Download - BIOS2001 Genetic Risk Factors for AD
GEORGIOS LOULOUDIS Department of Neuroscience Dr Frances Edwards
Genetic Risk Factors for Alzheimer’s Disease
Abstract
There have been great developments in the study of the genetics of Alzheimer’s
disease (AD) over the last few years. Quite recent genome-wide association
studies (GWAS) have expanded the list of genes that are associated with
increased AD risk. While it is important to know which genes confer risk, it is
much more important to know how and by which biochemical mechanisms those
genes can increase susceptibility for AD. Possession of such knowledge would
be immensely important as it would allow for the identification of therapeutic
targets and the development of new treatments. However, not much is known yet
about the link between those genes and AD pathology. In the present report, an
attempt is made to elucidate the biochemical mechanisms by which all those
genes may increase AD risk. The genes under investigation are APOE, ABCA7,
SORL1, CD2AP, BIN1, CLU, PICALM, CR1, INPP5D, CD33, TREM2, HLA-
DRB5/DRB1, EPHA1, SLC24A4-RIN3, CELF1, MEF2C, ZCWPW1, FERMT2,
PTK2B, MS4A, CASS4, PLD3 and NME8. Those genes fall into functional
groups, underlining the importance of processes, such as the immune system
and endocytosis, in the disease’s pathology.
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GEORGIOS LOULOUDIS Department of Neuroscience Dr Frances Edwards
Introduction
Alzheimer’s disease (AD) is a neurodegenerative disease, which causes
progressive memory and cognitive decline, ultimately resulting in dementia
(Nisbet et al., 2014) and eventually death (Danielsson et al., 2006). Given the
high prevalence of AD worldwide, e.g. 35.6 million people worldwide suffering
from dementia in 2010 (Prince et al., 2013), and the difficulty that AD brings to
the lives of those who suffer from it, researchers must devote their attention to
understanding the disease and several of its aspects, such as genetic
susceptibility and potentially implicated biological pathways. The focus of the
present report will be placed on the genetic variants that more or less predispose
individuals to the disease.
Amyloid plaques and neurofibrillary tangles are the pathogical hallmarks that
can be detected in the brains of AD patients (Nisbet et al., 2014). Amyloid
plaques form as a result of increased production of beta-amyloid (Aβ), abnormal
amyloid precursor protein (APP) processing or impaired Aβ clearance (Bojarski
et al., 2008). There is increasing evidence that Aβ induces its neurotoxic effects
via tau and that the two molecules are probably linked via a mechanism involving
Fyn (Nisbet et al., 2014), which will be reviewed later in this report. Normally, tau
is a microtubule-stabilising protein and its function is modulated by site-specific
phosphorylation (Johnson and Stoothoff, 2004). Hyperphosphorylated tau though
is a constituent of neurofibrillary tangles and has been associated with
impairments in microtubule stability and axonal transport (Johnson and Stoothoff,
2004). Other effects of toxic tau include mitochondrial dysfunction, calcium
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GEORGIOS LOULOUDIS Department of Neuroscience Dr Frances Edwards
dysregulation, synaptic deficits, activation of caspases and apoptosis (Kopeikina
et al., 2012).
Genome wide association studies (GWAS) of the last decade have revealed
several genetic variants, which can contribute to the toxic effects of Aβ and tau.
With these GWAS, researchers obtain valuable data regarding the frequency of
these genetic risk factors in populations, as well as the degree of risk that these
are associated with (see figure 1). In the present report, APOE, ABCA7, SORL1,
CD2AP, BIN1, CLU, PICALM, CR1, INPP5D, CD33, TREM2, HLA-DRB5/DRB1,
EPHA1, SLC24A4-RIN3, CELF1, MEF2C, ZCWPW1, FERMT2, PTK2B, MS4A,
CASS4, PLD3 and NME8 will be reviewed in terms of the risk they convey and
their involvement in late-onset AD (LOAD). The genes fall into these three
functional groups: (1) lipid and vesicular transport, (2) immune system and (3)
signaling.
