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Immune and central nervous system-related miRNAs expression profiling in monocytes of multiple sclerosis patients

Amoruso, Antonella, Blonda, Maria, Gironi, Maira, Grasso, Roberta, Di Francescantonio, Valeria, Scaroni, Federica, Furlan, Roberto, Verderio, Claudia, Avolio, Carlo·2020·Scientific Reports
DOI 10.1038/s41598-020-63282-3PMC PMC7145856
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Abstract

It is widely recognized that monocytes-macrophages adopt a wide variety of phenotypes, influencing the inflammatory activity and demyelination in Multiple Sclerosis (MS). However, how the phenotype of human monocytes evolves in the course of MS is largely unknown. The aim of our preliminary study was to analyse in monocytes of relapsing-remitting and progressive forms of MS patients the expression of a set of miRNAs which impact monocyte-macrophage immune function and their communication with brain cells. Quantitative PCR showed that miRNAs with anti-inflammatory functions, which promote pro-regenerative polarization, are increased in MS patients, while pro-inflammatory miR-155 is downregulated in the same patients. These changes may indicate the attempt of monocytes to counteract neuroinflammation. miR-124, an anti-inflammatory marker but also of myeloid cell quiescence was strongly downregulated, especially in progressive MS patients, suggesting complete loss of homeostatic monocyte function in the progressive disease phase. Profiling of miRNAs that control monocyte polarization may help to define not only the activation state of monocytes in the course of the disease but also novel pathogenic mechanisms.

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Figure 1 miRNAs expression levels in monocytes of HDs and MS patients by Real-Time PCR. Quantitative Real-Time PCR analysis of (a) mir-146a; (b) mir-223; (c) mir-125a; (d) mir-30c; (e) mir-181a; (f) mir-23a; (g) mir-155; (h) miR-124 was performed. The relative expression levels were calculated using the comparative Ct method, with RNU1A1 as endogenous control. Data are expressed as mean ± SEM of fold change values (*p < 0.05; **p < 0.01; ***p < 0.001), Kruskal-Wallis followed by Mann Whitney U test.
Figure 1 miRNAs expression levels in monocytes of HDs and MS patients by Real-Time PCR. Quantitative Real-Time PCR analysis of (a) mir-146a; (b) mir-223; (c) mir-125a; (d) mir-30c; (e) mir-181a; (f) mir-23a; (g) mir-155; (h) miR-124 was performed. The relative expression levels were calculated using the comparative Ct method, with RNU1A1 as endogenous control. Data are expressed as mean ± SEM of fold change values (*p < 0.05; **p < 0.01; ***p < 0.001), Kruskal-Wallis followed by Mann Whitney U test.CC BY · PubMed Central
Figure 2 Phenotypic mRNAs expression levels in monocytes of HDs and MS patients by Real-Time PCR. Quantitative Real-Time PCR analysis of (a) IL-1β; (b) TNF-α; (c) IL-10; (d) CHI3L1 was performed. The relative expression levels were calculated using the comparative Ct method, with ACT-β as endogenous control. Data are expressed as mean ± SEM of fold change values (*p < 0.05; **p < 0.01; ***p < 0.001), Kruskal-Wallis followed by Mann Whitney U test.
Figure 2 Phenotypic mRNAs expression levels in monocytes of HDs and MS patients by Real-Time PCR. Quantitative Real-Time PCR analysis of (a) IL-1β; (b) TNF-α; (c) IL-10; (d) CHI3L1 was performed. The relative expression levels were calculated using the comparative Ct method, with ACT-β as endogenous control. Data are expressed as mean ± SEM of fold change values (*p < 0.05; **p < 0.01; ***p < 0.001), Kruskal-Wallis followed by Mann Whitney U test.CC BY · PubMed Central

