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Home / Equine Research Bank / Animals (Basel) / Use of Omics Data in Fracture Prediction; a Scoping and Syst...
Animals : an open access journal from MDPI2021; 11(4); 959; doi: 10.3390/ani11040959

Use of Omics Data in Fracture Prediction; a Scoping and Systematic Review in Horses and Humans.

Abstract: Despite many recent advances in imaging and epidemiological data analysis, musculoskeletal injuries continue to be a welfare issue in racehorses. Peptide biomarker studies have failed to consistently predict bone injury. Molecular profiling studies provide an opportunity to study equine musculoskeletal disease. A systematic review of the literature was performed using preferred reporting items for systematic reviews and meta-analyses protocols (PRISMA-P) guidelines to assess the use of miRNA profiling studies in equine and human musculoskeletal injuries. Data were extracted from 40 papers between 2008 and 2020. Three miRNA studies profiling equine musculoskeletal disease were identified, none of which related to equine stress fractures. Eleven papers studied miRNA profiles in osteoporotic human patients with fractures, but differentially expressed miRNAs were not consistent between studies. MicroRNA target prediction programmes also produced conflicting results between studies. Exercise affected miRNA profiles in both horse and human studies (e.g., miR-21 was upregulated by endurance exercise and miR-125b was downregulated by exercise). MicroRNA profiling studies in horses continue to emerge, but as yet, no miRNA profile can reliably predict the occurrence of fractures. It is very important that future studies are well designed to mitigate the effects of variation in sample size, exercise and normalisation methods.
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Publication Date: 2021-03-30 PubMed ID: 33808497PubMed Central: PMC8065418DOI: 10.3390/ani11040959Google 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 article discusses how molecular profiling studies, particularly those involving miRNA, have been used in an attempt to predict bone injuries in horses and humans – an objective that has not been fully accomplished due to inconsistency and variability in results.

Objective and Methodology

  • The study aims to review and assess the use of miRNA profiling studies in predicting musculoskeletal injuries in both horses and humans.
  • A systematic review is conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) guidelines. This approach ensures that the review is thorough, standardized, and of high quality.
  • The review involved extracting data from 40 papers published between 2008 and 2020. The articles chosen were those that primarily studied miRNA profiles linked to musculoskeletal diseases.

Findings

  • Out of the 40 papers, only three were found to study miRNA profiles connected to equine musculoskeletal disease. However, none offered relevant insight into equine stress fractures – a common injury in racehorses.
  • Eleven papers had studied miRNA profiles in osteoporotic human patients with fractures. Nevertheless, the identified differentially expressed miRNAs were inconsistent across the studies.
  • In terms of fitness activities, miRNA profiles did show alterations in both horse and human subjects following exercise. For example, miR-21 was found to increase following endurance exercise, while miR-125b was found to decrease.

Limitations and Future Directions

  • The research highlighted that miRNA profiling is still evolving in the field of fracture prediction, with no profile having demonstrated a reliable ability to anticipate fracture occurrence to date.
  • Large variations in sample size, normalization methods, and the exercise undertaken by subjects were identified as major contributing factors to inconsistent findings across studies.
  • The study encourages future research to be more meticulously designed so as to negate the variability caused by these factors. Such careful planning is projected to lead to more consistent results, enhancing the practical use of miRNA profiling in fracture prediction.

Cite This Article

APA
Lee S, Baker ME, Clinton M, Taylor SE. (2021). Use of Omics Data in Fracture Prediction; a Scoping and Systematic Review in Horses and Humans. Animals (Basel), 11(4), 959. https://doi.org/10.3390/ani11040959

Publication

Animals : an open access journal from MDPI
ISSN: 2076-2615
NlmUniqueID: 101635614
Country: Switzerland
Language: English
Volume: 11
Issue: 4
PII: 959

Researcher Affiliations

Lee, Seungmee
  • The Dick Vet Equine Hospital, The Roslin Institute, Easter Bush, Roslin, Midlothian EH25 9RG, UK.
Baker, Melissa E
  • The Dick Vet Equine Hospital, The Roslin Institute, Easter Bush, Roslin, Midlothian EH25 9RG, UK.
Clinton, Michael
  • The RICE Group, Division of Gene Function and Development, The Roslin Institute, Easter Bush, Roslin, Midlothian EH25 9RG, UK.
Taylor, Sarah E
  • The Dick Vet Equine Hospital, The Roslin Institute, Easter Bush, Roslin, Midlothian EH25 9RG, UK.

