# Metal Dyshomeostasis and Inflammation in Alzheimer’s and

Authors: Oddvar Myhre; Hans Utkilen; Nur Duale; Gunnar Brunborg; Tim Hofer
Journal: Oxidative Medicine and Cellular Longevity
 (2013)

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## Abstract

A dysregulated metal homeostasis is associated with both Alzheimer’s (AD)
and Parkinson’s (PD) diseases; AD patients have decreased cortex and
elevated serum copper levels along with extracellular amyloid-beta plaques
containing copper, iron, and zinc. For AD, a putative hepcidin-mediated lowering
of cortex copper mechanism is suggested. An age-related mild chronic
inflammation and/or elevated intracellular iron can trigger hepcidin production
followed by its binding to ferroportin which is the only neuronal iron exporter,
thereby subjecting it to lysosomal degradation. Subsequently raised neuronal
iron levels can induce translation of the ferroportin assisting and copper
binding amyloid precursor protein (APP); constitutive APP transmembrane passage
lowers the copper pool which is important for many enzymes. Usingin
silico gene expression analyses, we here show significantly
decreased expression of copper-dependent enzymes in AD brain and
metallothioneins were upregulated in both diseases. Although few AD exposure
risk factors are known, AD-related tauopathies can result from cyanobacterial
microcystin and β-methylamino-L-alanine (BMAA) intake.
Several environmental exposures may represent risk factors for PD; for this
disease neurodegeneration is likely to involve mitochondrial dysfunction,
microglial activation, and neuroinflammation. Administration of metal chelators
and anti-inflammatory agents could affect disease outcomes.


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## Body

## 1. Introduction

Degenerative brain disorders among the elderly constitute a growing burden for the
affected individuals, their families, and for the society. The mechanisms behind
Alzheimer’s and Parkinson’s diseases (AD and PD) are still unclear.
Although symptom-relieving drugs exist, drugs halting their progression are still
lacking [1–5]. Our brains are continuously exposed to a broad spectrum of
chemicals from various sources; these may react or interfere with biomolecules, or
they may bioaccumulate (e.g., mercury, nanoparticles, and pesticides and persistent
organic pollutants (POPs)), causing changes in brain function. In addition, an
endogenous production of metabolic byproducts including free radicals inflict
damages which constantly need to be repaired. Whereas repeated single chemical
exposures may be associated with PD [6–8], convincing evidence
is lacking that single chemical exposures (e.g., copper, mercury, or POPs) are
causal for AD; several previously suspected agents (e.g., aluminium from
antiperspirants and pans) have been written off [9]. However, there is strong support for the involvement of metal
dyshomeostasis, inflammation, and oxidative damages to biomolecules in both diseases
[10–13]. AD is a slowly progressing disease for which age is the
most important risk factor [1, 2], and factors regulating metal homeostasis and
inflammation known to change with age may be causally related to both AD and PD.
Microglia activation is seen in multiple sclerosis [14], stroke [15], traumatic brain
injury [16], Creutzfeldt-Jakob disease [17], in addition to PD and AD.In this paper, AD metal dyshomeostasis and potential AD-causative cyanobacterial
neurotoxins present in water and foods are discussed. We propose a neuronal metal
dyshomeostasis mechanism mediated by the systemic iron regulatory peptide hepcidin
and discuss therapeutic use of metal chelators and possible preventive measures. For
PD, putative roles of chemical and nanoparticle exposure, metal dyshomeostasis and
inflammation are discussed.


## 2. Alzheimer’s Disease (AD)

AD is the most common form of dementia, characterized histopathologically by
extracellular amyloid-beta (Aβ) plaques and intraneural
fibrillar tangles (microtubule-associated tau protein aggregates) along with
synaptic and neuronal losses. These pathological processes are initiated in the
entorhinal cortex and hippocampus for unknown reasons and spread as the disease
progresses, resulting in cortex and hippocampal shrinkage, dementia, personality
changes, and death. Late-onset (>60 years) sporadic AD accounts for most cases
and has been suggested to result from complex interactions among multiple genetic,
epigenetic, and environmental factors [2]
where food composition, physical, and mental activities appear important [25], but for which chemical exposure risk
factors other than possibly smoking [25] have
been difficult to identify. Individuals carrying the mutant apolipoprotein E4
(apoE4) allele are at increased risk for late-onset AD which is believed to be
related to apoE’s role in Aβ clearance [2, 26].
Early-onset (<60 years) autosomal dominant genetic inheritage accounts for less
than 1% of all AD cases [2] and affects
individuals carrying mutations in three genes: the amyloid precursor protein (APP),
and presenilin 1 and 2 (γ-secretase components). Unlike this
genotype, a rare APP mutation positioned close to the site where
β-secretase cleaves APP into
amyloid-β leads to reduced formation of
Aβ peptide monomers and protection against AD [27]. Aβ peptides (ca.
90% Aβ
40 and 10% Aβ
42, of which Aβ
42 is considered to be more toxic) are formed through sequential
intramembranous and extraneuronal proteolytic processing of the transmembranal APP
by β- and γ-secretases (Figure 1). Aβ has been
suggested to act as an antioxidant when present as a monomer but seems to lose this
function when aggregated into oligomers or plaques, then becoming a reactive oxygen
species (ROS) generator [28]. The high
prevalence of sporadic AD, with an incidence of approximately one person out of
twenty over the age of 65 suffering from Alzheimer’s disease [29], has yet not been explained by single
exposure factors. To some surprise, a moderate alcohol consumption appears to be
protective against dementia [30], possibly
due to anti-inflammatory effects [31].Figure 1
Putative linkage between cytokine (IL-6) and iron (Fe) induced hepcidin
production with APP-mediated copper (Cu) lowering in the AD brain. Both
liver and brain cells can produce the iron regulatory peptide hepcidin which
may cross the blood-brain barrier (BBB). (A) In neurons, plasma membrane
localized ferroportin exports ferrous iron (Fe2+) which is
oxidized extracellularly by means of the ferroportin-collaborating amyloid
precursor protein (APP) which has ferroxidase activity [18] and which loads ferric iron
(Fe3+) into transferrin. (B) Hepcidin binding to ferroportin
causes its internalization and lysosomal breakdown, preventing iron export
[19, 20]. In response, iron levels in individual neurons may
increase during aging, initiating APP-mRNA iron responsive constitutive
translation of APP [21] which
contains a copper binding domain. (C) APP travels to the plasma membrane and
is cleaved by secretases to form short peptides, of which the
Aβ peptide can form plaques containing metal ions
[22–24]. Lowered neuronal copper levels, for which the
cellular pool is low, can affect vital copper enzymes negatively (e.g.,
mitochondrial respiratory ATP producing COX, Cu/Zn-SOD, etc.).
Aβ-plaque attacking microglia release various
cytokines including IL-6 and ROS, that along with ROS generated from
Aβ-plaque associated redox-cycling metals (e.g.,
Fe and Cu ions) inflict free radical damage to neurons. Liver hepcidin
production affects iron metabolism in several organs (see text).In the light of new knowledge, we hypothesize that the iron and inflammation
responsive hormone hepcidin could cause metal dyshomeostasis and oxidative stress in
AD. We therefore performedin silico gene analyses of proteins
regulating metal homeostasis and compared AD cases with unaffected elderly.
Regarding environmental exposure risks, recent studies suggest that highly potent
neurotoxins from food and drink contaminated with cyanobacteria can induce
AD-resembling pathologies. Food constituents (e.g., antioxidants) can also protect
against AD and much effort is spent on developing treatments, including drugs. These
topics are discussed below.


### 2.1. Metal Dyshomeostasis in AD

For both AD and PD, numerous studies support a dysregulated metal (iron, copper,
and zinc) brain homeostasis and metal catalysed oxidative damages [10–13]. A recent meta-analysis study on reported AD (versus aged
controls) brain metal levels found no support for elevated neocortex iron,
copper, or zinc levels, but significantly decreased neocortex copper levels when
considering quantitative (metal content per wet weight tissue) analyses [32]. The same study also found a
significant publication bias, with papers reporting increased iron levels were
much more frequently cited than those reporting no change or decreased levels
[32]. Still there is convincing
support of the notion that certain Aβ-plaques forms
contain iron, copper, and zinc [22–24], and individual
intracellular or brain regional metal levels may also differ. Whereas
Aβ-plaque associated iron and copper ions can redox
cycle and produce ROS [11], zinc does
not, but has been reported to be a particularly good
Aβ-plaque aggregator [24, 33] and a tau
hyperphosphorylation inducer [34]. Zinc
may also inhibit APP’s iron-export ferroxidase activity [18]. Approximately 20–40% of
cognitively normal elderly people also show evidence of significant brain
Aβ-plaque depositions [35] suggesting that not all plaque forms are toxic. Another
recent meta-analysis found significantly increased serum copper levels among AD
patients versus controls [36]. Positive
outcomes dominate when metal chelators were administrated therapeutically in AD
animal models and in clinical human AD studies, see below.


