Stability analysis of the ODE model representation of amyloidogenic processing in Alzheimer's disease in the presence of SORLA.

The proteolytic breakdown of the amyloid precursor protein (APP) by secretases is a complex cellular process that results in the formation of neurotoxic Aβ peptides, causative of neurodegeneration in Alzheimer's disease (AD). Processing involves monomeric and dimeric forms of APP that are transported through distinct cellular compartments where the various secretases reside. Amyloidogenic processing is also influenced by modifiers such as sorting receptor-related protein (SORLA), an inhibitor of APP breakdown and a major AD risk factor. This paper analyzed the temporal behavior of a mathematical model describing APP processing under the influence of SORLA, by performing a stability analysis of the mathematical model. We found one biochemically meaningful equilibrium point ξ. By means of linearization, Hartman-Grobman theorem, and Routh-Hurwitz test, it was shown that ξ is a locally asymptotically stable equilibrium point. The region of attraction of ξ was approximated by using the fluctuation lemma. An immediate consequence of the stability analysis of the reduced system to the temporal behavior of the solutions of the original system was also obtained. The biological implications of these results for the dynamic behavior of the activity of APP and secretases under SORLA's influence were established.

[1]  T. Willnow,et al.  Lipoprotein receptors in Alzheimer's disease , 2006, Trends in Neurosciences.

[2]  C. Masters,et al.  Amyloid-β Peptide (Aβ) Neurotoxicity Is Modulated by the Rate of Peptide Aggregation: Aβ Dimers and Trimers Correlate with Neurotoxicity , 2008, The Journal of Neuroscience.

[3]  D. Selkoe,et al.  Soluble protein oligomers in neurodegeneration: lessons from the Alzheimer's amyloid β-peptide , 2007, Nature Reviews Molecular Cell Biology.

[4]  Jean-Pierre Gabriel,et al.  Differential equation models of some parasitic infections: Methods for the study of asymptotic behavior , 1985 .

[5]  Angelyn R. Lao,et al.  Quantitative modelling of amyloidogenic processing and its influence by SORLA in Alzheimer's disease , 2012, The EMBO journal.

[6]  James D. Murray Mathematical Biology: I. An Introduction , 2007 .

[7]  S. Wiggins Introduction to Applied Nonlinear Dynamical Systems and Chaos , 1989 .

[8]  B. Hyman,et al.  Neuronal sorting protein-related receptor sorLA/LR11 regulates processing of the amyloid precursor protein. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[9]  N. Rashevsky,et al.  Mathematical biology , 1961, Connecticut medicine.

[10]  J. Hardy,et al.  The Amyloid Hypothesis of Alzheimer ’ s Disease : Progress and Problems on the Road to Therapeutics , 2009 .

[11]  Olaf Wolkenhauer,et al.  Multi-compartmental modeling of SORLA’s influence on amyloidogenic processing in Alzheimer’s disease , 2012, BMC Systems Biology.

[12]  John Hardy,et al.  The amyloid hypothesis for Alzheimer’s disease: a critical reappraisal , 2009, Journal of neurochemistry.

[13]  S. Bhat,et al.  Modeling and analysis of mass-action kinetics , 2009, IEEE Control Systems.