ARTICLE IN PRESS
Neuroscience and Biobehavioral Reviews xx (2003) xxx–xxx
www.elsevier.com/locate/neubiorev
Review
Analysis of neurological disease in four dimensions: insight
from ALS-PDC epidemiology and animal models
C.A. Shawa,b,c,d,*,1, J.M.B. Wilsona,1
a
Program in Neuroscience, University of British Columbia, Vancouver, BC, Canada
Department of Ophthalmology, University of British Columbia, Vancouver, BC, Canada
c
Department of Physiology, University of British Columbia, Vancouver, BC, Canada
d
Department of Experimental Medicine, University of British Columbia, Vancouver, BC, Canada
b
Received 1 May 2003; revised 9 July 2003; accepted 14 August 2003
Abstract
The causal factor(s) responsible for sporadic neurological diseases are unknown and the stages of disease progression remain undefined
and poorly understood. We have developed an animal model of amyotrophic lateral sclerosis-parkinsonism dementia complex which mimics
all the essential features of the disease with the initial neurological insult arising from neurotoxins contained in washed cycad seeds. Animals
fed washed cycad develop deficits in motor, cognitive, and sensory behaviors that correlate with the loss of neurons in specific regions of the
central nervous system. The ability to recreate the disease by exposure to cycad allows us to extend the model in multiple dimensions by
analyzing behavioral, cellular, and biochemical changes over time. In addition, the ability to induce toxin-based neurodegeneration allows us
to probe the interactions between genetic and epigenetic factors. Our results show that the impact of both genetic causal and susceptibility
factors with the cycad neurotoxins are complex. The article describes the features of the model and suggests ways that our understanding of
cycad-induced neurodegeneration can be used to decipher and identify the early events in various human neurological diseases.
q 2003 Published by Elsevier Ltd.
Keywords: Amyotrophic lateral sclerosis-Parkinsonism dementia complex; Alzheimer’s disease; Parkinsonism; Amyotrophic lateral sclerosis; Cycad;
Neurodegeneration; Excitotoxicity; Sterol glucoside; Animal model; Time course
Contents
1. Introduction: the fundamental problems in neurological disease research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2. Defining neurological disease in four dimensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3. The ‘Timeline’ concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4. Overview of age-related neurological diseases. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5. Is there a neurological Rosetta Stone?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6. A murine model of ALS-PDC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7. Does the ALS-PDC model satisfy standard criteria? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8. Genetic – epigenetic interactions in the cycad model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9. Time line of neurodegenerative events in the cycad model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
10. Template matching to human neurological disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
11. The mouse model of ALS-PDC: implications for prophylaxis and for halting disease progression . . . . . . . . . . . . . .
12. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
* Corresponding author. Address: Research Pavilion, VGH, Rm 386, 828
West 10th Ave., Vancouver, BC, Canada V6T 1Z3. Tel.: þ 1-604-8754111x68375; fax: þ1-604-875-4376.
E-mail address: [email protected] (C.A. Shaw).
1
Equal co-authors.
0149-7634/$ - see front matter q 2003 Published by Elsevier Ltd.
doi:10.1016/j.neubiorev.2003.08.001
000
000
000
000
000
000
000
000
000
000
000
000
000
1. Introduction: the fundamental problems
in neurological disease research
Of all the diseases that humans have sought to understand
and thereby control, those involving the nervous system have
ARTICLE IN PRESS
2
C.A. Shaw, J.M.B. Wilson / Neuroscience and Biobehavioral Reviews xx (2003) xxx–xxx
proven to be the most intractable. Within the realm of
neurological diseases, those that are age-dependent (i.e.
Alzheimer’s Disease (AD), Parkinson’s Disease (PD) and
amyotrophic lateral sclerosis (ALS)) are the most common
and the most difficult to track in time given that they may be
initiated early in life yet normally express in late middle to old
age. For these diseases, there are neither definitive hypotheses
nor unambiguous experimental data showing what the causal
factors are likely to be. In particular, we are still uncertain
whether these diseases have genetic and/or environmental
origins and how factors associated with either can influence
neural cell survival. It is also unclear how pathological
processes evolve from the initial insult(s) through to cell
death, or what the functional relationships are between neural
pathology and behavioral outcome at any stage of the disease
process. Postmortem studies have identified numerous
molecules that appear to be altered in amount or function,
but the larger context or interrelationships between such
molecules, and the temporal sequence of changes in the
affected cells or neural systems are largely unknown. Details
about rates of progression from clinical diagnosis to death are
known, but minimal details are available about early preclinical events before classical symptoms are observed.
Therapeutic intervention has proven to be difficult due to
the lack of a clearly established link to any of the putative
causal factors for neurological disease. The prevention of
disease initiation becomes challenging without knowing in
advance which individuals are susceptible and for what
reasons. Similarly, without understanding or being able to
identify pre-clinical symptoms, early prognosis for those
potentially afflicted in the future—and perhaps still
treatable—becomes nearly impossible. To halt disease
progression would require a detailed understanding of the
temporal sequence of events transpiring between the initial
insult and the endpoint of massive neural cell death. The
inability to either prevent or halt the disease process leaves
those in the field in the unfortunate position of at best being
able to treat symptoms, but only once clinically identified.
Currently, treatment is primarily palliative, though this may
change in the future with the advent of stem cell or other
future technological breakthroughs. However, due to
significant theoretical and economic factors, ‘curing’ these
diseases following clinical diagnosis may never be successful. Without a clear understanding of how various
pathological processes arise and evolve in real time to
cause neural death, especially in relation to outcomes at all
levels of neural cell function, no therapeutic strategy can be
successful. In order for us to advance beyond palliation, a
‘multi-dimensional’ view of the disease processes is
required. Such a view would encompass successive levels of
neural organization, from behavior to cellular/biochemical
function. ‘Time’ comprises the fourth dimension of this
analysis. The concept of a four dimensional analysis of
neurological disease is further defined below.
This article describes what is known about the temporal
progression of human neurological diseases, AD, PD, ALS,
and ALS-parkinsonism dementia complex (ALS-PDC). We
go on to relate this information to insights gained from a
new animal model of ALS-PDC in which we can observe
the evolution of neurodegeneration in each of the above
dimensions.
2. Defining neurological disease in four dimensions
To fully understand a progressive neurological disease, it
must be observed across various neurological ‘dimensions’.
In place of the three traditional physical dimensions of
height, width, and breadth, our use of the word ‘dimension’
is directed at various levels of neural organization. For the
purpose of the present discussion, we define these as: (i)
biochemical processes which normally or abnormally occur
in the various neural cell types, (ii) the normal or abnormal
cellular morphologies associated with different neural cell
types, and (iii) the normal or abnormal outcomes of the
behavioral response. We acknowledge that there are
additional sub-levels that can be discussed (for a more
complete description of our concept of neural levels of
organization see Ref. [1]) and that our choice of levels/
dimensions is arbitrary. Each of these levels is dynamically
interactive with those ‘above’ and ‘below’. For example,
toxins that alter the biochemical makeup of a particular
neural subtype (i.e. type I mitochondrial inhibitors acting on
dopaminergic neurons) may kill the cell in question, thus
disrupting the overall neural circuit in which that cell acted.
In turn, disruptions of cellular interactions impact larger
neural circuits and systems, ultimately altering the behavioral outcome. A full understanding of the degenerative
process and the development of therapeutic strategies to
block the neurodegeneration, requires an appreciation of the
time course or ‘timeline’ (see Fig. 1).
3. The ‘Timeline’ concept
The notion of a ‘timeline’ is crucial for understanding the
evolving cascade of pathological events in neurodegeneration. The simplest notion is that the timeline consists of a
straightforward relationship between the presence of some
toxicant molecule, gene or gene product and the number of
dead or dying cells in affected regions of the central nervous
system (CNS). For example, as the amount of a particular
toxin increases, the cumulative number of dead cells should
increase as well. In this example, the relationship is much
like the well-known Michaelis – Menton curve that
describes enzyme-substrate reactions. Certainly, in neurological diseases the progression of neurodegeneration could
follow mathematical functions such as this and might occur
in cases where high concentrations of a specific and acutely
toxic molecule were present. Another simple form of
timeline might substitute ‘time’ for dose, such that for a
given dose of any toxic molecule, the cumulative number of
ARTICLE IN PRESS
C.A. Shaw, J.M.B. Wilson / Neuroscience and Biobehavioral Reviews xx (2003) xxx–xxx
3
Fig. 1. Schematic: neurological disease in four dimensions. The combined X; Y; and Z-axes represent an arbitrary region of CNS affected by a progressive
neurodegenerative disorder of undefined nature. The X-axis represents cell structure/function (neuron number/structure in particular regions of CNS), Y
represents normal behavioral function, and Z represents biochemical processes in the CNS. Axis length corresponds to percent remaining function and has been
arbitrarily set for this example. As the disease progresses, the biochemical malfunction leads to greater cell loss and ultimate decreased behavioral function.
