Physiological and anatomical properties of dopamine neurons: clues to differential susceptibility in Parkinson's disease
Prof. Paul Bolam
(University of Oxford)
Abstract:
Theories that explain the loss of dopamine neurons of the substantia nigra pars compacta (SNc) in
Parkinson's disease (PD) must account for the fact that it is this sub-population of dopamine neurons,
among all the different sub-types of dopamine neurons, and indeed all other neurons in the brain, that
are the most sensitive to dying in PD. Furthermore, it is this population of dopamine neurons that shows
greatest sensitivity to toxins, even general mitochondrial poisons like rotenone and greatest sensitivity
in genetic forms of PD. In this communication some of the characteristics of dopamine neurons in terms
of their electrophysiological properties, their connections and morphological properties will be described.
There is very little difference in the electrical activity and afferent synapses of different populations
of dopamine neurons in the SNc that could account for differential susceptibility. However, the axon
and synaptic output of SNc dopamine neurons is remarkably different to other populations of dopamine
neurons and to all other neurons in the brain. Individual dopamine neurons give rise to hundreds of
thousands of synapses in their target region in the striatum where the connections are not targeted [2],
[3]. This an order of magnitude higher than other types of dopamine neurons and several orders of
magnitude greater than other neuron types in the brain. Single cell filling by Matsuda and colleagues
([1]) have shown than the axon of an individual dopamine neuron can be up to 70 cm in total length.
We propose that this massive axonal arbour, which is probably an order of magnitude even greater in
humans, will put a high energetic demand on the neurons for, amongst other things, the generation of
action potentials and the maintenance of the membrane potential. Any stressor, e.g. oxidative stress,
genetic mutations, mitochondrial poisons or dopamine neurotoxins, will have a preferential effect on these
neurons because they are energetically 'on-the-edge', leading to die-back and eventual death. Thus the
loss of SNc dopamine neurons in PD may, at least in part, be a consequence of the high energy demand
of their massive and complex axonal arbours.
[1] W. Matsuda, T. Furuta, K. Nakamura, H. Hioki, F. Fujiyama, R. Arai, and T. Kaneko. Single
nigrostriatal dopaminergic neurons form widely spread and highly dense axonal arborizations in the
neostriatum. Journal of Neuroscience, 29(2):444-453, 2009.
[2] J. Moss and J. Bolam. A dopaminergic axon lattice in the striatum and its relationship with cortical
and thalamic terminals. Journal of Neuroscience, 28(44):11221-11230, 2008.
[3] J. Moss and J. Bolam. The relationship between dopaminergic axons and glutamatergic synapses
in the striatum: structural considerations. In L. Iversen, S. Iversen, S. Dunnett, and A. Björklund,
editors, The Dopamine Handbook, chapter 2.4, pages 49-59. Oxford University Press, 2010.
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Closing the loop on Parkinson's disease etiology:
a modelling study of the feedback between protein and oxidative metabolism
Dr. Mathieu Cloutier
(École Polytechnique Montreal)
Abstract:
Except for a small percentage of genetic cases, the causes of Parkinson's disease are unknown. How-
ever, the progress of the disease has been linked to a number of biological mechanisms. We study two
such mechanisms - the excessive accumulation of reactive oxygen species (ROS) and misfolded α-synuclein
(αSYN) protein, both of which are thought to play central roles in the pathogenesis of idiopathic Parkinson's disease. Despite their association with Parkinson's disease, the relative causal contributions of ROS
and αSYN remain poorly understood. With this theme of causality in mind, we explore the potential
pathogenic contributions of ROS and misfolded αSYN in terms of a multi-factorial feedback interaction.
By distilling the biochemistry of a descriptive mathematical model down to its essential components, we
are able to identify a positive feedback loop that interlinks changes in intracellular ROS and misfolded
αSYN concentrations. This feedback system exhibits bistability for a wide range of physiological conditions, with one stable state at high ROS and misfolded αSYN concentrations. This indicates a highly
plausible mechanism to explain the dynamic and irreversible progression of Parkinson's disease. We can
thus illustrate in silico how balances that are normally held in homeostasis by a healthy cell can be
irreversibly disturbed by multi-factorial etiopathogenic inputs. The theoretical and in silico predictions
obtained from the core feedback motif are thus coherent with experimental observations in Parkinson's
disease, and offer a number of testable predictions.
