Systems-based approaches to cardiovascular disease

Abstract

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.

Genetics and Genetic Testing in Congenital Heart Disease

“…These applications hold considerable future diagnostic and clinical potential and are already providing great utility for investigators applying comprehensive system-based approaches to the study of CHD 94,95 . The recognition that multiple independent insults are likely to contribute to at least a subset of CHD phenotypes indicate that systemsbased approaches will be necessary to understand CHD risk factor networks and properly contextualize many genetic testing results, particularly in the absence of extra-cardiac features or clear syndromic diagnoses.…”

Bridging Paradigms: Hybrid Mechanistic-Discriminative Predictive Models

“…However, such statistical genetics models have no mechanistic underpinning and it is significant that Lusis highlighted the revival of functional studies in his recent review [25]. An additional recent strand of research has been in systems biology [26], targeting genomic networks in well characterized but relevant cell-types networks or tissue-based networks defined by correlations between genes within the manifestation of the disease.…”

Perspectives for metabolomics in testosterone replacement therapy

“…Brockmoller et al (2012) integrated the analysis of the lipidome and metabolome with protein and gene expression data from a cohort of breast cancer patients to underline the general relevance of metabolic changes in cancer pathogenesis and tumour progression. Altogether, there is an increasing consensus that systems biology principles will play important roles in tuberculosis (Comas & Gagneux 2011), cancer (Lund & Dumeaux 2008), type 2 diabetes mellitus (Hu 2011) and CVD research (Maclellan et al 2012).…”