Behav: behavioral function. Cell struct: cell structure/function. Biochem: normal biochemical processes.
dead or dying cells would increase over time. An example of
the latter function is the association binding kinetics of
receptor– ligand interactions.
Although these simple examples may apply to neural
cells in some constrained circumstances, e.g. in vitro for
single cell types in cell culture preparations, they are
unlikely to do so in vivo. The reasons why such simple
relations are not likely to apply in vivo include the
following: (i) in vivo, multiple cell types interact in any
region of the nervous system; (ii) various cell types are
differentially impacted by any toxin or gene; (iii) sub-acute
toxin levels may initially damage rather than kill certain
cells; and (iv) secondary and tertiary, etc. molecules
released by one or multiple cell types can impact the health
and survival of surrounding cells. In other words, the in vivo
system is dynamic and reflects an ongoing interplay of
multiple cell types and numerous biochemical cascades over
time. This consideration indicates that while any initial local
toxic action may reflect a simple toxin-induced destruction
of particular cells, the longer term consequence will be a
series of biochemical cascades of great complexity and
involving numerous cell types. The latter circumstance is
almost certainly the case in human chronic neurological
disease states. In the present article, our use of the term
‘timeline’ will refer generally to the more complex case.
4. Overview of age-related neurological diseases
The age-related neurological diseases, including AD,
PD, and ALS, are diagnosed only once significant
behavioral deficits have been observed clinically. Alzheimer’s disease involves the death of neurons of various
regions of the cerebral cortex and the hippocampus and
results in the loss of cognitive functions such as memory
and learning. In Parkinson’s disease, portions of the
nigral –striatal system degenerate. Initial stages involve
the loss of terminal projections of dopamine-containing
neurons from the substantia nigra (SN). In turn, the
neuron cell bodies in the SN die, impacting motor
control and leading to tremor and gait disturbances. ALS
primarily involves the loss of spinal and cortical motor
neurons, leading to increasing paralysis and eventually
death. Table 1 compares several aspects of ALS, AD, PD
and ALS-PDC not further mentioned in this article.
Each of these diseases appears to target relatively specific
populations of neurons in the CNS whose loss leads to
particular neurological symptoms at a behavioral level. The
conventional perspective is that these are quite distinct
diseases, arising from different etiologies, and expressing as
unique behavioral and neuropathological outcomes. To some
extent this view is justified due to differential primary
Table 1
Comparison of ALS, PD, AD, and ALS-PDC
ALS
PD
AD
ALS-PDC
Incidence per 100,000
Male:female ratio
Mean age of onset
1–4 [3,82]
21 [3]; 19 in Estonia [84]; ,100–200 on Als and
Faroe Islands [85]; Greenland [86]; and Bulgaria [87]
39–101 [89]; 401 [3]
2:1 [83]; 1.6:1 [3]
2.1:1 [88]; 1.1:1 [3]
59.3 [3]
61.9 [3]
1:1.7 [90]; 1.1:1 (but ratio reverses
after age 75 years) [3]
1945–1960: ,2:1
1995–1999: comparable rates [25]
71.9 [3]
1945–1960: 114 –155
1995–1999: 27 [25]
1945–1960: 50 –59
1995–1999: 65 –69 [25]
ALS: amyotrophic lateral sclerosis, PD: Parkinson’s disease, AD: Alzhiemer’s disease and ALS-PDC (ALS-parkinsonism dementia complex) are
compared.
ARTICLE IN PRESS
4
C.A. Shaw, J.M.B. Wilson / Neuroscience and Biobehavioral Reviews xx (2003) xxx–xxx
symptoms and pathological outcomes of the diseases at a
cellular and neural circuit level. However, recent research
also reveals significant commonalities and apparent boundary crossing amongst these disorders (see Refs. [2,3] for
reviews). For example, patients suffering from AD may show
tremor [4], a hallmark of PD. Similarly, PD and ALS patients
may show losses of cognitive function [5 – 7], primarily an
AD symptom. A recent article by Masliah et al. [8] has linked
AD and PD as possibly having overlapping pathogenic
pathways. Clinically, neurological gait abnormalities in
elderly persons normally seen in PD patients have been
shown to be a significant predictor of the risk of developing
later dementia [9]. Clinical observations have also defined a
new disorder called ‘ALS-plus’, which is a form of ALS
combined with dementia and/or parkinsonism features [10].
(For further examples of commonalities in theses diseases
see Refs. [11 –13]).
At postmortem analysis, some of the hallmark features of
the different disorders may cross conventional boundaries as
well. For example, neurofibrillary tangles (NFT), characteristic of AD, have now been identified in some cases of PD
[14] and ALS [15]. Similarly, a-synuclein, a major
component of Lewy bodies and Lewy neurites, the
pathological hallmarks of PD, were originally isolated
from amyloid plaques in AD patients [16].
Eisen and Calne [3] have suggested that AD, PD and
ALS share more basic underlying features, e.g. generic
protein misfolding alterations that differ in the types of
proteins affected. For example, the protein alterations
involving b-amyloid (AD), a-synuclein (PD) and heavy
neurofilaments (ALS) may suggest that an important step in
neurodegeneration is altered cytoskeletal protein per se,
rather than the particular protein involved.
In each of the above diseases, by the time clinical diagnosis
is achieved, major damage has been done to the specific
region(s) of the nervous system most affected. Estimates of
neuron loss in these areas vary, but may be extensive (e.g.
70% loss of functional spinal alpha motor neurons in ALS
[17]; . 75% loss of neurons of the nucleus basalis of Meynert
in AD [18]; 60% loss of the enzyme dopa-decarboxylase as a
gauge of dopaminergic terminals in striatum in PD [19]). A
recent study with AD patients using MRI volume measurements of medial temporal lobe structures (hippocampus and
entorhinal cortex) showed a 16.6% decrease compared to
controls [20]. Across the various diseases discussed here,
neural compensation by surviving neurons may sustain the
individual over long periods, at least until a final threshold of
functional neurons is lost. Clinical symptoms may become
detectable only after severe damage beyond this threshold is
done to the most affected neural subset(s).
5. Is there a neurological Rosetta Stone?
A classical example of overlapping symptoms in a
progressive neurological disease is the unusual Guamanian
disorder, ALS-PDC which first gained serious attention in
the 1950s. L.T. Kurland and various other investigators
described in detail this disease complex, which could
express as a conventional form of ALS (termed ‘lytico’ or
‘paralytico’ by the Chamorro population of Guam and Rota)
or as a form of Alzheimer’s disease with strong parkinsonian features (locally termed ‘bodig’). A number of patients
presented with a combination of features, often sequentially
developed, with the ALS component usually appearing first
[21]. Kurland and other early investigators (for review, see
Refs. [22,23]) thought the disorder remarkable in several
key aspects. First, the overall incidence was vastly higher
than for related disorders elsewhere (50 – 100 times more
prevalent among the Chamorros of Guam than in the rest of
the world, [24]), so much so that Kurland estimated that
25% of adult deaths on Guam/Rota were due to ALS-PDC.
Second, the disease often struck those much younger than
the average age of onset for similar disorders elsewhere
(mean age onset 44 years [24] vs. 59 for ALS, 62 for PD and
72 for AD [3]). Finally, the overlapping features in many
cases seemed to point to a common etiology, one that might
shed light on all forms of age-related neurological disease.
The view at that time was that ALS-PDC could serve as a
type of neurological ‘Rosetta Stone’, the decipherment of
which would unlock crucial clues to neurological disorders
worldwide.
Early studies of the environment and genetics of the
Chamorro people gave hope that straightforward causal
factors would be readily unearthed. For example, the
Chamorro population was then relatively homogeneous in
genetic background [25]. Additionally, Kurland and colleagues cited the relative lack of potential environmental
toxins of human origin. In spite of this, detailed screening
over many years failed to identify a genetic etiology (for a
recent reference, see Ref. [25]). Largely for this reason,
investigators rapidly focused on potential environmental
toxins, screening hundreds of potential factors, including
the ionic composition of ground water, native food products,
industrial materials associated with military activity, and
radiation. Most of these potential candidates were eliminated as being sole causal factors, although we note that
controversy still remains about possible synergistic interactions between weak toxins and/or between weak toxins
and possible genetic susceptibilities [25].