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Fig. 1 Graph of risk of Alzheimer’s (low-med-high risk, causes Alzheimer’s) vs frequency in the
population (%). Low-risk variants, e.g. ABCA7, CELF1, are so common, that they are statistically
going to show up in most populations/GWAS. The medium/high-risk genes, e.g. PLD3, TREM2,
homozygosity for APOE4, are less common. The high risk that these genes convey, however,
cannot go totally unnoticed and therefore, these genetic risk factors can be detected even in
small populations/GWAS. This is also the case with the eFAD mutations in APP, PSEN1 and
PSEN2. There are, however, exceptions to this statistical trend, as APOE4 conveys medium risk
for AD and it is quite common in populations. Modified from Karch and Goate, 2015.
Lipid and vesicular transport; Endocytosis; Aβ processing and clearance
(APOE, SORL1, ABCA7, CD2AP, BIN1, CLU, PICALM)
APOE
The most important gene that falls under this category is APOE (apolipoprotein
E). There are three common APOE alleles: the ε2, ε3 and ε4 (Roses, 1996). Of
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those, the ε2 is considered protective against AD, whereas the ε4 is still the
greatest genetic risk factor for AD (Spinney, 2014). APOE is mainly synthesized
by astrocytes and it can bind lipids, cholesterol and Aβ in the cerebrospinal fluid
(CSF) via its C-terminal domain, and receptors LDLR and LRP1, influencing their
transport in neurons (Bu, 2009). Specifically, APOE alleles differentially modulate
APP processing to Aβ through an LRP1-dependant mechanism, with APOE4
leading to greatest production of Aβ (see figure 3) (Bu, 2009). Αlso, APOE
isoforms promote Aβ clearance by neprilysin and insulin-degrading enzyme, with
APOE4 leading to less efficient clearance and, quite often, reduced expression of
these enzymes is observed with APOE4 (Bu, 2009). In addition, the clearance of
APOE4-Aβ complexes via APOE receptors is less efficient than the clearance of
APOE2-Aβ and APOE3-Aβ receptors (Bu, 2009). Apart from the deposition of
amyloid plaques, it has been found that transgenic expression of APOE4 in
neurons increases tau phosphorylation in mice (Bu, 2009). Although all these
mechanisms have been identified both in vivo and in vitro, the link between
APOE4 and AD is far from understood (Bu, 2009).
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GEORGIOS LOULOUDIS Department of Neuroscience Dr Frances Edwards
Fig. 2 Aβ production and clearance by APOE. A) Vesicular transport of APP via clathrin-
mediated endocytosis to endosomes leads to intracellular APP processing. Rapid endocytosis of
LRP1 accelerates APP endocytosis and APOE4 and LRP1 favour the amyloidogenic pathway of
APP processing and the production of Αβ molecules. Interestingly, the product of SORL1
(Sortilin-related receptor), another genetic risk variant of AD, is important for directing APP to the
Golgi bodies, where APP processing to Αβ is avoided. This allows for the estimation that loss-of-
function mutations in SORL1 also contribute to AD. B) Accumulation of Aβ occurs in the brain
parenchyma, causing amyloid plaque formation in the brain and around cerebrovascular arteries.
LRP1 seems to be a major receptor for clearance of Αβ. In all cases, APOE4 appears to be less
efficient in clearing Aβ compared to APOE3. Obtained from Bu, 2009.
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GEORGIOS LOULOUDIS Department of Neuroscience Dr Frances Edwards
SORL1
As seen in figure 3, SORL1 is important in transporting APP to the Golgi bodies,
where no amyloidogenic processing occurs and, therefore, APP processing
would increase by SORL1 loss-of-function mutations. Andersen et al. (2005)
used ELISA to measure Aβ levels in Sorl1 deficient and wild-type mice and they
found that Aβ production was greater in Sorl1 knockout mice. More interestingly,
Ma et al. (2007) supported that genetic polymorphisms that reduce SORL1
expression increase AD risk, but that such polymorphisms are rare in cases with
SORL1 deficits. This seems to suggest that factors, other than that of SORL1 risk
variants, may greatly be contributing to SORL1 downregulation. Ma et al. (2007)
investigated the role of docosahexaenoic acid (DHA) in SORL1 upregulation and
the reduction of Aβ accumulation. They observed the DHA-induced increase in
SORL1 in primary rat neurons, aged non-Tg mice and aged DHA-depleted
APPsw AD mice models, as well as in a human neuronal line, highlighting the
potential role of DHA in AD prevention. Initial clinical trials of 1.7 g/day DHA to
mild to moderate patients did not halt cognitive decline, whereas this decline got
stabilized in patients at the earliest stages of AD (Ma et al., 2007).
