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Home / Equine Research Bank / Genes (Basel) / Enriched Pathways of Calcium Regulation, Cellular/Oxidative ...
Genes2022; 13(10); doi: 10.3390/genes13101853

Enriched Pathways of Calcium Regulation, Cellular/Oxidative Stress, Inflammation, and Cell Proliferation Characterize Gluteal Muscle of Standardbred Horses between Episodes of Recurrent Exertional Rhabdomyolysis.

Abstract: Certain Standardbred racehorses develop recurrent exertional rhabdomyolysis (RER-STD) for unknown reasons. We compared gluteal muscle histopathology and gene/protein expression between Standardbreds with a history of, but not currently experiencing rhabdomyolysis (N = 9), and race-trained controls (N = 7). Eight RER-STD had a few mature fibers with small internalized myonuclei, one out of nine had histologic evidence of regeneration and zero out of nine degeneration. However, RER-STD versus controls had 791/13,531 differentially expressed genes (DEG). The top three gene ontology (GO) enriched pathways for upregulated DEG (N = 433) were inflammation/immune response (62 GO terms), cell proliferation (31 GO terms), and hypoxia/oxidative stress (31 GO terms). Calcium ion regulation (39 GO terms), purine nucleotide metabolism (32 GO terms), and electron transport (29 GO terms) were the top three enriched GO pathways for down-regulated DEG (N = 305). DEG regulated RYR1 and sarcoplasmic reticulum calcium stores. Differentially expressed proteins (DEP ↑N = 50, ↓N = 12) involved the sarcomere (24% of DEP), electron transport (23%), metabolism (20%), inflammation (6%), cell/oxidative stress (7%), and other (17%). DEP included ↑superoxide dismutase, ↑catalase, and DEP/DEG included several cysteine-based antioxidants. In conclusion, gluteal muscle of RER-susceptible Standardbreds is characterized by perturbation of pathways for calcium regulation, cellular/oxidative stress, inflammation, and cellular regeneration weeks after an episode of rhabdomyolysis that could represent therapeutic targets.
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Publication Date: 2022-10-14 PubMed ID: 36292738PubMed Central: PMC9601720DOI: 10.3390/genes13101853Google Scholar: Lookup
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  • Journal Article
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  • Non-U.S. Gov't

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 investigates the characteristics of the gluteal muscles in Standardbred racehorses suffering from recurrent exertional rhabdomyolysis (RER-STD), focusing on the associated changes in calcium regulation, cellular stress response, inflammation, and cell proliferation pathways. Anomalies in these pathways could help develop therapies for this condition.

Objective of the Research

  • The research aims to shed light on the unknown causes of recurrent exertional rhabdomyolysis (RER-STD) in certain Standardbred racehorses by studying the changes in the gluteal muscle history and gene/protein expression.

Research Methodology

  • Gluteal muscle tissue samples were collected from RER-STD Standardbred horses that were not currently having an episode. These samples were compared with those taken from healthy, race-trained Standardbred horses (the control group).

Research Findings

  • Muscle histopathology showed a small number of mature fibers with internalized myonuclei in the RER-STD group. Still, there was no clear evidence of muscle tissue degeneration or regeneration.
  • Gene expression analysis showed differences in 791 out of 13,531 genes between the RER-STD and control groups.
  • Upregulated genes (those with increased expression) in the RER-STD group were primarily associated with inflammation, immune response, cell proliferation, and hypoxia/oxidative stress.
  • Downregulated genes (those with decreased expression) were mostly involved in calcium ion regulation, purine nucleotide metabolism, and electron transport.
  • Changes in protein expression (both increase and decrease) affected the sarcomere, electron transport, metabolism, inflammation, and cellular stress response.
  • The research also recorded changes in the expression of specific proteins and genes like superoxide dismutase, catalase, and several cysteine-based antioxidants.

Conclusion

  • The study concludes that the gluteal muscle in Standardbred horses susceptible to RER-STD exhibits disturbances in pathways relating to calcium regulation, cellular stress, inflammation, and cell regeneration.
  • These anomalies could potentially serve as therapeutic targets for the treatment and prevention of RER-STD in Standardbred racehorses.