The primary clue to the cause of the disease was the
historical record showing toxic effects of the seed of the
cycad palm (Cycas micronesica K.D. Hill, previously
referred to as Cycas circinalis), a traditional food often
used as a primary foodstuff during times of famine. Cycad
seeds were harvested, cut open to expose the starchy
endosperm, sliced into ‘chips’, then washed for periods up
to 10 days. The Chamorros had originally been introduced
to cycad consumption by the Spanish who taught them to
wash out acutely toxic factors (Steele, personal communication). It was noted that Captain Cook’s sailors visiting the
island in the late 1700s had consumed unwashed cycad and
ARTICLE IN PRESS
C.A. Shaw, J.M.B. Wilson / Neuroscience and Biobehavioral Reviews xx (2003) xxx–xxx
had become seriously ill, some showing acute neurological
signs [26]. Cattle and other ruminants feeding on cycad in
other locales died after exhibiting symptoms of neurological
dysfunction [26]. As noted above, cycad had been
consumed by the Chamorros as a dietary staple and
occasional famine food, but the level of consumption rose
to far greater levels during WWII due to harsh conditions
during the Japanese occupation of the island. ALS-PDC
incidence peaked within several years of the war and
dramatically declined as cycad consumption lessened
during the post-war years. Guamanians who adopted a
more conventional ‘Americanized’ diet showed declining
incidences of ALS-PDC [19]. Notably, the Chamorro
people of Saipan, genetically identical to the Chamorros
of Guam, had not consumed cycad during most of the 20th
Century and had no cases of ALS-PDC, with only one case
of ALS and three cases of parkinsonism without dementia
among the approximately 17,000 inhabitants. These rates
were comparable to those in North America [21]. Thus,
genetically identical populations showed two completely
different outcomes, apparently based solely on exposure to
one potential source of toxicity.
Each of these factors led Kurland and others to conclude
that cycad toxins were the key etiological factor in ALSPDC and this conclusion sparked a hunt for the principal
toxin involved. The various cycad species are gymnosperms, appearing earlier in evolution than angiosperms, or
flowering plants [27]. While the latter use birds and
mammals as a means to distribute seeds, cycads do not,
and the leaves and seeds contain a number of compounds
that are acutely toxic to mammals [28]. Some of these
include the amino sugar cycasin and its active compound,
the aglycone methyl azoxylmethanol (MAM), the latter
being acutely toxic as well as having both carcinogenic and
mutagenic properties [29]. Various amino acids able to
activate subclasses of the ionotropic glutamate receptor
family are also present, including b-N-oxalylamino-L alanine (BOAA) and b-N-methylamino- L -alanine
(BMAA), agonists for AMPA and NMDA receptors,
respectively. A number of other compounds have also
been detected in cycad, some still not well characterized
[30,31]. Investigators in the 1960s seized on the toxicity of
MAM, using either cycad or the isolated toxin in a series of
experiments designed to demonstrate both the neuronal
effects as well as the mechanisms of action. Two facts
gradually became apparent. First, animals exposed to
cycasin/MAM or BMAA did not exhibit the full gamut of
behavioral or pathological outcomes that resembled ALSPDC [32,33], although Spencer and colleagues did succeed
in producing motor dysfunctions accompanied by loss of
spinal motor neurons in monkeys with the latter toxin [34].
Second, both cycasin and MAM were significantly eluted by
the traditional washing procedure of the Chamorros [35].
Spencer et al. [36,37] did demonstrate that BMAA could
induce pathological neurological outcomes in vitro [38] and
in vivo [39]. A more chronic form of neuronal dysfunction
5
due to BOAA is ‘lathyrism’ arising from the consumption of
the chickling pea [40,41]. Recently, Cox and Sacks [42]
suggested that the source of the ALS-PDC inducing toxin is
indeed cycad, but that this toxicity is biomagnified by being
stored in the bodies of fruit bats, the latter eaten by the
Chamorros until the 1970s.
Traditional washing of cycad chips as part of processing,
however, removes most toxins [35], suggesting that various
water soluble compounds are not primary factors responsible for ALS-PDC. This observation, however, does not
discount the possibility of biomagnification in which the
washing of the cycad seeds may become irrelevant.
In spite of the ebb and flow of etiological hypotheses, the
strongest epidemiological data for ALS-PDC still pointed to
cycad consumption, a fact that led our group to reexamine
the ‘cycad hypothesis’ from the perspective that still
unknown, water-insoluble cycad toxins might be causal to
the disease. Some of the key conclusions of our studies are
presented below and form the basis for our murine model of
ALS-PDC.
6. A murine model of ALS-PDC
We recently reexamined the cycad model of ALS-PDC
using quantitative assay procedures combined with bioassays
for neural activity and cell death [43]. These studies
identified the most toxic types of molecules contained in
washed cycad as a sterol glucoside whose actions in vitro
included the excitotoxic release of glutamate and an
abnormal increase in the activity of various protein kinases.
We expanded our studies to include in vivo feeding of
washed cycad seed flour and employed a battery of motor,
cognitive, and olfactory behavioral measures to determine
the outcome of consumption. These studies demonstrated a
temporal sequence of behavioral deficits that correlated to
neural cell death in appropriate regions of the CNS [7,43] (a
summary is provided in Fig. 2). With regard to motor neuron
disorders, cycad-fed mice showed significant losses of the leg
extension reflex (Fig. 2C), pronounced gait disturbances
(Fig. 2B), as well as losses of muscle strength and balance.
MRI scans of the brains and spinal cords of control and cycad
treated animals ex vivo showed decreased cross sectional
areas of various regions of motor and somatosensory cortex,
decreased volumes in hippocampus, substantia nigra/striatum, olfactory bulb and ventral horn of the spinal cord
(Fig. 2D – F). In addition, motor neuron number was
decreased significantly in ventral cord (Fig. 2F(i)). On
sacrifice, mice fed with cycad showed TUNEL and caspase-3
positive cells indicative of apoptosis in spinal cord, cortex,
hippocampus, substantia nigra and olfactory bulb
(Fig. 2G – I). In addition to motor deficits, observed regions
of neural degeneration were consistent with observed
cognitive and sensory deficits. Both spatial learning (Morris
water maze) and reference memory (radial arm maze)
ARTICLE IN PRESS
6
C.A. Shaw, J.M.B. Wilson / Neuroscience and Biobehavioral Reviews xx (2003) xxx–xxx
Fig. 2. Summary of data from the cycad mouse model. A –C: behavioral deficits displayed by cycad-fed mice (A) cycad-fed mice, (B) control mice. A:
radial arm maze test of spatial memory. Reference memory (entrances into incorrect arms) and working memory (entrances to previously visited arms)
errors by cycad-fed and control mice are shown. B: Paw Print testing for walking gait length. C: Leg extension reflex test, a measure of motor neuron
integrity. D– F: Cell counts or MRI volume measurements in specific CNS areas of cycad-fed mice compared to controls. D: i. Cortical thickness
measurement of several areas of cortex. V1: primary visual cortex. LEnt: lateral entorhinal cortex. M1: primary motor cortex. S1: primary
somatosensory cortex. Pir: piriform cortex. ii. Hippocampus volumes of control and cycad-fed mice. E: i. Striatum volumes of control and cycad-fed
mice. ii. Substantia nigra (SN) volumes of control and cycad-fed mice. F: i. Motor neuron counts from ventral horn of spinal cord from control and
cycad-fed mice. ii. Ventral horn volumes of control and cycad-fed mice. G–I: Histological display of cell pathology in CNS of cycad-fed mice. G:
TUNEL labeling in cycad-fed mouse. i, ii: TUNEL labeling in cortex. iii. TUNEL labeling in Dentate gyrus. i–iii 40 £ magnification. H: Caspase-3
labeling of cycad-fed mouse substantia nigra (SN). i. 10 £ magnification. ii. 40 £ magnification. I: Cresyl Violet staining of spinal cord motor
neurons. i. Control, ii, iii. Cycad-fed mouse. J–L: Examples of selected biochemical changes in CNS tissue from cycad-fed and control mice. J:
Immunolabeling of GLT-1 in primary motor cortex,. i: Control, ii. Cycad-fed. K: Tyrosine hydroxalase (TH) labeling of striatum. i: Control, ii. Cycadfed. L: Immunolabeling of GLT-1 of spinal cord. i: Control, ii. Cycad-fed. J, L: scale bar ¼ 80 mm.All graphs show means ^ SEM, (* P , 0:05: A– C,
G –I: Original data from [7]; D –F: Original data from [81]; J, L: Original data from Ref. [44]; K: Original data from Ref. [45]).
ARTICLE IN PRESS
C.A. Shaw, J.M.B. Wilson / Neuroscience and Biobehavioral Reviews xx (2003) xxx–xxx
(Fig. 2A) tasks were degraded, with corresponding neurodegeneration seen in regions of cerebral cortex and
hippocampus (Fig. 2D). In addition, the olfactory system
showed a significant loss of function accompanied by
disrupted structures and cell loss in the olfactory glomeruli.