### 2.2. Are Hepcidin and APP Causal for Decreased Copper Levels in AD Cortex
Neurons?

In the brain, the complex processes regulating metal delivery to the various cell
types, metal storage and export mechanisms, are yet not fully understood. In
aging, a mild systemic inflammation [37]
and elevated iron levels in some organs (brain [38–40], skeletal
muscle [41, 42], and liver [41])
is commonly seen, while iron levels decrease in bone marrow (related to anaemia)
[43]. Human brain iron levels
increase with age to reach a relative steady state at around 55 years in
neurologically normal subjects [32].
Hepcidin, a master regulator of body iron metabolism, is an evolutionary
conserved antimicrobial-like peptide hormone expressed in several organs
including brain [20, 44] as part of the innate (nonspecific)
immune system in response to pathogens [45] including lipopolysaccharide (LPS) [44]. Hepcidin restricts iron availability for microbes by
its binding to the only known cellular iron exporter ferroportin in host cell
membranes which causes internalization and lysosomal ferroportin degradation
(Figure 1) [19]. Liver hepcidin expression can be induced via the bone
morphogenetic protein (BMP6) pathway by intracellular iron or through the
JAK-STAT3 pathway by the cytokine interleukin 6 (IL-6; possibly also other
cytokines) [46, 47]. Brain hepcidin mRNA increases with aging in mice
[20]. The expression of the iron
exporter ferroportin is induced by iron (and heme) through an mRNA iron
regulatory element (IRE) [48]. However,
in experiments studying neuronal cell (substantia nigra) produced hepcidin
[49] or injected hepcidin [50], hepcidin was found to downregulate
ferroportin expression, suggesting that hepcidin (over iron) dominantly controls
ferroportin. Systemic increased plasma hepcidin lowers transferrin-bound plasma
iron by inhibiting iron release from several organs (also liver).
Reticuloendothelial cells (macrophages) accumulate iron through constant red
blood cell phagocytosis; with increased hepcidin less iron passes on towards the
bone marrow for red blood cell synthesis by hematopoietic cells [46], which may cause age-related anaemia
[51]. Also iron absorption from food
in the gut is blocked since hepcidin prevents enterocyte-mediated iron export
into the blood system. It is presently unclear if liver produced hepcidin
reaches the brain, but several peptides are known to cross the blood-brain
barrier (BBB). It is suggested that hepcidin in the brain mainly originates from
other organs (unpublished data) [52]. The
same study found that hepcidin was absent in microglia but colocalized with
ferroportin in neurons and astrocytes [52]. Hepcidin’s inhibition of ferroportin [19] may increase intracellular neuronal iron levels which
can induce APP-mRNA translation due to an IRE stem loop in the
5′-untranslated region [21].APP is a multifunctional metalloprotein containing a copper binding domain (not
localized in its Aβ part) [53]. APP was found to possess ferroxidase (oxidizes
Fe2+ into Fe3+) activity assisting in plasma membrane
Fe2+-export by ferroportin, counteracting iron accumulation and
oxidative stress [18]. APP’s
ferroxidase activity has been shown to take place on the extracellular plasma
membrane side, where APP (in interaction with ferroportin) loads Fe3+
into blood transferrin [18] (Figure 1). Ceruloplasmin also has ferroxidase
activity, but this protein is normally not expressed in cortical neurons [54]. APP may therefore be the sole
iron-exporting ferroxidase in neurons [18].In neuronal supporting astrocytes, cellular copper export is mediated by the
copper transporting P-type ATPase ATP7A, which translocates from the trans-Golgi
network to the plasma membrane in the presence of elevated copper [55]. Free intracellular copper is bound to
metallothioneins or is stored in vesicular copper pools, but copper levels are
generally low, much lower than the iron pool which includes cytosolic and
mitochondrially stored iron in the form of ferritin. We hypothesize that
constitutive expression of APP may be responding to elevated iron levels in
individual neurons, with the purpose of assisting iron export by ferroportin
through the plasma membrane. However, since ferroportin may have been
internalized by hepcidin, and since APP has a copper binding domain [53], constitutive APP transmembranal
passage and extracellular proteolysis may reduce the already relatively low
intracellular copper pool, resulting in suboptimal copper levels in individual
neurons. In support of this (see also Section 2.3), overexpression of the APP in transgenic mice resulted in
significantly lower copper levels, but the iron levels remained unaltered [56]. Enzymes requiring copper include
cytoplasmic Cu/Zn-superoxide dismutase (intracellular SOD1, extracellular SOD3),
tyrosinase, cytochrome c oxidase (COX), ceruloplasmin, dopamine
beta-hydroxylase, hephaestin, lysyl oxidase, peptidylglycine alpha-amidating
monooxygenase (PAM), and amine oxidases, of which several are important for
neurological functioning [57]. COX is
vital for mitochondrial respiratory ATP production, and fewer well-functional
mitochondria may induce apoptosis. Significantly decreased COX activities (but
not respiratory complexes I + III, II + III activities) in AD temporal cortex
and hippocampus were observed [58].
Decreased SOD1 activity and increased cerebrospinal fluid copper levels were
noted in several neurodegenerative diseases [59].In addition to the described cellular challenges, microglial cells recognize and
attack Aβ-plaques, starting a vicious circle of ROS
(e.g., superoxide, O
2
•
-; hydrogen peroxide, H2O2; and
hypochlorous acid, HOCl) and cytokine (e.g., IL-6, IL-1β,
and tumour necrosis factor-alfa, TNF-α) release [60] (Figure
1). ROS is also produced from
extracellular iron and copper ions attached to
Aβ-oligomers and plaques [23, 24], and peroxides react
with loosely attached redox-cycling intracellular iron ions attached to
biomolecules (e.g., nucleic acids, lipids, and proteins) inflicting oxidative
damage. Elevated intracellular ROS levels can also be sensed by transcription
factors such as heme oxygenase-1 (HO-1) [61] and also nuclear factor-kappa B (NF-κB)
[62], which can lead to further
production of inflammatory cytokines also in neurons. Notably, microglia also
have a protective role by mediating clearance of Aβ
through phagocytosis [63].Negatively charged nucleic acids attract loosely attached iron ions inflicting
ROS mediated damages through Fenton chemistry [64, 65]. In particular,
oxidative RNA damages, commonly observed in AD [10, 66, 67], may cause erroneous protein translations or
truncations leading to dysfunctional proteins [66]. Observation of significantly less protein in AD frontal cortex
has been reported [68]. Reactive
byproducts from lipid peroxidation include the intermediates
4-hydroxy-2,3-nonenal (HNE), 4-oxo-2-nonenal (ONE), and acrolein, that react
with macromolecules forming alkylative adducts [12, 69]. Metal-catalysed
oxidation of amino acids generates protein carbonyls [70, 71] which may
hinder proper protein function. Not all forms of alkylative and oxidative
lesions are well repaired.


### 2.3.In Silico Analysis of Genes Involved in Brain
Copper/Iron Homeostasis Pathway

We wanted to investigate how the expression patterns of genes involved in brain
copper/iron homeostasis pathway are modulated in neurologically normal (healthy)
elderly and AD-affected individuals. To do so, we performed a search in the
publicly available gene expression database NCBI Gene Expression Omnibus (GEO)
[72]. We used the microarray data
from Liang et al. (2008) [73] and Liang
et al. (2007) [74] (GEO accession number
GSE5281), which are comprehensive genome-wide gene expression studies of samples
collected from six brain regions that are either histopathologically or
metabolically relevant to AD: hippocampus (HIP), entorhinal cortex (EC), middle
temporal gyrus (MTG), posterior cingulate cortex (PC), superior frontal gyrus
(SFG), and primary visual cortex (VCX) [73, 74]. For more detailed
description of sample collection, experimental design and flow, we refer the
reader to the original studies [73, 74]. We downloaded the raw microarray data
(GSE5281) deposited in the GEO database [72]. The raw microarray data were reanalyzed using J-Express v2009
as described previously [75, 76]. From the dataset we selected 61 genes
involved in brain copper/iron homeostasis pathway. The processed intensities of
the selected 61 genes were log2-transformed. Figure 2 shows unsupervised hierarchical clustering analysis of
these 61 genes, and the results were visualized in a dendrogram using the MeV
v4.7 software [77]. By visual inspection
of the heatmap (Figure 2), we observed
that samples from AD-affected individuals clustered close to each other in one
branch while samples from normal elderly individuals clustered in the other
branch. Two-class, unpaired SAM (Significance Analysis of Microarray) [78] analysis was conducted in order to
identify genes whose mean expression level is significantly different between
AD-affected and normal elderly individuals control samples. Twenty-one genes
were differentially expressed (false discovery rate, FDR < 10%).
Eleven of these genes were overexpressed in AD-affected individuals and
underexpressed in normal elderly individuals, whereas 10 genes were
underexpressed in AD-affected individuals and overexpressed in normal elderly
individuals (Table 1). Genes
overexpressed in AD-affected individuals include FTHL17, SLC40A1, AOC3,
MT1E, HEPH, MT1X, MT1H, MT1F, MT1G, MT2A, and MT1 M(Table 1), and most of these
genes clustered close to each other in one branch (Figure 2), while COX6A1, COX6C, HMOX2, COX11, SOD1, PAM,
ATOX1, COX5B, COX6B1, and COX7B were
underexpressed (Table 1), and clustered
together in another branch (Figure 2).
Notably, brain tissue is composed of several types of cells (astrocytes,
neurons, microglia, and endothelial cells, etc.) where neuron supporting
astrocytes numerically dominate, but the results show that crucial
copper-dependent enzymes (COX, SOD1, and PAM) and ATOX1 (a copper-chaperone
protein) are underexpressed in AD brains. Amine oxidase (copper containing 3),
however, was overexpressed in AD brains for unclear reasons. Moreover, in AD
brains, several metallothioneins (small copper and zinc binding proteins) are
overexpressed, as well as iron binding ferritin and ferroportin (SLC40A1).
Hephaestin (contains copper but functions as an iron ferroxidase in
collaboration with ferroportin) was overexpressed in AD brains. Tight
transcriptional control of the Cu/Fe homeostasis pathway involved genes in the
brain is very important, and dysregulation of these genes might affect the Cu/Fe
balance, resulting in potential damage to brain function. The gene expression
profiles constituted by these altered genes can be used to identify candidate
genes to be associated with AD, which might contribute to early detection of
this complex disorder. Identifying AD-predictive genes may uncover gene products
with mechanistic properties relevant to AD; this should be pursued in future
studies.Table 1
Genes (n
=
21) involved in brain metal homeostasis pathways for
which expression is significantly changed in AD.
Gene symbol
Description
SAM score (d)*
Fold up- or downregulation
MT1M
Metallothionein 1M
6.7
2.50
MT2A
Metallothionein 2A
5.3
2.00
MT1G
Metallothionein 1G
4.8
2.30
MT1F
Metallothionein 1F
4.6
2.30
MT1H
Metallothionein 1H
4.4
2.00
MT1X
Metallothionein 1X
4.2
1.80
HEPH
Hephaestin
4.1
2.00
MT1E
Metallothionein 1E
4.0
1.80
AOC3
Amine oxidase, copper containing 3 (vascular
adhesion protein 1)
3.8
2.90
SLC40A1
Solute carrier family 40 (iron-regulated
transporter), member 1
3.0
1.50
FTHL17
Ferritin, heavy polypeptide-like 17
2.2
1.60
COX6A1
Cytochrome c oxidase subunit VIa polypeptide
1
−3.3
−1.43
COX6C
Cytochrome c oxidase subunit VIc
−3.7
−1.67
HMOX2
Heme oxygenase (decycling) 2
−3.7
−1.67
COX11
COX11 cytochrome c oxidase assembly homolog
(yeast)
−4.3
−1.43
SOD1
Superoxide dismutase 1, soluble
−4.5
−2.00
PAM
Peptidylglycine alpha-amidating
monooxygenase
−4.6
−1.67
ATOX1
ATX1 antioxidant protein 1 homolog (yeast)
−4.6
−2.00
COX5B
Cytochrome c oxidase subunit Vb
−5.2
−1.67
COX6B1
Cytochrome c oxidase subunit VIb polypeptide 1
(ubiquitous)
−5.3
−2.00
COX7B
Cytochrome c oxidase subunit VIIb
−5.8
−2.00
*Significantly differentially expressed genes between
AD-affected cases and controls, FDR < 10% for GSE5281
microarray date, and unlogged fold up- and downregulated genes (n
=
21). Eleven genes were overexpressed and 10 genes
were underexpressed in the samples from AD-affected cases in
comparison to age-matched unaffected controls.Figure 2
Unsupervised hierarchical clustering analysis of 61 selected genes
involved in brain copper/iron homeostasis, comparing gene expression
profiles of AD and unaffected age-matched controls. Unsupervised
hierarchical clustering analysis (complete-linkage and Manhattan
distance similarity measurement) is based on similarities in gene
expression. The 21 SAM-identified genes are color coded (right side of
figure) based on the group they belong to: red color code represents 11
overexpressed genes, while green color code represents 10 underexpressed
genes. The horizontal red color bar indicates AD-affected samples (n
=
87), whereas the green bar indicates normal elderly
controls (n
=
74).


