A systems biological approach to Parkinson's disease

Parkinson’s Disease (PD) is the second most common neurodegenerative disorder with an average prevalence of approximately 0.3%, with numbers rising as populations age (1%/4% prevalence for over 60/80 year olds respectively). Initial symptoms feature disorders in motor functions followed by non-motor symptoms such as depression, amongst others. The major characteristic of the disease is the degeneration of dopaminergic neurons. Nevertheless the underlying mechanisms cannot yet be fully explained. Various molecular approaches identified key genes/proteins involved e.g. LRRK2, SNCA and PARK7. This suite of implicated genes spans 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 in particular, the differences between causal and symptomic pathways are 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 developed a protein-protein interaction model describing all proteins implicated in PD. The candidate protein list is based on literature and the latest human genetics studies data (hand-curated). Molecular interactions have been retrieved from public databases (Hippie, Intact, etc.). The network’s community structure was obtained by applying clustering techniques (Newman, 2006). As expected, we find many PD proteins associated with presynaptic compartments. However we can see specific enrichment in subsets of proteins associated with synaptic vesicle cycling and other subsets more closely associated with post-synaptic complexes in glutamatergic neurons each of which may represent different mechanisms involved in the disease pathology.
REFERENCES: Parkinson Disease: from pathology to molecular disease mechanisms, Dexter D, et al., (2013), Free Radical Bio Med, 62, 132 Modularity and community structure in networks, Newman M, (2006), PNAS, 103, 8577