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Fracture Prediction: History
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Subjects: Agriculture, Dairy & Animal Science
Contributor: Melissa Baker

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 and potentially discover biomarkers to aid in prediction and diagnosis. 

  • microRNA
  • repetitive load injury
  • bone
  • biomarker
  • RNA-seq
  • SNP
  • Equine
  • Fracture prediction
  • systematic review
  • omics data

1. Introduction

Musculoskeletal injuries in racehorses are common and associated with potential welfare issues. In a recent meta-analysis, the pooled incidence of catastrophic musculoskeletal injury was 1.17 per 1000 race starts [1]. At least one fatal outcome was reported at 21.5% of National Hunt events, with bone injuries being the most common [2]. The majority of deaths reported in this study resulted from injuries to bone (77.8%), and these predominantly involved the distal limb, with the third metacarpal or metatarsal as the most commonly affected structure [2]. Similarly, in flat racing, the majority (77%) of fatalities of Thoroughbreds in Great Britain were associated with a bone injury [3]. Early detection of incomplete fractures can be difficult, and whilst imaging represents the frontline approach to the screening of racehorses, there is currently no consensus about the specific interpretation of various imaging modalities including radiography, nuclear scintigraphy, computed tomography, magnetic resonance imaging and positron emission tomography [4].

Stress fractures arise because of an imbalance between damage accumulation and targeted repair at predictable sites of repetitive bone injury. Despite the progress in advanced imaging, micro-CT [5] and MRI [6] have failed to predict why certain levels of bone densification and microdamage that lack targeted repair go on to propagate to complete fracture in some individuals, yet the same levels are tolerated by others [7].

Omics technologies, genomics, transcriptomics, proteomics and metabolomics represent the study of the molecules, DNA, RNA, protein and metabolites, respectively. Genetic association studies aim to identify if a certain gene (DNA) controls the phenotype of a particular disease. Transcriptomic studies use next generation sequencing to identify if messenger RNA (mRNA) influences a particular disease. MicroRNAs (miRNAs) are small non-coding RNA molecules that are able to influence post-transcriptional gene expression. MicroRNAs have been proposed as potential diagnostic and prognostic biomarkers [8][9] in many diseases, and numerous miRNAs have been shown to be dysregulated in various different types of cancers as oncogenes or tumour suppressor genes [10]. In addition to their potential as biomarkers, miRNAs are being evaluated for their use as therapeutics in some cancers and in treating hepatitis C. Several miRNA-targeted therapeutics in humans have reached clinical trials, including a tumour suppressor miRNA-34a mimic in Phase I clinical trials [11][12] and miR-122 anti-miRNA in Phase II clinical trials for treating hepatitis C infection [13].

As circulating miRNAs have been identified as potential biomarkers of fractures in osteoporosis [14][15][16][17][18] and are beginning to be evaluated in equine orthopaedic disease [19][20][21][22][23][24], the analysis of circulating miRNAs represents an exciting opportunity to study musculoskeletal health, yet currently, there are no standardised pre-analytical, analytical and post-analytical guidelines to allow for comparison between studies. It is therefore timely to conduct a review of the literature. Whilst the aetiopathogenesis of equine stress fractures secondary to repetitive loading is clearly different to that of osteoporotic stress fractures, it was hoped that parallels in study design and analysis could be drawn. The authors chose to consider both equines and humans, as both species sustain stress fractures [25] and their bones have been shown to heal in situ without removal of the damaged domain [26].

Systematic reviews use explicit methods to identify, select, appraise and synthesise results from similar but separate studies to identify high-quality evidence and highlight gaps in the current research. Scoping reviews are essential where there is a large and diverse evidence base, to provide a broad overview of the current evidence and to identify areas suitable for more detailed evaluation in a systematic review. Currently there are only two narrative reviews of miRNA relating to veterinary orthopaedics [27][28], and no published systematic reviews or scoping reviews pertaining to stress fractures. There are a range of different frameworks that have been developed to optimise the process of systematic reviews. Preferred reporting items for systematic reviews and meta-analyses (PRISMA) is widely accepted as the methodological framework for systematic reviews and is recommended by many journals [29][30]. PRISMA provides an evidence-based minimum set of items that should be evaluated and reported, and their resources include a standardised checklist and flow diagram.

