Abstract

Introduction: Alzheimer’s Disease (AD) remains among the top 10 causes of death in the United States and is projected to affect nearly 14 million people by 2050. To this point, studies of Alzheimer’s genetics and endophenotypes have yielded a bounty of results that culminated in the first disease-modifying drugs, lecanemab and donanemab, in 2022. Most of the genetic studies for Alzheimer’s disease to date have been focused on late-onset AD or Autosomal dominant AD, leaving a critical need for studying sporadic early-onset AD (EOAD; ~10% of cases). Furthermore, the demand for clinical portability has created a need for high-sensitivity proteomic assays for plasma biomarker analysis. I aim to use some of the latest biomarker assays and age at onset (AAO) as endophenotypes in a genome-wide association study framework (GWAS) to uncover the genetics underlying AD and their biological implications. Broadly, I aim to answer the following question: how can genetic studies contribute further to our understanding of AD biology? Methods: In my first aim, I perform genetic analyses on concentrations of plasma amyloid-β peptides Aβ40 (n=1,467) and Aβ42 (n=1,484), Aβ42/40 (n=1,467), total tau (n=504), tau phosphorylated (p-tau181; n=1,079), and neurofilament light (NfL; n=2,058). GWAS and gene-based analysis were used to identify single variants and genes associated with plasma levels. Finally, polygenic risk score and summary statistics were used to investigate overlapping genetic architecture between plasma biomarkers, CSF biomarkers, and AD risk. In my second aim, I performed a multi-ancestry (non-Hispanic European, African, and East Asian) genome-wide association study (GWAS) including a total of 7,349 cases and 17,887 controls. Cases with an age of onset younger than 70 years were included. Sensitivity analysis, including cases with onset ≤65, was performed. Only controls older than 70 were included to decrease the risk of developing LOAD. Results: In my first aim, I found a total of six genome-wide significant signals. APOE was associated with plasma Aβ42, Aβ42/40, tau, p-tau181, and NfL. I proposed ten candidate functional genes based on 12 SNP-biomarker pairs and brain differential gene expression analysis. I found a significant genetic overlap between CSF and plasma biomarkers. I also demonstrate that it is possible to improve the specificity and sensitivity of these biomarkers when genetic variants regulating protein levels are included in the model. In my second aim, I identified eight novel significant loci: six in the ancestry-specific analyses and two in the trans-ancestry analysis. By integrating gene-based analysis, eQTL, pQTL, and functional annotations, I nominate eight novel genes that are involved in microglia activation, glutamate production, and signaling pathways. Discussion: I set out my aims with the goal of addressing my driving research question, “How can genetic studies contribute further to our understanding of AD biology?” Taking these results together and in the context of other researchers, this work has demonstrated that using age at onset and biomarker endophenotypes captures disease-relevant findings, such as elucidating the potentially key role of glutamate and synaptic homeostasis proteins in disease biology, especially affecting tau and neurodegeneration phenotypes.

Committee Chair

Nancy Saccone

Committee Members

John Rice

Degree

Doctor of Philosophy (PhD)

Author's Department

Biology & Biomedical Sciences (Human & Statistical Genetics)

Author's School

Graduate School of Arts and Sciences

Document Type

Dissertation

Date of Award

12-31-2025

Language

English (en)

Author's ORCID

0000-0003-0217-4808

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