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Home / Equine Research Bank / Front Vet Sci / Lipidomics and biochemical profiling of adult Yili horses in...
Frontiers in veterinary science2025; 12; 1597739; doi: 10.3389/fvets.2025.1597739

Lipidomics and biochemical profiling of adult Yili horses in a 26 km endurance race: exploring metabolic adaptations.

Abstract: The equine lipid metabolism is activated during and after endurance exercise to provide energy in response to the metabolic and physiological changes in the body caused by prolonged exercise; however, the specific regulatory mechanisms remain controversial and identifying differential lipid metabolites associated with equine endurance is essential to elucidate these regulatory mechanisms. In this study, blood samples for lipid metabolomic analysis and biochemical indices were collected before and after a 26 km race from 12 Yili horses with different endurance performance. The biochemical results showed that: the albumin (ALB) level was significantly higher in the general group than in the excellent group before the competition, but significantly lower in the ordinary group after the competition (p < 0.05); the pre-competition alanine aminotransferase (ALT) in the excellent group was significantly higher than that of the general group (p < 0.05); and the urea nitrogen (BUN) in the general group was significantly higher than that of the excellent group after the competition (p < 0.05). The lipid metabolism results showed that a total of 1,537 lipid differential metabolites were obtained, mainly enriched in the pathways of fatty acid biosynthesis, cortisol synthesis and secretion, bile secretion, aldosterone regulation of sodium reabsorption, biotin metabolism, steroid hormone biosynthesis, and neuroactive ligand-receptor interactions. Metabolomics and biochemical correlation analyses screened PC (18:3/18:4) and PI (18:1/18:2) as potential biomarkers to identify endurance performance in Yili horses. The results of this study provide a solid foundation for improving equine racing performance and for the selection and breeding of endurance horses by providing a comprehensive reference on the mechanisms of lipid metabolism in equine endurance.
Copyright © 2025 Chang, Zhang, Yao, Meng, Ren and Zeng.
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Publication Date: 2025-04-22 PubMed ID: 40331217PubMed Central: PMC12052713DOI: 10.3389/fvets.2025.1597739Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research delves into the metabolic adaptations of adult Yili horses during a 26 km endurance race. The study collected blood samples to analyze lipid metabolites and biochemical indices, with a focus on identifying changes related to endurance. It aims to enhance understanding of equine racing performance and assist in selective breeding of endurance horses.

Methodology

  • The researchers collected blood samples before and after a 26 km endurance race from 12 Yili horses. These horses had varying endurance performance. The samples were then used to conduct lipid metabolomic analysis and biochemical indices.
  • They measured a number of biochemical parameters including the albumin (ALB) level, alanine aminotransferase (ALT), and urea nitrogen (BUN).

Results

  • The findings showed that the albumin level was significantly higher in the general group of horses than in the excellent performing group prior to the race, but significantly lower in the ordinary group following the race.
  • The pre-race alanine aminotransferase in the excellent group was remarkably higher than that of the general group.
  • The urea nitrogen in the general group was significantly higher than that of the excellent group post competition.

Lipid Metabolism

  • A total of 1,537 distinct lipid metabolites were detected and were primarily enriched in the pathways of fatty acid biosynthesis, cortisol synthesis and secretion, bile secretion, aldosterone regulation of sodium reabsorption, biotin metabolism, steroid hormone biosynthesis, and neuroactive ligand-receptor interactions.
  • Metabolomics and biochemical correlation analyses screened PC (18:3/18:4) and PI (18:1/18:2) as potential biomarkers to identify endurance performance in Yili horses.

Conclusion

  • This study provides a comprehensive reference on the mechanisms behind lipid metabolism in equine endurance, offering essential insights into endurance performance in Yili horses.
  • The research lays a solid foundation for enhancing equine racing performance, selection, and breeding of endurance horses.

