Date Available

8-2-2023

Year of Publication

2023

Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation

College

Public Health

Department/School/Program

Epidemiology and Biostatistics

First Advisor

Dr. Richard Charnigo

Abstract

In this series of studies, we examined the potential of a variety of blood-based plasma biomarkers for the identification of Alzheimer's disease (AD) progression and cognitive decline. With the end goal of studying these biomarkers via mixture modeling, we began with a literature review of the methodology. An examination of the biomarkers with demographics and other health factors found evidence of minimal risk of confounding along the causal pathway from biomarkers to cognitive performance. Further study examined the usefulness of linear combinations of biomarkers, achieved via partial least squares (PLS) analysis, as predictors of various cognitive assessment scores and clinical cognitive diagnosis. The identified biomarker linear combinations were not effective at predicting cognitive outcomes. The final study of our biomarkers utilized mixture modeling through the extension of group-based trajectory modeling (GBTM). We modeled five biomarkers, covering a range of functions within the body, to identify distinct trajectories over time. Final models showed statistically significant differences in baseline risk factors and cognitive assessments between developmental trajectories of the biomarker outcomes. This course of study has added valuable information to the field of plasma biomarker research in relation to Alzheimer’s disease and cognitive decline.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2023.325

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