FREE SHIPPING over $40
OVER 9000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Home / Equine Research Bank / Front Vet Sci / Omic technology to monitoring resilience and adaptation to e...
Frontiers in veterinary science2026; 12; 1734969; doi: 10.3389/fvets.2025.1734969

Omic technology to monitoring resilience and adaptation to exercise and heat stress in endurance horses.

Abstract: In horses, heat exposure modulates the hypothalamic-pituitary-adrenal axis, autonomic nervous system, and hypothalamic-pituitary-thyroid axis to maintain body temperature and prevent excessive heat accumulation. However, during strenuous exercise under hot and humid conditions, heat production may exceed dissipation, leading to heat stress, anhidrosis, heat stroke, or brain damage. Unassigned: Incremental field standardized exercise tests (fSETs) provide a reliable approach to assess training and fitness levels. Six Arabian horses from Italia Endurance Stable and Academy were monitored during fSETs performed under heat stress (HS) and thermoneutral (TN) conditions, with blood samples collected before and after each test. Hematocrit, lactate, and biochemical parameters were measured, and total serum RNA was sequenced. A protein-protein interaction (PPI) network of miRNA targets was constructed and analyzed for Gene Ontology (GO) enrichment. Unassigned: Lactatemia and hematocrit were significantly higher in HS vs. TN, while alanine aminotransferase, creatinine, and creatine kinase increased in HS POST vs. PRE fSET. Differentially expressed small RNAs included eca-myomir-206, eca-mir-301, eca-mir-3613-3p, eca-mir-142, and eca-mir-144, which were modulated by temperature and exercise. In POST vs. PRE fSET, enriched terms involved transcriptional regulation, glucose and LDL response, intracellular trafficking, cytoskeleton organization, cardiac conduction, ion channels, and immune regulation. In HS POST vs. PRE fSET, enrichment was observed for positive regulation of dendritic cell cytokine production, negative regulation of inflammation, and attenuation of oxidative stress-induced apoptotic signaling. Unassigned: This study aimed to investigate the molecular features underlying resilience and adaptation to combined heat- and exercise-induced stress in horses. Overall, our findings indicate that heat amplifies the physiological burden of endurance exercise and alters the molecular mechanisms supporting performance and recovery. Circulating small RNAs may act as early signals for homeostatic restoration and could help elucidate adaptive responses to stress, guiding personalized training strategies.
Copyright © 2026 Mecocci, Porzio, Chiaradia, Pepe, Paris, Bergagna, Pietrucci, Chillemi, Beccati and Cappelli.
Get Full Text
Publication Date: 2026-01-09 PubMed ID: 41585523PubMed Central: PMC12827092DOI: 10.3389/fvets.2025.1734969Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
LinkedInCopy
  • Journal Article

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.

Research Overview

  • This study examined how endurance horses adapt and respond at the molecular and physiological levels to exercise performed under heat stress versus thermoneutral conditions.
  • Using standardized exercise tests and advanced omic technologies, the researchers monitored various blood markers and gene expression changes to investigate resilience and recovery mechanisms.

Background and Importance

  • Horses exposed to heat use neuroendocrine systems—the hypothalamic-pituitary-adrenal axis, autonomic nervous system, and hypothalamic-pituitary-thyroid axis—to regulate body temperature and avoid overheating.
  • When undertaking intense exercise in hot, humid environments, heat production can exceed dissipation capacity, potentially causing heat stress, anhidrosis (inability to sweat), heat stroke, or brain damage.
  • Understanding how horses adapt to combined heat and exercise stress is vital to optimizing training and preventing health issues.

Study Design and Methods

  • Six Arabian endurance horses were selected from Italia Endurance Stable and Academy.
  • Each horse performed incremental field standardized exercise tests (fSETs) under two conditions: heat stress (HS) and thermoneutral (TN) environments.
  • Blood samples were taken before and after each test.
  • Measurements taken included hematocrit (proportion of red blood cells), lactate, biochemical parameters (alanine aminotransferase, creatinine, creatine kinase), and total serum RNA sequencing to examine small RNA expression.
  • A protein-protein interaction (PPI) network was constructed based on miRNA targets to identify enriched biological processes using Gene Ontology (GO) analysis.

Key Physiological Findings

  • Lactate and hematocrit levels were significantly higher when horses exercised under heat stress compared to thermoneutral conditions, indicating increased physiological strain and potentially greater muscle metabolism and dehydration.
  • Alanine aminotransferase (liver enzyme), creatinine (kidney function marker), and creatine kinase (muscle damage marker) all increased after the fSET performed in heat stress, suggesting heightened organ and muscle stress.