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Modelling and measurement of cerebral signalling circuits
Guillaume Drion
(University of Liege)
Abstract:
Midbrain dopaminergic neurons in the substantia nigra, pars compacta and ventral tegmental area are
critically important in many physiological functions. These neurons exhibit firing patterns that include
tonic slow pacemaking, irregular firing and bursting, and the amount of dopamine that is present in the
synaptic cleft is much increased during bursting. The mechanisms responsible for the switch between
these spiking patterns remain unclear.
Firstly, using both in vivo recordings combined with microiontophoretic or intraperitoneal drug applications and in vitro experiments, we have found that M-type channels, which are present in midbrain
dopaminergic cells, modulate the firing during bursting, without affecting the background low frequency
pacemaker firing. Thus, a selective blocker of these channels, XE991, specifically potentiated burst firing.
Computer modeling of the dopamine neuron confirmed the possibility of a differential influence of M-type
channels on excitability during various firing patterns. Therefore, these channels may provide a novel
target for the treatment of dopamine-related diseases, including Parkinsons disease and drug addiction.
Moreover, our results demonstrate that the influence of M-type channels on the excitability of these slow
pacemaker neurons is conditional upon their firing pattern.
Secondly, using computer modeling, we suggest a basic mechanism for the control of firing patterns
and synchrony in dopaminergic neurons, based on the modulation of small conductance calcium-activated
potassium (SK) channels. Moreover, we found that this mechanism may apply to many pacemaker
neurons such as mitral cells of the olfactory bulb or subthalamic nucleus neurons, many of these being
involved in Parkinson's disease. On the basis of this mechanism, we extracted a potential role for SK
channels in the pathological neuronal activity which accompanies Parkinson's disease.
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A whole cell model of calcium homeostasis in dopaminergic substantia nigra neurons
Dr. Míriam R. García
(NUI Maynooth)
Abstract:
The degeneration of dopaminergic (DA) neurons in the Substantia Nigra pars compacta (SNc) is a
hallmark of idiopathic Parkinson's disease (PD). However, resolving the degeneration mechanisms which
target these neurons is not simple. For example, it is well known that DA neurons in the SNc deteriorate
with age and are prone to die in PD, but there is no clear picture of what causes this or other related
processes.
Fortunately, some clues have come to light in recent epidemiologic studies. The latest work show how
hypertensive drugs that block L-type calcium channels in the brain also considerably reduce the incidence
of PD [2]. Following this insight, experiments with in vivo and in vitro models of PD have shown that
SNc DA neurons rely on L-type Cav 1.3 channels to sustain their autonomous pacemaking. Significantly
for PD, this reliance upon calcium channels for pacemaking increases with age [1]. This linkage strongly
suggests that the control of calcium homeostasis, which is fundamental for the normal function of any
cell, may be especially compromised in ageing SNc neurons. Unfortunately, calcium signalling involves
the interplay of multiple intracellular organelles and it becomes extremely difficult to design experiments
to estimate the energy cost of calcium regulation and to associate it with levels of predisposition to PD.
In this communication, we propose that the control of calcium homeostasis and the degeneration of
aged DA SNc neurons may be better understood from a systems perspective. To this end, we describe
the development of a mathematical model of whole cell dynamics with which we are able to reproduce
all relevant pathological features. In order to maintain the physiological meaning, and avoid technical
issues of system identifiability, a modular approach was used during model development. Model modules
representing different components - such as ion channels and pumps - were separately developed and
calibrated with available data specific to SNc cells. finally, each module can be integrated in a model
framework for the whole cell and in a form that is capable of predicting ATP consumption, in the form
of an energy budget, for both healthy and compromised cells.
In future works, the model will be further extended to explore positive feedback loops due to calcium
stress. One interesting example is the feedback mechanism that includes: mitochondria stress, production
of reactive oxygen species, misfolding of α-synuclein, and where the extension includes calcium cell specific
mechanisms such as sequestration of calbindin and increase of calcium cytoplasm.
[1] C. Chan, J. Guzman, E. Ilijic, J. Mercer, C. Rick, T. Tkatch, G. Meredith, and D. Surmeier. 'Rejuvenation' protects neurons in mouse models of Parkinson's disease. Nature, 447(7148):1081-1086,
2007.
[2] B. Ritz, S. L. Rhodes, L. Qian, E. Schernhammer, J. H. Olsen, and S. Friis. L-Type Calcium Channel
Blockers and Parkinson Disease in Denmark. Annals of Neurology, 67(5):600-606, 2010.
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In-vitro measurement for modelling of brain energy metabolism
Prof. Mario Jolicoeur
(École Polytechnique Montreal)
Abstract:
Parkinson's disease (PD) is a pernicious neurodegenerative disease for which no cure exists. Its
main cellular hallmark is the formation of Lewy inclusion bodies by alpha-synuclein protein aggregation.
