the master synaptic regulator: activity regulated
TRANSCRIPT
City University of New York (CUNY) City University of New York (CUNY)
CUNY Academic Works CUNY Academic Works
Dissertations, Theses, and Capstone Projects CUNY Graduate Center
2-2019
The Master Synaptic Regulator: Activity Regulated Cytoskeleton The Master Synaptic Regulator: Activity Regulated Cytoskeleton
Associated Protein, Arc, in Normal Aging and Diseases with Associated Protein, Arc, in Normal Aging and Diseases with
Cognitive Impairment Cognitive Impairment
Amber Khan The Graduate Center, City University of New York
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The Master Synaptic Regulator: Activity Regulated
Cytoskeleton Associated Protein, Arc, in Normal Aging and
Diseases with Cognitive impairment.
by
Amber Khan
A dissertation submitted to the Graduate Faculty in Biology in partial fulfillment of the
requirements for the degree of Doctor of Philosophy, The City University of New York
2019
ii
© 2018
AMBER KHAN
All Rights Reserved
iii
This manuscript has been read and accepted for the Graduate Faculty in Biology in satisfaction
of the dissertation requirement for the degree of Doctor of Philosophy.
___________________ ______________________________________________
Date Chair of Examining Committee
Dr. Hoau-Yan Wang, CUNY School of Medicine
___________________ ______________________________________________
Date Executive Officer
Dr. Cathy Savage-Dunn
______________________________________________
Dr. Itzhak Mano, CUNY School of Medicine
______________________________________________
Dr. John H. Martin, CUNY School of Medicine
_______________________________________________
Dr. Jonathan Levitt, City College
________________________________________________
Dr. Robert Nagele,
Rowan University School of Osteopathic Medicine
______________________________________________
Supervising Committee
The City University of New York
iv
Abstract:
Master Synaptic Regulator: Activity Regulated Cytoskeleton
Associated Protein, Arc in Normal Aging and Diseases with
Cognitive impairment.
By: Amber Khan
Advisor: Dr. Hoau-Yan Wang
Alzheimer’s disease (AD) is a progressive neurodegenerative disease with complex
underlying pathogenic mechanisms. Epidemiological studies have forecasted that in the next 3
decades, the number of AD cases will rise to epidemic proportions with enormous medical,
emotional and financial burdens impacting individuals affected and society. Among many risk
factors for AD, advancing age is clearly essential and necessary. Revelation of molecular changes
in synaptic activities leading to the prodromal, mild cognitive impairment (MCI) stage may help
illuminate the course of pathogenic progression and its cause-effect relationship with various
targets thereby enabling target-driven disease-modifying therapeutic agents for AD.
Activity-regulated cytoskeleton-associated (Arc) protein is a prominent regulator of
synaptic plasticity and homeostasis that localizes exclusively in postsynaptic regions of the
excitatory systems in the brain. Arc is involved in AMPA receptor endocytosis in LTD and late
phase LTP consolidation at the dendritic fields. NMDA receptor activation increases Arc
expression to facilitate synaptic activities and promote remodeling of dendritic spines. AD
pathologies can be found in brains of cognitively normal elderly individuals. Together with the
fact that synaptic activity is altered during aging and markedly deteriorated in AD, we therefore
v
hypothesize that altered basal and activity-driven Arc expression contribute to deleterious synaptic
changes at old age and in AD. The altered Arc contributes to synaptopathy in AD through its
interactions at the postsynaptic density and dendritic spine. However, the mechanisms responsible
for Arc alteration during normal aging and in AD are currently not clear.
In these studies, we systemically investigate changes in Arc protein levels under basal and
stimulation conditions in hippocampal formation (HF) and prefrontal cortex (PFC) from wild-type
(WT) and 3x transgenic (Tg) AD mice at varying ages. The results derived from WT and 3xTg
AD mice show Arc protein levels increase along with advancing age and in AD under non-
stimulated basal condition. More importantly, Arc expression is increased in response to NMDAR
and insulin receptor stimulation and these stimulation-elicited Arc increases are dramatically
attenuated in AD. We present evidence to show Arc is regulated by phosphorylation on the serine
and tyrosine residues and this post-translational modification process is driven by receptor
stimulation. Arc is also sensitive to oxidative damage as indicated by elevation of nitrated Arc
levels in aged WT and 3 x Tg AD mice. We reveal that Arc is associated with PSD-95/NMDAR
and filamin A (FLNA) signaling pathways. Further, we identify protein kinase C (PKC) and Src
in the PSD-95/NMDAR complexes as well as JAK2 and PAK1 in the FLNA signaling cascade as
the kinases that phosphorylate Arc following activation of the NMDARs and insulin receptor,
respectively. Most importantly, we observed a reduced association of Arc with NMDARs
accompanied by increased Arc linkage to FLNA during normal aging and in AD.
The relevancy of the findings in mouse AD models is affirmed by examining the
postmortem human HF from age-, gender- and postmortem interval-matched sets of cognitively
normal controls, subjects with mild cognitive impairment (MCI) with or without AD pathology
(MCI-AD and MCI-SNAP, respectively) and AD cases. Arc protein levels are higher in MCI-
vi
SNAP and AD under the non-stimulated conditions. Similar to the observation made in mouse
brain, Arc expression is increased by exposure to NMDA/glycine (NMDAR), PNU282987 (α7
nicotinic receptor), insulin (IR) and BDNF (TrkB) in human HF slices from non-demented
controls. The receptor stimulation induced Arc expression is universally and markedly reduced in
MCI-AD and AD as well as in MCI-SNAP although with lesser extent. Oxidative damage to Arc
is evidenced in MCI-AD and AD but not in MCI-SNAP. Arc is predominantly associated with
PSD-95/NMDARs in control and MCI-SNAP cases but linked to FLNA in MCI-AD and AD.
In summary, the data presented indicate for the first time that phosphorylation of Arc
mediated by kinases in its associated NMDAR and FLNA is a regulatory mechanism for Arc under
physiological conditions. More importantly, defected activity-driven Arc expression is observed
prevalently in diseases with cognitive impairment. The reduced activity-induced Arc expression
can occur with or without elevated Arc protein levels and the altered connections with PSD-
95/NMDAR and FLNA signaling complexes. The data derived from this study indicate that
reduced activity-driven Arc expression and altered Arc connections occur early in the course of
synaptopathy and are integral parts of AD pathologies. Our data suggest that restoring activity-
driven Arc expression may rescue synaptic dysfunction and thereby improve cognitive function in
diseases with cognitive impairments such as Alzheimer’s disease.
vii
Table of Contents:
Abstract: ....................................................................................................................................... iv
Introduction: ................................................................................................................................. 1
a) Cognitive ability varies with age and disease: .................................................................................... 1
I) Specific pathological changes correlate with cognitive decline. .................................................... 2
b) Mild Cognitive Impairment (MCI) is clinically and pathologically a unique, early stage of
dementia. .................................................................................................................................................. 3
c) Alzheimer’s disease is the most common cause of dementia in the global population. .................... 5
I) Alzheimer’s disease is a public health epidemic. ............................................................................ 6
II) Diseases of cognitive impairment are clinically assessed using a diagnostic screening tool. ...... 7
III) Disease pathogenesis is measured and monitored using various detection methods. ................ 8
d) Alzheimer’s Disease has a complex, multifactorial pathogenesis. .................................................. 10
I) Amyloid Beta Plaque Pathology and the Amyloid Hypothesis. .................................................... 11
II) Tau Hyperphosphorylation and the Tau Hypothesis .................................................................. 15
e) Early Neurodegeneration and dysfunction in Alzheimer’s Disease is characterized by synaptic
changes and loss of synapses. ................................................................................................................ 17
f) The post-synaptic density of glutamatergic, excitatory synapses is a major site for long term
potentiation and depression. .................................................................................................................. 19
I) LTP and LTD at glutamatergic excitatory synapses depend on NMDA and AMPA receptor
activity. ................................................................................................................................................ 19
II) Scaffolding Proteins PSD-95 and FLNA function as binding partners and regulate receptors
in key signaling pathways involved in memory formation. .............................................................. 21
III) Immediate Early Genes and their protein products function as a rapid response mechanism to
cellular stimuli. ................................................................................................................................... 23
g) Activity Regulated Cytoskeleton Associated Protein (Arc) ............................................................... 24
I) Synaptic Functions of Arc mediate AMPAR Regulation in LTP/LTD. ....................................... 25
II) Nuclear functions of Arc .............................................................................................................. 28
III) Regulatory mechanisms of Arc: posttranslational modifications ............................................. 29
h) Arc expression and function is altered in disease ............................................................................ 31
I) Cognitive disorders, aging and AD ................................................................................................ 32
viii
Experimental Procedures ........................................................................................................... 35
Human Postmortem Hippocampal formation sections......................................................................... 35
Description of case cohorts .................................................................................................................... 35
3xTg AD Mouse Model Tissue Preservation and Selection ................................................................. 38
a) Ex-Vivo Stimulation ....................................................................................................................... 39
b) Immunoprecipitation and co-immunoprecipitation ...................................................................... 40
c) Western Blot Procedure ................................................................................................................. 41
d) Statistical Evaluation ..................................................................................................................... 43
Results .......................................................................................................................................... 43
1) Isolation of Arc by immunoprecipitation with anti-Arc is complete and specific. ................... 43
2) Assessing Arc Expression .................................................................................................................. 46
2a) Basal and Activity-driven Arc expression is decreased during normal aging and in AD. ........ 46
2b) Assessment of the overall Arc protein levels. .............................................................................. 49
2c) Altered basal and activity-driven Arc expression in Human postmortem HF from well-
matched subjects with Alzheimer’s disease (AD), mild cognitive impairment (MCI) and cognitively
normal control subjects. ..................................................................................................................... 51
3) Arc is modified post-translationally by phosphorylation. ............................................................. 54
3a) Phosphorylation of Arc at serine (pS) and tyrosine (pY) is responsive to receptor stimulation.
............................................................................................................................................................ 58
3b) Arc phosphorylation states are altered during normal aging and in AD pathogenesis. ........... 58
4) Nitration of Arc indicates oxidative stress occurs during AD pathogenesis modifies Arc. ........ 64
6) Regulation of Arc by Phosphorylation is mediated by PKC/Src and JAK2/PAK1 associated
respectively with NMDARs and FLNA ............................................................................................... 73
Conclusions .................................................................................................................................. 77
References .................................................................................................................................... 86
ix
Table of Figures
Figure 1: Time course of Cognitive Decline ....................................................................................1
Figure 2: Comparison of current criteria for mild cognitive impairment (MCI) .............................4
Figure 3: Suggested criteria for the likelihood that MCI is due to AD............................................5
Figure 4: Projected Populations of AD ............................................................................................6
Figure 5: A hypothetical temporal model of Alzheimer's disease biomarkers ................................9
Figure 6: APP processing occurs via either the amyloidogenic or canonical pathway .................12
Figure 7: Tau hyperphosphorylation and Tau pathology. ..............................................................15
Figure 8: The sequence of major pathogenic events leading to AD proposed by the amyloid
cascade hypothesis .........................................................................................................................17
Figure 9: Mechanisms of LTP and LTD in the PSD .....................................................................20
Figure 10: Proposed Molecular Organization of the PSD .............................................................22
Figure 11: Graphic Representation of Arc domain structure ........................................................25
Figure 12: Arc has multiple effects through its actions in the synapse and nucleus .....................27
Figure 13: Sites of Post-translational modifications on Arc ..........................................................29
Figure 14: Anti-Arc immunoprecipitation in the HF and PFC is complete and specific ..............46
Figure 15: Activity dependent Arc expression changes as a function of age and disease .............49
Figure 16: Basal Arc Expression levels in aging and AD .............................................................51
Figure 17: Arc expression is altered in cognitively impaired human HF ......................................53
Figure 18: Arc immunoprecipites contain serine- and tyrosine- but not threonine-phosphorylated
Arc in the HF and PFC...................................................................................................................56
x
Figure 19: Immunoprecipitation with antibodies against the indicated phosphoepitopes in the HF
and PFC from WT mice .................................................................................................................57
Figure 20: Basal and activity dependent Arc phosphorylation expression are altered in HF of
aged WT and 3xTg AD mice .........................................................................................................60
Figure 21: Basal and activity dependent Arc phosphorylation expression are altered in PFC of
aged WT and 3xTg AD mice. ........................................................................................................61
Figure 22: Human HF shows disease dependent changes in Arc phosphorylation. ......................62
Figure 23: a-c: Arc does not show phosphorylation on the Threonine epitope .............................63
Figure 24: Arc is modified by nitration in the HF and PFC of WT and 3xTg AD animals ..........65
Figure 25: Increased nitrated Arc in the postmortem human HF from patients with cognitive
impairments....................................................................................................................................66
Figure 26: Altered Arc linkages with signaling complexes in aged and 3xTg AD mice ..............70
Figure 27: Altered Arc linkages with signaling complexes in aged and 3xTg AD mice in HF ....71
Figure 28: Altered Arc linkages with signaling complexes in aged and 3xTg AD mice in PFC ..72
Figure 29: Identification of critical kinases responsible for pS-Arc and pY-Arc in HF................75
Figure 30: Revelation of the kinases that mediate Arc phosphorylation in PFC ...........................76
Figure 31: Proposed mechanism of Arc function in physiological and pathogenic conditions .....84
1
Introduction:
a) Cognitive ability varies with age and disease:
Basic cognitive functions are broadly defined as processes to attain knowledge of, and
interact with, the environment. These abilities are a dynamic skill set that include memory (explicit
versus implicit), intelligence (crystallized versus fluid), and executive function, and are some of
the primary functions that decline with age.1 These abilities can also be influenced by other factors
such as genetics and lifestyle choices which also affect the brain throughout an individual’s
lifetime. When comparing the effects of neurodegenerative disease on cognitive abilities, a greater
functional deficit is apparent compared to the healthy age-matched population (figure 1).1-3
Figure 1: Time course of Cognitive Decline. Progression from normal aging to Alzheimer’s disease or other
types of dementia. Cognitive function diminishes with advancing age. The onset and progression of dementia
correlates with the severity of the loss of function progressing.
Source: http://www.mind.uci.edu/dementia/mild-cognitive-impairment/
2
I) Specific pathological changes correlate with cognitive decline.
Several pathological changes have been connected to age-related cognitive decline.
Region-specific changes in grey matter volume begin after the age of twenty and continue to
progress in an age-dependent manner1. Such changes have been attributed to several potential
causes, including subtle changes in the synaptic structure of the brain especially in the
hippocampus and prefrontal cortex. As studies in mice have shown, animals undergo age-
dependent changes in α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPA-
R) and N-methyl-D-aspartate receptor (NMDA-R) density and assembly’s in the postsynaptic
density (PSD)4. In Sprague-Dawley rats, the abundance of NMDA-Rs is lower in animals at 25
months of age and older compared to very young rats (< 3 months)5,6. Such changes in
compositions and/or density of these crucial synaptic receptors can conceivably negatively affect
the neuronal function due to altered signaling downstream of NMDA-Rs and AMPA-Rs.
Significantly, these receptor changes also compromise synaptic transmission and ultimately,
diminish long term potentiation induction and maintenance5-7. Such changes contribute to overall
grey matter volume loss through decreased synaptic density and reduction in neuron size.
Changes in volume and function of white matter in various brain regions has also been
reported in non-demented, aged subjects and patients with cognitive impairment8. Significant age-
related decreases in white matter volume was noted in regions important for their communication
with the hippocampus.8,10-11 In support, anterior changes in white matter, and loss of integrity in
white matter tracts of the corpus callosum have been reported using diffuse tensor imaging (DTI).12
The pathological changes and consequent functional impairments seen in aging are accelerated in
diseases of cognitive impairment.
3
b) Mild Cognitive Impairment (MCI) is clinically and pathologically a unique,
early stage of dementia.
Mild cognitive impairment (MCI) is a clinical classification that was originally identified
and described by Petersen and colleagues in 1999.12 It marks an important phase of disease
progression that is generally considered a transitional state between normal cognitive function and
dementia.12,13 Individuals with MCI have been shown to convert to Alzheimer’s disease at a rate
of 5-20% per year. By comparison, the incidence rate of Alzheimer’s disease in the general
population of age-matched individuals is approximately 1-2%13. One of the original goals of
identifying this prodromal stage of cognitive impairment was to establish a window for early
therapeutic intervention in dementia patients that were specific to Alzheimer’s disease dementia13-
15. In the nearly two decades since its original conception, the definition of MCI has evolved and
expanded to include unique subtypes, thereby complicating the clinical and pathological definition
of MCI14. Importantly, these subtypes include heterogeneous patient population each with distinct
pathogenic pathways and the potential to progress to a variety of dementias.
MCI is classified into distinct subtypes based on a patient’s clinical presentation (figure 2).
A subject will be classified as either amnestic MCI (aMCI) or non-amnestic MCI (naMCI) based
on neuropsychological tests of cognitive function13,15,16. If an individual exhibits memory deficits,
they will be given a diagnosis of aMCI. If a subject shows reduced cognitive function in another
domain, (e.g. language, executive function) but does not test poorly in memory, they are classified
as naMCI 14. Individuals can be classified as having impairments in a single cognitive domain or
multiple domains.
4
In 2011, the National Institute on Aging-Alzheimer’s Association (NIA-AA) proposed
criteria to subdivide individuals into two distinct categories based on pathology using imaging and
fluid biomarkers: MCI-AD (MCI caused by Alzheimer’s disease) and MCI-sNAP (MCI suspected
non-Alzheimer disease pathology)17. Although MCI-sNAP subjects exhibit neurodegeneration
similar to AD subjects, they do not exhibit elevated levels of Aβ deposition as present in AD
brains16. In contrast, MCI-AD subjects have accelerated neuronal injury, degeneration, and
biomarker profiles that more closely parallel the levels seen in AD16 (figure 3).
Figure 2: Comparison of current criteria for mild cognitive impairment (MCI).
Source: Modified from Petersen RC, Caracciolo B, Brayne C, Gauthier S, Jelic V, Fratiglioni L. Mild
cognitive impairment: a concept in evolution. Journal of internal medicine. 275(3):214-228.
doi:10.1111/joim.12190. (2014)
5
Importantly, both amnestic and non-amnestic patients can be classified into either MCI-AD or
MCI-sNAP groups; this indicates that a clinical diagnosis does not necessarily predict the
pathology underlying the disease. Further, although the rates of conversion to AD are higher in
MCI-AD patients, both MCI-sNAP and MCI-AD individuals can progress to AD. This
underscores the idea that AD has a complex pathogenic mechanism.
c) Alzheimer’s disease is the most common cause of dementia in the global
population.
Dementia is a syndrome that affects memory, language and other cognitive skills severely
enough to impair an individual’s everyday functioning. This is a result of damage to neurons in
specific regions of the brain. Alzheimer’s disease is the leading cause of dementia, but it is not
the only one20. Several other types of dementia are commonly seen in elderly patients, including:
Figure 3: Suggested criteria for the likelihood that MCI is due to AD. The presence of Aβ42 can be detected
with PET and CSF analysis. The presence of neuronal injury can be detected using MRI. Low levels of Aβ42 and
elevated tau in the CSF with tau/ Aβ42 ratio ≥ 0.39 indicates progression to AD, as does a low ratio of Aβ42 to tau
in the CSF
Source: Modified from Petersen, R. C. Mild cognitive impairment. New England Journal of Medicine, 364(23),
2227-2234. (2011).
6
vascular dementia, Lewy body dementia, and Fronto-temporal dementia among others19. Many
individuals who are diagnosed with one form of dementia may have pathology and symptoms of
a secondary form, resulting in wide varieties of mixed dementia20-22. This mixed pathology
complicates research models as well as the successful diagnosis and treatment of patients.
Regardless of this complication, the overwhelming data indicates that a majority of dementia
patients are diagnosed with AD as the primary form of dementia20. Further, this number is
projected to increase in the coming decades.
I) Alzheimer’s disease is a public health epidemic.
Increasingly larger percentages of the global population are living longer than previous
generations21. The total number of people over 60 years old is estimated to become 22% of the
world’s population by 2050 with the number of people afflicted with some form of dementia
doubling every 20 years21,23 (figure 4).
Figure 4: Projected Populations of AD. The projected number of people age 65 years and older (total
and by age group) in the U.S. population with Alzheimer's disease, 2010 to 2050.
Source: Alzheimer's Association. 2016 Alzheimer's disease facts and figures. Alzheimer's &
Dementia, 12(4), 459-509. (2016).
7
Due to this increase in the cognitively impaired patient population, the incidence rate of
AD is expected to increase proportionally. It is estimated that by the year 2050, 13.8 million
individuals in the United States of America alone will have AD dementia24. The estimated cost
of care for AD patients is expected to approach $221 billion nationally21. These conservative
financial estimates underscore the urgent and significant need for early and reliable diagnosis,
effective treatment and management of the economic burden as the AD patient population
continues to grow.
II) Diseases of cognitive impairment are clinically assessed using a diagnostic
screening tool.
The Folstein Mini Mental State Exam (MMSE) is a widely used neuropsychological
assessment tool in the Western hemisphere. It is used by physicians and other clinical
professionals to evaluate changes in an individual’s cognitive function over time25. The DSM
recommends that physicians administer this test to patients who are 65 years and older and
indicate/exhibit a possibility of dementia26. The MMSE is a paper based 11 item exam with a
maximum possible score of 30. Subjects answer questions on different topics ranging from
comprehension, memory recall and attention. A score in the range of 24-30 is considered normal
while a lower score indicates some degree of cognitive impairment27. One of the major limitations
of this screening tool is it exhibits a ceiling effect. That is, individuals who fall into the pre-
dementia phase of cognitive decline will not be effectively diagnosed as at risk using this exam
because they will fall into the upper “normal” range27.
The Montreal Cognitive Assessment (MoCA), another frequently used assessment tool
that addresses the MMSE’s issue of poor sensitivity, especially in the earlier stages of cognitive
8
impairment29. Similar in format to the MMSE, the MCoA is an 11 item, 30 point test. However,
it includes more challenging questions that focus on higher level functioning such as visuospatial
processing, language and executive functions.29 This more thorough interrogation of executive
function may be crucial in discerning MCI from healthy cognitive function as well as from normal
cognitive aging.27-30 However, in some cases, MCI patients do not exhibit clinical symptoms.
Further, a varying degree of subjectivity can make clinical diagnoses difficult. Therefore, other
methods are used to measure pathological changes for detection and diagnosis of diseases.
III) Disease pathogenesis is measured and monitored using various detection
methods.