In various regions, key molecules associated with
neuronal degeneration were altered. These included an
elevation of tau protein and various protein kinases, notably
various PKC subtypes and CDK5. In addition, elements of
the glutamatergic system were severely affected, most
notably a dramatic decrease in levels of two variants of the
GLT –1 glutamate transporter (EAAT2) (Fig. 2J and L)
accompanied by a decrease in NMDA and AMPA receptor
binding [44]. The apparent down-regulation in GLT and
glutamate receptor subtypes was noted in regions of the
CNS showing neural degeneration. Labeling for tyrosine
hydroxylase revealed a significant decrease of labeled
terminals in striatum and of cell bodies in substantia nigra
pars compacta of cycad fed mice (Fig. 2K) [45].
All of the features described above are consistent with
features of ALS-PDC, as well as key aspects of AD, PD, and
ALS. Of particular significance is the observation that the
alterations in behavior and CNS morphology are progressive in adult mice even after cycad exposure ends [7].
7. Does the ALS-PDC model satisfy standard criteria?
A model is defined as any experimental preparation
developed for the purpose of studying a condition in the
same or different species [46]. When assessing any model it
is critical to consider the explicit purpose of the model as
this determines the criteria that must be satisfied to establish
validity. In this regard, three components of validity must be
satisfied: predictive, construct, and etiological. With regard
to modeling human neurological disease, the latter assumes
the greatest significance and is a point on which most animal
models fail. For example, b-amyloid mice display cognitive
deficits [8], but genetic induction of b-amyloid is not likely
the cause of late onset AD in most patients [47,48].
Similarly, for ALS the SOD-1 mutant mouse is widely used,
but mutant SOD in humans only accounts for 2% of all ALS
cases (20% of familial ALS patients [49]). In the same vein,
a-synuclein accumulation can be a feature of both sporadic
and familial PD, but it has only been linked as the cause of
the parkinsonism in a small number of families [50]. In
contrast to these models, consumption of cycad in humans is
the strongest epidemiological link to ALS-PDC and as
described above similar feeding paradigms in mice produce
neurological outcomes that mimic the disease in all essential
features. Thus, the murine model of ALS-PDC meets the
criterion of ‘etiological’ validity.
Construct validity is defined as the accuracy with which a
test measures what it is intended to measure. Any animal
model of a progressive neurological disease should provide
7
predictable time-dependent losses of neural cells in the
same CNS regions affected in the human disease. The ALSPDC model satisfies this criterion since it demonstrates
progressive neuronal loss in regions of CNS accompanied
by appropriate behavioral dysfunction, both resembling
measurable features of ALS-PDC. In addition, the phenomenology is robust in that it has been routinely observed in
multiple batches of animals and displays the range of motor
and cognitive outcomes that comprise the diverse
expression of the various sub-disorders in ALS-PDC, i.e.
ALS, PDC and the combined symptoms.
The final standard—predictive validity—is defined as the
ability of a test to predict a criterion that is of interest to
the investigator [46]. In any neurodegenerative disease, the
major criterion of interest is a progressive degeneration of
specific neuronal subsets. For example, in Parkinson’s
disease, the major neuronal degeneration is in the substantia
nigra and striatum; in ALS, degeneration of upper and/or
lower motor neurons of the brain/spinal cord; AD is
typified by degeneration of cortical neurons and cortical
thinning along with the appearance of NFT and/or amyloid
plaques. Our model of ALS-PDC meets this criterion as
well: Mice fed with washed cycad flour display progressive
cognitive and motor behavioral deficits as well as
corresponding CNS pathologies. In addition, a clearly predictive feature of our model is the olfactory sensory
deficit and disruption of the morphology of olfactory
glomeruli. These data predict similar deficits in human
AD, PD, ALS, and ALS-PDC, features which are now
reported in Refs. [51 –53].
8. Genetic– epigenetic interactions in the cycad model
Our results have clearly demonstrated that an exogenous
neurotoxin contained in cycad can induce features of ALSPDC in a mouse model. These results lend strong support to
the notion that many of the features of the human disease, as
well as similar age-related neurodegenerative diseases,
could have as their basis an environmental toxin to which
various fractions of the population are exposed and
susceptible. The notion that environmental toxins could be
primary etiological factors has long been considered for
various neurological diseases and a recent study on identical
twins lends increasing support to the notion that environment, rather than a simple genetic factor, is crucial (see Ref.
[54]). Nevertheless, familial forms of these diseases exist
and in such cases there is abundant evidence for genetic
causality of a limited scope. Animal models of genetic
factors involved in human neurological diseases have
provided much information about potential mechanisms
leading to cell death. For example, transgenic mice
over-expressing b-amyloid show cognitive losses and
neuronal damage similar to AD and mutant superoxide
dismutase (mSOD1) mice expressing a toxic gain of
ARTICLE IN PRESS
8
C.A. Shaw, J.M.B. Wilson / Neuroscience and Biobehavioral Reviews xx (2003) xxx–xxx
function mutation for SOD show a progressive degeneration
of motor neurons.
Given the above data, it is too simplistic to view any of
the sporadic forms of neurological disease as solely the
result of either genes or environment. In fact, a growing
number of investigators have concluded that the intersection
of genetic-epigenetic factors is involved. Fig. 3 illustrates
this concept, showing the intersection of genetic susceptibility factors with environmental toxins, along with age as
the critical third variable. This last factor is crucial,
especially given that the diseases under discussion in this
article all occur within specific age ranges, usually
beginning in late middle age.
We have begun to examine gene-environment interactions using our cycad mouse model due to the ability of
this model system to reliably induce neurodegeneration in
specific neural subsets. We have now combined cycad
feeding with two genetic variants. First, APO E transgenic
mice have been used to explore the interaction of cycad
toxins with genetic susceptibility co-factors. APO E
proteins are involved in cholesterol handling and the
various allele variants have been implicated in AD, ALS,
and ALS-PDC [55]. Second, transgenic mice over-expressing mutant human SOD (mSOD1) have been used to
examine cycad interactions with a genetic causal factor.
mSOD has been linked to some forms of familial ALS
(FALS) [56].
APOE knockout (KO) mice fed cycad did not display
significant behavioral deficits, in marked contrast to cycadfed wild-type (WT) APOE mice which showed significant
deficits across a range of functions [57]. Histology showed
cell death in the substantia nigra, hippocampus, and
striatum in cycad-fed WT mice, but not in cycad-fed
APOE KO mice. Cycad-fed APOE KO mice also showed
increased cholesterol levels without displaying cycadinduced damage to heart or liver [57]. (Experiments in
which cycad will be fed to mice expressing specific APOE
isoforms (E2, E3, and E4) are currently underway.) These
data clearly demonstrate that certain genetic susceptibility
factors can increase or decrease sensitivity to toxin
exposure, reinforcing the notion that the interplay of
genes and environment is likely part of the overall
constellation of factors leading to neurodegenerative
disease. With regard to this last point, additional complexity is certain to arise in future experiments as we examine
the complete temporal sequence of events from initial toxic
insult to cell death, especially for animals of different ages.
mSOD mice fed cycad showed accelerated motor
behavioral losses, but in a manner that was not simply
the sum of cycad effects combined with those of the
mutation [58]. For example, measurements of leg extension, an index of spinal motor neuron integrity, showed
that mSOD mice fed cycad had a move rapid decline than
either mSOD mice or cycad-fed wild type mice. Measurements of latency to fall on a rotarod test gave a very
different picture with cycad-fed mSOD mice performing
better than mSOD mice not exposed to cycad. These data
are preliminary and await confirmation, but highlight again
the notion that gene-environment interactions are likely to
be complex.
9. Time line of neurodegenerative events
in the cycad model
Fig. 3. Potential synergies of causal and risk factors in sporadic
neurological disease. Causal factors involved in such diseases may reflect
exposure to toxin(s) that can arise from the environment or as a result of
individual biochemical processes. In the former case, the toxins may be
synthetic or naturally occurring. The toxic factor is represented by the set on
the left side of the diagram. The range of toxin’s effects run from left to
right as ‘low to high’. Intersecting this is a set consisting of a genetic
susceptibility factors that could arise due to genetic polymorphism in
efficiency of detoxification mechanisms (from right to left, expressed as
‘high to low’). Genes coding for transport proteins (e.g. APO E alleles)
could also be involved. The intersection of these two sets describes the
individuals who may be at risk of developing the neurological disorder.
Note that the intersecting region can increase or decrease depending on
strength of either variable. Intersecting these two sets is the variable of age
with the risk factor increasing from young to old (bottom to top).