Cite This Article

APA
Valberg SJ, Velez-Irizarry D, Williams ZJ, Henry ML, Iglewski H, Herrick K, Fenger C. (2022). Enriched Pathways of Calcium Regulation, Cellular/Oxidative Stress, Inflammation, and Cell Proliferation Characterize Gluteal Muscle of Standardbred Horses between Episodes of Recurrent Exertional Rhabdomyolysis. Genes (Basel), 13(10). https://doi.org/10.3390/genes13101853

Publication

Genes
ISSN: 2073-4425
NlmUniqueID: 101551097
Country: Switzerland
Language: English
Volume: 13
Issue: 10

Researcher Affiliations

Valberg, Stephanie J
  • Mary Anne McPhail Equine Performance Center, Department of Large Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, East Lansing, MI 48824, USA.
Velez-Irizarry, Deborah
  • Mary Anne McPhail Equine Performance Center, Department of Large Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, East Lansing, MI 48824, USA.
Williams, Zoë J
  • Mary Anne McPhail Equine Performance Center, Department of Large Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, East Lansing, MI 48824, USA.
Henry, Marisa L
  • Mary Anne McPhail Equine Performance Center, Department of Large Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, East Lansing, MI 48824, USA.
Iglewski, Hailey
  • Mary Anne McPhail Equine Performance Center, Department of Large Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, East Lansing, MI 48824, USA.
Herrick, Keely
  • Mary Anne McPhail Equine Performance Center, Department of Large Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, East Lansing, MI 48824, USA.
Fenger, Clara
  • Equine Integrated Medicine, PLC, Lexington, KY 40324, USA.

MeSH Terms

  • Animals
  • Calcium / metabolism
  • Cell Proliferation
  • Cysteine
  • Horse Diseases / genetics
  • Horses
  • Inflammation / genetics
  • Inflammation / veterinary
  • Inflammation / metabolism
  • Muscle, Skeletal / metabolism
  • Oxidative Stress
  • Purine Nucleotides / metabolism
  • Rhabdomyolysis / genetics
  • Rhabdomyolysis / veterinary
  • Rhabdomyolysis / metabolism
  • Ryanodine Receptor Calcium Release Channel

Conflict of Interest Statement

The authors declare that they have no competing interests with the contents of this article. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results”.