MCI was designated as a unique phase of cognitive impairment by Petersen and colleagues
1999, with the intention of providing an opportunity for early therapeutic intervention12. Indeed,
changes in specific pathological traits associated with AD begin during progressive mild cognitive
impairment (MCI) or earlier. To monitor disease progression as well as determine disease
prognosis, researchers and clinicians use a combination of different neuroimaging and fluid
biomarker methods (figure 5). In addition, neuropsychological testing to assess clinical symptoms
is conducted to correlate clinical and pathological symptoms in subjects. Neuroimaging
techniques, which are less invasive than CSF biomarkers, include structural MRI, functional MRI,
and PET imaging using the (11)C-labelled Pittsburgh Compound-B to determine the levels of
amyloid deposits. The most commonly used fluid biomarkers are cerebrospinal fluid (CSF) levels
of Aβ42, total tau (t-tau) and phosphorylated tau (p-tau)31.
9
AD causes region-specific cortical thinning and atrophy, specifically, in the hippocampus
and cortex32. To measure these changes, structural MRI is used to assess volumetric changes and
loss in a progressive, longitudinal manner. Similarly, functional changes are known to occur as a
result of impaired synaptic function. This results in decreased metabolic activity which is assessed
using functional MRI32. Amyloid beta deposition in the brain is assessed using PET imaging31.
The Pittsburgh Compound used in PET imaging to detect levels of Aβ deposition has been used in
the largest number of patients to date31,32.
Figure 5: A hypothetical temporal model of Alzheimer's disease biomarkers. The threshold for the first detection
of biomarkers associated with pathophysiological changes is indicated by the black horizontal line. The area below
the detection threshold is the zone in which abnormal changes lie. In this model, tau pathology can precede Aβ
deposition in time, but only in the early stages of the disease. Aβ deposition occurs independently and rises above the
biomarker detection threshold (purple and red arrows). This accelerates tauopathy, and CSF tau then rises above the
detection threshold (light blue arrow). Later, changes in PET and MRI (dark blue arrow) rise above the detection
threshold. Finally, cognitive impairment becomes evident (green arrow), with a wide range of cognitive responses that
depend on the individual's risk profile (light green‐filled area). Note that while CSF Aβ42 alteration is plotted as a
biomarker (purple), this represents a decrease in CSF Aβ42 levels and is a surrogate for an increase in parenchymal
Aβ42 and changes in other Aβ peptides in the brain tissue. Aβ, amyloid β‐protein; FDG, fluorodeoxyglucose; MCI,
mild cognitive impairment.
Source: Selkoe, D. J. and Hardy, J. EMBO Mol Med. 8, 595-608 (2016)
10
Since CSF is in direct contact with neurons that house and eventually expel the hallmark
pathological features of AD, the levels of Aβ and tau (p/total) in CSF functions as a barometer of
neuronal damage and neuronal AD pathology. Several studies have shown that CSF Aβ42 levels
in patients with AD were reduced compared to age-matched cognitively normal controls31-33. This
is due to amyloid peptide aggregation and plaque formation in the brain, resulting in a decreased
Aβ42availability in the CSF. Hence, there is an inverse relationship between CSF Aβ42 in AD and
disease progression. Total tau levels in CSF have been shown to be three times higher in AD
patients compared to age-matched controls. However, because there are many neurodegenerative
diseases with tauopathies, this measure of AD disease progression is nonspecific33. In contrast,
phosphorylated-tau (p-tau) protein is an extremely specific biomarker of AD. CSF p-tau levels in
non-AD diseases, including tauopathies, are normal compared to AD.
d) Alzheimer’s Disease has a complex, multifactorial pathogenesis.
AD, an extremely complex chronic neurodegenerative disease that is pathologically
characterized by progressive neuronal death, accumulation of Aβ42-rich amyloid plaques and p-
Tau containing neurofibrillary tangles 29. While it has been consistently shown that AD patients
have markedly deteriorated cognitive functioning beyond their age, there is no clear relationship
between the progression of pathological changes and clinical symptoms. The conclusive AD
diagnosis can only be made with pathological markers in the postmortem condition that supports
clinical symptoms36. The etiology and pathogenesis can vary between subjects due to a variety of
factors and can be attributed to changes in a several different signaling pathways that have been
11
shown to alter the course of disease progression, which further complicates attempts to
characterize the disease.
Advancing age is an essential and necessary risk factor for AD37. One well characterized
risk factor that occurs in aging and neurodegeneration is oxidative stress. Due to an imbalance in
redox states, reactive oxygen or nitration species accumulate along with increasing age to hasten
AD pathogenic progression38-40. Another important signaling pathway that is related to AD
disease progression is insulin signaling. Insulin receptors are widely distributed throughout the
brain41. Increasing age is reported to be associated with a decrease in central insulin receptor
signaling (i.e. IR, IRS-1, Akt) termed insulin resistance42. Comparing to age-matched non-
demented subjects, insulin resistance in the brain is more severe 42. The dysfunctional insulin and
insulin-like growth factor (IGF-1) signaling pathways are integral components of the complex
AD pathogenic mechanisms. Dysfunction of the APP processing pathway, which results in
amyloid beta plaque generation, is central and critical in AD pathogenesis. This pathology, in
addition to the dysfunctions in the insulin signaling pathway, increased oxidative stress, and
immune dysfunction collectively contribute to disease progression.
I) Amyloid Beta Plaque Pathology and the Amyloid Hypothesis.
The amyloid hypothesis proposes that a dyshomeostasis in Amyloid-beta (Aβ) protein is
a key pathogenic event in AD43. This imbalance is caused by a combination of increased Aβ
production and/or a failure in Aβ clearance mechanisms.
12
Amyloid beta peptides are created through the cleavage of the amyloid precursor protein
(APP) in a sequential series of enzymatic cleavages. APP is a member of an evolutionarily
conserved protein family that includes APP, APLP1 and APLP244. It is sequentially cleaved in
either the canonical pathway or the amyloidogenic pathway to generate P3 or Aβ peptides (figure
Figure 6: APP processing occurs via either the Amyloidogenic or canonical pathway. APP initially undergoes
cleavage at either α - or β-secretase sites to release sAPPα or sAPPβ, respectively. This allows γ-secretase to
cleave the membrane-embedded fragments . Proteolysis by γ-secretase promotes the extracellular release of the
amyloidogenic Aβ fragments () in the toxic pathway whereas proteolysis by γ-secretase generates an N-terminally
truncated and non-toxic 3 kDa P3 peptide in the non-toxic pathway.
Source: Fraering, P. C. Structural and Functional Determinants of γ-secretase, an intramembrane protease
implicated in Alzheimer's disease. Current genomics, 8(8), 531-549. (2007).
13
6). In the non-toxic, canonical pathway, α-secretase makes an initial cleavage which generates
secreted APP α (sAPPα), a large extracellular fragment that is released into the extracellular
medium, and the C-terminal fragment (CTF) that remains in the membrane. The α-CTF is cleaved
subsequently by the γ-secretase complex, a group of enzymes which includes presenilin 1 or 2
(PS1 and PS2) together with other enzymes. Significantly, the cleavage site of APP by α-secretase
lies within the Aβ sequence and thus prohibits Aβ peptide production. In contrast, cleavage of
APP by β-secretase mediates the first step in the amyloidogenic pathway. This causes the release
of a large sAPPβ fragment into the extracellular medium and a longer β-CTF that remains in the
membrane. The β-CTF fragment is then cleaved by γ-secretase. This successive cleavage of β-
CTF leads to the generation of Aβ peptides with 38-43 amino acids that are secreted into
extracellular space43.
Most Aβ peptides are 40 residues in length (Aβ40), however, a small percentage contain
42 residues (Aβ42). Increased extracellular accumulation of toxic Aβ species, particularly Aβ42,
promotes the formation of Aβ oligomers. As the amount of both monomeric and oligomeric forms
of Aβ overwhelm the brains capacity to remove and degrade the toxic Aβ species, they form
extracellular plaques. Ultimately, through activation of various different cellular mechanisms
including inflammatory cascades, the neurons will become damaged and die.
Since its original proposal several decades ago, this amyloid hypothesis has been met with
great skepticism due to its inability to fully explain the pathology seen in AD and failure to
reconcile discrepancies seen between cognitive impairment and degree of Aβ deposits since
cognitive deficits correlate better with soluble Aβ levels45-48. An alternative amyloid pathogenic
theory that indicates soluble Aβ monomers, dimers or small oligomers bind the α7 nicotinic
acetylcholine receptors (α7nAChRs) with high affinity to elicit toxic signaling. The Aβ-
14
α7nAChR complexes are then internalized and accumulated, resulting in impaired transport and
ultimately lysis of the affected neurons to form plaques49-55. Although it remains incomplete, the
amyloid theory provides a broad framework to guide drug development and to gain insights into
the complex mechanisms of AD. Critically, the amyloid hypothesis is able to explain the fact that
all AD patients experience progressive Aβ plaque buildup in brain areas that are relevant to
memory and cognition, and that mutations of APP accelerate Aβ production56. Experimental
studies have shown that increased Aβ deposition may be the critical initiating step in the AD
pathogenesis cascade57-59.
15
II) Tau Hyperphosphorylation and the Tau Hypothesis
One of the other key pathogenic mechanisms in AD is tau hyperphosphorylation. Tau
belongs to the family of microtubule-associated proteins60. There are six isoforms of tau proteins
primarily found within neurons in the adult brain, created through alternative splicing60. The
primary function of tau is to monitor the assembly and stabilization of microtubules. Several
neurodegenerative diseases, collectively termed tauopathies, are linked to tau pathology. Among
Figure 7: Tau hyperphosphorylation and Tau pathology. In AD pathology, tau phosphorylation events occur
in a sequential series of steps.
Source: Johnson, G. V., & Stoothoff, W. H. (2004). Tau phosphorylation in neuronal cell function and
dysfunction. Journal of cell science, 117(24), 5721-5729.
16
them are frontotemporal dementia (FTD), Pick’s disease, progressive supranuclear palsy (PSP),
traumatic brain injury (TBI) and AD. Specifically, in these conditions, tau pathology is due to
dysregulated tau phosphorylation resulting in hyperphosphorylated tau61.
Hyperphosphorylated tau loses affinity for microtubules and dissociates from them. The
increased pool of free hyperphosphorylated tau after dissociation from microtubules is likely an
important first step to its aggregation in AD. Untethered from microtubules, hyperphosphorylated
tau twists together to form paired helical filaments (PHFs) that are found abundantly in
neurofibrillary tangles (figure 7). In a toxic gain of function, hyperphosphorylated tau also
actively disrupts microtubules and inhibits their assembly and even sequesters functional tau and
other microtubule-associated proteins. Hyperphosphorylation also changes tau’s localization
from axon-predominant to include dendrites, neuronal cell bodies and presynaptic areas, leading
to wide spread synaptic, dendritic and axonal dysfunction. In cultured cells, abnormal tau is
shown to convert normal tau into abnormal tau. This conversion mechanism has been
hypothesized to be a mechanism by which tau aggregates in particular neuron populations
propagate to other brain areas62-64. This spread of tau is correlated with disease progression
according to Braak staging, and is considered a later development in AD pathogenic disease
progression relative to Aβ plaque deposition36.
17
e) Early Neurodegeneration and dysfunction in Alzheimer’s Disease is
characterized by synaptic changes and loss of synapses. One of the earliest pathological manifestations of AD, is a dysfunction and loss of synapses
(figure 8). This change at the synapses, which has been investigated for several years and is
recognized as a significant transformation in the progression toward disease, begins decades before
Figure 8: The sequence of major pathogenic events leading to AD proposed by the amyloid
cascade hypothesis. Highlighted in red is a critical early event: compromise in synaptic function due to
Aβ oligomers, which may directly injure the synapses.
Source: Modified from Selkoe, D. J. and Hardy, J. EMBO Mol Med. 2016;8:595-608
18
the presentation of clinical symptoms of AD and continues throughout the course of the disease.
It has been well studied and established that dendritic spine morphology is modifiable and dictated
by functional changes occurring at the dendritic spines65. That is, the spine morphology change
according to the coordinated responses of the scaffold proteins, receptors and channels located at
these synapses to environmental signals. In the absence of any neurodegenerative disease, brain
changes in older adults, are largely due to decreases in synaptic density, rather than frank cell
death66,67. However, age-related synaptic loss is accelerated in brains of MCI and AD. In a
quantitative study measuring the density of synapses in the frontal and temporal cortices using
biopsied tissue, a significant decrease (25-36%) in the abundance of synapses was found in patients
who had been given a diagnosis of AD in the past 2-4 years. Additionally, there is an estimated of
15-35% synapse loss per cortical neuron in individuals with AD68. In another quantitative
assessment study using postmortem hippocampus from AD subjects, there was a 44% synapse
loss. In comparison, the age matched MCI group showed a statistically non-significant 13%
synapse loss. These were synaptic losses compared to the age matched NCI (no cognitive
impairment) group, which experienced no significant synapse loss67. Importantly, these
quantitative studies show that synapse loss correlates better with cognitive deficits as indicated by
MMSE scores than the overall density of plaques and tangles68,69. Together, these studies indicate
that synaptic destruction occurs early in the AD pathogenesis and contributes to functional deficits.
Thus, unraveling the underlying mechanisms for synaptic destruction can lead to more effective
treatments for AD.
19
f) The post-synaptic density of glutamatergic, excitatory synapses is a major site
for long term potentiation and depression.
The postsynaptic density (PSD) is a thick, multilayer compartment. It is a region of critical
protein-protein interactions that regulate LTP, LTD, and downstream signal transduction in the
postsynaptic cells. Altered PSD structure and molecular compositions are implicated in numerous
neurological diseases including AD. Synaptic plasticity is a broad term that describes long lasting,
activity-related strengthening or weakening of synaptic transmission. Such modifications in
synaptic strength enable consolidation and encoding of memories through coordinated changes in
various cellular mechanisms and signaling pathways that result in remodeling of dendritic spines
of pyramidal neurons in key brain regions such as cerebral cortex. These include the well-
established phenomena of long term potentiation (LTP) and long term depression (LTD).
I) LTP and LTD at glutamatergic excitatory synapses depend on NMDA and
AMPA receptor activity.
LTP was first demonstrated in 197370, and has been extensively studied since. The NMDA-
R dependent model of LTP is considered to be widespread in the CNS71, although other types of
LTP do exist (e.g. mossy fiber LTP)72. There are two phases of LTP: early phase (induction) and
late phase (consolidation). Early phase LTP (E-LTP) is initiated by an influx of Ca2+ ions through
NMDA receptors.73 Increased [Ca2+] leads to activation of Calcium/Calmodulin Kinase II
(CamKII). CamKII contacts the actin cytoskeleton through an unknown number of mediators and
modulators and results in changes in dendritic spine morphology (figure 9a and 9b).74-76
Concurrently, AMPA receptors are activated by kinase-dependent phosphorylation. LTP results in
an increase in surface level expression of AMPA-R receptors.77 The consolidation phase of LTP
is dependent on gene transcription for the synthesis of new proteins in order to maintain synaptic
strength. The duration of this phase can range from 60 minutes to days or weeks. Specifically, the
20
activation of transcription factor CREB, along with various signaling proteins and kinases have
been implicated in this late phase.71,75
Long term depression (LTD), similar to LTP, is widely expressed in the CNS.71 Like LTP,
induction of LTD can be dependent on a postsynaptic influx of [Ca2+] through NMDA-R.
Alternatively, in mGluR mediated LTD, the induction and changes in expression are due to surface
mGlu-receptors. Although these two different forms of LTD have different mechanisms, the
outcome of both is the same: a decrease in the amount of AMPA-R receptors expressed at the
postsynaptic membrane75,78. Several studies have shown that this dynamic fluctuation in surface
Figure 9: Mechanisms of LTP and LTD in the PSD.
(a) Weak activity of the presynaptic neuron leads to a modest depolarization and Ca2+ influx through NMDA receptors.
This preferentially activates phosphatases that dephosphorylate AMPA receptors, thus promoting receptor endocytosis.
Strong activity (which is paired with strong depolarization) triggers LTP in part via activation of CaMKII, receptor
phosphorylation, and exocytosis
(b) Structural changes associated with LTP and LTD. (1) Synaptic strength correlates with spine volume and the area
of the postsynaptic density (orange). Note that the PSD in potentiated synapses is often perforated. (B) LTP can also
lead to the appearance of new spines.
Source: Modified from Lüscher, C., & Malenka, R. C. (2012). NMDA receptor-dependent long-term potentiation and
long-term depression (LTP/LTD). Cold Spring Harbor perspectives in biology, a005710.
a)
b)
21
expression of AMPA-R is a result of receptor endocytosis mediated through various signaling
cascades. Several postsynaptic proteins have been implicated in this process and more molecules
remain to be determined. After induction by low-frequency stimulation, the increased [Ca2+] in the
postsynaptic cell activates calcineurin and protein phosphatase I, as well as various kinases (e.g.
CamKII, PKC) to ultimately decrease AMPA-R levels in the postsynaptic membrane75,77,78.
Importantly, this endocytic process of LTD, as well as the accompanying dendritic shrinkage
through cytoskeletal remodeling (figure 9), involve several postsynaptic proteins, including Arc,
implicated as important players in these processes of memory formation and encoding74,75,78.
II) Scaffolding Proteins PSD-95 and FLNA function as binding partners and
regulate receptors in key signaling pathways involved in memory formation.
The postsynaptic density (PSD) of glutamatergic, excitatory neurons is the site of a variety
of important protein-protein interactions. The PSD is multilayered, with an intentional
organization of molecules based on their functional role(s)79 (figure 10). Within this laminar
structure, each layer has different dynamic compositions. Proteins are organized to allow for
efficient downstream transduction of signals received from the presynaptic cell. The membrane,
or surface layer, contains transmembrane proteins such as NMDA-R and AMPA-R receptors.
NMDA-R activity at the PSD results in changes in AMPA-R concentrations seen in LTP and LTD.
In the cytoplasmic layer of the PSD, there are a host of proteins that interact with the cytoskeleton
to mediate dynamic changes in dendritic spine structure80. Among the most critical and abundant
proteins located throughout the PSD are scaffolding proteins. This specific protein class regulates
a host of signaling pathways. Specifically, they organize and stabilize various proteins and
receptors, such as NMDA-R and AMPA-R, into complexes in the PSD.
22
One critical scaffolding protein is PSD-95. Substantial data shows that PSD-95 is one of
the critical proteins involved in AMPA-R dependent changes at the PSD in response to synaptic
activity. Overexpression of PSD-95 selectively increased AMPA-R mediated EPSCs in
hippocampal neurons without detectable change in NMDAR-mediated EPSCs81-83. Conversely, in
a PSD-95 knockdown study using RNA interference (RNAi), there was a selective reduction in
AMPA-R mediated EPSCs84,85. These studies show that PSD-95 regulates the synaptic
transmission of AMPA-R mediated EPSCs. Although NMDAR-mediated EPSC is not influenced
by genetic manipulation of the PSD-95, PSD-95 is associated with and recruited to NMDARs upon
receptor activation86, 52-54. The functional importance of the NMDAR-PSD-95 linkage is
demonstrated in the conditions in which excitotoxicity has been elicited such as in stroke as
blockade of PSD-95 reduces infarct size87.
Figure 10: Proposed Molecular Organization of the PSD.
The synapse membrane is enriched with both AMPA and NMDA receptors, but mGluRs are
distributed in the perisynaptic membrane. The PSD is composed of multiple layers, with the
stable molecules localized in the surface layer (dark blue). The cytoplasmic layer (light green)
is enriched with dynamic proteins interacting with F-actin. CaMKII holoenzymes are also
enriched on the cytoplasmic face of the PSD.
23
Filamin A (FLNA), also known as actin binding protein-a, is another scaffolding protein
that is abundant in the PSD. FLNA was shown to be essential in cytoskeleton assembly and
rearrangement. The function of FLNA can be modulated by phosphorylation mediated by
serine/threonine kinases such as Pak1 found in the cytoskeletal compartment of the PSD88.
Dysfunction or altered conformation of FLNA is a prominent pathology of AD89. FLNA is
recruited to α7nAChR and toll-like receptor 4 (TLR4) upon soluble Aβ binding to α7nAChRs and
TLR4 complex. Thus Aβ interaction with α7nAChRs promotes Aβ toxic signaling toactivate
downstream kinases which hyperphosphorylate tau and ultimately the formation of the second type
of hallmark pathology seen in AD: neurofibrillary tangles. By activation TLR4, Aβ triggers
release of inflammatory cytokines to promote neuroinflammation. These critical proteins and
many others, including several immediate early gene proteins also located in the PSD, are crucial
in the synaptic functions that regulate neuron activity in memory formation.
III) Immediate Early Genes and their protein products function as a rapid
response mechanism to cellular stimuli.
Immediate early genes (IEGs), a category of genes expressed in response to stimuli, are
implicated in LTP and LTD because of their rapid and transient responses to synaptic activation88.
Various types of stimuli can provoke upregulation of IEGs. Increased neuronal activity via sensory
stimuli, pharmacologically induced seizure activity, and behavioral tasks such as the MWM all
induce IEG expression in neurons in a specific brain regions89-92-80.
The response of IEGs to neuronal activity can be seen in the PSD. Specifically, IEG protein
products (e.g. Arc and homer1a, H1a) are critical in the PSD signal response to neuronal stimuli.
Using a fluorescence in situ hybridization (FISH) experiment strategy, Arc and H1a RNA
24
transcription was induced in rat hippocampal and cortical neurons when rats were exploring a
novel environment. This result supports the idea that Arc and H1a in the PSD may influence long
term changes in synaptic plasticity93
g) Activity Regulated Cytoskeleton Associated Protein (Arc)
First discovered in 1995, Arc/Arg3.1 (activity regulated cytoskeleton associated) is a
vertebrate specific gene that is a member of the IEG family94. It produces Arc (Activity regulated
cytoskeleton associated), a single 55kDa protein that functions in the postsynaptic density and
nuclear regions of the neuron95. Arc’s mRNA is localized to dendrites in response to synaptic
activity from the nucleus and is subsequently locally translated in response to synaptic activity.
Significantly, studies have shown that Arc is expressed almost exclusively in excitatory,
glutamatergic neurons in the hippocampus and neocortex96. In support, visual cortex of the Arc
knockout mice (Arc-/-), was not affected by both sensory stimuli, or the absence thereof97,98. These
experiments indicate that Arc plays a critical role in experience-dependent synaptic plasticity in
the cortex. Due to this important, central function, a great effort has been dedicated to analyzing
Arc’s structure with the goal of improving our knowledge regarding Arc’s mechanisms of
action99,100. Arc, however, is more challenging to understand at the molecular level because it is a
single copy gene that does not have any known genetic homologues98.