Molecular and Genomic Insights

  • Several small RNAs, including eca-myomir-206, eca-mir-301, eca-mir-3613-3p, eca-mir-142, and eca-mir-144, were differentially expressed depending on temperature and exercise status.
  • Post-exercise compared to pre-exercise, enriched biological pathways involved:
    • Transcriptional regulation (gene expression control)
    • Glucose and LDL (low-density lipoprotein) response pathways
    • Intracellular trafficking and cytoskeleton organization (cell structural and transport mechanisms)
    • Cardiac conduction and ion channel function (heart performance and electrical activity)
    • Immune regulation mechanisms
  • Specifically under heat stress post-exercise, the gene ontology enrichment highlighted:
    • Positive regulation of dendritic cell cytokine production (immune activation)
    • Negative regulation of inflammation (anti-inflammatory processes)
    • Attenuation of oxidative stress-induced apoptotic signaling (protection against cell death triggered by oxidative damage)

Conclusions and Applications

  • The study demonstrates that heat amplifies the physiological and molecular demands of endurance exercise, pushing horses’ recovery and homeostatic mechanisms harder.
  • Circulating small RNAs in the blood appear to be promising early biomarkers signaling the activation of adaptive responses to combined heat and exercise stress.
  • These molecular signals could help understand resilience in athletic horses and guide the development of personalized training and recovery protocols tailored to environmental conditions.
  • Overall, integrating omic technologies with physiological testing provides a powerful approach to monitor and improve horse performance and welfare under challenging environmental stresses.

Cite This Article

APA
(2026). Omic technology to monitoring resilience and adaptation to exercise and heat stress in endurance horses. Front Vet Sci, 12, 1734969. https://doi.org/10.3389/fvets.2025.1734969

Publication

Frontiers in veterinary science
ISSN: 2297-1769
NlmUniqueID: 101666658
Country: Switzerland
Language: English
Volume: 12
Pages: 1734969
PII: 1734969