Grant Funding

  • Prj 790 / Horseracing Betting Levy Board

Conflict of Interest Statement

The authors declare no conflict of interest. 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 88 references
  1. Hitchens PL, Morrice-West AV, Stevenson MA, Whitton RC. Meta-analysis of risk factors for racehorse catastrophic musculoskeletal injury in flat racing.. Vet J 2019 Mar;245:29-40.
    doi: 10.1016/j.tvjl.2018.11.014pubmed: 30819423google scholar: lookup
  2. Allen SE, Rosanowski SM, Stirk AJ, Verheyen KLP. Description of veterinary events and risk factors for fatality in National Hunt flat racing Thoroughbreds in Great Britain (2000-2013).. Equine Vet J 2017 Nov;49(6):700-705.
    doi: 10.1111/evj.12676pubmed: 28235142google scholar: lookup
  3. Rosanowski SM, Chang YM, Stirk AJ, Verheyen KL. Descriptive epidemiology of veterinary events in flat racing Thoroughbreds in Great Britain (2000 to 2013).. Equine Vet J 2017 May;49(3):275-281.
    doi: 10.1111/evj.12592pubmed: 27208544google scholar: lookup
  4. Colgate VA, Marr CM. Science-in-brief: Risk assessment for reducing injuries of the fetlock bones in Thoroughbred racehorses.. Equine Vet J 2020 Jul;52(4):482-488.
    doi: 10.1111/evj.13273pubmed: 32525619google scholar: lookup
  5. Whitton RC, Ayodele BA, Hitchens PL, Mackie EJ. Subchondral bone microdamage accumulation in distal metacarpus of Thoroughbred racehorses.. Equine Vet J 2018 Nov;50(6):766-773.
    doi: 10.1111/evj.12948pubmed: 29660153google scholar: lookup
  6. Tranquille CA, Murray RC, Parkin TD. Can we use subchondral bone thickness on high-field magnetic resonance images to identify Thoroughbred racehorses at risk of catastrophic lateral condylar fracture?. Equine Vet J 2017 Mar;49(2):167-171.
    doi: 10.1111/evj.12574pubmed: 27030308google scholar: lookup
  7. Moreira CA, Bilezikian JP. Stress Fractures: Concepts and Therapeutics.. J Clin Endocrinol Metab 2017 Feb 1;102(2):525-534.
    doi: 10.1210/jc.2016-2720pubmed: 27732325google scholar: lookup
  8. Yu H, Guan Z, Cuk K, Brenner H, Zhang Y. Circulating microRNA biomarkers for lung cancer detection in Western populations.. Cancer Med 2018 Oct;7(10):4849-4862.
    doi: 10.1002/cam4.1782pmc: PMC6198213pubmed: 30259714google scholar: lookup
  9. Peng Q, Zhang X, Min M, Zou L, Shen P, Zhu Y. The clinical role of microRNA-21 as a promising biomarker in the diagnosis and prognosis of colorectal cancer: a systematic review and meta-analysis.. Oncotarget 2017 Jul 4;8(27):44893-44909.
    doi: 10.18632/oncotarget.16488pmc: PMC5546529pubmed: 28415652google scholar: lookup
  10. Zou Y, Jing C, Liu L, Wang T. Serum microRNA-135a as a diagnostic biomarker in non-small cell lung cancer.. Medicine (Baltimore) 2019 Dec;98(50):e17814.
    doi: 10.1097/MD.0000000000017814pmc: PMC6922492pubmed: 31852062google scholar: lookup
  11. Beg MS, Brenner AJ, Sachdev J, Borad M, Kang YK, Stoudemire J, Smith S, Bader AG, Kim S, Hong DS. Phase I study of MRX34, a liposomal miR-34a mimic, administered twice weekly in patients with advanced solid tumors.. Invest New Drugs 2017 Apr;35(2):180-188.
    doi: 10.1007/s10637-016-0407-ypmc: PMC5893501pubmed: 27917453google scholar: lookup
  12. Rupaimoole R, Slack FJ. MicroRNA therapeutics: towards a new era for the management of cancer and other diseases.. Nat Rev Drug Discov 2017 Mar;16(3):203-222.
    doi: 10.1038/nrd.2016.246pubmed: 28209991google scholar: lookup
  13. Janssen HL, Reesink HW, Lawitz EJ, Zeuzem S, Rodriguez-Torres M, Patel K, van der Meer AJ, Patick AK, Chen A, Zhou Y, Persson R, King BD, Kauppinen S, Levin AA, Hodges MR. Treatment of HCV infection by targeting microRNA.. N Engl J Med 2013 May 2;368(18):1685-94.
    doi: 10.1056/NEJMoa1209026pubmed: 23534542google scholar: lookup
