Time for a change in the research paradigm for Alzheimer's disease: the value of a chaotic matrix modeling approach

Abstract

The amyloid cascade hypothesis, based on the genetic data from early onset, familial forms of the disease, has been the dominant model for many years and involves over production and deposition of the beta amyloid protein as causal in the disease process. However, it does not apply very well to the more common, later onset, sporadic form of the disease, where a wider range of factors appear to be involved in disease progression. Over recent years, data illustrating reciprocal interactions between the amyloid precursor protein (APP) and its various metabolites with many factors involved in normal synaptic plasticity have emerged. These feedback relationships have the potential to affect the complex kinase cascades involved in every aspect of neuronal function. Further, data regarding the multiple roles of the presenilins have the potential to allow the over expression and deposition of the amyloid beta protein to be both a cause and consequence of disease progression, with relevance in both sporadic and familial of Alzheimer's disease (AD). Disease progression might be better explained by a chaotic matrix of factors and raises the question again whether AD should be approached as a single entity or as a syndrome, with important consequences for disease identification and treatment.

Figure 1

Model of disease progression based on decoherence in flow of biological information through the matrix of factors underlying synaptic plasticity.