Researcher Affiliations

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 89 references
  1. Gabai G, Amadori M, Knight CH, Werling D. The immune system is part of a whole-organism regulatory network.. Res Vet Sci (2018) 116:1–3.
    doi: 10.1016/j.rvsc.2017.09.018pubmed: 28958409google scholar: lookup
  2. Staley M, Conners MG, Hall K, Miller LJ. Linking stress and immunity: Immunoglobulin A as a non-invasive physiological biomarker in animal welfare studies.. Horm Behav (2018) 102:55–68.
    doi: 10.1016/j.yhbeh.2018.04.011pubmed: 29705025google scholar: lookup
  3. Amadori M. The Innate Immune Response to Noninfectious Stressors.. Amsterdam, Netherlands: Elsevier Inc. (2016).
  4. Glencross DA, Ho T-R, Camiña N, Hawrylowicz CM, Pfeffer PE. Air pollution and its effects on the immune system.. Free Radic Biol Med (2020) 151:56–68.
    doi: 10.1016/j.freeradbiomed.2020.01.179pubmed: 32007522google scholar: lookup
  5. Miglio A, Cappelli K, Capomaccio S, Mecocci S, Silvestrelli M, Antognoni MT. Metabolic and biomolecular changes induced by incremental long-term training in young thoroughbred racehorses during first workout season.. Animals (2020) 10:317.
    doi: 10.3390/ani10020317pmc: PMC7071023pubmed: 32085444google scholar: lookup
  6. Razzuoli E, Villa R, Sossi E, Amadori M. Characterization of the Interferon-α response of pigs to the weaning stress.. J Interferon Cytokine Res (2011) 31:237–47.
    doi: 10.1089/jir.2010.0041pubmed: 20950132google scholar: lookup
  7. Marcato F, van den Brand H, Kemp B, van Reenen K. Evaluating potential biomarkers of health and performance in veal calves.. Front Vet Sci (2018) 5:133.
    doi: 10.3389/fvets.2018.00133pmc: PMC6021515pubmed: 29977895google scholar: lookup
  8. Pachauri RK, Mayer L, Intergovernmental Intergovernmental Panel on Climate Change eds. Climate change 2014: synthesis report.. Geneva, Switzerland: Intergovernmental Panel on Climate Change. (2015). 151 p..
  9. Tebaldi C, Debeire K, Eyring V, Fischer E, Fyfe J, Friedlingstein P. Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6.. Earth Syst Dyn (2021) 12:253–93.
    doi: 10.5194/esd-12-253-2021google scholar: lookup
  10. . IL CLIMA IN ITALIA NEL 2023. Delibera del Consiglio SNPA n250/24 del 02.07.2024.. Available online at: https://www.snpambiente.it/wp-content/uploads/2024/07/Rapporto-SNPA-clima-2023.pdf (Accessed April 22, 2025).
  11. Gaughan J, Cawdell-Smith AJ. Impact of Climate Change on Livestock Production and Reproduction.. In: Sejian V, Gaughan J, Baumgard L, Prasad C, editors. Climate Change Impact on Livestock: Adaptation and Mitigation. New Delhi: Springer India (2015). p. 51–60.
    doi: 10.1007/978-81-322-2265-1_4google scholar: lookup
  12. Sellami M, Gasmi M, Denham J, Hayes LD, Stratton D, Padulo J. Effects of acute and chronic exercise on immunological parameters in the elderly aged: can physical activity counteract the effects of aging?. Front Immunol (2018) 9:2187.
    doi: 10.3389/fimmu.2018.02187pmc: PMC6191490pubmed: 30364079google scholar: lookup
  13. Noakes TD. Physiological models to understand exercise fatigue and the adaptations that predict or enhance athletic performance: physiological models to study exercise.. Scand J Med Sci Sports (2000) 10:123–45.
    doi: 10.1034/j.1600-0838.2000.010003123.xpubmed: 10843507google scholar: lookup
  14. Arfuso F, Giudice E, Panzera M, Rizzo M, Fazio F, Piccione G. Interleukin-1Ra (Il-1Ra) and serum cortisol level relationship in horse as dynamic adaptive response during physical exercise.. Vet Immunol Immunopathol (2022) 243:110368.
    doi: 10.1016/j.vetimm.2021.110368pubmed: 34922262google scholar: lookup
  15. Malinowski K. Effects of training/exercise/stress on plasma cortisol and lactate in Standardbred yearlings.. J Anim Sci (1987) 65:222.
  16. Arfuso F, Rizzo M, Perillo L, Arrigo F, Giudice E, Piccione G, et al. The effect of ambient temperature, relative humidity, and temperature–humidity index on stress hormone and inflammatory response in exercising adult standardbred horses. Animals. (2025) 15:1436. doi: 10.3390/ani15101436
    doi: 10.3390/ani15101436pmc: PMC12108177pubmed: 40427313google scholar: lookup
  17. Piccione G, Arfuso F, Fazio F, Bazzano M, Giannetto C. Serum lipid modification related to exercise and polyunsaturated fatty acid supplementation in jumpers and thoroughbred horses. J Equine Vet Sci. (2014) 34:1181–7. doi: 10.1016/j.jevs.2014.07.005