### 2.4. Cyanobacterial Toxins-Potential Tauopathy and AD Risk Factors

Cyanobacteria and their potential impact on human health are an emerging public
health issue that has received increasing scientific interest resulting in new
research [79–81]. While it has been confirmed that cyanobacteria produce
toxins (e.g., microcystins, MCs [80], and
chemicals resembling amino acids [81])
that are potentially capable of causing neurological disorders in humans, many
questions remain unanswered regarding the identification and quantification of
cyanobacteria and cyanotoxins in the environment and to what degree they
translate into health risks.Several freshwater cyanobacteria produce MCs that irreversibly inhibit
serine/threonine-specific protein phosphatases [83] and have caused morbidities in animals and humans [84, 85]. In a severe human MC intoxication 1996 in Caruaru, Brazil,
patients developed signs of acute neurotoxicity, for example, deafness,
tinnitus, intermittent blindness, as well as subsequent hepatotoxicity [86]. In conjunction with some animal
studies this suggests that MCs are potent neurotoxins acting by inducing caspase
activity, chromatin condensation, and microtubule tau hyperphosphorylation
[79, 83]. In one study, the effect of MCs on neurite degeneration has
been analyzed with confocal microscopy; neurite length was determined using
image analysis [83]. MC induced
significant neurodegeneration already at 0.5 μM
MC-LF (Figure 3) and neuronal apoptosis
was significantly increased by the MC variants MC-LF and MC-LW at higher
concentrations (≥3 μM). Moreover, sustained
hyperphosphorylation of the tau protein with all MC congeners was found [83]. The concentration and
congener-dependent mechanisms observed suggest that low concentrations of MC-LF
and MC-LW can induce subtle neurodegenerative effects, reminiscent of
Alzheimer’s disease type human tauopathies. Such effects should be taken
more seriously with regard to potential human health effects, than the apical
cytotoxicity (apoptosis or necrosis) demonstrated at high MC concentrations
[83]. It has been shown that MC-LR
(see Figure 3) treated hippocampi showed
alterations in proteins involved in cytoskeleton, neurodegenerative disease,
oxidative stress, apoptosis, and energy metabolism; three proteins related to
neurodegenerative disease, septin5,  α-internexin, and  α-synuclein, were identified to be altered by MC-LR exposure. It
was found that MC-LR induced inhibition of protein phosphatases and abnormal
hyperphosphorylation of the neural microtubule associated protein tau [79]. This was found to lead to impairment
of learning and memory, accompanied by severe damage and neuronal apoptosis in
the hippocampal CA1 regions of rats. Thus, MC-LR was found to induce tau
hyperphosphorylation, spatial memory impairment, neural degenerative changes,
and apoptosis, suggesting that this cyanotoxin may contribute to
Alzheimer’s disease in humans [79].Figure 3
General
“cyclo–(D-Ala1–X2–D–MeAsp3–Z4–Adda5–D–Glu6–Mdha7)”
structure of microcystins (MCs), showing the most frequently found
variations. X and Z are variable L-amino acids (in MC-LR, MC-LF and
MC-LW, X = L-Leucine (L) and Z = arginine (R), phenylalanine (F) or
tryptophan (W)); R1 and R2 are H
(demethylmicrocystins) or CH3; D-MeAsp is
D-erythro-β-methylaspartic
acid and Adda is
(2S,3S,8S,9S)-3-amino-9-methoxy-2,6,8-trimethyl-10-phenyldeca-4,6
dienooic acid; Mdha is N-methyldehydroalanine (Dha = dehydroalanine).
From [82].Cyanobacteria also produce beta-methylamino-L-alanine (BMAA; Figure4), a nonprotein amino acid produced by
several cyanobacteria including Spirulina that can be
misincorporated into protein chains within human neurons, causing proteins to
misfold and form aggregates within the cells [87] and is thought to lead to neurofibrillary tangles, an indication
of neurodegenerative disease. Whereas a tie between cyanobacteria and human
health is rather well accepted [80], at
this point there is interestingly also a possible tie between cyanobacterial
toxins and risk of progressive neurodegenerative disease (BMAA was identified in
neuroproteins from AD and amyotrophic lateral sclerosis (ALS) brains [88]), an issue which is rarely
discussed.Figure 4
β-Methylamino-L-alanine (BMAA).Exposure to cyanobacteria toxins can occur by drinking untreated water from a
lake, pond, reservoir, or spring with a cyanobacterial bloom, or when ingesting
contaminated foods (e.g., crops watered with untreated water) [89]. Also aerosol inhalation from blooming
waters may pose a health risk, for example, when watering the lawn. MC
intoxication frequently occurs in conjunction with toxic cyanobacterial blooms
in water reservoirs (lakes and ponds) used for drinking water or recreational
purposes. It has also been suggested that nutritional supplements from
cyanobacteria (blue-green algae) such as Spirulina and
Aphanizomenon may not only be beneficial as they may
contain MCs which constitute a group of cyanobacterial toxins with more than 100
congeners [90]. Since cyanobacteria
blooms occur all over the world, the possible implication of the cyanobacteria
for health problems might be severe. Globally the most frequently found
cyanobacterial toxins in blooms from fresh and brackish waters are the cyclic
peptide toxins of the microcystin and nodularin family [82]. Large numbers of the human population are therefore at
risk to be exposed to these toxins with adverse health effects.


### 2.5. Treatment of and Protection from AD

Removing pathogenic Aβ peptides to prevent, and possibly
reverse, aggregation is the most sought after method for slowing or delaying the
onset of AD. Development of AD-modifying drugs include amyloidtargeting
monoclonal antibodies (mAbs), β- and
γ-secretase inhibitors, anti-amyloid vaccines, and
tau-based therapies [3]. In principle,
Aβ targeting mAbs should penetrate the blood-brain
barrier and recognize various forms of Aβ, guiding
Aβ clearance into the blood stream for liver
degradation. However, some recent clinical mAbs phase III trials have failed
[3]. Secretase inhibitors are intended
to decrease APP cleavage and lower the amount of Aβ
peptides formed, and, vaccines can be used to boost the immune system to
recognize Aβ. Tau-based therapies are reported to
moderate downstream effects due to Aβ-plaque build-up
[3].The hepcidin-mediated copper lowering mechanisms discussed above suggest that
locally active antagonists interfering with hepcidin’s binding to
neuronal cell’s ferroportin would be expected to promote neuronal
ferroportin export of iron, decreasing undesired APP-mediated copper export as
well as iron-mediated oxidative damages intracellularly. Ways of downregulating
hepatic hepcidin expression (e.g., siRNA) could be attempted, but lowered
systemic hepcidin levels will also result in increased intestinal iron
absorption. Membrane-permeable metal chelators capable of washing out toxic
metals may be effective [91–94], and in vitro,
Aβ deposits can be dissolved using metal chelators
[22]. Lowering systemic iron levels
by controlled phlebotomy has been suggested as an AD therapeutic [95]. A clinical study administrating
deferoxamine (a nonmembrane-permeable strong Fe3+-chelator that to
some degree is taken up into cells by endocytosis, but which does not cross the
BBB readily) slowed the clinical progression of dementia associated with AD
[96]. For a patient suffering from an
iron metabolism disorder, treatment for 10 months with the iron chelator
deferoxamine decreased brain iron stores, prevented progression of the
neurological symptoms, and reduced plasma lipid peroxidation [97]. Many issues confront the use of
chelators including metal saturation. The compounds’ ability to reach the
intended site is affected by metabolic instability, and toxicity is an important
issue (administration of copper chelators to dissolve
Aβ-plaques could further lower neuronal copper levels,
etc). Current clinical oral administration of lipophilic membrane permeable iron
chelators includes deferiprone (produced by ApoPharma) and deferasirox
(Novartis). These are today mainly used for treatment of thalassemia major and
anaemia, respectively; only a few reports concern their uses in relevant
neurodegenerative situations [98].
Molecular modifications may be needed for improved BBB passage and stability
[99]. For efficient iron removal from
the brain, it has been suggested that the lipophilic chelator-iron (III) complex
should have a molecular mass less than 500 Da and be uncharged for cell
membrane and BBB permeability [93]. The
copper/zinc chelator clioquinol (CQ) [100] was suggested to inhibit Aβ accumulation
due to its ability to remove metals from the brain; however, CQ is now
considered toxic. This led to the development of the analogue PBT2, a potential
therapeutic compound for AD which reduced cerebrospinal fluid (CSF)
Aβ
42 and improved cognition without serious adverse effects, according
to a phase II clinical trial [101]; the
compound is being further investigated. Other chelators tested in AD models
having showed positive effects include the iron chelator M30 [92], the copper chelators JKL-169 [102] and IQM-622 [103], and the calcium/copper/zinc chelators DP-109 and
DP-460 [104, 105]. On the contrary, a clinical trial of
D-penicillamine, a copper chelator, was unable to produce any clinical
improvement in AD patients and resulted in toxicities [106]. Nanoparticle-based chelators that can cross the
blood-brain barrier are also being developed [107].Antioxidants from food such as flavonoids, carotenoids, tocopherols, and selenium
have been suggested to protect against AD [94, 108–111]. Interestingly, the occurrence of AD
in India was found to be just one quarter of that in the USA which may be
related to intake of the plant phenolic antioxidant curcumin possessing iron
binding capacity [112]. Curcumin is
present in roots of the turmeric plant used as spice in various foods including
curry [108, 113]. Natural antioxidants have also showed protective
effects against PD [114], and can also
lower microglial cytokine production [115]. Also food compounds not expected to act as antioxidants may
protect against neurodegeneration. One example is caffeine (present in coffee)
which has been suggested to be a potent neuroprotector [116, 117].


## 2.1. Metal Dyshomeostasis in AD

For both AD and PD, numerous studies support a dysregulated metal (iron, copper,
and zinc) brain homeostasis and metal catalysed oxidative damages [10–13]. A recent meta-analysis study on reported AD (versus aged
controls) brain metal levels found no support for elevated neocortex iron,
copper, or zinc levels, but significantly decreased neocortex copper levels when
considering quantitative (metal content per wet weight tissue) analyses [32]. The same study also found a
significant publication bias, with papers reporting increased iron levels were
much more frequently cited than those reporting no change or decreased levels
[32]. Still there is convincing
support of the notion that certain Aβ-plaques forms
contain iron, copper, and zinc [22–24], and individual
intracellular or brain regional metal levels may also differ. Whereas
Aβ-plaque associated iron and copper ions can redox
cycle and produce ROS [11], zinc does
not, but has been reported to be a particularly good
Aβ-plaque aggregator [24, 33] and a tau
hyperphosphorylation inducer [34]. Zinc
may also inhibit APP’s iron-export ferroxidase activity [18]. Approximately 20–40% of
cognitively normal elderly people also show evidence of significant brain
Aβ-plaque depositions [35] suggesting that not all plaque forms are toxic. Another
recent meta-analysis found significantly increased serum copper levels among AD
patients versus controls [36]. Positive
outcomes dominate when metal chelators were administrated therapeutically in AD
animal models and in clinical human AD studies, see below.