Cite This Article

APA
Chang X, Zhang Z, Yao X, Meng J, Ren W, Zeng Y. (2025). Lipidomics and biochemical profiling of adult Yili horses in a 26 km endurance race: exploring metabolic adaptations. Front Vet Sci, 12, 1597739. https://doi.org/10.3389/fvets.2025.1597739

Publication

Frontiers in veterinary science
ISSN: 2297-1769
NlmUniqueID: 101666658
Country: Switzerland
Language: English
Volume: 12
Pages: 1597739

Researcher Affiliations

Chang, Xiaokang
  • College of Animal Science, Xinjiang Agricultural University, Urumqi, China.
Zhang, Zihan
  • College of Animal Science, Xinjiang Agricultural University, Urumqi, China.
Yao, Xinkui
  • College of Animal Science, Xinjiang Agricultural University, Urumqi, China.
  • Xinjiang Key Laboratory of Equine Breeding and Exercise Physiology, Urumqi, China.
Meng, Jun
  • College of Animal Science, Xinjiang Agricultural University, Urumqi, China.
  • Xinjiang Key Laboratory of Equine Breeding and Exercise Physiology, Urumqi, China.
Ren, Wanlu
  • College of Animal Science, Xinjiang Agricultural University, Urumqi, China.
  • Xinjiang Key Laboratory of Equine Breeding and Exercise Physiology, Urumqi, China.
Zeng, Yaqi
  • College of Animal Science, Xinjiang Agricultural University, Urumqi, China.
  • Xinjiang Key Laboratory of Equine Breeding and Exercise Physiology, Urumqi, China.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