One of the challenges to understanding the regulatory mechanisms involved in Arc’s
unique functions is the limited information available regarding Arc’s structure and binding sites.
In 2015, Zhang and colleagues demonstrated the first partial crystallization of Arc, however, full
length Arc has never been crystallized100. Beyond this crystallization study, mass spectrometry
and spectroscopy analyses indicated that Arc is likely to contain two lobar regions with
predominantly α-helical content that are linked by a disordered, flexible region99,100. Through
25
various research studies, several cytosolic, dendritic and nuclear proteins have been found to
interact with Arc via dedicated binding sequences in either the Arc C-lobe or N-lobe (figure 11).
Since the mechanisms through which Arc influences neurons have not been fully elucidated, Arc-
protein interactions, their dedicated binding sites and the functions of these interactions continue
to be investigated.
I) Synaptic Functions of Arc mediate AMPAR Regulation in LTP/LTD.
Arc protein plays a central role in both long-term potentiation (LTP) and long-term
depression (LTD) by acting in response to activity through interactions with several proteins in
the postsynaptic density94. Specifically, LTP increases Arc expression whereas LTD leads to
decreased local Arc translation and expression90. This is also supported by earlier studies that
show late phase LTP or the consolidation phase of LTP requires sustained Arc expression. Arc’s
role in LTP and LTD has been investigated in numerous studies, yet many questions still remain.
Figure 11: Graphic Representation of Arc domain structure. Shown are selected regions and known
binding sites with function. NRD, nuclear retention domain; NES, nuclear export signal; NLS nuclear
localization signal. Scale unit − amino acids.
Source: Modified from Nikolaienko, O., Patil, S., Eriksen, M. S., & Bramham, C. R. (2017,
September). Arc protein: a flexible hub for synaptic plasticity and cognition. In Seminars in cell &
developmental biology. Academic Press.
26
Experiments have shown that while Arc likely plays a role in early-phase LTP, it is critical
for late phase LTP99-101. When Arc antisense oligodeoxynucleotides (ODNs) were infused into
the hippocampi of rats before LTP induction, LTP consolidation was lost, but early-phase LTP
remained intact99. In another study by Messaoudi et al (2007), rats were infused with Arc
antisense ODNs 2h after HFS. The rats had a profound and permanent loss of late-phase LTP, but
not early-phase LTP112. These experiments indicate that Arc is essential and necessary for the
consolidation phase of LTP.
LTP has been shown to induce dendritic spine remodeling, a morphological change that is
linked to learning and memory formation114,115. Thus, Arc not only regulates synapse strength, but
may also play a role in sculpting dendritic spine morphology during LTP although the underlying
mechanisms remain to be fully elucidated. Through mechanisms and interactions that are not fully
understood, Arc is involved in cytoskeletal dynamics at the PSD. One protein that interacts with
Arc is cofilin, a postsynaptic protein that binds and severs filamentous actin (F-actin), thus
promoting the formation of actin monomers116,117. Cofilin is negatively regulated by
phosphorylation which is induced by synaptic activity (e.g. HFS)115. During late phase LTP in the
hippocampus of live rats, cofilin is phosphorylated during LTP and blocking cofilin
phosphorylation partially reduced late phase LTP, and, 115. In this same study, Arc AS infusion 2h
after LTP induction resulted in cofilin dephosphorylation and subsequent activation22. These
results indicate that Arc is necessary for stabilization of F-actin, and cofilin phosphorylation during
LTP. Other signaling cascades involving Arc and its role in LTP induced cytoskeletal changes
continue to be investigated.
27
In addition to its various, critical functions in LTP, Arc is also necessary for LTD. It has
been well established that AMPARs at the synapse are internalized via clathrin-coated vesicles
following LTD indiction118-120. In 2006, Chowdhury et al. showed that Arc mediated this AMPAR
trafficking via its interactions with the accessory proteins endophilin and dynamin118. Specifically,
Arc affected synaptic activity by interacting with endophilin 1 and dynamin 2 to promote AMPAR
endocytosis (figure 12). Arc mutants with altered binding sites for either endophilin or dynamin,
significantly reduces surface GluR1 levels118. This indicates that Association of Arc with both
endophilin 1 and dynamin 2 is a necessary regulator of the endocytosis of AMPARs during LTD.
Figure 12: Arc has multiple effects through its actions in the synapse and nucleus.
Interactions with various cellular proteins mediate Arc’s functions in the synapse and nucleus to affect
LTP and LTD. Arc is shown to form a complex with Endophilin and Dynamin to regulate AMPAR
endocytosis in LTD. It has also been shown to interact with βSpectrinIV and PML-NB in the nucleus,
although the exact function of this interaction is unclear. LTP; long term potentiation. LTD; long term
depression. PML-NB; promyelocytic leukemia nuclear bodies.
Source: Korb, E., & Finkbeiner, S. Arc in synaptic plasticity: from gene to behavior. Trends in
neurosciences, 34(11), 591-598. (2011).
28
Arc expression is induced when group 1 mGluRs are activated. This leads to endocytosis
of the AMPARs in a process termed mGluR-LTD. Overexpression of the Arc protein in neurons
causes a reduction in surface expression of certain types of GluA subunits and both mGluR- and
NMDAR-mediated LTD121. Exactly how Arc regulates the endocytic machinery is unclear, and no
direct evidence shows that low frequency stimulation causes Arc to localize to endophilin and
dynamin. To fully explain how Arc can associate with and regulate both LTP and LTD, additional
research is needed to better understand the cellular functions of Arc and how they are regulated by
different stimuli. Together, these studies suggest that Arc expression can be utilized to gauge the
changes in the synaptic activity and dendritic dynamics in the diseased brain tissues.
II) Nuclear functions of Arc
Although the majority of Arc’s cellular impact is exerted through its role at the synapse,
nuclear expression of Arc is also critical and increases in response to stimuli 102, 103. Arc gene
expression is regulated by several second messengers (e.g. kinases) that amplify signaling
downstream of synaptic activity. Arc transcripts appear within 5 minutes of neural activity, hence
it’s classification as an IEG.106
Through its effects inside the nucleus, Arc also exerts a cell-wide change that is implicated
in homeostatic plasticity. This critical, regulatory mechanism functions to balance the effects of
synaptic plasticity (i.e. LTP and LTD). Through homeostatic scaling, a neuron is able to adjust its
response to long-term changes in activity, so that it can maintain the same firing rate. In
experiments of Arc KO or overexpression, this scaling ability was shown to be compromised110.
Arc translocates to the nucleus hours after activity induced translation at the synapse. There is a
direct, positive correlation between time and the ratio of nuclear to cytoplasmic Arc in response to
stimuli. Arc is localized to the nucleus via phosphorylation by the MEK-ERK signaling
29
pathway.104,109 Once inside the nucleus, Arc is involved in a series of actions that have been shown
to be responsible for Arc’s critical function in homeostatic scaling. In cultured hippocampal
neurons, Arc co-localizes with βSpIVΣ5, a spectrin scaffolding protein107 (figure 12). The
association of both Arc and βSpIVΣ5 (and neither Arc nor βSpIVΣ5 alone) in nuclear puncta
results in increased promyelocytic leukemia nuclear bodies (PML-nb), a known transcription
regulator108. Further, it has been shown that Arc acts indirectly through PML-nb’s to reduce GluA1
transcription resulting in a decreased surface level expression of GluA1103,107.
III) Regulatory mechanisms of Arc: posttranslational modifications
The majority of eukaryotic proteins undergo some form of post-translational modification
(PTM), a processing event that results in chemical changes to proteins after translation. Generally,
PTMs occur through proteolytic cleavage or the reversible addition of a modifying group (e.g.
acetyl, phosphate) to a specific sequence of amino acids within the protein target. Some of the key
regulatory functions of PTMs include altering protein conformation for targeting and localizing to
subcellular regions, activation, and degradation123. The role of PTM in Arc function and its protein-
protein interactions is of particular interest because Arc is a dynamic protein: it binds to several
Figure 13: Sites of Post-translational modifications on Arc. Several residues within the Arc protein
have been identified as target sites for key post-translational modifications. Among them are
phosphorylation (P), SUMO1-ylation (S1) or ubiquitination (Ub). ? indicates predicted target sites.
Source: Carmichael, R. E., & Henley, J. M. Transcriptional and post-translational regulation of Arc in
synaptic plasticity. In Seminars in cell & developmental biology. Academic Press. (2017).
30
proteins and has versatile functions that change based on cellular location and neuronal
conditions103,105,111,118. These characteristics point to the high probability of PTM involvement in
directing Arc localization, function, and other aspects of Arc regulation as well as sites of
dysfunction in diseases (figure 13). However, PTMs of Arc have mostly not been revealed.
SUMOylation, an important PTM used in cellular regulation of protein localization and
function, is the addition of an approximately 10kD protein from the small ubiquitin-like modifier
(SUMO) family of proteins124. Arc has been shown to be a substrate of SUMO, with two
SUMOylation sites125. Overexpression of a double mutant for both SUMOylation sites in cultured
hippocampal neurons prevented Arc’s localization patterns to the expected subcellular regions126.
When LTP was induced by activity in rats, SUMOylated Arc accumulates in large amounts to the
synaptoneurosomal and cytoskeletal fraction of the dentate gyrus127. These results show that newly
synthesized Arc likely requires modification by SUMO to be targeted to the actin cytoskeleton in
the consolidation phase of LTP.
Arc is a tightly regulated protein. It is unsurprising, then, that the PTM type that has the
most identified consensus sequence sites on Arc to date are ubiquitination sites. In a 2014 study,
researchers showed that Triad3A, a ubiquitin ligase, ubiquitinates Arc and induces its proteasomal
degradation. In a series of RNAi experiments, Triad3A loss-of-function analysis showed a
decrease in Triad3A by 75%, with a subsequent increase in Arc accumulation. When Triad3A was
overexpressed, Arc levels were reduced and this led to an increase in the level of synaptic AMPA
receptors128. Experimentally, Arc is also ubiquitinated by ubiquitin E3 ligase, Ube3A94,129. RNAi
knockdown of Ube3A experiments result in elevated Arc protein levels129. Like Triad3A,
overexpression of Ube3A leads to a decreased Arc-mediated AMPAR endocytosis.
31
The most common type of PTM in eukaroytes is phosphorylation, as it has been well documented
that phosphorylation is a key regulator of protein activity (i.e. kinase activation). Phosphorylation
of key proteins is a crucial component of the pathways between synaptic activity and cellular
responses in various transduction mechanisms, including during Arc transcription and
translation104,106. While four phosphorylation sites have been identified based on consensus
sequence, direct phosphorylation of Arc has not been directly demonstrated. Arc has been shown
to interact with calcium/calmodulin-dependent kinase CamKII in a method termed inverse
synaptic tagging, thus indicating that there is a phosphorylation site for CamKII130. In addition,
there are putative phosphorylation sites for protein kinase C (PKC) and casein kinase II (CKII)38.
However, phosphorylation at all of these sites and possibly other potential phosphorylation sites
remain to be verified or identified. More importantly, the function of phosphorylation of Arc must
be elucidated to fully appreciate the role of Arc in the dynamic regulation of PSD and the dendritic
field in health and disease.
h) Arc expression and function is altered in disease
A balance between excitation and inhibition are critical to proper, overall neuronal
function. Therefore, it is unsurprising that Arc, a critical regulator of synaptic function, has been
implicated in a large number of neurological disorders. More specifically, a wide range of
neurological diseases, including schizophrenia, AD, and autism spectrum disorders (ASD) among
others have pathological manifestations that include dendritic spine abnormalities132,133. These
include dysfunctional actin and cytoskeletal dynamics132,133. Despite the fact that there are no
known Arc mutations that are directly implicated in disease conditions, many animal models of
disease have shown altered Arc expression95. Indeed, Arc itself was discovered during a search for
genes that were expressed in an individual after a seizure, indicating a role for Arc in epilepsy.
32
Since its discovery, research into Arc has shown that it may be a central protein in a variety of
other diseases. In animal models of major depressive disorder, Arc expression is significantly
increased upon exposure to chronic stress134. Changes in Arc mRNA are seen in the PFC after even
a single exposure to addictive drugs, as Fumagalli and colleagues showed in a rat model. This may
indicate a significant role for Arc in addictive behaviors138. In schizophrenia, genes encoding
proteins that are associated with Arc have been found through genome wide association studies
(GWAS) and other large scale analyses139. Arc and its protein complexes are of interest in
schizophrenia because NMDAR hypofunction and downstream signaling dysfunction may be
etiologically important in this disease86.
I) Cognitive disorders, aging and AD
Arc dysfunction has been strongly implicated in diseases with cognitive defects. The
neurodevelopmental disease Angelman syndrome is characterized by neurodevelopmental delays
including speech impairments resulted from a mutation in Ube3A129,136. Mutations and copy
number variants for Ube3A can also result in ASDs. Mouse models of ASD with altered Ube3A
indicate decreased levels of Arc along with elevated Ube3A due to Ube3A’s modulatory role in
Arc protein degradation136.
Fragile X Syndrome (FXS) is the most common inherited form of mental retardation140.
The FMR1 gene, which produces the FMRP protein, has been experimentally shown to be
responsible for FXS. FXS is pathologically associated with elevated levels of mGluR-LTD and
overexpression of several proteins including Arc. This abnormally heightened Arc expression
leads to increased endocytosis of AMPARs and increased mGluR-LTD. importantly, altered
dendritic spine morphology is noted in animal models of FXS and humans with this disorder.
33
While the role for Arc in diseases with synaptic pathologies and brain dysfunction in these
neurodevelopmental disorders is postulated, little is known about the changes of Arc during normal
aging and age-related disorders with synaptopathy such as AD. More importantly, it remains
elusive whether change in Arc is the result or the cause of dysfunction and loss of synapses in the
disease progression in aged and AD brains. Although milder in magnitude, some AD pathologies
can be found in brains of non-demented elderly144. In support, brains of the older wild-type mice
that showed reduced synaptic function as indicated by the attenuated receptor function also
accompanied by elevated basal but diminished stimulated Arc expression54. Among various
pathogenic factors, soluble Aβ even when added exogenously can inhibit activity-dependent Arc
expression54. Addition of Aβ oligomers (Aβo) at µM or near μM range to neurons inhibits LTP
and directly induces LTD, spine loss, and eventual cell death94,95,145. Arc has been shown to be
directly involved in production of the Aβ peptide through its association with endosomes that
contain the secretases BACE1 and presenilin that are responsible for the cleavage of APP into
Aβ146. Several investigative studies have also shown reciprocal relationships between Aβ and Arc.
Wu et al. showed that the number of amyloid plaques were reduced in a mouse model of AD when
Arc was deleted65. In human AD tissues, Arc protein levels are elevated146. When soluble Aβo are
added directly to cultured neurons, an increase in Arc protein level is accompanied by a lengthened
but reduced number of dendritic spines. In a transgenic mouse model of AD (hAPPFAD), Arc
mRNA expression was shown to be reduced in the hippocampus together with behavioral
deficits147. Moreover, a study investigating changes in Arc expression due to age showed a
reduction in Arc expression induced by spatial exploration in granule cells in the hippocampus143.
Although these data link Arc to spine morphology and behavioral abnormalities during aging and
in AD, the cause-effect relationship during AD pathogenesis is still not clear.
34
This proposed study therefore aims to fill the knowledge gaps by systemically investigating
the regulatory mechanisms on Arc during normal aging and in AD. Using varying ages of wild-
type and 3x Tg AD mice, the age-dependent and AD effects on non-stimulated (basal) and activity-
dependent Arc expression were determined in both prefrontal cortex (PFC) and hippocampal
formation (HF). To gain insight into the regulatory mechanism of Arc and whether the regulation
of Arc alters during normal aging and in AD, we assessed the phosphorylation and nitration of Arc
under basal and receptor-stimulated conditions in both brain regions from wild-type and 3x Tg AD
at various ages. The inter-relationship of Arc with various signaling complexes and the kinases
that mediate Arc phosphorylation were also elucidated and confirmed using enzyme inhibitors,
The relevancy of the data obtained in mouse AD model to AD pathogenesis was further determined
using postmortem hippocampal formation from 8 sets of age- and gender-matched non-demented
controls, AD as well as MCI-AD and MCI-sNAP cases.
35
Experimental Procedures
Human Postmortem Hippocampal formation sections
This study protocol conformed to the tenets of the Declaration of Helsinki as reflected in a
previous approval by the City College of New York and City University of New York School of
Medicine human research committee. De-identified neurologically normal controls and patients
with diagnosis validated MCI-sNAP, MCI-AD and AD cases were obtained from NIH-sponsored
brain banks: the RUSH Alzheimer’s disease center (Chicago, IL), the University of Pennsylvania
Brain Tissue Resource Center (Philadelphia, PA), the Harvard Brain Tissue Resource Center
(HBTRC, Belmont, MA) and the UCLA Brain Tissue Resource Center (UBTRC, Los Angeles,
CA).
Description of case cohorts
The AD cases from University of Pennsylvania were from a subset of a cross-sectional
study of AD pathology. The MCI cases obtained from RUSH Alzheimer’s disease center were
part of a longitudinal epidemiological and clinico-pathological study of aging called Religious
orders study (ROS) and Memory and Aging Project (MAP), including MCI and AD. ROS cases
are elderly Catholic clergy (nuns, priests, and brothers) who enter the study without signs of
cognitive impairment. MAP is a community based aging study. All ROS and MAP subjects were
examined annually with full clinical and neuropsychological evaluations and donate their brains
upon death. The follow-up rate for annual testing is above 95%, and the autopsy rate exceeds
90%148, 149. These MCI subjects were selected randomly from the 350 deceased ROS subjects who
had validated MCI diagnosis and were similar in age (< 5 year), postmortem interval and gender
with control and AD cases. None of the cases included have history of diabetes, stroke or
36
psychiatric disorders. There was no evidence of vascular anomalies in the hippocampal formation
of any case used in the current study. Diagnoses of AD and MCI studied met clinical criteria for
that disorder specified by NINCDS-ADRDA150 based on the assessments in the consensus
conferences after review of medical records, direct clinical assessments, and interviews of care
providers. Clinical diagnosis stipulates that an individual showed clear cognitive decline from his
or her previous levels as verified in the memory tests with at least one other cognitive domain (e.g.,
perceptual speed). The diagnoses were confirmed by postmortem examination of neuritic plaque
densities in midfrontal gyrus (dorsolateral prefrontal cortex), superior + inferior temporal gyrus,
inferior parietal gyrus, hippocampus, and substantia nigra as specified by the Consortium to
Establish a Registry for AD151. The final diagnoses were consistent with Braak scores for
neurofibrillary tangle (NFT) pathology as recommended by the NIA-Reagan Institute consensus
on diagnosis of AD152. Diagnostic neuropathological examination was also done in all tissues
using fixed sections stained with hematoxylin and eosin and with modified Bielschowsky silver
staining153 to establish any disease diagnosis according to defined criteria152. The presence of both
amyloid plaques and NFTs in all AD brains was also confirmed by Nissl and Bielschowsky
staining and characterized immunohistochemically with anti-Aβ42 and -NFT staining in both
frontal and entorhinal cortex as well as hippocampus, as described previously49, 51. Control tissues
typically exhibited only minimal, localized microscopic neuropathology of AD (0 –3 neuritic
plaques/10% field and 0 – 6 NFTs/10% field in hippocampus).
Diagnosis of MCI 154,155was purely clinical and indicates that an individual was rated at the last
examination as cognitively impaired according to neuropsychological tests. A diagnosis of
amnestic MCI (aMCI, MCI-AD) indicates that the individual displayed prominent deficits in
episodic memory at the final evaluation. As this implies, a diagnosis of non-amnestic MCI (naMCI,
37
MCI-sNAP) indicates that the individual displayed predominant cognitive deficits other than
memory (i.e., perceptual speed and/or visuospatial ability) at the last evaluation. Cognitive Testing
Yearly evaluations of the ROS subjects include neuropsychological testing, as well as completion
of a medical history, neurological examination, and ratings on psychiatric scales. The average time
between the last neuropsychological evaluation and death is 6-7 months. As previously
described156,157, such evaluation included the MMSE and 7 tests of episodic memory, 4 of semantic
memory, 4 of working memory, 2 of perceptual speed, and 2 of visuospatial ability. For data
reduction in each subject, raw scores on individual tests were converted to z scores relative to the
baseline mean and standard deviation for the entire ROS cohort. These were averaged to yield
composite scores on the cognitive domains noted above (e.g., episodic memory), which were in
turn averaged to yield a composite global cognition score.
Tissue Collection Autopsy consent was obtained from the brain donors, next-of-kin, or legal
guardians in all cases. Postmortem cases were stored at 2-4°C until autopsy. After sagittal bisection
of the forebrain, the brain was cut into coronal slabs. One hemisphere was sampled for tissues to
be examined microscopically, including the cerebellar cortex, HF, and other brain areas used for
diagnostic neuropathological assessments indicated above. Samples were fixed in neutral-buffered
formalin for 24-48 h, and embedded in paraffin. The remaining tissue was frozen overnight at -
80°C and sealed in plastic bags for long-term storage at -80°C. HF tissue were later dissected from
the frozen hemispheres of 8 matched pairs of normal and AD cases for the ex vivo stimulation
with, NMDA/glycine, insulin and BDNF as described below. Surfaces were shaved before thawing
to remove oxidized surfaces. Based on the stimulating postmortem studies in rodents and
postmortem brain studies that tested the effect of PMI on ex vivo stimulation paradigm86,51, 158, the
postmortem time intervals for collecting these brains were <12 hr. Of the selected cases in the
38
current study, the mean postmortem intervals for collection of control, MCI-AD, MCI-sNAP and
AD brain samples were 6.8 ± 0.6hr, 5. 9 ± 0.6 hr, 6.6 ± 0.5 hr and 6.3 ± 1.0 hr, respectively). One-
gram blocks from hippocampal formation were dissected using a band saw from fresh frozen
coronal brain sections maintained at -80°C. All experiments were performed as a best-matched set
that consist of control-MCI-AD, MCI-sNAP and AD without knowledge of clinical information.
Postmortem interval (PMI) is defined as the period of time between death and when the tissue
is frozen1. Previous research149,150 has shown how varying PMD can affect tissue integrity.
Specifically, DNA, RNA and protein expression are known to be compromised as temperature and
PMD increase. For each cohort, a total of n = 8 samples were selected.
3xTg AD Mouse Model Tissue Preservation and Selection
While AD is a uniquely human disease, animal models are useful for investigating specific
pathologic mechanisms during aging and diseases of cognitive impairment151.