## 2.2. Are Hepcidin and APP Causal for Decreased Copper Levels in AD Cortex
Neurons?

In the brain, the complex processes regulating metal delivery to the various cell
types, metal storage and export mechanisms, are yet not fully understood. In
aging, a mild systemic inflammation [37]
and elevated iron levels in some organs (brain [38–40], skeletal
muscle [41, 42], and liver [41])
is commonly seen, while iron levels decrease in bone marrow (related to anaemia)
[43]. Human brain iron levels
increase with age to reach a relative steady state at around 55 years in
neurologically normal subjects [32].
Hepcidin, a master regulator of body iron metabolism, is an evolutionary
conserved antimicrobial-like peptide hormone expressed in several organs
including brain [20, 44] as part of the innate (nonspecific)
immune system in response to pathogens [45] including lipopolysaccharide (LPS) [44]. Hepcidin restricts iron availability for microbes by
its binding to the only known cellular iron exporter ferroportin in host cell
membranes which causes internalization and lysosomal ferroportin degradation
(Figure 1) [19]. Liver hepcidin expression can be induced via the bone
morphogenetic protein (BMP6) pathway by intracellular iron or through the
JAK-STAT3 pathway by the cytokine interleukin 6 (IL-6; possibly also other
cytokines) [46, 47]. Brain hepcidin mRNA increases with aging in mice
[20]. The expression of the iron
exporter ferroportin is induced by iron (and heme) through an mRNA iron
regulatory element (IRE) [48]. However,
in experiments studying neuronal cell (substantia nigra) produced hepcidin
[49] or injected hepcidin [50], hepcidin was found to downregulate
ferroportin expression, suggesting that hepcidin (over iron) dominantly controls
ferroportin. Systemic increased plasma hepcidin lowers transferrin-bound plasma
iron by inhibiting iron release from several organs (also liver).
Reticuloendothelial cells (macrophages) accumulate iron through constant red
blood cell phagocytosis; with increased hepcidin less iron passes on towards the
bone marrow for red blood cell synthesis by hematopoietic cells [46], which may cause age-related anaemia
[51]. Also iron absorption from food
in the gut is blocked since hepcidin prevents enterocyte-mediated iron export
into the blood system. It is presently unclear if liver produced hepcidin
reaches the brain, but several peptides are known to cross the blood-brain
barrier (BBB). It is suggested that hepcidin in the brain mainly originates from
other organs (unpublished data) [52]. The
same study found that hepcidin was absent in microglia but colocalized with
ferroportin in neurons and astrocytes [52]. Hepcidin’s inhibition of ferroportin [19] may increase intracellular neuronal iron levels which
can induce APP-mRNA translation due to an IRE stem loop in the
5′-untranslated region [21].APP is a multifunctional metalloprotein containing a copper binding domain (not
localized in its Aβ part) [53]. APP was found to possess ferroxidase (oxidizes
Fe2+ into Fe3+) activity assisting in plasma membrane
Fe2+-export by ferroportin, counteracting iron accumulation and
oxidative stress [18]. APP’s
ferroxidase activity has been shown to take place on the extracellular plasma
membrane side, where APP (in interaction with ferroportin) loads Fe3+
into blood transferrin [18] (Figure 1). Ceruloplasmin also has ferroxidase
activity, but this protein is normally not expressed in cortical neurons [54]. APP may therefore be the sole
iron-exporting ferroxidase in neurons [18].In neuronal supporting astrocytes, cellular copper export is mediated by the
copper transporting P-type ATPase ATP7A, which translocates from the trans-Golgi
network to the plasma membrane in the presence of elevated copper [55]. Free intracellular copper is bound to
metallothioneins or is stored in vesicular copper pools, but copper levels are
generally low, much lower than the iron pool which includes cytosolic and
mitochondrially stored iron in the form of ferritin. We hypothesize that
constitutive expression of APP may be responding to elevated iron levels in
individual neurons, with the purpose of assisting iron export by ferroportin
through the plasma membrane. However, since ferroportin may have been
internalized by hepcidin, and since APP has a copper binding domain [53], constitutive APP transmembranal
passage and extracellular proteolysis may reduce the already relatively low
intracellular copper pool, resulting in suboptimal copper levels in individual
neurons. In support of this (see also Section 2.3), overexpression of the APP in transgenic mice resulted in
significantly lower copper levels, but the iron levels remained unaltered [56]. Enzymes requiring copper include
cytoplasmic Cu/Zn-superoxide dismutase (intracellular SOD1, extracellular SOD3),
tyrosinase, cytochrome c oxidase (COX), ceruloplasmin, dopamine
beta-hydroxylase, hephaestin, lysyl oxidase, peptidylglycine alpha-amidating
monooxygenase (PAM), and amine oxidases, of which several are important for
neurological functioning [57]. COX is
vital for mitochondrial respiratory ATP production, and fewer well-functional
mitochondria may induce apoptosis. Significantly decreased COX activities (but
not respiratory complexes I + III, II + III activities) in AD temporal cortex
and hippocampus were observed [58].
Decreased SOD1 activity and increased cerebrospinal fluid copper levels were
noted in several neurodegenerative diseases [59].In addition to the described cellular challenges, microglial cells recognize and
attack Aβ-plaques, starting a vicious circle of ROS
(e.g., superoxide, O
2
•
-; hydrogen peroxide, H2O2; and
hypochlorous acid, HOCl) and cytokine (e.g., IL-6, IL-1β,
and tumour necrosis factor-alfa, TNF-α) release [60] (Figure
1). ROS is also produced from
extracellular iron and copper ions attached to
Aβ-oligomers and plaques [23, 24], and peroxides react
with loosely attached redox-cycling intracellular iron ions attached to
biomolecules (e.g., nucleic acids, lipids, and proteins) inflicting oxidative
damage. Elevated intracellular ROS levels can also be sensed by transcription
factors such as heme oxygenase-1 (HO-1) [61] and also nuclear factor-kappa B (NF-κB)
[62], which can lead to further
production of inflammatory cytokines also in neurons. Notably, microglia also
have a protective role by mediating clearance of Aβ
through phagocytosis [63].Negatively charged nucleic acids attract loosely attached iron ions inflicting
ROS mediated damages through Fenton chemistry [64, 65]. In particular,
oxidative RNA damages, commonly observed in AD [10, 66, 67], may cause erroneous protein translations or
truncations leading to dysfunctional proteins [66]. Observation of significantly less protein in AD frontal cortex
has been reported [68]. Reactive
byproducts from lipid peroxidation include the intermediates
4-hydroxy-2,3-nonenal (HNE), 4-oxo-2-nonenal (ONE), and acrolein, that react
with macromolecules forming alkylative adducts [12, 69]. Metal-catalysed
oxidation of amino acids generates protein carbonyls [70, 71] which may
hinder proper protein function. Not all forms of alkylative and oxidative
lesions are well repaired.


## 2.3.In Silico Analysis of Genes Involved in Brain
Copper/Iron Homeostasis Pathway

We wanted to investigate how the expression patterns of genes involved in brain
copper/iron homeostasis pathway are modulated in neurologically normal (healthy)
elderly and AD-affected individuals. To do so, we performed a search in the
publicly available gene expression database NCBI Gene Expression Omnibus (GEO)
[72]. We used the microarray data
from Liang et al. (2008) [73] and Liang
et al. (2007) [74] (GEO accession number
GSE5281), which are comprehensive genome-wide gene expression studies of samples
collected from six brain regions that are either histopathologically or
metabolically relevant to AD: hippocampus (HIP), entorhinal cortex (EC), middle
temporal gyrus (MTG), posterior cingulate cortex (PC), superior frontal gyrus
(SFG), and primary visual cortex (VCX) [73, 74]. For more detailed
description of sample collection, experimental design and flow, we refer the
reader to the original studies [73, 74]. We downloaded the raw microarray data
(GSE5281) deposited in the GEO database [72]. The raw microarray data were reanalyzed using J-Express v2009
as described previously [75, 76]. From the dataset we selected 61 genes
involved in brain copper/iron homeostasis pathway. The processed intensities of
the selected 61 genes were log2-transformed. Figure 2 shows unsupervised hierarchical clustering analysis of
these 61 genes, and the results were visualized in a dendrogram using the MeV
v4.7 software [77]. By visual inspection
of the heatmap (Figure 2), we observed
that samples from AD-affected individuals clustered close to each other in one
branch while samples from normal elderly individuals clustered in the other
branch. Two-class, unpaired SAM (Significance Analysis of Microarray) [78] analysis was conducted in order to
identify genes whose mean expression level is significantly different between
AD-affected and normal elderly individuals control samples. Twenty-one genes
were differentially expressed (false discovery rate, FDR < 10%).
Eleven of these genes were overexpressed in AD-affected individuals and
underexpressed in normal elderly individuals, whereas 10 genes were
underexpressed in AD-affected individuals and overexpressed in normal elderly
individuals (Table 1). Genes
overexpressed in AD-affected individuals include FTHL17, SLC40A1, AOC3,
MT1E, HEPH, MT1X, MT1H, MT1F, MT1G, MT2A, and MT1 M(Table 1), and most of these
genes clustered close to each other in one branch (Figure 2), while COX6A1, COX6C, HMOX2, COX11, SOD1, PAM,
ATOX1, COX5B, COX6B1, and COX7B were
underexpressed (Table 1), and clustered
together in another branch (Figure 2).
Notably, brain tissue is composed of several types of cells (astrocytes,
neurons, microglia, and endothelial cells, etc.) where neuron supporting
astrocytes numerically dominate, but the results show that crucial
copper-dependent enzymes (COX, SOD1, and PAM) and ATOX1 (a copper-chaperone
protein) are underexpressed in AD brains. Amine oxidase (copper containing 3),
however, was overexpressed in AD brains for unclear reasons. Moreover, in AD
brains, several metallothioneins (small copper and zinc binding proteins) are
overexpressed, as well as iron binding ferritin and ferroportin (SLC40A1).
Hephaestin (contains copper but functions as an iron ferroxidase in
collaboration with ferroportin) was overexpressed in AD brains. Tight
transcriptional control of the Cu/Fe homeostasis pathway involved genes in the
brain is very important, and dysregulation of these genes might affect the Cu/Fe
balance, resulting in potential damage to brain function. The gene expression
profiles constituted by these altered genes can be used to identify candidate
genes to be associated with AD, which might contribute to early detection of
this complex disorder. Identifying AD-predictive genes may uncover gene products
with mechanistic properties relevant to AD; this should be pursued in future
studies.Table 1
Genes (n
=
21) involved in brain metal homeostasis pathways for
which expression is significantly changed in AD.
Gene symbol
Description
SAM score (d)*
Fold up- or downregulation
MT1M
Metallothionein 1M
6.7
2.50
MT2A
Metallothionein 2A
5.3
2.00
MT1G
Metallothionein 1G
4.8
2.30
MT1F
Metallothionein 1F
4.6
2.30
MT1H
Metallothionein 1H
4.4
2.00
MT1X
Metallothionein 1X
4.2
1.80
HEPH
Hephaestin
4.1
2.00
MT1E
Metallothionein 1E
4.0
1.80
AOC3
Amine oxidase, copper containing 3 (vascular
adhesion protein 1)
3.8
2.90
SLC40A1
Solute carrier family 40 (iron-regulated
transporter), member 1
3.0
1.50
FTHL17
Ferritin, heavy polypeptide-like 17
2.2
1.60
COX6A1
Cytochrome c oxidase subunit VIa polypeptide
1
−3.3
−1.43
COX6C
Cytochrome c oxidase subunit VIc
−3.7
−1.67
HMOX2
Heme oxygenase (decycling) 2
−3.7
−1.67
COX11
COX11 cytochrome c oxidase assembly homolog
(yeast)
−4.3
−1.43
SOD1
Superoxide dismutase 1, soluble
−4.5
−2.00
PAM
Peptidylglycine alpha-amidating
monooxygenase
−4.6
−1.67
ATOX1
ATX1 antioxidant protein 1 homolog (yeast)
−4.6
−2.00
COX5B
Cytochrome c oxidase subunit Vb
−5.2
−1.67
COX6B1
Cytochrome c oxidase subunit VIb polypeptide 1
(ubiquitous)
−5.3
−2.00
COX7B
Cytochrome c oxidase subunit VIIb
−5.8
−2.00
*Significantly differentially expressed genes between
AD-affected cases and controls, FDR < 10% for GSE5281
microarray date, and unlogged fold up- and downregulated genes (n
=
21). Eleven genes were overexpressed and 10 genes
were underexpressed in the samples from AD-affected cases in
comparison to age-matched unaffected controls.Figure 2
Unsupervised hierarchical clustering analysis of 61 selected genes
involved in brain copper/iron homeostasis, comparing gene expression
profiles of AD and unaffected age-matched controls. Unsupervised
hierarchical clustering analysis (complete-linkage and Manhattan
distance similarity measurement) is based on similarities in gene
expression. The 21 SAM-identified genes are color coded (right side of
figure) based on the group they belong to: red color code represents 11
overexpressed genes, while green color code represents 10 underexpressed
genes. The horizontal red color bar indicates AD-affected samples (n
=
87), whereas the green bar indicates normal elderly
controls (n
=
74).


