Recordings of a number of sessions from the 1st Symposium on Systems Approaches to Parkinson's Disease.
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Introductory Remarks
Prof. Peter Wellstead
The Hamilton Institute, NUI Maynooth Show abstract »Welcome to the Symposium on Systems Approaches to Parkinson’s Disease, organised in conjunction with the 3rd International Workshop on Systems Biology.
Neurodegenerative diseases of age, such as Parkinson’s disease, pose a huge social and economic challenge to health care in Western societies. As life expectancy increases, the human and social costs will grow and potentially overwhelm our capacity to care for the elderly. Despite the enormity of this problem, the causes of many neurodegenerative diseases of age, such as Parkinson’s, are unknown and there are no cures.
There is however a hope that we can increase our understanding of Parkinson’s disease, and related conditions, using Systems Biology methods that are specifically aimed at the disease causes, pathologies and treatments. To this end the Symposium brings together a panel of international experts who are applying their expertise to understanding Parkinson’s disease from a range of systems perspectives that include, amongst others, Deep Brain Stimulation, electrochemical signalling, in-vivo/in-vitro neurochemical sensing, mathematical modelling and dynamical systems analysis.
The symposium organising committee extends a warm welcome to both speakers and delegates for what we are sure will be a stimulating event.
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Symposium Official Opening and Remarks
Mr. Michael Kelly
Trustee Board, Hilde Ulrichs Foundation Parkinson Research -
Systems approaches to Parkinson's disease
Prof. Peter Wellstead
The Hamilton Institute, NUI Maynooth Show 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.
Bibliography
[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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Closing the loop on Parkinson's disease etiology: a modelling study of the feedback between protein and oxidative metabolisms
Dr. Mathieu Cloutier
Chemical Engineering, École Polytechnique de Montréal Show abstract »Except for a small percentage of genetic cases, the causes of Parkinson’s disease are unknown. However, 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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Physiological and anatomical properties of dopamine neurons: clues to differential susceptibility in Parkinson's disease
Prof. J. Paul Bolam
MRC Anatomical Neuropharmacology Unit, Department of Pharmacology, University of Oxford Show 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.
Bibliography
[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. -
A whole cell model of calcium homeostasis in dopaminergic substantia nigra neurons
Dr. Míriam R. García
The Hamilton Institute, NUI Maynooth Show 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 combines mitochondria stress, production of reactive oxygen species and misfolding of α-synuclein with 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. ‘Re- juvenation’ protects neurons in mouse models of Parkinson’s disease. Nature, 447(7148):1081–1086, 2007.
Bibliography
[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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Cell Systems Modelling of Aging Phenotypes using Fuzzy Logic
Prof. Andres Kriete
Biomedical Engineering, Drexel University Show 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 pro- cess are NF-κB and mTOR. For instance, cells from older humans demonstrate higher NF-kB DNA binding activity accompanied by an inflammatory gene expression profile [2]. While the role of NF-kB 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 investi- gations 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 re- sponse 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 consider- ation 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.
Bibliography
[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-kappab activity. Immunity & Ageing, 5(1):5, 2008.
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Modelling and measurement of cerebral signalling circuits
Mr. Guilluame Drion
Department of EE & CS, University of Liège Show 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 ap- plications 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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An approach for the study of energy regulated pathway in Parkinson's disease: an experimental platform and a model
Prof. Mario Jolicœur
Chemical Engineering, École Polytechnique de Montréal Show 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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