It has been recommended that miRNA–RNA interactions should be validated in appropriate biological systems [31]. Analysis of miRNA–target interactions has been performed with respect to bone using the following approaches: (1) target prediction programmes followed by mRNA detection in bone tissue [17]; (2) correlations of differentially expressed miRNAs with bone turnover markers [32]; (3) transfection of cells with miRNA and assessment of in vitro osteogenic potential, such as bone alkaline phosphatase assays and Alizarin red staining [33]; (4) treatment of mice with an agomir of the miRNA of interest and an evaluation of bone density [18].

2. Protocol and Registration

The review followed the methodology described in the Cochrane handbook for systematic reviews and the PRISMA statement for reporting systematic reviews and meta-analyses [29][30]. This protocol was modified based on previously published systematic review papers [34][35]. The preferred reporting items for systematic reviews and meta-analyses protocols (PRISMA-P). The intervention for this scoping and systematic review was stress fractures in horses and the outcome under consideration was the concentration of serum/plasma miRNA in horses. As no literature was identified measuring miRNA in horses with stress fractures, the intervention was broadened to include stress fractures in humans. Stress fractures in horses occur frequently in young athletes during racing or training. Similar injuries also occur in humans, especially elite athletes or military recruits. Since there are only limited miRNA studies in horses, core findings in systematic human studies could also be valuable for a better understanding of the horse studies. Consequently, the outcomes included plasma/serum miRNA concentration in horses and humans. Widening the search for this systematic review was considered appropriate, as stress fractures that occur in young equines also occur in elite athletes and military recruits [25]. When the literature was searched for stress fractures in humans and horses, again there was a paucity of studies. As the objectives of this review included making recommendations regarding blood sampling for miRNA studies with respect to timing of feeding, exercise and haemolysis, the search inclusion criteria were further broadened to include omics studies in normal exercising horses and those with musculoskeletal disease.

3. Synthesis of Outcomes for the Systematic Review

The three primary outcomes were to identify (1a) changes microRNAs/peptide analysis/gene expression related to musculoskeletal injuries in horses, (1b) microRNAs and their targets in response to exercise and mechanical loading in horses and humans and (1c) genetic association studies related to stress fractures in horses and young adults (e.g., athletes/military recruits) equivalent to equine stress fractures. The secondary outcomes were to analyse miRNA and their targets related to osteoporotic fragility fractures in humans.

4. Eligibility Criteria

We included randomised controlled trials (RCTs), and cohort, case-control and cross-sectional studies. We excluded case series, case reports, narrative reviews and textbook chapters. Study definition and categorisation were based on the Joanna Briggs Institute (JBI) reviewer’s manual and methods for the development of the National Institute for Health and Care Excellence (NICE) public health guidance. A randomised controlled trial (RCT) is a study where participants are randomly allocated to receive either the intervention or the control. A quasi-experimental study or non-randomised controlled trial is a study where participants are allocated to receive either the intervention or the control, but the allocation is not randomised, an approach often called a controlled before-and-after or a time-series study. A cohort study is an observational study in which a group of people or animals (cohort) are observed over time in order to see who develops the outcome longitudinally. A case-control study is a study where the investigator selects people or animals who have an outcome of interest (e.g., disease) and others who do not (controls), and then collects data to determine previous exposure to possible causes. A cross-sectional study is an observational study in which the source population is examined to see what proportion has the outcome of interest, or has been exposed to a risk factor of interest, or both [36][37]. A study was included if the full text could be obtained from any of the University of Edinburgh libraries or e-libraries, through University of Edinburgh journal subscriptions, or from free online Open Access sources.

5. microRNAs/Peptide Analysis/Gene Expression Related to Musculoskeletal Injuries in Horses

