Dissertation
A local accumulation connected spread model of neurofibrillary tangle propagation in the human neocortex
Doctor of Philosophy (Ph.D.), Drexel University
28 Sep 2021
DOI:
https://doi.org/10.17918/00000531
Abstract
The objective of this work was to develop a biophysical model that would elucidate the role of the brain neurofibrillary tangles (NFTs) play in the development of Alzheimer's disease (AD). AD is a devastating neurodegenerative disease, and this study [the study of Ian] is not only of substantial societal impact, but it will also contribute to the multidisciplinary efforts aimed at early detection, understanding factors behind disease progression and possibly personalized treatment of the disease. AD affects approximately 6.2 million Americans and is expected to grow exponentially by 2050 as the population ages. Those with AD required 15.3 billion hours of care, most of which is unpaid care from family members, and costs, on average, $321,780 per person. Current hypotheses on the mechanism of AD incorporate the combined role of two proteins: beta amyloid plaques and NFTs. They are hypothesized to work together in the amyloid cascade hypothesis to bring about the toxic effects of disease. The tau protein normally stabilizes microtubules in the central nervous system, but its phosphorylation causes destabilization and the formation of tangles. The direct cause of this phosphorylation is unknown, but amyloid plaques are believed to play a role. These tangles disrupt neuron function and synaptic communication. Unable to communicate, these cells die. The tangles propagate via synapticsynaptic connections, resulting in neuronal dysfunction, eventually cell death and thus regional atrophy which follows the pattern of NFTs. Cognitive decline increases as the disease worsens, generally thought to correlate with increasing spread of NFTs. Currently, AD is only able to be definitively diagnosed at autopsy, complicating the understanding of the disease and validation of therapeutic clinical trials. The advent of amyloid- and tau-specific PET tracers in conjunction with other imaging biomarkers has led to a hypothetical model of the progression of AD. However, the mechanism of propagation of disease is still not well defined. Quantitative and qualitative descriptions of the accumulation and advancement of NFTs throughout the cerebrum from both in vitro pathologic staining and in vivo flortaucipir NFT PET imaging characterizes the propagation of NFTs by increasing local intensity and increasing spatial extent. Here we describe a local accumulation connected spread (LACS) model of NFT propagation which naturally encompasses the intensity-extent phenomenon through a reaction-diffusion equation wherein the molecular mechanisms leading to tau accumulation in neurons represents the reaction and the expansion of tau with increasing disease stage along connected white matter trajectories is considered as a diffusion process. We explored three objectives to better understand the utility of the LACS model in predicting future NFT burden as represented by flortaucipir PET. First, we examined confounding factors inherent to flortaucipir PET and their effects on flortaucipir quantitation. Second, we generated a whole brain connectome to model the diffusion process and related harmonics of the connectome to flortaucipir uptake to understand concordance between connectivity and NFT burden. Third, we estimated parameters for LACS using Bayesian inversion to incorporate the uncertainties inherent to flortaucipir quantitation and the LACS model itself and predicted future NFT burden in a clinical trial population. The application of LACS modeling may provide insight into the accumulation and propagation of NFTs as represented by flortaucipir (FTP) PET throughout the cerebrum as well as the development of novel, tailored endpoints for AD therapeutic trials.
Metrics
46 File views/ downloads
43 Record Views
Details
- Title
- A local accumulation connected spread model of neurofibrillary tangle propagation in the human neocortex
- Creators
- Ian Andrew Kennedy - Drexel University, School of Biomedical Engineering, Science, and Health Systems
- Contributors
- Michael D. Devous (Advisor)Andres Kriete (Advisor) - Drexel University, School of Biomedical Engineering, Science, and Health Systems
- Awarding Institution
- Drexel University
- Degree Awarded
- Doctor of Philosophy (Ph.D.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- xiv, 58 pages
- Resource Type
- Dissertation
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems (1997-2026); Drexel University
- Other Identifier
- 991015606267404721