## 2.4. Cyanobacterial Toxins-Potential Tauopathy and AD Risk Factors

Cyanobacteria and their potential impact on human health are an emerging public
health issue that has received increasing scientific interest resulting in new
research [79–81]. While it has been confirmed that cyanobacteria produce
toxins (e.g., microcystins, MCs [80], and
chemicals resembling amino acids [81])
that are potentially capable of causing neurological disorders in humans, many
questions remain unanswered regarding the identification and quantification of
cyanobacteria and cyanotoxins in the environment and to what degree they
translate into health risks.Several freshwater cyanobacteria produce MCs that irreversibly inhibit
serine/threonine-specific protein phosphatases [83] and have caused morbidities in animals and humans [84, 85]. In a severe human MC intoxication 1996 in Caruaru, Brazil,
patients developed signs of acute neurotoxicity, for example, deafness,
tinnitus, intermittent blindness, as well as subsequent hepatotoxicity [86]. In conjunction with some animal
studies this suggests that MCs are potent neurotoxins acting by inducing caspase
activity, chromatin condensation, and microtubule tau hyperphosphorylation
[79, 83]. In one study, the effect of MCs on neurite degeneration has
been analyzed with confocal microscopy; neurite length was determined using
image analysis [83]. MC induced
significant neurodegeneration already at 0.5 μM
MC-LF (Figure 3) and neuronal apoptosis
was significantly increased by the MC variants MC-LF and MC-LW at higher
concentrations (≥3 μM). Moreover, sustained
hyperphosphorylation of the tau protein with all MC congeners was found [83]. The concentration and
congener-dependent mechanisms observed suggest that low concentrations of MC-LF
and MC-LW can induce subtle neurodegenerative effects, reminiscent of
Alzheimer’s disease type human tauopathies. Such effects should be taken
more seriously with regard to potential human health effects, than the apical
cytotoxicity (apoptosis or necrosis) demonstrated at high MC concentrations
[83]. It has been shown that MC-LR
(see Figure 3) treated hippocampi showed
alterations in proteins involved in cytoskeleton, neurodegenerative disease,
oxidative stress, apoptosis, and energy metabolism; three proteins related to
neurodegenerative disease, septin5,  α-internexin, and  α-synuclein, were identified to be altered by MC-LR exposure. It
was found that MC-LR induced inhibition of protein phosphatases and abnormal
hyperphosphorylation of the neural microtubule associated protein tau [79]. This was found to lead to impairment
of learning and memory, accompanied by severe damage and neuronal apoptosis in
the hippocampal CA1 regions of rats. Thus, MC-LR was found to induce tau
hyperphosphorylation, spatial memory impairment, neural degenerative changes,
and apoptosis, suggesting that this cyanotoxin may contribute to
Alzheimer’s disease in humans [79].Figure 3
General
“cyclo–(D-Ala1–X2–D–MeAsp3–Z4–Adda5–D–Glu6–Mdha7)”
structure of microcystins (MCs), showing the most frequently found
variations. X and Z are variable L-amino acids (in MC-LR, MC-LF and
MC-LW, X = L-Leucine (L) and Z = arginine (R), phenylalanine (F) or
tryptophan (W)); R1 and R2 are H
(demethylmicrocystins) or CH3; D-MeAsp is
D-erythro-β-methylaspartic
acid and Adda is
(2S,3S,8S,9S)-3-amino-9-methoxy-2,6,8-trimethyl-10-phenyldeca-4,6
dienooic acid; Mdha is N-methyldehydroalanine (Dha = dehydroalanine).
From [82].Cyanobacteria also produce beta-methylamino-L-alanine (BMAA; Figure4), a nonprotein amino acid produced by
several cyanobacteria including Spirulina that can be
misincorporated into protein chains within human neurons, causing proteins to
misfold and form aggregates within the cells [87] and is thought to lead to neurofibrillary tangles, an indication
of neurodegenerative disease. Whereas a tie between cyanobacteria and human
health is rather well accepted [80], at
this point there is interestingly also a possible tie between cyanobacterial
toxins and risk of progressive neurodegenerative disease (BMAA was identified in
neuroproteins from AD and amyotrophic lateral sclerosis (ALS) brains [88]), an issue which is rarely
discussed.Figure 4
β-Methylamino-L-alanine (BMAA).Exposure to cyanobacteria toxins can occur by drinking untreated water from a
lake, pond, reservoir, or spring with a cyanobacterial bloom, or when ingesting
contaminated foods (e.g., crops watered with untreated water) [89]. Also aerosol inhalation from blooming
waters may pose a health risk, for example, when watering the lawn. MC
intoxication frequently occurs in conjunction with toxic cyanobacterial blooms
in water reservoirs (lakes and ponds) used for drinking water or recreational
purposes. It has also been suggested that nutritional supplements from
cyanobacteria (blue-green algae) such as Spirulina and
Aphanizomenon may not only be beneficial as they may
contain MCs which constitute a group of cyanobacterial toxins with more than 100
congeners [90]. Since cyanobacteria
blooms occur all over the world, the possible implication of the cyanobacteria
for health problems might be severe. Globally the most frequently found
cyanobacterial toxins in blooms from fresh and brackish waters are the cyclic
peptide toxins of the microcystin and nodularin family [82]. Large numbers of the human population are therefore at
risk to be exposed to these toxins with adverse health effects.


## 2.5. Treatment of and Protection from AD

Removing pathogenic Aβ peptides to prevent, and possibly
reverse, aggregation is the most sought after method for slowing or delaying the
onset of AD. Development of AD-modifying drugs include amyloidtargeting
monoclonal antibodies (mAbs), β- and
γ-secretase inhibitors, anti-amyloid vaccines, and
tau-based therapies [3]. In principle,
Aβ targeting mAbs should penetrate the blood-brain
barrier and recognize various forms of Aβ, guiding
Aβ clearance into the blood stream for liver
degradation. However, some recent clinical mAbs phase III trials have failed
[3]. Secretase inhibitors are intended
to decrease APP cleavage and lower the amount of Aβ
peptides formed, and, vaccines can be used to boost the immune system to
recognize Aβ. Tau-based therapies are reported to
moderate downstream effects due to Aβ-plaque build-up
[3].The hepcidin-mediated copper lowering mechanisms discussed above suggest that
locally active antagonists interfering with hepcidin’s binding to
neuronal cell’s ferroportin would be expected to promote neuronal
ferroportin export of iron, decreasing undesired APP-mediated copper export as
well as iron-mediated oxidative damages intracellularly. Ways of downregulating
hepatic hepcidin expression (e.g., siRNA) could be attempted, but lowered
systemic hepcidin levels will also result in increased intestinal iron
absorption. Membrane-permeable metal chelators capable of washing out toxic
metals may be effective [91–94], and in vitro,
Aβ deposits can be dissolved using metal chelators
[22]. Lowering systemic iron levels
by controlled phlebotomy has been suggested as an AD therapeutic [95]. A clinical study administrating
deferoxamine (a nonmembrane-permeable strong Fe3+-chelator that to
some degree is taken up into cells by endocytosis, but which does not cross the
BBB readily) slowed the clinical progression of dementia associated with AD
[96]. For a patient suffering from an
iron metabolism disorder, treatment for 10 months with the iron chelator
deferoxamine decreased brain iron stores, prevented progression of the
neurological symptoms, and reduced plasma lipid peroxidation [97]. Many issues confront the use of
chelators including metal saturation. The compounds’ ability to reach the
intended site is affected by metabolic instability, and toxicity is an important
issue (administration of copper chelators to dissolve
Aβ-plaques could further lower neuronal copper levels,
etc). Current clinical oral administration of lipophilic membrane permeable iron
chelators includes deferiprone (produced by ApoPharma) and deferasirox
(Novartis). These are today mainly used for treatment of thalassemia major and
anaemia, respectively; only a few reports concern their uses in relevant
neurodegenerative situations [98].
Molecular modifications may be needed for improved BBB passage and stability
[99]. For efficient iron removal from
the brain, it has been suggested that the lipophilic chelator-iron (III) complex
should have a molecular mass less than 500 Da and be uncharged for cell
membrane and BBB permeability [93]. The
copper/zinc chelator clioquinol (CQ) [100] was suggested to inhibit Aβ accumulation
due to its ability to remove metals from the brain; however, CQ is now
considered toxic. This led to the development of the analogue PBT2, a potential
therapeutic compound for AD which reduced cerebrospinal fluid (CSF)
Aβ
42 and improved cognition without serious adverse effects, according
to a phase II clinical trial [101]; the
compound is being further investigated. Other chelators tested in AD models
having showed positive effects include the iron chelator M30 [92], the copper chelators JKL-169 [102] and IQM-622 [103], and the calcium/copper/zinc chelators DP-109 and
DP-460 [104, 105]. On the contrary, a clinical trial of
D-penicillamine, a copper chelator, was unable to produce any clinical
improvement in AD patients and resulted in toxicities [106]. Nanoparticle-based chelators that can cross the
blood-brain barrier are also being developed [107].Antioxidants from food such as flavonoids, carotenoids, tocopherols, and selenium
have been suggested to protect against AD [94, 108–111]. Interestingly, the occurrence of AD
in India was found to be just one quarter of that in the USA which may be
related to intake of the plant phenolic antioxidant curcumin possessing iron
binding capacity [112]. Curcumin is
present in roots of the turmeric plant used as spice in various foods including
curry [108, 113]. Natural antioxidants have also showed protective
effects against PD [114], and can also
lower microglial cytokine production [115]. Also food compounds not expected to act as antioxidants may
protect against neurodegeneration. One example is caffeine (present in coffee)
which has been suggested to be a potent neuroprotector [116, 117].


## 3. Parkinson’s Disease (PD)

PD is today recognized as the second most common neurodegenerative disorder after AD.
The disease is known to cause motor dysfunctions in addition to autonomic and
cognitive deficits [118]. PD is
characterized by the accumulation of  α-synuclein and selective and progressive loss of dopaminergic
neurons in the substantia nigra (SN) and the degeneration of projecting nerve fibres
in the striatum [119, 120]; however, its true aetiology still remains unknown.  α-Synuclein aggregation is thought to appear early in disease
development and to spread across the nervous system as the disease progresses [121], and early neuroimmune activation by oligomerized  α-synuclein has been speculated to precede neuronal degeneration.
There are probably both environmental and genetic (familial) causative factors for
developing PD. About 5–10% of patients are known to have monogenic forms
of the disease; for those, mutations in at least 13 loci and 9 genes have been
reported to correlate with PD [122].
However, exposure to environmental factors may play a more significant role than
genetic mutations in the vast majority of PD patients (sporadic PD) [123, 124]. This is supported by an etiology study of twins with PD [124], where it was found that genetic factors
do not play a major role in causing typical PD; no genetic component was evident
when the disease began after the age of 50. On the other hand, genetic factors
appear to be important when the disease began at or before the age 50 [124]. It is then tempting to speculate that
aging may play a predominant role in the etiology of PD but in combination with
environmental toxins.Hypotheses on the loss of dopaminergic neurons in PD suggest that mitochondrial
dysfunction may be involved in neuronal death [125, 126], through mechanisms
involving oxidative stress and impaired energy metabolism [127, 128]. Inhibition
of complex I can lead to ROS, lipid peroxidation, protein dysfunction, and a
decrease in reduced glutathione: all hallmark features of postmortem PD [129]. Moreover, chemically induced
mitochondrial dysfunction and cellular lesions can activate inflammatory pathways.
Below we discuss the role of inflammation in the context of environmental risk
factors for the development of PD. We also present data from in
silico analysis of published transcription data of PD compared to
normal brains.


### 3.1. Inflammation in PD

Inflammation in the brain has recently garnered much interest due to clinical
investigations, which show an increase in activated microglia and high levels of
inflammatory factors in the nigrostriatal system from postmortem analyses of PD
patients [130]. In some cases, the onset
of PD has been reported to be associated with head trauma or encephalitis, also
suggesting that an inflammatory component is involved in the disease process
[131]. Levels of proinflammatory
cytokines are elevated in PD patients compared with healthy subjects, and it has
been shown that these cytokines can contribute to dopaminergic cell death
in vivo [132, 133]. Indeed, several recent studies have
demonstrated an important inflammatory component in PD pathogenesis. Injection
of lipopolysaccharide (LPS), an endotoxin produced by gram-negative bacteria,
into the SN [134] or striatum [135] induces inflammation in the brain,
and this has been used as a tool to produce animal models of PD. As reported by
Zhou and coworkers in 2012, a single intracerebroventricular injection of LPS
led to activation of microglia in the hippocampus, striatum, and in the SN,
followed by phospho-α-synuclein expression and abnormal motor behaviour [134]. Interestingly, these results
indicate that microglia are activated for several months after a single, low
dose injection of LPS in the rat, which eventually results in progressive and
selective damage to dopaminergic neurons in the SN.Although PD and AD have distinct pathologies, they also share some similarities.
Both underlying pathologies present different forms of protein aggregates that
appear to be causally linked to their respective diseases [151]. The pathological hallmark of AD involves misfolding
and aggregation of Aβ-plaques and neurofibrillar tangles,
mainly composed of the protein tau, whereas PD inclusions (Lewy bodies) are
largely composed of intracytoplasmic aggregates of  α-synuclein. However, aggregations of Aβ and  α-synuclein are not unique to AD and PD; the pathologies are
often found to coexist in patients with each of these conditions [152, 153].
α-Synuclein has been reported to activate microglia in the SN
pars compacta of mice, which precipitates dopaminergic degeneration [154]. In vitro
observations have suggested that  α-synuclein can have a direct effect on microglial activation
[155]. An increased susceptibility
of dopaminergic cells to LPS-induced toxicity is seen in neurons overexpressing
the human form of  α-synuclein, and the generated inflammatory response further
leads to aggregation of  α-synuclein in nigral neurons [156]. Furthermore, Aβ deposition may be
deleterious not only in AD but also in PD, and this Aβ
effect is associated with inflammatory processes. Inflammation can promote
Aβ deposition that can in turn lead to ROS formation,
neuronal cell death [157], glia cell
activation, and subsequent release of proinflammatory cytokines [158, 159]. Hochstrasser et al. (2013) showed that
Aβ significantly decreased the number of, for
example, hydroxylase-positive dopaminergic neurons, and that anti-inflammatory
drugs partially counteracted the Aβ-induced neuronal
decline through the suppression of glial cell activation [160]. Recent data have indicated that
Aβ is slightly decreased in the cerebral spinal fluid
of PD patients and Aβ can interact with
α-synuclein to accelerate cognitive decline [161]. Further investigations on the
relation between  α-synuclein and Aβ may provide new
insights into the molecular mechanisms of the pathogenesis of PD and suggest
potential new approaches to its treatment.