Reviewing miRNAs and their targets to equine musculoskeletal injuries identified 12 publications including 2 miRNA candidate studies, 1 miRNA profiling study, 2 mRNA profiling studies and 7 biomarker studies (horse peptide biomarker studies prior to 2008 were not reviewed). The three miRNA studies reported on diverse disease processes, tendon injury, laminitis and osteochondrosis, and unsurprisingly, did not report on the same miRNAs. One randomised controlled trial that scored highly in the quality appraisal and risk of bias reported a decrease in miRNA-29a levels in tendon injury, yet it should be remembered that participants were not blinded to treatment assignment. The decrease in miRNA-29a was confirmed using an miR-29a mimic in equine tenocytes, which selectively targeted to COL3A1 encoding type III collagen [21]. Another study reported that levels of miR-23b-3p, miR-145-5p and miR-200b-3p increased in acute laminitis [20]; however, the case-control study of acute laminitis may have been subjected to age biases as the cases were mature horses with laminitis and the controls were immature horses. Targets of these miRNAs were linked to the glutamatergic pathway, which is associated with the major excitatory neurotransmitter released in synapse of the pain-transmitting afferent neurons. Combining the pain-deregulated miRNAs (miR-145-5p and miR-200b-3p) resulted in a positive correlation with horse grimace scores in acute laminitic horses. A further study, with a small sample size, reported a decrease in levels of miR-126-5p, miR-135a-5p, miR-451 and miR-486 in cartilage and an increase in levels of miR-1249 and miR-197 in bone from three 10 month old foals with osteochondrosis compared to three control foals [19].

In terms of peptide biomarker candidate studies for fracture/injury risk factors, three studies [38][39][40] reported a decreased serum level of carboxy-terminal telopeptide fragments of type II collagen (CTX-II) in in 2–3 year old Thoroughbreds following carpal or fetlock joint injuries. However, arthroscopic scores were not correlated with synovial fluid or serum CTX-II in one of these studies [40]. Furthermore, as cohort studies [38][39] the results could be subject to selection bias as a result of horses being lost to follow-up. A separate paper found the two biomarkers CTX-I and bone alkaline phosphatase were not accurate biomarkers for bone fragility syndrome represented by scapula stress fractures [41]. also reported that there was no significant difference between injury and control at the baseline or entry time point. In a longitudinal study, the greatest change of four biomarkers occurred 4–6 month prior to injury: a decrease of articular cartilage biomarkers, glycosaminoglycan (GAGs) and aggrecan chondroitin sulfate 846 epitope (CS486), and an increase in bone biomarkers, CTX-I and osteocalcin [42]. In one recent study [39], decreased osteocalcin and CTX-I, representing altered bone turnover, were specific for injured horses in a population of Polish racehorses in contrast to findings in a North American population.

6. microRNAs and Their Targets in Response to Exercise and Mechanical Loading in Horses and Humans

A review of miRNAs and their targets in response to exercise and mechanical loading in horses and humans identified 11 publications including 5 horse miRNA profiling studies [43][44][45][46][47], 1 human miRNA profiling study [48], 2 human miRNA candidate studies [49][50], 2 horse mRNA profiling studies [51][52] and 1 horse mRNA candidate study [53]. Overall 10 of the 11 studies were quasi-experimental studies, e.g., before and after the intervention (exercise), where miRNAs were measured at two points in time. These were not randomised, and therefore, interpolation should be carried out cautiously to similar populations. The following results should be interpreted with caution, as many of the studies only scored as low on the Grade/vetGRADE pyramid.

The three horse miRNA studies [44][46][47] and one human miRNA study [49] reported an increase in miR-21-5p levels after exercise; although, a further human study [48] reported stable expression of miR-21-5p, even after exercise. These horse studies also reported an increase in levels of members of the let-7 family in response to exercise [44][46][47]. A decrease in levels of miR-16 following an 160 km endurance competition was reported in two of these horse studies [46][47], and a gradual decrease in miR-16 levels followed by explosive strength training was also reported in one human study [49]. Analysis of the predicted genes targeted by miRNAs increased upon exercise (e.g., miR-1, miR-133 and miR-206) [43][50], suggesting the involvement of the muscle remodelling pathway (IGF1R, EGFR, PURB, TAGLN, TMOD2, LASP1 and SGCD) [43]. Two mRNA profiling studies in Arabian horses [53][52] reported that race training or competing in flat races induced an osteoclast differentiation pathway involving CTSK, IL6ST, NFATc1, CLEC5A and VAV3.

