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Home / Equine Research Bank / BMC Vet Res / Equine synovial fluid small non-coding RNA signatures in ear...
BMC veterinary research2021; 17(1); 26; doi: 10.1186/s12917-020-02707-7

Equine synovial fluid small non-coding RNA signatures in early osteoarthritis.

Abstract: Osteoarthritis remains one of the greatest causes of morbidity and mortality in the equine population. The inability to detect pre-clinical changes in osteoarthritis has been a significant impediment to the development of effective therapies against this disease. Synovial fluid represents a potential source of disease-specific small non-coding RNAs (sncRNAs) that could aid in the understanding of the pathogenesis of osteoarthritis. We hypothesised that early stages of osteoarthritis would alter the expression of sncRNAs, facilitating the understanding of the underlying pathogenesis and potentially provide early biomarkers. Methods: Small RNA sequencing was performed using synovial fluid from the metacarpophalangeal joints of both control and early osteoarthritic horses. A group of differentially expressed sncRNAs was selected for further validation through qRT-PCR using an independent cohort of synovial fluid samples from control and early osteoarthritic horses. Bioinformatic analysis was performed in order to identify putative targets of the differentially expressed microRNAs and to explore potential associations with specific biological processes. Results: Results revealed 22 differentially expressed sncRNAs including 13 microRNAs; miR-10a, miR-223, let7a, miR-99a, miR-23b, miR-378, miR-143 (and six novel microRNAs), four small nuclear RNAs; U2, U5, U11, U12, three small nucleolar RNAs; U13, snoR38, snord96, and one small cajal body-specific RNA; scarna3. Five sncRNAs were validated; miR-223 was significantly reduced in early osteoarthritis and miR-23b, let-7a-2, snord96A and snord13 were significantly upregulated. Significant cellular actions deduced by the differentially expressed microRNAs included apoptosis (P < 0.0003), necrosis (P < 0.0009), autophagy (P < 0.0007) and inflammation (P < 0.00001). A conservatively filtered list of 57 messenger RNA targets was obtained; the top biological processes associated were regulation of cell population proliferation (P < 0.000001), cellular response to chemical stimulus (P < 0.000001) and cell surface receptor signalling pathway (P < 0.000001). Conclusions: Synovial fluid sncRNAs may be used as molecular biomarkers for early disease in equine osteoarthritic joints. The biological processes they regulate may play an important role in understanding early osteoarthritis pathogenesis. Characterising these dynamic molecular changes could provide novel insights on the process and mechanism of early osteoarthritis development and is critical for the development of new therapeutic approaches.
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Publication Date: 2021-01-09 PubMed ID: 33422071PubMed Central: PMC7796526DOI: 10.1186/s12917-020-02707-7Google Scholar: Lookup
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  • 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.

The research focuses on identifying early signs of osteoarthritis in horses using small non-coding RNAs (sncRNAs) found in synovial fluid and how their expression changes may be used to understand disease progression better. This knowledge may guide the development of effective therapeutic methodologies.

Methodology

  • The study compares small RNA sequencing from the synovial fluid of horses’ metacarpophalangeal joints, both from those with early osteoarthritis and controls.
  • The differentially expressed sncRNAs were further validated using an independent cohort of synovial fluid samples in the same conditions.
  • Through bioinformatics analysis, the researchers aimed to identify the potential actions of these differentially expressed miRNAs and how they relate to particular biological processes.

Findings

  • They identified 22 differentially expressed sncRNAs, including 13 specific microRNAs and other RNA types.
  • Five sncRNAs were validated – miR-223, which was significantly lower in early osteoarthritis, and four others that were significantly higher, including miR-23b, let-7a-2, snord96A, and snord13.
  • The differential expression could infer significant cellular actions such as apoptosis, necrosis, autophagy, and inflammation.
  • A list of 57 mRNA targets was obtained. The top associated biological processes were regulation of cell population proliferation, cellular response to chemical stimulus, and cell surface receptor signaling pathways.

Conclusion

  • These results suggest that sncRNAs in synovial fluid could be used as potential biomarkers to detect early osteoarthritis in equine joints.
  • The biological processes they regulate may provide vital insight into the pathogenesis of early onset osteoarthritis.
  • Better understanding of these molecular changes could offer novel insights into the development process and mechanism of early osteoarthritis and could be crucial for developing new therapeutic strategies.