  14. Kelch S, Balmayor ER, Seeliger C, Vester H, Kirschke JS, van Griensven M. miRNAs in bone tissue correlate to bone mineral density and circulating miRNAs are gender independent in osteoporotic patients.. Sci Rep 2017 Nov 20;7(1):15861.
    doi: 10.1038/s41598-017-16113-xpmc: PMC5696459pubmed: 29158518google scholar: lookup
  15. Mäkitie RE, Hackl M, Niinimäki R, Kakko S, Grillari J, Mäkitie O. Altered MicroRNA Profile in Osteoporosis Caused by Impaired WNT Signaling.. J Clin Endocrinol Metab 2018 May 1;103(5):1985-1996.
    doi: 10.1210/jc.2017-02585pubmed: 29506076google scholar: lookup
  16. Mandourah AY, Ranganath L, Barraclough R, Vinjamuri S, Hof RV, Hamill S, Czanner G, Dera AA, Wang D, Barraclough DL. Circulating microRNAs as potential diagnostic biomarkers for osteoporosis.. Sci Rep 2018 May 30;8(1):8421.
    doi: 10.1038/s41598-018-26525-ypmc: PMC5976644pubmed: 29849050google scholar: lookup
  17. Seeliger C, Karpinski K, Haug AT, Vester H, Schmitt A, Bauer JS, van Griensven M. Five freely circulating miRNAs and bone tissue miRNAs are associated with osteoporotic fractures.. J Bone Miner Res 2014 Aug;29(8):1718-28.
    doi: 10.1002/jbmr.2175pubmed: 24431276google scholar: lookup
  18. Sun M, Hu L, Wang S, Huang T, Zhang M, Yang M, Zhen W, Yang D, Lu W, Guan M, Peng S. Circulating MicroRNA-19b Identified From Osteoporotic Vertebral Compression Fracture Patients Increases Bone Formation.. J Bone Miner Res 2020 Feb;35(2):306-316.
    doi: 10.1002/jbmr.3892pubmed: 31614022google scholar: lookup
  19. Desjardin C, Vaiman A, Mata X, Legendre R, Laubier J, Kennedy SP, Laloe D, Barrey E, Jacques C, Cribiu EP, Schibler L. Next-generation sequencing identifies equine cartilage and subchondral bone miRNAs and suggests their involvement in osteochondrosis physiopathology.. BMC Genomics 2014 Sep 17;15(1):798.
    doi: 10.1186/1471-2164-15-798pmc: PMC4190437pubmed: 25227120google scholar: lookup
  20. Lecchi C, Dalla Costa E, Lebelt D, Ferrante V, Canali E, Ceciliani F, Stucke D, Minero M. Circulating miR-23b-3p, miR-145-5p and miR-200b-3p are potential biomarkers to monitor acute pain associated with laminitis in horses.. Animal 2018 Feb;12(2):366-375.
    doi: 10.1017/S1751731117001525pubmed: 28689512google scholar: lookup
  21. Watts AE, Millar NL, Platt J, Kitson SM, Akbar M, Rech R, Griffin J, Pool R, Hughes T, McInnes IB, Gilchrist DS. MicroRNA29a Treatment Improves Early Tendon Injury.. Mol Ther 2017 Oct 4;25(10):2415-2426.
    doi: 10.1016/j.ymthe.2017.07.015pmc: PMC5628866pubmed: 28822690google scholar: lookup
  22. Balaskas P, Green JA, Haqqi TM, Dyer P, Kharaz YA, Fang Y, Liu X, Welting TJM, Peffers MJ. Small Non-Coding RNAome of Ageing Chondrocytes.. Int J Mol Sci 2020 Aug 7;21(16).
    doi: 10.3390/ijms21165675pmc: PMC7461137pubmed: 32784773google scholar: lookup
  23. Castanheira C, Balaskas P, Falls C, Ashraf-Kharaz Y, Clegg P, Burke K, Fang Y, Dyer P, Welting TJM, Peffers MJ. Equine synovial fluid small non-coding RNA signatures in early osteoarthritis.. BMC Vet Res 2021 Jan 9;17(1):26.
    doi: 10.1186/s12917-020-02707-7pmc: PMC7796526pubmed: 33422071google scholar: lookup
  24. Riasat K, Bardell D, Goljanek-Whysall K, Clegg PD, Peffers MJ. Epigenetic mechanisms in Tendon Ageing.. Br Med Bull 2020 Oct 14;135(1):90-107.
    doi: 10.1093/bmb/ldaa023pmc: PMC7585832pubmed: 32827252google scholar: lookup
  25. Innes JF, Clegg P. Comparative rheumatology: what can be learnt from naturally occurring musculoskeletal disorders in domestic animals?. Rheumatology (Oxford) 2010 Jun;49(6):1030-9.
    doi: 10.1093/rheumatology/kep465pubmed: 20176567google scholar: lookup
  26. Boyde A. The real response of bone to exercise.. J Anat 2003 Aug;203(2):173-89.