This article includes 55 references
  1. Zhou Q, Ghorasaini M, Cornelis FMF, Assi R, de Roover A, Giera M. Lipidomics unravels lipid changes in osteoarthritis articular cartilage.. Ann Rheum Dis (2025).
    doi: 10.1016/j.ard.2025.01.009pubmed: 39894691google scholar: lookup
  2. San-Millán I, Stefanoni D, Martinez JL, Hansen Kirk C, D’Alessandro A, Nemkov T. Metabolomics of endurance capacity in world tour professional cyclists.. Front Physiol (2020) 11:578–94.
    doi: 10.3389/fphys.2020.00578pmc: PMC7291837pubmed: 32581847google scholar: lookup
  3. Wang F, Wanyu W, He X, Qian P, Chang J, Lu Z. Effects of moderate intensity exercise on liver metabolism in mice based on multi-omics analysis.. Sci Rep (2024) 14:31072–84.
    doi: 10.1038/s41598-024-82150-ypmc: PMC11680863pubmed: 39730655google scholar: lookup
  4. Xiang K, Qin Z, Zhang H, Liu X. Energy metabolism in exercise-induced physiologic cardiac hypertrophy.. Front Pharmacol (2020) 11:1135–48.
    doi: 10.3389/fphar.2020.01133pmc: PMC7403221pubmed: 32848751google scholar: lookup
  5. Pakula PD, Halama A, AlDous EK, Johnson SJ, Filho SA, Suhre K. Characterization of exercise-induced hemolysis in endurance horses.. Front Vet Sci (2023) 10:1115776–84.
    doi: 10.3389/fvets.2023.1115776pmc: PMC10174325pubmed: 37180073google scholar: lookup
  6. Bonhomme MM, Patarin F, Kruse CJ, François AC, Renaud B, Couroucé A. Untargeted metabolomics profiling reveals exercise intensity-dependent alterations in thoroughbred Racehorses' plasma after routine conditioning sessions.. ACS Omega (2023) 8:48557–71.
    doi: 10.1021/acsomega.3c08583pmc: PMC10733985pubmed: 38144146google scholar: lookup
  7. Klein DJ, KH MK, Mirek ET, Anthony TG. Metabolomic response of equine skeletal muscle to acute fatiguing exercise and training.. Front Physiol (2020) 11:110–24.
    doi: 10.3389/fphys.2020.00110pmc: PMC7040365pubmed: 32132934google scholar: lookup
  8. Mouskeftara T, Kalopitas G, Liapikos T, Arvanitakis K, Theocharidou E, Germanidis G. Lipidomic analysis of liver and adipose tissue in a high-fat diet-induced non-alcoholic fatty liver disease mice model reveals alterations in lipid metabolism by weight loss and aerobic exercise.. Molecules (2024) 29:1494–511.
    doi: 10.3390/molecules29071494pmc: PMC11013466pubmed: 38611773google scholar: lookup
  9. Anna L, Cindy N, Gael C, Jacques C, Marianne F. A targeted UHPLC-MS/MS method to monitor lipidomic changes during a physical effort: optimization and application to blood microsamples from athletes.. J Pharm Biomed Anal (2023) 229:115373–86.
    doi: 10.1016/j.jpba.2023.115373pubmed: 37003087google scholar: lookup
  10. Yang Q, Cai Y, Wang Z, Guo S, Qiu S, Zhang A. Understanding the physiological mechanisms and therapeutic targets of diseases: Lipidomics strategies.. Life Sci (2025) 363:123411–24.
    doi: 10.1016/j.lfs.2025.123411pubmed: 39848598google scholar: lookup
  11. Warren JL, Hunter GR, Gower BA, Bamman MM, Windham ST, Moellering DR. Exercise effects on mitochondrial function and lipid metabolism during energy balance.. Med Sci Sports Exerc (2020) 52:827–34.
    doi: 10.1249/mss.0000000000002190pmc: PMC7117801pubmed: 31652245google scholar: lookup
  12. Schader JF, Haid M, Cecil A, Schoenfeld J, Halle M, Pfeufer A. Metabolite shifts induced by Marathon race competition differ between athletes based on level of fitness and performance: a substudy of the Enzy-mag IC study.. Meta (2020) 10:87–100.
    doi: 10.3390/metabo10030087pmc: PMC7143325pubmed: 32121570google scholar: lookup
  13. Contrepois K, Wu S, Moneghetti KJ, Hornburg D, Ahadi S, Tsai MS. Molecular choreography of acute exercise.. Cell (2020) 181:1112–1130.e16.
    doi: 10.1016/j.cell.2020.04.043pmc: PMC7299174pubmed: 32470399google scholar: lookup
