Platelet reactivity (PR) is variable between individuals and modulates clinical outcome in cardiovascular (CV) patients treated with antiplatelet drugs. Although several data point to a genetic control of platelet reactivity, the genes contributing to the modulation of this phenotype are not clearly identified. Integration of data derived from high-throughput technologies may yield novel insights into the molecular mechanisms that govern platelet reactivity. The aim of this study is to identify candidate genes modulating platelet reactivity in aspirin-treated CV patients using an integrative network-based approach. Patients with extreme high (n = 6) or low PR (n = 6) were selected and data derived from quantitative proteomic of platelets and platelet sub-cellular fractions, as well as from transcriptomic analysis were integrated with a network biology approach. Two modules within the network containing 123 and 182 genes were identified. We then specifically assessed the level of miRNAs in these two groups of patients. Among the 12 miRNAs differentially expressed, 2 (miR-135a-5p and miR-204-5p) correlated with PR. The predicted targets of these miRNAs were mapped onto the network, allowing the identification of seven overlapping genes (THBS1, CDC42, CORO1C, SPTBN1, TPM3, GTPBP2, and MAPRE2), suggesting a synergistic effect of these two miRNAs on these predicted targets. Integration of several omics data sets allowed the identification of 2 candidate miRNAs and 7 candidate genes regulating platelet reactivity in aspirin-treated CV patients.