ABCA7 and CD2AP
ABCA7 (ATP-Binding Cassette, Sub-family A, Member 7) and CD2AP (CD2-
Associated Protein) have been implicated in both lipid transport and immune
response in AD, but they are normally involved in lipid transport (Rosenthal and
Kamboh, 2014). Kim et al. (2013), in an attempt to understand the role of ABCA7
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in AD, compared J20 amyloidogenic mice with Abca7 knock-out mice of the
same AD model in terms of Aβ accumulation. It was shown that Abca7 deletion
caused a doubling of insoluble Αβ levels in the brain. However, APP processing
and APOE levels were not affected by Abca7 deletion, there were no cognitive
differences between the two mouse models and the only notable difference was
that in the knock-out mice, bone marrow-derived macrophages were not able to
take up oligomeric Aβ effectively. This shows that ABCA7 ablation increases the
amount of insoluble Aβ (Rosenthal and Kamboh, 2014). On the other hand,
CD2AP has been associated with Aβ clearance, but, at the same time, loss of the
fly ortholog of CD2AP has been found to increase tau neurotoxicity in transgenic
flies (Rosenthal and Kamboh, 2014). CD2AP has been found to interact with the
product of another LOAD genetic variant, INPP5D (Rosenthal and Kamboh,
2014), as will be viewed later in this report.
BIN1
Chapuis et al. (2013) focused on BIN1 (Bridging Integrator 1), which is normally
involved in endocytosis, actin dynamics, membrane trafficking and tubulation.
They reported that BIN1 levels are increased in human AD brains and in
neurons. They also investigated the effect of the Drosophila BIN1 ortholog Amph,
by making use of a model in which Aβ42 expression causes rough eyes and found
that there was no change in external eye morphology, suggesting that BIN1 is
not linked to amyloid pathology. They then used Drosophila with tau-induced
rough eyes and they decreased Amph expression by RNAi-mediated knockdown.
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GEORGIOS LOULOUDIS Department of Neuroscience Dr Frances Edwards
They managed to inhibit tau-induced neurotoxicity, as eye surface decreased by
30% in flies overexpressing tau. Overall, with their study they support that BIN1
gain-of-function mutations increase AD risk via tau pathology.
CLU
CLU (Clusterin) is an apolipoprotein that is involved in stabilization of stressed
proteins and in cholesterol and lipid metabolism (Nuutinen et al., 2009). It has
been suggested that it interacts with BIN1 in AD (Zhou et al., 2014). CLU can
also bind Bax protein in the cytoplasm and inhibit apoptosis, and this, along with
the fact that CLU is upregulated in AD to bind Aβ and counteract plaque
formation, shows that CLU may be protective against AD (Nuutinen et al., 2009).
However, Zhou et al. (2014) attribute this effect to the secreted form of CLU
(sCLU) and argue that increased levels of intracellular CLU (iCLU) contribute to
AD risk. They argue that the interaction between iCLU and BIN1 prevents the
binding of BIN1 to dynamin 2, disrupting endocytosis and, at the same time, may
modulate the function of tau and thus increase AD risk. CLU has been found to
regulate Aβ toxicity, by inducing the expression of Dickkopf-1 (Dkk1), a canonical
WNT pathway antagonist (Killick et al., 2014), as will be seen later in this report.
PICALM
PICALM (Phosphatidylinositol Binding Clathrin Assembly Protein), is normally
involved in APP trafficking and Aβ clearance via clathrin-mediated endocytosis
(Rosenthal and Kamboh, 2014). However, several single nucleotide
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GEORGIOS LOULOUDIS Department of Neuroscience Dr Frances Edwards
polymorphisms (SNPs) in the gene lead to its increased proteolysis by calpain
and caspase (Ando et al., 2013). Rosenthal and Kamboh (2014) stated that this
aberrant PICALM proteolysis may affect Aβ clearance, but that no interaction
between PICALM and Aβ has ever been noticed. Co-localisation of PICALM and
tau in neurofibrillary tangles has also been noticed in AD brains, as Ando et al.