References

This article includes 75 references
  1. Isgren CM, Upjohn MM, Fernandez-Fuente M, Massey C, Pollott G, Verheyen KL, Piercy RJ. Epidemiology of exertional rhabdomyolysis susceptibility in standardbred horses reveals associated risk factors and underlying enhanced performance.. PLoS ONE 2010;5:e11594.
    doi: 10.1371/journal.pone.0011594pmc: PMC2904368pubmed: 20644724google scholar: lookup
  2. MacLeay JM, Sorum SA, Valberg SJ, Marsh WE, Sorum MD. Epidemiologic analysis of factors influencing exertional rhabdomyolysis in Thoroughbreds.. Am. J. Vet. Res. 1999;60:1562–1566.
    pubmed: 10622169
  3. McGowan CM, Fordham T, Christley RM. Incidence and risk factors for exertional rhabdomyolysis in thoroughbred racehorses in the United Kingdom.. Vet. Rec. 2002;151:623–626.
    doi: 10.1136/vr.151.21.623pubmed: 12479297google scholar: lookup
  4. Norton EM, Mickelson JR, Binns MM, Blott SC, Caputo P, Isgren CM, McCoy AM, Moore A, Piercy RJ, Swinburne JE. Heritability of Recurrent Exertional Rhabdomyolysis in Standardbred and Thoroughbred Racehorses Derived From SNP Genotyping Data.. J. Hered. 2016;107:537–543.
    doi: 10.1093/jhered/esw042pmc: PMC5006745pubmed: 27489252google scholar: lookup
  5. Fritz KL, McCue ME, Valberg SJ, Rendahl AK, Mickelson JR. Genetic mapping of recurrent exertional rhabdomyolysis in a population of North American Thoroughbreds.. Anim. Genet. 2012;43:730–738.
    doi: 10.1111/j.1365-2052.2012.02351.xpmc: PMC3665002pubmed: 22497487google scholar: lookup
  6. Dranchak PK, Valberg SJ, Onan GW, Gallant EM, MacLeay JM, McKenzie EC, De La Corte FD, Ekenstedt K, Mickelson JR. Inheritance of recurrent exertional rhabdomyolysis in thoroughbreds.. J. Am. Vet. Med. Assoc. 2005;227:762–767.
    doi: 10.2460/javma.2005.227.762pubmed: 16178398google scholar: lookup
  7. Aldrich K, Velez-Irizarry D, Fenger C, Schott M, Valberg SJ. Pathways of calcium regulation, electron transport, and mitochondrial protein translation are molecular signatures of susceptibility to recurrent exertional rhabdomyolysis in Thoroughbred racehorses.. PLoS ONE 2021;16:e0244556.
    doi: 10.1371/journal.pone.0244556pmc: PMC7875397pubmed: 33566847google scholar: lookup
  8. Barrey E, Bonnamy B, Barrey EJ, Mata X, Chaffaux S, Guerin G. Muscular microRNA expressions in healthy and myopathic horses suffering from polysaccharide storage myopathy or recurrent exertional rhabdomyolysis.. Equine Vet. J. 2010;42:303–310.
    doi: 10.1111/j.2042-3306.2010.00267.xpubmed: 21059022google scholar: lookup
  9. Barrey E, Jayr L, Mucher E, Gospodnetic S, Joly F, Benech P, Alibert O, Gidrol X, Mata X, Vaiman A. Transcriptome analysis of muscle in horses suffering from recurrent exertional rhabdomyolysis revealed energetic pathway alterations and disruption in the cytosolic calcium regulation.. Anim. Genet. 2012;43:271–281.
    doi: 10.1111/j.1365-2052.2011.02246.xpubmed: 22486498google scholar: lookup
  10. Scholte HR, Verduin MH, Ross JD, Van den Hoven R, Wensing T, Breuking HJ, Meijer AE. Equine exertional rhabdomyolysis: Activity of the mitochondrial respiratory chain and the carnitine system in skeletal muscle.. Equine Vet. J. 1991;23:142–144.
    doi: 10.1111/j.2042-3306.1991.tb02740.xpubmed: 2044508google scholar: lookup
  11. Valberg S, Haggendal J, Lindholm A. Blood chemistry and skeletal muscle metabolic responses to exercise in horses with recurrent exertional rhabdomyolysis.. Equine Vet. J. 1993;25:17–22.
    doi: 10.1111/j.2042-3306.1993.tb02894.xpubmed: 8422879google scholar: lookup
  12. Valberg S, Jonsson L, Lindholm A, Holmgren N. Muscle histopathology and plasma aspartate aminotransferase, creatine kinase and myoglobin changes with exercise in horses with recurrent exertional rhabdomyolysis.. Equine Vet. J. 1993;25:11–16.
    doi: 10.1111/j.2042-3306.1993.tb02893.xpubmed: 8422878google scholar: lookup
  13. Van den Hoven R, Breukink HJ, Wensing T, Meijer AE, Tigges AJ. Loosely coupled skeletal muscle mitochondria in exertional rhabdomyolysis.. Equine Vet. J. 1986;18:418–421.
    doi: 10.1111/j.2042-3306.1986.tb03673.xpubmed: 3769889google scholar: lookup
