Abstract Alzheimer’s disease (AD) is a devastating neurodegenerative disorder that leads to dramatic effects on the affected individuals and their families. While the characterization of the genetic contribution to AD and underlying molecular mechanisms have advanced the understanding of the disease in recent years, studies show that sex differences account for much of the observed differences in risk, progression, and severity across individuals. Here, we directly dissect the contribution of sex-specific variation down to the region- specific and cell-type-specific molecular basis by systematic profiling, computational integration, and experimental validation of the transcriptional, epigenomic, and genetic signatures across individuals, brain regions, and cell types. In Aim 1, we use genetic, epigenomic, and transcriptional profiles, generating millions of single-cell (sc) level maps using scRNA-seq and scATAC-seq across human and mouse samples of varying ages and genetic risk status. In Aim 2, we analyze the resulting datasets in the context of known AD genetic risk variation and underlying molecular mechanisms, enabling us to discover and converge variants, regulatory regions, genes, pathways, cell types, and brain regions to functional, causal mechanisms that drive sex-related differences. In Aim 3, we use our well-established mouse and iPSC models to test our predicted mechanisms with both high-throughput and cell-type specific assays. The resulting datasets, computational predictions, and experimentally-supported mechanisms will shed light on the sex-related differences of AD and will help deepen our understanding the disease in general as we develop more personalized therapeutic approaches in treating AD.

Narrative Alzheimer’s Disease (AD) is a devastating neurodegenerative disease that is the most common cause of dementia, and a significant healthcare burden worldwide. This condition results in progressive memory loss and cognitive decline, which lead to dramatic repercussions for affected individuals and their families. Many genetic studies have identified sex differences to be a critical factor in AD risk, progression, and severity across individuals, but precisely which sex-related mechanisms are responsible for these differences remain unknown. These studies systematically dissect the mechanisms underlying these observed differences using cutting-edge experimental and computational methods to predict sex-specific causal variants, regulatory regions, genes, and pathways; and systematic experimental characterization of predicted drivers using mouse models to better understand the mechanistic basis of sex-related differences in AD. These results will form the foundation for a deeper understanding of AD and new therapeutic development against this devastating disorder.