Genome-wide association studies (GWAS) have discovered >200 associations for coronary artery disease (CAD), each of which could point to genes and pathways that influence disease risk. It is thought that a fraction of these CAD risk loci influences the functions of endothelial cells, and that genes in multiple GWAS loci might act together in certain pathways. Yet, identifying these genes and pathways has proven challenging: each GWAS locus can have 2-20 candidate genes, a gene may participate in one or more pathways in a given cell type, and it remains unclear which genes and pathways would be likely to influence disease risk. I will present our work to address this challenge by developing a Variant-to-Gene-to-Program (V2G2P) framework to study the role of endothelial cells in coronary artery disease, involving building a Variant-to-Gene map with ABC and a Gene-to-Program map with systematic Perturb-seq. Our study nominates new genes that likely influence risk for CAD, identifies convergence of CAD risk loci into certain gene programs in endothelial cells, and demonstrates a generalizable strategy to catalog gene programs to connect disease variants to functions.