  14. Nolazco Sassot L, Villarino NF, Dasgupta N, Morrison JJ, Bayly WM, Gang D. The lipidome of thoroughbred racehorses before and after supramaximal exercise.. Equine Vet J (2019) 51:696–700.
    doi: 10.1111/evj.13064pubmed: 30600546google scholar: lookup
  15. Wang C, Zeng Y, Wang J, Wang T, Li X, Shen Z. Estimation of genetic parameters of body conformation and racing performance traits in Yili horses.. J Equine Vet Sci (2025) 146:105378–87.
    doi: 10.1016/j.jevs.2025.105378pubmed: 39922246google scholar: lookup
  16. Wang T, Zeng Y, Ma C, Meng J, Wang J, Ren W. Plasma non-targeted metabolomics analysis of Yili horses raced on tracks with different surface hardness.. J Equine Vet Sci (2022) 121:104197–205.
    doi: 10.1016/j.jevs.2022.104197pubmed: 36572130google scholar: lookup
  17. Lindner A, Esser M, López R, Boffi F. Relationship between resting and recovery heart rate in horses.. Animals (2020) 10:120–7.
    doi: 10.3390/ani10010120pmc: PMC7022646pubmed: 31940806google scholar: lookup
  18. Perera TRW, Bromfield EG, Gibb Z, Nixon B, Sheridan AR, Rupasinghe T. Plasma Lipidomics reveals lipid signatures of early pregnancy in mares.. Int J Mol Sci (2024) 25:11073–89.
    doi: 10.3390/ijms252011073pmc: PMC11508387pubmed: 39456856google scholar: lookup
  19. Maśko M, Domino M, Jasiński T, Witkowska-Piłaszewicz O. The physical activity-dependent hematological and biochemical changes in school horses in comparison to blood profiles in endurance and race horses.. Animals (2021) 11:1128–40.
    doi: 10.3390/ani11041128pmc: PMC8071065pubmed: 33920044google scholar: lookup
  20. Belhaj MR, Lawler NG, Hoffman NJ. Metabolomics and Lipidomics: expanding the molecular landscape of exercise biology.. Meta (2021) 11:151–84.
    doi: 10.3390/metabo11030151pmc: PMC8001908pubmed: 33799958google scholar: lookup
  21. Rao G, Sui J, Zhang J. Metabolomics reveals significant variations in metabolites and correlations regarding the maturation of walnuts (Juglans regia L.).. Biology Open (2016) 5:829–36.
    doi: 10.1242/bio.017863pmc: PMC4920193pubmed: 27215321google scholar: lookup
  22. Tohge T. From fruit omics to fruiting omics: systematic studies of tomato fruiting by metabolic networks.. Mol Plant (2020) 13:1114–6.
    doi: 10.1016/j.molp.2020.07.012pubmed: 32711126google scholar: lookup
  23. Mukhopadhyay TK, Trauner D. Concise synthesis of Glycerophospholipids.. J Org Chem (2023) 88:11253–7.
    doi: 10.1021/acs.joc.2c02096pubmed: 36449029google scholar: lookup
  24. Zhou H, Huo Y, Yang N, Wei T. Phosphatidic acid: from biophysical properties to diverse functions.. FEBS J (2023) 291:1870–85.
    doi: 10.1111/febs.16809pubmed: 37103336google scholar: lookup
  25. Song Y, Shi X, Gao Z, Li R, Tian J, Cao X. Acupoint catgut embedding improves lipid metabolism in exercise-induced fatigue rats via the PPAR signaling pathway.. Animals (2023) 13:558–75.
    doi: 10.3390/ani13040558pmc: PMC9951690pubmed: 36830344google scholar: lookup
  26. Schranner D, Kastenmüller G, Schönfelder M, Römisch-Margl W, Wackerhage H. Metabolite concentration changes in humans after a bout of exercise: a systematic review of exercise metabolomics studies.. Sports Med Open (2020) 6:11–27.
    doi: 10.1186/s40798-020-0238-4pmc: PMC7010904pubmed: 32040782google scholar: lookup
  27. Cichoń-Woźniak J, Ostapiuk-Karolczuk J, Cieślicka M, Dziewiecka H, Basta P, Maciejewski D. Effect of 2 weeks rest-pause on oxidative stress and inflammation in female basketball players.. Sci Rep (2024) 14:14578–86.
    doi: 10.1038/s41598-024-65309-5pmc: PMC11199628pubmed: 38918542google scholar: lookup
  28. Okon IA, Beshel JA, Owu DU, Orie NN, Jim AE, Edet LI. Moderate aerobic exercise improves haematological indices without altering cardio-metabolic enzyme activities in sedentary healthy young adults.. BMC Sports Sci Med Rehabil (2025) 17:32–40.
    doi: 10.1186/s13102-025-01080-ypmc: PMC11871804pubmed: 40022144google scholar: lookup
