PROJECT SUMMARY Precision Medicine refers to the identification of risk factors and customization of medical treatment to the individual characteristics of each patient. To advance Precision Medicine, we need to better understand the molecular mechanisms underlying common and complex traits. The Accelerating Medicines Partnership (AMP) has been investigating traits, including Alzheimer's disease (AD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Parkinson's disease (PD), Schizophrenia (SCZ) and Type 2 diabetes (T2D), which have complex and partially shared polygenic architecture, and their pathophysiology involves inflammatory mechanisms regulated by the innate and adaptive immunity found in the brain and periphery. We will utilize EpiXcan, a novel machine learning approach, which leverages expression reference panels (eQTLs cohorts with expression and genotype data) to understand the genetically driven perturbations of shared and distinct immune mechanisms across AMP-related traits. As input data to this analysis, we will integrate multiple GWAS summary statistics for AMP-related traits with high dimensional single-cell data in human purified microglia and peripheral blood mononuclear cells (PBMCs) from matched donors and expanded in-house population- level RNA-seq and ATAC-seq data in human purified microglia combined with external omics data of brain immune cells, PBMC and synovium. Our analysis will identify trait-trait correlations, gene-trait associations and molecular pathways associated with shared genes implicated across AMP-related traits, serving as potential targets for future, novel therapeutic treatments.