Coronary Artery Disease (CAD) is the most common form of heart disease. It affects nearly 13 millionAmericans and is the leading cause of death in the United States. The disease is intimately linked to theaging of the cardiovascular system, environmental assault, and genetic predisposition. This multifactorialdisease is an excellent model to elucidate associated genetic variation and the impact of changesintranscription and epigenetic influences. A better understanding of the complex interplay of the molecularfactors involved in CAD will help to define molecular markers that lead to disease predisposition,formation,and progression. This training proposal will identify molecular factors that lead to CAD using family basedassociation analysis of early onset CAD linkage regions and through the application of high-resolutiongenomic microarray experimentsto determine DNA methylation patterns and transcription factor bindingassociated with CAD. The array work focuseson two components, (1) defining GATA2 DNA binding sitesacross the human genome and (2) identifying DNA methylationpatterns in proliferating aortic smoothmuscle cells.