3xTg AD mutant mice, also known as the LaFerla mouse, were obtained from the LaFerla lab
at University of California at Irvine152. This mutant strain harbors 3 mutations that facilitate the
production of AD pathological markers: APPswe mutations result in a substitution of lysine and
methionine with arginine and leucine, respectively, leading to an increased production of Aβ152.
The second mutation is PS1M146V which changes methionine to valine at exon 5 that also promotes
Aβ42 secretion. The third mutation is MAPTP301L. This mutation accelerates the pathology of tau
helical filaments seen in AD although tau pathology in AD is not due to a mutation but the result
of hyperphosphorylation and consequent loss of function. The 3xTg AD mouse exhibits age-
dependent changes that partially resembles some changes seen in human AD although there is little
neurodegeneration until at least 12-month of age152.
39
PFC and HF were collected from wild-type E129 (from Taconic in Germantown, NY) and
3xTg AD mice to evaluate under basal and ex-vivo stimulation conditions. For the 3xTgAD mice,
mice were sacrificed at 6-, 10-, and 15-months of age (n=5). For the wild-type E129 mice, tissue
samples were collected at 4-, 6-, 10- and 15-months of age. In the earlier reports, Aβ plaque
pathology has been shown to develop at 6 months of age in the 3xTg AD mouse model, with tau
pathology observed at 10 months or older4,54. The 4-month-old E129 mice were used as the
references for age-related changes. In all experimental series, WTs were assessed simultaneous
with age-matched 3xTg AD mice. .
a) Ex-Vivo Stimulation
For in vitro assessments, postmortem tissues were gradually thawed (from -80°C to -
20°C), sliced using a chilled McIlwain tissue chopper (100μm X 100μm X 3 mm) and suspended
in ice-cold oxygenated low Mg2+ K-R (LMKR), containing (in mM): 25 HEPES, pH 7.4, 118
NaCl, 4.8 KCl, 1.3 CaCl2, 1.2 KH2PO4, 0.3 MgSO4, 25 NaHCO3, 10 glucose, 100 μM ascorbic
acid and protease inhibitor cocktail (Roche). After centrifugation and two additional washes with
1 ml of ice-cold LMKR, brain slices were suspended in 1 ml of LMKR.
Using a well-established ex vivo stimulation method139, human postmortem HP from non-
demented controls, MCI-sNAP, MCI-AD, and AD cases were immediately suspended in ice-cold
oxygenated LMKR with protease inhibitors, washed and distributed into 5 tubes each with
approximately 5 mg. Each was incubated at 37°C with either Kreb’s-Ringer (K-R), NMDA (10
μM)/glycine (1 μM) for 10 min, 1 nM insulin for 30 min, 50 ng/ml BDNF for 30 min or PNU
282987 (PNU282987 is a potent and selective agonist for α7nAChRs) for 10 min. In the cases of
NMDA/glycine and PNU282987, slices were briefly centrifuged (at 25°C) and re-suspended and
40
incubated in LMKR for an additional 20 min. The reaction was terminated by addition of protein
phosphate inhibitors, diluting with ice-cold Ca2+-free LMKR and centrifugation at 4°C.
Similarly, slices of HF and PFC derived from WT* and 3xTg AD mice at age 4-, 6-, 10-
and 15- months (n=5) were prepared using a chilled McIlwain tissue chopper (100μm X 100μm X
3 mm) and suspended in ice-cold oxygenated LMKR containing protease inhibitor cocktails ,
washed and distributed into 3 tubes (approximately 2.5 mg/tube) each was incubated at 37°C with
either LMKR, NMDA (10 μM)/glycine (1 μM) for 10 min followed by a 20-min incubation with
LMKR or 1 nM insulin for 30 min. The reaction was terminated by addition of protein phosphate
inhibitors, diluting with ice-cold Ca2+-free and centrifugation at 4°C.
*The 4 month cohort had WT tissue only, there was no 3xTgAD matched samples.
b) Immunoprecipitation and co-immunoprecipitation
These assessments used previously described co-immunoprecipitation methods51, 53, 158. Two
hundred micrograms of postmitochondrial fractions from either postmortem human HF, PFC or
HF of mice. Brain slices pelleted by centrifugation were solubilized by brief sonication in 250 μl
of immunoprecipitation buffer (containing 25mM HEPES, pH 7.5, 200mM NaCl, 1mM EDTA,
protease and protein phosphatase inhibitor cocktails (Roche) and 0.1% 2-mercaptoethanol
containing 0.5% digitonin, 0.2% sodium cholate, and 0.5% NP-40) and incubated at 4°C with
end-to-end shaking for 1 hr. After dilution with 750 μl of ice-cold immunoprecipitation buffer
and centrifugation (4°C) to remove insoluble debris, Arc and its associated signaling complexes
including FLNA and NMDARs in the lysate were isolated by immunoprecipitation with 16 hr
incubation at 4°C with rabbit anti-Arc (1μg) immobilized on protein A/G-conjugated agarose
beads. The resultant immunocomplexes were pelleted by centrifugation at 4°C.After three washes
with 1ml of ice-cold PBS, pH 7.2, and centrifugation, the isolated Arc complexes were dissociated
41
by resuspended in 90 μl of elution buffer (pH2.8) for 10 min and centrifuged to obtained the
supernatant that contains Arc and its associated proteins. The resultant supernatant was
neutralized by addition of 10 μl 1.5M Tris HCl, pH8.8 and neutralized by adding 100 μl of 2 X
SDS-PAGE sample preparation buffer (125 mM Tris-HCl, pH 6.8, 20% glycerol, 4% SDS, 10%
2-mercaptoethanol, 0.2% bromophenol blue) and boiling for 5 min. The content of Arc and its
associated proteins in the anti-Arc immunoprecipitate was determined by Western blotting with
monoclonal antibodies directed against the indicated target. The Arc complex blots were stripped
and reprobed with monoclonal anti-Arc to assess immunoprecipitation efficiency and loading. To
determine Arc levels in response to stimuli, immobilized rabbit anti-actin (0.5 μg)–protein A-
conjugated agarose was added together with anti-Arc in the co-immunoprecipitation process. The
content of β-actin in resultant immunoprecipitates was analyzed by Western blotting using
monoclonal anti–β-actin to illustrate even immunoprecipitation efficiency and loading.
c) Western Blot Procedure
Samples of both HF and PFC, under basal and stimulated conditions, were size-fractionated
on a 10% polyacrylamide gel with Tris/glycine/SDS buffer at 100 V for approximately 100
minutes at room temperature. The gels were electrophorectically transferred onto BioRad 0.2μm
nitrocellulose membranes in 20% (v/v) methanol transfer buffer. Membranes were blocked with
10% nonfat milk in phosphate buffered saline containing 0.1% Tween-20 (0.1%PBST) for 1 hour
at room temperature. The membranes were incubated with primary antibodies of choice such as
anti-Arc monoclonal antibody were diluted in PBST and at 4°C overnight or at 25ºC for 2 hr.
After incubation, the primary antibodies were removed and membranes were washed 3 times with
0.1%PBST and the incubated with HRP-conjugated anti-mouse (1:7,500-10,000 in PBST) for 60
minutes. Membranes were washed with 0.1%PBST twice and distilled H2O once and the
42
immunocomplexes were detected using chemiluminescent method (SuperSignal West Peco or
Femto Maximum Sensitivity substrate, and visualized by exposure to X-Ray film. The specific
protein bands were quantified using densitometric scan using ImageJ software. The same blot
was stripped and re-probed with different antibodies to assess up to three additional parameters
such as loading control (anti-β-Actin antibody) and specific phosphoepitopes (phosphotyrosine
(pY), phosphothreonine (pT) and phosphoserine (pS) on Arc. Additionally, Arc modified by
oxidative stress was interrogated by probing the blot with antibodies direct against nitrotyrosine
to assess the nitrated Y-Arc levels in immunopurified Arc.
43
d) Statistical Evaluation
Statistical analyses of 2 conditions were done using a Student’s t-test. Statistical analyses of
multiple comparisons were done using a 1-way ANOVA. These were computed in Microsoft
Excel. These results are represented as the mean ± SEM (unless otherwise stated). P values less
than 0.05 are considered significant.
Results
1) Isolation of Arc by immunoprecipitation with anti-Arc is complete and
specific. The specificity and completeness of isolating Arc by immunoprecipitation with anti-Arc
antibodies was tested in hippocampi and prefrontal cortices from wild-type mice. Mouse
hippocampi and prefrontal cortices were homogenized in 500 μl of ice-cold immunoprecipitation
medium. Following centrifugation to remove nucleus and mitochondria, 200 μg of the resultant
post-mitochondrial fraction (adjust to 150 μl with immunoprecipitation medium) was sonicated on
ice for 10 sec and solubilized at 4°C for 1 hr by 0.5% NP-40/0.2% Na cholate/0.5% digitonin with
end-to-end shaking as indicated above. Following centrifugation to remove insoluble debris, the
obtained lysate was diluted with incubated with anti-Arc (Santa Cruz Biotechnology SC-15325),
-rabbit IgG immobilized onto protein A/G-conjugated agarose beads or protein A/G-conjugated
agarose beads alone. Separately, brain lysate (200 μg) was combined with 6X sample preparation
buffer and boiled for 5 min (Lysate). The obtained immunocomplexes were obtained by
centrifugation. The supernatant was removed and concentrated using 10-KDa molecular weight
cut-off filter and combined with 6X sample preparation buffer and boiled for 5 min. The
immunocomplex containing pellet was washed with PBS and Arc proteins are eluted from
immunocomplexes by 90 μl of antigen elution buffer (pH2.8). The obtained Arc-containing eluate
44
was neurolized with 10 μl 1.5M Tris HCl, pH8.8 and solubilized by adding 100 μl of 2X sample
preparation buffer and boiling for 5 min. The solubilized lysate and immunoprecipitates were
analyzed by Western blotting to evaluate the completeness and specificity of the Arc purification
procedure.
To affirm the completeness and specificity of the anti-Arc immunoprecipitation, 200 μg of
solubilized post-mitochondrial fractions derived from control HF and PFC slices were also
assessed by a two-step immunoprecipitation. Lysates were immunoprecipitated first with 1 μg of
immobilized anti-Arc, -rabbit IgG or protein A/G-conjugated agarose beads. The resultant
supernatants were then immunoprecipitated with 1 μg of immobilized anti-Arc.
The results summarized in Figure 14 indicate that 1 μg of anti-Arc antibodies completely
and specifically purified Arc from brain lysate. The completeness is supported by the data showing
the abundance of Arc in anti-Arc immunoprecipitates from 100 μg of brain lysate is similar to that
in equal amounts of brain lysate. In contrast, the supernatant has negligible residual Arc. Further
supports for complete immunoprecipitation by anti-Arc can also be drawn from the data indicating
that there is no more Arc in the Anti-Arc immunoprecipitates derived from supernatant of the first
anti-Arc immunoprecipitation.
The specificity of anti-Arc is supported by the data showing Arc only present in anti-Arc
but not anti-IgG or protein A/G precipitates in the first round of immunoprecipitation. The fact
that equal amounts of Arc can be immunoprecipitated from supernatants of the first
immunoprecipitation step by anti-Arc clearly illustrate immunoprecipitation with 1 μg of anti-Arc
is complete and specific.
45
Figure 14: Anti-Arc immunoprecipitation in the HF and PFC is
complete and specific.
The completeness and specificity of anti-Arc immunoprecipitation was
determined in mouse HF and PFC. The blots shown are the representatives
of three experiments.
46
2) Assessing Arc Expression
2a) Basal and Activity-driven Arc expression is decreased during normal aging
and in AD.
Since Arc expression is strongly related to synaptic activity and synaptic activity is clearly
declined during normal aging and even more sharply in AD, it is of interest to assess changes in
Arc expression, especially in response to stimuli that regulate postsynaptic activities. To this end,
Arc protein expression under non-stimulated basal conditions and in response to 10 μM NMDA/1
μM glycine or 1 nM insulin was assessed in both HF and PFC derived from varying ages of WT
and 3xTg AD mice. Following incubation, total Arc proteins were purified by
immunoprecipitation along with actin that are used to gauge the efficiency of immunoprecipitation
and serve as the loading control. The data summarized in figure 15a and 15b clearly indicate Arc
expression increases in response to stimulation of HF and PFC mouse tissue by activating
NMDARs and IRs with NMDA/glycine and insulin, respectively. The NMDA/glycine- and
insulin-driven Arc expression was significantly decreased in an age dependent manner in WT brain
by 10-month of age. The reductions in activity-induced Arc expression are more robust in the 3xTg
AD animal. By 6 months old, 3xTg AD animals display a greater than 60% reduction in
NMDA/glycine- and insulin-evoked Arc expression and further reduction in this stimulation-
driven activity is evidenced at 10- and 15-month of age. The reduced activity-driven Arc
expression in brains of older (>10-month-old) WT and 3XTg AD mice was accompanied by and
coincided with elevated basal Arc levels. Increased AD pathologies are found in aged cognitively
normal subjects144. Together with heightened synaptic dysfunction illustrated as reduced LTP and
increased LTD at old age and in AD, the data presented in figure 16 suggest that elevated basal
Arc levels and reduced activity-induced Arc expression are associated with and contributed to a
47
decline in synaptic functions in aged and AD brains. Together with heightened AD pathologies
and synaptic defects at old age and in AD, these data indicate that increased basal Arc may function
as a compensatory change in response to altered, activity driven Arc expression.
48
0
0.25
0.5
0.75
1
0
200
400
600
Arc
/-A
cti
n r
ati
o%
Sti
mu
lati
on
*
* * ** **
*
**
*
**
*
**
*
**
+ ++
# #
# #
# #
# #
# #
++++
++
^^^^
4-month W
T6-m
onth WT
6-month TG
10-month W
T10-m
onth TG15-m
onth WT
15-month TG
0
0.25
0.5
0.75
1
0
200
400
600
Arc
/-A
cti
n r
ati
o%
Sti
mu
lati
on
*
* * ** **
*
**
*
**
*
**
*
**
+ ++
# #
# #
# #
# #
# #
++++
++
^^^^
4-month W
T6-m
onth WT
6-month TG
10-month W
T10-m
onth TG15-m
onth WT
15-month TG
0
0.25
0.5
0.75
1
0
200
400
600
Arc
/-A
cti
n r
ati
o%
Sti
mu
lati
on
*
* * ** **
*
**
*
**
*
**
*
**
+ ++
# #
# #
# #
# #
# #
++++
++
^^^^
4-month W
T6-m
onth WT
6-month TG
10-month W
T10-m
onth TG15-m
onth WT
15-month TG
0
0.25
0.5
0.75
1
0
200
400
600
4-month W
T6-m
onth WT
6-month TG
10-month W
T10-m
onth TG15-m
onth WT
15-month TG
Kreb’s Ringer
10 μM NMDA + 1 μM Glycine
1 nM Insulin
*
*** *
**
*
**
*
**
*
**
*
**
+ +
# ## #
## # #
# #+++
^^ ^^
^
∆
0
0.25
0.5
0.75
1
0
200
400
600
4-month W
T6-m
onth WT
6-month TG
10-month W
T10-m
onth TG15-m
onth WT
15-month TG
Kreb’s Ringer
10 μM NMDA + 1 μM Glycine
1 nM Insulin
*
*** *
**
*
**
*
**
*
**
*
**
+ +
# ## #
## # #
# #+++
^^ ^^
^
∆
0
0.25
0.5
0.75
1
0
200
400
600
4-month W
T6-m
onth WT
6-month TG
10-month W
T10-m
onth TG15-m
onth WT
15-month TG
Kreb’s Ringer
10 μM NMDA + 1 μM Glycine
1 nM Insulin
*
*** *
**
*
**
*
**
*
**
*
**
+ +
# ## #
## # #
# #+++
^^ ^^
^
∆
0
0.25
0.5
0.75
1
0
200
400
600
4-month
WT
6-month
WT
6-month
TG
10-month
WT
10-month
TG
15-month
WT
15-month
TG
Kreb’s Ringer
10 μM NMDA + 1 μM Glycine
1 nM Insulin
*
*** *
**
*
**
*
**
*
**
*
**
+ +
# ## #
## # #
# #+++
^^ ^^
^
∆
a)
b)
Figure 15: Activity dependent Arc expression changes as a function of age and disease.
a: Representative blots showing activation-induced Arc expression in HF (LEFT) and PFC (RIGHT) of aged wild-
type (WT) and 3x AD transgenic (TG) mice.
b: Quantitative assessment of the activation-induced Arc expression in HF and PFC from 5 sets of 4-, 6-, 10-, and
15-month 3xTg AD mice with age matched WT. Data are expressed as the mean ± SEM of Arc/β-Actin optical
density ratios or % increase above basal Arc expression under non-stimulated, Kreb’s-Ringer incubated condition.
β-Actin levels are used as the immunoprecipitation/loading controls. HF = Hippocampal Formation, PFC =
Prefrontal Cortex.
*p<0.01 Compared to Kreb’s Ringer treated 4-month old WT group, #p<0.01 Compared to respective level in 4-
month old WT group, +p<0.01, ++p<0.05 Compared to respective level in 6-month old 3xTg group, ^p<0.01,
^^p<0.05 Compared to respective level in 10-month old WT group, Δp<0.01 Compared to respective level in
10-month old 3xTg group
49
2b) Assessment of the overall Arc protein levels.
Since Arc is an important synaptic regulator, we determined whether the overall Arc
protein expression in the HF and PFC is altered during normal aging and in AD. To achieve this
goal, the post-mitochondrial fractions prepared from 4-, 6-, 10-, and 15-month-old (there is no
3xTg AD cohort at 4 months) WT and 3xTg AD mice were solubilized by boiling in SDS-PAGE
sample preparation buffer (n=5). The Arc protein levels were assessed using Western blotting
with anti-Arc antibodies (Santa Cruz Biotechnology: SC-17839). The blots were stripped and re-
probed with anti-β-actin antibody (SC-517582) to ascertain even loading. The data shown in the
representative blots (figure 16a) and quantification (figure 16b) indicate that Arc protein
expression increases as mice age in both brain regions of WT mice. While the Arc protein levels
in HF did not differ between 4- and 6-month of age, Arc expression increased by 44% at 10- and
15-month of age. Similarly, the Arc expression in FCX did not change at 6-month of age but
increased by 12 and 24% respectively at the 10- and 15-month of age. This change in Arc protein
levels is even more severe in 3xTg AD mice. In the HF of 3xTg AD cohort, a 64-67 % elevation
in Arc expression level was evident by 6- and 10-month of age. At 15month-old, there is a 76%
increase in the Arc protein level. A robust, age-dependent increase in Arc expression is observed
in PFC of the 3xTg AD mice as Arc protein levels increased by 44%, 51% and 62% at 6-, 10- and
15-month of age, respectively. Together with the data showing markedly reduced activity-
dependent Arc expression in both HF and PFC (figure 15), these data may suggest that increased
Arc expression levels is an adaptive change in response to the reduced activity-driven Arc
expression. The elevated Arc protein levels in aged and 3xTg AD brains may suggest degradation
and/or increased gene expression of Arc occur during aging and in AD.
50
55
70
3529
130
55
35
Arc
β-Actin
55
70
3529
130
55
35
Arc
β-Actin
55
70
3529
130
55
35
Arc
β-Actin
0
0.5
1
1.5
4 Month W
T6 M
onth WT
6 Month 3xTG
10 Month W
T
10 Month 3xTG
15 Month W
T15 M
onth 3xTG
Arc
/-A
cti
n
Rati
o
*
**
*
*
*# ##
55
70
3529
130
55
35
Arc
β-Actin
0
0.5
1
1.5
4 Month W
T6 M
onth WT
6 Month 3xTG
10 Month W
T
10 Month 3xTG
15 Month W
T15 M
onth 3xTG
Arc
/-A
cti
n
Rati
o
**
**
*# ##
##
a)
b)
Figure 16: Basal Arc Expression levels in aging and AD
a: Representative blots showing basal Arc expression in HF (LEFT) and PFC (RIGHT) of wild-type (WT) and
3x AD transgenic (TG) mice at varying ages.
b: Quantitative assessment of the basal Arc expression in HF (LEFT) and PFC (RIGHT) from 5 sets of 4-, 6-,
10-, and 15-month-old WT and age-matched 3xTg AD mice. Data are expressed as the mean ± SEM of Arc/β-
Actin optical density ratios.
β-Actin levels are used as the immunoprecipitation/loading controls. *P < 0.01 Compared to 4-month WT #p
< 0.01, ##p < 0.05 compared to respective WT. HF = Hippocampal Formation, PFC = Prefrontal Cortex.
51
2c) Altered basal and activity-driven Arc expression in Human postmortem HF
from well-matched subjects with Alzheimer’s disease (AD), mild cognitive
impairment (MCI) and cognitively normal control subjects.
The data derived in AD mouse model suggest that reduced activity-driven Arc expression
may be related to synaptic dysfunction during AD pathogenesis. To assess the relationship
between the changes in Arc expression, especially in response to receptor stimulation, basal and
receptor activation-induced Arc expression was measured in the HF of 8 patients with AD
compared to well-matched subjects in control, MCI-sNAP and MCI-AD cohorts. In addition to
stimulation of the NMDAR by NMDA/glycine, activation of the α7nAchRs by PNU 282987 (a
potent, selective α7nAchR agonist), the trkBs by BDNF and insulin receptors by insulin was also
determined. The α7nAchR is the known upstream regulator of the NMDARs 145 and BDNF-trkB
signaling is intimately associated with NMDARs52,53. Upon incubation of the HF slices from
cognitive normal controls with NMDA/glycine, insulin, BDNF and PNU 282987, marked
increases in Arc expression was observed (figure 17a).
This receptor stimulation-evoked Arc expression is reduced most robustly in MCI-AD and
AD than in MCI-sNAP cases (figure 17b). In addition to the reduced stimulation-driven Arc
expression, significant increase in Arc levels in MCI-SNAP and AD under non-stimulated basal
condition was also noted. The increased Arc protein levels under basal conditions may partially
contribute to the observed reduction in activity-driven Arc expression in MCI-SNAP and AD.
More importantly, the dampened stimulation-induced Arc expression can occur without changes
in Arc protein levels under non-stimulated conditions as found in MCI-AD supports the notion
that reduced activity-driven Arc expression occurs earlier during the course of AD pathogenesis.
The elevated Arc protein levels under the basal condition is the result of adaptive increase in Arc
transcription in response to increased synaptic dysfunction and destruction in later phases of AD.