Cite This Article

APA
Castanheira C, Balaskas P, Falls C, Ashraf-Kharaz Y, Clegg P, Burke K, Fang Y, Dyer P, Welting TJM, Peffers MJ. (2021). Equine synovial fluid small non-coding RNA signatures in early osteoarthritis. BMC Vet Res, 17(1), 26. https://doi.org/10.1186/s12917-020-02707-7

Publication

BMC veterinary research
ISSN: 1746-6148
NlmUniqueID: 101249759
Country: England
Language: English
Volume: 17
Issue: 1
Pages: 26

Researcher Affiliations

Castanheira, Catarina
  • Department of Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, William Henry Duncan Building, 6 West Derby Street, Liverpool, L7 8TX, UK. C.Castanheira@liverpool.ac.uk.
Balaskas, Panagiotis
  • Department of Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, William Henry Duncan Building, 6 West Derby Street, Liverpool, L7 8TX, UK.
Falls, Charlotte
  • Department of Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, William Henry Duncan Building, 6 West Derby Street, Liverpool, L7 8TX, UK.
Ashraf-Kharaz, Yalda
  • Department of Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, William Henry Duncan Building, 6 West Derby Street, Liverpool, L7 8TX, UK.
Clegg, Peter
  • Department of Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, William Henry Duncan Building, 6 West Derby Street, Liverpool, L7 8TX, UK.
Burke, Kim
  • Institute of Veterinary Science, University of Liverpool, Chester High Road, Neston, CH64 7TE, UK.
Fang, Yongxiang
  • Centre for Genomic Research, Institute of Integrative Biology, University of Liverpool, Biosciences Building, Crown Street, Liverpool, L69 7ZB, UK.
Dyer, Philip
  • Institute of Infection and Global Health, University of Liverpool, 8 West Derby Street, Liverpool, L7 3EA, UK.
Welting, Tim J M
  • Department of Orthopaedic Surgery, Maastricht University Medical Centre, Maastricht, AZ, 6202, The Netherlands.
Peffers, Mandy J
  • Department of Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, William Henry Duncan Building, 6 West Derby Street, Liverpool, L7 8TX, UK.

MeSH Terms

  • Animals
  • Biomarkers
  • Horse Diseases / diagnosis
  • Horses
  • Osteoarthritis / diagnosis
  • Osteoarthritis / metabolism
  • Osteoarthritis / veterinary
  • RNA, Small Untranslated / metabolism
  • Synovial Fluid

Grant Funding

  • Wellcome Trust
  • MR/P020941/1 / Medical Research Council
  • 107471/Z/15/Z / Wellcome Trust

Conflict of Interest Statement

The authors declare no competing interests.