As described above, our studies in cycad-fed mice have
utilized a battery of behavioral, biochemical, and morphological measures to create a working time line for the
emergence of behavioral and pathological outcomes beginning with the initial toxin insult and progressing through to
animal death. The data clearly reveal that the various
behaviors are impacted at different times following exposure
to cycad toxins. We do not yet have corresponding
biochemical and histological studies for each time point,
but these data are now beginning to emerge from our ongoing
studies. For example, we now know that the down-regulation
of glutamate transporter subtypes is a relatively early event,
likely occurring long before cell death [44]. Placed in
context, the alterations in protein kinase C we have noted in
previous experiments, are likely to occur even earlier and
may possibly be involved in abnormal phosphorylation of the
transporter leading to down-regulation and loss of function
[44]. Current studies will extend this timeline from
initial insult, through the period of overt expression of
neurological outcomes, and the stages leading to neural cell
death. Fig. 4 illustrates our progress to date and provides
ARTICLE IN PRESS
C.A. Shaw, J.M.B. Wilson / Neuroscience and Biobehavioral Reviews xx (2003) xxx–xxx
Fig. 4. ALS-PDC mouse model timeline of various behavioral and
pathological events. Events described are from data collected from cycadfed mice at the time point in which the event falls. ‘Progressing Behaviour’
lists events occurring during the time from start of feeding to sacrifice. The
‘Sacrifice’ column describes events that were found post mortem in CNS
tissue. ‘Predicted Progression’ describes hypothetical progression of the
cycad-induced outcomes. Arrows indicate predicted continuations ( ! ) or
predicted originations ( ˆ ) of the events described. " : increasing
levels/amounts. # : decreasing levels/amounts. Abbreviations: MN’s:
ventral horn spinal cord motor neurons; NFT: neurofibrillary tangles.
a current interpretation of where the various behavioral and
pathological events may be found along the timeline.
Once the model timeline is completed, we will be in a
position to attempt therapeutic interventions in our treated
animals at each stage of the disease process to prevent
further deterioration. Even if successful, however, ultimately we will need to transpose these data to the human
population in order that such treatments can be directed to
the right target at the precise time to have the greatest
impact. The ‘template matching’ between data from animal
models and human disease states, especially preclinical
states, remains the greatest single challenge for treating
neurological disease patients.
10. Template matching to human neurological disease
What is actually known about human neurological disease
progression? A search of the literature reveals that the rates
of decline for the various neurological diseases vary
9
quantitatively for each disease post clinical diagnosis, but
that the decline ‘function’ is usually linear. For example in
ALS, progression is linear for the decline of motor neurons
[59] as is the risk of death [60], but these measures depend on
the time of diagnosis [61]. For PD, there is a variable course of
progression of different PD symptoms depending on age of
onset, but these are always linear [62–64]. For AD, disease
progression measured by cognitive decline varies depending
on sex and age of behavioral onset [65]. Unfortunately, filling
in more details is unlikely to offer much in the way of
treatment options. Of greater concern, there seems to be very
little data about pre-clinical stages of these diseases, which
may show different rates of decline compared to postdiagnosis. For example, loss of function (strength and
functional activities) is linear, but the loss of motor neurons
may be exponential with an initial rapid fall that precedes
diagnosis followed by a more linear motor neuron loss as the
disease progresses [66]. However, it is during the pre-clinical
stage that the hope for effective prophylaxis or early treatment
exists.
This pre-clinical ‘gap’ is where animal models can
make the greatest contribution, for by extending the
timeline backwards to disease-initiating factors they
allow us to focus attention on the earliest potentially
treatable stages of each disease. Although results are
scattered and incomplete, some attempts have been made
in this regard. For example, in the amyloid b model of AD,
researchers have shown an exponential increase in amyloid
b deposits [67]. Similarly, mSOD mice used to model ALS
show exponentially increasing microglial activation from 0
to 120 days [68]. Some examples from the literature are
summarized in Table 2. In regard to our own model, cycadfed mice show exponential decays in motor and cognitive
functions, interspersed with what appear to be temporary
surges in behavioral compensation (see Refs. [7,69]).
In Fig. 5 we merge the two data sets, including the ALSPDC model system data with those from studies of human
age-dependent neurological disease. Note that the former
Table 2
Disease progression of human and animal modeled neurodegenerative disorders
Human (post-diagnosis
progression)
Mouse models (entire
disease progression)
AD
PD
ALS
Disease progression roughly
constant with time [65]
Variable course of progression
of different PD symptoms depending
on age of onset, but always linear [62]
Constant risk of death (Fig. 3a) [63]
Linear decline of motor neurons [59]
Exponential increase of
Amyloid B deposits in
PS1 þ APP transgenic AD
mouse [67]
Dopaminergic degeneration in PD
appears to slow down during course
of the disease [64]
Exponentially decreasing risk in
chemically induced model of PD
(Fig. 3D) [63]
Constant risk of death, but depending
on time of diagnosis [60]
Exponentially increasing microglial
activation from 0–120 days (Fig. 3)
in mSOD1 [68]
Disease progression rates are compared for Alzheimer’s disease (AD), Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS). Human disease rates
are determined from beginning of behavioral symptoms, while animal models measure progression from onset to death.
ARTICLE IN PRESS
10
C.A. Shaw, J.M.B. Wilson / Neuroscience and Biobehavioral Reviews xx (2003) xxx–xxx
Fig. 5. Predicted timeline of human neurological diseases. Symptoms and
pathological outcomes from Alzheimer’s disease, Parkinson’s disease and
ALS are described in a timeline of events. Preclinical symptoms describe
events that are thought to occur prior to overt behaviour symptoms seen at
clinical diagnosis. Features at death describe postmortem pathological
findings and end-state behavioral deficits. Arrows indicate predicted
continuations ( ! ) or predicted origins ( ˆ ) of events described. " :
increasing levels/amounts. # : decreasing levels/amounts.
starts from the initial insult and moves forward in time to the
end state condition, while the latter attempts to ‘reverse
engineer’ the earliest stages from the end state. Neither data
set alone is sufficient, but the hope is that the future success
of our model will allow us to fill in the enormous gaps that
now exist concerning the timeline of pathological events in
human neurological diseases.
As discussed above, the problem is that we have no
timeline to speak of for tracing the course of age-dependent
human neurological diseases. How, for example, can we
know who is pre-symptomatic for any of these diseases,
especially any of the sporadic varieties? In principle, various
brain scans or biomarkers could be widely employed, but the
first is not economically feasible for the population at large;
the second would depend on the identification of crucial
molecules, most of these still unknown. The necessary
crossover and template matching from an animal model to
human neurological disease states is a twofold process. First,
we have to be able to place what we know from our model
system into a clear description of events in all four
dimensions. Second, armed with this information, we can
then attempt template matching to pre- and post-clinical
human patients. This procedure may be a time consuming
one, yet offers, in our view, the only realistic possibility for
prevention and early treatment of human neurological
disease. We discuss a potential strategy in more detail below.
11. The mouse model of ALS-PDC: implications for
prophylaxis and for halting disease progression
Our work has demonstrated the following: First, we have
been able to show that a toxin contained in cycad is able to
kill neurons. Mice fed with washed cycad develop the same
behavioral and pathological outcomes as ALS-PDC victims.
Second, we have been able to show clear interactions of
cycad toxicity with various susceptibility (APO E) or causal
(mSOD) gene abnormalities. Third, we have begun the long
process of defining the various stages leading from toxic
insult to neurodegeneration.
Each of these outcomes has potentially enormous
implications for detecting and treating neurological disease.
The identification of potential toxins should now spark a
search for these molecules and molecules sharing their
mode of action in the human environment. The isolation and
partial characterization of the toxicity of various sterol
glucosides as the toxins giving rise to ALS-PDC may
suggest that an important future goal is the identification of
the sources of these toxins. Tracing such toxins would
naturally include a search for them in food products other
than in cycad. For example, soybeans may contain sterol
glucoside levels greater than those of cycad (Soybean flour:
214.9 mg/g [70]; Cycad: 11.5 – 84.5 mg/g [28,43]), although
whether processed soy does so as well is still an unanswered
question. In addition, sterol glucosides may be present in
other sources, i.e. a data base search reveals that sterol
glucosides are found in tobacco and survive in tobacco
smoke [71,72]. A recent report also shows that Helicobacter
pylori bacteria make a similar sterol glucoside, specifically a
cholesterol glucoside, [73,74] (note that Khabazian et al.
[43], found cholesterol glucoside to be extremely neurotoxic
in vitro). H. pylori infections are associated with increased
risk for PD [75] and this potential link to PD, and the
possible relation to other neurological disorders, should be
examined in greater detail.