This entry is adapted from the peer-reviewed paper 10.3390/ani11040959

References

  1. Hitchens, P.L.; Morrice-West, A.V.; Stevenson, M.A.; Whitton, R.C. Meta-analysis of risk factors for racehorse catastrophic musculoskeletal injury in flat racing. Vet. J. 2019, 245, 29–40.
  2. Allen, S.E.; Rosanowski, S.M.; Stirk, A.J.; Verheyen, K.L.P. Description of veterinary events and risk factors for fatality in National Hunt flat racing Thoroughbreds in Great Britain (2000–2013). Equine Vet. J. 2017, 49, 700–705.
  3. Rosanowski, S.M.; Chang, Y.M.; Stirk, A.J.; Verheyen, K.L.P. Descriptive epidemiology of veterinary events in flat racing Thoroughbreds in Great Britain (2000 to 2013). Equine Vet. J. 2016, 49, 275–281.
  4. Colgate, V.A.; Marr, C.M.; Carpenter, R.; Kawcak, C.; Muir, P.; Palmer, S.; Parkin, T.; Powell, S.; Ramzan, P.; Riggs, C.; et al. Science-in-brief: Risk assessment for reducing injuries of the fetlock bones in Thoroughbred racehorses. Equine Vet. J. 2020, 52, 482–488.
  5. Whitton, R.C.; Ayodele, B.A.; Hitchens, P.L.; Mackie, E.J. Subchondral bone microdamage accumulation in distal metacarpus of Thoroughbred racehorses. Equine Vet. J. 2018, 50, 766–773.
  6. Tranquille, C.A.; Murray, R.C.; Parkin, T.D.H. 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. 2016, 49, 167–171.
  7. Moreira, C.A.; Bilezikian, J.P. Stress fractures: Concepts and therapeutics. J. Clin. Endocrinol. Metab. 2016, 102, 525–534.
  8. Yu, H.; Guan, Z.; Cuk, K.; Brenner, H.; Zhang, Y. Circulating microRNA biomarkers for lung cancer detection in Western populations. Cancer Med. 2018, 7, 4849–4862.
  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, 8, 44893–44909.
  10. Zou, Y.; Jing, C.; Liu, L.; Wang, T. Serum microRNA-135a as a diagnostic biomarker in non-small cell lung cancer. Medicine 2019, 98, e17814.
  11. Beg, M.S.; Brenner, A.J.; Sachdev, J.; Borad, M.; Kang, Y.-K.; Stoudemire, J.; Smith, S.; Bader, A.G.; Kim, S.; Hong, D.S. Phase I study of MRX34, a liposomal miR-34a mimic, administered twice weekly in patients with advanced solid tumors. Investig. New Drugs 2017, 35, 180–188.
  12. Rupaimoole, R.; Slack, F.J. MicroRNA therapeutics: Towards a new era for the management of cancer and other diseases. Nat. Rev. Drug Discov. 2017, 16, 203–222.
  13. Janssen, H.L.A.; Reesink, H.W.; Lawitz, E.J.; Zeuzem, S.; Rodriguez-Torres, M.; Patel, K.; Van Der Meer, A.J.; Patick, A.K.; Chen, A.; Zhou, Y.; et al. Treatment of HCV Infection by Targeting MicroRNA. N. Engl. J. Med. 2013, 368, 1685–1694.
  14. Kelch, S.; Balmayor, E.R.; Seeliger, C.; Vester, H.; Kirschke, J.S.; Van Griensven, M. miRNAs in bone tissue correlate to bone mineral density and circulating miRNAs are gender independent in osteoporotic patients. Sci. Rep. 2017, 7, 1–12.
  15. Makitie, R.E.; Hackl, M.; Niinimaki, R.; Kakko, S.; Grillari, J.; Makitie, O. Altered MicroRNA Profile in Osteoporosis Caused by Impaired WNT Signaling. J. Clin. Endocrinol. Metab. 2018, 103, 1985–1996.
  16. Mandourah, A.Y.; Ranganath, L.; Barraclough, R.; Vinjamuri, S.; Hof, R.V.; Hamill, S.; Czanner, G.; Dera, A.A.; Wang, D.; Barraclough, D.L. Circulating microRNAs as potential diagnostic biomarkers for osteoporosis. Sci. Rep. 2018, 8, 1–10.
  17. Seeliger, C.; Karpinski, K.; Haug, A.T.; Vester, H.; Schmitt, A.; Bauer, J.S.; Van Griensven, M. Five Freely Circulating miRNAs and Bone Tissue miRNAs Are Associated With Osteoporotic Fractures. J. Bone Miner. Res. 2014, 29, 1718–1728.
