Coronary heart disease remains the leading cause of death in the Western World. The advent of microarray and next-generation sequencing technologies has generated multi-dimensional data sets, allowing for new pathophysiological insights into this complex disease. To date, genome-wide association studies (GWAS) have identified 152 associated loci and 320 candidate genes, contributing to the genetic risk of coronary artery disease (CAD) and acute myocardial infarction (AMI). The majority of single nucleotide polymorphisms (SNPs) mediate their risk by unknown mechanisms. A functional analysis based on Gene Ontology and KEGG pathways of candidate genes that are associated with CAD/AMI-SNPs showed the strongest evidence for genes regulating cholesterol metabolism. Additional clusters were significantly enriched for pathways, which play prominent roles during AMI and the development of atherosclerotic plaques in vascular tissue, including focal adhesion/extracellular matrix interaction, TGF-β signaling, apoptosis, regulation of vascular smooth muscle contraction, angiogenesis, calcium ion binding, and transcription factors. A systems genetics approach, which incorporates genetic risk with gene expression data, metabolomic data, and protein biochemistry into genome-wide network studies, holds promise to elucidate the complex interplay between genetic risk and environmental factors for coronary artery disease.