(2013) used different anti-tau antibodies that recognized conformational,
phosphorylated and caspase-cleaved tau, and anti-PICALM antibodies.
Abnormal PICALM accumulation was observed in 85% of the tangles. They also
speculated that PICALM proteolysis may be associated with defects in vesicle
sorting and synaptic activity. Currently, the link between PICALM and AD is far
from understood (Ando et al., 2013).
Immune system (TREM2, CR1, CD33, INPP5D, CD2AP, HLA-DRB5/DRB1)
TREM2
Rather recent GWAS, such as that by Jonsson et al. (2013), have recognized
the role of mutant TREM2 (triggering receptor of myeloid cells 2) in AD. Frank et
al. (2008) observed that Trem2 was upregulated in aged APP23 transgenic mice.
They also supported that TREM2 induces microglial phagocytosis of amyloid
plaques, and that it also prevents microglia from releasing harmful
proinflammatory cytokines. Τherefore, TREM2 upregulation is important in driving
the immune response against the toxic effects of Aβ. However, Frank et al.
(2008) did note that TREM2 only mediates weak immune responses and that AD,
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in fact, can be partly attributed to the ineffectiveness of immune responses in the
brain. More on the role of TREM2 in AD under figure 3.
Fig. 3 TREM2 functions in AD. A) There are two types of microglial activation phenotypes. The
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induction of these phenotypes, the M1-like and the M2-like, is dependent on TREM2 levels.
Reduced levels of TREM2 cause the activation of the M1-like phenotype and the secretion of pro-
inflammatory cytokines, which can cause bystander neuronal damage (Jiang et al., 2013).
Increased TREM2 levels induce the M2-like phenotype, Aβ phagocytosis, and the secretion of
anti-inflammatory cytokines, which can prevent inflammation-related neuronal damage (Jiang et
al., 2013). B) The TREM2-DAP12 complex embedded in the microglial membrane is responsible
for the uptake of Aβ amyloid. Also, it can recognize unknown ligands that are displayed by
apoptotic cells/neurons and cause their removal (Jiang et al., 2013). It can therefore be
understood that these neuroprotective processes can be inhibited by reductions in TREM2 levels,
which would lead to increased risk of AD, and indeed, homozygous TREM2 loss-of-function
mutations have been reported to contribute to AD (Guerreiro et al., 2013). Modified from Jiang et
al., 2013.
CD33
In contrast to TREM2, CD33 gain-of-function mutations must be associated with
increased AD risk, as CD33 overexpression in monocytes has been associated
with cognitive decline and AD (Bradshaw et al., 2013). CD33 is a member of the
sialic acid-binding immunoglobulin-like lectins (Siglecs) (Rosenthal and Kamboh,
2014). Griciuc et al. (2013) noted that CD33 expression was increased in the
microglia of postmortem brain samples of AD patients and that it disrupted Aβ
clearance in migroglial cell cultures. They also deleted Cd33 from APP
transgenic mice and observed a reduction in amyloid plaque formation.
Therefore, increased CD33 levels probably act to block microglial Aβ clearance
and contribute to amyloid plaque build-up.
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GEORGIOS LOULOUDIS Department of Neuroscience Dr Frances Edwards
CR1
CR1 (Complement Component Receptor 1) encodes for a membrane receptor
on erythrocytes, leukocytes and podocytes, which binds complement fragments
C3b and C4b (Rochowiak and Niemir, 2010). The complement pathway itself
involves pathogen opsonisation, the release of pro-inflammatory agents and the
induction of inflammatory responses (Dunkelberger and Song, 2010) and CR1
regulates the clearance of immune complexes from the circulatory system
(Fearon, 1985). The exact ways by which CR1 is linked to AD are yet unknown
(Rosenthal and Kamboh, 2014).
