PurposeThe primary objective of the present study was to examine the association between branched chain and aromatic amino acid profiles (BCAA and AAA respectively) and the metabolic syndrome (MS), and to evaluate the clinical utility of these associations in the diagnostic process.MethodsTwo hundred and sixty three healthy men with MS [MS(+): n = 165] and without MS [MS(−): n = 98] were enrolled in the observational study. Anthropometrical, biochemical, and amino acid measurements were performed. The ability of the BCAA and AAA to discriminate subjects with MS and insulin resistance was tested. Based on logistic discrimination, a multivariate early MS diagnostic model was built, and its discrimination properties were evaluated.ResultsTwo functionally independent amino acid clusters were identified. BCAA and phenylalanine differed significantly between MS(+) and MS(−) participants (P = 0.003). These factors were also found to be indicators of MS(+) individuals (AUC: 0.66; 95% CI: 0.5757–0.7469), and correlated with cardiometabolic factors. No statistically significant differences in amino acid concentrations between those with and without insulin resistance were noted, and none of the amino groups were indicators of insulin resistance. The proposed MS multivariate diagnostic model consisted of phenylalanine, insulin, leptin, and adiponectin, and had good discrimination properties [AUC 0.79; 95% CI: 0.7239–0.8646].ConclusionsMS is associated with selective BCAA and AAA profile disturbances, which could be part of cardiometabolic disease pathogenesis and derive neither directly from insulin sensitivity impairment, nor obesity or muscle mass. The MS diagnostic model developed and described herein should be validated in future studies.

The metabolomic approach to research on lifestyle diseases has led to the discovery of new potential biomarkers of pathological conditions as well as key metabolic pathways that may become targets of therapeutic intervention. Current evidence supports plasma branched chain amino acids (BCAAs) as potential diagnostic and prognostic biomarkers of cardiometabolic diseases. However, the biological mechanisms of the associations that have been identified are still not completely understood and should be clarified before implementing BCAA-based biomarkers in the clinical setting. The most crucial issue that needs to be solved first is determining whether BCAA plasma profile disturbances are only passive biomarkers or whether they facilitate dysmetabolic processes. In this context, further research is also warranted to investigate the role of dietary BCAAs. Gaining this knowledge would be significant progress in molecular nutrition research, providing perspective for target therapeutic and prophylactic interventions. This paper provides a comprehensive review of the main hypotheses and mechanistic models that consider circulating BCAAs both as passive biomarkers and as contributors to cardiometabolic diseases.

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