52
Moreover, the increased Arc protein levels under non-stimulated basal conditions noted in MCI-
AD hints that the homeostastic Arc levels are regulated by multiple factors including transcription
and degradation which are likely different between AD and MCI-SNAP. While the expression
in response to all stimuli was reduced most dramatically in MCI-AD and AD, the dampened
NMDA/glycine- and insulin-induced Arc response was evidenced together with relatively milder
decreases in BDNF and PNU 282987 responses in MCI-SNAP. These data together indicate that
reduced activity-induced Arc expression is an integral part of synaptic dysfunction in diseases with
cognitive impairments. The differential changes in MCI-AD and MCI-SNAP further highlight the
differences in disease progression and possibly the contribution of various pathogenic factors to
the synaptic/dendritic dysfunction in these brain diseases.
53
-Actin
Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
BDNF (50ng/ml):
+
+
+
Control
+
+
+
MCI-AD
+
+
+
MCI-SNAP
+
+
+
AD
70
100
55
35
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
PNU282987(0.1 μM):++++
a)
b)
Figure 17: Arc expression is altered in cognitively impaired human HF.
a: Representative blots showing basal and activation-induced Arc expression in HF from cognitive normal
control, MCI-AD (amnestic MCI), MCI-SNAP (non-amnestic MCI) and AD (Alzheimer’s disease) subjects. β-
Actin levels are used as the immunoprecipitation/loading controls.
b: Quantitative assessment of the basal and activation-induced Arc expression in HF from 10 sets of cognitive
normal control, MCI-AD (amnestic MCI), MCI-SNAP (non-amnestic MCI) and AD (Alzheimer’s disease)
subjects. β-Actin levels are used as the immunoprecipitation/loading controls. Data are expressed as the mean
± SEM of Arc/β-Actin optical density ratios or % increase above basal Arc expression under non-stimulated,
Kreb’s-Ringer incubated condition.
54
3) Arc is modified post-translationally by phosphorylation.
Post-translational modification such as phosphorylation of a given protein not only
influences its function greatly but also often is incorporated into the signaling pathway as the
regulatory mechanism for controlling the protein’s localization, interaction with other molecules
and even degradation. Given that Arc is one of the more prominent synaptic regulators in the
postsynaptic field, it is of interest whether post-translational modifications of Arc exist, how this
process is regulated in physiological conditions and whether these mechanisms are altered during
aging and AD pathogenesis. To this end, the phosphorylation state of Arc was determined by
immunoblotting in HF and PFC from WT and 3xTg AD mice and human postmortem HF tissues.
The completeness and specificity of Arc phosphorylation was first tested by reciprocal
immunoprecipitation methods. The phosphorylated Arc in the anti-Arc immunoprecipitates was
first tested by Western blotting using antibodies directed against phospho-serine (pS), -tyrosine
(pY) or –threonine (pT). In addition, the presence and abundance of the phosphorylated Arc in
the anti-pS, -pY or –pT immunoprecipitates was determined by Western blotting with anti-Arc.
The results summarized in figure 18 demonstrate again that anti-Arc specifically and
completely immunoprecipitates Arc which contains pS- and pY- but not pT-Arc in both HF and
PFC of the WT mice. In support of complete and specific immunoprecipitation of Arc, the contents
of pS- and pY-Arc in the supernatants from anti-rabbit IgG or protein A/G-agarose beads are
similar to anti-Arc in the anti-Arc immunoprecipitates.
Further support of the idea that Arc is modified only at the serine and tyrosine but not
threonine sites as well as the completeness and specificity of immunoprecipitation procedure can
be drawn from the data presented in figure 19. The data showing pS- and pY- but not pT-Arc is
55
presented in the anti-pS and -pY immunoprecipitates indicate the immunoprecipitation by anti-pS
and –pY and –pT is specific.
The establishment of the immunoprecipitation method enables us to assess the effects of
age and AD pathologies on post-translational modification of Arc in brains from mouse model of
AD and humans.
56
Figure 18: Arc immunoprecipites contain serine- and tyrosine- but not
threonine-phosphorylated Arc in the HF and PFC.
a: Immunopurified Arc from HF is phosphorylated at both serine and
tyrosine but not threonine sites.
b: Immunopurified Arc from PFC is phosphorylated at both serine and
tyrosine but not threonine sites.
57
Figure 19: Immunoprecipitation with antibodies against the indicated
phosphoepitopes in the HF and PFC from WT mice.
Anti-pS and anti-pY but not anti-pT immunoprecipitates contain
phosphorylatedArc in both HF and PFC.
58
3a) Phosphorylation of Arc at serine (pS) and tyrosine (pY) is responsive to
receptor stimulation.
The phosphorylation states of Arc in the HF and PFC of both 3xTg AD and WT mice at
varying ages (4-, 6-, 10-, and 15-months old) under non-stimulated, basal conditions and following
stimulation of the NMDARs and IRs respectively by NMDA/glycine and insulin, was assessed in
the anti-Arc immunoprecipitates by Western blotting using phosphoepitope-specific antibodies.
Similarly, we also determined the phosphorylation states of Arc in postmortem human HF from
non-demented controls, MCI-SNAP, MCI-AD, and AD subjects (n=8) under non-stimulated basal
conditions and following stimulation by NMDA/glycine, insulin, BDNF and PNU 282987. The
data shown in figure 20-23 indicate that Arc is phosphorylated on tyrosine (Y) and Serine (S) but
not threonine (T) sites in mouse HF and PFC and postmortem human HF. Arc phosphorylation
on tyrosine and serine is increased following activation by all stimuli tested in both mouse and
human samples, suggesting that Arc’s function is regulated by phosphorylation.
3b) Arc phosphorylation states are altered during normal aging and in AD
pathogenesis.
Under the non-stimulated basal condition, pY- and pS-Arc levels are increased in both HF
and PFC of wild-type mice at age ≥ 10-month of age as well as all ages of 3xTg AD mice. In
accord with the reduced receptor stimulation induced Arc expression in old WT and 3xTg AD
mice, activity-dependent pY- and pS-Arc is reduced in an age- and disease pathology-dependent
manner. 3xTg AD mice exhibited greater elevations in basal Arc phosphorylation and greater
reductions in activity-dependent Arc phosphorylation compared to age-matched WT. This is most
evident in the 10- and 15-month old 3xTg AD mice (relative to the WT).
Phosphorylation of Arc is also observed in postmortem human HF. The data shown in
figure 22 indicate that under the non-stimulated basal condition, pY- and pS-Arc levels are
59
increased in MCI-SNAP and AD cases and activation-dependent pY- and pS-Arc is reduced in
MCI-AD, MCI-SNAP and most severely in AD.
These results indicate for the first time that Arc function is modulated by phosphorylation,
and these phosphorylation states are modified by advancing age and progression of AD
pathologies. The fact that changes in Arc phosphorylation are similar in pattern to the alterations
in basal and activity-dependent Arc expression, strongly suggests that phosphorylation is a
physiological feedback regulatory mechanism of Arc. The elevated levels of pS- and pY-Arc are
likely the result of a dysfunctional protein phosphatase system that is failing to dephosphorylate
Arc and other proteins at old age and in pathological conditions such as AD, thereby leading to its
accumulation.
60
a)
b)
-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
+
+
4M-WT
IP:
An
ti-A
rc
An
ti-A
cti
n55
35
+
+
+
+
+
+
+
+
+
+
+
+
6M-WT 6M-TG 10M-WT 10M-TG 15M-WT 15M-TG
pY-Arc55
NY-Arc
55
55
55
pT-Arc
0
0.25
0.5
0.75
1
1.25
0
200
400
600
800
pS
-Arc
/-A
cti
n r
ati
o%
In
cre
as
e
4-month
WT
6-month
WT
6-month
TG
10-month
WT
10-month
TG
15-month
WT
15-month
TG
*
**
**
**
*
*
*
*
**
*
**
** *++ ++
# #
#
#
# ## #
# #
++^^
^
^
0
0.25
0.5
0.75
1
1.25
0
200
400
600
800
pY
-Arc
/-A
cti
n r
ati
o%
In
cre
as
e
4-month
WT
6-month
WT
6-month
TG
10-month
WT
10-month
TG
15-month
WT
15-month
TG
*
***
* **
**
*
* *
*
**
*
**
# # # # # ## #
^ ^
^
Figure 20: Basal and activity dependent Arc phosphorylation expression are altered in HF
of aged WT and 3xTg AD mice.
a: Representative blots showing basal and activation-induced Arc phosphorylation expression in
HF of aged wild-type (WT) and 3x AD transgenic (TG) mice.
b: Quantitative assessment of basal and activity dependent changes in Arc phosphorylations in 5
sets of 4-, 6-, 10-, and 15-month 3xTg AD mice with age matched WT. Data are expressed as the
mean ± SEM of Arc/β-Actin optical density ratios or % increase above basal Arc expression under
non-stimulated, Kreb’s-Ringer incubated condition. LEFT: pY-Arc, RIGHT: pS-Arc
β-Actin levels are used as the immunoprecipitation/loading controls. HF = Hippocampal
Formation, PFC = Prefrontal Cortex.
61
-Actin
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
+
+
4M-WTIP
: A
nti
-Arc
An
ti-A
cti
n
55
35
+
+
+
+
+
+
+
+
+
+
+
+
6M-WT 6M-TG 10M-WT 10M-TG 15M-WT 15M-TG
pS-Arc
pY-Arc55
NY-Arc
55
55
55
pT-Arc
0
0.25
0.5
0.75
1
0
200
400
600
800p
S-A
rc/
-Acti
n r
ati
o%
In
cre
as
e
4-month
WT
6-month
WT
6-month
TG
10-month
WT
10-month
TG
15-month
WT
15-month
TG
** **
****
* * ** * *
*
*
**
*
# #
# #
### #
# #
^^^^
^
pY
-Arc
/-A
cti
n r
ati
o
0
0.25
0.5
0.75
1
0
200
400
600
800
% I
ncre
as
e
# #
# #
# #
# #
# #
4-month
WT
6-month
WT
6-month
TG
10-month
WT
10-month
TG
15-month
WT
15-month
TG
** **** ** * * ** * *
* *
*
*^
*
a)
b)
Figure 21: Basal and activity dependent Arc phosphorylation expression are altered in PFC of aged WT and
3xTg AD mice.
a: Representative blots showing basal and activation-induced Arc phosphorylation expression in PFC of aged wild-
type (WT) and 3x AD transgenic (TG) mice.
b: Quantitative assessment of basal and activity dependent changes in Arc phosphorylations in 5 sets of 4-, 6-, 10-,
and 15-month 3xTg AD mice with age matched WT. Data are expressed as the mean ± SEM of Arc/β-Actin optical
density ratios or % increase above basal Arc expression under non-stimulated, Kreb’s-Ringer incubated condition.
LEFT: pY-Arc, RIGHT: pS-Arc
β-Actin levels are used as the immunoprecipitation/loading controls. PFC = Prefrontal Cortex.
62
Figure 22: Human HF shows disease dependent changes in Arc phosphorylation expression.
a) Representative blots showing pY- and pS-Arc increase in response to indicated stimuli.
b) Quantitative assessment of basal and activity dependent changes in Arc phosphorylations in 8 sets of HF from age matched
cognitive normal controls and disease cohorts. While pY- and pS-Arc levels are increased in MCI-SNAP and AD, the
activation-induced tyrosine- and serine-phosphorylation of Arc is reduced in MCI-AD, MCI-SNAP and AD comparing to
controls.
Data are expressed as the mean ± SEM of Arc/β-Actin optical density ratios or % increase above basal Arc expression under
non-stimulated, Kreb’s-Ringer incubated condition. β-Actin levels are used as the immunoprecipitation/loading controls. pY-Arc: phosphotyrosine modified Arc; pS-Arc: phosphoserine-Arc. MCI-AD: amnestic MCI; MCI-SNAP: non-amnestic
MCI; AD: Alzheimer’s disease; HF = Hippocampal Formation. β-Actin levels serve as the immunoprecipitation/loading
controls.
-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
BDNF (50ng/ml):
+
+
+
Control
+
+
+
MCI-AD
+
+
+
MCI-SNAP
+
+
+
AD
55
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
PNU282987(0.1 μM):++++
pT-Arc55
pY-Arc55
NY-Arc55
-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
BDNF (50ng/ml):
+
+
+
Control
+
+
+
MCI-AD
+
+
+
MCI-SNAP
+
+
+
AD
55
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
PNU282987(0.1 μM):++++
pT-Arc55
pY-Arc55
NY-Arc55
-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
BDNF (50ng/ml):
+
+
+
Control
+
+
+
MCI-AD
+
+
+
MCI-SNAP
+
+
+
AD
55
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
PNU282987(0.1 μM):++++
pT-Arc55
pY-Arc55
NY-Arc55
a)
b)
Kreb’s Ringer
NMDA/Glycine
Insulin
BDNF
PNU282987
63
-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
+
+
4M-WT
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
+
+
+
+
+
+
+
+
+
+
+
+
6M-WT 6M-TG 10M-WT 10M-TG 15M-WT 15M-TG
pY-Arc55
NY-Arc
55
55
55
pT-Arc
-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
+
+
4M-WT
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
+
+
+
+
+
+
+
+
+
+
+
+
6M-WT 6M-TG 10M-WT 10M-TG 15M-WT 15M-TG
pY-Arc55
NY-Arc
55
55
55
pT-Arc
-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
+
+
4M-WT
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
+
+
+
+
+
+
+
+
+
+
+
+
6M-WT 6M-TG 10M-WT 10M-TG 15M-WT 15M-TG
pY-Arc55
NY-Arc
55
55
55
pT-Arc
-Actin
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
+
+
4M-WT
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
+
+
+
+
+
+
+
+
+
+
+
+
6M-WT 6M-TG 10M-WT 10M-TG 15M-WT 15M-TG
pS-Arc
pY-Arc55
NY-Arc
55
55
55
pT-Arc
-Actin
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
+
+
4M-WT
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
+
+
+
+
+
+
+
+
+
+
+
+
6M-WT 6M-TG 10M-WT 10M-TG 15M-WT 15M-TG
pS-Arc
pY-Arc55
NY-Arc
55
55
55
pT-Arc
-Actin
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
+
+
4M-WT
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
+
+
+
+
+
+
+
+
+
+
+
+
6M-WT 6M-TG 10M-WT 10M-TG 15M-WT 15M-TG
pS-Arc
pY-Arc55
NY-Arc
55
55
55
pT-Arc
-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
BDNF (50ng/ml):
+
+
+
Control
+
+
+
MCI-AD
+
+
+
MCI-SNAP
+
+
+
AD
55
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
PNU282987(0.1 μM):++++
pT-Arc55
pY-Arc55
NY-Arc55
-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
BDNF (50ng/ml):
+
+
+
Control
+
+
+
MCI-AD
+
+
+
MCI-SNAP
+
+
+
AD
55
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
PNU282987(0.1 μM):++++
pT-Arc55
pY-Arc55
NY-Arc55
-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
BDNF (50ng/ml):
+
+
+
Control
+
+
+
MCI-AD
+
+
+
MCI-SNAP
+
+
+
AD
55
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
PNU282987(0.1 μM):++++
pT-Arc55
pY-Arc55
NY-Arc55
a)
c)
b)
Figure 23 a-c: Arc does not show phosphorylation on the phosphoThreonine epitope.
pT: phosphoThreonine-Arc; Representative blots showing pT-Arc is not present in basal, unstimulated conditions and does not
increase in response to indicated stimuli in either mice or human samples. MCI-AD: amnestic MCI; MCI-SNAP: non-amnestic
MCI; AD: Alzheimer’s disease. β-Actin levels serve as the immunoprecipitation/loading controls.
64
4) Nitration of Arc indicates oxidative stress occurs during AD pathogenesis
modifies Arc.
Oxidative stress is one of the most common and well documented pathogenic processes in
aging and neurodegenerative disorders146. The high level of reactive oxygen species (ROS) is
associated with synaptic damage and causes functional defects in affected proteins. To determine
whether Arc is influenced by oxidative stress, the level of nitration of Arc estimated by the
abundance of nitrotyrosine in immunopurified Arc was determined by Western blotting with a
specific antibody directed against nitrotyrosine. The level of nitrotyrosine on Arc was measured
under non-stimulated, basal conditions and following receptor activation in the immunopurified
Arc from WT and 3xTg AD mice as well as human postmortem disease. The data shown in figure
24 indicate that elevated nitrated Arc is evidenced in WT at age ≥10-month of age and 3xTg AD
mice without effects from receptor stimulation. The nitrated Arc levels in both brain regions of
3xTg AD mice are markedly higher comparing to their nitrated Arc expression levels relative to
age-matched WT (figure 24). These data suggests that the heightened oxidative stress during AD
pathogenesis can destroy Arc’s function thereby limiting Arc’s responsiveness to receptor
stimulation. The fact that nitrated Arc levels are much higher in HF compared to PFC may suggest
that HF has a greater severity in oxidative damage (figure 24b). The human postmortem tissue
results support the idea that oxidative stress correlates with AD pathologies since nitrated Arc is
absent in MCI-SNAP cases and the levels of nitrated Arc is lower in MCI-AD than AD (figure
25). These results demonstrate for the first time that Arc is modified by oxidative stress in MCI-
AD and AD. The levels of nitrated Arc may be used to gauge the severity of oxidative stress and
AD pathologies.
65
-Actin
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
+
+
4M-WT
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
+
+
+
+
+
+
+
+
+
+
+
+
6M-WT 6M-TG 10M-WT 10M-TG 15M-WT 15M-TG
pS-Arc
pY-Arc55
NY-Arc
55
55
55
pT-Arc-Actin
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
+
+
4M-WT
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
+
+
+
+
+
+
+
+
+
+
+
+
6M-WT 6M-TG 10M-WT 10M-TG 15M-WT 15M-TG
pS-Arc
pY-Arc55
NY-Arc
55
55
55
pT-Arc
-Actin
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
+
+
4M-WT
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
+
+
+
+
+
+
+
+
+
+
+
+
6M-WT 6M-TG 10M-WT 10M-TG 15M-WT 15M-TG
pS-Arc
pY-Arc55
NY-Arc
55
55
55
pT-Arc
0
0.25
0.5
0.75
1
NY
-Arc
/-A
cti
n r
ati
o
4-month
WT
6-month
WT
6-month
TG
10-month
WT
10-month
TG
15-month
WT
15-month
TG
*** *** ** *
***
** *
###
## #
^^^## #
## #
## #
-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
+
+
4M-WT
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
+
+
+
+
+
+
+
+
+
+
+
+
6M-WT 6M-TG 10M-WT 10M-TG 15M-WT 15M-TG
pY-Arc55
NY-Arc
55
55
55
pT-Arc-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
+
+
4M-WT
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
+
+
+
+
+
+
+
+
+
+
+
+
6M-WT 6M-TG 10M-WT 10M-TG 15M-WT 15M-TG
pY-Arc55
NY-Arc
55
55
55
pT-Arc
-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
+
+
4M-WT
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
+
+
+
+
+
+
+
+
+
+
+
+
6M-WT 6M-TG 10M-WT 10M-TG 15M-WT 15M-TG
pY-Arc55
NY-Arc
55
55
55
pT-Arc
0
0.25
0.5
0.75
1
4-month
WT
6-month
WT
6-month
TG
10-month
WT
10-month
TG
15-month
WT
15-month
TG
***
NY
-Arc
/-A
cti
n r
ati
o
* **
* **
***##
#
## #
## ### #
^^^
Figure 24: Arc is modified by nitration in the HF and PFC of WT and 3xTg AD animals.
a: Representative blots showing nitrated Arc under basal and stimulation conditions in HF of aged wild-type
(WT) and 3x AD transgenic (TG) mice.
b: Quantitative assessment of basal and activity dependent changes in nY-Arc of 4-, 6-, 10-, and 15-month 3xTg
AD mice with age-matched WT. Data are expressed as the mean ± SEM of Arc/β-Actin optical density ratios or
% increase above basal Arc expression under non-stimulated, Kreb’s-Ringer incubated condition. LEFT: pY-
Arc, RIGHT: pS-Arc
β-Actin levels are used as the immunoprecipitation/loading controls. HF = Hippocampal Formation, PFC =
Prefrontal Cortex.
a)
b)
66
-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
BDNF (50ng/ml):
+
+
+
Control
+
+
+
MCI-AD
+
+
+
MCI-SNAP
+
+
+
AD
55
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
PNU282987(0.1 μM):++++
pT-Arc55
pY-Arc55
NY-Arc55
-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
BDNF (50ng/ml):
+
+
+
Control
+
+
+
MCI-AD
+
+
+
MCI-SNAP
+
+
+
AD
55
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
PNU282987(0.1 μM):++++
pT-Arc55
pY-Arc55
NY-Arc55
-Actin
pS-Arc
NMDA (10 μM) /Glycine (1 μM):
Insulin (1nM):
BDNF (50ng/ml):
+
+
+
Control
+
+
+
MCI-AD
+
+
+
MCI-SNAP
+
+
+
AD
55
IP:
An
ti-A
rc
An
ti-A
cti
n
55
35
PNU282987(0.1 μM):++++
pT-Arc55
pY-Arc55
NY-Arc55
Figure 25: Arc is modified by nitration in the human postmortem HF.
a: Representative blot showing nitration of Arc under basal and stimulated conditions in HF
from cognitive normal control, NY-Arc: Nitrotyrosine-Arc; MCI-AD: amnestic MCI; MCI-
SNAP: non-amnestic MCI; AD: Alzheimer’s disease. β-Actin serves as the loading control.
b: Quantitative assessment of nitrated Arc under basal and stimulation conditions in human
postmortem HF. Data are expressed as the mean ± SEM of Arc/β-Actin optical density ratios or
% increase above basal Arc expression under non-stimulated, Kreb’s-Ringer incubated
condition. β-Actin levels are used as the immunoprecipitation/loading controls. HF =
Hippocampal Formation.
Kreb’s Ringer
NMDA/Glycine
Insulin
BDNF
PNU282987
a)
b)
67
5) Altered Arc connection with key signaling cascades during aging and AD
pathogenesis contributes to its altered phosphorylation and dysfunction.
