Misfolding and aggregation of proteins are common phenomena within the cell. Under normal circumstances the quality control mechanisms of the cell are able to refold and if needed, degrade, these potentially pathological species. A range of factors, and in particular ageing, can affect these so called ‘proteostatic’ mechanisms. Indeed, perturbations of proteostasis and the accumulation of misfolded proteins are central to the pathogenesis of many human and animal disorders, including Alzheimer’s and Parkinson’s diseases (AD and PD), Amyotrophic Lateral Sclerosis (ALS). It is becoming increasingly clear that a paradigm shift in the study of these diseases is needed in order to understand their complexity. These disorders cannot be described simply by a linear cascade of events (a unique pathway). Indeed, in the case of Alzheimer’s disease, the multitude of effector pathways published to date strongly argues against the single pathway view. More likely, the disease results from a complex network of interactions between multiple sub-cellular pathways. This conclusion has two implications. First, if there are multiple pathways, the complexity and probable heterogeneity of the problem will require novel approaches to dissect out these pathways and, second, any rational effort to control the disease process will require detailed knowledge of the pathways and their regulation.
The focus of my research is to build and analyze the network of pathways associated with Alzheimer’s disease. I am part of a large Alzheimer’s disease consortium, which includes groups from Cambridge, Bristol, Hamburg and Toronto and integrates tools from physics, chemistry, engineering, systems biology and neurobiology. Through this consortium we have access to experimental data that we use, in conjunction with freely available databases, to build the network of disease associated genetic pathways. As many genes are differentially expressed at different ages, it is crucial to study the temporal evolution of such a network, or, in other words, how the cascade of events that leads from the healthy to the diseased state changes with time and with the age of the organism.
The power of such a network/system approach is that we will be able to verify a large number of hypothesis regarding the downstream pathways of AD, not only the ones in which a single effector pathway is present, but, importantly, the ones in which several (even very distinct) pathways contribute to the disease. The ultimate aim of this research is to build a recursive approach, in which the predictions from the theoretical model can be used to design new sets of experiments whose results can be used to refine the model and obtain a new set of more accurate predictions.
We have just released esyN.org an easy to use network making tool.
Lab members: Daniel Bean, Yao Lian, Lorenzo Ficorella
1. G. Favrin, D. M. Bean, E. Bilsland, H. Boyer, B. E. Fischer, S. Russell, D. C. Crowther, H. A. Baylis, S. G. Oliver & M. E. Giannakou. (2013) Identification of novel modifiers of Aβ toxicity by transcriptomic analysis in the fruitfly. Scientific Reports 3 : 3512
2. Bolognesi B, Kumita JR, Barros TP, Esbjorner EK, Luheshi LM, Crowther DC, Wilson MR, Dobson CM, Favrin G, Yerbury JJ. (2010) ANS binding reveals common features of cytotoxic amyloid species. ACS Chem Biol. 5(8):735-40.
3. Cheon M, Chang I, Mohanty S, Luheshi LM, Dobson CM, Vendruscolo M, Favrin G. (2007) Structural reorganisation and potential toxicity of oligomeric species formed during the assembly of amyloid fibrils. PLoS Computational Biology Vol. 3 , No. 9, e173