The integrated analysis method based on functional genome information and network topological structure information mining atherosclerotic risk disease gene, provide a new perspective of atherosclerosis research in genome level. Through double selection, differential expression analysis and support vector machine (SVM), disease related risk gene with high confidencecould be uncovered. It is helpful for accurately distinguishing the disease genes and non-disease genes in the protein-protein interaction network, and building relationship between two type of these genes. Base on our strategy, 59 risk disease genes were exploited from macrophages sample and 61 risk disease genes from foam cell sample which shared common biological function and signal pathways with known AS disease gene. Furthermore, this method could be used to study the pathogenesis of other complex diseases in genome level.