Project Abstract Genetic studies of Alzheimer’s disease (AD) and related-diseases (ADRD) have identified over 72 loci associated with susceptibility. Although some of the most penetrant variants have been studied independently, the majority of sequence variants and features are unlikely to act in isolation. In addition, the range of susceptibility loci cover coding, epigenetic, and regulatory regions of the genome, suggesting complex relationships that cannot be captured by large-scale transcriptomic and proteomic profiling alone. With this in mind, we systematically interrogate combinations of variants across validated AD loci in a cell autonomous and non-autonomous manner using a combination of molecular, epigenetic, and functional assays. This allows to create a functional network across AD loci, and identify nodal points where the effects of individual loci interact to trigger the hallmarks of AD pathology and clinical phenotypes. As part of this effort, we propose to establish a novel AD Locus Annotator interface that synthesizes information about AD-associated sequence features from reference databases encompassing existing multi-omic and clinical data, as well as new data sets that capture quantitative proteoform and cellular functional data; these latter two data modalities have been under-characterized in AD research to date, but are crucial to identifying cross-loci interactions. From this synthesized data analysis and portal effort, we then establish a set of gene editing efforts to validate and extend our mechanistic understanding of multi- locus functional networks from these AD-associated sequence features. Taken together, these analyses and experiments allow us to link the heterogeneity of AD-associated genetic variation and clinical manifestations into a coherent framework that link AD loci with the temporal sequence of events in AD onset and progression.