Holton et al. (2013) support that intronic SNPs in the gene (rs6701713,
rs1408077, rs3818361 and rs6656401) and that low levels of CR1 have been
noted in the cerebellum and white matter of AD brains. Killick et al. (2013)
focused on Crry (the mouse ortholog of CR1) and its deletion in mice. Although
they did not mention that they had used AD mouse models, they did record the
effects of the Crry deletions on the levels of complement factor H (CFH), a
plasma biomarker for AD (Hye et al., 2006), and tau phosphorylation at serine
235. Both CFH levels and tau phosphorylation were reduced. This should not be
taken to justify that Crry knockdown leads to a reduction in AD-related toxicity
unless properly supported with studies of AD mouse models. It does allow
though for a mere speculation that CR1 gain-of-function mutations may act to
increase AD risk.
According to Crehan et al. (2012), Aβ can activate the complement pathway by
interacting with the collagen-like domain of C1q, which shows that an overactive
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complement pathway is a characteristic of AD. This is shown by Fonseca et al.
(2004), who generated an AD mouse model that lacked C1q and observed a
decrease in amyloid plaque pathology. The downstream effect of active C1q is
the activation of the membrane attack complex (MAC) and it has been suggested
that AD components are activators of MAC (Crehan et al., 2012). Crehan et al.
(2012) go on supporting that MAC insertion in the membrane forms a pore that
mediates Ca2+ with the end-effect of cell lysis, and that CD59 is a complement
regulator which prevents cell lysis. By making use of ELISA, Yang et al. (2000)
showed that CD59 is low in the hippocampus and frontal cortex of AD brains and
they attributed this to the effect of Aβ. Overall, it might be that overexpression of
CR1 leads to an overactive complement system and an enhancement in AD-
related neurotoxicity.
INPP5D and CD2AP
The product of INPP5D is SH2-containing inositol 5-phosphatase 1 (SHIP1),
which is involved in receptor-mediated immune responses, such as those that
arise by the association of the tyrosine kinase Btk with the membrane of B cells
(Metzner et al., 2009; Bolland et al., 1998). As it had been previously stated,
SHIP1 interacts with CD2AP. The complex that these two proteins form has been
implicated in the positive regulation of BDCA2/FcεR1γ signalling in human
plasmacytoid dendritic cells (Bao et al., 2012). Knockdown of either CD2AP or
INPP5D has been shown to stimulate the degradation of FcεR1γ by E3 ubiquitin
ligase Cbl and, therefore, CD2AP/SHIP1 positively regulate BDCA2/FcεR1γ
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signaling by inhibiting E3 ubiquitin ligase Cbl (Bao et al., 2012). E3 ubiquitin
ligases have been implicated in full-length APP ubiquitination, which may or may
not affect secretase-mediated APP processing (Wang and Saunders, 2014).
Wang and Saunders (2014) mentioned that, in certain studies, proteosome
inhibitors, such as lactamycin, caused an increase in Aβ generation and that
disruption of the ubiquitin-proteosome system (UPS) has been observed in many
neurodegenerative diseases.
Despite the fact that the relationship between E3 ubiquitin ligase Cbl and AD
pathology has not been properly investigated yet, this information does allow for
the speculation that SHIP1 and CD2AP may contribute to AD pathology by
inhibition of APP ubiquitination/proteolysis. It can then be assumed that INPP5D
and CD2AP gain-of-function mutations increase AD risk. However, it had been
previously noted that CD2AP may likely be involved in Αβ clearance. The
relationship between the expression of INPP5D and CD2AP and AD pathology
requires further research, but attention should mostly be paid to the role of UPS
in neurodegeneration, as this would highlight potential targets for the
development of treatments for AD and other neurodegenerative diseases (Chung
et al., 2001).
HLA-DRB1/DRB5
As stated by Rosenthal and Kamboh (2014), HLA-DRB1/DRB5 is a component
of the major histocompatibility complex (MHC) and involved in multiple immune
responses. Tooyama et al. (1990) examined postmortem AD brains and
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confirmed that reactive microglia exhibit MHC class I (HLA-A,B,C) and class II
(HLA-DR) antigen expression, with class II antigen expression being more
abundant. However, our knowledge of the effect of this locus in AD is limited.
Rosenthal and Kamboh (2014) mentioned that knocking out MHCII has a
neuroprotective effect in Parkinsonian mice and they assumed that enhanced
HLA-DRB1/DRB5 signaling would also contribute to AD pathology.