Sterol glucosides are only one type of molecule able to
induce the types of neurodegeneration seen in our model
and in human neurological disease. Further, the sterol
glucosides identified by us may contribute only a small
fraction of total disease cases. From this, two possibilities
arise: first, structurally dissimilar molecules may have
similar mechanisms of action. Second, sterol glucosides
may interact synergistically with molecules having very
different mechanisms of action on neurons. In the latter
case, we consider the possibility of such interactions
between excitotoxins and oxidative stress (see Ref. [76]).
Overall, the identification of potential neurotoxins may
serve as a first means of prophylaxis since if we can detect
such molecules in the environment, we may be able to avoid
them.
Of equal importance, the notion that certain genetic
susceptibilities may be crucial, ties in with the identification
of putative toxins, and can be explored in several ways.
First, one could screen for the obvious gene candidates:
SOD, APO E, etc. A more sophisticated search would look
for genes involved in some process with which the putative
toxin could interact. For example, our identification of sterol
glucosides, including cholesterol glucoside, as potential
neurotoxins in neurological disease is directly relevant to
the notion that APO E allele variants can contribute to the
expression of such diseases. Similarly, genes coding for the
synthesis or modification of other sterols, e.g. the various
CYP genes [77,78], for example, may be important. In
addition, genes that control enzymes involved in the
synthesis or degradation of sterol glucosides could be
crucial [79,80]. The identification of human genetic profiles,
ARTICLE IN PRESS
C.A. Shaw, J.M.B. Wilson / Neuroscience and Biobehavioral Reviews xx (2003) xxx–xxx
especially as they relate to environmental toxins, may serve
to identify those persons at future risk of developing or
expressing the disease. Prophylaxis may be achieved by
identification of the putative toxin or by the identification of
those whose genetic susceptibility makes them vulnerable to
that toxin.
As valuable as prophylaxis would be to those not yet
affected, what does any of this imply for those at early and
middle stages of exposure and presumed emerging neural
damage? How are these individuals to be identified in order
that targeted therapeutics halt the biochemical cascades
from culminating in neurodegeneration and the clinical
manifestation of disease? The answer to this must arise from
a thorough understanding of the stages of the disease
process and, as discussed, this can only occur via a
comprehensive animal model that combines behavioral,
biochemical, and histological analyses over an extended
time period. In addition, an understanding of the full fourdimensional aspects of the disease process will allow
targeted therapeutics to be applied to halt degenerative
cascades. For example, early glutamate transporter abnormalities [44] created by excessive kinase activity might be
reversed by either a selective block of that kinase or an
induced up-regulation of the transporter. The timely
application of therapeutic agents, at the right place and
time, will be key components of a successful treatment
paradigm.
The challenge, however, is to extrapolate the animal fourdimensional data to the pre-clinical human population. We
envision a process something like the following: The mouse
timeline provides not only sequenced events leading to
neurodegeneration, but also comparative behavioral data
and, perhaps, the identification of various biomarkers for
early stages of the disease process. Working backwards from
patients currently diagnosed with the various diseases, we
can attempt strong correlations to earlier pre-clinical
behavioral changes. These, in turn, may lead to attempts to
identify such behavioral outcomes in pre-clinical populations. A good example of this process would be the use of
the apparent early olfactory disturbance in PD [51,52] to
place these individuals into the correct position in the
timeline. Behavioral indices of altered neural function might
then trigger the search for identified biomarkers, the latter
symptomatic of unique changes within the nervous system at
particular time points. MRI or other imaging methods could
then be employed to confirm changes to neural morphology.
As above, template matching between human patients and
animal models may allow a blockade of the neurodegenerative cascades at an early stage of the disease progression,
when most behavioural function is still intact.
12. Conclusion
ALS-PDC is a unique disease that displays aspects of the
major progressive neurodegenerative diseases, AD, PD and
11
ALS. The exceptional features of ALS-PDC may suggest
that AD, PD, and ALS share some common features and
may arise in part due to common etiologies. The ALS-PDC
behavioral and neuropathological outcomes can be reproduced in an animal model based on the consumption of
toxins contained in cycad seeds. The data obtained by this
model include the possible identification of the putative
neurotoxin as well as a preliminary understanding of the
temporal progression of neurodegeneration following
exposure. In addition, we have begun to explore aspects
of gene – environment interactions as determinants of
neurodegeneration. The insights gained by use of this
model may allow for future prophylaxis and treatment of
human neurological diseases.
Acknowledgements
This work was supported by grants from the ALS
Association, Scottish Rite Charitable Foundation of Canada,
Natural Science and Engineering Research Council of
Canada, and the US Army Medical Research and Materiel
Command (#DAMD17-02-1-0678) (to CAS). The authors
thank Drs S. Blackband and S. Grant of the University of
Florida, USA and D. Pow of the University of Queensland,
Australia for collaborations on MRI imaging and glutamate
transporter labeling, respectively. The authors also thank
H. Bavinton, C Melder, and M. Wong for comments on the
manuscript. Cycad seeds were provided by our colleagues
on Guam, Drs U. Craig and T. Marler to whom we are very
grateful. This review acknowledges the unique contributions of the late Dr L.T. Kurland.
References
[1] Shaw CA, McEachern JC. Toward a theory of neuroplasiticity.
Philadelphia: Psychology Press; 2001.
[2] Calne DB, Eisen A. The relationship between Alzheimer’s disease,
Parkinson’s disease and motor neuron disease. Can J Neurol Sci 1989;
16:547–50.
[3] Eisen A, Calne D. Amyotrophic lateral sclerosis, Parkinson’s disease
and Alzheimer’s disease: phylogenetic disorders of the human neocortex
sharing many characteristics. Can J Neurol Sci 1992;19:117–23.
[4] Yokoyama K, Ikebe S, Komatsuzaki Y, Takanashi M, Mori H,
Mochizuki H, Mizuno Y. A 68-year-old woman with dementia and
parkinsonism. No To Shinkei 2002;54:175–84.
[5] Aarsland D, Andersen K, Larsen JP, Lolk A, Kragh-Sorensen P.
Prevalence and characteristics of dementia in Parkinson disease: an 8year prospective study. Arch Neurol 2003;60:387–92.
[6] Vaphiades MS, Husain M, Juhasz K, Schmidley JW. Motor neuron
disease presenting with slow saccades and dementia. Amyotroph
Lateral Scler Other Motor Neuron Disord 2002;3:159–62.
[7] Wilson JM, Khabazian I, Wong MC, Seyedalikhani A, Bains JS,
Pasqualotto BA, Williams DE, Andersen RJ, Simpson RJ, Smith R,
Craig UK, Kurland LT, Shaw CA. Behavioral and neurological
correlates of ALS-parkinsonism dementia complex in adult mice fed
washed cycad flour. Neuromol Med 2002;1:207– 21.
[8] Masliah E, Rockenstein E, Veinbergs I, Sagara Y, Mallory M,
Hashimoto M, Mucke L. Beta-amyloid peptides enhance alphasynuclein accumulation and neuronal deficits in a transgenic mouse
ARTICLE IN PRESS
12
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18]
[19]
[20]
[21]
[22]
[23]
[24]
[25]
[26]
[27]
[28]
[29]
C.A. Shaw, J.M.B. Wilson / Neuroscience and Biobehavioral Reviews xx (2003) xxx–xxx
model linking Alzheimer’s disease and Parkinson’s disease. Proc Natl
Acad Sci USA 2001;98:12245–50.
Verghese J, Lipton RB, Hall CB, Kuslansky G, Katz MJ, Buschke H.
Abnormality of gait as a predictor of non-Alzheimer’s dementia. N
Engl J Med 2002;347:1761–8.
Zoccolella S, Palagano G, Fraddosio A, Russo I, Ferrannini E,
Serlenga L, Maggio F, Lamberti S, Iliceto G. ALS-plus: 5 cases of
concomitant amyotrophic lateral sclerosis and parkinsonism. Neurol
Sci 2002;23(Suppl 2):S123–4.
Price DL. New order from neurological disorders. Nature 1999;399:
A3–A5.
Wilson CM, Grace GM, Munoz DG, He BP, Strong MJ. Cognitive
impairment in sporadic ALS: a pathologic continuum underlying a
multisystem disorder. Neurology 2001;57:651–7.
Marquard R, Bergida R, Muller R, Becker I, Wada M, Kurz A.
Dementia accompanying motor neuron disease—7 cases. Dementia
Geriatr Cogn Disord 2003;16:98 –102.
Arima K, Hirai S, Sunohara N, Aoto K, Izumiyama Y, Ueda K, Ikeda
K, Kawai M. Cellular co-localization of phosphorylated tau- and
NACP/alpha-synuclein-epitopes in lewy bodies in sporadic Parkinson’s disease and in dementia with Lewy bodies. Brain Res 1999;843:
53–61.
