Integrative Metabolomic and Echocardiographic Profiling Reveals Metabolic-Cardiac Structural Coupling in Yili Horses...

This study integrated echocardiography with widely targeted metabolomics to decipher how plasma metabolic dynamics couple with cardiac geometry in Yili horses during incremental treadmill exercise. Nine speed-type horses underwent a graded exercise test (6% incline; 0 to 9 m/s). Jugular venous blood samples collected at rest (0 m/s) and at 3, 5, 7, and 9 m/s were profiled by LC-MS, and Pearson correlation analysis was applied to relate differentially expressed metabolites (DEMs) to twenty echocardiographic structural indices. A core set of 314 shared DEMs (124 upregulated, 190 downregulated) was identified across all exercise comparisons, spanning amino acids, organic acids, and fatty acyls. These metabolites were mapped to ABC transporter, thermogenesis, aldosterone-regulated sodium reabsorption, steroid hormone biosynthesis, and one-carbon folate metabolism pathways. At rest (0 m/s), right ventricular end-diastolic dimension correlated positively with arginyl-isoleucine (p < 0.001), whereas left ventricular free wall thickness (diastolic and systolic) correlated positively with undecanedioic acid (p < 0.001) and proline-hydroxyproline (p < 0.01). At peak exercise (9 m/s), left ventricular mass and left ventricular mass index correlated positively with succinic acid (p < 0.05) and methylmalonic acid (p < 0.05), while left ventricular minor axis correlated with carnitine C14:2 and carnitine C12:1 (p < 0.05). Left ventricular end-systolic dimension and left atrial end-diastolic dimension correlated negatively with cysteine-glutathione disulfide and N2-(1-carboxyethyl)-L-arginine, respectively. These findings illuminate a robust metabolic-cardiac structure axis: amino acid metabolites support collagen matrix turnover and redox homeostasis, organic acids sustain mitochondrial energy flux and antioxidant defense, and fatty acyls fuel continuous contractile activity via enhanced fatty acid oxidation. This metabolome-informed framework furnishes a mechanistic basis for precision training and performance phenotyping in equine athletes.