    doi: 10.1046/j.1469-7580.2003.00213.xpmc: PMC1571152pubmed: 12924818google scholar: lookup
  27. Hollis AR, Starkey MP. MicroRNAs in equine veterinary science.. Equine Vet J 2018 Nov;50(6):721-726.
    doi: 10.1111/evj.12954pubmed: 29672919google scholar: lookup
  28. van der Kolk JH, Pacholewska A, Gerber V. The role of microRNAs in equine medicine: a review.. Vet Q 2015 Jun;35(2):88-96.
    doi: 10.1080/01652176.2015.1021186pubmed: 25695624google scholar: lookup
  29. Harris JD, Quatman CE, Manring MM, Siston RA, Flanigan DC. How to write a systematic review.. Am J Sports Med 2014 Nov;42(11):2761-8.
    doi: 10.1177/0363546513497567pubmed: 23925575google scholar: lookup
  30. Shamseer L, Moher D, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation.. BMJ 2015 Jan 2;350:g7647.
    doi: 10.1136/bmj.g7647pubmed: 25555855google scholar: lookup
  31. Witwer KW, Halushka MK. Toward the promise of microRNAs - Enhancing reproducibility and rigor in microRNA research.. RNA Biol 2016 Nov;13(11):1103-1116.
    doi: 10.1080/15476286.2016.1236172pmc: PMC5100345pubmed: 27645402google scholar: lookup
  32. Kocijan R, Muschitz C, Geiger E, Skalicky S, Baierl A, Dormann R, Plachel F, Feichtinger X, Heimel P, Fahrleitner-Pammer A, Grillari J, Redl H, Resch H, Hackl M. Circulating microRNA Signatures in Patients With Idiopathic and Postmenopausal Osteoporosis and Fragility Fractures.. J Clin Endocrinol Metab 2016 Nov;101(11):4125-4134.
    doi: 10.1210/jc.2016-2365pubmed: 27552543google scholar: lookup
  33. Weilner S, Skalicky S, Salzer B, Keider V, Wagner M, Hildner F, Gabriel C, Dovjak P, Pietschmann P, Grillari-Voglauer R, Grillari J, Hackl M. Differentially circulating miRNAs after recent osteoporotic fractures can influence osteogenic differentiation.. Bone 2015 Oct;79:43-51.
    doi: 10.1016/j.bone.2015.05.027pubmed: 26026730google scholar: lookup
  34. Curtis L, Burford JH, England GCW, Freeman SL. Risk factors for acute abdominal pain (colic) in the adult horse: A scoping review of risk factors, and a systematic review of the effect of management-related changes.. PLoS One 2019;14(7):e0219307.
    doi: 10.1371/journal.pone.0219307pmc: PMC6622499pubmed: 31295284google scholar: lookup
  35. Piscopo P, Lacorte E, Feligioni M, Mayer F, Crestini A, Piccolo L, Bacigalupo I, Filareti M, Ficulle E, Confaloni A, Vanacore N, Corbo M. MicroRNAs and mild cognitive impairment: A systematic review.. Ageing Res Rev 2019 Mar;50:131-141.
    doi: 10.1016/j.arr.2018.11.005pubmed: 30472218google scholar: lookup
  36. Aromataris E.M.Z.E.. JBI Manual for Evidence Synthesis. JBI; Adelaide, SA, Australia: 2020.
  37. National Institute for Health and Care Excellence. Methods for the Development of NICE Public Health Guidance. National Institute for Health and Care Excellence; London, UK: 2012.
  38. Alonso-Coello P, Schünemann HJ, Moberg J, Brignardello-Petersen R, Akl EA, Davoli M, Treweek S, Mustafa RA, Rada G, Rosenbaum S, Morelli A, Guyatt GH, Oxman AD. GRADE Evidence to Decision (EtD) frameworks: a systematic and transparent approach to making well informed healthcare choices. 1: Introduction.. BMJ 2016 Jun 28;353:i2016.
    doi: 10.1136/bmj.i2016pubmed: 27353417google scholar: lookup
  39. Bowen IM, Redpath A, Dugdale A, Burford JH, Lloyd D, Watson T, Hallowell GD. BEVA primary care clinical guidelines: Analgesia.. Equine Vet J 2020 Jan;52(1):13-27.
    doi: 10.1111/evj.13198pubmed: 31657050google scholar: lookup
  40. Frisbie DD, Mc Ilwraith CW, Arthur RM, Blea J, Baker VA, Billinghurst RC. Serum biomarker levels for musculoskeletal disease in two- and three-year-old racing Thoroughbred horses: A prospective study of 130 horses.. Equine Vet J 2010 Oct;42(7):643-51.
    doi: 10.1111/j.2042-3306.2010.00123.xpubmed: 20840580google scholar: lookup