    doi: 10.1016/j.jevs.2014.07.005google scholar: lookup
  18. Kang H, Zsoldos RR, Sole-Guitart A, Narayan E, Cawdell-Smith AJ, Gaughan JB. Heat stress in horses: a literature review. Int J Biometeorol. (2023) 67:957–73. doi: 10.1007/s00484-023-02467-7
    doi: 10.1007/s00484-023-02467-7pmc: PMC10267279pubmed: 37060454google scholar: lookup
  19. Mccutcheon LJ, Geor RJ. Effects of short-term training on thermoregulatory and sweat responses during exercise in hot conditions. Equine Vet J. (2010) 42:135–41. doi: 10.1111/j.2042-3306.2010.00235.x
    doi: 10.1111/j.2042-3306.2010.00235.xpubmed: 21058995google scholar: lookup
  20. Verdegaal E-LJMM, Howarth GS, McWhorter TJ, Delesalle CJG. Thermoregulation during field exercise in horses using skin temperature monitoring. Animals. (2023) 14:136. doi: 10.3390/ani14010136
    doi: 10.3390/ani14010136pmc: PMC10777899pubmed: 38200867google scholar: lookup
  21. Arfuso F, Rizzo M, Giannetto C, Giudice E, Cirincione R, Cassata G, et al. Oxidant and antioxidant parameters' assessment together with homocysteine and muscle enzymes in racehorses: evaluation of positive effects of exercise. Antioxidants. (2022) 11:1176. doi: 10.3390/antiox11061176
    doi: 10.3390/antiox11061176pmc: PMC9220350pubmed: 35740073google scholar: lookup
  22. Périard JD, Eijsvogels TMH, Daanen HAM. Exercise under heat stress: thermoregulation, hydration, performance implications, and mitigation strategies. Physiol Rev. (2021) 101:1873–979. doi: 10.1152/physrev.00038.2020
    doi: 10.1152/physrev.00038.2020pubmed: 33829868google scholar: lookup
  23. Cunningham EP, Dooley JJ, Splan RK, Bradley DG. Microsatellite diversity, pedigree relatedness and the contributions of founder lineages to thoroughbred horses. Anim Genet. (2001) 32:360–4. doi: 10.1046/j.1365-2052.2001.00785.x
    doi: 10.1046/j.1365-2052.2001.00785.xpubmed: 11736806google scholar: lookup
  24. Bowling AT, Del Valle A, Bowling M. A pedigree-based study of mitochondrial d-loop DNA sequence variation among Arabian horses. Anim Genet. (2000) 31:1–7. doi: 10.1046/j.1365-2052.2000.00558.x
    doi: 10.1046/j.1365-2052.2000.00558.xpubmed: 10690354google scholar: lookup
  25. Hinchcliff KW, Geor RJ. “Chapter 1.1 - The horse as an athlete: a physiological overview.,” In: Hinchcliff KW, Geor RJ, Kaneps AJ, editors. Equine Exercise Physiology. Edinburgh: W.B. Saunders; (2008). p. 2–11 doi: 10.1016/B978-070202857-1.50003-2
    doi: 10.1016/B978-070202857-1.50003-2google scholar: lookup
  26. De Maré L, Boshuizen B, Vidal Moreno De Vega C, De Meeûs C, Plancke L, Gansemans Y, et al. Profiling the aerobic window of horses in response to training by means of a modified lactate minimum speed test: flatten the curve. Front Physiol. (2022) 13:792052. doi: 10.3389/fphys.2022.792052
    doi: 10.3389/fphys.2022.792052pmc: PMC8982777pubmed: 35392373google scholar: lookup
  27. Halsey LG, Bryce CM. Are humans evolved specialists for running in the heat? Man vs. horse races provide empirical insights. Exp Physiol. (2021) 106:258–68. doi: 10.1113/EP088502
    doi: 10.1113/EP088502pubmed: 32602586google scholar: lookup
  28. Brownlow M, Dart A, Jeffcott L. Exertional heat illness: a review of the syndrome affecting racing Thoroughbreds in hot and humid climates. Aust Vet J. (2016) 94:240–7. doi: 10.1111/avj.12454
    doi: 10.1111/avj.12454pubmed: 27349884google scholar: lookup
  29. Mooren FC, Viereck J, Krüger K, Thum T. Circulating micrornas as potential biomarkers of aerobic exercise capacity. Am J Physiol Heart Circ Physiol. (2014) 306:H557–63. doi: 10.1152/ajpheart.00711.2013
    doi: 10.1152/ajpheart.00711.2013pmc: PMC3920240pubmed: 24363306google scholar: lookup
  30. Nagy A, Dyson SJ, Murray JK. A veterinary review of endurance riding as an international competitive sport. Vet J. (2012) 194:288–93. doi: 10.1016/j.tvjl.2012.06.022
    doi: 10.1016/j.tvjl.2012.06.022pubmed: 22819800google scholar: lookup
  31. Amory H, Votion D-M, Fraipont A, Goachet AG, Robert C, Farnir F, et al. Altered systolic left ventricular function in horses completing a long distance endurance race. Equine Vet J. (2010) 42:216–9. doi: 10.1111/j.2042-3306.2010.00253.x
    doi: 10.1111/j.2042-3306.2010.00253.xpubmed: 21059009google scholar: lookup