The fact that Arc is phosphorylated in response to receptor stimulation suggests that Arc is
associated with key signaling pathways in the postsynaptic density (PSD). To test this hypothesis,
we conducted an Arc co-IP experiment and first probed for key scaffold proteins and their
associated signaling molecules in aged 3xTg AD and WT mice. To achieve equal Arc protein
levels, the input anti-Arc immunoprecipitates for WT and 3xTg AD mice were adjusted according
to their Arc levels under basal conditions (figure 16). Our data presented in figures 27 and 28
indicate that Arc is predominantly associated with NMDARs and also Filamin A (FLNA) to a
lesser extent in both HF and PFC from young (< 6-month of age) WT mice. While the Arc and
PSD-95/NMDAR linkage is supported by the high levels of obligatory NR1 subunits and
regulatory NR2A subunits and scaffolding protein, PSD-95, Arc-FLNA connection is indicated by
the presence of JAK2, PAK1, PTEN and PP2A along with FLNA (figure 26). As the age increased
(≥10-month of age) in WT and especially with AD pathogenesis in 3xTg AD mice, the Arc-FLNA
connection is strengthened together with reduction in Arc-PSD-95/NMDAR linkage (figure 26-
28). Such rearrangement in binding partners for Arc during normal aging and in AD pathogenesis
may indicate age- and disease-related changes in regulatory mechanisms for Arc and possibly
consequent altered synaptic plasticity and dendritic dynamics.
NMDAR signaling complexes play an important role in the regulation of synaptic plasticity
in the postsynaptic density. NMDA receptors signaling dysfunction is linked to synaptic defects
and dendritic abnormalities in the AD pathogenesis and to a lesser extent during the aging
process51, 53, 54. This receptor functional downregulation appears to cause derangement of the
postsynaptic density with specifically, reduction of NR1 and NR2 levels158, ,159. The defects in
postsynaptic density during aging and in AD are supported by the data from the present study
68
showing reduced Arc associated NR1, NR2A and PSD-95 in 3xTg AD and to a lesser extent in
aged (≥ 10-month of age) WT mice. Consistent with the interaction of PSD95 with NR2A, PSD‐
95 may be required for NMDAR localization to synapses160,161. The NMDAR dysfunction coupled
with diminished Arc-NMDAR connections can lead to reduced LTP and failed synaptic activation
resulting in eventual cognitive impairments in elderly and AD.
Filamin A (FLNA) is a critical scaffolding protein that is associated with and regulates
dozens of receptors and signaling molecules and intracellular protein trafficking by modulating
actin polymerization166. FLNA is associated constitutively with the insulin receptor166. Altered
FLNA conformation in aging and AD is a critical mechanism of disease pathogenesis77. Among
key kinases of interest in the regulation of Arc is Jak2, a non-receptor tyrosine kinase linking to
FLNA166. Jak2, along with its primary downstream target, Stat3, are both located in dendritic
spines. The Jak2-Stat3 pathway has been implicated in synaptic plasticity.163 Pak1 is a member of
the conserved p21-activated serine-threonine kinase family and is a cytoplasmic protein that is
recruited to the membrane upon activation. Phosphatase and tensin homolog deleted on
chromosome 10 (PTEN) is a tyrosine phosphatase that has been extensively characterized for its
central role in cancer, but has also been implicated in ASDs and other diseases. PTEN has been
shown to be a critical link between Aβ and postsynaptic depression, although the mechanism of
this function is unclear156,157. Here, we show that the levels of FLNA-associated PTEN were
decreased with age in WT animals and an even more robust reduction observed in FLNA-
associated PTEN levels in 3xTg AD mice. The serine/threonine protein phosphatase PP2A is a
protein comprised of scaffold, catalytic and regulatory subunits. Reduced function of PP2A has
been implicated in the disrupted L-LTD in AD. Similar to PTEN, decreased FLNA-linked PP2A
69
as indicated by reduced PP2A-Cα/β was noted in the brains of aged WT at ≥ 10-month-old with
even greater reduction in the brains of 3xTg AD mice.
Together, the data presented confirm previous report that Arc is in the NMDAR signaling
complex and indicate for the first time that Arc is primarily associated with NMDARs and also
with FLNA signaling pathways as its physiological regulators. While the Arc-NMDAR
connection is deteriorated during normal aging and more robust with the presence of AD
pathologies, Arc-FLNA association is dramatically increased in AD and to a less extent in WT
mice at the age ≥ 10-month of age. Such alteration in Arc’s binding partners indicates a shift in
its regulation during pathogenic progression that may be significantly related with synaptic defects
in AD and aged brains.
70
Filamin A
JAK2
PAK1
PTEN
PP2A-C/
NR2A
PSD-95
NR1
100
100
130
35
55
70
70
250IP
: A
nti
-Arc
4 Month W
T
6 Month W
T
6 Month 3xTG
10 Month W
T
10 Month 3xTG
15 Month W
T
15 Month 3xTG
Arc55
Figure 26: Altered Arc linkages with signaling complexes in aged and 3xTg AD
mice.
Arc association with its interactors are altered in the HF and PFC of 3xTg AD mice
compared to WT controls. Tissue lysates were IP’ed for Arc complexes and probed for
FLNA, JAK2, PAK1, PTEN, PP2A-Cα/β, NR2A, NR1, and PSD95 by immunoblotting.
71
Figure 27: Altered Arc linkages with signaling complexes in the HF of aged and
3xTg AD mice.
Arc association with its interactors are altered in the HF of 3xTg AD mice compared to
WT controls. HF tissue lysates were IP’ed for Arc complexes and probed for FLNA,
JAK2, PAK1, PTEN, PP2A-Cα/β, NR2A, NR1, and PSD95 by immunoblotting.
72
Figure 28: Altered Arc linkages with signaling complexes in the PFC of aged and
3xTg AD mice.
Arc association with its interactors are altered in the PFC of 3xTg AD mice compared to
WT controls. HF tissue lysates were IP’ed for Arc complexes and probed for FLNA,
JAK2, PAK1, PTEN, PP2A-Cα/β, NR2A, NR1, and PSD95 by immunoblotting.
73
6) Regulation of Arc by Phosphorylation is mediated by PKC/Src and
JAK2/PAK1 associated respectively with NMDARs and FLNA
The data showing Arc is regulated by phosphorylation of tyrosine and serine and the
revelation of Arc’s connection with NMDAR and FLNA signaling cascades suggest that kinases
associated with these signaling pathways are involved in phosphorylation of Arc. To test this
hypothesis, we incubated HF and PFC tissues with specific enzyme inhibitors.
Accordingly, HF and PFC slices from 6-month-old wild-type mice were incubated with
selected kinase inhibitors (table 1): Chelerythrine (PKC), PP1 (Src), Tryphostin B42 (JAK2) or
NVS PAK1 (PAK1) prior to exposure to either NMDA (10μM) + Glycine (1 μM) or Insulin (1nM).
PP1 is a potent, reversible and selective inhibitor of the Src family of protein tyrosine kinases.
Chelerythrine is a potent inhibitor of PKC. As expected, PP1 blocks NMDA/glycine-induced
tyrosine phosphorylation of Arc only (figures 29, 30). In contrast, inhibition of PKC by
chelerythrine blocks NMDA/glycine-induced phosphorylation of Arc on both tyrosine and serine
(figures 29, 30). This result is in accord with the previous observation that PKC can activate Src
via PyK2 in the NMDAR signaling163,164.
In addition, we also tested the role for kinases associated with FLNA in the regulation of
Arc by phosphorylation induced by insulin. Selectively inhibiting JAK2 by pre-treatment with
Tyrphostin B42 blocks insulin-induced phosphorylation of Arc on both tyrosine and serine sites.
In contrast, pretreatment with NVS PAK1, an allosteric inhibitor of p21-activated kinases prevents
insulin-induced serine phosphorylation exclusively. In agreement with an earlier report165, our
present data indicate that JAK2 is an upstream regulator of PAK1 in the FLNA signaling
cascade165.
74
Taken together, the data obtained using kinase inhibitors support the notion that Arc is
regulated by phosphorylation mediated through activation of NMDAR and FLNA signaling
pathways.
Name Target
PP1 Src family Tyrosine Kinase Inhibitor
Chelerythrine Potent inhibitor of Protein Kinase C (Ser/Thr)
Tyrphostin B42 Inhibitor of Jak2 (Tyr)
NVS PAK1 Potent allosteric inhibitor of PAK1 (Ser/Thr)
Table 1: Pharmacological agents used and targets of action.
75
Figure 29: Identification of critical
kinases responsible for pS-Arc and pY-
Arc in HF.
a: Representative blot showing pS-Arc and
pY-Arc in HF under stimulated conditions.
Tissue was treated with different enzyme
inhibitors to measure phosphorylation levels.
b: Quantitative assessment of stimulation
dependent changes in Arc phosphorylations
due to addition of kinase inhibitors in HF of
mice.
HF = Hippocampal Formation.
a)
b)
76
Figure 30: Revelation of the kinases that
mediateArc phosphorylation in PFC.
a: Representative blot showing pS-Arc and pY-
Arc in PFC under stimulated conditions. Tissue
was treated with different enzyme inhibitors to
measure phosphorylation levels.
b: Quantitative assessment of stimulation
dependent changes in Arc phosphorylations due
to addition of kinase inhibitors in PFC of mice.
PFC = Prefrontal Cortex
a)
b)
77
Conclusions
Deterioration in activity-dependent synaptic function during the aging process has been
proposed to be a risk factor in neurological disorders and especially in neurodegenerative diseases
with cognitive impairment. However, the underlying mechanisms remain largely unresolved
although defective synaptic regulatory mechanisms are likely involved. The postsynaptic activity
is modulated by the prominent regulatory protein Arc. Arc plays a critical role in regulation of
learning and memory by modulating stimulation-induced synaptic activity leading to L-LTP and
dendritic remodeling81-83. Given the pivotal role of Arc in sculpting neuronal function, in this thesis
project I studied the molecular mechanisms that regulate Arc expression. In particular, I examined
Arc under activity-dependent conditions during aging and in diseases of cognitive impairment
using two brain regions from a mouse model of AD and postmortem human HF tissue.
We demonstrate that in response to stimulation of the various neuronal receptors located
in the dendritic field, Arc expression dramatically increased in both brain regions of mice and in
postmortem human HF. The time frame of this rapid activity-elicited Arc expression is in
agreement with previous findings that mRNA for Arc is localized in the synaptic/dendritic field
rather than synthesized in the cell bodies and then shipped to the synapses for local activity172, 173.
Most importantly, we presented evidence that activity-dependent Arc expression is reduced during
the aging process and in the MCI phase with or without AD pathologies and most severely in AD.
The graded reduction in brains from aged, MCI and AD cases support the notion that age-related
deterioration of Arc responsiveness to stimuli is an integral part of synaptic/dendritic dysfunction.
In accord with the reduced receptor stimulation induced Arc expression, defected NMDAR,
α7nAChR and IR function have all been demonstrated in aged and AD brains174, 53, 54, 159. In
contrast, an increased TrkB activity in AD has been noted175. The reduced BDNF-induced Arc
78
expression in AD therefore supports the notion that synaptic activation by the activated TrkB is
mediated by the NMDARs through pY-TrkB-NMDAR linkage as previously demonstrated in
earlier studies175. The defected activity-dependent Arc expression in AD and MCI-SNAP but not
MCI-AD is accompanied by an elevated Arc protein level. These data suggest that basal Arc
protein level is driven by adaptive increases in Arc gene expression in cell bodies. Further, these
increases are related to the magnitude and/or dimension of synaptic dysfunction and/or destruction
rather than directly linked to the reduced activity-evoked Arc expression. In this regard, the
magnitude of synaptic dysfunction in the brains of MCI-AD is milder compared to AD and
therefore, most likely occurs earlier during AD pathogenesis elicited by Aβ, especially Aβ42. In
addition to the AD pathogenesis, reduced receptor function was also observed in the brains of
MCI-SNAP cases that are without significantly higher AD pathologies than their age-matched
peers. Hence, dampened activity-dependent Arc expression can be induced by pathological
changes other than, or in addition to, Aβ. The fact that impaired synaptic functions were observed
to be mediated, at least in part, by a failure to promote Arc expression by activation of multiple
receptors may suggest the damage occurs to common mechanisms required for receptor operation
such as adequate mitochondrial function, healthy synaptic membranes. Alternatively, reduced Arc
mRNA levels, resulting from: a failure to transport mRNA from cell bodies to the synaptic field,
improper mRNA storage, mRNA protection and/or defects in translational machinery may also
play a role in reduction in activity-driven Arc expression. Clearly, further research is required to
elucidate these unknowns.
Although activity-induced Arc expression has been well-established, the fate of Arc protein
once it is synthesized is largely unknown. We paid particular attention to the most common post-
translational modification: phosphorylation since phosphorylation of a protein not only changes
79
its behavior and disposal but also reflects its inter-relationship to and health of specific signaling
pathways. We show here, for the first time, that Arc is phosphorylated at tyrosine and serine but
not threonine sites. The fact that the levels of tyrosine- and serine-phosphorylated Arc increase
proportionally following receptor stimulation suggest that phosphorylation of Arc is a
physiological regulator of Arc that likely influences its function, localization, disposal and/or
interaction with its binding partners. The reduced activity-driven Arc phosphorylation in the brains
of MCI and AD cases as well as in 3xTg AD and aged WT mice indicate that Arc is tightly
regulated and closely associated with the synaptic activities. The highly coordinated
phosphorylation of Arc suggests that Arc is phosphorylated by the kinases within the signaling
pathways located in close proximity of or even physically associated with Arc. This hypothesis is
supported by our data showing that Arc is physically associated with the NMDARs probably
through PSD-95 and FLNA as Arc can be co-immunoprecipitated with PSD-95 and FLNA
although PSD-95 and FLNA are not directly connected. These data indicate there are at least two
populations of Arc located in close proximity but not physically associated with each other that
serve to modulate the synaptic activities within different synaptic/dendritic microdomains. In
accord, PSD-95 and its linked NMDARs are found in dendritic spines whereas FLNA is
predominantly located in dendritic shaft176, 177.
In an effort to elucidate the protein kinases that phosphorylate Arc, we induced Arc
phosphorylation by stimulation with NMDA/glycine and insulin to activate NMDARs and IRs,
respectively. Confirmed using selective kinase inhibitors, our data indicate that PKC and Src
tyrosine kinase are responsible for PSD-95 linked NMDAR activation induced Arc
phosphorylation, whereas JAK2 and PAK1 mediate FLNA-associated IR activation by insulin.
Blockade of PKC reduces both serine- and tyrosine phosphorylation of Arc confirming that PKC
80
activation can activate Src, as shown previously178. Inhibition of JAK2 prevents insulin-induced
tyrosine- and serine-phosphorylation on Arc thus demonstrating PAK1 can be activated by JAK2
activation166. Since Arc is synthesized on demand to orchestrate the dendritic remodeling in
response to increases in synaptic activities, phosphorylation of Arc with the kinases within the
signaling pathways may represent a mechanism to provide close monitoring of the selective
synaptic/dendritic regions by improving Arc’s interaction with specific protein(s) in the synapse
and/or ability to translocate to specific dendritic fields to monitor synaptic activity.
Most importantly, our data show that during aging and more prominently in AD, there is a
shift in the Arc connections from PSD-95/NMDARs to FLNA. This rearrangement of Arc
association during aging and in AD pathogenesis appears to occur gradually to provide a prominent
underlying mechanism by which the diminished Arc in the dendritic spines mediates deleterious
synaptic activities. Together with the data showing ex vivo exposure to Aβ42 markedly reduces
NMDA/glycine-induced Arc expression54, our data suggests that the increased Aβ42-elicited
pathology during AD pathogenesis reduces NMDAR signal transduction and disrupts Arc-PSD-
95/NMDAR linkage but promotes Arc-FLNA interaction leading to the dominant presence of Arc
in the FLNA signaling complexes. The reduced PTEN and PP2A in the FLNA signaling complexes
from 3x Tg AD mice and AD may, at least in part, be responsible for the elevated phosphorylated
Arc under basal conditions in AD.
An altered conformation of FLNA is closely linked to the amyloid and tau pathologies in
AD54. The altered FLNA can be induced by Aβ monomers or small oligomers since aberrant
FLNA is found prevalently in mice infused intracerebroventicularly with soluble Aβ54. In AD and
to a lesser extent aged brains, Aβ42 binding to α7nAChRs and TLR4 (CD14) recruits FLNA to
promote sustained Aβ42 toxic signaling to accelerate neurofibrillary lesions and
81
neuroinflammation, respectively53, 54. The abnormal FLNA may also play a role in insulin
resistance prevalently present in AD159. Hence, in addition to increased Aβ piling onto α7nAChRs,
the aberrant FLNA with altered conformation may also cause accumulation of Arc in the FLNA
associated signaling pathways including α7nAChRs, TLR4 and IRs.
It has been well-established that elevated Aβ monomers or small oligomers in AD
destabilize mitochondria, leading to oxidative stress and production of ROS/RNS that
deleteriously modify the function of multiple proteins such as tau. In this study, we show for the
first time that ROS/RNS also modify Arc as indicated by the presence of nitrated Arc in AD and
MCI-AD (but not MCI-SNAP). The oxidative stress modified Arc was also present in 3xTg AD
and to a lesser extent aged WT mice. The differential nitration of Arc observed in the HF and PFC
of the 3xTg AD mice suggests that susceptibility to oxidative stress is different in these two brain
regions. These data lend support to the notion that defected Arc plays a significant role in
mediating neuronal dysfunction induced by the escalated pathologies induced by soluble Aβ.
While the precise effect of nitration on Arc remains elusive, it is highly conceivable that nitration
on Arc impairs Arc’s function and consequently synaptic transmission and dendritic remodeling.
Lastly, reduction in activity-dependent Arc together with higher basal Arc expression are
observed in the brains from MCI-SNAP patients. Since the levels of Arc-PSD-95/NMDAR or -
FLNA connections in the MCI-SNAP cases are comparable to controls and there is no evidence
Arc is nitrated, the reduced activity-evoked Arc expression in MCI-SNAP is unlikely the result of
escalated Aβ-induced AD pathologies. Hence, the underlying mechanism(s) responsible for the
reduced receptor activation driven Arc is not known although universal attenuation of activity-
induced Arc expression across 4 distinct receptors suggests that defects in common factor(s) that
82
are vital to proper receptor function such as altered membrane fluidity may be the primary culprit.
Future studies are clearly required to fully address this change.
In summary, our results support the notion that activity-dependent Arc expression is a
pivotal event in the modulation of postsynaptic activities and dendritic remodeling to not only
meet the demands of a rapidly changing neuronal environment but also to support long-term
neuronal function such as memory consolidation. The data presented indicate that changes in
activity-dependent Arc expression as well as Arc’s regulation and connections during aging and
in diseases with cognitive impairment, especially AD, play an essential role in mediating decline
in postsynaptic/dendritic activity, diminished dendritic flexibility and neurodegeneration. Based
on the observed changes in Arc expression as well as its regulation and connections during aging
and in AD, we propose a hypothetical model (figure 31) to depict pathological consequences of
altered FLNA-enabled Aβ42 signaling via α7nAChR. Soluble Aβ42 monomers or small oligomers
bind α7nAChR thereby inducing recruitment of FLNA to these receptors. Dimers of native FLNA,
coupled to insulin receptors but not to α7nAChR or TLR4, are depicted as straight rods; red curly
FLNA depicts the conformation altered form that is recruited to α7nAChR and TLR4 and possibly
also associated with IRs. Enabled by altered FLNA’s new linkages, Aβ42 activates α7nAChR to
hyperphosphorylate tau subsequently leading to neurofibrillary lesions and neurodegeneration.
While Arc is associated with both PSD-95/NMDARs and FLNAs under the physiological
conditions, the elevated Aβ also promote the translocation of Arc from PSD-95/NMDARs to
FLNAs. This change is accompanied by an enhanced inflammatory cytokine release (TNFα, IL-
1β and IL-6) by reactive astrocytes resulting from persistently activated TLR453,54. This
neuroinflammation can contribute to insulin desensitization159. Although the insulin receptor is
constitutively associated with native FLNA, it is highly plausible that altered FLNA also
83
contributes to the insulin receptor dysfunction in AD. Aβ’s aberrant signaling through α7nAChR
impairs function of α7nAChR and of downstream NMDARs thereby limiting calcium influx
through both receptors. Increasing Aβ42 piling onto α7nAChR results in internalization and
accumulation of intraneuronal Aβ42-α7nAChR complexes. The hyperphosphorylation of tau
causes tau to dissociate from microtubules, disrupting microtubule stability, axonal/dendritic
transport and neuronal function. Along with dysfunctional tau, impaired NMDARs reduce Arc
expression and LTP with heightened LTD. The diminished postsynaptic activity in the dendritic
spines resulting from reduced activity-driven Arc expression and perhaps the increased nitrated
and/or phosphorylated Arc eventually can then cause shrinkage of dendritic spines and loss of
synapses. Along the AD pathogenic progression, cognitive impairment becomes more apparent
and neuropil treads and neurofibrillary tangles are accumulated, neurons degenerated and neuritic
plaques are formed. Thus, augmentation of postsynaptic activity mediated by activity-driven Arc
expression should be considered as one of the therapeutic goals for preventing or delaying age-
associated neurological diseases especially Alzheimer’s disease.
84
Figure 31: Proposed mechanism of action of Arc.
(a) Under physiological conditions. Arc associates with native conformation FLNA (blue sticks),
Jak2, Pak1 and NMDAR in the postsynaptic density.
(b) Under pathological conditions. Aβ42 and altered FLNA (curly orange springs) cause a host of
pathological changes downstream. Significantly, Arc is uncoupled from the complex it functions
in within the PSD. This leads to the altered expression seen.
a)
b)
85
Through studying changes in Arc expression level in relation to neurotransmitter-
and/neuroregulator-driven activities, alteration in Arc protein as well as Arc’s interaction with
other synaptic and neuronal proteins, this study has shed light on the role of Arc in the pathogenic
progression in the cognition relevant brain regions of MCI and AD. In addition, by investigating
the relationship between Arc and various pathogenic factors in MCI-SNAP, MCI-AD and AD, this
study has uncovered novel mechanisms that may alter Arc’s function during the course of
Alzheimer’s disease pathogenesis that may help to illuminate the differences between MCI-SNAP
and MCI-AD. The results obtained may facilitate the development of early diagnosis of AD and
novel treatment strategies. Altogether, the data obtained will help define the role of Arc in the
progression of postsynaptic/dendritic pathologies in key cognition regulatory brain areas in
diseases with cognitive defects.
86
References
1. Harada, C. N., Natelson Love, M. C., and Triebel, K.. “Normal Cognitive Aging.” Clinics in
geriatric medicine 29.4: 737–752. PMC. (2013).