  14. Beech J, Lindborg S, Fletcher JE, Lizzo F, Tripolitis L, Braund K. Caffeine contractures, twitch characteristics and the threshold for Ca2+-induced Ca2+ release in skeletal muscle from horses with chronic intermittent rhabdomyolysis.. Res. Vet. Sci. 1993;54:110–117.
    doi: 10.1016/0034-5288(93)90019-Cpubmed: 8434138google scholar: lookup
  15. Houben R, Leleu C, Fraipont A, Serteyn D, Votion DM. Determination of muscle mitochondrial respiratory capacity in Standardbred racehorses as an aid to predicting exertional rhabdomyolysis.. Mitochondrion 2015;24:99–104.
    doi: 10.1016/j.mito.2015.07.006pubmed: 26219220google scholar: lookup
  16. Khatri P, Sirota M, Butte AJ. Ten years of pathway analysis: Current approaches and outstanding challenges.. PLoS Comput. Biol. 2012;8:e1002375.
    doi: 10.1371/journal.pcbi.1002375pmc: PMC3285573pubmed: 22383865google scholar: lookup
  17. Murphy S, Dowling P, Zweyer M, Mundegar RR, Henry M, Meleady P, Swandulla D, Ohlendieck K. Proteomic analysis of dystrophin deficiency and associated changes in the aged mdx-4cv heart model of dystrophinopathy-related cardiomyopathy.. J. Proteom. 2016;145:24–36.
    doi: 10.1016/j.jprot.2016.03.011pubmed: 26961938google scholar: lookup
  18. Capitanio D, Moriggi M, Torretta E, Barbacini P, De Palma S, Vigano A, Lochmuller H, Muntoni F, Ferlini A, Mora M. Comparative proteomic analyses of Duchenne muscular dystrophy and Becker muscular dystrophy muscles: Changes contributing to preserve muscle function in Becker muscular dystrophy patients.. J. Cachexia Sarcopenia Muscle 2020;11:547–563.
    doi: 10.1002/jcsm.12527pmc: PMC7113522pubmed: 31991054google scholar: lookup
  19. Lindholm A, Piehl K. Fibre composition, enzyme activity and concentrations of metabolites and electrolytes in muscles of standardbred horses.. Acta Vet. Scand. 1974;15:287–309.
    doi: 10.1186/BF03547460pmc: PMC8407315pubmed: 4137664google scholar: lookup
  20. Cumming JKF, Mahon M. Color Atlas of Muscle Pathology.. Mosby-Wolfe; London, UK: 1994.
  21. Valberg SJ, Nicholson AM, Lewis SS, Reardon RA, Finno CJ. Clinical and histopathological features of myofibrillar myopathy in Warmblood horses.. Equine Vet. J. 2017;49:739–745.
    doi: 10.1111/evj.12702pmc: PMC5640499pubmed: 28543538google scholar: lookup
  22. Blomstrand E, Ekblom B. The needle biopsy technique for fibre type determination in human skeletal muscle—A methodological study.. Acta Physiol. Scand. 1982;116:437–442.
    doi: 10.1111/j.1748-1716.1982.tb07163.xpubmed: 6221506google scholar: lookup
  23. Williams ZJ, Velez-Irizarry D, Petersen JL, Ochala J, Finno CJ, Valberg SJ. Candidate gene expression and coding sequence variants in Warmblood horses with myofibrillar myopathy.. Equine Vet. J. 2021;53:306–315.
    doi: 10.1111/evj.13286pmc: PMC7864122pubmed: 32453872google scholar: lookup
  24. Smeds L, Künstner A. ConDeTri-a content dependent read trimmer for Illumina data.. PLoS ONE 2011;6:e26314.
    doi: 10.1371/journal.pone.0026314pmc: PMC3198461pubmed: 22039460google scholar: lookup
  25. Kim D, Paggi JM, Park C, Bennett C, Salzberg SL. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype.. Nat. Biotechnol. 2019;37:907–915.
    doi: 10.1038/s41587-019-0201-4pmc: PMC7605509pubmed: 31375807google scholar: lookup
  26. Pertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads.. Nat. Biotechnol. 2015;33:290–295.
    doi: 10.1038/nbt.3122pmc: PMC4643835pubmed: 25690850google scholar: lookup
  27. Bolger AM, Lohse M, Usadel B. Trimmomatic: A flexible trimmer for Illumina sequence data.. Bioinformatics 2014;30:2114–2120.
    doi: 10.1093/bioinformatics/btu170pmc: PMC4103590pubmed: 24695404google scholar: lookup
  28. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, 1000 Genome Project Data Processing Subgroup. The Sequence Alignment/Map format and SAMtools.. Bioinformatics 2009;25:2078–2079.
    doi: 10.1093/bioinformatics/btp352pmc: PMC2723002pubmed: 19505943google scholar: lookup
  29. Anders S, Pyl PT, Huber W. HTSeq—A Python framework to work with high-throughput sequencing data.. Bioinformatics 2015;31:166–169.
    doi: 10.1093/bioinformatics/btu638pmc: PMC4287950pubmed: 25260700google scholar: lookup
