Precision and network medicine in cardiovascular prevention and disease

Cardiovascular diseases are characterized by mechanistic heterogeneity, varied genetic and environmental risk factors, and diverse clinical manifestations. Precision medicine has emerged as a paradigm to identify patient subgroups more clearly that share pathophysiologic, diagnostic, and/or therapeutic characteristics in order to harness them for more effective disease prevention and management strategies. Cardiovascular biomarkers have provided a starting point for applying a precision medicine-based approach for cardiovascular care. However, traditional biomarkers are often derived from associative and reductionist studies, having only a limited capacity to subclassify patients based on mechanistically relevant drivers of pathology. As a result, they have often had only modest impacts on reclassifying cardiovascular risk assessments for patients. Current approaches also have yet to fully leverage deep phenotyping and genotyping techniques, such as molecular imaging and multi-omic characterization. At the same time, the growing complexity of multi-omic data sets requires new methodologies to harness biologically meaningful insights to support precision-focused patient care goals. Systems biology and network medicine can provide a new strategy to advance precision medicine in cardiovascular diseases by being able to accommodate large datasets and integrate multiple data types into new analytical structures, such as network graphs, for unbiased evaluations that can yield new biomarkers and targets for study (Graphical Abstract). Here, we concisely review the current landscape of blood-based, genetic, and imaging biomarkers in cardiovascular diseases and discuss how systems biology and network medicine can serve as the basis for advancing precision medicine in cardiovascular diseases.