References

This article includes 76 references
  1. Ireland JL, Clegg PD, Mcgowan CM, Mckane SA, Chandler KJ, Pinchbeck GL. Disease prevalence in geriatric horses in the United Kingdom: veterinary clinical assessment of 200 cases.. Equine Vet J 2012;44:101–106.
    doi: 10.1111/j.2042-3306.2010.00361.xpubmed: 21668494google scholar: lookup
  2. Ireland JL, Clegg PD, McGowan CM, Platt L, Pinchbeck GL. Factors associated with mortality of geriatric horses in the United Kingdom.. Prev Vet Med 2011;101:204–218.
    doi: 10.1016/j.prevetmed.2011.06.002pubmed: 21733586google scholar: lookup
  3. Woolf AD, Pfleger B. Burden of major musculoskeletal conditions.. Bull World Health Organ 2003;81:646–656.
    pmc: PMC2572542pubmed: 14710506
  4. Mobasheri A, Batt M. An update on the pathophysiology of osteoarthritis.. Ann Phys Rehabil Med 2016;59:333–339.
    doi: 10.1016/j.rehab.2016.07.004pubmed: 27546496google scholar: lookup
  5. Ashkavand Z, Malekinejad H, Vishwanath BS. The pathophysiology of osteoarthritis.. J Pharm Res 2013;7:132–138.
  6. Goodrich LR, Nixon AJ. Medical treatment of osteoarthritis in the horse - a review.. Vet J 2006;171:51–69.
    doi: 10.1016/j.tvjl.2004.07.008pubmed: 16427582google scholar: lookup
  7. McIlwraith CW, Frisbie DD, Kawcak CE. The horse as a model of naturally occurring osteoarthritis.. Bone Joint Res 2012;1:297–309.
    doi: 10.1302/2046-3758.111.2000132pmc: PMC3626203pubmed: 23610661google scholar: lookup
  8. Adams BD, Parsons C, Walker L, Zhang WC, Slack FJ. Targeting noncoding RNAs in disease.. J Clin Invest 2017;127:761–771.
    doi: 10.1172/JCI84424pmc: PMC5330746pubmed: 28248199google scholar: lookup
  9. Díaz-Prado S, Cicione C, Muiños-López E, Hermida-Gómez T, Oreiro N, Fernández-López C. Characterization of microRNA expression profiles in normal and osteoarthritic human chondrocytes.. BMC Musculoskelet Disord 2012;13:144.
    doi: 10.1186/1471-2474-13-144pmc: PMC3495209pubmed: 22883423google scholar: lookup
  10. Miyaki S, Nakasa T, Otsuki S, Grogan SP, Higashiyama R, Inoue A. MicroRNA-140 is expressed in differentiated human articular chondrocytes and modulates interleukin-1 responses.. Arthritis Rheum 2009;60:2723–2730.
    doi: 10.1002/art.24745pmc: PMC2806094pubmed: 19714579google scholar: lookup
  11. Murata K, Yoshitomi H, Tanida S, Ishikawa M, Nishitani K, Ito H. Plasma and synovial fluid microRNAs as potential biomarkers of rheumatoid arthritis and osteoarthritis.. Arthritis Res Ther 2010;12:R86.
    doi: 10.1186/ar3013pmc: PMC2911870pubmed: 20470394google scholar: lookup
  12. Hu W, Zhang W, Li F, Guo F, Chen A. miR-139 is up-regulated in osteoarthritis and inhibits chondrocyte proliferation and migration possibly via suppressing EIF4G2 and IGF1R.. Biochem Biophys Res Commun 2016;474:296–302.
    doi: 10.1016/j.bbrc.2016.03.164pubmed: 27105918google scholar: lookup
  13. Wang Z, Chi X, Liu L, Wang Y, Mei X, Yang Y. Long noncoding RNA maternally expressed gene 3 knockdown alleviates lipopolysaccharide-induced inflammatory injury by up-regulation of miR-203 in ATDC5 cells.. Biomed Pharmacother 2018;100:240–249.
    doi: 10.1016/j.biopha.2018.02.018pubmed: 29432995google scholar: lookup
  14. Chang Z, Meng F, Zhang Z, Mao G, Huang Z, Liao W. MicroRNA-193b-3p regulates matrix metalloproteinase 19 expression in interleukin-1β-induced human chondrocytes.. J Cell Biochem 2018;119:4775–4782.
    doi: 10.1002/jcb.26669pubmed: 29323744google scholar: lookup
  15. Yu X-M, Meng H-Y, Yuan X-L, Wang Y, Guo Q-Y, Peng J. MicroRNAs’ Involvement in Osteoarthritis and the Prospects for Treatments Evid Based Complement.. Alternat Med 2015;2015:236179.
    pmc: PMC4637488pubmed: 26587043
  16. Endisha H, Rockel J, Jurisica I, Kapoor M. The complex landscape of microRNAs in articular cartilage: biology, pathology, and therapeutic targets.. JCI Insight 2018;3(17):e121630.
    doi: 10.1172/jci.insight.121630pmc: PMC6171796pubmed: 30185670google scholar: lookup
  17. Peffers MJ, Balaskas P, Smagul A. Osteoarthritis year in review 2017: genetics and epigenetics.. Osteoarthr Cartil 2018;26:304–311.
    doi: 10.1016/j.joca.2017.09.009pmc: PMC6292677pubmed: 28989115google scholar: lookup
  18. Ge Q, Zhou Y, Lu J, Bai Y, Xie X, Lu Z. miRNA in plasma exosome is stable under different storage conditions.. Molecules 2014;19:1568–1575.
    doi: 10.3390/molecules19021568pmc: PMC6271968pubmed: 24473213google scholar: lookup
  19. Wang K. The ubiquitous existence of MicroRNA in body fluids.. Clin Chem 2017;63:784–785.
    doi: 10.1373/clinchem.2016.267625pubmed: 28082463google scholar: lookup