  30. Robinson MD, Oshlack A. A scaling normalization method for differential expression analysis of RNA-seq data.. Genome Biol. 2010;11:R25.
    doi: 10.1186/gb-2010-11-3-r25pmc: PMC2864565pubmed: 20196867google scholar: lookup
  31. Robinson MD, McCarthy DJ, Smyth GK. edgeR: A Bioconductor package for differential expression analysis of digital gene expression data.. Bioinformatics 2010;26:139–140.
    doi: 10.1093/bioinformatics/btp616pmc: PMC2796818pubmed: 19910308google scholar: lookup
  32. Law CW, Chen Y, Shi W, Smyth GK. voom: Precision weights unlock linear model analysis tools for RNA-seq read counts.. Genome Biol. 2014;15:R29.
    doi: 10.1186/gb-2014-15-2-r29pmc: PMC4053721pubmed: 24485249google scholar: lookup
  33. Liu R, Holik AZ, Su S, Jansz N, Chen K, Leong HS, Blewitt ME, Asselin-Labat ML, Smyth GK, Ritchie ME. Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses.. Nucleic Acids Res. 2015;43:e97.
    doi: 10.1093/nar/gkv412pmc: PMC4551905pubmed: 25925576google scholar: lookup
  34. McCarthy DJ, Chen Y, Smyth GK. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation.. Nucleic Acids Res. 2012;40:4288–4297.
    doi: 10.1093/nar/gks042pmc: PMC3378882pubmed: 22287627google scholar: lookup
  35. McCarthy DJ, Smyth GK. Testing significance relative to a fold-change threshold is a TREAT.. Bioinformatics 2009;25:765–771.
    doi: 10.1093/bioinformatics/btp053pmc: PMC2654802pubmed: 19176553google scholar: lookup
  36. Yu G, Wang LG, Han Y, He QY. clusterProfiler: An R package for comparing biological themes among gene clusters.. OMICS A J. Integr. Biol. 2012;16:284–287.
    doi: 10.1089/omi.2011.0118pmc: PMC3339379pubmed: 22455463google scholar: lookup
  37. Branson OE, Freitas MA. A multi-model statistical approach for proteomic spectral count quantitation.. J. Proteom. 2016;144:23–32.
    doi: 10.1016/j.jprot.2016.05.032pmc: PMC4967010pubmed: 27260494google scholar: lookup
  38. Min EJ, Safo SE, Long Q. Penalized co-inertia analysis with applications to—Omics data.. Bioinformatics 2019;35:1018–1025.
    doi: 10.1093/bioinformatics/bty726pmc: PMC6419918pubmed: 30165424google scholar: lookup
  39. Kanehisa M, Goto S. KEGG: Kyoto encyclopedia of genes and genomes.. Nucleic Acids Res. 2000;28:27–30.
    doi: 10.1093/nar/28.1.27pmc: PMC102409pubmed: 10592173google scholar: lookup
  40. Yu G, He QY. ReactomePA: An R/Bioconductor package for reactome pathway analysis and visualization.. Mol. Biosyst. 2016;12:477–479.
    doi: 10.1039/C5MB00663Epubmed: 26661513google scholar: lookup
  41. Yu G, Wang LG, Yan GR, He QY. DOSE: An R/Bioconductor package for disease ontology semantic and enrichment analysis.. Bioinformatics 2015;31:608–609.
    doi: 10.1093/bioinformatics/btu684pubmed: 25677125google scholar: lookup
  42. Carlson M. Genome Wide Annotation for Human.. Bioconductor 2019.
    doi: 10.18129/B9.bioc.org.Hs.eg.dbgoogle scholar: lookup
  43. Farries G, Bryan K, McGivney CL, McGettigan PA, Gough KF, Browne JA, MacHugh DE, Katz LM, Hill EW. Expression Quantitative Trait Loci in Equine Skeletal Muscle Reveals Heritable Variation in Metabolism and the Training Responsive Transcriptome.. Front. Genet. 2019;10:1215.
    doi: 10.3389/fgene.2019.01215pmc: PMC6902038pubmed: 31850069google scholar: lookup
  44. Kanehisa M. Toward understanding the origin and evolution of cellular organisms.. Protein Sci. 2019;28:1947–1951.
    doi: 10.1002/pro.3715pmc: PMC6798127pubmed: 31441146google scholar: lookup
  45. Pandey R, Riley CL, Mills EM, Tiziani S. Highly sensitive and selective determination of redox states of coenzymes Q9 and Q10 in mice tissues: Application of orbitrap mass spectrometry.. Anal Chim Acta 2018;1011:68–76.
    doi: 10.1016/j.aca.2018.01.066pmc: PMC5831383pubmed: 29475487google scholar: lookup
  46. Chen Z, Putt DA, Lash LH. Enrichment and functional reconstitution of glutathione transport activity from rabbit kidney mitochondria: Further evidence for the role of the dicarboxylate and 2-oxoglutarate carriers in mitochondrial glutathione transport.. Arch Biochem. Biophys. 2000;373:193–202.
    doi: 10.1006/abbi.1999.1527pubmed: 10620338google scholar: lookup
