Common cardiovascular diseases, such as atherosclerosis and congestive heart failure, are exceptionally complex, involving a multitude of environmental and genetic factors that often show nonlinear interactions as well as being highly dependent on sex, age, and even the maternal environment. Although focused, reductionistic approaches have led to progress in elucidating the pathophysiology of cardiovascular diseases, such approaches are poorly powered to address complex interactions. Over the past decade, technological advances have made it possible to interrogate biological systems on a global level, raising hopes that, in combination with computational approaches, it may be possible to more fully address the complexities of cardiovascular diseases. In this Review, we provide an overview of such systems-based approaches to cardiovascular disease and discuss their translational implications.
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