  41. Jackson BF, Dyson PK, Lonnell C, Verheyen KL, Pfeiffer DU, Price JS. Bone biomarkers and risk of fracture in two- and three-year-old Thoroughbreds.. Equine Vet J 2009 Apr;41(4):410-3.
    doi: 10.2746/042516409X416206pubmed: 19562906google scholar: lookup
  42. Jackson BF, Reed SR, Price JS, Verheyen KL. Relationship between serum biomarkers of cartilage and bone metabolism and joint injury in young Thoroughbred racehorses in training.. Am J Vet Res 2015 Aug;76(8):679-87.
    doi: 10.2460/ajvr.76.8.679pubmed: 26207965google scholar: lookup
  43. Turlo AJ, Cywinska A, Frisbie DD. Revisiting predictive biomarkers of musculoskeletal injury in thoroughbred racehorses: longitudinal study in polish population.. BMC Vet Res 2019 Feb 26;15(1):66.
    doi: 10.1186/s12917-019-1799-7pmc: PMC6390350pubmed: 30808359google scholar: lookup
  44. Arens AM, Puchalski SM, Whitcomb MB, Bell R, Gardner IA, Stover SM. Comparison of the use of scapular ultrasonography, physical examination, and measurement of serum biomarkers of bone turnover versus scintigraphy for detection of bone fragility syndrome in horses.. J Am Vet Med Assoc 2013 Jan 1;242(1):76-85.
    doi: 10.2460/javma.242.1.76pubmed: 23234285google scholar: lookup
  45. Cleary OB, Trumble TN, Merritt KA, Brown MP. Effect of exercise and osteochondral injury on synovial fluid and serum concentrations of carboxy-terminal telopeptide fragments of type II collagen in racehorses.. Am J Vet Res 2010 Jan;71(1):33-40.
    doi: 10.2460/ajvr.71.1.33pubmed: 20043778google scholar: lookup
  46. Arai K, Tagami M, Hatazoe T, Nishimatsu E, Shimizu Y, Fujiki M, Misumi K. Analysis of cartilage oligomeric matrix protein (COMP) in synovial fluid, serum and urine from 51 racehorses with carpal bone fracture.. J Vet Med Sci 2008 Sep;70(9):915-21.
    doi: 10.1292/jvms.70.915pubmed: 18840965google scholar: lookup
  47. Zavodovskaya R, Stover SM, Murphy BG, Katzman S, Durbin-Johnson B, Britton M, Finno CJ. Bone formation transcripts dominate the differential gene expression profile in an equine osteoporotic condition associated with pulmonary silicosis.. PLoS One 2018;13(6):e0197459.
    doi: 10.1371/journal.pone.0197459pmc: PMC5983561pubmed: 29856822google scholar: lookup
  48. Kuemmerle JM, Theiss F, Okoniewski MJ, Weber FA, Hemmi S, Mirsaidi A, Richards PJ, Cinelli P. Identification of Novel Equine (Equus caballus) Tendon Markers Using RNA Sequencing.. Genes (Basel) 2016 Nov 10;7(11).
    doi: 10.3390/genes7110097pmc: PMC5126783pubmed: 27834918google scholar: lookup
  49. Sansoni V, Perego S, Vernillo G, Barbuti A, Merati G, La Torre A, Banfi G, Lombardi G. Effects of repeated sprints training on fracture risk-associated miRNA.. Oncotarget 2018 Apr 6;9(26):18029-18040.
    doi: 10.18632/oncotarget.24707pmc: PMC5915055pubmed: 29719588google scholar: lookup
  50. Cappelli K, Capomaccio S, Viglino A, Silvestrelli M, Beccati F, Moscati L, Chiaradia E. Circulating miRNAs as Putative Biomarkers of Exercise Adaptation in Endurance Horses.. Front Physiol 2018;9:429.
    doi: 10.3389/fphys.2018.00429pmc: PMC5928201pubmed: 29740341google scholar: lookup
  51. 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
  52. Horak M, Zlamal F, Iliev R, Kucera J, Cacek J, Svobodova L, Hlavonova Z, Kalina T, Slaby O, Bienertova-Vasku J. Exercise-induced circulating microRNA changes in athletes in various training scenarios.. PLoS One 2018;13(1):e0191060.
    doi: 10.1371/journal.pone.0191060pmc: PMC5770042pubmed: 29338015google scholar: lookup
  53. McGivney BA, Griffin ME, Gough KF, McGivney CL, Browne JA, Hill EW, Katz LM. Evaluation of microRNA expression in plasma and skeletal muscle of thoroughbred racehorses in training.. BMC Vet Res 2017 Nov 22;13(1):347.