  32. Scoppetta F, Tartaglia M, Renzone G, Avellini L, Gaiti A, Scaloni A, et al. Plasma protein changes in horse after prolonged physical exercise: a proteomic study. J Proteomics. (2012) 75:4494–504. doi: 10.1016/j.jprot.2012.04.014
    doi: 10.1016/j.jprot.2012.04.014pubmed: 22546489google scholar: lookup
  33. Paris A, Accorroni L, Pepe M, Cappelli K, Chiaradia E, Mecocci S, et al. Retrospective study of standardised field exercise test on injury development, blood lactate and recovery time in endurance horses. Comp Exerc Physiol (2024) 20:1–12. doi: 10.1163/17552559-20220059
    doi: 10.1163/17552559-20220059google scholar: lookup
  34. Kumari KA. The role of non-coding RNAs in gene regulation and cellular signaling pathways. Int J Innov Sci Eng Manag (2025) 4:174–180. doi: 10.69968/ijisem.2025v4i1174-180
    doi: 10.69968/ijisem.2025v4i1174-180google scholar: lookup
  35. McGivney BA, Griffin ME, Gough KF, McGivney CL, Browne JA, Hill EW, et al. Evaluation of microRNA expression in plasma and skeletal muscle of thoroughbred racehorses in training. BMC Vet Res. (2017) 13:347. doi: 10.1186/s12917-017-1277-z
    doi: 10.1186/s12917-017-1277-zpmc: PMC5700565pubmed: 29166903google scholar: lookup
  36. Brownlow MA, Mizzi JX. Pathophysiology of exertional heat illness in the Thoroughbred racehorse: Broadening perspective to include an exercise-induced gastrointestinal syndrome in which endotoxaemia and systemic inflammation may contribute to the condition. Equine Vet Educ. (2023) 35:271–80. doi: 10.1111/eve.13750
    doi: 10.1111/eve.13750google scholar: lookup
  37. Cappelli K, Capomaccio S, Viglino A, Silvestrelli M, Beccati F, Moscati L, et al. Circulating miRNAs as putative biomarkers of exercise adaptation in endurance horses. Front Physiol (2018) 9:429. doi: 10.3389/fphys.2018.00429
    doi: 10.3389/fphys.2018.00429pmc: PMC5928201pubmed: 29740341google scholar: lookup
  38. Cappelli K, Mecocci S, Capomaccio S, Beccati F, Palumbo AR, Tognoloni A, et al. Circulating transcriptional profile modulation in response to metabolic unbalance due to long-term exercise in equine athletes: a pilot study. Genes. (2021) 12:1965. doi: 10.3390/genes12121965
    doi: 10.3390/genes12121965pmc: PMC8701225pubmed: 34946914google scholar: lookup
  39. Ma S, Ren W, Li Z, Li L, Wang R, Su Y, et al. Comparative analysis of miRNA expression in Yili horses pre- and post-5000-m race. Front Genet. (2025) 16:1676558. doi: 10.3389/fgene.2025.1676558
    doi: 10.3389/fgene.2025.1676558pmc: PMC12520636pubmed: 41098164google scholar: lookup
  40. Denham J, McCluskey M, Denham MM, Sellami M, Davie AJ. Epigenetic control of exercise adaptations in the equine athlete: current evidence and future directions. Equine Vet J. (2021) 53:431–50. doi: 10.1111/evj.13320
    doi: 10.1111/evj.13320pubmed: 32671871google scholar: lookup
  41. Krishona M, Marcia H, Christie W, Roy J. Caring for horses during hot weather. (2024). Available online at: https://extension.umn.edu/horse-care-and-management/caring-horses-during-hot-weather (Accessed September 30, 2025).
  42. Habeeb AA, Gad AE, Atta MA. Temperature-humidity indices as indicators to heat stress of climatic conditions with relation to production and reproduction of farm animals. Int J Biotechnol Recent Adv. (2018) 1:35–50. doi: 10.18689/ijbr-1000107
    doi: 10.18689/ijbr-1000107google scholar: lookup
  43. R Core Team. R: A Language and Environment for Statistical Computing. R Found Stat Comput Vienna Austria (2023) Available online at: https://www.R-project.org/ (Accessed May 28, 2025).
  44. Head SR, Komori HK, LaMere SA, Whisenant T, Van Nieuwerburgh F, Salomon DR, et al. Library construction for next-generation sequencing: overviews and challenges. Biotechniques. (2014) 56:61–77. doi: 10.2144/000114133
    doi: 10.2144/000114133pmc: PMC4351865pubmed: 24502796google scholar: lookup
  45. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. (2012) 9:357–9. doi: 10.1038/nmeth.1923
    doi: 10.1038/nmeth.1923pmc: PMC3322381pubmed: 22388286google scholar: lookup
  46. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol (2014) 15:550. doi: 10.1186/s13059-014-0550-8
    doi: 10.1186/s13059-014-0550-8pmc: PMC4302049pubmed: 25516281google scholar: lookup
  47. Han J-H, Kwak J-Y, Lee S-S, Kim H-G, Jeon H, Cha R-R. Markedly Elevated Aspartate Aminotransferase from Non-Hepatic Causes. J Clin Med. (2022) 12:310. doi: 10.3390/jcm12010310