  47. Witherspoon JW, Meilleur KG. Review of RyR1 pathway and associated pathomechanisms.. Acta Neuropathol. Commun. 2016;4:121.
    doi: 10.1186/s40478-016-0392-6pmc: PMC5114830pubmed: 27855725google scholar: lookup
  48. Munro ML, Jayasinghe ID, Wang Q, Quick A, Wang W, Baddeley D, Wehrens XH, Soeller C. Junctophilin-2 in the nanoscale organisation and functional signalling of ryanodine receptor clusters in cardiomyocytes.. J. Cell Sci. 2016;129:4388–4398.
    doi: 10.1242/jcs.196873pmc: PMC5201013pubmed: 27802169google scholar: lookup
  49. Arcuri C, Giambanco I, Bianchi R, Donato R. Subcellular localization of S100A11 (S100C, calgizzarin) in developing and adult avian skeletal muscles.. Biochim. Biophys. Acta. 2002;1600:84–94.
    doi: 10.1016/S1570-9639(02)00448-Xpubmed: 12445463google scholar: lookup
  50. Lee KJ, Hyun C, Woo JS, Park CS, Kim DH, Lee EH. Stromal interaction molecule 1 (STIM1) regulates sarcoplasmic/endoplasmic reticulum Ca2+-ATPase 1a (SERCA1a) in skeletal muscle.. Pflug. Arch. 2014;466:987–1001.
    doi: 10.1007/s00424-013-1361-6pubmed: 24077737google scholar: lookup
  51. Valberg SJ, Soave K, Williams ZJ, Perumbakkam S, Schott M, Finno CJ, Petersen JL, Fenger C, Autry JM, Thomas DD. Coding sequences of sarcoplasmic reticulum calcium ATPase regulatory peptides and expression of calcium regulatory genes in recurrent exertional rhabdomyolysis.. J. Vet. Intern. Med. 2019;33:933–941.
    doi: 10.1111/jvim.15425pmc: PMC6430904pubmed: 30720217google scholar: lookup
  52. Cheng AJ, Andersson DC, Lanner JT. Can’t live with or without it: Calcium and its role in Duchenne muscular dystrophy-induced muscle weakness. Focus on “SERCA1 overexpression minimizes skeletal muscle damage in dystrophic mouse models”.. Am. J. Physiol. Cell Physiol. 2015;308:C697–C698.
    doi: 10.1152/ajpcell.00056.2015pubmed: 25740154google scholar: lookup
  53. Valberg S, Essen Gustavsson B, Skoglund Wallberg H. Oxidative capacity of skeletal muscle fibres in racehorses: Histochemical versus biochemical analysis.. Equine Vet. J. 1988;20:291–295.
    doi: 10.1111/j.2042-3306.1988.tb01527.xpubmed: 3168990google scholar: lookup
  54. Roneus M, Essen-Gustavsson B, Lindholm A, Persson SG. Skeletal muscle characteristics in young trained and untrained standardbred trotters.. Equine Vet. J. 1992;24:292–294.
    doi: 10.1111/j.2042-3306.1992.tb02838.xpubmed: 1499537google scholar: lookup
  55. Roneus N, Essen-Gustavsson B, Lindholm A, Eriksson Y. Plasma lactate response to submaximal and maximal exercise tests with training, and its relationship to performance and muscle characteristics in standardbred trotters.. Equine Vet. J. 1994;26:117–121.
    doi: 10.1111/j.2042-3306.1994.tb04348.xpubmed: 8575372google scholar: lookup
  56. Valberg S. Muscling in on the cause of tying up. Proceedings of the 58th Annual Convention of the American Association of Equine Practitioners; Anaheim, CA, USA. 1–5 December 2012; pp. 85–123.
  57. Weins A, Schwarz K, Faul C, Barisoni L, Linke WA, Mundel P. Differentiation- and stress-dependent nuclear cytoplasmic redistribution of myopodin, a novel actin-bundling protein.. J. Cell Biol. 2001;155:393–404.
    doi: 10.1083/jcb.200012039pmc: PMC2150840pubmed: 11673475google scholar: lookup
  58. Frank D, Frey N. Cardiac Z-disc signaling network.. J. Biol. Chem. 2011;286:9897–9904.
    doi: 10.1074/jbc.R110.174268pmc: PMC3060542pubmed: 21257757google scholar: lookup
  59. Kostek MC, Chen YW, Cuthbertson DJ, Shi R, Fedele MJ, Esser KA, Rennie MJ. Gene expression responses over 24 h to lengthening and shortening contractions in human muscle: Major changes in CSRP3, MUSTN1, SIX1, and FBXO32.. Physiol. Genom. 2007;31:42–52.
    doi: 10.1152/physiolgenomics.00151.2006pubmed: 17519359google scholar: lookup
  60. Richard E, Gallego-Villar L, Rivera-Barahona A, Oyarzabal A, Perez B, Rodriguez-Pombo P, Desviat LR. Altered Redox Homeostasis in Branched-Chain Amino Acid Disorders, Organic Acidurias, and Homocystinuria.. Oxid. Med. Cell. Longev. 2018;2018:1246069.
    doi: 10.1155/2018/1246069pmc: PMC5884027pubmed: 29743968google scholar: lookup