### 3.2. Environmental Toxins, Microglia, and Neurodegenerative Diseases

In the brain, microglia perform dynamic cellular functions that include synaptic
plasticity [162], cleaning of cellular
debris, wound healing through alternative activation [163, 164], and
innate immune defence. Microglial cells comprise approximately
10–12% of the cells in the brain and dominate in the grey matter,
with particularly high concentrations in the hippocampus, hypothalamus, basal
ganglia, and SN [165–167]. In general, age-related priming of
microglia in the brain plays a role in the development of age-related
inflammatory diseases [168], as shown by
a progressive increase in the expression of microglial MHCII in rodents and
primates [169]. A variety of noxious
compounds released from inappropriately activated microglia, including ROS,
reactive nitrogen species (RNS; e.g., nitric oxide, NO
•, and peroxynitrite, ONOO−), proinflammatory
cytokines (e.g., TNFα, IL-1β, and IL-6), and prostaglandins
may be important mediators of dopaminergic cell death [170–172],
which may propagate into a disease state [173]. Stressed dopaminergic neurons are reported to cause microglial
activation by releasing stimulatory signalling molecules such as  α-synuclein, neuromelanin, and matrix metalloproteinase-3 [174–176]. Also, cytokines, such as TNFα, IL-1β [177], IL-4 [178]
and IL-13 [179], are reported to
initiate microglial NADPH oxidase activation and O
2
•
- generation.Microglia express the phagocyte NADPH oxidase [182, 183], composed of four
regulatory cytosolic components (p47phox, p67phox, p40phox, and rac proteins)
and a transmembrane flavocytochrome heterodimer consisting of the p22phox and
the gp91phox (NOX2) catalytic subunit (Figure 5). NOX2 redox signalling has been shown to play an essential role
in the microglial proinflammatory response and associated neurotoxicity, and
there is evidence for ROS involvement in regulation of NOX2 subunits Rac1 and
P47phox [136, 184]. Environmental toxins (including paraquat, rotenone,
dieldrin, diesel exhaust particles, lindane, mancozeb, maneb, in addition to
some metals; Table 2) have been
reported to reach the brain and activate microglial NADPH oxidase to produce ROS
and induce mitochondrial dysfunction. Continued neuronal damage and rotenone
have been shown to synergistically activate NOX2 and amplify the microglial
proinflammatory response to LPS and neurotoxicity in vitro
[8, 138]. It has recently been shown that
1-methyl-4-phenyl-1,2,5,6-tetrahydro-pyridine (MPTP) intoxication is accompanied
by a strong microglia response which is characterized by the release of
inflammatory molecules that are believed to further drive inflammation-mediated
degeneration of DA neurons [185].
Interestingly, paraquat is shown to be a potent inducer of microglial
activation; both in vivo [186] and in vitro [187] studies suggest that this is the primary mechanism of
dopaminergic neurotoxicity. Rotenone is known to inhibit the transfer of
electrons from iron-sulphur centres in complex I to ubiquinone (coenzyme Q10).
In vitro experiments indicate that rotenone is selectively
toxic to dopaminergic neurons only in the presence of microglia [138]. Thus, altogether these studies show
that triggering of microglial NADPH oxidase activation include both
environmental toxins and central nervous system (CNS) disease pathways,
suggesting that the microglial NADPH oxidase may be a promising target for PD
treatment, especially in delaying the progression of PD.Table 2
Environmental toxins linked to neuronal diseases.
Environmental toxins (linked to brain disease)
Implicated disease/condition in humans or in animal
studies
References
Cyanobacterial toxins (MCs, BMAA)
Tau hyperphosphorylation in AD (MC) and protein
misfolding (BMAA)
[79, 83, 87]
Smoking
Dementia, AD
[25]
Paraquat
Cell death dopaminergic neurons (Bcl-2 induced) and
PD possibly by mitochondrial dysfunction and oxidative
stress
[6, 136, 137]
Rotenone
Oxidative stress, potent inhibitor of mitochondrial
complex I, nigrostriatal cell death (Bcl-2 induced) and PD
[8, 138]
Dieldrin
PD
[139]
Diesel exhaust particles (air pollution)
PD
[140]
Lindane
PD
[141]
Mancozeb
PD
[142]
Maneb
Oxidative stress, cell death (Bcl-2 induced), and
PD
[6, 142]
3-nitropropionate
Inhibits succinate dehydrogenase; striatal
degeneration; Huntington's disease
[143,
144]
Trichloroethylene
Mitochondrial dysfunction in striatum and PD
[145]
1-methyl-4-phenyl-1,2,5,6-tetrahydropyridine
(MPTP)
Oxidative stress, cell death (Bcl-2 induced), and
PD
[7]
Insecticides (Lorsban, Dursban, or other
chlorpyrifos products)
PD
[146]
Metals (e.g., manganese, copper)
PD
[147–149]
Nanoparticles in air emissions
Brain functional deficits?
[150]Figure 5
Chemical stress and aging can alter microglia reactivity and activation
of the phagocytic NADPH oxidase complex. (a) Stimulation of microglia
induces the parallel activation of oxidase components within the
cytoplasm. This activation causes the conversion of Rac into an active
GTP-bound form and the phosphorylation of p47phox and p67phox. These
subunits then translocate to the membrane where they interact with
p22phox and gp91phox (NOX) to initiate ROS production (b) [180]. Excessive or prolonged
inflammation (e.g., IL-1β, IL-6, TNF-α) (c) and ROS resulting from increased microglial
activation may contribute to neuronal damage (d). In addition, chemicals
can damage complex I in mitochondria ((e) figure adapted from [181]) and induce deleterious
changes to neurons in SN by ROS formation and ATP depletion. The figure
is adapted with modifications from [168].Epidemiological studies have suggested exposure to various pesticides as risk
factors for PD. These include the fungicide maneb which contains manganese
[188], paraquat, and other
herbicides or other pesticides [189,
190]. Chronic occupational exposure
to manganese or copper, individually, or in combination with lead, iron and
copper, is associated with PD [147]. In
PD patients, redox-active iron and copper are considered to be an important
factor in the pathology and progression of PD due to its ability to generate
free radicals and to promote redox reactions. Accumulation of iron is frequently
observed in brain areas linked to PD [191]. The brain regions responsible for motor functions seem to have
more iron than nonmotor related regions also explaining why movement disorders
such as PD are often associated with iron loading [192]. High content of copper and zinc is also present in
the cerebrospinal fluid of patients affected by PD [193]; the concentrations of these metals were up to
threefold higher than control levels. A detailed review of Cu, Zn, and Fe
related to neurodegeneration in PD can be found in Kozlowski et al. (2012)
[194].Recent studies have revealed a possible link between nanoparticle (NP) exposure,
and neuronal inflammation and disease. Silver (Ag) particles are one of the most
used NP in consumer products; exposure has been suggested to induce learning and
memory deficits in rats, possibly through oxidative stress-induced pathological
changes in the hippocampus and attenuation of long-term potentiation [198]. It has previously been shown that a
single intravenous exposure of rats to AgNP caused time- and size-dependent
accumulation of NPs in the brain [199].
Further, AgNP induced DNA-strand breaks, apoptosis, necrosis, and decreased
proliferation in different cell models [200, 201]. AgNPs may disturb
the neurotransmitter signaling in the brain [202], and according to the authors such disturbances are linked to
conditions such as PD and AD, and have been implicated in motor, cognitive, and
affective functions. In general, the observed effects of NP in the brain can be
categorized as inflammation and oxidative stress, which may be responsible for
cognitive deficits and other diseases [203]. Recently, several types of inorganic NPs have been shown to
activate microglia and damage neurons in vitro [204]. While the accumulation of NPs in
brain has been clearly demonstrated, less information is available concerning
potential contribution of health-related outcome(s) from NP exposure in airborne
emissions, particularly in modest polluted areas. Elder et al. (2006) showed
increases in proinflammatory mediators and markers of oxidative stress and
immune cell activation (e.g., TNF-α), and SOD in rat brain regions where manganese accumulated
following manganese oxide NP exposure [205]. These findings suggest that NP exposure resulted in CNS
oxidative stress and inflammation. Although mechanisms driving NP-induced CNS
pathology are poorly understood, new evidence suggests that microglial
activation may be a key component, with an important contribution of conditions
that predispose the individual to oxidative stress [206]. However, further research should address the
mechanisms of toxicity and the risk of the general population for developing PD
after NP exposure. Motor, cognitive, and behavioral functions have been assessed
in healthy children and elderly residents in Valcamonica, Italy, and an
increased prevalence of Parkinsonism was observed as being associated with the
manganese levels in the deposited dust from ferroalloy airborne emissions [148]. Inflammation of the olfactory bulb
and deficits in olfaction has been observed in Mexican children residing in
highly polluted areas [207]. Olfactory
loss is an early finding in both AD and PD and precedes cognitive and motor
symptoms [208, 209].  α-Synuclein neuronal aggregation and accumulation of
3-nitrotyrosine and 8-hydroxydeoxyguanosine, biomarkers of oxidative stress,
were also detected in nuclei of these children’s brainstem [150]. That NPs can significantly enhance
the rate of protein fibrillation adds a new important aspect to NP’s role
in neurodegeneration [207].