  20. Zhang Z, Qin YW, Brewer G, Jing Q. MicroRNA degradation and turnover: regulating the regulators.. Wiley Interdiscip Rev RNA 2012;3:593–600.
    doi: 10.1002/wrna.1114pmc: PMC3635675pubmed: 22461385google scholar: lookup
  21. Moldovan L, Batte KE, Trgovcich J, Wisler J, Marsh CB, Piper M. Methodological challenges in utilizing miRNAs as circulating biomarkers.. J Cell Mol Med 2014;18:371–390.
    doi: 10.1111/jcmm.12236pmc: PMC3943687pubmed: 24533657google scholar: lookup
  22. Buschmann D, Haberberger A, Kirchner B, Spornraft M, Riedmaier I, Schelling G. Toward reliable biomarker signatures in the age of liquid biopsies - how to standardize the small RNA-Seq workflow.. Nucleic Acids Res 2016;44:5995–6018.
    doi: 10.1093/nar/gkw545pmc: PMC5291277pubmed: 27317696google scholar: lookup
  23. Stepanov GA, Filippova JA, Komissarov AB, Kuligina EV, Richter VA, Semenov DV. Regulatory role of small Nucleolar RNAs in human diseases.. Biomed Res Int 2015;2015:206849.
    doi: 10.1155/2015/206849pmc: PMC4427830pubmed: 26060813google scholar: lookup
  24. Steinbusch MMF, Fang Y, Milner PI, Clegg PD, Young DA, Welting TJM. Serum snoRNAs as biomarkers for joint ageing and post traumatic osteoarthritis.. Sci Rep 2017;7:1–11.
    doi: 10.1038/s41598-016-0028-xpmc: PMC5333149pubmed: 28252005google scholar: lookup
  25. Kim M-C, Lee S-W, Ryu D-Y, Cui F-J, Bhak J, Kim Y. Identification and characterization of MicroRNAs in Normal equine tissues by next generation sequencing.. PLoS One 2014;9:e93662.
    doi: 10.1371/journal.pone.0093662pmc: PMC3973549pubmed: 24695583google scholar: lookup
  26. Pacholewska A, Mach N, Mata X, Vaiman A, Schibler L, Barrey E. Novel equine tissue miRNAs and breed-related miRNA expressed in serum.. BMC Genomics 2016;17:1–15.
    doi: 10.1186/s12864-016-3168-2pmc: PMC5080802pubmed: 27782799google scholar: lookup
  27. 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(SUPPL. 38):303–310.
    doi: 10.1111/j.2042-3306.2010.00267.xpubmed: 21059022google scholar: lookup
  28. Desjardin C, Vaiman A, Mata X, Legendre R, Laubier J, Kennedy SP. Next-generation sequencing identifies equine cartilage and subchondral bone miRNAs and suggests their involvement in osteochondrosis physiopathology.. BMC Genomics 2014;15:798.
    doi: 10.1186/1471-2164-15-798pmc: PMC4190437pubmed: 25227120google scholar: lookup
  29. da Costa SH, Hess T, Bruemmer J, Splan R. Possible role of MicroRNA in equine insulin resistance: a pilot study.. J Equine Vet Sci 2018;63:74–79.
    doi: 10.1016/j.jevs.2017.10.024google scholar: lookup
  30. McIlwraith CW. Use of synovial fluid and serum biomarkers in equine bone and joint disease: a review.. Equine Vet J 2010;37:473–482.
    doi: 10.2746/042516405774480102pubmed: 16163952google scholar: lookup
  31. Li Y-H, Tavallaee G, Tokar T, Nakamura A, Sundararajan K, Weston A. Identification of synovial fluid microRNA signature in knee osteoarthritis: differentiating early- and late-stage knee osteoarthritis.. Osteoarthr Cartil 2016;24:1577–1586.
    doi: 10.1016/j.joca.2016.04.019pubmed: 27143365google scholar: lookup
  32. Xu JF, Zhang SJ, Zhao C, Qiu BS, Gu HF, Hong JF. Altered microRNA expression profile in synovial fluid from patients with knee osteoarthritis with treatment of hyaluronic acid.. Mol Diagnosis Ther 2015;19:299–308.
    doi: 10.1007/s40291-015-0155-2pubmed: 26232909google scholar: lookup
  33. Antunes J, Koch TG, Koenig J, Cote N, Dubois M-S. On the road to biomarkers: developing a robust system for miRNA evaluation in equine blood and synovial fluid.. Osteoarthr Cartil 2019;27:S110–S111.
    doi: 10.1016/j.joca.2019.02.165google scholar: lookup
  34. Chu CR, Williams AA, Coyle CH, Bowers ME. Early diagnosis to enable early treatment of pre-osteoarthritis.. Arthritis Res Ther 2012;14:212.
    doi: 10.1186/ar3845pmc: PMC3446496pubmed: 22682469google scholar: lookup
  35. McCoy AM. Animal models of osteoarthritis: comparisons and key considerations.. Vet Pathol 2015;52:803–818.
    doi: 10.1177/0300985815588611pubmed: 26063173google scholar: lookup
  36. Neundorf RH, Lowerison MB, Cruz AM, Thomason JJ, McEwen BJ, Hurtig MB. Determination of the prevalence and severity of metacarpophalangeal joint osteoarthritis in thoroughbred racehorses via quantitative macroscopic evaluation.. Am J Vet Res 2010;71:1284–93.
    doi: 10.2460/ajvr.71.11.1284pubmed: 21034319google scholar: lookup
  37. Ireland JL. Demographics, management, preventive health care and disease in aged horses.. Vet Clin North Am Equine Pract 2016;32:195–214.
    doi: 10.1016/j.cveq.2016.04.001pubmed: 27449388google scholar: lookup
  38. Zhang M, Lygrissea K, Wanga J. Role of MicroRNA in osteoarthritis.. J Arthritis 2017;06.