Kokubo Y, Kuzuhara S, Narita Y. Geographical distribution of
amyotrophic lateral sclerosis with neurofibrillary tangles in the Kii
Peninsula of Japan. J Neurol 2000;247:850–2.
Lucking CB, Brice A. Alpha-synuclein and Parkinson’s disease. Cell
Mol Life Sci 2000;57:1894 –908.
Arasaki K, Tamaki M. A loss of functional spinal alpha motor neurons
in amyotrophic lateral sclerosis. Neurology 1998;51:603–5.
Whitehouse PJ, Price DL, Struble RG, Clark AW, Coyle JT, Delon
MR. Alzheimer’s disease and senile dementia: loss of neurons in the
basal forebrain. Science 1982;215:1237–9.
Leenders KL, Salmon EP, Tyrrell P, Perani D, Brooks DJ, Sager H,
Jones T, Marsden CD, Frackowiak RS. The nigrostriatal dopaminergic system assessed in vivo by positron emission tomography in
healthy volunteer subjects and patients with Parkinson’s disease. Arch
Neurol 1990;47:1290 –8.
Schott JM, Fox NC, Frost C, Scahill RI, Janssen JC, Chan D, Jenkins
R, Rossor MN. Assessing the onset of structural change in familial
Alzheimer’s disease. Ann Neurol 2003;53:181–8.
Steele JC, Guzman T. Observations about amyotrophic lateral sclerosis
and the parkinsonism–dementia complex of Guam with regard to
epidemiology and etiology. Can J Neurol Sci 1987;14:358–62.
Kurland LT. Amyotrophic lateral sclerosis and Parkinson’s disease
complex on Guam linked to an environmental neurotoxin. Trends
Neurosci 1988;11:51– 4.
Hirano A, Malamud N, Elizan TS, Kurland LT. Amyotrophic lateral
sclerosis and Parkinsonism-dementia complex on Guam. Further
pathologic studies. Arch Neurol 1966;15:35–51.
Kurland LT, Mulder DW. Epidemiologic investigations of amyotrophic lateral sclerosis. Neurology 1954;4:355–78.
Plato CC, Garruto RM, Galasko D, Craig UK, Plato M, Gamst A,
Torres JM, Wiederholt W. Amyotrophic lateral sclerosis and
parkinsonism – dementia complex of Guam: changing incidence
rates during the past 60 years. Am J Epidemiol 2003;157:149–57.
Hall WT. Cycad (zamia) poisoning in Australia. Aust Vet J 1987;64:
149–51.
Schneider D, Wink M, Sporer F, Lounibos P. Cycads: their evolution,
toxins, herbivores and insect pollinators. Naturwissenschaften 2002;
89:281–94.
Kisby GE, Ellison M, Spencer PS. Content of the neurotoxins cycasin
(methylazoxymethanol beta-D -glucoside) and BMAA (beta-N-methylamino-L -alanine) in cycad flour prepared by Guam Chamorros.
Neurology 1992;42:1336–40.
Hoffmann GR, Morgan RW. Review: putative mutagens and
carcinogens in foods. V. Cycad azoxyglycosides. Environ Mutagen
1984;6:103–16.
[30] Oh CH, Brownson DM, Mabry TJ. Screening for non-protein amino
acids in seeds of the Guam cycad, Cycas circinalis, by an improved
GC-MS method. Planta Med 1995;61:66–70.
[31] Pan M, Mabry TJ, Cao P, Moini M. Identification of nonprotein amino
acids from cycad seeds as N-ethoxycarbonyl ethyl ester derivatives by
positive chemical-ionization gas chromatography – mass spectrometry. J Chromatogr A 1997;787:288–94.
[32] Campbell ME, Mickelsen O, Yang MG, Laqueur GL, Keresztesy JC.
Effects of strain, age and diet on the response of rats to the ingestion of
Cycas circinalis. J Nutr 1966;88:115– 24.
[33] Hooper PT, Best SM, Campbell A. Axonal dystrophy in the spinal
cords of cattle consuming the cycad palm, Cycas media. Aust Vet J
1974;50:146–9.
[34] Perry TL, Bergeron C, Biro AJ, Hansen S. Beta-N-methylamino-L alanine. Chronic oral administration is not neurotoxic to mice.
J Neurol Sci 1989;94:173–80.
[35] Duncan MW, Steele JC, Kopin IJ, Markey SP. 2-Amino-3(methylamino)-propanoic acid (BMAA) in cycad flour: an unlikely
cause of amyotrophic lateral sclerosis and parkinsonism–dementia of
Guam. Neurology 1990;40:767–72.
[36] Spencer PS, Nunn PB, Hugon J, Ludolph AC, Ross SM, Roy DN,
Robertson RC. Guam amyotrophic lateral sclerosis-parkinsonism–
dementia linked to a plant excitant neurotoxin. Science 1987;237:
517 –22.
[37] Esclaire F, Kisby G, Spencer P, Milne J, Lesort M, Hugon J. The
Guam cycad toxin methylazoxymethanol damages neuronal DNA and
modulates tau mRNA expression and excitotoxicity. Exp Neurol
1999;155:11–21.
[38] Weiss JH, Koh JY, Choi DW. Neurotoxicity of beta-N-methylaminoL -alanine (BMAA) and beta-N-oxalylamino-L -alanine (BOAA) on
cultured cortical neurons. Brain Res 1989;497:64– 71.
[39] Allen CN, Omelchenko I, Ross SM, Spencer P. The neurotoxin, betaN-methylamino-L -alanine (BMAA) interacts with the strychnineinsensitive glycine modulatory site of the N-methyl-D -aspartate
receptor. Neuropharmacology 1995;34:651–8.
[40] Spencer PS, Schaumburg HH. Lathyrism: a neurotoxic disease.
Neurobehav Toxicol Teratol 1983;5:625–9.
[41] Ravindranath V. Neurolathyrism: mitochondrial dysfunction in
excitotoxicity mediated by L -beta-oxalyl aminoalanine. Neurochem
Int 2002;40:505–9.
[42] Cox PA, Sacks OW. Cycad neurotoxins, consumption of flying foxes,
and ALS-PDC disease in Guam. Neurology 2002;58:956– 9.
[43] Khabazian I, Bains JS, Williams DE, Cheung J, Wilson JM,
Pasqualotto BA, Pelech SL, Andersen RJ, Wang YT, Liu L, Nagai
A, Kim SU, Craig UK, Shaw CA. Isolation of various forms of sterol
beta-d-glucoside from the seed of Cycas circinalis: neurotoxicity and
implications for ALS-parkinsonism dementia complex. J Neurochem
2002;82:516–28.
[44] Wilson JM, Khabazian I, Pow DV, Craig UK, Shaw CA. Decrease in
Glial Glutamate transporter variants and excitatory amino acid
receptor down-regulation in a murine model of ALS-PDC. Neuromolecular Med 2003;3:41–53.
[45] Schulz JD, Khabazian I, Wilson JM, Shaw CA. A murine model of
ALS-PDC with behavioural and neuropathological features of
Parkinsonism. Ann N Y Acad Sci 2003;991:326–9.
[46] Geyer MA, Markou A. Animal models of psychiatric disorders. In:
Bloom FE, Kupfer DJ, editors. Psychopharmacology: the fourth
generation of progress. New York: Raven Press; 1995. p. 787– 98.
[47] Levy-Lahad E, Tsuang D, Bird TD. Recent advances in the genetics of
Alzheimer’s disease. J Geriatr Psychiatry Neurol 1998;11:42–54.
[48] Shastry BS, Giblin FJ. Genes and susceptible loci of Alzheimer’s
disease. Brain Res Bull 1999;48:121–7.
[49] Robberecht W. Genetics of amyotrophic lateral sclerosis. J Neurol
2000;247:2–6.
[50] Gasser T. Genetics of Parkinson’s disease. J Neurol 2001;248:833 –40.
[51] Ahlskog JE, Waring SC, Petersen RC, Esteban-Santillan C, Craig UK,
O’Brien PC, Plevak MF, Kurland LT. Olfactory dysfunction in
ARTICLE IN PRESS
C.A. Shaw, J.M.B. Wilson / Neuroscience and Biobehavioral Reviews xx (2003) xxx–xxx
[52]
[53]
[54]
[55]
[56]
[57]
[58]
[59]
[60]
[61]
[62]
[63]
[64]
[65]
[66]
[67]
[68]
[69]
Guamanian ALS, parkinsonism, and dementia. Neurology 1998;51:
1672–7.
Tissingh G, Berendse HW, Bergmans P, DeWaard R, Drukarch B,
Stoof JC, Wolters EC. Loss of olfaction in de novo and treated
Parkinson’s disease: possible implications for early diagnosis. Mov
Disord 2001;16:41 –6.
