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.

Total word count: 4981

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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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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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A


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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B


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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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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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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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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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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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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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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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

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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


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


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Documents

BIOS2001 Genetic Risk Factors for AD