    pmc: PMC5533289pubmed: 28758052doi: 10.4172/2167-7921.1000239google scholar: lookup
  39. Si HB, Zeng Y, Liu SY, Zhou ZK, Chen YN, Cheng JQ. Intra-articular injection of microRNA-140 (miRNA-140) alleviates osteoarthritis (OA) progression by modulating extracellular matrix (ECM) homeostasis in rats.. Osteoarthr Cartil 2017;25:1698–1707.
    doi: 10.1016/j.joca.2017.06.002pubmed: 28647469google scholar: lookup
  40. Yin C-M, Suen W-C-W, Lin S, Wu X-M, Li G, Pan X-H. Dysregulation of both miR-140-3p and miR-140-5p in synovial fluid correlate with osteoarthritis severity.. Bone Joint Res 2017;6:612–618.
    doi: 10.1302/2046-3758.611.BJR-2017-0090.R1pmc: PMC5717073pubmed: 29092816google scholar: lookup
  41. Iliopoulos D, Malizos KN, Oikonomou P, Tsezou A. Integrative MicroRNA and proteomic approaches identify novel osteoarthritis genes and their collaborative metabolic and inflammatory networks.. PLoS One 2008;3:e3740.
    doi: 10.1371/journal.pone.0003740pmc: PMC2582945pubmed: 19011694google scholar: lookup
  42. Ham O, Song BW, Lee SY, Choi E, Cha MJ, Lee CY. The role of microRNA-23b in the differentiation of MSC into chondrocyte by targeting protein kinase a signaling.. Biomaterials 2012;33:4500–4507.
    doi: 10.1016/j.biomaterials.2012.03.025pubmed: 22449550google scholar: lookup
  43. Karlsen TA, Jakobsen RB, Mikkelsen TS, Brinchmann JE. MicroRNA-140 targets RALA and regulates chondrogenic differentiation of human mesenchymal stem cells by translational enhancement of SOX9 and ACAN.. Stem Cells Dev 2014;23:290–304.
    doi: 10.1089/scd.2013.0209pubmed: 24063364google scholar: lookup
  44. Sui G, Zhang L, Hu Y. MicroRNA-let-7a inhibition inhibits LPS-induced inflammatory injury of chondrocytes by targeting IL6R.. Mol Med Rep 2019;20:2633–2640.
    pmc: PMC6691277pubmed: 31322277
  45. Beyer C, Zampetaki A, Lin NY, Kleyer A, Perricone C, Iagnocco A. Signature of circulating microRNAs in osteoarthritis.. Ann Rheum Dis 2015;74:e18.
    doi: 10.1136/annrheumdis-2013-204698pubmed: 24515954google scholar: lookup
  46. Feng L, Feng C, Wang CX, Xu DY, Chen JJ, Huang JF. Circulating microRNA let–7e is decreased in knee osteoarthritis, accompanied by elevated apoptosis and reduced autophagy.. Int J Mol Med 2020;45:1464–1476.
    pmc: PMC7138275pubmed: 32323821
  47. Okuhara A, Nakasa T, Shibuya H, Niimoto T, Adachi N, Deie M. Changes in microRNA expression in peripheral mononuclear cells according to the progression of osteoarthritis.. Mod Rheumatol 2012;22:446–457.
    doi: 10.3109/s10165-011-0536-2pubmed: 22006119google scholar: lookup
  48. Tu J, Huang W, Zhang W, Mei J, Zhu C. The emerging role of lncRNAs in chondrocytes from osteoarthritis patients.. Biomed Pharmacother 2020;131:110642.
    doi: 10.1016/j.biopha.2020.110642pubmed: 32927251google scholar: lookup
  49. Ying H, Wang Y, Gao Z, Zhang Q. Long non-coding RNA activated by transforming growth factor beta alleviates lipopolysaccharide-induced inflammatory injury via regulating microRNA-223 in ATDC5 cells.. Int Immunopharmacol 2019;69:313–320.
    doi: 10.1016/j.intimp.2019.01.056pubmed: 30771739google scholar: lookup
  50. Peffers MJ, Chabronova A, Balaskas P, Fang Y, Dyer P, Cremers A. SnoRNA signatures in cartilage ageing and osteoarthritis.. Sci Rep 2020;10:10641.
    doi: 10.1038/s41598-020-67446-zpmc: PMC7326970pubmed: 32606371google scholar: lookup
  51. Peffers MJ, Ripmeester E, Caron M, Steinbusch M, Balaskas P, Cremers A. A role for the snoRNA U3 in the altered translational capacity of ageing and osteoarthritic chondrocytes.. Osteoarthr Cartil 2018;26:S45–S46.
    doi: 10.1016/j.joca.2018.02.106google scholar: lookup
  52. Mcmahon M, Contreras A, Ruggero D. Small RNAs with big implications: new insights into H/ACA snoRNA function and their role in human disease.. Wiley Interdiscip Rev RNA 2015;6:173–189.
    doi: 10.1002/wrna.1266pmc: PMC4390053pubmed: 25363811google scholar: lookup
  53. Goldring SR, Goldring MB. The role of cytokines in cartilage matrix degeneration in osteoarthritis. Clinical Orthopaedics and Related Research 2004;pp. S27–S36.
    pubmed: 15480070
  54. Wang X, Hunter DJ, Jin X, Ding C. The importance of synovial inflammation in osteoarthritis: current evidence from imaging assessments and clinical trials.. Osteoarthr Cartil 2018;26:165–174.
    doi: 10.1016/j.joca.2017.11.015pubmed: 29224742google scholar: lookup
  55. Hwang HS, Kim HA. Chondrocyte apoptosis in the pathogenesis of osteoarthritis.. Int J Mol Sci 2015;16:26035–26054.
    doi: 10.3390/ijms161125943pmc: PMC4661802pubmed: 26528972google scholar: lookup
