Mechanistic modeling of pathological biomarkers to study Alzheimer’s disease progression

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dc.contributor.advisorIgoshin, Olegen_US
dc.contributor.advisorCristini, Vittorioen_US
dc.creatorPeláez Soní, María Joséen_US
dc.date.accessioned2021-05-03T21:52:37Zen_US
dc.date.available2023-05-01T05:01:14Zen_US
dc.date.created2021-05en_US
dc.date.issued2021-04-19en_US
dc.date.submittedMay 2021en_US
dc.date.updated2021-05-03T21:52:37Zen_US
dc.description.abstractAlzheimer’s disease (AD) is one of the leading causes of death in the United States. It is a neurodegenerative disorder that affects cognitive abilities, characterized by deterioration of the brain tissue due to synaptic loss caused by the abnormal accumulation of amyloid-β (Aβ) peptide and hyperphosphorylated tau proteins, leading to the formation of senile plaques and neurofibrillary tangles, respectively. Mathematical models based on AD biomarkers can be used as a tool to estimate disease progression kinetics, make disease prognosis, determine novel treatment strategies, and develop patient-specific treatment regimens. In this thesis, I developed a novel kinetic model, formulated as a system of differential equations, and a dynamic network diffusion model to characterize the spatiotemporal evolution of pathological biomarkers during AD progression. The kinetic model was calibrated with the ADNI database and simulated the temporal evolution of the five variables of the model: CSF tau, CSF phosphorylated tau, neuronal activity, CSF soluble Aβ, and Aβ plaques. Additionally, parametric analysis of the model highlighted key parameters responsible for disease progression, which hold the potential to design new treatment strategies.en_US
dc.embargo.terms2023-05-01en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationPeláez Soní, María José. "Mechanistic modeling of pathological biomarkers to study Alzheimer’s disease progression." (2021) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/110448">https://hdl.handle.net/1911/110448</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/110448en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectAlzheimer's diseaseen_US
dc.subjectKinetic modelen_US
dc.subjectNetwork modelen_US
dc.titleMechanistic modeling of pathological biomarkers to study Alzheimer’s disease progressionen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentApplied Physicsen_US
thesis.degree.disciplineNatural Sciencesen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.majorMathematics in Medicineen_US
thesis.degree.nameMaster of Scienceen_US
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