Signaling and transcriptional events; calcium dysregulation (CLU, EPHA1,
SLC24A4-RIN3, CELF1, MEF2C, ZCWPW1, FERMT2, PTK2B,
MS4A4/MS4A6E, CASS4, PLD3, NME8)
CLU
As stated earlier, CLU regulates Aβ toxicity by activating the expression of
Dkk1, a canonical WNT pathway inhibitor. By siRNA knockdown of Clu in primary
neuronal cultures, Killick et al. (2014) caused a reduction in Aβ toxicity and
inhibition of Dkk1 upregulation, and addition of Aβ increased iCLU and
decreased sCLU as a result of Dkk1 induction by p53. They then carried out
whole-genome expression of the neurons under the effect of Aβ and Dkk1 and
determined that the WNT-planar cell polarity (PCP)-c-Jun N-terminal kinase
(JNK) pathway is involved. The overall effect of Aβ and Dkk1 was the induction of
certain genes, whose silencing protected against Aβ and tau toxicity. They also
induced Dkk1 overexpression in Tg2576 mice, which activated the WNT-PCP-
JNK pathway and increased age-dependent tau phosphorylation. Importantly,
this was noticed only in amyloid-based mouse models. Overall, any mutation that
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increases iCLU levels and decreases sCLU levels may increase AD risk via
canonical WNT signaling inhibition.
PTK2B
PTK2B (Protein Tyrosine Kinase 2B), is a focal adhesion kinase, which is
phosphorylated on tyrosine residues (Tyr402) to cause the activation of Src
family kinases (SFKs) and hence, its involvement in Ca2+-dependent modulation
of ion channel activity and actin cytoskeleton reorganization (Zhang et al., 2014;
Lev et al., 2002; Du et al., 2001). Its property as an ion channel modulator is
crucial, because Ca2+ dysregulation has been implicated in AD (Bojarski et al.,
2008) and it is thought that Ca2+ influx pathways can modulate Aβ production
(Green and LaFerla, 2008). However, a rather probable mechanism by which
PTK2B may be involved in AD is one which is also likely to link Aβ toxicity with
tau toxicity (see figure 4). By focusing on both human and transgenic mouse
brain tissue and primary cortical neurons, Larson et al. (2012) showed that by
preventing the binding of oligomeric Aβ to cellular prion protein (PrPc), protein-
tyrosine kinase(Fyn)-dependent tau hyperphosphorylation was inhibited. Wang
and Xue (2014) stated that the binding of Aβ triggers a sequence of signaling
events, whereby PTK2B phosphorylates and activates Fyn, which then
hyperphosphorylates tau on microtubules. This seems to suggest that
upregulation of PTK2B activity probably increases AD risk.
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Fig. 4 Signaling cascade by which PTK2B can be implicated in AD. Aβ dimers bind to PrPc.
This eventually leads up to the phosphorylation of Fyn by PTK2B. Phosphorylated Fyn in turn
hyperphosphorylates tau on microtubules and contributes to tau toxicity. Hyperphosphorylated
tau detaches from microtubules and forms neurofibrillary tangles. The microtubules are
destabilised. Modified from Wang and Xue, 2014.
EPHA1
EPHA1 (Eph Receptor A1) is a member of the Eph receptor tyrosine kinases,
which are mainly involved in facilitating synapse formation, plasticity and axon
guidance during development (Rosenthal and Kamboh, 2014; Lai and Ip, 2009).
The involvement of EPHA1 in AD has not been studied thoroughly. EPHA4,
however, is a γ-secretase substrate and there is a positive correlation between
EPHA4 processing and synaptic activity (Inoue et al., 2009). EphA4 knockdown
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GEORGIOS LOULOUDIS Department of Neuroscience Dr Frances Edwards
in neurons led to a decreased number of dendritic spines, which was attributed to
the loss of EPHA4 processing by γ-secretase (Inoue et al., 2009) and therefore,
EPHA4 deficits may be contributing to AD-related synaptic deficits. However,
even though EPHA1 and EPHA4 belong in the same category of Eph receptors,
EPHA1 may not be involved in AD in the same way. What has been noted so far
regarding the relationship between EPHA1 and AD, is that there has been no
evidence of differential expression of EPHA1 mRNA in the disease, and that the
SNPs rs11767557 and rs11771145 have been associated with reduced risk for
LOAD (Karch and Goate, 2015).