    doi: 10.3390/jcm12010310pmc: PMC9821092pubmed: 36615110google scholar: lookup
  48. Gomes CLN, Alves AM, Ribeiro Filho JD, Moraes Júnior FJ, Barreto Júnior RA, Fucuta RS, et al. Physiological and biochemical responses and hydration status in equines after two barrel racing courses. Pesqui Veterinária Bras. (2020) 40:992–1001. doi: 10.1590/1678-5150-pvb-6710
    doi: 10.1590/1678-5150-pvb-6710google scholar: lookup
  49. 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. doi: 10.3390/ani13193110
    doi: 10.3390/ani13193110pmc: PMC10572052pubmed: 37835716google scholar: lookup
  50. Padilha FGF, Dimache LAG, Almeida FQD, Ferreira AMR. Blood biochemical parameters of Brazilian sport horses under training in tropical climate. Rev Bras Zootec. (2017) 46:678–82. doi: 10.1590/s1806-92902017000800008
    doi: 10.1590/s1806-92902017000800008google scholar: lookup
  51. Sawka MN, Leon LR, Montain SJ, Sonna LA. Integrated physiological mechanisms of exercise performance, adaptation, and maladaptation to heat stress. Compr Physiol. (2011) 1:1883–928. doi: 10.1002/cphy.c100082
    doi: 10.1002/cphy.c100082pubmed: 23733692google scholar: lookup
  52. Brownlow M, Mizzi JX. An overview of exertional heat illness in thoroughbred racehorses: pathophysiology, diagnosis, and treatment rationale. Animals. (2023) 13:610. doi: 10.3390/ani13040610
    doi: 10.3390/ani13040610pmc: PMC9951674pubmed: 36830397google scholar: lookup
  53. Buckley P, Buckley DJ, Freire R, Hughes KJ. Pre-race and race management impacts serum muscle enzyme activity in Australian endurance horses. Equine Vet J. (2022) 54:895–904. doi: 10.1111/evj.13519
    doi: 10.1111/evj.13519pmc: PMC9545901pubmed: 34601756google scholar: lookup
  54. Pakula PD, Halama A, Al-Dous EK, Johnson SJ, Filho SA, Suhre K, et al. Characterization of exercise-induced hemolysis in endurance horses. Front Vet Sci. (2023) 10:1115776. doi: 10.3389/fvets.2023.1115776
    doi: 10.3389/fvets.2023.1115776pmc: PMC10174325pubmed: 37180073google scholar: lookup
  55. Peng S, Magdesian KG, Dowd J, Blea J, Carpenter R, Ho W, et al. Investigation of high gamma-glutamyltransferase syndrome in California thoroughbred racehorses. J Vet Intern Med. (2022) 36:2203–12. doi: 10.1111/jvim.16582
    doi: 10.1111/jvim.16582pmc: PMC9708438pubmed: 36377652google scholar: lookup
  56. Stucchi L, Rossi R, Mainardi E, Ferrucci F. Antioxidant capacity and athletic condition of endurance horses undergoing nutraceutical supplementation. J Equine Vet Sci. (2025) 146:105364. doi: 10.1016/j.jevs.2025.105364
    doi: 10.1016/j.jevs.2025.105364pubmed: 39864602google scholar: lookup
  57. Keller P, Vollaard NBJ, Gustafsson T, Gallagher IJ, Sundberg CJ, Rankinen T, et al. transcriptional map of the impact of endurance exercise training on skeletal muscle phenotype. J Appl Physiol. (2011) 110:46–59. doi: 10.1152/japplphysiol.00634.2010
    doi: 10.1152/japplphysiol.00634.2010pmc: PMC3253010pubmed: 20930125google scholar: lookup
  58. McCarthy JJ, Esser KA. MicroRNA-1 and microRNA-133a expression are decreased during skeletal muscle hypertrophy. J Appl Physiol. (2007) 102:306–13. doi: 10.1152/japplphysiol.00932.2006
    doi: 10.1152/japplphysiol.00932.2006pubmed: 17008435google scholar: lookup
  59. Ye J, Liu X. Interactions between endoplasmic reticulum stress and extracellular vesicles in multiple diseases. Front Immunol. (2022) 13:955419. doi: 10.3389/fimmu.2022.955419
    doi: 10.3389/fimmu.2022.955419pmc: PMC9402983pubmed: 36032078google scholar: lookup
  60. Wang Y, Du J, Liu Y, Yang S, Wang Q. microRNA-301a-3p is a potential biomarker in venous ulcers vein and gets involved in endothelial cell dysfunction. Bioengineered. (2022) 13:14138–58. doi: 10.1080/21655979.2022.2083821
    doi: 10.1080/21655979.2022.2083821pmc: PMC9342147pubmed: 35734851google scholar: lookup
  61. Kaminsky LW, Al-Sadi R, Ma TY. IL-1β and the Intestinal Epithelial Tight Junction Barrier. Front Immunol. (2021) 12:767456. doi: 10.3389/fimmu.2021.767456
    doi: 10.3389/fimmu.2021.767456pmc: PMC8574155pubmed: 34759934google scholar: lookup
  62. Kleemann M, Bereuther J, Fischer S, Marquart K, Hänle S, Unger K, et al. Investigation on tissue specific effects of pro-apoptotic micro RNAs revealed miR-147b as a potential biomarker in ovarian cancer prognosis. Oncotarget. (2017) 8:18773–91. doi: 10.18632/oncotarget.13095