Christen-Zaech S, Kraftsik R, Pillevuit O, Kiraly M, Martins R,
Khalili K, Miklossy J. Early olfactory involvement in Alzheimer’s
disease. Can J Neurol Sci 2003;30:20–5.
Tanner CM, Ottman R, Goldman SM, Ellenberg J, Chan P, Mayeux R,
Langston JW. Parkinson disease in twins: an etiologic study. JAMA
1999;281:341 –6.
Bedlack RS, Strittmatter WJ, Morgenlander JC. Apolipoprotein E and
neuromuscular disease: a critical review of the literature. Arch Neurol
2000;57:1561 –5.
Radunovic A, Leigh PN. ALSODatabase: database of SOD1 (and
other) gene mutations in ALS on the Internet. European FALS Group
and ALSOD consortium. Amyotroph Lateral Scler Other Motor
Neuron Disord 1999;1:45–9.
Wilson JMB, Petrik MS, Blackband SJ, Grant SG, Moghadasian MH,
Shaw CA. Role of ApcE in Neurodegenerative disorders using an
environmentally induces murine model of ALS-PDC. Program No.
630.9.2003 Abstract Viewer/Itinerary Planner. Washington, DC:
Society for Neuroscience, 2003. CD-ROM.
Melder CL, Bavinton HB, Krieger C, Shaw CA. The combined effects
of cycad toxins and the Sod1 mutation on a Murine model of ALSPDC. Society for Neuroscience Abstracts; 2003, (Abstract), in press.
Munsat TL, Andres PL, Finison L, Conlon T, Thibodeau L. The
natural history of motoneuron loss in amyotrophic lateral sclerosis.
Neurology 1988;38:409–13.
Christensen PB, Hojer-Pedersen E, Jensen NB. Survival of patients
with amyotrophic lateral sclerosis in 2 Danish counties. Neurology
1990;40:600– 4.
Louwerse ES, Visser CE, Bossuyt PM, Weverling GJ. Amyotrophic
lateral sclerosis: mortality risk during the course of the disease and
prognostic factors. The Netherlands ALS Consortium. J Neurol Sci
1997;152(Suppl 1):S10–S17.
Jankovic J, Kapadia AS. Functional decline in Parkinson disease.
Arch Neurol 2001;58:1611–5.
Clarke G, Collins RA, Leavitt BR, Andrews DF, Hayden MR,
Lumsden CJ, McInnes RR. A one-hit model of cell death in inherited
neuronal degenerations. Nature 2000;406:195–9.
Pirker W, Djamshidian S, Asenbaum S, Gerschlager W, Tribl G,
Hoffmann M, Brucke T. Progression of dopaminergic degeneration in
Parkinson’s disease and atypical parkinsonism: a longitudinal betaCIT SPECT study. Mov Disord 2002;17:45–53.
Neumann PJ, Araki SS, Arcelus A, Longo A, Papadopoulos G, Kosik
KS, Kuntz KM, Bhattacharjya A. Measuring Alzheimer’s disease
progression with transition probabilities: estimates from CERAD.
Neurology 2001;57:957–64.
Bromberg MB. Electrodiagnostic studies in clinical trials for motor
neuron disease. J Clin Neurophysiol 1998;15:117–28.
Gordon MN, Holcomb LA, Jantzen PT, DiCarlo G, Wilcock D, Boyett
KW, Connor K, Melachrino J, O’Callaghan JP, Morgan D. Time
course of the development of Alzheimer-like pathology in the doubly
transgenic PS1 þ APP mouse. Exp Neurol 2002;173:183–95.
Hall ED, Oostveen JA, Gurney ME. Relationship of microglial and
astrocytic activation to disease onset and progression in a transgenic
model of familial ALS. Glia 1998;23:249–56.
Shaw CA, Wilson JM, Khabazian I. Reverse engineering neurological
disease. Proceedings of International Conference on Complex
Systems, Brief article; 2002; available online at: http://www.
interjournal.org/cgi-bin/manuscript_abstract.cgi?7759
13
[70] Sugiyama M, Seki J. In vivo application of lipoproteins as drug
carriers: pharmacological evaluation of sterylglucoside-lipoprotein
complexes. Targeted Diagn Ther 1991;5:315–50.
[71] Johnstone RA, Plimmer JR. Chem Rev 1959;59:885.
[72] Stedman RL. The chemical composition of tobacco and tobacco
smoke. Chem Rev 1968;68:153–207.
[73] Hirai Y, Haque M, Yoshida T, Yokota K, Yasuda T, Oguma K.
Unique cholesteryl glucosides in Helicobacter pylori: composition
and structural analysis. J Bacteriol 1995;177:5327–33.
[74] Haque M, Hirai Y, Yokota K, Mori N, Jahan I, Ito H, Hotta H, Yano I,
Kanemasa Y, Oguma K. Lipid profile of Helicobacter spp.: presence
of cholesteryl glucoside as a characteristic feature. J Bacteriol 1996;
178:2065–70.
[75] Dobbs SM, Dobbs RJ, Weller C, Charlett A. Link between
Helicobacter pylori infection and idiopathic parkinsonism. Med
Hypotheses 2000;55:93–8.
[76] Shaw CA, Bains JS. Synergistic versus antagonistic actions of
glutamate and glutathione: the role of excitotoxicity and oxidative
stress in neuronal disease. Cell Mol Biol (Noisy-le-grand) 2002;48:
127–36.
[77] Lin D, Harikrishna JA, Moore CC, Jones KL, Miller WL. Missense
mutation serine106—proline causes 17 alpha-hydroxylase deficiency.
J Biol Chem 1991;266:15992–8.
[78] Yu L, Romero DG, Gomez-Sanchez CE, Gomez-Sanchez EP.
Steroidogenic enzyme gene expression in the human brain. Mol
Cell Endocrinol 2002;190:9–17.
[79] Warnecke D, Heinz E. Purification of a membrane-bound UDPglucose:sterol [beta]-D -glucosyltransferase based on its solubility in
diethyl ether. Plant Physiol 1994;105:1067– 73.
[80] Warnecke D, Erdmann R, Fahl A, Hube B, Muller F, Zank T,
Zahringer U, Heinz E. Cloning and functional expression of UGT
genes encoding sterol glucosyltransferases from Saccharomyces
cerevisiae, Candida albicans, Pichia pastoris, and Dictyostelium
discoideum. J Biol Chem 1999;274:13048–59.
[81] Petrik MS, Wilson JMB, Grant SG, Blackband SJ, Lai J, Shaw CA.
Quantitative measurement of neurodegeneration in ALS-PDC model
using MRI. Program No. 630.10.2003 Abstract Viewer/Itinerary
Planner. Washington, DC: Society for Neuroscience, 2003. CD-ROM.
[82] Bromberg MB. Pathogenesis of amyotrophic lateral sclerosis: a
critical review. Curr Opin Neurol 1999;12:581–8.
[83] Militello A, Vitello G, Lunetta C, Toscano A, Maiorana G, Piccoli T,
La Bella V. The serum level of free testosterone is reduced in
amyotrophic lateral sclerosis. J Neurol Sci 2002;195:67–70.
[84] Taba P, Asser T. Incidence of Parkinson’s disease in estonia.
Neuroepidemiology 2003;22:41– 5.
[85] Wermuth L, von Weitzel-Mudersbach P, Jeune B. A two-fold difference
in the age-adjusted prevalences of Parkinson’s disease between the
island of Als and the Faroe Islands. Eur J Neurol 2000;7:655–60.
[86] Wermuth L, Pakkenberg H, Jeune B. High age-adjusted prevalence of
Parkinson’s disease among Inuits in Greenland. Neurology 2002;58:
1422– 5.
[87] Milanov I, Kmetska K, Karakolev B, Nedialkov E. Prevalence of
Parkinson’s disease in Bulgaria. Neuroepidemiology 2001;20:212 –4.
[88] Baldereschi M, Di Carlo A, Rocca WA, Vanni P, Maggi S,
Perissinotto E, Grigoletto F, Amaducci L, Inzitari D. Parkinson’s
disease and parkinsonism in a longitudinal study: two-fold higher
incidence in men. ILSA Working Group. Italian Longitudinal Study
on Aging. Neurology 2000;55:1358–63.
[89] Kirby L, Lehmann P, Majeed A. Dementia in people aged 65 years
and older: a growing problem? Popul Trends 1998;23–8.
[90] McGonigal G, Thomas B, McQuade C, Starr JM, MacLennan WJ,
Whalley LJ. Epidemiology of Alzheimer’s presenile dementia in
Scotland, 1974–88. BMJ 1993;306:680–3.