Untargeted LC-HRMS metabolomic analysis reveals exercise-induced biochemical alterations in endurance Arabian horses.

This study found that after 80-km endurance rides, Arabian horses show widespread changes in blood metabolites that point to greater use of fats for energy, heightened mitochondrial activity, increased oxidative stress, and shifts in neurotransmitter-related pathways. The results identify candidate blood biomarkers that could help monitor fatigue, metabolic stress, and performance in endurance horses.

What the researchers asked and why it matters

• Question: How does prolonged aerobic exercise remodel the circulating metabolome of trained purebred Arabian horses?
• Rationale: Endurance performance relies on coordinated shifts in energy supply, redox balance, and neuromodulation; untargeted metabolomics can capture these systemic changes and reveal biomarkers to guide training and health monitoring.

Study design and analytical approach

• Population: Twelve trained purebred Arabian horses completing 80-km endurance rides.
• Sampling: Plasma collected immediately before and after the rides, enabling within-horse comparison of exercise effects.
• Platforms: Untargeted LC–HRMS using two complementary chromatographies:
  • HILIC to profile polar metabolites (e.g., organic acids, amino acids, small peptides).
  • Reversed-phase C18 to profile less polar species (e.g., acylcarnitines, lipid-derived oxidation products).
• Statistics: PLS-DA showed clear pre/post separation, indicating a global metabolic shift; significance testing identified 47 metabolites with altered concentrations.
• Cross-reference: Classical exercise markers (creatinine, urea, lactate) were measured and strongly correlated with LC-HRMS findings (r > 0.99, p < 0.05).

Key metabolite changes after 80-km endurance exercise

• Energy and substrate metabolism:
  • Marked increases in medium- and long-chain acylcarnitines.
  • Higher levels of 3-hydroxybutyric acid (a ketone body), pyruvate, and TCA cycle intermediates.
  • Elevated lactic acid alongside increased oxidative pathway intermediates, consistent with mixed substrate use.
• Protein and amino acid metabolism:
  • Decreases in tryptophan and small peptides, suggesting intensified amino acid utilization/catabolism.
  • Increases in urea and creatinine, reflecting heightened nitrogen turnover and muscle metabolic load (and potentially dehydration).
• Oxidative stress and inflammation-related signals:
  • Upregulation of HpODE (hydroperoxyoctadecadienoic acid), a lipid peroxidation product derived from linoleic acid.
  • Upregulation of allantoin, an oxidation product of uric acid, indicating reactive oxygen species activity.
• Neuromodulation:
  • Increased homovanillic acid (HVA), a dopamine catabolite, pointing to altered dopaminergic turnover with prolonged exertion.

Physiological interpretation

• Shift toward fatty-acid β-oxidation:
  • Rising medium/long-chain acylcarnitines indicate enhanced mitochondrial import and partial oxidation of fatty acids; accumulation reflects high flux and transient mismatch between β-oxidation and TCA capacity.
  • Elevated 3-hydroxybutyrate suggests increased hepatic fat-derived ketone production as a supplementary fuel during prolonged aerobic work.
• Enhanced mitochondrial oxidative phosphorylation:
  • Higher pyruvate and TCA intermediates imply accelerated anaplerosis and TCA cycling to meet sustained ATP demand.
  • Concurrent lactate elevation indicates ongoing glycolysis, consistent with a balanced use of carbohydrate and fat substrates under endurance conditions.
• Accelerated amino acid turnover and possible links to fatigue:
  • Reduced plasma tryptophan and small peptides suggest utilization of amino acids for energy and gluconeogenesis, or increased tissue uptake for repair and mitochondrial support.
  • Changes in tryptophan availability and increased dopamine turnover (higher HVA) are compatible with central fatigue mechanisms involving monoamine signaling, although directionality and causality require targeted neurochemical studies.
• Oxidative stress activation:
  • HpODE and allantoin increases reflect lipid and purine oxidation, respectively, marking exercise-induced reactive oxygen species and redox signaling typical of prolonged aerobic activity.
  • These signals can mediate adaptive responses but may also indicate oxidative load when excessive.

Relation to classical exercise biomarkers

• Creatinine, urea, and lactate rose significantly and correlated very strongly with untargeted metabolomics outputs (r > 0.99), validating the LC–HRMS readouts against well-established physiological markers.
• Interpretation nuances:
  • Creatinine can reflect muscle metabolism and hydration status; urea indicates nitrogen turnover; lactate reflects glycolytic flux and clearance capacity.

Practical implications for endurance horse management

• Monitoring and performance:
  • Panels including acylcarnitines, 3-hydroxybutyrate, HpODE/allantoin, and HVA could complement lactate, urea, and creatinine to track training load, metabolic stress, and recovery.
  • Trends in acylcarnitines and TCA intermediates may indicate fat-oxidation capacity and mitochondrial readiness across training cycles.
• Recovery and nutrition:
  • Redox-sensitive markers (HpODE, allantoin) can inform antioxidant periodization strategies (dietary polyphenols, vitamin E/Se) while avoiding blunting of training adaptations.
  • Amino acid dynamics suggest attention to protein quality and timing to support repair and maintain neurotransmitter balance.
• Health surveillance:
  • Deviation from expected post-ride patterns (e.g., disproportionate acylcarnitine accumulation or persistent oxidative markers) could flag maladaptation or elevated risk for muscle disorders and overtraining.

Strengths and limitations

• Strengths:
  • Within-subject design enhances sensitivity to exercise-induced changes.
  • Dual chromatography improved coverage of both polar metabolites and lipid-like species.
  • Alignment with classical biomarkers supports physiological relevance.
• Limitations:
  • Small sample size (n = 12) limits generalizability and precise effect estimation.
  • Untargeted identifications can include putative assignments; targeted validation and isotopic standards would strengthen confidence.
  • Timing of post-ride sampling, nutrition, hydration, and environmental factors can influence metabolite levels; these details are not specified in the abstract.
  • PLS-DA is supervised and susceptible to overfitting; robust cross-validation and permutation testing are needed (not reported in the abstract).

Future directions

• Methodological:
  • Targeted quantification of key candidates (acylcarnitines, 3-hydroxybutyrate, HpODE isomers, allantoin, HVA) with stable-isotope standards.
  • Time-course sampling (pre-, mid-, immediate post-, and recovery) to map kinetics and recovery half-lives.
• Integrative physiology:
  • Link metabolite trajectories to performance metrics (speed, heart rate, cardiac recovery index), hydration status, and muscle damage indices (e.g., CK, AST).
  • Assess interactions with diet (fat adaptation), training phase, sex/age, and genetic background within the Arabian breed.
• Neuro-fatigue axis:
  • Combine plasma metabolomics with behavioral assessments and, where feasible, central or peripheral neurochemical proxies to clarify dopaminergic/serotonergic contributions to fatigue.

Bottom line

• Prolonged endurance exercise in Arabian horses induces a coordinated metabolic reprogramming characterized by greater reliance on fat oxidation, elevated mitochondrial flux, heightened oxidative stress signaling, and altered monoamine metabolism.
• These untargeted metabolomic signatures nominate practical plasma biomarkers to monitor training load, fatigue, and recovery in equine endurance athletes, pending targeted validation and broader studies.