The postgenomic shift in paradigm from reductionism to systems-wide network inference has increased recognition that cardiovascular diseases are not simply determined by the genome but arise from an interaction and dynamic dysregulation of gene regulatory networks, proteins, and metabolic alterations. The advent of postgenomic technologies promises to interrogate these complex pathophysiological perturbations by applying concepts of systemic relationships to biomarker discovery. A multibiomarker panel consisting of biomarkers capturing different levels of information (eg, microRNAs to assess endothelial and platelet activation, molecular lipid species to profile metabolic status, and proteolytic degradation products to assess vascular integrity) could outperform inflammatory biomarkers without vascular specificity in their ability of predicting cardiovascular risk. As atherosclerosis develops over decades, different biomarkers may be required for different stages of disease. Thus far, there is no simple blood test to directly assess the health of blood vessels or identify vulnerable patients. We discuss strategies for biomarker discovery using post genomics technologies, with a particular focus on circulating microRNAs. The aim is to reveal distinctive cardiovascular phenotypes and identify biomarker signatures that complement the Framingham risk scores in clinical decision-making and in a stratified medicine approach for early preventive treatment of disease.