### 3.3.In Silico Analysis of Genes Involved in
Parkinson’s Disease

To further elucidate the mechanisms for degeneration of the SN in PD patients, we
performed a search in the publicly available databases and in the literature for
genes involved in brain metal homeostasis pathways, neurodegenerative disorders
related genes (in particular PD), oxidative phosphorylation, oxidative stress,
and apoptosis pathways related genes. We selected 138 genes from these pathways.
To investigate whether the expression patterns of those genes are modulated in
neurologically normal elderly and PD individuals, we downloaded the microarray
data (GSE8397) deposited in the GEO database [72] where tissue samples from PD-cases were compared to controls
[195]. Whole genome expression
profiling of studies of 47 tissue samples collected from brain regions relevant
to PD were analyzed for PD-cases and controls: lateral substantia nigra (LSN),
medial substantia nigra (MSN), and superior frontal gyrus (SFG) [195]. For more detailed description of
sample collection, experimental design and flow, we refer the reader to the
original studies [195]. From the GSE8397
dataset, we identified 60 genes (out of our 138 gene list) whose mean expression
level is differentially expressed between PD-cases and controls using two-class,
unpaired SAM (FDR < 10%) [78].
The processed intensities of the 60 genes were mean-centered and
log2-transformed. Figure 6 shows
unsupervised hierarchical clustering analysis of these 60 genes, and the results
were visualized in a dendrogram using MeV v4.8 software [77]. By visual inspection of the heatmap
(Figure 6), we observed that samples from
PD-cases clustered close to each other in one branch while samples from controls
clustered in the other branch. We further compared the identified 60 genes with
gene expression datasets available in the Parkinson’s disease database
(Park DB: http://www2.cancer.ucl.ac.uk/Parkinson_Db2/index.php) in
order to identify key genes with consistent expression profiles across several
datasets. Of the 60 genes, we selected 18 genes showing significant differences
across three different datasets (Table 3) [195–197].Table 3
Genes (n
=
18) involved in brain metal homeostasis and
neurodegeneration for which expression is significantly changed in
PD.
Gene symbol
Description
SAM score (d)*
Fold up- or downregulation
Fold changea
Fold changeb,c
MT1G
Metallothionein 1G
1.7
1.94
0.90
0.82
MT1F
Metallothionein 1F
1.6
1.87
0.88
0.55
MT1M
Metallothionein 1M
1.5
1.73
1.10
0.92
MT1P2
Metallothionein 1 pseudogene 2
1.5
1.79
0.43
0.57
MT1H
Metallothionein 1H
1.5
1.65
0.69
0.79
MT1E
Metallothionein 1E
1.5
1.64
0.62
0.58
MT1X
Metallothionein 1X
1.4
1.56
0.67
0.73
BCL2L11
BCL2-like 11 (apoptosis facilitator)
1.4
2.05
0.29
0.61
MT2A
Metallothionein 2A
1.3
1.51
0.46
0.81
SLC30A1
Solute carrier family 30 (zinc transporter),
member 1
1.3
1.38
0.47
0.37
MT4
Metallothionein 4
1.2
3.51
0.29
0.22
CAT
Catalase
1.1
2.00
0.30
0.40
TF
Transferrin
1.0
1.62
0.68
0.74
SNAP25
Synaptosomal-associated protein,
25 kDa
−1.3
−1.50
−1.50
−1.90
SYP
Synaptophysin
−1.3
−2.04
−0.51
−0.53
CD200
CD200 molecule
−1.5
−1.90
−0.62
−1.10
STXBP1
Syntaxin binding protein 1
−1.8
−1.90
−1.00
−0.71
SLC30A9
Solute carrier family 30 (zinc transporter),
member 9
−1.9
−1.79
−0.69
−0.63
*Significantly differentially expressed genes between PD-cases
and controls, FDR < 10% for GSE8397 microarray date and
unlogged fold up- and downregulated genes (n
=
18). Thirteen genes were overexpressed and 5 genes
were underexpressed in the samples from PD-affected cases in
comparison to age-matched unaffected controls. The microarray
dataset is from (a) microarray dataset from Moran et al., 2006
[195] with GEO accession
number, GSE8397; (b) microarray dataset from Zhang et al. 2005
[196] with accession
number GSE20168; (c) microarray dataset from Lesnick et al. 2007
[197] with GEO accession
number GSE7621. All three microarray datasets are reanalyzed in the
Parkinson's disease database (Park DB: http://www2.cancer.ucl.ac.uk/Parkinson_Db2/index.php).
a,b,cAre log-transformed fold change differences between
PD-cases and controls from Park DB.Figure 6
Unsupervised hierarchical clustering analysis (complete-linkage and
Manhattan distance similarity measurement) of the expression of 60
selected genes in PD. The clustering analysis is based on similarities
in gene expression. The yellow color code represents overexpressed genes (n
=
47), while blue color code represents underexpressed
genes (n
=
13). The horizontal red color bar indicates PD-affected
samples (n
=
31) and the green bar indicates normal elderly controls (n
=
16).Genes consistently overexpressed in PD-cases includeMT1E, MT1F, MT1G,
MT1H, MT1 M, MT1P2, MT1X, MT2A, MT4, BCL2L11, CAT, SLC30A1,andTF, while CD200, SLC30A9, SNAP25,
STXBP1,andSYPwere underexpressed (Table 3). Noticeably, in the PD brains, several
metallothioneins are overexpressed, as well as iron binding transferrin.
Dysregulation of these genes might disturb or compensate a dysregulated metal
homeostasis. Downregulation of proteins in SN or prefrontal cortex associated
with synaptic functions in neurons, such as synaptosomal-associated protein
(SNAP25), synaptophysin (SYP), and syntaxin binding protein 1 (STXBP1),
indicates synaptic functional disturbance and neuronal loss. Decreased CD200
expression indicates loss of neuronal regulation of microglia, and increase of
CAT expression level may indicate oxidative stress. Interestingly, several genes
(NOX1, NOX3, NOX4,andNOX5) coding
proteins in the NADPH oxidase complex are overexpressed (Figure 6) in the PD-cases which may indicate
formation of ROS and proinflammatory mediators in the SN. Altogether the
expression profile constituted by these genes may serve as a basis for
identification of PD-predictive genes that may explain the underlying molecular
mechanisms associated with PD. This should be pursued in future studies.


## 3.1. Inflammation in PD

Inflammation in the brain has recently garnered much interest due to clinical
investigations, which show an increase in activated microglia and high levels of
inflammatory factors in the nigrostriatal system from postmortem analyses of PD
patients [130]. In some cases, the onset
of PD has been reported to be associated with head trauma or encephalitis, also
suggesting that an inflammatory component is involved in the disease process
[131]. Levels of proinflammatory
cytokines are elevated in PD patients compared with healthy subjects, and it has
been shown that these cytokines can contribute to dopaminergic cell death
in vivo [132, 133]. Indeed, several recent studies have
demonstrated an important inflammatory component in PD pathogenesis. Injection
of lipopolysaccharide (LPS), an endotoxin produced by gram-negative bacteria,
into the SN [134] or striatum [135] induces inflammation in the brain,
and this has been used as a tool to produce animal models of PD. As reported by
Zhou and coworkers in 2012, a single intracerebroventricular injection of LPS
led to activation of microglia in the hippocampus, striatum, and in the SN,
followed by phospho-α-synuclein expression and abnormal motor behaviour [134]. Interestingly, these results
indicate that microglia are activated for several months after a single, low
dose injection of LPS in the rat, which eventually results in progressive and
selective damage to dopaminergic neurons in the SN.Although PD and AD have distinct pathologies, they also share some similarities.
Both underlying pathologies present different forms of protein aggregates that
appear to be causally linked to their respective diseases [151]. The pathological hallmark of AD involves misfolding
and aggregation of Aβ-plaques and neurofibrillar tangles,
mainly composed of the protein tau, whereas PD inclusions (Lewy bodies) are
largely composed of intracytoplasmic aggregates of  α-synuclein. However, aggregations of Aβ and  α-synuclein are not unique to AD and PD; the pathologies are
often found to coexist in patients with each of these conditions [152, 153].
α-Synuclein has been reported to activate microglia in the SN
pars compacta of mice, which precipitates dopaminergic degeneration [154]. In vitro
observations have suggested that  α-synuclein can have a direct effect on microglial activation
[155]. An increased susceptibility
of dopaminergic cells to LPS-induced toxicity is seen in neurons overexpressing
the human form of  α-synuclein, and the generated inflammatory response further
leads to aggregation of  α-synuclein in nigral neurons [156]. Furthermore, Aβ deposition may be
deleterious not only in AD but also in PD, and this Aβ
effect is associated with inflammatory processes. Inflammation can promote
Aβ deposition that can in turn lead to ROS formation,
neuronal cell death [157], glia cell
activation, and subsequent release of proinflammatory cytokines [158, 159]. Hochstrasser et al. (2013) showed that
Aβ significantly decreased the number of, for
example, hydroxylase-positive dopaminergic neurons, and that anti-inflammatory
drugs partially counteracted the Aβ-induced neuronal
decline through the suppression of glial cell activation [160]. Recent data have indicated that
Aβ is slightly decreased in the cerebral spinal fluid
of PD patients and Aβ can interact with
α-synuclein to accelerate cognitive decline [161]. Further investigations on the
relation between  α-synuclein and Aβ may provide new
insights into the molecular mechanisms of the pathogenesis of PD and suggest
potential new approaches to its treatment.


