An integrative omics and genetic investigation of Alzheimer’s disease and related dementias
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Abstract
Alzheimer’s disease (AD) is a neurodegenerative disease defined by the presence of extracellular deposits of misfolded amyloid protein and intracellular neurofibrillary tangles composed of hyperphosphorylated Tau protein. It is the leading cause of dementia and affects millions of people, with this number expected to grow due to increases in life expectancy. Developments in high-throughput sequencing have enabled the disease to be studied from a number of complementary angles. In this dissertation I combine genomic and bulk and single-nucleus RNA-sequencing (snRNAseq) data to perform in-depth analyses investigating the roles of genetic variation and gene expression in AD. My analysis of brain-derived bulk and single-nucleus RNAseq data from individuals with AD demonstrated that individuals with pathological evidence of vascular disease had a higher expression of microglial expression of P2RY12 and CX3CR1 and a lower expression of microglial activation genes compared to other cases. This was associated with a decrease in the expression of angiogenesis-related genes in endothelial cells. In another study, I derived an AD polygenic risk score (PRS) from common genetic variants in whole-genome sequencing data from the Alzheimer’s Disease Sequencing Project participants, and then applied a novel approach for detection of AD-associated rare variants by stratifying individuals into high and low PRS groups. In individuals with high PRS, novel protective variants in ALDH9A1, BICC1, and PAN3 were identified. Similarly, novel risk variants were discovered across a 5.7 Mb region of chromosome 14, with some located in NYNRIN and LINC02286. These risk variants were almost exclusively found in a subset of Amish individuals. To further analyze the effect of PRS on AD biology, associations between PRS and gene expression were evaluated in a variety of cell types from snRNAseq data from Religious Orders Study and Memory and Aging Project participants. My analysis of expression quantitative trait scores (eQTS) derived from association data enabled me to prioritize genes which play an important role in AD biology. In total we detected 16,468 eQTS across seven cell types. Of these, an eQTS for PTPRG in microglia was the most strongly associated with the AD PRS. In summary, this thesis combines data from multiple different modalities to identify novel genes involved in AD biology.
Description
2026
License
Attribution 4.0 International