In recent years, microRNAs (miRNAs) were found to play critical roles in many important biological processes. On the other hand, the rapid development of genome-wide association studies (GWAS) help identify potential genetic variants associated with the disease phenotypic variance. Therefore, we suggested a combined analysis of microRNA expression profiling with genome-wide Single Nucleotide Polymorphism (SNP) genotyping to identify potential disease-related biomarkers. Considering functional SNPs in miRNA genes or target sites might be important signals associated with human complex diseases, we constructed a miRNA-miRNA synergistic network related to coronary artery disease (CAD) by performing a genome-wide scan for SNPs in human miRNA 3' -untranslated regions (UTRs) target sites and computed potential SNP cooperation effects contributing to disease based on potential miRNA-SNP interactions reported recently. Furthermore, we identified some potential CAD-related miRNAs by analyzing the constructed miRNAmiRNA synergistic network. As a result, the predicted miRNA-miRNA network and miRNA clusters were validated by significantly high interaction effects of CAD-related miRNAs. Accurate classification performances were obtained for all of the identified miRNA clusters, and the sensitivity and specificity were all more than 90%. The network topological analysis confirmed some novel CAD-related miRNAs identified recently by experiments. Our method might help to understand miRNA function and CAD disease, as well as to explore the novel mechanisms involved.