2. Glisky EL. Changes in Cognitive Function in Human Aging. In: Riddle DR, editor. Brain
Aging: Models, Methods, and Mechanisms. Boca Raton (FL): CRC Press/Taylor & Francis;
2007. Chapter 1. Available from: https://www.ncbi.nlm.nih.gov/books/NBK3885/
3. Shi, L., Adams, M. and Brunso-Bechtold, J. K. Subtle Alterations in Glutamatergic Synapses
Underlie the Aging-Related Decline in Hippocampal Function. In: Riddle DR, editor. Brain
Aging: Models, Methods, and Mechanisms. Boca Raton (FL): CRC Press/Taylor & Francis;
2007. Chapter 8. Available from: https://www.ncbi.nlm.nih.gov/books/NBK3885/
4. Clayton DA, et al. A hippocampal NR2B deficit can mimic age-related changes in long-term
potentiation and spatial learning in the Fischer 344 rat. J Neurosci, 22: 3628. (2002).
5. Wenk GL, Barnes CA. Regional changes in the hippocampal density of AMPA and NMDA
receptors across the lifespan of the rat. Brain Res. 885:1. (2000).
6. Potier B, et al. NMDA receptor activation in the aged rat hippocampus. Exp Gerontol. 35:1185.
(2000).
7. Bach ME, et al. Age-related defects in spatial memory are correlated with defects in the late
phase of hippocampal long-term potentiation in vitro and are attenuated by drugs that enhance
the cAMP signaling pathway. Proc Natl Acad Sci USA. 96, 5280. (1999).
8. Salat DH, Kaye JA, Janowsky JS. Prefrontal gray and white matter volumes in healthy aging
and Alzheimer disease. Archives of neurology. 56, 338–44. (1999).
9. Sullivan P, Pary R, Telang F, Rifai AH, Zubenko GS. Risk factors for white matter changes
detected by magnetic resonance imaging in the elderly. Stroke; A Journal of Cerebral
Circulation. 21, 1424–8. (1990).
10. Meier-Ruge W, Ulrich J, Bruhlmann M, Meier E. Age-related white matter atrophy in the
human brain. Annals of the New York Academy of Sciences. 673, 260–9. (1992).
11. Rogalski E, Stebbins GT, Barnes CA, et al. Age-related changes in parahippocampal white
matter integrity: a diffusion tensor imaging study. Neuropsychologia. 50, 1759–65. (2012).
12. Petersen, R.C., Smith, G.E., Waring, S.C., Ivnik, R.J., Tangalos, E.G. and Kokmen, E. Mild
cognitive impairment: clinical characterization and outcome. Archives of neurology, 56(3),
303-308 (1999).
87
13. Petersen, Ronald C. Mild cognitive impairment. New England Journal of Medicine 364 (23),
2227-2234. (2011).
14. Schott, J. M. and Petersen, R. C. New criteria for Alzheimer’s disease: which, when and why?,
Brain, 138(5), 1134–1137, (2015).
15. Petersen, R. C., Caracciolo, B., Brayne, C., Gauthier, S., Jelic, V., & Fratiglioni, L. Mild
cognitive impairment: a concept in evolution. Journal of internal medicine, 275(3), 214-228.
(2014).
16. Petersen RC, Knopman DS, Boeve BF, et al. Mild Cognitive Impairment: Ten Years Later.
Archives of neurology. 66(12), 1447-1455. doi:10.1001/archneurol.2009.266. (2009).
17. Petersen, R. C., Aisen, P. , Boeve, B. F., Geda, Y. E., Ivnik, R. J., Knopman, D. S., Mielke, M.
, Pankratz, V. S., Roberts, R. , Rocca, W. A., Weigand, S. , Weiner, M. , Wiste, H. and Jack,
C. R. Mild cognitive impairment due to Alzheimer disease in the community. Ann Neurol., 74,
199-208. (2013).
18. Albert, M.S., DeKosky, S.T., Dickson, D, et al. The diagnosis of mild cognitive impairment
due to Alzheimer's disease: recommendations from the National Institute on Aging and
Alzheimer's Association Workgroup. Alzheimers Dementia 7:270–279. (2011).
19. De Reuck, J., Deramecourt, V., Cordonnier, C., Pasquier, F., Leys, D., Maurage, C. A., and
Bordet, R. The incidence of post-mortem neurodegenerative and cerebrovascular pathology in
mixed dementia. Journal of the Neurological Sciences, 366, 164-166. (2016).
20. Barker, W.W., Luis, C.A., Kashuba, A., Luis, M., Harwood, D.G., Loewenstein, D. et al.
Relative frequencies of Alzheimer's disease, Lewy body, vascular and frontotemporal
dementia, and hippocampal sclerosis in the State of Florida Brain Bank. Alzheimer Dis Assoc
Disord. 16: 203–212 (2002).
21. Alzheimer's Association. 2018 Alzheimer's disease facts and figures. Alzheimer's & Dementia
14.3, 367-429 (2018).
22. Jellinger, K.A. The enigma of mixed dementia. Alzheimers Dementia. 3: 40–53. (2007).
23. Prince, M., Bryce, R., Albanese, E., Wimo, A., Ribeiro, W. and Ferri, C.P. The global
prevalence of dementia: A systematic review and metaanalysis. Alzheimer’s & Dementia, 9:
63–75. (2013).
24. Hebert, L.E., Weuve J, Paul, A., Scherr, P.A. and Evans, D.A. Alzheimer disease in the United
States (2010–2050) estimated using the 2010 census. Neurology, 80: 1778–1783. (2013).
25. Arevalo-Rodriguez, I, Smailagic, N, Ciapponi A, Sanchez-Perez E, Giannakou A, Roqué i
Figuls M, et al. Mini-Mental State Examination (MMSE) for the detection of Alzheimer's
88
disease and other dementias in people with mild cognitive impairment (MCI). Cochrane
Database of Systematic Reviews, 10. (2013).
26. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental
disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.
27. Folstein, M. F., Folstein, S. E., and McHugh, P. R. “Mini-mental state”: a practical method for
grading the cognitive state of patients for the clinician. Journal of psychiatric research 12(3),
189-198. (1975).
28. Creavin, S.T., Wisniewski, S., Noel-Storr, A.H., et al. Mini-Mental State Examination
(MMSE) for the detection of dementia in clinically unevaluated people aged 65 and over in
community and primary care populations. Cochrane Database of Systematic Reviews. 1. DOI:
10.1002/14651858.CD011145.pub2. (2016).
29. Roalf, D. R. et al. Comparative Accuracies of Two Common Screening Instruments for the
Classification of Alzheimer’s Disease, Mild Cognitive Impairment and Healthy Aging.
Alzheimer’s & Dementia : The Journal of the Alzheimer’s Association 9(5), 529–537. (2013).
30. Trzepacz, P.T., Hochstetler, H., Wang, S., Walker, B., Saykin A.J. and “Alzheimer’s Disease
Neuroimaging Initiative.” Relationship between the Montreal Cognitive Assessment and Mini-
Mental State Examination for Assessment of Mild Cognitive Impairment in Older Adults.
BMC Geriatrics, 15:107. (2015).
31. Albert, M.S., DeKosky, S.T., Dickson, D., Dubois, B., Feldman, H.H., Fox, N.C., Gamst, A.,
Holtzman, D.M., Jagust, W.J., Petersen, R.C. and Snyder, P.J. The diagnosis of mild cognitive
impairment due to Alzheimer’s disease: Recommendations from the National Institute on
Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer's disease.
Alzheimer's & dementia, 7(3), pp.270-279. (2011).
32. Bejjani, C., Mehanna, R., & Shah, A. Biomarkers in Alzheimer’s Disease. Directions in
Psychiatry, 36 (4), 261-281. (2016).
33. Shaw, L. M., Vanderstichele, H., Knapik‐Czajka, M., Clark, C. M., Aisen, P. S., Petersen, R.
C., ... & Dean, R. Cerebrospinal fluid biomarker signature in Alzheimer's disease
neuroimaging initiative subjects. Annals of Neurology, 65(4), 403-413. (2009).
34. Gunnarsson, M. D., Lannfelt, L., Ingelsson, M., Basun, H., & Kilander, L. (2014). High tau
levels in cerebrospinal fluid predict rapid decline and increased dementia mortality in
Alzheimer's disease. Dementia and geriatric cognitive disorders, 37(3-4), 196-206.
35. Braak, H. and Braak, E. Neuropathological stageing of Alzheimer-related changes. Acta
Neuropathologica, 82:239-259. (1991).
36. LeVine, H. and Walker, L.C., 2006. Models of Alzheimer's disease. In Handbook of Models
for Human Aging (pp. 121-134).
89
37. Bhat, A. H., Dar, K. B., Anees, S., Zargar, M. A., Masood, A., Sofi, M. A., & Ganie, S. A.
Oxidative stress, mitochondrial dysfunction and neurodegenerative diseases; a mechanistic
insight. Biomedicine & Pharmacotherapy, 74, 101-110. (2015).
38. Kim, G. H., Kim, J. E., Rhie, S. J., and Yoon, S. The role of oxidative stress in
neurodegenerative diseases. Experimental neurobiology, 24(4), 325-340. (2015).
39. Niedzielska, E., Smaga, I., Gawlik, M., Moniczewski, A., Stankowicz, P., Pera, J., & Filip, M.
Oxidative stress in neurodegenerative diseases. Molecular neurobiology, 53(6), 4094-4125.
(2016).
40. Fernandez, A.M. & Torres-Alemán, I. 2012. The many faces of insulin-like peptide signalling
in the brain. Nat. Rev. Neurosci. 13:225–239. doi:10.1038/nrn3209 (2012).
41. Arnold, S.E., Arvanitakis, Z., Macauley-Rambach, S.L., Koenig, A.M., Wang, H.Y., Ahima,
R.S., Craft, S., Gandy, S., Buettner, C., Stoeckel, L.E. and Holtzman, D.M.. Brain insulin
resistance in type 2 diabetes and Alzheimer disease: concepts and conundrums. Nature Reviews
Neurology, 14(3), 168. (2018).
42. Fraering, P.C. Structural and Functional Determinants of γ-secretase, an intramembrane
protease implicated in Alzheimer's disease. Current Genomics, 8(8), 531-549. (2007).
43. O'Brien, R. J. & Wong, P. C. Amyloid precursor protein processing and Alzheimer's disease.
Annual Review of Neuroscience, 34, 185-204. (2011).
44. Hardy, J., & Selkoe, D. J. The amyloid hypothesis of Alzheimer's disease: progress and
problems on the road to therapeutics. Science, 297(5580), 353-356. (2002).
45. Tanzi, R.E. & Bertram. L. Twenty years of the Alzheimer's disease amyloid hypothesis: a
genetic perspective. Cell, 120, 545-555. (2005).
46. McLean, C.A., Cherny, R.A., Fraser, F.W., Fuller, S.J., Smith, M.J., Vbeyreuther, K., Bush,
A.I. and Masters, C.L. Soluble pool of Aβ amyloid as a determinant of severity of
neurodegeneration in Alzheimer's disease. Annals of neurology, 46(6), 860-866. (1999).
47. Haass, C., and Selkoe, D. J. Soluble protein oligomers in neurodegeneration: lessons from the
Alzheimer's amyloid β-peptide. Nature reviews Molecular cell biology, 8(2), 101-112. (2007).
48. Näslund, J., Haroutunian, V., Mohs, R., Davis, K. L., Davies, P., Greengard, P., and Buxbaum,
J. D. Correlation between elevated levels of amyloid β-peptide in the brain and cognitive
decline. Jama, 283(12), 1571-1577. (2000).
49. Wang, H. Y., Lee, D. H., D'Andrea, M. R., Peterson, P. A., Shank, R. P., and Reitz, A. B. β-
Amyloid1–42 binds to α7 nicotinic acetylcholine receptor with high affinity implications for
Alzheimer's disease pathology. Journal of Biological Chemistry, 275(8), 5626-5632. (2000a).
90
50. Wang, H. Y., Lee, D. H., Davis, C. B., and Shank, R. P. Amyloid Peptide Aβ1‐42 Binds
Selectively and with Picomolar Affinity to α7 Nicotinic Acetylcholine Receptors. Journal of
Neurochemistry, 75(3), 1155-1161. (2000b).
51. Wang, H. Y., Stucky, A., Liu, J., Shen, C., Trocme-Thibierge, C., and Morain, P. Dissociating
β-amyloid from α7 nicotinic acetylcholine receptor by a novel therapeutic agent, S 24795,
normalizes α7 nicotinic acetylcholine and NMDA receptor function in Alzheimer's disease
brain. Journal of Neuroscience, 29(35), 10961-10973. (2009).
52. Wang, H. Y., Bakshi, K., Shen, C., Frankfurt, M., Trocmé-Thibierge, C., and Morain, P. S
24795 Limits β-Amyloid–α7 Nicotinic Receptor Interaction and Reduces Alzheimer's Disease-
Like Pathologies. Biological Psychiatry, 67(6), 522-530. (2010).
53. Wang, H. Y., Bakshi, K., Frankfurt, M., Stucky, A., Goberdhan, M., Shah, S. M., and Burns,
L. H. Reducing amyloid-related Alzheimer's disease pathogenesis by a small molecule
targeting filamin A. Journal of Neuroscience, 32(29), 9773-9784. (2012).
54. Wang, H. Y., Lee, K. C., Pei, Z., Khan, A., Bakshi, K., and Burns, L. H. PTI-125 binds and
reverses an altered conformation of filamin A to reduce Alzheimer's disease pathogenesis.
Neurobiology of Aging, 55, 99-114 (2017a).
55. Nagele, R. G., D’andrea, M. R., Anderson, W. J., and Wang, H. Y. Intracellular accumulation
of β-amyloid1–42 in neurons is facilitated by the α7 nicotinic acetylcholine receptor in
Alzheimer’s disease. Neuroscience, 110(2), 199-211. (2002).
56. Lewis, J., Dickson, D. W., Lin, W. L., Chisholm, L., Corral, A., Jones, G., ... & Eckman, C.
Enhanced neurofibrillary degeneration in transgenic mice expressing mutant tau and APP.
Science, 293(5534), 1487-1491, (2001).
57. De Strooper, B., Saftig, P., Craessaerts, K., Vanderstichele, H., Guhde, G., Annaert, W., ... &
Van Leuven, F. (1998). Deficiency of presenilin-1 inhibits the normal cleavage of amyloid
precursor protein. Nature, 391(6665), 387. (1998).
58. Wolfe, M. S., Xia, W., Ostaszewski, B. L., Diehl, T. S., Kimberly, W. T., & Selkoe, D. J. Two
transmembrane aspartates in presenilin-1 required for presenilin endoproteolysis and γ-
secretase activity. Nature, 398(6727), 513. (1999).
59. Yu, Y., Run, X., Liang, Z., Li, Y., Liu, F., Liu, Y., ... & Gong, C. X. Developmental regulation
of tau phosphorylation, tau kinases, and tau phosphatases. Journal of Neurochemistry, 108(6),
1480-1494.). (2009).
60. Kovacs, G. G. Invited review: neuropathology of tauopathies: principles and practice.
Neuropathol. Appl. Neurobiol. 41, 3–23. doi: 10.1111/nan.12208 (2015).
91
61. Clavaguera, F., Bolmont, T., Crowther, R.A., Abramowski, D., Frank, S., Probst, A., Fraser,
G., Stalder, A.K., Beibel, M., Staufenbiel, M. and Jucker, M. Transmission and spreading of
tauopathy in transgenic mouse brain. Nature Cell Biology, 11(7), p.909. (2009).
62. Nonaka, T., Masuda-Suzukake, M., Arai, T., Hasegawa, Y., Akatsu, H., Obi, T., Yoshida, M.,
Murayama, S., Mann, D.M., Akiyama, H. and Hasegawa, M., 2013. Prion-like properties of
pathological TDP-43 aggregates from diseased brains. Cell Reports, 4(1), 124-134. (2013).
63. Hasegawa, M. Molecular mechanisms in the pathogenesis of Alzheimer’s disease and
tauopathies-prion-like seeded aggregation and phosphorylation. Biomolecules, 6(2), p.24.
(2016).
64. Kandel, Eric R., et al. Principles of Neural Science. New York, McGraw-Hill Health
Professions Division, (2013).
65. Hedden, T. & Gabrieli, J.D. Insights into the ageing mind: a view from cognitive
neuroscience. Nat. Rev. Neurosci. 5, 87–96. (2004).
66. Raz, N., Gunning-Dixon, F.M., Head, D., Dupuis, J.H. & Acker, J.D. Neuroanatomical
correlates of cognitive aging: evidence from structural magnetic resonance imaging.
Neuropsychology 12, 95–114. (1998).
67. Davies, C. A., Mann, D. M. A., Sumpter, P. Q., & Yates, P. O. A quantitative morphometric
analysis of the neuronal and synaptic content of the frontal and temporal cortex in patients with
Alzheimer's disease. Journal of the neurological sciences, 78(2), 151-164. (1987).
68. Scheff, S. W., Price, D. A., Schmitt, F. A., & Mufson, E. J. Hippocampal synaptic loss in early
Alzheimer's disease and mild cognitive impairment. Neurobiology of Aging, 27(10), 1372-
1384. (2006).
69. Bliss, T. V., & Lømo, T. Long‐lasting potentiation of synaptic transmission in the dentate area
of the anaesthetized rabbit following stimulation of the perforant path. The Journal of
Physiology, 232(2), 331-356. (1973).
70. Nicoll, R. A., & Roche, K. W. Long-term potentiation: peeling the onion. Neuropharmacology,
74, 18-22. (2013).
71. Nicoll, R. A., & Schmitz, D. Synaptic plasticity at hippocampal mossy fibre synapses. Nature
Reviews Neuroscience, 6(11), 863. (2005).
72. Gustafsson B, Wigstrom H. Long-term potentiation in the hippocampal CA1 region: its
induction and early temporal development. Prog Brain Res., 83:223–232. (1990).
73. Herring, B.E. and Nicoll. R. A. Long-Term Potentiation: From CaMKII to AMPA Receptor
Trafficking. Annu. Rev. Physiol., 78, 351-365. (2016).
92
74. Malenka, R. C., & Bear, M. F. LTP and LTD: an embarrassment of riches. Neuron, 44(1), 5-
21. (2004).
75. Nicoll, R. A. A brief history of long-term potentiation. Neuron, 93(2), 281-290. (2017).
76. Barria, A., Muller, D., Derkach, V., Griffith, L. C., and Soderling, T. R. Regulatory
phosphorylation of AMPA-type glutamate receptors by CaM-KII during long-term
potentiation. Science, 276, 2042-2045. (1997).
77. Malenka, R.C. Synaptic plasticity in the hippocampus: LTP and LTD. Cell, 78(4), 535-538.
(1994).
78. J.G. Valtschanoff, R.J. Weinberg. Laminar organization of the NMDA receptor complex
within the postsynaptic density. Journal of Neuroscience, 21, 1211-1217. (2001).
79. Okabe, S. Molecular anatomy of the postsynaptic density. Molecular and Cellular
Neuroscience, 34(4), 503-518. (2007).
80. J.C. Beique, R. Andrade. PSD-95 regulates synaptic transmission and plasticity in rat cerebral
cortex. Journal of Physiology, 546, 859-867 (2003).
81. K. Futai, M.J. Kim, T. Hashikawa, P. Scheiffele, M. Sheng, Y. Hayashi. Retrograde
modulation of presynaptic release probability through signaling mediated by PSD-95-
neuroligin. Nature Neuroscience, 10186-195. (2007).
82. M. Niethammer, E. Kim, M. Sheng. Interaction between the C terminus of NMDA receptor
subunits and multiple members of the PSD-95 family of membrane-associated guanylate
kinases. Journal of Neuroscience, 16, 2157-2163. (1996).
83. M. Sheng, M.J. Kim. Postsynaptic signaling and plasticity mechanisms. Science, 298, 776-
780. (2002).
84. V. Stein, D.R. House, D.S. Bredt, R.A. Nicoll. Postsynaptic density-95 mimics and occludes
hippocampal long-term potentiation and enhances long-term depression. Journal of
Neuroscience, 23, 5503-5506. (2003).
85. Vadlamudi, R. K., Li, F., Adam, L., Nguyen, D., Ohta, Y., Stossel, T. P., & Kumar, R. Filamin
is essential in actin cytoskeletal assembly mediated by p21-activated kinase 1. Nature Cell
Biology, 4(9), 681. (2002).
86. Hahn, C.G., Wang, H.Y., Cho, D.S., Talbot, K., Gur, R.E., Berrettini, W.H., Bakshi, K.,
Kamins, J., Borgmann-Winter, K.E., Siegel, S.J. and Gallop, R.J. Altered neuregulin 1–erbB4
signaling contributes to NMDA> receptor hypofunction in schizophrenia. Nature medicine,
12(7), 824. (2006).
93
87. Burns, L.H. and Wang, H.Y., Altered filamin A enables amyloid beta-induced tau
hyperphosphorylation and neuroinflammation in Alzheimer’s disease. Neuroimmunology and
Neuroinflammation, 4, 263-71. (2017).
88. Okuno, H. Regulation and function of immediate-early genes in the brain: beyond neuronal
activity markers. Neuroscience Research, 69, 175–186. doi: 0.1016/j.neures.2010.12.007
(2011).
89. Morgan, J. I., Cohen, D. R., Hempstead, J. L., and Curran, T. Mapping patterns of c-fos
expression in the central nervous system after seizure. Science, 237, 192–197. doi:
10.1126/science.3037702 (1987).
90. Lyford, G. L., Yamagata, K., Kaufmann, W. E., Barnes, C. A., Sanders, L. K., Copeland, N.
G., et al. Arc, a growth factor and activity-regulated gene, encodes a novel cytoskeleton-
associated protein that is enriched in neuronal dendrites. Neuron, 14, 433–445. doi:
10.1016/0896-6273(95)90299-6 (1995).
91. Guzowski, J. F., Setlow, B., Wagner, E. K., and McGaugh, J. L. Experience-dependent gene
expression in the rat hippocampus after spatial learning: a comparison of the immediate-early
genes Arc, c-fos, and zif268. Journal of Neuroscience, 21, 5089–5098. (2001).
92. Shepherd, J. D., & Bear, M. F. New views of Arc, a master regulator of synaptic plasticity.
Nature Neuroscience, 14(3), 279. (2011).
93. Korb, E., & Finkbeiner, S. Arc in synaptic plasticity: from gene to behavior. Trends in
Neurosciences, 34(11), 591-598. (2011).
94. Vazdarjanova, A., Ramirez‐Amaya, V., Insel, N., Plummer, T. K., Rosi, S., Chowdhury, S., ...
& Barnes, C. A. Spatial exploration induces ARC, a plasticity‐related immediate‐early gene,
only in calcium/calmodulin‐dependent protein kinase II‐positive principal excitatory and
inhibitory neurons of the rat forebrain. Journal of Comparative Neurology, 498(3), 317-329.