FERMT2 and CELF1
FERMT2 (Fermitin Family Member 2) is a cell-matrix adhesion molecule
(Rosenthal and Kamboh, 2014), whereas CELF1 (CUGBP Elav-like family
member 1) has recently been characterized as a post-transcriptional regulator
(Dang et al., 2014). Shulman et al. (2014) carried out functional screening in
Drosophila model of AD to test the involvement of 67 candidate genes in AD. By
RNAi-induced knock-out of either Fit1 or Fit2 (FERMT2 homologues), the flies
developed tau-associated rough eyes, whereas overexpression of the
homologues suppressed tau toxicity. This was also the case with aret (CELF1
homologue). Overall, it is possible that loss-of-function mutations in those two
genes may contribute to AD pathology via tau-related mechanisms, whereas
gain-of-function mutations might be neuroprotective.
SLC24A4/RIN3
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GEORGIOS LOULOUDIS Department of Neuroscience Dr Frances Edwards
According to Rosenthal and Kamboh (2014), SLC24A4 (Solute Carrier Family
24, Member 4) is a sodium/potassium/calcium exchanger, whose variants have
been associated with amelogenesis imperfecta and hypertenstion. On the other
hand, RIN3 (Rab Interactor 3) is a guanine nucleotide exchange factor that has
been implicated in the suppression of mast cell responses to Stem Cell Factor
(Janson et al., 2012). Not much is known about the role of SLC24A4 in AD, but
since it is involved in calcium transport, impairment of its activity may be linked to
Ca2+ dysregulation. The role of RIN3 in AD has not been characterized.
MS4A
Ma et al. (2014) stated that the MS4A locus encodes for membrane proteins
with four membrane-spanning domains that are found in hematopoietic cells and
in tissues such as those of the brain. The researchers go on stating that the
products of the MS4A locus have been previously found to be involved in the
differentiation and activation of B cells and in the control of intracellular Ca2+, by
regulation of both Ca2+ entry and Ca2+ mobilisation from intracellular stores.
According to Ma et al. (2014), the members of the locus increase calcium
conductance, leading to the augmentation of intracellular Ca2+ concentration and
AD-associated calcium dysregulation. They state, however, that the mechanism
by which this is achieved is still unknown. MS4A products may also activate T-
cells and direct them to the brain via the blood-brain barrier (Ma et al, 2014).
These cells will then stimulate microglial release of pro-inflammatory cytokines
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GEORGIOS LOULOUDIS Department of Neuroscience Dr Frances Edwards
that cause neuronal damage (Ma et al., 2014). Overall, it may be that MS4A
gain-of-function mutations are associated with increased AD risk.
MEF2C
MEF2C (myocyte enhancer factor 2C) is a transcription factor that is involved in
the regulation of muscle, bone and cardiovascular development (Arnold et al.,
2007). Barbosa et al. (2008) deleted Mef2c in mice and observed a substantial
increase in the amount of excitatory synapses, along with the impairment of
hippocampal-dependent learning and memory. MEF2C deletions have also been
associated with seizures (Nowakowska et al., 2010), and seizures, in turn, are a
symptom of AD (Palop and Mucke, 2009). As Palop and Mucke (2009) argue that
Aβ may be contributing to the cognitive deficits in AD via a mechanism involving
abnormal excitatory neuronal activity, it could be that there is a relationship
between MEF2C deletions and AD-related seizures, and this may be of
relevance regarding the potential mechanism by which MEF2C may increase AD
risk. However, it must be noted that the epileptiform activity in AD occurs at the
level of the neuronal circuit and that Aβ depresses excitatory activity at the level
of the synapse (Palop and Mucke, 2010). Given that Mef2c deletions caused the
number of excitatory synapses to increase in the study by Barbosa et al. (2008),
the notion that MEF2C increases AD risk via a mechanism involving epileptiform
activity can be easily challenged.