  29. Giers J, Bartel A, Kirsch K, Müller SF, Horstmann S, Gehlen H. Blood-based markers for skeletal and cardiac muscle function in eventing horses before and after cross-country rides and how they are influenced by plasma volume shift.. Animals (2023) 13:3110–3128.
    doi: 10.3390/ani13193110pmc: PMC10572052pubmed: 37835716google scholar: lookup
  30. Valentine WJ, Tomomi HY, Shota Y, Hideo S. Biosynthetic enzymes of membrane Glycerophospholipid diversity as therapeutic targets for drug development.. Druggable Lipid Signaling Pathways (2020) 1274:5–27.
    doi: 10.1007/978-3-030-50621-6_2pubmed: 32894505google scholar: lookup
  31. Halama A, Oliveira JM, Filho SA, Qasim M, Achkar IW, Johnson S. Metabolic predictors of equine performance in endurance racing.. Meta (2021) 11:82–99.
    doi: 10.3390/metabo11020082pmc: PMC7912089pubmed: 33572513google scholar: lookup
  32. Kita Y, Shindou H, Shimizu T. Cytosolic phospholipase a 2 and lysophospholipid acyltransferases.. Biochimica et Biophysica Acta (BBA)-Molecular and Cell Biology of Lipids (2019) 1864:838–45.
    doi: 10.1016/j.bbalip.2018.08.006pubmed: 30905348google scholar: lookup
  33. Alves-Vas FJ, Toro-Román V, Sánchez IB, Pérez FJG, Maynar-Mariño M, Vicho GB. Erythrocyte phospholipid fatty acid profile in high-level endurance runners.. Appl Sci (2024) 14:3965–74.
    doi: 10.3390/app14103965pmc: PMC11206387pubmed: 38931250google scholar: lookup
  34. Alves Vas FJ, Grijota Pérez FJ, Toro-Román V, Sánchez IB, Maynar Mariño M, Barrientos Vicho G. Changes in the fatty acid profile in erythrocytes in high-level endurance runners during a sports season.. Nutrients (2024) 16:1895–907.
    doi: 10.3390/nᘒ1895pmc: PMC11206387pubmed: 38931250google scholar: lookup
  35. Zabrouskov V, Knowles NR. Changes in lipid molecular species and sterols of microsomal membranes during aging of potato (Solanum tuberosum L.) seed-tubers.. Lipids (2002) 37:309–15.
    doi: 10.1007/s11745-002-0896-0pubmed: 11942483google scholar: lookup
  36. Danielle D, Kayla C, Shiva S, Heather B, Michel A. Differential incorporation of alpha-linolenic acid into phospholipid classes in H4IIE cells.. Curr Dev Nutr (2021) 5:491–1.
    doi: 10.1093/cdn/nzab041_006pubmed: 0google scholar: lookup
  37. Defries D, Curtis K, Petkau JC, Shariati-Ievari S, Blewett H, Aliani M. Patterns of alpha-linolenic acid incorporation into phospholipids in H4IIE cells.. J Nutr Biochem (2022) 106:109014–4.
    doi: 10.1016/j.jnutbio.2022.109014pubmed: 35461904google scholar: lookup
  38. Maunder E, Rothschild JA, Fritzen AM, Jordy AB, Kiens B, Brick MJ. Skeletal muscle proteins involved in fatty acid transport influence fatty acid oxidation rates observed during exercise.. Pflugers Archiv Europ J Physiol (2023) 475:1061–72.
    doi: 10.1007/s00424-023-02843-7pmc: PMC10409849pubmed: 37464190google scholar: lookup
  39. Barneda D, Janardan V, Niewczas I, Collins DM, Cosulich S, Clark J. Acyl chain selection couples the consumption and synthesis of phosphoinositides.. EMBO J (2022) 41:e110038–55.
    doi: 10.15252/embj.2021110038pmc: PMC9475507pubmed: 35771169google scholar: lookup
  40. Tian J, Wu Y, Zhao W, Zhang G, Zhang H, Xue L. Transcriptomic and metabolomic-based revelation of the effect of fresh corn extract on meat quality of Jingyuan chicken.. Poult Sci (2025) 104:104814–25.
    doi: 10.1016/j.psj.2025.104814pmc: PMC11795593pubmed: 39848207google scholar: lookup
  41. Chandel NS. Lipid Metabolism.. Cold Spring Harb Perspect Biol (2021) 13:a040576–95.
    doi: 10.1101/cshperspect.a040576pmc: PMC8411952pubmed: 34470787google scholar: lookup
  42. Ballew SH, Zhou L, Surapaneni A, Grams ME, Windham BG, Selvin E. A novel creatinine muscle index based on creatinine filtration: associations with frailty and mortality.. J Am Soc Nephrol (2023) 34:495–504.