  56. Stewart HL, Kawcak CE. The importance of Subchondral bone in the pathophysiology of osteoarthritis.. Front Veterinary Sci 2018;5:178.
    doi: 10.3389/fvets.2018.00178pmc: PMC6122109pubmed: 30211173google scholar: lookup
  57. Thomas CM, Fuller CJ, Whittles CE, Sharif M. Chondrocyte death by apoptosis is associated with cartilage matrix degradation.. Osteoarthr Cartil 2007;15:27–34.
    doi: 10.1016/j.joca.2006.06.012pubmed: 16859932google scholar: lookup
  58. Lin EA, Liu C-J. The role of ADAMTSs in arthritis.. Protein Cell 2010;1:33–47.
    doi: 10.1007/s13238-010-0002-5pmc: PMC4418016pubmed: 21203996google scholar: lookup
  59. Yoon BS, Ovchinnikov DA, Yoshii I, Mishina Y, Behringer RR, Lyons KM. Bmpr1a and Bmpr1b have overlapping functions and are essential for chondrogenesis in vivo.. Proc Natl Acad Sci U S A 2005;102:5062–5067.
    doi: 10.1073/pnas.0500031102pmc: PMC555995pubmed: 15781876google scholar: lookup
  60. Akeson G, Malemud CJ. A role for soluble IL-6 receptor in osteoarthritis.. J Funct Morphol Kinesiol 2017;2:27.
    doi: 10.3390/jfmk2030027pmc: PMC5739325pubmed: 29276788google scholar: lookup
  61. Nakamura A, Rampersaud YR, Nakamura S, Sharma A, Zeng F, Rossomacha E. MicroRNA-181a-5p antisense oligonucleotides attenuate osteoarthritis in facet and knee joints.. Ann Rheum Dis 2019;78:111–121.
    doi: 10.1136/annrheumdis-2018-213629pubmed: 30287418google scholar: lookup
  62. Baek D, Lee KM, Park KW, Suh JW, Choi SM, Park KH. Inhibition of miR-449a promotes cartilage regeneration and prevents progression of osteoarthritis in in vivo rat models.. Mol Ther - Nucleic Acids 2018;13:322–333.
    doi: 10.1016/j.omtn.2018.09.015pmc: PMC6197768pubmed: 30326428google scholar: lookup
  63. Baccarella A, Williams CR, Parrish JZ, Kim CC. Empirical assessment of the impact of sample number and read depth on RNA-Seq analysis workflow performance.. BMC Bioinformatics 2018;19:423.
    doi: 10.1186/s12859-018-2445-2pmc: PMC6234607pubmed: 30428853google scholar: lookup
  64. Kawcak CE, Frisbie DD, Werpy NM, Park RD, Mcilwraith CW. Effects of exercise vs experimental osteoarthritis on imaging outcomes.. Osteoarthr Cartil 2008;16:1519–1525.
    doi: 10.1016/j.joca.2008.04.015pubmed: 18504148google scholar: lookup
  65. McIlwraith CW, Frisbie DD, Kawcak CE, Fuller CJ, Hurtig M, Cruz A. The OARSI histopathology initiative - recommendations for histological assessments of osteoarthritis in the horse.. Osteoarthr Cartil 2010;18:S93–105.
    doi: 10.1016/j.joca.2010.05.031pubmed: 20864027google scholar: lookup
  66. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads.. EMBnet J 2011;17:10.
    doi: 10.14806/ej.17.1.200google scholar: lookup
  67. Kim D, Pertea G, Trapnell C, Pimentel H, Kelley R, Salzberg SL. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions.. Genome Biol 2013;14.
    pmc: PMC4053844pubmed: 23618408doi: 10.1186/gb-2013-14-4-r36google scholar: lookup
  68. 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
  69. Anders S, Huber W. Differential expression analysis for sequence count data.. Genome Biol 2010;11.
    pmc: PMC3218662pubmed: 20979621doi: 10.1186/gb-2010-11-10-r106google scholar: lookup
  70. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing.. J R Stat Soc Ser B 1995;57:289–300.
  71. Xie F, Xiao P, Chen D, Xu L, Zhang B. miRDeepFinder: a miRNA analysis tool for deep sequencing of plant small RNAs.. Plant Mol Biol 2012;80:75–84.
    doi: 10.1007/s11103-012-9885-2pubmed: 22290409google scholar: lookup
  72. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔCT method.. Methods 2001;25:402–408.
    doi: 10.1006/meth.2001.1262pubmed: 11846609google scholar: lookup
  73. Mi H, Muruganujan A, Ebert D, Huang X, Thomas PD. PANTHER version 14: more genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools.. Nucleic Acids Res 2018;47:D419–D426.
    doi: 10.1093/nar/gky1038pmc: PMC6323939pubmed: 30407594google scholar: lookup
  74. Supek F, Bošnjak M, Škunca N, Šmuc T. REVIGO summarizes and visualizes long lists of gene ontology terms.. PLoS One 2011;6:e21800.
    doi: 10.1371/journal.pone.0021800pmc: PMC3138752pubmed: 21789182google scholar: lookup
  75. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D. Cytoscape: a software environment for integrated models of biomolecular interaction networks.. Genome Res 2003;13:2498–2504.
    doi: 10.1101/gr.1239303pmc: PMC403769pubmed: 14597658google scholar: lookup
  76. Xia J, Psychogios N, Young N, Wishart DS. MetaboAnalyst: a web server for metabolomic data analysis and interpretation.. Nucleic Acids Res 2009;37.
    pmc: PMC2703878pubmed: 19429898doi: 10.1093/nar/gkp356google scholar: lookup