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GEORGIOS LOULOUDIS Department of Neuroscience Dr Frances Edwards
PLD3
PLD3 (phospholipase D3) is a type 2 endoplasmic reticulum-associated
transmembrane protein that is mainly expressed in neurons and which is thought
to be most likely involved in APP processing (Wang et al., 2015; Cruchaga et al.,
2014). In general though, Phospholipase D enzymes hydrolyse phospholipids,
such as phosphatidylcholine, causing the release of phosphatidic acid and
choline (Kolesnikov et al., 2012). Cruchaga et al. (2014) overexpressed wild-type
human PLD3 in mouse neuroblastoma cells bearing the wild-type human
APP695 gene. This resulted in an immense reduction in levels of Aβ42 (48%) and
Aβ40 (58%). Knocking-out PLD3 by shRNA caused Aβ elevation. It can therefore
be understood that PLD3 loss-of-function mutations may significantly increase
AD risk. The role of PLD3 in molecular pathways associated with AD pathology
requires further investigation (Wang et al, 2015).
ZCWPW1
ZCWPW1 (Zinc Finger, CW Type with PWWP Domain 1) is an epigenetics
regulator, e.g. histone modifications, methylation states and chromatin
remodeling (Rosenthal and Kamboh, 2014). Epigenetics may have an important
role to play in AD, since gene expression changes can also occur by changes in
DNA methylation patterns rather than genetic mutations. Lord and Cruchaga
(2014) reviewed an epigenome-wide association study in AD, in which the
researchers had focused on the link between amyloid plague deposition and the
methylation pattern at 415848 CpG dinucleotides. This study showed that there
23
GEORGIOS LOULOUDIS Department of Neuroscience Dr Frances Edwards
were 71 discrete CpGs in 60 differentially methylated regions, two of which
corresponded to the ABCA7 and BIN1 LOAD loci. It may be that epigenetic
changes may be one of the factors driving differential gene expression during AD
and that ZCWPW1 is a key player in this process. ZCWPW1 mutations could be
causing changes in the epigenetic mechanisms that are governing the gene
expression changes that occur in AD, therefore increasing AD risk by
upregulating or downregulating the expression of AD genes, such as ABCA7 and
BIN1.
CASS4
CASS4 (Cas Scaffolding Protein Family Member 4) is a member of scaffold
proteins which act as regulators of protein complexes that are involved in
chemotaxis, apoptosis, cell cycle and differentiation (Tikhmyanova et al., 2010). It
has not been well characterised in AD, but it may be involved in inducing
apoptotic mechanisms that may be relevant to AD.
NME8
The expression of NME8 (NME/NM23 Family Member 8) is limited in the testis
and respiratory epithelial cells, but defects in this gene have been associated
with primary ciliary dyskinesia and oxidative stress in the brain (Rosenthal and
Kamboh, 2014). Liu et al. (2014) investigated the link between NME8 rs2718058
genotypes and AD and determined that the particular locus is protective against
24
GEORGIOS LOULOUDIS Department of Neuroscience Dr Frances Edwards
AD. This would allow for the suggestion that NME8 loss-of-function mutations
may exacerbate AD. However, the link between NME8 and AD is not known.
Conclusion
It is clear that there is still a lot to be done on the topic of the relationship
between genes and AD. Our understanding of the mechanisms by which those
genes may contribute to AD pathology is still obscure. As Karch and Goate
(2015) also concluded, it seems that most of the genetic variants that were
reviewed in this report are mostly linked to amyloid toxicity. Another important
flaw in the scientific literature is that it does not thoroughly focus on the
interaction between environmental and genetic factors, as implied by Rosenthal
and Kamboh (2014). It would be important to understand what is in the
environmental risk factors themselves that could trigger the molecular pathways
of AD and in what ways these factors could be controlled to suppress the effect
of the genetic risk factors. This would also allow for the identification of
therapeutic targets and hence, the development of treatments. However, given
the disease’s complexity and the multiple pathways that may be involved in it,
developing effective therapeutics for AD is never an easy task.
Acknowledgements
Special thanks go to Dr Frances Edwards for her support throughout this
project.
25
GEORGIOS LOULOUDIS Department of Neuroscience Dr Frances Edwards
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