(2006).
95. McCurry, C. L., Shepherd, J. D., Tropea, D., Wang, K. H., Bear, M. F., & Sur, M. Loss of Arc
renders the visual cortex impervious to the effects of sensory experience or deprivation. Nature
Neuroscience, 13(4), 450. (2010).
96. El-Boustani, S., Ip, J. P., Breton-Provencher, V., Knott, G. W., Okuno, H., Bito, H., & Sur, M.
Locally coordinated synaptic plasticity of visual cortex neurons in vivo. Science, 360(6395),
1349-1354. (2018)
97. Myrum, C., Baumann, A., Bustad, H. J., Flydal, M. I., Mariaule, V., Alvira, S., ... & Márquez,
J. A. Arc is a flexible modular protein capable of reversible self-oligomerization. Biochemical
Journal, 468(1), 145-158. (2015).
94
98. Zhang, W., Wu, J., Ward, M. D., Yang, S., Chuang, Y. A., Xiao, M., ... & Worley, P. F.
Structural basis of arc binding to synaptic proteins: implications for cognitive disease. Neuron,
86(2), 490-500. (2015).
99. Campioni, M. R., & Finkbeiner, S. Going retro: ancient viral origins of cognition. Neuron,
86(2), 346-348. (2015).
100. Day, C., & Shepherd, J. D. (2015). Arc: building a bridge from viruses to memory. Biochemical
Journal, 469(1), e1-e3.
101. Korb, E., Wilkinson, C. L., Delgado, R. N., Lovero, K. L., & Finkbeiner, S. Arc in the nucleus
regulates PML-dependent GluA1 transcription and homeostatic plasticity. Nature
Neuroscience, 16(7), 874. (2013).
102. Epstein, I., & Finkbeiner, S. The Arc of cognition: Signaling cascades regulating Arc and
implications for cognitive function and disease. Seminars in cell & developmental biology
(Vol. 77, pp. 63-72). Academic Press. (2018).
103. Nikolaienko, O., Eriksen, M. S., Patil, S., Bito, H., & Bramham, C. R. Stimulus-evoked ERK-
dependent phosphorylation of activity-regulated cytoskeleton-associated protein (Arc)
regulates its neuronal subcellular localization. Neuroscience, 360, 68-80. (2017).
104. Ramírez-Amaya, V., Vazdarjanova, A., Mikhael, D., Rosi, S., Worley, P. F., & Barnes, C. A.
Spatial exploration-induced Arc mRNA and protein expression: evidence for selective,
network-specific reactivation. Journal of Neuroscience, 25(7), 1761-1768. (2005).
105. Bloomer, W. A., VanDongen, H. M., & VanDongen, A. M. Activity-regulated cytoskeleton-
associated protein Arc/Arg3. 1 binds to spectrin and associates with nuclear promyelocytic
leukemia (PML) bodies. Brain research, 1153, 20-33. (2007).
106. Bernardi, R. & Pandolfi, P.P. Structure, dynamics and functions of promyelocytic leukaemia
nuclear bodies. Nature Reviews Molecular Cell Biology, 8, 1006–1016 (2007).
107. Huang, F., Chotiner, J. K., & Steward, O. Actin polymerization and ERK phosphorylation are
required for Arc/Arg3. 1 mRNA targeting to activated synaptic sites on dendrites. Journal of
Neuroscience, 27(34), 9054-9067. (2007).
108. Shepherd, J. D., Rumbaugh, G., Wu, J., Chowdhury, S., Plath, N., Kuhl, D., ... & Worley, P.
F. Arc/Arg3. 1 mediates homeostatic synaptic scaling of AMPA receptors. Neuron, 52(3), 475-
484. (2006).
109. Guzowski, J. F., Lyford, G. L., Stevenson, G. D., Houston, F. P., McGaugh, J. L., Worley, P.
F., & Barnes, C. A. Inhibition of activity-dependent arc protein expression in the rat
hippocampus impairs the maintenance of long-term potentiation and the consolidation of long-
term memory. Journal of Neuroscience, 20(11), 3993-4001. (2000).
95
110. Messaoudi, E., Kanhema, T., Soulé, J., Tiron, A., Dagyte, G., da Silva, B., & Bramham, C. R.
Sustained Arc/Arg3. 1 synthesis controls long-term potentiation consolidation through
regulation of local actin polymerization in the dentate gyrus in vivo. Journal of
Neuroscience, 27(39), 10445-10455. (2007).
111. Plath, N., Ohana, O., Dammermann, B., Errington, M. L., Schmitz, D., Gross, C., ... & Kobalz,
U. Arc/Arg3. 1 is essential for the consolidation of synaptic plasticity and
memories. Neuron, 52(3), 437-444. (2006).
112. Yuste, R. & Bonhoeffer, T. Morphological changes in dendritic spines associated with long-
term synaptic plasticity. Annual Review of Neuroscience, 24, 1071–1089. (2001)
113. Maletic-Savatic, M., Malinow, R. & Svoboda, K. Rapid dendritic morphogenesis in CA1
hippocampal dendrites induced by synaptic activity. Science 283, 1923–1927 (1999).
114. Fukazawa, Y., Saitoh, Y., Ozawa, F., Ohta, Y., Mizuno, K., & Inokuchi, K. Hippocampal LTP
is accompanied by enhanced F-actin content within the dendritic spine that is essential for late
LTP maintenance in vivo. Neuron, 38(3), 447-460. (2003).
115. Sarmiere PD, & Bamburg JR. Regulation of the neuronal actin cytoskeleton by ADF/cofilin.
Journal of Neurobiology, 58, 103–117. (2004).
116. Chowdhury, S., Shepherd, J. D., Okuno, H., Lyford, G., Petralia, R. S., Plath, N., ... & Worley,
P. F. Arc/Arg3. 1 interacts with the endocytic machinery to regulate AMPA receptor
trafficking. Neuron, 52(3), 445-459. (2006).
117. Man, H. Y., Lin, J. W., Ju, W. H., Ahmadian, G., Liu, L., Becker, L. E., ... & Wang, Y. T.
Regulation of AMPA receptor–mediated synaptic transmission by clathrin-dependent receptor
internalization. Neuron, 25(3), 649-662. (2000).
118. Ehlers, M. D. Reinsertion or degradation of AMPA receptors determined by activity-
dependent endocytic sorting. Neuron, 28(2), 511-525. (2000).
119. Waung, M. W., Pfeiffer, B. E., Nosyreva, E. D., Ronesi, J. A., & Huber, K. M. Rapid
translation of Arc/Arg3. 1 selectively mediates mGluR-dependent LTD through persistent
increases in AMPAR endocytosis rate. Neuron, 59(1), 84-97. (2008).
120. Bürkle, A. Posttranslational Modification. Brenner's Online Encyclopedia of Genetics, Four-
Volume Set (pp. 1533-1533). Elsevier Inc. (2001).
121. Martin, S., Wilkinson, K. A., Nishimune, A., & Henley, J. M. Emerging extranuclear roles of
protein SUMOylation in neuronal function and dysfunction. Nature Reviews Neuroscience,
8(12), 948. (2007).
96
122. Craig, T. J., and Henley, J. M. SUMOylation, Arc and the regulation homeostatic synaptic
scaling Implications in health and disease. Commun. Integr. Biol. 5, 634–636. doi:
10.4161/cib.21712. (2012).
123. Craig, T. J., Jaafari, N., Petrovic, M. M., Rubin, P. P., Mellor, J. R., & Henley, J. M.
Homeostatic synaptic scaling is regulated by protein SUMOylation. Journal of Biological
Chemistry, 287(27), 22781-22788. (2012).
124. Nair, R. R., Patil, S., Tiron, A., Kanhema, T., Panja, D., Schiro, L., ... & Bramham, C. R.
Dynamic Arc SUMOylation and selective interaction with F-actin-binding protein drebrin A
in LTP consolidation in vivo. Frontiers in Synaptic Neuroscience, 9, 8. (2017).
125. Mabb, A. M., Je, H. S., Wall, M. J., Robinson, C. G., Larsen, R. S., Qiang, Y., ... & Ehlers, M.
D. Triad3A regulates synaptic strength by ubiquitination of Arc. Neuron, 82(6), 1299-1316.
(2014).
126. Greer, P. L., Hanayama, R., Bloodgood, B. L., Mardinly, A. R., Lipton, D. M., Flavell, S. W.,
... & Ploegh, H. L. The Angelman Syndrome protein Ube3A regulates synapse development
by ubiquitinating arc. Cell, 140(5), 704-716. (2010).
127. Okuno, H., Akashi, K., Ishii, Y., Yagishita-Kyo, N., Suzuki, K., Nonaka, M., ... & Natsume,
R. Inverse synaptic tagging of inactive synapses via dynamic interaction of Arc/Arg3. 1 with
CaMKIIβ. Cell, 149(4), 886-898. (2012).
128. Link, W., Konietzko, U. W. E., Kauselmann, G., Krug, M., Schwanke, B., Frey, U., & Kuhl,
D. Somatodendritic expression of an immediate early gene is regulated by synaptic activity.
Proceedings of the National Academy of Sciences, 92(12), 5734-5738. (1995).
129. Blanpied, T. A., & Ehlers, M. D. Microanatomy of dendritic spines: emerging principles of
synaptic pathology in psychiatric and neurological disease. Biological Psychiatry, 55(12),
1121-1127. (2004).
130. Newey, S. E., Velamoor, V., Govek, E. E., & Van Aelst, L. Rho GTPases, dendritic structure,
and mental retardation. Journal of Neurobiology, 64(1), 58-74. (2005).
131. Li, Y., Pehrson, A. L., Waller, J. A., Dale, E., Sanchez, C., & Gulinello, M. A critical
evaluation of the activity-regulated cytoskeleton-associated protein (Arc/Arg3. 1)'s putative
role in regulating dendritic plasticity, cognitive processes, and mood in animal models of
depression. Frontiers in Neuroscience, 9, 279. (2015).
132. Smith, S. E., Zhou, Y. D., Zhang, G., Jin, Z., Stoppel, D. C., & Anderson, M. P. Increased gene
dosage of Ube3a results in autism traits and decreased glutamate synaptic transmission in mice.
Science Translational Medicine, 3(103), 103ra97-103ra97. (2011).
97
133. Niere, F., Wilkerson, J. R., & Huber, K. M. Evidence for a fragile X mental retardation protein-
mediated translational switch in metabotropic glutamate receptor-triggered Arc translation and
long-term depression. Journal of Neuroscience, 32(17), 5924-5936. (2012).
134. Managò, F., Mereu, M., Mastwal, S., Mastrogiacomo, R., Scheggia, D., Emanuele, M., ... &
Papaleo, F. Genetic disruption of Arc/Arg3. 1 in mice causes alterations in dopamine and
neurobehavioral phenotypes related to schizophrenia. Cell Reports, 16(8), 2116-2128. (2016).
135. Fumagalli F, Franchi C, Caffino L, Racagni G, Riva MA, Cervo L. Single session of cocaine
intravenous self-administration shapes goal-oriented behaviours and up-regulates Arc mRNA
levels in rat medial prefrontal cortex. International Journal of Neuropsychopharmacology,
12(3):423–429. (2009).
136. Takagi, S., Balu, D. T., & Coyle, J. T. Subchronic pharmacological and chronic genetic NMDA
receptor hypofunction differentially regulate the Akt signaling pathway and Arc expression in
juvenile and adult mice. Schizophrenia Research, 162(1-3), 216-221. (2015).
137. Garber, K. B., Visootsak, J., & Warren, S. T. Fragile X syndrome. European Journal of Human
Genetics, 16(6), 666. (2008).
138. Niere, F., Wilkerson, J. R., & Huber, K. M. Evidence for a fragile X mental retardation
protein-mediated translational switch in metabotropic glutamate receptor-triggered Arc
translation and long-term depression. Journal of Neuroscience, 32(17), 5924-5936. (2012).
139. Burke, S.N., Barnes, C.A. Aging ensembles:circuit contributions to memory deficits. In:
Mizumori SJY (ed) Hippocampal place fields: relevance to learning, memory. Oxford
University Press, Oxford, pp 364–384. (2008).
140. Hsieh, H., Boehm, J., Sato, C., Iwatsubo, T., Tomita, T., Sisodia, S., & Malinow, R. AMPAR
removal underlies Aβ-induced synaptic depression and dendritic spine loss. Neuron, 52(5),
831-843. (2006).
141. Lacor, P. N., Buniel, M. C., Chang, L., Fernandez, S. J., Gong, Y., Viola, K. L., ... & Krafft,
G. A. Synaptic targeting by Alzheimer's-related amyloid β oligomers. Journal of
Neuroscience, 24(45), 10191-10200. (2004).
142. Wu, J., Petralia, R. S., Kurushima, H., Patel, H., Jung, M. Y., Volk, L., ... & Kuhl, D.
Arc/Arg3. 1 regulates an endosomal pathway essential for activity-dependent β-amyloid
generation. Cell, 147(3), 615-628. (2011).
143. Palop, J. J., Chin, J., Bien-Ly, N., Massaro, C., Yeung, B. Z., Yu, G. Q., & Mucke, L.
Vulnerability of dentate granule cells to disruption of arc expression in human amyloid
precursor protein transgenic mice. Journal of Neuroscience, 25(42), 9686-9693. (2005).
98
144. Bennett, D. A., Schneider, J. A., Arvanitakis, Z., Kelly, J. F., Aggarwal, N. T., Shah, R. C.,
and Wilson, R. S. Neuropathology of older persons without cognitive impairment from two
community-based studies. Neurology, 66(12), 1837-1844. (2006).
145. Fulda, S., Gorman, A. M., Hori, O., & Samali, A. Cellular stress responses: cell survival and
cell death. International journal of cell biology, 2010. (2010).
146. Wang, H. W., Pasternak, J. F., Kuo, H., Ristic, H., Lambert, M. P., Chromy, B., ... &
Trommer, B. L. Soluble oligomers of β amyloid (1-42) inhibit long-term potentiation but not
long-term depression in rat dentate gyrus. Brain Research, 924(2), 133-140. (2002).
147. Durrenberger, P. F., Fernando, S., Kashefi, S. N., Ferrer, I., Hauw, J. J., Seilhean, D., ... &
Palkovits, M. Effects of antemortem and postmortem variables on human brain mRNA quality:
a BrainNet Europe study. Journal of Neuropathology & Experimental Neurology, 69(1), 70-
81. (2010).
148. Ferrer, I., Martinez, A., Boluda, S., Parchi, P., & Barrachina, M. Brain banks: benefits,
limitations and cautions concerning the use of post-mortem brain tissue for molecular studies.
Cell and Tissue Banking, 9(3), 181. (2008).
149. Bennett, D. A., Wilson, R. S., Schneider, J. A., Evans, D. A., Beckett, L. A., Aggarwal, N. T.,
... & Bach, J. Natural history of mild cognitive impairment in older persons. Neurology, 59(2),
198-205. (2002).
150. Bennett, D. A., Schneider, J. A., Buchman, A. S., de Leon, C. M., Bienias, J. L., & Wilson,
R. S. The Rush Memory and Aging Project: study design and baseline characteristics of the
study cohort. Neuroepidemiology, 25(4), 163-175. (2005).
151. McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. Clinical
diagnosis of Alzheimer's disease Report of the NINCDS‐ADRDA Work Group* under the
auspices of Department of Health and Human Services Task Force on Alzheimer's Disease.
Neurology, 34(7), 939-939. (1984).
152. Mirra, S. S., Heyman, A., McKeel, D., Sumi, S. M., Crain, B. J., Brownlee, L. M., ... & Berg,
L. The Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Part II.
Standardization of the neuropathologic assessment of Alzheimer's disease. Neurology, 41(4),
479-479. (1991).
153. Hyman, B. T., & Trojanowski, J. Q. Editorial on consensus recommendations for the
postmortem diagnosis of Alzheimer disease from the National Institute on Aging and the
Reagan Institute Working Group on diagnostic criteria for the neuropathological assessment
of Alzheimer disease. Journal of neuropathology and experimental neurology, 56(10), 1095.
(1997).
99
154. Yamamoto, T., & Hirano, A. A comparative study of modified Bielschowsky, Bodian and
thioflavin S stains on Alzheimer's neurofibrillary tangles. Neuropathology and applied
neurobiology, 12(1), 3-9. (1986).
155. Nelson, A. P., & O'Connor, M. G. Mild cognitive impairment: a neuropsychological
perspective. CNS spectrums, 13(1), 56-64. (2008).
156. Petersen, R. C., & Negash, S. Mild cognitive impairment: an overview. CNS spectrums, 13(1),
45-53. (2008).
157. Wilson, R. S., Barnes, L. L., De Leon, C. M., Aggarwal, N. T., Schneider, J. S., Bach, J., ...
& Bennett, D. A. Depressive symptoms, cognitive decline, and risk of AD in older persons.
Neurology, 59(3), 364-370. (2002a)
158. Wilson, R. S., Beckett, L. A., Barnes, L. L., Schneider, J. A., Bach, J., Evans, D. A., &
Bennett, D. A. Individual differences in rates of change in cognitive abilities of older persons.
Psychology and aging, 17(2), 179. (2002b)
159. Talbot, K., Wang, H. Y., Kazi, H., Han, L. Y., Bakshi, K. P., Stucky, A., ... & Arvanitakis, Z.
Demonstrated brain insulin resistance in Alzheimer’s disease patients is associated with IGF-
1 resistance, IRS-1 dysregulation, and cognitive decline. The Journal of clinical investigation,
122(4), 1316-1338. (2012).
160. LeVine, H., & Walker, L. C. Models of Alzheimer's disease. In Handbook of Models for
Human Aging (pp. 121-134). (2006).
161. Oddo, S., Caccamo, A., Shepherd, J. D., Murphy, M. P., Golde, T. E., Kayed, R., ... & LaFerla,
F. M. Triple-transgenic model of Alzheimer's disease with plaques and tangles: intracellular
Aβ and synaptic dysfunction. Neuron, 39(3), 409-421. (2003).
162. Talbot, K., Wang, H. Y., Kazi, H., Han, L. Y., Bakshi, K. P., Stucky, A., ... & Arvanitakis, Z.
Demonstrated brain insulin resistance in Alzheimer’s disease patients is associated with IGF-
1 resistance, IRS-1 dysregulation, and cognitive decline. The Journal of Clinical Investigation,
122(4), 1316-1338. (2012).
163. Nicolas C. S., Peineau, S., Amici, M., Csaba, Z., Fafouri, A., Javalet, C…Collingridge, G.L.
The Jak/STAT pathway is involved in synaptic plasticity. Neuron. 73(2):374-90. (2012).
164. Huang Y. Aβ-independent roles of apolipoprotein E4 in the pathogenesis of Alzheimer’s
disease. Trends in Molecular Medicine.16:287–94. (2010).
165. Bakshi, K., Gennaro, S., Chan, C. Y., Kosciuk, M., Liu, J., Stucky, A., ... & Wang, H. Y.
Prenatal cocaine reduces AMPA receptor synaptic expression through hyperphosphorylation
of the synaptic anchoring protein GRIP. Journal of Neuroscience, 29(19), 6308-6319. (2009).
100
166. Rider, L., Shatrova, A., Feener, E. P., Webb, L., & Diakonova, M. JAK2 tyrosine kinase
phosphorylates PAK1 and regulates PAK1 activity and functions. Journal of Biological
Chemistry, 282(42), 30985-30996. (2007).
167. Burns, L. H., & Wang, H. Y. Altered filamin A enables amyloid beta-induced tau
hyperphosphorylation and neuroinflammation in Alzheimer’s disease. Neuroimmunology and
Neuroinflammation, 4:263-71. (2017).
168. A.J. Mishizen-Eberz, R.A. Rissman, T.L. Carter, M.D. Ikonomovic, B.B. Wolfe, D.M.
Armstrong. Biochemical and molecular studies of NMDA receptor subunits NR1/2A/2B in
hippocampal subregions throughout progression of Alzheimer's disease pathology.
Neurobiology of Disease, 15, 80-92, 10.1016/j.nbd.2003.09.016 (2004).
169. N. Amada, K. Aihara, R. Ravid, M. Horie. Reduction of NR1 and phosphorylated
Ca2+/calmodulin-dependent protein kinase II levels in Alzheimer's disease. Neuroreport, 16,
1809-1813. (2005).
170. Buller AL,Monaghan DT. Pharmacological heterogeneity of NMDA receptors:
Characterization of NR1a/NR2D heteromers expressed in Xenopus oocytes. European Journal
of Pharmacology, 320, 87–94. (1997).
171. Hoe HS, Pocivavsek A,Chakraborty G,Fu Z,Vicini S,Ehlers MD,Rebeck GW. Apolipoprotein
E receptor 2 interactions with the N‐methyl‐D‐aspartate receptor. Journal of Biological
Chemistry, 281, 3425–3431. (2006).
172. Steward, O., & Worley, P. F. Selective targeting of newly synthesized Arc mRNA to active
synapses requires NMDA receptor activation. Neuron, 30(1), 227-240. (2001).
173. Farris, S., Lewandowski, G., Cox, C. D., & Steward, O. Selective localization of arc mRNA
in dendrites involves activity-and translation-dependent mRNA degradation. Journal of
Neuroscience, 34(13), 4481-4493. (2014).
174. Battaglia, F., Wang, H. Y., Ghilardi, M. F., Gashi, E., Quartarone, A., Friedman, E., & Nixon,
R. A. Cortical plasticity in Alzheimer’s disease in humans and rodents. Biological Psychiatry,
62(12), 1405-1412. (2007).
175. Wang, H. Y., Stucky, A., Hahn, C. G., Wilson, R., Bennett, D., & Arnold, S. BDNF-trkB
signaling in late life cognitive decline and Alzheimer’s disease. Translational Neuroscience,
2(2), 91-100. (2011).
176. Pak, D. T., Yang, S., Rudolph-Correia, S., Kim, E., & Sheng, M. Regulation of dendritic spine
morphology by SPAR, a PSD-95-associated RapGAP. Neuron, 31(2), 289-303. (2001).
177. Noam, Y., Phan, L., McClelland, S., Manders, E. M., Ehrengruber, M. U., Wadman, W. J., ...
& Chen, Y. Distinct regional and subcellular localization of the actin‐binding protein filamin
a in the mature rat brain. Journal of Comparative Neurology, 520(13), 3013-3034. (2012).
101
178. Huang Y. Aβ-independent roles of apolipoprotein E4 in the pathogenesis of Alzheimer’s
disease. Trends in Molecular Medicine. 16:287–94. (2010).