Energy metabolism is deregulated by etiopathogenic factors of PD and this can have implications in
disease onset and progression. However brain energy metabolism is not limited to neuronal metabolism
as astrocytes provide metabolic support in the form of energy substrates trafficking. In that context, we
propose an ordinary differential equations model to study astrocyte's metabolism and its deregulation by
genetic factors of PD. The metabolic model is built on the main energy pathways: glycolysis, tricarboxylic
acids cycle, and oxidative phosphorylation chain. Model development is supported by an experimental
platform allowing in vitro monitoring of the bioenergetic behaviour of living cells and tissues. Preliminary
results will be presented as well as the state of development of the platform.
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Cell Systems Modelling of Aging Phenotypes using Fuzzy Logic
Prof. Andres Kriete
(Drexel University)
Abstract:
Aging is characterized not only by accumulating damage and dysfunction but also by stress-responsive
and adaptive mechanisms at the cellular level. Two specific pathways known to modulate the aging process are NF-κB and mTOR. For instance, cells from older humans demonstrate higher NF-κB DNA
binding activity accompanied by an inflammatory gene expression profile [2]. While the role of NF-κB
and mTOR pathways is initially adaptive and protective, chronic elevated high levels are characteristic
markers of age related diseases including dementias. Therefore it is important to decipher the behavior
of these pathways during aging and to predict the potential outcome of interventions with the goal to
extend healthspan. Since our work is inspired by a systems biology approach, the experimental investigations with respect to cell phenotypes and molecular cell states are complemented by a computer based
cell modeling [1]. Computer simulations are particularly desirable due to the slow progression of aging
in humans and difficulties to emulate aging experimentally in cells within reasonable timeframes. Our
computational approach is based on a generic, whole cell network graph representing the connectivity of
key cellular mechanisms structured into positive and negative feedback loop motifs centrally important
for aging. The network is casted into a fuzzy-logic, hybrid-intelligent framework based on interaction
rules assembled from experimental and a priori knowledge. Time-lapse simulations of the adaptive response model uncover how transcriptional and translational changes, mediated by stress sensors NF-κB
and mTOR, counteract accumulating damage and dysfunction by modulating mitochondrial respiration,
metabolic fluxes, biosynthesis, and autophagy, crucial for cellular survival. The model allows consideration of cell lifespan optimization scenarios with respect to fitness criteria using a sensitivity analysis.
It also supports the generation of hypotheses about chronic elevation of NF-κB and mTOR activities.
Therefore, our work establishes a novel extendable and scalable approach capable to connect tractable
molecular mechanisms and interventions with cellular network dynamics underlying aging and age-related
disease phenotypes.
[1] A. Kriete, W. Bosl, and G. Booker. Rule-based cell systems model of aging using feedback loop motifs
mediated by stress responses. PLoS Computational Biology, 6(6), 06 2010.
[2] A. Kriete, K. Mayo, N. Yalamanchili, W. Beggs, P. Bender, C. Kari, and U. Rodeck. Cell autonomous
expression of inflammatory genes in biologically aged fibroblasts associated with elevated NF-κB
activity. Immunity & Ageing, 5(1):5, 2008.
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Modelling and methods to control the field of activation for deep brain stimulation
Prof. Richard Bayford
(Middlesex University)
Abstract:
Despite the widely accepted clinical efficacy of deep brain stimulation (DBS), the underlying physiological mechanisms of this therapeutic tool have not yet been fully discovered. This has greatly limited
the development of more efficient and safer DBS systems, which, in turn, has not provided researchers
with better means to explore the effects of DBS. This presentation describes the development of methods
to model the electrical field in the human head and achieve better selectivity and electric field shifting during deep brain stimulation. Methods based on the use of a current-steering tripolar electrode
configuration, characterized by tunable ratio, α, between the anodic currents, combined with the use
of triangular current pulses are explored and illustrated. The result is to minimize the anodal break
excitation associated with fast decays of square pulses. finite element models were employed in order to
investigate the behavior of the electric fields generated with the tripolar electrode configuration. Physical
models where also developed to validate the electric field profiles and shifting capability of the adopted
tripolar configuration.
