Alzheimer's Disease Sequencing Project Umbrella Study

A central goal of human genetics is to understand the link between genotypic and phenotypic variation, including disease risk and local adaptations. In order to perform these analyses reliably, we need to characterize population structure reliably. The historical signatures of our past such as population mixtures, contractions, and expansions, as well as human diseases and natural selection, have left traces in our genomes. In this proposal, our objective is to develop and apply computational methods to reliably characterize population history, including admixture (recent and ancient events including Neanderthal and Denisovan gene flow), founder events and natural selection in the diverse populations in the ADSP dataset. We will use these inferences to then reliably characterize disease associations and identify signals of natural selection, leveraging local and global ancestry inferences and estimates of relatedness across samples in a linear mixed model or other frameworks. We will look for associations between Alzheimer's disease and other cognitive traits and identify genes and genomic regions/ pathways associated to these traits. We will also study the distribution of archaic ancestry––from Neanderthals, Denisovans or other unknown archaic hominins––across the genome to find regions of exceptional high (or low) archaic ancestry that might provide hints about the function of these regions. Further, we will characterize the differences in mutation patterns across different human populations and archaic and modern human lineages. Together, this project will provide insights about our evolutionary past, mutation patterns and genes associated to local adaptations and Alzheimer’s disease and cognitive traits in a diverse multi-ethnic cohort. Together, this project will provide insights about our evolutionary past, genes associated to local adaptations and Alzheimer’s disease, and evolution of cognitive traits in a diverse multi-ethnic cohort.

Evolutionary history shapes our genes and traits. The historical signatures of our past such as population mixtures, contractions, and expansions, as well as human diseases and natural selection, have left traces in our genomes. In this proposal, our objective is to develop and apply computational methods to reliably characterize population history, including admixture, founder events and natural selection in multi-ethnic individuals. Additionally, we will use these insights to reliably map genes and pathways associated to Alzheimer's disease and other traits in the diverse individuals in ADSP.