    doi: 10.1186/s12917-017-1277-zpmc: PMC5700565pubmed: 29166903google scholar: lookup
  54. Håkansson KEJ, Sollie O, Simons KH, Quax PHA, Jensen J, Nossent AY. Circulating Small Non-coding RNAs as Biomarkers for Recovery After Exhaustive or Repetitive Exercise.. Front Physiol 2018;9:1136.
    doi: 10.3389/fphys.2018.01136pmc: PMC6113669pubmed: 30246800google scholar: lookup
  55. Kim HA, Kim MC, Kim NY, Ryu DY, Lee HS, Kim Y. Integrated analysis of microRNA and mRNA expressions in peripheral blood leukocytes of Warmblood horses before and after exercise.. J Vet Sci 2018 Jan 31;19(1):99-106.
    doi: 10.4142/jvs.2018.19.1.99pmc: PMC5799405pubmed: 28927254google scholar: lookup
  56. Mach N, Plancade S, Pacholewska A, Lecardonnel J, Rivière J, Moroldo M, Vaiman A, Morgenthaler C, Beinat M, Nevot A, Robert C, Barrey E. Integrated mRNA and miRNA expression profiling in blood reveals candidate biomarkers associated with endurance exercise in the horse.. Sci Rep 2016 Mar 10;6:22932.
    doi: 10.1038/srep22932pmc: PMC4785432pubmed: 26960911google scholar: lookup
  57. Mach N, Ramayo-Caldas Y, Clark A, Moroldo M, Robert C, Barrey E, López JM, Le Moyec L. Understanding the response to endurance exercise using a systems biology approach: combining blood metabolomics, transcriptomics and miRNomics in horses.. BMC Genomics 2017 Feb 17;18(1):187.
    doi: 10.1186/s12864-017-3571-3pmc: PMC5316211pubmed: 28212624google scholar: lookup
  58. Stefaniuk-Szmukier M, Ropka-Molik K, Piórkowska K, Bugno-Poniewierska M. The expression profile of genes involved in osteoclastogenesis detected in whole blood of Arabian horses during 3 years of competing at race track.. Res Vet Sci 2019 Apr;123:59-64.
    doi: 10.1016/j.rvsc.2018.12.013pubmed: 30586653google scholar: lookup
  59. Stefaniuk-Szmukier M, Ropka-Molik K, Piórkowska K, Żukowski K, Bugno-Poniewierska M. Transcriptomic hallmarks of bone remodelling revealed by RNA-Seq profiling in blood of Arabian horses during racing training regime.. Gene 2018 Nov 15;676:256-262.
    doi: 10.1016/j.gene.2018.07.040pubmed: 30021131google scholar: lookup
  60. Blott SC, Swinburne JE, Sibbons C, Fox-Clipsham LY, Helwegen M, Hillyer L, Parkin TD, Newton JR, Vaudin M. A genome-wide association study demonstrates significant genetic variation for fracture risk in Thoroughbred racehorses.. BMC Genomics 2014 Feb 21;15:147.
    doi: 10.1186/1471-2164-15-147pmc: PMC4008154pubmed: 24559379google scholar: lookup
  61. Chatzipapas C, Boikos S, Drosos GI, Kazakos K, Tripsianis G, Serbis A, Stergiopoulos S, Tilkeridis C, Verettas DA, Stratakis CA. Polymorphisms of the vitamin D receptor gene and stress fractures.. Horm Metab Res 2009 Aug;41(8):635-40.
    doi: 10.1055/s-0029-1216375pmc: PMC3135021pubmed: 19391078google scholar: lookup
  62. Friedman E, Moran DS, Ben-Avraham D, Yanovich R, Atzmon G. Novel candidate genes putatively involved in stress fracture predisposition detected by whole-exome sequencing.. Genet Res (Camb) 2014;96:e004.
    doi: 10.1017/S001667231400007Xpmc: PMC7045058pubmed: 25023003google scholar: lookup
  63. Korvala J, Hartikka H, Pihlajamäki H, Solovieva S, Ruohola JP, Sahi T, Barral S, Ott J, Ala-Kokko L, Männikkö M. Genetic predisposition for femoral neck stress fractures in military conscripts.. BMC Genet 2010 Oct 21;11:95.
    doi: 10.1186/1471-2156-11-95pmc: PMC2975640pubmed: 20961463google scholar: lookup
  64. Varley I, Hughes DC, Greeves JP, Stellingwerff T, Ranson C, Fraser WD, Sale C. The association of novel polymorphisms with stress fracture injury in Elite Athletes: Further insights from the SFEA cohort.. J Sci Med Sport 2018 Jun;21(6):564-568.
    doi: 10.1016/j.jsams.2017.10.038pubmed: 29129460google scholar: lookup
