Dissertation/Thesis Abstract

Mathematical Models for the Etiology of Schizophrenia and White Matter Lesions
by Corbitt, Paul Timothy, Ph.D., University of Maryland, Baltimore County, 2014, 358; 3624344
Abstract (Summary)

The thesis consists of two projects. The first project uses mathematical models from nuclear physics to explore epidemiological data related to schizophrenia. These models improve the state of the art understanding of the biological etiology of schizophrenia, suggesting that regular internal biological events are responsible for disease development. The schizophrenia project develops two families of mathematical models that describe the course of schizophrenia. First, the models are applied to schizophrenia prevalence data for different populations. Parameters from these models are analyzed for trends relating to the parameters. The parameters are used to simulate datasets showing the relationship of the models back to the observed parameters. These models from theoretical physics can explain monozygotic twin discordance in schizophrenia. The second project explores white matter lesions in a Mexican-American population across the adult lifespan. A novel mathematical model is created to relate white matter lesion development to aging, diabetes, and hypertension. The white matter lesion project examined real data from a Mexican-American population. The model revealed that diabetes, hypertension, and age are strongly associated with the development of white matter lesions. The data revealed a transition from lower volume, number, and average volume of lesions in the 36-45 to 46-55 decades of life. The novel mathematical model uses a logistic differential equation and elements of probability theory to recreate the data. Further analysis of the model showed that it not only fit the Mexican-American data, but also fit data related to the Austrian Stroke Prevention Study. It made predictions about the effects of diabetes and hypertension in a simulated Mexican-American population. The totality of the projects show that physics is a fertile ground for developing physically based mathematical models that can be applied to diverse problems relating to medicine. Potential extensions to this work will also be discussed.

Indexing (document details)
Advisor: Kramer, Ivan
Commitee: Martins, Vanderlei, Rada, Roy, Tagamets, Malle A., Takacs, Laszlo
School: University of Maryland, Baltimore County
Department: Physics, Applied
School Location: United States -- Maryland
Source: DAI-B 75/10(E), Dissertation Abstracts International
Subjects: Mental health, Theoretical physics, Epidemiology
Keywords: Applied probability, Epidemiological models, Leukoaraiosis, Mathematical modeling, Physics, Schizophrenia
Publication Number: 3624344
ISBN: 978-1-303-97613-1
Copyright © 2020 ProQuest LLC. All rights reserved. Terms and Conditions Privacy Policy Cookie Policy