  61. Kinnunen S, Hyyppa S, Lappalainen J, Oksala N, Venojarvi M, Nakao C, Hanninen O, Sen CK, Atalay M. Exercise-induced oxidative stress and muscle stress protein responses in trotters.. Eur. J. Appl. Physiol. 2005;93:496–501.
    doi: 10.1007/s00421-004-1162-xpubmed: 15221402google scholar: lookup
  62. Bruce M, Constantin-Teodosiu D, Greenhaff PL, Boobis LH, Williams C, Bowtell JL. Glutamine supplementation promotes anaplerosis but not oxidative energy delivery in human skeletal muscle.. Am. J. Physiol. Endocrinol. Metab. 2001;280:E669–E675.
    doi: 10.1152/ajpendo.2001.280.4.E669pubmed: 11254475google scholar: lookup
  63. Peterson JM, Bakkar N, Guttridge DC. NF-kappaB signaling in skeletal muscle health and disease.. Curr. Top. Dev. Biol. 2011;96:85–119.
    doi: 10.1016/B978-0-12-385940-2.00004-8pubmed: 21621068google scholar: lookup
  64. Di Rosa M, Malaguarnera G, De Gregorio C, Drago F, Malaguarnera L. Evaluation of CHI3L-1 and CHIT-1 expression in differentiated and polarized macrophages.. Inflammation 2013;36:482–492.
    doi: 10.1007/s10753-012-9569-8pubmed: 23149946google scholar: lookup
  65. Lombardo SD, Mazzon E, Mangano K, Basile MS, Cavalli E, Mammana S, Fagone P, Nicoletti F, Petralia MC. Transcriptomic Analysis Reveals Involvement of the Macrophage Migration Inhibitory Factor Gene Network in Duchenne Muscular Dystrophy.. Genes 2019;10:939.
    doi: 10.3390/genes10110939pmc: PMC6896047pubmed: 31752120google scholar: lookup
  66. Ullah HMA, Elfadl AK, Park S, Kim YD, Chung MJ, Son JY, Yun HH, Park JM, Yim JH, Jung SJ. Nogo-A Is Critical for Pro-Inflammatory Gene Regulation in Myocytes and Macrophages.. Cells 2021;10:282.
    doi: 10.3390/cells10020282pmc: PMC7912613pubmed: 33572505google scholar: lookup
  67. Ciciliot S, Schiaffino S. Regeneration of mammalian skeletal muscle. Basic mechanisms and clinical implications.. Curr. Pharm. Des. 2010;16:906–914.
    doi: 10.2174/138161210790883453pubmed: 20041823google scholar: lookup
  68. Tidball JG, Villalta SA. Regulatory interactions between muscle and the immune system during muscle regeneration.. Am. J. Physiol. Regul. Integr. Comp. Physiol. 2010;298:R1173–R1187.
    doi: 10.1152/ajpregu.00735.2009pmc: PMC2867520pubmed: 20219869google scholar: lookup
  69. Folker ES, Baylies MK. Nuclear positioning in muscle development and disease.. Front. Physiol. 2013;4:363.
    doi: 10.3389/fphys.2013.00363pmc: PMC3859928pubmed: 24376424google scholar: lookup
  70. Roman W, Gomes ER. Nuclear positioning in skeletal muscle.. Semin. Cell Dev. Biol. 2018;82:51–56.
    doi: 10.1016/j.semcdb.2017.11.005pubmed: 29241690google scholar: lookup
  71. Valberg SJ, Mickelson JR, Gallant EM, MacLeay JM, Lentz L, de la Corte F. Exertional rhabdomyolysis in quarter horses and thoroughbreds: One syndrome, multiple aetiologies.. Equine Vet. J. 1999;31:533–538.
    doi: 10.1111/j.2042-3306.1999.tb05279.xpubmed: 10659313google scholar: lookup
  72. Randazzo D, Khalique U, Belanto JJ, Kenea A, Talsness DM, Olthoff JT, Tran MD, Zaal KJ, Pak K, Pinal-Fernandez I. Persistent upregulation of the beta-tubulin tubb6, linked to muscle regeneration, is a source of microtubule disorganization in dystrophic muscle.. Hum. Mol. Genet. 2019;28:1117–1135.
    doi: 10.1093/hmg/ddy418pmc: PMC6423419pubmed: 30535187google scholar: lookup
  73. Chandramouli K, Qian PY. Proteomics: Challenges, techniques and possibilities to overcome biological sample complexity.. Hum. Genom. Proteom. 2009;2009:239204.
    doi: 10.4061/2009/239204pmc: PMC2950283pubmed: 20948568google scholar: lookup
  74. McGivney BA, Eivers SS, MacHugh DE, MacLeod JN, O’Gorman GM, Park SD, Katz LM, Hill EW. Transcriptional adaptations following exercise in thoroughbred horse skeletal muscle highlights molecular mechanisms that lead to muscle hypertrophy.. BMC Genom. 2009;10:638.
    doi: 10.1186/1471-2164-10-638pmc: PMC2812474pubmed: 20042072google scholar: lookup
  75. Van Pelt DW, Kharaz YA, Sarver DC, Eckhardt LR, Dzierzawski JT, Disser NP, Piacentini AN, Comerford E, McDonagh B, Mendias CL. Multiomics analysis of the mdx/mTR mouse model of Duchenne muscular dystrophy.. Connect. Tissue Res. 2021;62:24–39.
    doi: 10.1080/03008207.2020.1791103pubmed: 32664808google scholar: lookup

