Network Medicine: A New Paradigm for Cardiovascular Disease Research and Beyond

Until recently, advances in multi-omic data generation have not been met with commensurate increases in our understanding of human (patho)biology. This discrepancy is owing partly to the fact that contemporary biomedical research and medicine make the reductionist assumption that biological and disease processes occur in a vacuum. However, biology and life itself are governed by interconnected components (e.g. proteins, metabolites) that form dynamic complex systems (e.g. proteome, metabolome), the behavior of which is explicable only by investigating the system as a whole rather than assessment of the individual components in isolation. Network medicine summarizes this complexity as biological loci (nodes) and their interactions (edges). It is this simplification that enables one to model complex biological phenomena in a computationally efficient way. Network analysis of protein–protein interaction (PPI) maps (interactomes), generated computationally or experimentally, reveals novel genotype–phenotype relationships that are virtually indecipherable by conventional scientific reductionism. Network medicine also offers powerful computational tools to study the hidden links between seemingly distinct diseases, rethink conventional disease appraisal approaches, and revolutionize personalized and precision medicine. This chapter will review the foundations of network science, as well as the application of network-based approaches for the study, diagnosis, and treatment of cardiovascular disease (CVD).