  65. Yanovich R, Friedman E, Milgrom R, Oberman B, Freedman L, Moran DS. Candidate gene analysis in israeli soldiers with stress fractures.. J Sports Sci Med 2012;11(1):147-55.
    pmc: PMC3737837pubmed: 24149131
  66. Feichtinger X, Muschitz C, Heimel P, Baierl A, Fahrleitner-Pammer A, Redl H, Resch H, Geiger E, Skalicky S, Dormann R, Plachel F, Pietschmann P, Grillari J, Hackl M, Kocijan R. Bone-related Circulating MicroRNAs miR-29b-3p, miR-550a-3p, and miR-324-3p and their Association to Bone Microstructure and Histomorphometry.. Sci Rep 2018 Mar 20;8(1):4867.
    doi: 10.1038/s41598-018-22844-2pmc: PMC5861059pubmed: 29559644google scholar: lookup
  67. Yavropoulou MP, Anastasilakis AD, Makras P, Tsalikakis DG, Grammatiki M, Yovos JG. Expression of microRNAs that regulate bone turnover in the serum of postmenopausal women with low bone mass and vertebral fractures.. Eur J Endocrinol 2017 Feb;176(2):169-176.
    doi: 10.1530/EJE-16-0583pubmed: 27836951google scholar: lookup
  68. Feurer E, Kan C, Croset M, Sornay-Rendu E, Chapurlat R. Lack of Association Between Select Circulating miRNAs and Bone Mass, Turnover, and Fractures: Data From the OFELY Cohort.. J Bone Miner Res 2019 Jun;34(6):1074-1085.
    doi: 10.1002/jbmr.3685pubmed: 30830972google scholar: lookup
  69. Zarecki P, Hackl M, Grillari J, Debono M, Eastell R. Serum microRNAs as novel biomarkers for osteoporotic vertebral fractures.. Bone 2020 Jan;130:115105.
    doi: 10.1016/j.bone.2019.115105pubmed: 31669252google scholar: lookup
  70. Panach L, Mifsut D, Tarín JJ, Cano A, García-Pérez MÁ. Serum Circulating MicroRNAs as Biomarkers of Osteoporotic Fracture.. Calcif Tissue Int 2015 Nov;97(5):495-505.
    doi: 10.1007/s00223-015-0036-zpubmed: 26163235google scholar: lookup
  71. Ladang A, Beaudart C, Locquet M, Reginster JY, Bruyère O, Cavalier E. Evaluation of a Panel of MicroRNAs that Predicts Fragility Fracture Risk: A Pilot Study.. Calcif Tissue Int 2020 Mar;106(3):239-247.
    doi: 10.1007/s00223-019-00628-8pubmed: 31729554google scholar: lookup
  72. Varley I, Hughes DC, Greeves JP, Stellingwerff T, Ranson C, Fraser WD, Sale C. RANK/RANKL/OPG pathway: genetic associations with stress fracture period prevalence in elite athletes.. Bone 2015 Feb;71:131-6.
    doi: 10.1016/j.bone.2014.10.004pubmed: 25464125google scholar: lookup
  73. Varley I, Greeves JP, Sale C, Friedman E, Moran DS, Yanovich R, Wilson PJ, Gartland A, Hughes DC, Stellingwerff T, Ranson C, Fraser WD, Gallagher JA. Functional polymorphisms in the P2X7 receptor gene are associated with stress fracture injury.. Purinergic Signal 2016 Mar;12(1):103-13.
    doi: 10.1007/s11302-016-9495-6pmc: PMC4749527pubmed: 26825304google scholar: lookup
  74. Dufourd T, Robil N, Mallet D, Carcenac C, Boulet S, Brishoual S, Rabois E, Houeto JL, de la Grange P, Carnicella S. Plasma or serum? A qualitative study on rodents and humans using high-throughput microRNA sequencing for circulating biomarkers.. Biol Methods Protoc 2019;4(1):bpz006.
    doi: 10.1093/biomethods/bpz006pmc: PMC7200924pubmed: 32395624google scholar: lookup
  75. Wang K, Yuan Y, Cho JH, McClarty S, Baxter D, Galas DJ. Comparing the MicroRNA spectrum between serum and plasma.. PLoS One 2012;7(7):e41561.
    doi: 10.1371/journal.pone.0041561pmc: PMC3409228pubmed: 22859996google scholar: lookup
  76. Yokota M, Tatsumi N, Nathalang O, Yamada T, Tsuda I. Effects of heparin on polymerase chain reaction for blood white cells.. J Clin Lab Anal 1999;13(3):133-40.
    doi: 10.1002/(SICI)1098-2825(1999)13:3<133::AID-JCLA8>3.0.CO;2-0pmc: PMC6807949pubmed: 10323479google scholar: lookup
  77. Hebels DG, van Herwijnen MH, Brauers KJ, de Kok TM, Chalkiadaki G, Kyrtopoulos SA, Kleinjans JC. Elimination of heparin interference during microarray processing of fresh and biobank-archived blood samples.. Environ Mol Mutagen 2014 Jul;55(6):482-91.