    doi: 10.18632/oncotarget.13095pmc: PMC5386646pubmed: 27821806google scholar: lookup
  63. Chang X, Zhang Z, Yao X, Meng J, Ren W, Zeng Y. Lipidomics and biochemical profiling of adult Yili horses in a 26 km endurance race: exploring metabolic adaptations. Front Vet Sci. (2025) 12:1597739. doi: 10.3389/fvets.2025.1597739
    doi: 10.3389/fvets.2025.1597739pmc: PMC12052713pubmed: 40331217google scholar: lookup
  64. Arfuso F, Giannetto C, Interlandi C, Giudice E, Bruschetta A, Panzera MF, et al. Dynamic metabolic response, clotting times and peripheral indices of central fatigue in horse competing in a 44 Km endurance race. J Equine Vet Sci. (2021) 106:103753. doi: 10.1016/j.jevs.2021.103753
    doi: 10.1016/j.jevs.2021.103753pubmed: 34670693google scholar: lookup
  65. Smith JAB, Murach KA, Dyar KA, Zierath JR. Exercise metabolism and adaptation in skeletal muscle. Nat Rev Mol Cell Biol. (2023) 24:607–32. doi: 10.1038/s41580-023-00606-x
    doi: 10.1038/s41580-023-00606-xpmc: PMC10527431pubmed: 37225892google scholar: lookup
  66. Richter EA, Hargreaves M. Exercise, GLUT4, and Skeletal Muscle Glucose Uptake. Physiol Rev. (2013) 93:993–1017. doi: 10.1152/physrev.00038.2012
    doi: 10.1152/physrev.00038.2012pubmed: 23899560google scholar: lookup
  67. Hawley JA, Lessard SJ. Exercise training-induced improvements in insulin action. Acta Physiol. (2008) 192:127–35. doi: 10.1111/j.1748-1716.2007.01783.x
    doi: 10.1111/j.1748-1716.2007.01783.xpubmed: 18171435google scholar: lookup
  68. Docherty S, Harley R, McAuley JJ, Crowe LAN, Pedret C, Kirwan PD, et al. The effect of exercise on cytokines: implications for musculoskeletal health: a narrative review. BMC Sports Sci Med Rehabil. (2022) 14:5. doi: 10.1186/s13102-022-00397-2
    doi: 10.1186/s13102-022-00397-2pmc: PMC8740100pubmed: 34991697google scholar: lookup
  69. Cusseddu R, Robert A, Côté J-F. Strength through unity: the power of the mega-scaffold MACF1. Front Cell Dev Biol. (2021) 9:641727. doi: 10.3389/fcell.2021.641727
    doi: 10.3389/fcell.2021.641727pmc: PMC8012552pubmed: 33816492google scholar: lookup
  70. Ghasemizadeh A, Christin E, Guiraud A, Couturier N, Abitbol M, Risson V, et al. MACF1 controls skeletal muscle function through the microtubule-dependent localization of extra-synaptic myonuclei and mitochondria biogenesis. Elife. (2021) 10:e70490. doi: 10.7554/eLife.70490.sa2
    doi: 10.7554/eLife.70490.sa2pmc: PMC8500715pubmed: 34448452google scholar: lookup
  71. Ropka-Molik K, Stefaniuk-Szmukier M, Żukowski K, Piórkowska K, Gurgul A, Bugno-Poniewierska M. Transcriptome profiling of Arabian horse blood during training regimens. BMC Genet. (2017) 18:31. doi: 10.1186/s12863-017-0499-1
    doi: 10.1186/s12863-017-0499-1pmc: PMC5382464pubmed: 28381206google scholar: lookup
  72. Milczek-Haduch D, Żmigrodzka M, Witkowska-Piłaszewicz O. Extracellular vesicles in sport horses: potential biomarkers and modulators of exercise adaptation and therapeutics. Int J Mol Sci. (2025) 26:4359. doi: 10.3390/ijms26094359
    doi: 10.3390/ijms26094359pmc: PMC12073050pubmed: 40362597google scholar: lookup
  73. Kim SK, Bae GS, Bae T, Ku S-K, Choi B, Kwak M-K. Renal microRNA-144-3p is associated with transforming growth factor-β1-induced oxidative stress and fibrosis by suppressing the NRF2 pathway in hypertensive diabetic kidney disease. Free Radic Biol Med. (2024) 225:546–59. doi: 10.1016/j.freeradbiomed.2024.10.286
    doi: 10.1016/j.freeradbiomed.2024.10.286pubmed: 39423929google scholar: lookup
  74. Ahmed SMU, Luo L, Namani A, Wang XJ, Tang X. Nrf2 signaling pathway: pivotal roles in inflammation. Biochim Biophys Acta BBA Mol Basis Dis. (2017) 1863:585–97. doi: 10.1016/j.bbadis.2016.11.005
    doi: 10.1016/j.bbadis.2016.11.005pubmed: 27825853google scholar: lookup
  75. Zhang H, Peng L, Wang Y, Zhao W, Lau WB, Wang Y, et al. Extracellular vesicle-derived miR-144 as a novel mechanism for chronic intermittent hypoxia-induced endothelial dysfunction. Theranostics. (2022) 12:4237–49. doi: 10.7150/thno.69035
    doi: 10.7150/thno.69035pmc: PMC9169375pubmed: 35673562google scholar: lookup
  76. Kukoyi AT, Fan X, Staitieh BS, Hybertson BM, Gao B, McCord JM, et al. MiR-144 mediates Nrf2 inhibition and alveolar epithelial dysfunction in HIV-1 transgenic rats. Am J Physiol Cell Physiol. (2019) 317:C390–7. doi: 10.1152/ajpcell.00038.2019
