# Cardiac–Metabolic Coupling Revealed by Lipid and Energy Metabolomics Determines 80 km Endurance Performance in Yili Horses

**Authors:** Tongliang Wang, Jinlong Huang, Wanlu Ren, Jun Meng, Xinkui Yao, Hongzhong Chu, Runchen Yao, Manjun Zhai, Yaqi Zeng

PMC · DOI: 10.3390/biology14111581 · 2025-11-12

## TL;DR

This study explores how heart function and lipid metabolism in Yili horses affect their performance in 80 km endurance races.

## Contribution

The study identifies specific cardiac and metabolic markers linked to endurance performance in Yili horses.

## Key findings

- Horses that completed the race had significantly larger left ventricular dimensions and volumes.
- Metabolites like triglycerides and sphingomyelins were strongly associated with cardiac indicators.
- Sphingolipid metabolism and fatty acid degradation pathways were significantly activated during endurance exercise.

## Abstract

Endurance places extremely high demands on the cardiac function and energy metabolism of horses. The Yili horse, as a high-quality native breed in China, performs exceptionally well in long-distance endurance events. However, the academic community still lacks a systematic understanding of the physiological regulatory mechanisms behind the 80 km endurance performance of Yili horses. This study integrates echocardiography, lipidomics, and energy metabolomics technologies to analyze Yili horses with different competition results (pre-race finishers, post-race finishers, over-time finishers, and non-finishers), systematically exploring the correlations between cardiac structural and functional characteristics, plasma lipid metabolites, energy metabolism markers, and endurance performance. The research results show that the cardiac indicators such as left ventricular end-diastolic diameter (LVIDd) and end-diastolic volume (EDV) of the group that completed the race were significantly greater than those of the group that did not complete the race, and metabolites such as triglycerides, fatty acids, and sphingomyelins are significantly associated with cardiac indicators. At the same time, pathways such as sphingolipid metabolism, fatty acid degradation, and the tricarboxylic acid cycle (TCA) are significantly activated during endurance exercise. This study not only reveals the physiological and metabolic mechanisms by which Yili horses adapt to long-distance endurance exercise, but also provides potential biomarkers and a theoretical basis for the scientific selection, training, and performance evaluation of endurance horses.

This study aimed to investigate the regulatory mechanisms underlying the relationship between cardiac structure and function and plasma metabolic characteristics in Yili horses participating in an 80-km endurance, by integrating echocardiography, lipidomics, and energy metabolomics analyses. Twenty four competing Yili horses were selected and divided based on competition outcomes: Pre-Completion Group: PCG (n = 6); Post-Completion Group: PoCG (n = 6); Overtime Completion Group: OCG (n = 6); and Non-Completion Group: NCG (n = 6). Cardiac structural and functional parameters were assessed via echocardiography, and intergroup differences were analyzed using one-way ANOVA with a significance threshold of p < 0.05. Plasma lipids and energy metabolites were quantified using UPLC–MS/MS, applying screening criteria of variable importance in projection (VIP) > 1, p < 0.05, and fold change (FC) > 1.2 or FC < 0.833. Bioinformatics analyses were subsequently conducted to identify intergroup variations and correlations. Specifically, associations between cardiac structure/function and metabolites were examined using Pearson correlation analysis, with screening criteria of p < 0.05 and correlation coefficient > 0.8. The results revealed the following: (1) Regarding cardiac structure and function, the PCG group exhibited significantly superior indices, including End-diastolic left ventricular diameter (LVIDd), End-diastolic left ventricular volume (EDV), stroke volume (SV), and ejection fraction (EF), compared with OCG and NCG, and LVIDd showed a highly significant negative correlation with competition completion time. (2) In metabolomic analyses, few differential metabolites were found among groups before the competition (only 60 between PCG and NCG), whereas 234 differential lipids were detected between PoCG and PCG, mainly enriched in sphingolipid metabolism and fatty acid degradation pathways. Energy metabolites showed distinct exercise-responsive patterns, with 22 differential metabolites between PCG and NCG and 21 between PoCG and PCG, significantly enriched in amino sugar and nucleotide sugar metabolism and TCA pathways. Dynamic changes in key TCA intermediates, such as citrate and succinate, reflected enhanced aerobic oxidative metabolism during endurance exercise. (3) Carnitine C18:1, Carnitine C10:2, FFA (20:3), Cer (t17:2/23:0) and 3-phenyllactic acid were significantly correlated with cardiac indicators such as LVLD and LVFWs (p < 0.05). In summary, performance in the 80-km endurance of Yili horses was primarily influenced by enlarged LVIDd and EDV, as well as the regulation of sphingolipid–fatty acid metabolic pathways. Triglycerides, specific acyl compounds, and ceramides may serve as potential biomarkers for evaluating endurance performance, providing a theoretical basis for scientific training and breeding of endurance horses.

## Linked entities

- **Chemicals:** fatty acids (PubChem CID 264), sphingomyelins (PubChem CID 44176376), citrate (PubChem CID 31348), succinate (PubChem CID 160419), 3-phenyllactic acid (PubChem CID 3848)

## Full-text entities

- **Diseases:** stroke (MESH:D020521)
- **Chemicals:** succinate (MESH:D019802), citrate (MESH:D019343), fatty acid (MESH:D005227), C10:2 (-), amino sugar (MESH:D000606), Lipid (MESH:D008055), 3-phenyllactic acid (MESH:C017648), FFA (MESH:D005230), Carnitine (MESH:D002331), TCA (MESH:D014238), ceramides (MESH:D002518), sphingolipid (MESH:D013107), Triglycerides (MESH:D014280)
- **Species:** Equus caballus (domestic horse, species) [taxon 9796]

## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12650485/full.md

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Source: https://tomesphere.com/paper/PMC12650485