The Geography of Gene Regulation in Alzheimer's Disease

Abstract

Alzheimer's disease progresses in a spatially heterogeneous manner across the brain, yet how the gene regulatory networks (GRNs) of individual cells vary across space in affected tissue remains largely unstudied. This thesis investigates whether changes in the spatial location of cells in human Alzheimer's disease tissue can be related to changes in GRN structure and the activity of key regulators. Cell-specific GRNs were inferred from paired single-nucleus RNA and ATAC data using pyScReNI, a Python port of the ScReNI algorithm, and projected onto MERFISH spatial coordinates using Tangram, for four cell subtypes across ten overlapping donors from the Seattle Alzheimer's Disease Brain Cell Atlas. First, the spatial mapping was validated as a feasible proof of concept, placing 22-29% of held-out cells within 500μm of their true location. GRN structure was found to be non-randomly organised in tissue space: no signal was present at the level of the whole network, but a subset of leading GRN components was significantly spatially autocorrelated, and the resulting GRN-defined clusters were spatially contiguous beyond chance. This spatial signal was carried by specific regulators concentrated in the neuronal subtypes and absent in the glial subtypes. The most spatially autocorrelated of these, AC106845.1, reached roughly 2.4 times the subtype-median spatial autocorrelation, followed by ADAM28 and FAM189A2, and these regulators operated through an on and off change in activity rather than a rewiring of regulatory targets. A directional but non-significant association with disease severity was observed, which the ten-donor cohort left underpowered. These findings show that single-cell GRNs can be inferred and spatially analysed at a resolution finer than previously available methods, and that their structure is spatially organised by specific regulators in Alzheimer's disease tissue.