Understanding the Influence of Individual-level Sources of Pathology Variation on Neuroimaging Measures of Alzheimer Disease
Date of Award
Doctor of Philosophy (PhD)
The overall goal of this dissertation is to gain a better understanding of how current Alzheimer disease pathologic progression models interact with sources of individual-level variation in pathology to influence overall disease progression in a clinically meaningful way. Many sources of variation, both internal (e.g., genetic mutations, heterogeneity of tau pathology) and external (e.g., diet and exercise, sleep quality), are known to influence disease progression and symptom onset in AD. With the advent of therapies that have shown successful reduction of amyloid load in trials and the rapid progression of anti-tau therapies, we hypothesize that a better understanding of how these sources of pathology variation interact with and modify the pathological cascade will allow future studies to appropriately take these factors into account and assist in clinical decision making when it comes to therapeutic treatment of Alzheimer disease. In chapter 2 we examine the concurrent influences of tau and Aβ pathology and separate the influences of each pathology on grey matter structural integrity. We show that tau pathology is highly correlated with antecedent longitudinal change in cortical thickness and is likely the driving force behind both tau and Aβ correlations with cortical thickness loss in prior work. The higher levels of heterogeneity in tau pathology between individuals compared to diffuse cortical Aβ pathology suggests greater room for individual pathology trajectory differences to arise. In chapter 3 we show that the important external factors of sleep quality and BMI levels have profound influence on AD pathological development at an individual level and suggest that further work is needed to integrate the effects of these disease modifying factors into disease modeling strategies. In chapter 4 we highlight the difficulties in accounting for sources of individual pathology variations in current longitudinal disease modeling strategies and propose a new methodology for making individual-level disease progression predictions while accounting for these sources of individual pathology variations. In chapter 5 we show that effectiveness of an anti-amyloid therapy varies largely, but not solely, with how much Aβ pathology is present within an individual or region and suggest that regional levels of different Aβ plaque conformations may influence results.
Chair and Committee
Tammie LS Benzinger
McCullough, Austin Andrew, "Understanding the Influence of Individual-level Sources of Pathology Variation on Neuroimaging Measures of Alzheimer Disease" (2022). Arts & Sciences Electronic Theses and Dissertations. 2681.