  18. Sun, M.; Hu, L.; Wang, S.; Huang, T.; Zhang, M.; Yang, M.; Zhen, W.; Yang, D.; Lu, W.; Guan, M.; et al. Circulating MicroRNA-19b Identified From Osteoporotic Vertebral Compression Fracture Patients Increases Bone Formation. J. Bone Miner. Res. 2020, 35, 306–316.
  19. Desjardin, C.; Vaiman, A.; Mata, X.; Legendre, R.; Laubier, J.; Kennedy, S.P.; Laloë, D.; Barrey, E.; Jacques, C.; Cribiu, E.P.; et al. Next-generation sequencing identifies equine cartilage and subchondral bone miRNAs and suggests their involvement in osteochondrosis physiopathology. BMC Genom. 2014, 15, 798.
  20. Lecchi, C.; Costa, E.D.; 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, 12, 366–375.
  21. Watts, A.E.; Millar, N.L.; Platt, J.; Kitson, S.M.; Akbar, M.; Rech, R.; Griffin, J.; Pool, R.; Hughes, T.; McInnes, I.B.; et al. MicroRNA29a Treatment Improves Early Tendon Injury. Mol. Ther. 2017, 25, 2415–2426.
  22. Balaskas, P.; Green, J.A.; Haqqi, T.M.; Dyer, P.; Kharaz, Y.A.; Fang, Y.; Liu, X.; Welting, T.J.; Peffers, M.J. Small Non-Coding RNAome of Ageing Chondrocytes. Int. J. Mol. Sci. 2020, 21, 5675.
  23. Castanheira, C.; Balaskas, P.; Falls, C.; Ashraf-Kharaz, Y.; Clegg, P.; Burke, K.; Fang, Y.; Dyer, P.; Welting, T.J.M.; Peffers, M.J. Equine synovial fluid small non-coding RNA signatures in early osteoarthritis. BMC Vet. Res. 2021, 17, 1–12.
  24. Riasat, K.; Bardell, D.; Goljanek-Whysall, K.; Clegg, P.D.; Peffers, M.J. Epigenetic mechanisms in Tendon Ageing. Br. Med. Bull. 2020, 135, 90–107.
  25. Innes, J.F.; Clegg, P. Comparative rheumatology: What can be learnt from naturally occurring musculoskeletal disorders in domestic animals? Rheumatology 2010, 49, 1030–1039.
  26. Boyde, A. The real response of bone to exercise. J. Anat. 2003, 203, 173–189.
  27. Hollis, A.R.; Starkey, M.P. MicroRNAs in equine veterinary science. Equine Vet. J. 2018, 50, 721–726.
  28. Van Der Kolk, J.; Pacholewska, A.; Gerber, V. The role of microRNAs in equine medicine: A review. Vet. Q. 2015, 35, 88–96.
  29. Harris, J.D.; Quatman, C.E.; Manring, M.; Siston, R.A.; Flanigan, D.C. How to Write a Systematic Review. Am. J. Sports Med. 2014, 42, 2761–2768.
  30. Shamseer, L.; Moher, D.; Clarke, M.; Ghersi, D.; Liberati, A.; Petticrew, M.; Shekelle, P.; Stewart, L.A.; Group, P.-P. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: Elaboration and explanation. BMJ 2015, 350, g7647.
  31. Witwer, K.W.; Halushka, M.K. Toward the promise of microRNAs—Enhancing reproducibility and rigor in microRNA research. RNA Biol. 2016, 13, 1103–1116.
  32. Kocijan, R.; Muschitz, C.; Geiger, E.; Skalicky, S.; Baierl, A.; Dormann, R.; Plachel, F.; Feichtinger, X.; Heimel, P.; Fahrleitner-Pammer, A.; et al. Circulating microRNA Signatures in Patients with Idiopathic and Postmenopausal Osteoporosis and Fragility Fractures. J. Clin. Endocrinol. Metab. 2016, 101, 4125–4134.
  33. Weilner, S.; Skalicky, S.; Salzer, B.; Keider, V.; Wagner, M.; Hildner, F.; Gabriel, C.; Dovjak, P.; Pietschmann, P.; Grillari-Voglauer, R.; et al. Differentially circulating miRNAs after recent osteoporotic fractures can influence osteogenic differentiation. Bone 2015, 79, 43–51.
  34. Curtis, L.; Burford, J.H.; England, G.C.W.; Freeman, S.L. 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, e0219307.
  35. Piscopo, P.; Lacorte, E.; Feligioni, M.; Mayer, F.; Crestini, A.; Piccolo, L.; Bacigalupo, I.; Filareti, M.; Ficulle, E.; Confaloni, A.; et al. MicroRNAs and mild cognitive impairment: A systematic review. Ageing Res. Rev. 2019, 50, 131–141.