Citations

This article has been cited 21 times.
  1. Li L, Xu Z, Gao F, Xu J. Current status and future prospects of nanocarrier-mediated miRNA delivery for osteoarthritis therapy. Front Med (Lausanne) 2025;12:1728944.
    doi: 10.3389/fmed.2025.1728944pubmed: 41625748google scholar: lookup
  2. Castanheira CIGD, Taylor S, Skiöldebrand E, Rubio-Martinez LM, Hackl M, Clegg PD, Peffers MJ. Synovial Fluid and Serum MicroRNA Signatures in Equine Osteoarthritis. Int J Mol Sci 2025 Nov 19;26(22).
    doi: 10.3390/ijms262211190pubmed: 41303673google scholar: lookup
  3. Cullen JN, Cieslak J, Petersen JL, Bellone RR, Finno CJ, Kalbfleisch TS, Calloe K, Capomaccio S, Cappelli K, Coleman SJ, Distl O, Durward-Akhurst SA, Giulotto E, Hamilton NA, Hill EW, Katz LM, Klaerke DA, Lindgren G, MacHugh DE, Mackowski M, MacLeod JN, Metzger J, Murphy BA, Orlando L, Raudsepp T, Silvestrelli M, Strand E, Tozaki T, Trachsel DS, Valderrama Figueroa LS, Velie BD, Wade CM, Waud B, Mickelson JR, McCue ME. Charting the equine miRNA landscape: An integrated pipeline and browser for annotating, quantifying, and visualizing expression. PLoS Genet 2025 Sep;21(9):e1011835.
    doi: 10.1371/journal.pgen.1011835pubmed: 40911641google scholar: lookup
  4. Chabronova A, Walters M, Regårdh S, Jacobsen S, Bundgaard L, Anderson JR, Peffers MJ. Exploring the roles of snoRNA-induced ribosome heterogeneity in equine osteoarthritis. Front Vet Sci 2025;12:1562508.
    doi: 10.3389/fvets.2025.1562508pubmed: 40709001google scholar: lookup
  5. Walters M, Skovgaard K, Heegaard PMH, Fang Y, Kharaz YA, Bundgaard L, Skovgaard LT, Jensen HE, Andersen PH, Peffers MJ, Jacobsen S. Identification and characterisation of temporal abundance of microRNAs in synovial fluid from an experimental equine model of osteoarthritis. Equine Vet J 2025 Jul;57(4):1138-1150.
    doi: 10.1111/evj.14456pubmed: 39775906google scholar: lookup
  6. Andersen C, Walters M, Bundgaard L, Berg LC, Vonk LA, Lundgren-Åkerlund E, Henriksen BL, Lindegaard C, Skovgaard K, Jacobsen S. Intraarticular treatment with integrin α10β1-selected mesenchymal stem cells affects microRNA expression in experimental post-traumatic osteoarthritis in horses. Front Vet Sci 2024;11:1374681.
    doi: 10.3389/fvets.2024.1374681pubmed: 38596460google scholar: lookup
  7. Connard SS, Gaesser AM, Clarke EJ, Linardi RL, Even KM, Engiles JB, Koch DW, Peffers MJ, Ortved KF. Plasma and synovial fluid extracellular vesicles display altered microRNA profiles in horses with naturally occurring post-traumatic osteoarthritis: an exploratory study. J Am Vet Med Assoc 2024 Jun 1;262(S1):S83-S96.
    doi: 10.2460/javma.24.02.0102pubmed: 38593834google scholar: lookup
  8. Antunes J, Salcedo-Jiménez R, Lively S, Potla P, Coté N, Dubois MS, Koenig J, Kapoor M, LaMarre J, Koch TG. microRNAs are differentially expressed in equine plasma of horses with osteoarthritis and osteochondritis dissecans versus control horses. PLoS One 2024;19(2):e0297303.
    doi: 10.1371/journal.pone.0297303pubmed: 38394252google scholar: lookup
  9. Clarke E, Varela L, Jenkins RE, Lozano-Andrés E, Cywińska A, Przewozny M, van Weeren PR, van de Lest CHA, Peffers M, Wauben MHM. Proteome and phospholipidome interrelationship of synovial fluid-derived extracellular vesicles in equine osteoarthritis: An exploratory 'multi-omics' study to identify composite biomarkers. Biochem Biophys Rep 2024 Mar;37:101635.
    doi: 10.1016/j.bbrep.2023.101635pubmed: 38298208google scholar: lookup
