci 97, 428-437.

Orenstein, S. T., et al. (2014). "Prenatal organochlorine and methylmercury exposure and memory and learning in school-age children in communities near the New Bedford Harbor Superfund site, Massachusetts." Environ Health Perspect 122(11): 1253-1259.

Padilla, S., Culbreth, M., Deborah, L.H., Olin, J., Jarema, K., Jensen, K., Tennant, A., 2018. Reviewer Selection Summary - Screening for Developmental Neurotoxicity Using Larval Zebrafish: Assessing the Preparation and the Predictive Capability. TAAP DNT Special Issue (Submitted).

Pamies, D., P. Barreras, K. Block, G. Makri, A. Kumar, D. Wiersma, L. Smirnova, C. Zang, J. Bressler, K. M. Christian, G. Harris, G. L. Ming, C. J. Berlinicke, K. Kyro, H. Song, C. A. Pardo, T. Hartung and H. T. Hogberg (2017). "A human brain microphysiological system derived from induced pluripotent stem cells to study neurological diseases and toxicity." ALTEX 34(3): 362-376.

Park, S. T., K. T. Lim, Y. T. Chung and S. U. Kim (1996). "Methylmercury-induced neurotoxicity in cerebral neuron culture is blocked by antioxidants and NMDA receptor antagonists." NeuroToxicology 17: 37-46.

Porciuncula, L. O., J. B. Rocha, R. G. Tavares, G. Ghisleni, M. Reis and D. O. Souza (2003). "Methylmercury inhibits glutamate uptake by synaptic vesicles from rat brain." Neuroreport 14(4): 577-580.

Roda, E., T. Coccini, D. Acerbi, A. Castoldi, G. Bernocchi and L. Manzo (2008). "Cerebellum cholinergic muscarinic receptor (subtype-2 and -3) and cytoarchitecture after developmental exposure to methylmercury: an immunohistochemical study in rat." J Chem Neuroanat 35(3): 285-294.

Rush, T., X. Liu, A. B. Nowakowski, D. H. Petering and D. Lobner (2012). "Glutathione-mediated neuroprotection against methylmercury neurotoxicity in cortical culture is dependent on MRP1." Neurotoxicology 33(3): 476-481.

Ruszkiewicz, J. A., A. B. Bowman, M. Farina, J. B. T. Rocha and M. Aschner (2016). "Sex- and structure-specific differences in antioxidant responses to methylmercury during early development." Neurotoxicology 56: 118-126.

Saghazadeh, A. and N. Rezaei (2017). "Systematic review and meta-analysis links autism and toxic metals and highlights the impact of country development status: Higher blood and erythrocyte levels for mercury and lead, and higher hair antimony, cadmium, lead, and mercury." Prog Neuropsychopharmacol Biol Psychiatry 79(Pt B): 340-368.

Sakamoto, M., K. Miyamoto, Z. Wu and H. Nakanishi (2008). "Possible involvement of cathepsin B released by microglia in methylmercury-induced cerebellar pathological changes in the adult rat." Neurosci Lett 442(3): 292-296.

Sandström, J. et al. (2016) ‘Toxicology in Vitro Development and characterization of a human embryonic stem cell-derived 3D neural tissue model for neurotoxicity testing’, Tiv, pp. 1–12. doi: 10.1016/j.tiv.2016.10.001.

Santhanasabapathy, R., S. Vasudevan, K. Anupriya, R. Pabitha and G. Sudhandiran (2015). "Farnesol quells oxidative stress, reactive gliosis and inflammation during acrylamide-induced neurotoxicity: Behavioral and biochemical evidence." Neuroscience 308: 212-227.

Sarafian, T. A. et al. (1994) ‘Bcl-2 Expression Decreases Methyle Mercury-Induced Free-Radical Generation and Cel Killing in a Neural Cell Line’, Toxicol. Lett., 74(2), pp. 149–155.

Sokolowski, K., A. Falluel-Morel, X. Zhou and E. DiCicco-Bloom (2011). "Methylmercury (MeHg) elicits mitochondrial-dependent apoptosis in developing hippocampus and acts at low exposures." Neurotoxicology 32(5): 535-544.

Sokolowski, K., M. Obiorah, K. Robinson, E. McCandlish, B. Buckley and E. DiCicco-Bloom (2013). "Neural stem cell apoptosis after low-methylmercury exposures in postnatal hippocampus produce persistent cell loss and adolescent memory deficits." Dev Neurobiol 73(12): 936-949.

Sorg, O., B. Schilter, P. Honegger and F. Monnet-Tschudi (1998). "Increased Vulnerability of Neurones and Glial Cells to low Concentrations of Methylmercury in a Prooxidant Situation." Acta Neuropathol. 96: 621-627.

Taetzsch, T. and M. L. Block (2013). "Pesticides, microglial NOX2, and Parkinson's disease." J Biochem Mol Toxicol 27(2): 137-149.

Teixeira, F.B., Fernandes, R.M., Farias-Junior, P.M., Costa, N.M., Fernandes, L.M., Santana, L.N., Silva-Junior, A.F., Silva, M.C., Maia, C.S., Lima, R.R., 2014. Evaluation of the effects of chronic intoxication with inorganic mercury on memory and motor control in rats. Int J Environ Res Public Health 11, 9171-9185.

Tian, S.M., Ma, Y.X., Shi, J., Lou, T.Y., Liu, S.S., Li, G.Y., 2015. Acrylamide neurotoxicity on the cerebrum of weaning rats. Neural Regen Res 10, 938-943.

Vahter, M., A. Akesson, C. Liden, S. Ceccatelli and M. Berglund (2007). "Gender differences in the disposition and toxicity of metals." Environ Res 104(1): 85-95.

Wagner, C., Sudati, J.H., Nogueira, C.W., Rocha, J.B.T. (2010) In vivo and in vitro inhibition of mice thioredoxin reductase by methylmercury (2010) BioMetals, 23 (6), pp. 1171-1177.

Yadav, S., S. P. Gupta, G. Srivastava, P. K. Srivastava and M. P. Singh (2012). "Role of secondary mediators in caffeine-mediated neuroprotection in maneb- and paraquat-induced Parkinson's disease phenotype in the mouse." Neurochem Res 37(4): 875-884.

Yorifuji, T., et al. (2011). "Long-term exposure to methylmercury and psychiatric symptoms in residents of Minamata, Japan." Environ Int 37(5): 907-913.

Zhang, Y., V. J. Bolivar and D. A. Lawrence (2013). "Maternal exposure to mercury chloride during pregnancy and lactation affects the immunity and social behavior of offspring." Toxicol Sci 133(1): 101-111.