  36. Aromataris, E.M.Z.E. JBI Manual for Evidence Synthesis; JBI: Adelaide, SA, Australia, 2020.
  37. National Institute for Health and Care Excellence. NICE Process and Methods Guides. In Methods for the Development of NICE Public Health Guidance; National Institute for Health and Care Excellence: London, UK, 2012.
  38. Jackson, B.F.; Reed, S.R.; Price, J.S.; Verheyen, K.L.P. Relationship between serum biomarkers of cartilage and bone metabolism and joint injury in young Thoroughbred racehorses in training. Am. J. Vet. Res. 2015, 76, 679–687.
  39. Turlo, A.J.; Cywinska, A.; Frisbie, D.D. Revisiting predictive biomarkers of musculoskeletal injury in thoroughbred racehorses: Longitudinal study in polish population. BMC Vet. Res. 2019, 15, 66.
  40. Cleary, O.B.; Trumble, T.N.; Merritt, K.A.; Brown, M.P. 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, 71, 33–40.
  41. Arens, A.M.; Puchalski, S.M.; Whitcomb, M.B.; Bell, R.; Gardner, I.A.; Stover, S.M. 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, 242, 76–85.
  42. Frisbie, D.D.; Mc Ilwraith, C.W.; Arthur, R.M.; Blea, J.; Baker, V.A.; Billinghurst, R.C. 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, 42, 643–651.
  43. 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.
  44. McGivney, B.A.; Griffin, M.E.; Gough, K.F.; McGivney, C.L.; Browne, J.A.; Hill, E.W.; Katz, L.M. Evaluation of microRNA expression in plasma and skeletal muscle of thoroughbred racehorses in training. BMC Vet. Res. 2017, 13, 1–8.
  45. Kim, H.-A.; Kim, M.-C.; Kim, N.-Y.; Ryu, D.-Y.; Lee, H.-S.; Kim, Y. Integrated analysis of microRNA and mRNA expressions in peripheral blood leukocytes of Warmblood horses before and after exercise. J. Vet. Sci. 2018, 19, 99–106.
  46. Mach, N.; Plancade, S.; Pacholewska, A.; Lecardonnel, J.; Rivière, J.; Moroldo, M.; Vaiman, A.; Morgenthaler, C.; Beinat, M.; Nevot, A.; et al. Integrated mRNA and miRNA expression profiling in blood reveals candidate biomarkers associated with endurance exercise in the horse. Sci. Rep. 2016, 6, 22932.
  47. Mach, N.; Ramayo-Caldas, Y.; Clark, A.; Moroldo, M.; Robert, C.; Barrey, E.; Lopez, J.M.; Le Moyec, L. Understanding the response to endurance exercise using a systems biology approach: Combining blood metabolomics, transcriptomics and miRNomics in horses. BMC Genom. 2017, 18, 187.
  48. 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, 9, 18029–18040.
  49. Horak, M.; Zlamal, F.; Iliev, R.; Kučera, J.; Cacek, J.; Svobodova, L.; Hlavoňová, Z.; Kalina, T.; Slaby, O.; Bienertova-Vasku, J. Exercise-induced circulating microRNA changes in athletes in various training scenarios. PLoS ONE 2018, 13, e0191060.
  50. Håkansson, K.E.J.; Sollie, O.; Simons, K.H.; Quax, P.H.A.; Jensen, J.; Nossent, A.Y. Circulating Small Non-coding RNAs as Biomarkers for Recovery After Exhaustive or Repetitive Exercise. Front. Physiol. 2018, 9, 1136.
  51. Farries, G.; Bryan, K.; McGivney, C.L.; Mcgettigan, P.A.; Gough, K.F.; Browne, J.A.; MacHugh, D.E.; Katz, L.M.; Hill, E.W. Expression Quantitative Trait Loci in Equine Skeletal Muscle Reveals Heritable Variation in Metabolism and the Training Responsive Transcriptome. Front. Genet. 2019, 10, 1215.
  52. Stefaniuk-Szmukier, M.; Ropka-Molik, K.; Piorkowska, K.; Zukowski, 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, 676, 256–262.
  53. 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, 123, 59–64.
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