    doi: 10.1152/ajpcell.00038.2019pmc: PMC6732420pubmed: 31091144google scholar: lookup
  77. Snipe RMJ, Khoo A, Kitic CM, Gibson PR, Costa RJS. The impact of exertional-heat stress on gastrointestinal integrity, gastrointestinal symptoms, systemic endotoxin and cytokine profile. Eur J Appl Physiol. (2018) 118:389–400. doi: 10.1007/s00421-017-3781-z
    doi: 10.1007/s00421-017-3781-zpubmed: 29234915google scholar: lookup
  78. Vargas N, Marino F. Heat stress, gastrointestinal permeability and interleukin-6 signaling — Implications for exercise performance and fatigue. Temperature. (2016) 3:240–51. doi: 10.1080/23328940.2016.1179380
    doi: 10.1080/23328940.2016.1179380pmc: PMC4964994pubmed: 27857954google scholar: lookup
  79. Chaucheyras-Durand F, Sacy A, Karges K, Apper E. Gastro-intestinal microbiota in equines and its role in health and disease: the black box opens. Microorganisms. (2022) 10:2517. doi: 10.3390/microorganisms10122517
    doi: 10.3390/microorganisms10122517pmc: PMC9783266pubmed: 36557769google scholar: lookup
  80. Shrestha A, Carraro G, Nottet N, Vazquez-Armendariz AI, Herold S, Cordero J, et al. A critical role for miR-142 in alveolar epithelial lineage formation in mouse lung development. Cell Mol Life Sci. (2019) 76:2817–32. doi: 10.1007/s00018-019-03067-8
    doi: 10.1007/s00018-019-03067-8pmc: PMC11105218pubmed: 30887098google scholar: lookup
  81. Roberts LB, Jowett GM, Read E, Zabinski T, Berkachy R, Selkirk ME, et al. MicroRNA-142 critically regulates group 2 innate lymphoid cell homeostasis and function. J Immunol. (2021) 206:2725–39. doi: 10.4049/jimmunol.2000647
    doi: 10.4049/jimmunol.2000647pmc: PMC7610861pubmed: 34021046google scholar: lookup
  82. Chapnik E, Rivkin N, Mildner A, Beck G, Pasvolsky R, Metzl-Raz E, et al. miR-142 orchestrates a network of actin cytoskeleton regulators during megakaryopoiesis. Elife. (2014) 3:e01964. doi: 10.7554/eLife.01964.024
    doi: 10.7554/eLife.01964.024pmc: PMC4067751pubmed: 24859754google scholar: lookup
  83. Wang Y, Jia Z, Zheng M, Wang P, Gao J, Zhang X, et al. Inhibition of miR-142-3p promotes intestinal epithelial proliferation and barrier function after ischemia/reperfusion injury by targeting FoxM1. Mol Cell Biochem. (2025) 480:1121–35. doi: 10.1007/s11010-024-05038-5
    doi: 10.1007/s11010-024-05038-5pubmed: 38819598google scholar: lookup
  84. Liu J, Xu S, Liu S, Chen B. miR-3613-3p/MAP3K2/p38/caspase-3 pathway regulates the heat-stress-induced apoptosis of endothelial cells. Mol Med Rep. (2021) 24:633. doi: 10.3892/mmr.2021.12272
    doi: 10.3892/mmr.2021.12272pmc: PMC8280962pubmed: 34278472google scholar: lookup
  85. Liu J, Han X, Zhu G, Liu S, Lu Q, Tang Z. Analysis of potential functional significance of microRNA-3613-3p in human umbilical vein endothelial cells affected by heat stress. Mol Med Rep. (2019) 20:1846–56. doi: 10.3892/mmr.2019.10376
    doi: 10.3892/mmr.2019.10376pmc: PMC6625459pubmed: 31257536google scholar: lookup
  86. Giannone C, Bovo M, Ceccarelli M, Torreggiani D, Tassinari P. Review of the heat stress-induced responses in dairy cattle. Animals. (2023) 13:3451. doi: 10.3390/ani13223451
    doi: 10.3390/ani13223451pmc: PMC10668733pubmed: 38003069google scholar: lookup
  87. Cantet JM Yu Z, Ríus AG. Heat stress-mediated activation of immune–inflammatory pathways. Antibiotics. (2021) 10:1285. doi: 10.3390/antibiotics10111285
    doi: 10.3390/antibiotics10111285pmc: PMC8615052pubmed: 34827223google scholar: lookup
  88. Liu W, Meng P, Li Z, Shen Y, Meng X, Jin S, et al. The multifaceted impact of physical exercise on FoxO signaling pathways. Front Cell Dev Biol. (2025) 13:1614732. doi: 10.3389/fcell.2025.1614732
    doi: 10.3389/fcell.2025.1614732pmc: PMC12370687pubmed: 40861274google scholar: lookup
  89. Sarapultsev A, Gusev E, Komelkova M, Utepova I, Luo S, Hu D, et al. Signaling in inflammation and stress-related diseases: implications for therapeutic interventions. Mol Biomed. (2023) 4:40. doi: 10.1186/s43556-023-00151-1
    doi: 10.1186/s43556-023-00151-1pmc: PMC10632324pubmed: 37938494google scholar: lookup

Citations

This article has been cited 0 times.
Subscribe to our newsletter
Join 99,001 horse owners like you who receive our email updates on horse health and nutrition.