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Trends and developments in Deep Brain Stimulation for Parkinson's disease
Prof. Peter Tass
(Institute of Neuroscience and Medicine, Jülich)
Abstract:
A number of brain diseases, e.g. movement disorders such as Parkinson's disease, are characterized
by abnormal neuronal synchronization. Within the last years permanent high-frequency (HF) deep brain
stimulation became the standard therapy for medically refractory movement disorders. To overcome
limitations of standard HF deep brain stimulation, we use a model based approach. To this end, we
make mathematical models of affected neuronal target populations and use methods from statistical
physics and nonlinear dynamics to develop mild and efficient control techniques. Along the lines of a
top-down approach we test our control techniques in oscillator networks as well as neural networks. In
particular, we specifically utilize dynamical self-organization principles and plasticity rules. In this way,
coordinated reset (CR) stimulation [1], an effectively desynchronizing brain stimulation technique, has
been developed. The goal is not only to counteract pathological synchronization on a fast time scale,
but also to unlearn pathological synchrony by therapeutically reshaping neural networks [2]. I shall
present the theory, results from both experiments in MPTP monkeys and a first clinical application.
CR stimulation can also be applied non-invasively, e.g. as acoustic CR stimulation for the treatment of
tinnitus. The latter is characterized by abnormal delta band synchronization e.g. in the auditory cortex.
I shall present results from a single-blinded multicenter clinical trial in 63 patients.
[1] P. Tass. A model of desynchronization deep brain stimulation with a demand-controlled coordinated reset of neural subpopulations. Biological Cybernetics, 89:81-88, 2003.
[2] P. Tass and M. Majtanik. Long-term anti-kindling effects of desynchronizing brain stimulation: a
theoretical study. Biological Cybernetics, 94:58-66, 2006.
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Systems approaches to Parkinson's disease
Prof. Peter Wellstead
(NUI Maynooth)
Abstract:
The pathological mechanisms that determine the progress of Parkinson's disease are poorly understood, and the causes of the disease are unknown. In fact, evidence suggests that there is no unique cause,
and that disease progression involves multi-factorial interactions that will prove difficult to disentangle
with conventional neurobiological science. The aim of this symposium is to show how mathematical
modelling and dynamical systems analysis, combined with new neurological measurement and stimulation methods, offer novel ways of addressing the puzzle that is Parkinson's disease (PD). In this context,
the symposium speakers will present current research results on issues such as: (i) Systems approaches to
causation of PD and the selective vulnerability of specific brain areas. (ii) Mathematical modelling and
analysis of cellular mechanisms (such as aging) involved in PD pathologies. (iii) The electrophysiological properties of cells prominent in PD pathology. (iv) Analytical and therapeutic approaches to deep
brain stimulation. (v) Modelling and analysis of signalling circuit associated with vulnerable dopaminergic neurons. (vi) In-vivo real-time measurement of extracellular neurochemistry relevant in neurological
disorders[4].
As an introduction to the systems approach to PD, this talk will also describe an analysis of Parkinson's
disease based upon the distribution and use of energy within the brain [3]. Specifically, an integrative
mathematical model of the brain energy metabolism has been developed [1] as a framework for the in-silico
visualisation and mathematical analysis of factors thought to be involved in PD. The energy metabolism
model is modular and expandable, such that models of the cellular structures [2] and various mechanisms
associated with PD can be attached and studied. This enables the impact of, and the interactions between,
various etiopathological mechanisms to be studied rapidly and repeatably in a standard computational
environment (Matlab and CellML).
The brain energy metabolism model also allows the role of multi-factorial energy deficits in PD to
be studied [4]. Specifically, we posit that cumulative energy deficits from a number of sources create a
predisposition to PD. Using the brain energy metabolism model as an investigative tool, the role of energy
deficits induced by combinations of factors (aging, toxins and head trauma) is simulated in-silico. The
simulation results suggest long-term accumulation of transient energy deficits from a variety of factors as
a trigger mechanism for the onset of PD. Such long term multi-factorial energy deficits will be particularly
damaging to neurons preferentially vulnerable to Parkinsonian damage; e.g. dopaminergic neurons with
high energy budgets.
[1] M. Cloutier, F. Bolger, J. Lowry, and P. Wellstead. An integrative dynamical model of brain energy metabolism using in-vivo neurochemical measurements. Journal of Computational Neuroscience,
27(3):391-414, 2009.
[2] M. Cloutier and P. Wellstead. The control system structures of energy metabolism. Journal of the
Royal Society Interface, (7):651-665, 2010.
[3] P. Wellstead. Systems biology and the spirit of tustin. IEEE Control Systems Magazine, 30(1):57-102,
2010.
[4] P. Wellstead and M. Cloutier. An energy systems approach to parkinson's disease. WIREs Systems
Biology and Medicine, 2010.
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