## 3.2. Environmental Toxins, Microglia, and Neurodegenerative Diseases

In the brain, microglia perform dynamic cellular functions that include synaptic
plasticity [162], cleaning of cellular
debris, wound healing through alternative activation [163, 164], and
innate immune defence. Microglial cells comprise approximately
10–12% of the cells in the brain and dominate in the grey matter,
with particularly high concentrations in the hippocampus, hypothalamus, basal
ganglia, and SN [165–167]. In general, age-related priming of
microglia in the brain plays a role in the development of age-related
inflammatory diseases [168], as shown by
a progressive increase in the expression of microglial MHCII in rodents and
primates [169]. A variety of noxious
compounds released from inappropriately activated microglia, including ROS,
reactive nitrogen species (RNS; e.g., nitric oxide, NO
•, and peroxynitrite, ONOO−), proinflammatory
cytokines (e.g., TNFα, IL-1β, and IL-6), and prostaglandins
may be important mediators of dopaminergic cell death [170–172],
which may propagate into a disease state [173]. Stressed dopaminergic neurons are reported to cause microglial
activation by releasing stimulatory signalling molecules such as  α-synuclein, neuromelanin, and matrix metalloproteinase-3 [174–176]. Also, cytokines, such as TNFα, IL-1β [177], IL-4 [178]
and IL-13 [179], are reported to
initiate microglial NADPH oxidase activation and O
2
•
- generation.Microglia express the phagocyte NADPH oxidase [182, 183], composed of four
regulatory cytosolic components (p47phox, p67phox, p40phox, and rac proteins)
and a transmembrane flavocytochrome heterodimer consisting of the p22phox and
the gp91phox (NOX2) catalytic subunit (Figure 5). NOX2 redox signalling has been shown to play an essential role
in the microglial proinflammatory response and associated neurotoxicity, and
there is evidence for ROS involvement in regulation of NOX2 subunits Rac1 and
P47phox [136, 184]. Environmental toxins (including paraquat, rotenone,
dieldrin, diesel exhaust particles, lindane, mancozeb, maneb, in addition to
some metals; Table 2) have been
reported to reach the brain and activate microglial NADPH oxidase to produce ROS
and induce mitochondrial dysfunction. Continued neuronal damage and rotenone
have been shown to synergistically activate NOX2 and amplify the microglial
proinflammatory response to LPS and neurotoxicity in vitro
[8, 138]. It has recently been shown that
1-methyl-4-phenyl-1,2,5,6-tetrahydro-pyridine (MPTP) intoxication is accompanied
by a strong microglia response which is characterized by the release of
inflammatory molecules that are believed to further drive inflammation-mediated
degeneration of DA neurons [185].
Interestingly, paraquat is shown to be a potent inducer of microglial
activation; both in vivo [186] and in vitro [187] studies suggest that this is the primary mechanism of
dopaminergic neurotoxicity. Rotenone is known to inhibit the transfer of
electrons from iron-sulphur centres in complex I to ubiquinone (coenzyme Q10).
In vitro experiments indicate that rotenone is selectively
toxic to dopaminergic neurons only in the presence of microglia [138]. Thus, altogether these studies show
that triggering of microglial NADPH oxidase activation include both
environmental toxins and central nervous system (CNS) disease pathways,
suggesting that the microglial NADPH oxidase may be a promising target for PD
treatment, especially in delaying the progression of PD.Table 2
Environmental toxins linked to neuronal diseases.
Environmental toxins (linked to brain disease)
Implicated disease/condition in humans or in animal
studies
References
Cyanobacterial toxins (MCs, BMAA)
Tau hyperphosphorylation in AD (MC) and protein
misfolding (BMAA)
[79, 83, 87]
Smoking
Dementia, AD
[25]
Paraquat
Cell death dopaminergic neurons (Bcl-2 induced) and
PD possibly by mitochondrial dysfunction and oxidative
stress
[6, 136, 137]
Rotenone
Oxidative stress, potent inhibitor of mitochondrial
complex I, nigrostriatal cell death (Bcl-2 induced) and PD
[8, 138]
Dieldrin
PD
[139]
Diesel exhaust particles (air pollution)
PD
[140]
Lindane
PD
[141]
Mancozeb
PD
[142]
Maneb
Oxidative stress, cell death (Bcl-2 induced), and
PD
[6, 142]
3-nitropropionate
Inhibits succinate dehydrogenase; striatal
degeneration; Huntington's disease
[143,
144]
Trichloroethylene
Mitochondrial dysfunction in striatum and PD
[145]
1-methyl-4-phenyl-1,2,5,6-tetrahydropyridine
(MPTP)
Oxidative stress, cell death (Bcl-2 induced), and
PD
[7]
Insecticides (Lorsban, Dursban, or other
chlorpyrifos products)
PD
[146]
Metals (e.g., manganese, copper)
PD
[147–149]
Nanoparticles in air emissions
Brain functional deficits?
[150]Figure 5
Chemical stress and aging can alter microglia reactivity and activation
of the phagocytic NADPH oxidase complex. (a) Stimulation of microglia
induces the parallel activation of oxidase components within the
cytoplasm. This activation causes the conversion of Rac into an active
GTP-bound form and the phosphorylation of p47phox and p67phox. These
subunits then translocate to the membrane where they interact with
p22phox and gp91phox (NOX) to initiate ROS production (b) [180]. Excessive or prolonged
inflammation (e.g., IL-1β, IL-6, TNF-α) (c) and ROS resulting from increased microglial
activation may contribute to neuronal damage (d). In addition, chemicals
can damage complex I in mitochondria ((e) figure adapted from [181]) and induce deleterious
changes to neurons in SN by ROS formation and ATP depletion. The figure
is adapted with modifications from [168].Epidemiological studies have suggested exposure to various pesticides as risk
factors for PD. These include the fungicide maneb which contains manganese
[188], paraquat, and other
herbicides or other pesticides [189,
190]. Chronic occupational exposure
to manganese or copper, individually, or in combination with lead, iron and
copper, is associated with PD [147]. In
PD patients, redox-active iron and copper are considered to be an important
factor in the pathology and progression of PD due to its ability to generate
free radicals and to promote redox reactions. Accumulation of iron is frequently
observed in brain areas linked to PD [191]. The brain regions responsible for motor functions seem to have
more iron than nonmotor related regions also explaining why movement disorders
such as PD are often associated with iron loading [192]. High content of copper and zinc is also present in
the cerebrospinal fluid of patients affected by PD [193]; the concentrations of these metals were up to
threefold higher than control levels. A detailed review of Cu, Zn, and Fe
related to neurodegeneration in PD can be found in Kozlowski et al. (2012)
[194].Recent studies have revealed a possible link between nanoparticle (NP) exposure,
and neuronal inflammation and disease. Silver (Ag) particles are one of the most
used NP in consumer products; exposure has been suggested to induce learning and
memory deficits in rats, possibly through oxidative stress-induced pathological
changes in the hippocampus and attenuation of long-term potentiation [198]. It has previously been shown that a
single intravenous exposure of rats to AgNP caused time- and size-dependent
accumulation of NPs in the brain [199].
Further, AgNP induced DNA-strand breaks, apoptosis, necrosis, and decreased
proliferation in different cell models [200, 201]. AgNPs may disturb
the neurotransmitter signaling in the brain [202], and according to the authors such disturbances are linked to
conditions such as PD and AD, and have been implicated in motor, cognitive, and
affective functions. In general, the observed effects of NP in the brain can be
categorized as inflammation and oxidative stress, which may be responsible for
cognitive deficits and other diseases [203]. Recently, several types of inorganic NPs have been shown to
activate microglia and damage neurons in vitro [204]. While the accumulation of NPs in
brain has been clearly demonstrated, less information is available concerning
potential contribution of health-related outcome(s) from NP exposure in airborne
emissions, particularly in modest polluted areas. Elder et al. (2006) showed
increases in proinflammatory mediators and markers of oxidative stress and
immune cell activation (e.g., TNF-α), and SOD in rat brain regions where manganese accumulated
following manganese oxide NP exposure [205]. These findings suggest that NP exposure resulted in CNS
oxidative stress and inflammation. Although mechanisms driving NP-induced CNS
pathology are poorly understood, new evidence suggests that microglial
activation may be a key component, with an important contribution of conditions
that predispose the individual to oxidative stress [206]. However, further research should address the
mechanisms of toxicity and the risk of the general population for developing PD
after NP exposure. Motor, cognitive, and behavioral functions have been assessed
in healthy children and elderly residents in Valcamonica, Italy, and an
increased prevalence of Parkinsonism was observed as being associated with the
manganese levels in the deposited dust from ferroalloy airborne emissions [148]. Inflammation of the olfactory bulb
and deficits in olfaction has been observed in Mexican children residing in
highly polluted areas [207]. Olfactory
loss is an early finding in both AD and PD and precedes cognitive and motor
symptoms [208, 209].  α-Synuclein neuronal aggregation and accumulation of
3-nitrotyrosine and 8-hydroxydeoxyguanosine, biomarkers of oxidative stress,
were also detected in nuclei of these children’s brainstem [150]. That NPs can significantly enhance
the rate of protein fibrillation adds a new important aspect to NP’s role
in neurodegeneration [207].


## 3.3.In Silico Analysis of Genes Involved in
Parkinson’s Disease

To further elucidate the mechanisms for degeneration of the SN in PD patients, we
performed a search in the publicly available databases and in the literature for
genes involved in brain metal homeostasis pathways, neurodegenerative disorders
related genes (in particular PD), oxidative phosphorylation, oxidative stress,
and apoptosis pathways related genes. We selected 138 genes from these pathways.
To investigate whether the expression patterns of those genes are modulated in
neurologically normal elderly and PD individuals, we downloaded the microarray
data (GSE8397) deposited in the GEO database [72] where tissue samples from PD-cases were compared to controls
[195]. Whole genome expression
profiling of studies of 47 tissue samples collected from brain regions relevant
to PD were analyzed for PD-cases and controls: lateral substantia nigra (LSN),
medial substantia nigra (MSN), and superior frontal gyrus (SFG) [195]. For more detailed description of
sample collection, experimental design and flow, we refer the reader to the
original studies [195]. From the GSE8397
dataset, we identified 60 genes (out of our 138 gene list) whose mean expression
level is differentially expressed between PD-cases and controls using two-class,
unpaired SAM (FDR < 10%) [78].
The processed intensities of the 60 genes were mean-centered and
log2-transformed. Figure 6 shows
unsupervised hierarchical clustering analysis of these 60 genes, and the results
were visualized in a dendrogram using MeV v4.8 software [77]. By visual inspection of the heatmap
(Figure 6), we observed that samples from
PD-cases clustered close to each other in one branch while samples from controls
clustered in the other branch. We further compared the identified 60 genes with
gene expression datasets available in the Parkinson’s disease database
(Park DB: http://www2.cancer.ucl.ac.uk/Parkinson_Db2/index.php) in
order to identify key genes with consistent expression profiles across several
datasets. Of the 60 genes, we selected 18 genes showing significant differences
across three different datasets (Table 3) [195–197].Table 3
Genes (n
=
18) involved in brain metal homeostasis and
neurodegeneration for which expression is significantly changed in
PD.
Gene symbol
Description
SAM score (d)*
Fold up- or downregulation
Fold changea
Fold changeb,c
MT1G
Metallothionein 1G
1.7
1.94
0.90
0.82
MT1F
Metallothionein 1F
1.6
1.87
0.88
0.55
MT1M
Metallothionein 1M
1.5
1.73
1.10
0.92
MT1P2
Metallothionein 1 pseudogene 2
1.5
1.79
0.43
0.57
MT1H
Metallothionein 1H
1.5
1.65
0.69
0.79
MT1E
Metallothionein 1E
1.5
1.64
0.62
0.58
MT1X
Metallothionein 1X
1.4
1.56
0.67
0.73
BCL2L11
BCL2-like 11 (apoptosis facilitator)
1.4
2.05
0.29
0.61
MT2A
Metallothionein 2A
1.3
1.51
0.46
0.81
SLC30A1
Solute carrier family 30 (zinc transporter),
member 1
1.3
1.38
0.47
0.37
MT4
Metallothionein 4
1.2
3.51
0.29
0.22
CAT
Catalase
1.1
2.00
0.30
0.40
TF
Transferrin
1.0
1.62
0.68
0.74
SNAP25
Synaptosomal-associated protein,
25 kDa
−1.3
−1.50
−1.50
−1.90
SYP
Synaptophysin
−1.3
−2.04
−0.51
−0.53
CD200
CD200 molecule
−1.5
−1.90
−0.62
−1.10
STXBP1
Syntaxin binding protein 1
−1.8
−1.90
−1.00
−0.71
SLC30A9
Solute carrier family 30 (zinc transporter),
member 9
−1.9
−1.79
−0.69
−0.63
*Significantly differentially expressed genes between PD-cases
and controls, FDR < 10% for GSE8397 microarray date and
unlogged fold up- and downregulated genes (n
=
18). Thirteen genes were overexpressed and 5 genes
were underexpressed in the samples from PD-affected cases in
comparison to age-matched unaffected controls. The microarray
dataset is from (a) microarray dataset from Moran et al., 2006
[195] with GEO accession
number, GSE8397; (b) microarray dataset from Zhang et al. 2005
[196] with accession
number GSE20168; (c) microarray dataset from Lesnick et al. 2007
[197] with GEO accession
number GSE7621. All three microarray datasets are reanalyzed in the
Parkinson's disease database (Park DB: http://www2.cancer.ucl.ac.uk/Parkinson_Db2/index.php).
a,b,cAre log-transformed fold change differences between
PD-cases and controls from Park DB.Figure 6
Unsupervised hierarchical clustering analysis (complete-linkage and
Manhattan distance similarity measurement) of the expression of 60
selected genes in PD. The clustering analysis is based on similarities
in gene expression. The yellow color code represents overexpressed genes (n
=
47), while blue color code represents underexpressed
genes (n
=
13). The horizontal red color bar indicates PD-affected
samples (n
=
31) and the green bar indicates normal elderly controls (n
=
16).Genes consistently overexpressed in PD-cases includeMT1E, MT1F, MT1G,
MT1H, MT1 M, MT1P2, MT1X, MT2A, MT4, BCL2L11, CAT, SLC30A1,andTF, while CD200, SLC30A9, SNAP25,
STXBP1,andSYPwere underexpressed (Table 3). Noticeably, in the PD brains, several
metallothioneins are overexpressed, as well as iron binding transferrin.
Dysregulation of these genes might disturb or compensate a dysregulated metal
homeostasis. Downregulation of proteins in SN or prefrontal cortex associated
with synaptic functions in neurons, such as synaptosomal-associated protein
(SNAP25), synaptophysin (SYP), and syntaxin binding protein 1 (STXBP1),
indicates synaptic functional disturbance and neuronal loss. Decreased CD200
expression indicates loss of neuronal regulation of microglia, and increase of
CAT expression level may indicate oxidative stress. Interestingly, several genes
(NOX1, NOX3, NOX4,andNOX5) coding
proteins in the NADPH oxidase complex are overexpressed (Figure 6) in the PD-cases which may indicate
formation of ROS and proinflammatory mediators in the SN. Altogether the
expression profile constituted by these genes may serve as a basis for
identification of PD-predictive genes that may explain the underlying molecular
mechanisms associated with PD. This should be pursued in future studies.


## 4. Concluding Remarks

More studies are needed to investigate hepcidin’s role in the brain, focusing
on aging, metal dyshomeostasis, and inflammation in degenerative diseases. However,
to unravel the disease aetiologies of AD and PD in relation to metal storage and
shuttling between the various types of brain cells (e.g., astrocytes, neurons,
endothelial cells, and microglia) new studies are required. These should, however,
have high resolution and the capability to analyse protein (and/or gene)
expressional and functional changes of individual cell types during disease
progression. The role of combined chemical exposures for development of neuronal
diseases needs to be elucidated in future studies.



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*Source: 726954-2013-04-17.xml*