Citations

This article has been cited 7 times.
  1. Valberg SJ, Williams ZJ, Ames EG, Mickelson JR, Nout-Lomas YS, Landolt G, Sanz M, Gardner K. Aberrant skeletal muscle morphogenesis and myofiber differentiation characterize equine myotonic dystrophy. PLoS One 2026;21(1):e0341655.
    doi: 10.1371/journal.pone.0341655pubmed: 41610137google scholar: lookup
  2. Ren M, Michaelson LP, Mungunsukh O, Bedocs P, Friel L, Cofer K, Dartt CE, Sambuughin N, O'Connor FG. RNA Sequencing on Muscle Biopsies from Exertional Rhabdomyolysis Patients Revealed Down-Regulation of Mitochondrial Function and Enhancement of Extracellular Matrix Composition. Genes (Basel) 2025 Aug 2;16(8).
    doi: 10.3390/genes16080930pubmed: 40869978google scholar: lookup
  3. Connysson M, Jansson A. Starch Allowance and Muscle Enzyme Activity in Healthy Standardbred Trotters Trained by Professional Trainers. J Anim Physiol Anim Nutr (Berl) 2025 Sep;109(5):1130-1137.
    doi: 10.1111/jpn.14127pubmed: 40329464google scholar: lookup
  4. Holmes CM, Babasyan S, Wagner B. Neonatal and maternal upregulation of antileukoproteinase in horses. Front Immunol 2024;15:1395030.
    doi: 10.3389/fimmu.2024.1395030pubmed: 38736885google scholar: lookup
  5. Kruse CJ, Dieu M, Renaud B, François AC, Stern D, Demazy C, Burteau S, Boemer F, Art T, Renard P, Votion DM. New Pathophysiological Insights from Serum Proteome Profiling in Equine Atypical Myopathy. ACS Omega 2024 Feb 13;9(6):6505-6526.
    doi: 10.1021/acsomega.3c06647pubmed: 38371826google scholar: lookup
  6. Reißmann M, Rajavel A, Kokov ZA, Schmitt AO. Identification of Differentially Expressed Genes after Endurance Runs in Karbadian Horses to Determine Candidates for Stress Indicators and Performance Capability. Genes (Basel) 2023 Oct 24;14(11).
    doi: 10.3390/genes14111982pubmed: 38002925google scholar: lookup
  7. Santifort KM, Plonek M, Mandigers PJJ. Clinical Diagnosis of Rhabdomyolysis without Myoglobinuria or Electromyographic Abnormalities in a Dog. Animals (Basel) 2023 May 25;13(11).
    doi: 10.3390/ani13111747pubmed: 37889668google scholar: lookup
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