Coronary artery disease (CAD), computed tomography-defined coronary atherosclerosis (CT-CA), and cardiometabolic risk factors (CMRFs) are epidemiologically intertwined, yet their shared genetic basis has been explored through pairwise analyses. A comprehensive framework integrating clinical disease, subclinical imaging phenotypes, and upstream risk factors simultaneously remains lacking. We integrated large-scale genome-wide association study summary statistics for CAD, two CT-CA phenotypes (coronary artery calcium score and segment involvement score), and seven major CMRFs. Using MiXeR, we quantified global polygenic overlap, followed by cross-phenotype Bayesian analysis to identify pleiotropic variants. We observed substantial polygenic sharing across traits. A total of 530 shared SNPs were identified across 14 trait groups, yielding 325 unique lead pleiotropic variants. These loci were enriched in lipid metabolism and extracellular matrix organization pathways. Colocalization analysis in coronary artery tissue revealed 61 loci with shared causal variants influencing gene expression, including established cardiovascular genes such as PHACTR1 and ADAMTS7. Protein-protein interaction analysis identified lipid-related hub genes (e.g., APOE, PCSK9, LPL), most of which are druggable. Local genetic correlation analyses independently validated shared effects at 51 loci. Collectively, our findings demonstrate extensive shared genetic architecture linking cardiometabolic dysregulation, subclinical coronary atherosclerosis, and clinical CAD, providing insights into shared genetic mechanisms and a foundation for genetically informed risk stratification and precision prevention strategies.