Mathematical modeling of APP processing influenced by SORLA in Alzheimer's disease: Two pilot models

Angelyn R. Lao

College

College of Science

Department/Unit

Mathematics and Statistics Department

Document Type

Report

Publication Date

2010

Abstract

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by amyloid plaques in the brain of affected individuals. This project aims at modeling of neurodegenerative processes in AD.· Our study focuses on the interactome of neuronal factors central to the proteolytic processing of amyloid precursor protein (APP) into Aβ, the main constituent of senile plaques. Factors considered in this model include proteases, trafficking adaptors, as well as a novel sorting receptor SORLA. Here, we have generated a panel of cell lines in which the amount of APP and of accessory factors can be varied. These novel cell lines are important research tools that have since been applied to produce quantitative data. The quantitative dose-response series have been used to estimate reaction constants of mathematical models describing APP processing. We have established nonlinear ordinary differential equation models describing the cleavage of APP by alpha and beta secretases, and the influence of SORLA herein. We have queried different mathematical models concerning the interactions with SORLA and we have simplified the models based on justifiable steady state approximations. For the resulting algebraic models, we have estimated the model parameters from the dose-response curves by nonlinear optimization methods. These results provide the bases for further modeling of neurodegenerative processes and for determination of individual risk of AD.

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Disciplines

Mathematics

Keywords

Amyloid beta-protein precursor—Mathematical models; Alzheimer's disease

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