Abstract
BackgroundCardiovascular diseases (CVD) represent one of the most important causes of morbidity and mortality worldwide. Innovative approaches to increase the understanding of the underpinnings of CVD promise to enhance CVD risk assessment and might pave the way to tailored therapies. Within the last years, systems medicine has emerged as a novel tool to study the genetic, molecular and physiological interactions.ConclusionIn this review, we provide an overview of the current molecular-experimental, epidemiological and bioinformatical tools applied in systems medicine in the cardiovascular field. We will discuss the status and challenges in implementing interdisciplinary systems medicine approaches in CVD.
Highlights
Cardiovascular diseases (CVD) represent one of the most important causes of morbidity and mortality worldwide
Innovative approaches to increase the understanding of the multifactorial, complex underpinnings of CVD promises to enhance CVD risk assessment and might pave the way to tailored therapies
Despite success of genome-wide association studies [3,4,5,6] and sequencing approaches [7], the underlying pathophysiological mechanisms of CVD remain - in part, to be determined. Diseases such as CVD are typically defined by late-appearing disease manifestation, by the range of clinical pathophenotypes, this definition neglects the underlying molecular pathophysiological disease mechanisms [8]
Summary
Cardiovascular diseases (CVD) represent one of the most important causes of morbidity and mortality worldwide. To provide a more comprehensive picture, the systematic integration of multidimensional datasets evolves as an emerging, so called systems medicine approach including molecular findings of regulatory RNAs and DNA, proteins, metabolites as well as knowledge from cell biology, animal experiments and human phenotypic and clinical data [9, 10].
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