  10. Anderson JR, Johnson E, Jenkins R, Jacobsen S, Green D, Walters M, Bundgaard L, Hausmans BAC, van den Akker G, Welting TJM, Chabronova A, Kharaz YA, Clarke EJ, James V, Peffers MJ. Multi-Omic Temporal Landscape of Plasma and Synovial Fluid-Derived Extracellular Vesicles Using an Experimental Model of Equine Osteoarthritis. Int J Mol Sci 2023 Oct 4;24(19).
    doi: 10.3390/ijms241914888pubmed: 37834337google scholar: lookup
  11. Felekkis K, Pieri M, Papaneophytou C. Exploring the Feasibility of Circulating miRNAs as Diagnostic and Prognostic Biomarkers in Osteoarthritis: Challenges and Opportunities. Int J Mol Sci 2023 Aug 24;24(17).
    doi: 10.3390/ijms241713144pubmed: 37685951google scholar: lookup
  12. Yassin AM, AbuBakr HO, Abdelgalil AI, Farid OA, El-Behairy AM, Gouda EM. Circulating miR-146b and miR-27b are efficient biomarkers for early diagnosis of Equidae osteoarthritis. Sci Rep 2023 May 17;13(1):7966.
    doi: 10.1038/s41598-023-35207-3pubmed: 37198318google scholar: lookup
  13. Balaskas P, Goljanek-Whysall K, Clegg PD, Fang Y, Cremers A, Smagul A, Welting TJM, Peffers MJ. MicroRNA Signatures in Cartilage Ageing and Osteoarthritis. Biomedicines 2023 Apr 17;11(4).
    doi: 10.3390/biomedicines11041189pubmed: 37189806google scholar: lookup
  14. Winstanley-Zarach P, Rot G, Kuba S, Smagul A, Peffers MJ, Tew SR. Analysis of RNA Polyadenylation in Healthy and Osteoarthritic Human Articular Cartilage. Int J Mol Sci 2023 Apr 1;24(7).
    doi: 10.3390/ijms24076611pubmed: 37047586google scholar: lookup
  15. Baker ME, Lee S, Clinton M, Hackl M, Castanheira C, Peffers MJ, Taylor SE. Investigation of MicroRNA Biomarkers in Equine Distal Interphalangeal Joint Osteoarthritis. Int J Mol Sci 2022 Dec 8;23(24).
    doi: 10.3390/ijms232415526pubmed: 36555166google scholar: lookup
  16. Wang Y, Zheng X, Luo D, Xu W, Zhou X. MiR-99a alleviates apoptosis and extracellular matrix degradation in experimentally induced spine osteoarthritis by targeting FZD8. BMC Musculoskelet Disord 2022 Sep 20;23(1):872.
    doi: 10.1186/s12891-022-05822-8pubmed: 36127685google scholar: lookup
  17. Anderson JR, Jacobsen S, Walters M, Bundgaard L, Diendorfer A, Hackl M, Clarke EJ, James V, Peffers MJ. Small non-coding RNA landscape of extracellular vesicles from a post-traumatic model of equine osteoarthritis. Front Vet Sci 2022;9:901269.
    doi: 10.3389/fvets.2022.901269pubmed: 36003409google scholar: lookup
  18. Steinbusch MMF, van den Akker GGH, Cremers A, Witlox AMA, Staal HM, Peffers MJ, van Rhijn LW, Caron MMJ, Welting TJM. Adaptation of the protein translational apparatus during ATDC5 chondrogenic differentiation. Noncoding RNA Res 2022 Jun;7(2):55-65.
    doi: 10.1016/j.ncrna.2022.02.003pubmed: 35261930google scholar: lookup
  19. van den Akker GGH, Caron MMJ, Peffers MJ, Welting TJM. Ribosome dysfunction in osteoarthritis. Curr Opin Rheumatol 2022 Jan 1;34(1):61-67.
    doi: 10.1097/BOR.0000000000000858pubmed: 34750309google scholar: lookup
  20. Ramos YFM, Coutinho de Almeida R, Lakenberg N, Suchiman E, Mei H, Kloppenburg M, Nelissen RGHH, Meulenbelt I. Circulating MicroRNAs Highly Correlate to Expression of Cartilage Genes Potentially Reflecting OA Susceptibility-Towards Identification of Applicable Early OA Biomarkers. Biomolecules 2021 Sep 13;11(9).
    doi: 10.3390/biom11091356pubmed: 34572569google scholar: lookup
  21. Lee S, Baker ME, Clinton M, Taylor SE. Use of Omics Data in Fracture Prediction; a Scoping and Systematic Review in Horses and Humans. Animals (Basel) 2021 Mar 30;11(4).
    doi: 10.3390/ani11040959pubmed: 33808497google scholar: lookup
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