A Network-Based Study of the Dynamics of Aβ and τ Proteins in Alzheimer’s Disease

Due to the extreme complexity of Alzheimer’s disease (AD), the etiology of which is not yet known, and for which there are no known effective treatments, mathematical modeling can be very useful. Indeed, mathematical models, if deemed reliable, can be used to test medical hypotheses that could be difficult to verify directly. In this context, it is important to understand how Aβ and τ proteins, which, in abnormal aggregate conformations, are hallmarks of the disease, interact and spread. We are particularly interested, in this paper, in studying the spreading of misfolded τ. To this end, we present four different mathematical models, all on networks on which the protein evolves. The models differ in both the choice of network and diffusion operator. Through comparison with clinical data on τ concentration, which we carefully obtained with multimodal analysis techniques, we show that some models are more adequate than others to simulate the dynamics of the protein. This type of study may suggest that, when it comes to modeling certain pathologies, the choice of the mathematical setting must be made with great care if comparison with clinical data is considered decisive.

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Publication Details

Journal
Mathematical and Computational Applications
Published
2024-12-04
DOI
https://doi.org/10.3390/mca29060113
Citations
1
Primary Topic
Alzheimer's disease research and treatments
Type
article
Field-Weighted Citation Impact
0.33

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article

A Network-Based Study of the Dynamics of Aβ and τ Proteins in Alzheimer’s Disease

Maria Carla Tesi, Germana Landi, Claudia M. Testa, S. Bianchi et al.
1 citations
Mathematical and Computational Applications
Alzheimer's disease research and treatments
0.33
article

A Network-Based Study of the Dynamics of Aβ and τ Proteins in Alzheimer’s Disease

Maria Carla Tesi, Germana Landi, Claudia M. Testa, S. Bianchi, Camilla Marella
article en
1 citations

Abstract

Due to the extreme complexity of Alzheimer’s disease (AD), the etiology of which is not yet known, and for which there are no known effective treatments, mathematical modeling can be very useful. Indeed, mathematical models, if deemed reliable, can be used to test medical hypotheses that could be difficult to verify directly. In this context, it is important to understand how Aβ and τ proteins, which, in abnormal aggregate conformations, are hallmarks of the disease, interact and spread. We are particularly interested, in this paper, in studying the spreading of misfolded τ. To this end, we present four different mathematical models, all on networks on which the protein evolves. The models differ in both the choice of network and diffusion operator. Through comparison with clinical data on τ concentration, which we carefully obtained with multimodal analysis techniques, we show that some models are more adequate than others to simulate the dynamics of the protein. This type of study may suggest that, when it comes to modeling certain pathologies, the choice of the mathematical setting must be made with great care if comparison with clinical data is considered decisive.

Mathematical and Computational ApplicationsVol. 29(6)
University of Bologna (IT)
U.S. Department of Defense, Alzheimer's Association, Bristol-Myers Squibb, Eli Lilly and Company, Pfizer, Biogen, University of Southern California, Meso Scale Diagnostics, Alzheimer's Disease Neuroimaging Initiative, BioClinica, Novartis Pharmaceuticals Corporation, Northern California Institute for Research and Education, Eisai, Università di Bologna, Servier, H. Lundbeck A/S, National Institutes of Health, Canadian Institutes of Health Research
Openalex Percentile: Top 35%
Alzheimer's disease research and treatments
0.33
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