Metabolomics identifies molecular products produced in response to numerous stimuli, including both adaptive (includes exercise training) and disease processes. We analyzed a longitudinal cohort of American-style football (ASF) athletes, who reliably acquire maladaptive cardiovascular (CV) phenotypes during competitive training, with high-resolution metabolomics to determine whether metabolomics can discriminate exercise-induced CV adaptations from early CV pathology.
Matched discovery ( n = 42) and validation ( n = 40) multicenter cohorts of collegiate freshman ASF athletes were studied with longitudinal echocardiography, applanation tonometry, and high-resolution metabolomics. Liquid chromatography-mass spectrometry identified metabolites that changed ( P < 0.05, false discovery rate <0.2) over the season. Metabolites demonstrating similar changes in both cohorts were further analyzed in linear and mixed-effects models to identify those associated with left ventricular mass, tissue-Doppler myocardial E ' velocity (diastolic function), and arterial function (pulse wave velocity).
In both cohorts, 20 common metabolites changed similarly across the season. Metabolites reflective of favorable CV health included an increase in arginine and decreases in hypoxanthine and saturated fatty acids (heptadecanoate, arachidic acid, stearate, and hydroxydecanoate). In contrast, metabolic perturbations of increased lysine and pipecolate, reflective of adverse CV health, were also observed. Adjusting for player position, race, height, and changes in systolic blood pressure, weight, and pulse wave velocity, increased lysine ( β = 0.018, P = 0.02) and pipecolate ( β = 0.018, P = 0.02) were associated with increased left ventricular mass index. In addition, increased lysine ( β = -0.049, P = 0.01) and pipecolate ( β = -0.052, P = 0.008) were also associated with lower E ' (reduced diastolic function).
ASF athletes seem to develop metabolomic changes reflective of both favorable CV health and early CV maladaptive phenotypes. Whether metabolomics can discriminate early pathologic CV transformations among athletes is a warranted future research direction.