Amino acids — lifesaver or killer in patients with diabetes?

Disturbances in cardiac metabolism underlie most cardiovascular diseases. Metabolomics, one of the newer “omics” technologies, has emerged as a powerful tool for defining changes in both global and cardiac-specific metabolism that occur across a spectrum of cardiovascular disease states. Findings from metabolomics studies have contributed to better understanding of the metabolic changes that occur in heart failure and ischemic heart disease and have identified new cardiovascular disease biomarkers. As technologies advance, the metabolomics field continues to evolve rapidly. In this review, we will discuss the current state of metabolomics technologies, including consideration of various metabolomics platforms and elements of study design; the emerging utility of stable isotopes for metabolic flux studies; and the use of metabolomics to better understand specific cardiovascular diseases, with an emphasis on recent advances in the field.

Circulating branched-chain amino acid (BCAA) levels are elevated in obesity/diabetes and are a sensitive predictor for type 2 diabetes. Here we show in rats that insulin dose-dependently lowers plasma BCAA levels through induction of hepatic protein expression and activity of branched-chain α-keto acid dehydrogenase (BCKDH), the rate-limiting enzyme in the BCAA degradation pathway. Selective induction of hypothalamic insulin signaling in rats and genetic modulation of brain insulin receptors in mice demonstrate that brain insulin signaling is a major regulator of BCAA metabolism by inducing hepatic BCKDH. Short-term overfeeding impairs the ability of brain insulin to lower BCAAs in rats. High-fat feeding in nonhuman primates and obesity and/or diabetes in humans is associated with reduced BCKDH protein in liver. These findings support the concept that decreased hepatic BCKDH is a major cause of increased plasma BCAAs and that hypothalamic insulin resistance may account for impaired BCAA metabolism in obesity and diabetes. Copyright © 2014 Elsevier Inc. All rights reserved.

Background Metabolomics is a promising tool of cardiovascular biomarker discovery. We systematically reviewed the literature on comprehensive metabolomic profiling in association with incident cardiovascular disease (CVD). Methods and Results We searched MEDLINE and EMBASE from inception to January 2016. Studies were eligible if they pertained to adult humans; followed an agnostic and/or comprehensive approach; used serum or plasma (not urine or other biospecimens); conducted metabolite profiling at baseline in the context of examining prospective disease; and included myocardial infarction, stroke, and/or CVD death in the CVD outcome definition. We identified 12 original articles (9 cohort and 3 nested case‐control studies); participant numbers ranged from 67 to 7256. Mass spectrometry was the predominant analytical method. The number and chemical diversity of metabolites were very heterogeneous, ranging from 31 to >10 000 features. Four studies used untargeted profiling. Different types of metabolites were associated with CVD risk: acylcarnitines, dicarboxylacylcarnitines, and several amino acids and lipid classes. Only tiny improvements in CVD prediction beyond traditional risk factors were observed using these metabolites (C index improvement ranged from 0.006 to 0.05). Conclusions There are a limited number of longitudinal studies assessing associations between comprehensive metabolomic profiles and CVD risk. Quantitatively synthesizing the literature is challenging because of the widely varying analytical tools and the diversity of methodological and statistical approaches. Although some results are promising, more research is needed, notably standardization of metabolomic techniques and statistical approaches. Replication and combinations of novel and holistic methodological approaches would move the field toward the realization of its promise.