    doi: 10.1002/em.21869pubmed: 24740823google scholar: lookup
  78. Pizzamiglio S, Zanutto S, Ciniselli CM, Belfiore A, Bottelli S, Gariboldi M, Verderio P. A methodological procedure for evaluating the impact of hemolysis on circulating microRNAs.. Oncol Lett 2017 Jan;13(1):315-320.
    doi: 10.3892/ol.2016.5452pmc: PMC5244842pubmed: 28123561google scholar: lookup
  79. Faraldi M, Gomarasca M, Sansoni V, Perego S, Banfi G, Lombardi G. Normalization strategies differently affect circulating miRNA profile associated with the training status.. Sci Rep 2019 Feb 7;9(1):1584.
    doi: 10.1038/s41598-019-38505-xpmc: PMC6367481pubmed: 30733582google scholar: lookup
  80. de Gonzalo-Calvo D, Dávalos A, Montero A, García-González Á, Tyshkovska I, González-Medina A, Soares SM, Martínez-Camblor P, Casas-Agustench P, Rabadán M, Díaz-Martínez ÁE, Úbeda N, Iglesias-Gutiérrez E. Circulating inflammatory miRNA signature in response to different doses of aerobic exercise.. J Appl Physiol (1985) 2015 Jul 15;119(2):124-34.
    doi: 10.1152/japplphysiol.00077.2015pubmed: 25997943google scholar: lookup
  81. Wardle SL, Bailey ME, Kilikevicius A, Malkova D, Wilson RH, Venckunas T, Moran CN. Plasma microRNA levels differ between endurance and strength athletes.. PLoS One 2015;10(4):e0122107.
    doi: 10.1371/journal.pone.0122107pmc: PMC4400105pubmed: 25881132google scholar: lookup
  82. Smieszek A, Marcinkowska K, Pielok A, Sikora M, Valihrach L, Marycz K. The Role of miR-21 in Osteoblasts-Osteoclasts Coupling In Vitro.. Cells 2020 Feb 19;9(2).
    doi: 10.3390/cells9020479pmc: PMC7072787pubmed: 32093031google scholar: lookup
  83. Li S, Yang X, Yang J, Zhen J, Zhang D. Serum microRNA-21 as a potential diagnostic biomarker for breast cancer: a systematic review and meta-analysis.. Clin Exp Med 2016 Feb;16(1):29-35.
    doi: 10.1007/s10238-014-0332-3pubmed: 25516467google scholar: lookup
  84. Hadjiargyrou M, Komatsu DE. The Therapeutic Potential of MicroRNAs as Orthobiologics for Skeletal Fractures.. J Bone Miner Res 2019 May;34(5):797-809.
    doi: 10.1002/jbmr.3708pmc: PMC6536331pubmed: 30866092google scholar: lookup
  85. Pacholewska A, Mach N, Mata X, Vaiman A, Schibler L, Barrey E, Gerber V. Novel equine tissue miRNAs and breed-related miRNA expressed in serum.. BMC Genomics 2016 Oct 26;17(1):831.
    doi: 10.1186/s12864-016-3168-2pmc: PMC5080802pubmed: 27782799google scholar: lookup
  86. Sharma S, Eghbali M. Influence of sex differences on microRNA gene regulation in disease.. Biol Sex Differ 2014 Feb 1;5(1):3.
    doi: 10.1186/2042-6410-5-3pmc: PMC3912347pubmed: 24484532google scholar: lookup
  87. Gemmati D, Varani K, Bramanti B, Piva R, Bonaccorsi G, Trentini A, Manfrinato MC, Tisato V, Carè A, Bellini T. "Bridging the Gap" Everything that Could Have Been Avoided If We Had Applied Gender Medicine, Pharmacogenetics and Personalized Medicine in the Gender-Omics and Sex-Omics Era.. Int J Mol Sci 2019 Dec 31;21(1).
    doi: 10.3390/ijms21010296pmc: PMC6982247pubmed: 31906252google scholar: lookup
  88. Ryan-Moore E, Mavrommatis Y, Waldron M. Systematic Review and Meta-Analysis of Candidate Gene Association Studies With Fracture Risk in Physically Active Participants.. Front Genet 2020;11:551.
    doi: 10.3389/fgene.2020.00551pmc: PMC7308497pubmed: 32612634google scholar: lookup

Citations

This article has been cited 1 times.
  1. Finno CJ. Science-in-brief: Genomic and transcriptomic approaches to the investigation of equine diseases.. Equine Vet J 2022 Mar;54(2):444-448.
    doi: 10.1111/evj.13549pubmed: 35133024google scholar: lookup
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