Cardiovascular diseases (CVDs) are the leading cause of death worldwide, but their molecular etiology remains poorly understood, in part because they develop slowly as a result of a mixture of genetic and environmental factors. Given the complex nature of CVD, molecular profiling of processes more “proximal” to the disease than genetic markers may have great promise in revealing both “form” (novel biomarkers with clinical potential) and “function” (mechanisms of disease development) of CVD. CVD is often associated with conditions of perturbed energy homeostasis and metabolism, including obesity, insulin resistance, and diabetes. The strong relationship between CVD and certain circulating lipids such as cholesterol and triglycerides has been recognized for decades. However, beyond these well-established associations, there is a strong possibility that other links between metabolic dysregulation and CVD remain to be discovered, and as a corollary, that new metabolite signatures can be identified that enhance risk prediction models. Comprehensive metabolic profiling, or “metabolomics” is increasingly being applied to CVD, leading to recent discoveries with both form and function implications. Here we review recent progress in this rapidly expanding area. Metabolomics is a term used to describe the measurement of multiple small-molecule metabolites in biological specimens, including bodily fluids (urine, blood, saliva), tissues, and breath exhalate. Metabolomics is perceived as a very recent addition to the omics platforms relative to genomics, transcriptomics, or proteomics, but in fact, its origins are in the venerable discipline of analytic biochemistry. Recent technological advances have enabled high-throughput profiling of large numbers of metabolites in biological samples, with increasing application to disease research, including CVD. One seemingly attractive feature of metabolic profiling is the relatively small number of human metabolites (≈7000) relative to the estimated numbers of genes (25 000), transcripts (100 000), and proteins (1 000 000). However, in reality, metabolites exist in a very …
Shah et al. (Mon,) studied this question.