    doi: 10.1681/asn.0000000000000037pmc: PMC10103307pubmed: 36735317google scholar: lookup
  43. Yamamoto N, Tojo K, Mihara T, Maeda R, Sugiura Y, Goto T. Creatinine production rate is an integrative indicator to monitor muscle status in critically ill patients.. Crit Care (2025) 29:23–39.
    doi: 10.1186/s13054-024-05222-5pmc: PMC11731194pubmed: 39810218google scholar: lookup
  44. Mezincescu AM, Rudd A, Cheyne L, Horgan G, Philip S, Cameron D. Comparison of intramyocellular lipid metabolism in patients with diabetes and male athletes.. Nat Commun (2024) 15:3690–703.
    doi: 10.1038/s41467-024-47843-ypmc: PMC11096352pubmed: 38750012google scholar: lookup
  45. Lundsgaard AM, Fritzen AM, Kiens B. The importance of fatty acids as nutrients during post-exercise recovery.. Nutrients (2020) 12:280–93.
    doi: 10.3390/nሂ0280pmc: PMC7070550pubmed: 31973165google scholar: lookup
  46. Lu J, Zhang LM, Liu JJ, Liu YT, Lin XY, Wang XQ. High-intensity interval training alleviates exhaustive exercise-induced HSP70-assisted selective autophagy in skeletal muscle.. J Physiol Sci (2023) 73:32–44.
    doi: 10.1186/s12576-023-00884-2pmc: PMC10717669pubmed: 37990150google scholar: lookup
  47. Pratap GK, Priyadarshini CG. Crocetin inhibits Aβ aggregation in vitro and reduces ROS production and Aβ mediate cellular toxicity in neuronal SHSY5Y cells.. Alzheimers Dement (2025) 20:e087283–3.
    doi: 10.1002/alz.087283google scholar: lookup
  48. Xiang H, Jin S, Tan F, Xu Y, Lu Y, Wu T. Physiological functions and therapeutic applications of neutral sphingomyelinase and acid sphingomyelinase.. Biomed Pharmacother (2021) 139:111610–22.
    doi: 10.1016/j.biopha.2021.111610pubmed: 33957567google scholar: lookup
  49. Weissig V, Joshi MD, Migrino RQ. Cytoprotective effects of liposomal ganglioside GM1.. J Liposome Res (2025):1–6.
    doi: 10.1080/08982104.2025.2451776pubmed: 39827412google scholar: lookup
  50. Witkowska-Piłaszewicz O, Grzędzicka J, Seń J, Czopowicz M, Żmigrodzka M, Winnicka A. Stress response after race and endurance training sessions and competitions in Arabian horses.. Prev Vet Med (2021) 188:105265–9.
    doi: 10.1016/j.prevetmed.2021.105265pubmed: 33497894google scholar: lookup
  51. Grzędzicka J, Dąbrowska I, Malin K, Witkowska-Piłaszewicz O. Exercise-related changes in the anabolic index (testosterone to cortisol ratio) and serum amyloid a concentration in endurance and racehorses at different fitness levels.. Front Vet Sci (2023) 10:1148990–9003.
    doi: 10.3389/fvets.2023.1148990pmc: PMC10150884pubmed: 37138908google scholar: lookup
  52. Tsilosani A, Gao C, Zhang W. Aldosterone-regulated sodium transport and blood pressure.. Front Physiol (2022) 13:770375–91.
    doi: 10.3389/fphys.2022.770375pmc: PMC8859437pubmed: 35197862google scholar: lookup
  53. Pellicer-Caller R, Vaquero-Cristóbal R, González-Gálvez N, Abenza-Cano L, Horcajo J, de la Vega-Marcos R. Influence of exogenous factors related to nutritional and hydration strategies and environmental conditions on fatigue in endurance sports: a systematic review with Meta-analysis.. Nutrients (2023) 15:2700–29.
    doi: 10.3390/nᔒ2700pmc: PMC10305101pubmed: 37375605google scholar: lookup
  54. Revol-Cavalier J, Quaranta A, Newman JW, Brash AR, Hamberg M, Wheelock CE. The Octadecanoids: synthesis and bioactivity of 18-carbon oxygenated fatty acids in mammals, Bacteria, and Fungi.. Chem Rev (2024) 125:1–90.
    doi: 10.1021/acs.chemrev.3c00520pmc: PMC11719350pubmed: 39680864google scholar: lookup
  55. Alonso N, Almer G, Semeraro MD, Rodriguez-Blanco G, Fauler G, Anders I. Impact of high-fat diet and exercise on bone and bile acid metabolism in rats.. Nutrients (2024) 16:1744–63.
    doi: 10.3390/nᘑ1744pmc: PMC11174439pubmed: 38892677google scholar: lookup
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