Generating Predictive Gene Expression Signatures for Alzheimer's Disease Using Postmortem Brain Tissue

Author

Ashley Duche, Chapman UniversityFollow

Date of Award

Fall 12-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Pharmaceutical Sciences

First Advisor

Moom R. Roosan

Second Advisor

Rachita Sumbria

Third Advisor

Rennolds Ostrom

Fourth Advisor

Ajay Sharma

Abstract

Background: Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder characterized by the accumulation of amyloid-beta (Aβ) plaques and tau protein aggregates. These pathological features develop in specific brain regions, but why some areas are more vulnerable to early AD-related changes remains unclear. To address this, predictive gene expression signatures were developed to explore the molecular mechanisms underlying regional susceptibility to AD pathology.

Methods: This was performed using postmortem brain (PMB) tissue from participants in the Religious Orders Study and Memory and Aging Project (ROSMAP), Mayo Clinic, and Mount Sinai Brain Bank (MSBB) to generate gene expression signatures from six brain regions affected at different stages of AD. These regions included the temporal and frontal lobes, as well as the cerebellum in which differential gene expression analysis identified genes with altered expression patterns. Next, gene expression signatures were developed using the Adaptive Signature Selection and InteGratioN (ASSIGN) toolkit to predict AD activity. These predictions were validated against established neuropathological clinical markers, cognitive assessments, and clinical diagnoses. Dysregulation of key biological pathways was then analyzed using g:Profiler and ClueGO while genetic and sociodemographic factors influence on AD pathology was assessed and drug repurposing candidates were identified using the Connectivity Map (CMAP).

Results: As a result of this analysis, predictive gene expression signatures from six AD-affected brain regions were developed with the ability to distinguish AD activity in control and AD PMB tissue, correlating with clinical disease markers. These signatures revealed common mechanisms underlying regional vulnerability, including upregulation of extracellular matrix (ECM)-related processes and downregulation of hormonal signaling pathways. Notably, upregulation of S100A4 was revealed across all regions, while CRH was downregulated in all but the cerebellum. Additionally, apolipoprotein E (APOE) genotype e3/e4 and male sex influenced disease progression while drug repurposing analysis identified FGFR inhibitors, specifically orantinib, and bromodomain inhibitors as promising therapeutic candidates.

Conclusion: In all, this study highlights molecular signatures associated with regional vulnerability to AD and provides an understanding of genetic and systemic factors influencing disease progression. Key molecular pathways, including ECM-related processes and hormonal regulation, play critical roles in AD susceptibility. The identified drug repurposing candidates offer potential therapeutic avenues for further investigation.

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Recommended Citation

Duche, A. Generating Predictive Gene Expression Signatures for Alzheimer's Disease Using Postmortem Brain Tissue. [dissertation]. Irvine, CA: Chapman University; 2025. https://doi.org/10.36837/chapman.000705