A Systems Biological Approach to Parkinson's Disease

Research output: Contribution to conferencePosterpeer-review

Abstract / Description of output

Parkinson’s Disease (PD) is the second most common neurodegenerative disorder in industrialized countries. Its average prevalence is approximately 0.3%, with numbers rising as populations age (1% prevalence for over 60 year olds). Initial symptoms feature disorders in motor function followed by non-motor symptoms such as depression, amongst others.

Various molecular approaches have been taken to gain further understanding of the disease phenotype. In line with this, different studies have identified key genes/proteins involved e.g. LRRK2, SNCA, PARK. The suite of implicated genes seems to be linked to multiple functional pathways, explaining the complexity of the disease. Oxidative stress, altered mitochondrial, proteasomal and lysosomal function, inflammatory changes and excitotoxicity all play a role in the disease and its pathology (Dexter, 2013). Nevertheless the whole picture is far from being understood.

Systems biology provides a unique view of complex biological systems and gives a framework for integrating available experimental data. Several modelling approaches have been taken with respect to PD, mainly focusing on the impaired dopamine metabolism. However, few current models, give insights into molecular mechanisms of the disease.

We have started the generation of a static model focussing on a full interaction map of proteins involved in PD. The candidate protein list is based on literature and the latest GWAS data. Molecular interactions have been retrieved from public databases (Hippie, Intact, etc.). The network’s community structure was obtained by applying clustering techniques (Newman, 2006). We find clusters enriched with pre- and post-synaptic proteins, each of which may correspond to different mechanistic aspects of PD. The main known PD proteins appear to be located in a presynaptic compartment, and in particular in specific subsets associated with synaptic vesicle cycling.

Our aims are now to use richer systems biology modelling methods, such as dynamic and rule based approaches (Sekar, 2012) to analyse how these proteins might interact with one another and known signalling pathways to better understand the disease mechanism.

Parkinson Disease: from pathology to molecular disease mechanisms, Dexter D, et al., (2013), Free Radical Bio Med, 62, 132
Rule-Based Modeling of Signal Transduction: A Primer, Sekar J, et al., (2012), Methods Mol Biol, 880, 139
Modularity and community structure in networks, Newman M, (2006), PNAS, 103, 8577
Original languageEnglish
Publication statusPublished - 2014
EventSysBio2014: Advanced Lecture Course on Systems Biology - Innsbruck, Austria
Duration: 2 Mar 20148 Mar 2014


WorkshopSysBio2014: Advanced Lecture Course on Systems Biology


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