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Cites

Research works printed but not linked: 51

  1. Compston, A. & Coles, A. Multiple sclerosis. Lancet 372, 1502–1517 (2008). · DOI
  2. Sospedra, M. & Martin, R. Immunology of Multiple Sclerosis. Semin Neurol 36, 115–127 (2016). · DOI
  3. Milo, R. & Kahana, E. Multiple sclerosis: geoepidemiology, genetics and the environment. Autoimmun Rev 9, A387–394 (2010). · DOI
  4. Hemmer, B., Kerschensteiner, M. & Korn, T. Role of the innate and adaptive immune responses in the course of multiple sclerosis. Lancet Neurol 14, 406–419 (2015). · DOI
  5. Henderson, A. P. D., Barnett, M. H., Parratt, J. D. E. & Prineas, J. W. Multiple sclerosis: distribution of inflammatory cells in newly forming lesions. Ann. Neurol. 66, 739–753 (2009). · DOI
  6. Lucchinetti, C. et al. Heterogeneity of multiple sclerosis lesions: implications for the pathogenesis of demyelination. Ann. Neurol. 47, 707–717 (2000). · DOI
  7. Wang, N., Liang, H. & Zen, K. Molecular mechanisms that influence the macrophage m1-m2 polarization balance. Front Immunol 5, 614 (2014).
  8. Martinez, F. O., Sica, A., Mantovani, A. & Locati, M. Macrophage activation and polarization. Front. Biosci. 13, 453–461 (2008). · DOI · Paper page
  9. Jakobsson, J. et al. Monocyte and microglial activation in patients with mood-stabilized bipolar disorder. J Psychiatry Neurosci 40, 250–258 (2015). · DOI
  10. Locatelli, G. et al. Mononuclear phagocytes locally specify and adapt their phenotype in a multiple sclerosis model. Nat. Neurosci. 21, 1196–1208 (2018). · DOI · Paper page
  11. Filipowicz, W., Bhattacharyya, S. N. & Sonenberg, N. Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight? Nat. Rev. Genet. 9, 102–114 (2008). · DOI
  12. Essandoh, K., Li, Y., Huo, J. & Fan, G.-C. MiRNA-Mediated Macrophage Polarization and its Potential Role in the Regulation of Inflammatory Response. Shock 46, 122–131 (2016). · DOI
  13. Vella, L. J., Hill, A. F. & Cheng, L. Focus on Extracellular Vesicles: Exosomes and Their Role in Protein Trafficking and Biomarker Potential in Alzheimer’s and Parkinson’s Disease. Int J Mol Sci 17, 173 (2016). · DOI
  14. Selmaj, I. et al. Global exosome transcriptome profiling reveals biomarkers for multiple sclerosis. Ann. Neurol. 81, 703–717 (2017). · DOI
  15. Kimura, K. et al. Circulating exosomes suppress the induction of regulatory T cells via let-7i in multiple sclerosis. Nat Commun 9, 17 (2018). · DOI
  16. Jagot, F. & Davoust, N. Is It worth Considering Circulating microRNAs in Multiple Sclerosis? Front Immunol 7, 129 (2016). · DOI · Paper page
  17. Keller, A. et al. Multiple sclerosis: microRNA expression profiles accurately differentiate patients with relapsing-remitting disease from healthy controls. PLoS ONE 4, e7440 (2009). · DOI
  18. Junker, A. et al. MicroRNA profiling of multiple sclerosis lesions identifies modulators of the regulatory protein CD47. Brain 132, 3342–3352 (2009). · DOI · Paper page
  19. Ridolfi, E. et al. Expression and Genetic Analysis of MicroRNAs Involved in Multiple Sclerosis. Int J Mol Sci 14, 4375–4384 (2013). · DOI
  20. Fenoglio, C. et al. Expression and genetic analysis of miRNAs involved in CD4+ cell activation in patients with multiple sclerosis. Neurosci. Lett. 504, 9–12 (2011). · DOI
  21. Ghorbani, S. et al. MicroRNA-181 Variants Regulate T Cell Phenotype in the Context of Autoimmune Neuroinflammation. Front Immunol 8, 758 (2017). · DOI
  22. Fenoglio, C. et al. Effect of fingolimod treatment on circulating miR-15b, miR23a and miR-223 levels in patients with multiple sclerosis. J. Neuroimmunol. 299, 81–83 (2016). · DOI
  23. Ghadiri, N. et al. Analysis of the expression of mir-34a, mir-199a, mir-30c and mir-19a in peripheral blood CD4+T lymphocytes of relapsing-remitting multiple sclerosis patients. Gene 659, 109–117 (2018). · DOI
  24. Lu, L. et al. Time Series miRNA-mRNA integrated analysis reveals critical miRNAs and targets in macrophage polarization. Sci Rep 6, 37446 (2016). · DOI
  25. Xie, W. et al. MiR-181a regulates inflammation responses in monocytes and macrophages. PLoS ONE 8, e58639 (2013). · DOI
  26. Ceolotto, G. et al. miR-30c-5p regulates macrophage-mediated inflammation and pro-atherosclerosis pathways. Cardiovasc. Res. 113, 1627–1638 (2017). · DOI
  27. Ponomarev, E. D., Veremeyko, T. & Weiner, H. L. MicroRNAs are universal regulators of differentiation, activation, and polarization of microglia and macrophages in normal and diseased CNS. Glia 61, 91–103 (2013). · DOI · Paper page
  28. Harraz, M. M., Xu, J.-C., Guiberson, N., Dawson, T. M. & Dawson, V. L. MiR-223 regulates the differentiation of immature neurons. Mol Cell Ther 2 (2014). · DOI
  29. Blonda, M., Amoruso, A., Grasso, R., Di Francescantonio, V. & Avolio, C. Multiple Sclerosis Treatments Affect Monocyte-Derived Microvesicle Production. Front Neurol 8 (2017). · DOI
  30. Chuluundorj, D., Harding, S. A., Abernethy, D. & La Flamme, A. C. Expansion and preferential activation of the CD14(+)CD16(+) monocyte subset during multiple sclerosis. Immunol. Cell Biol. 92, 509–517 (2014). · DOI
  31. Waschbisch, A. et al. Pivotal Role for CD16+ Monocytes in Immune Surveillance of the Central Nervous System. J. Immunol. 196, 1558–1567 (2016). · DOI
  32. Wu, D. et al. Brain 491 endothelial miR-146a negatively modulates T-cell adhesion through repressing multiple 492 targets to inhibit NF-κB activation. J Cereb Blood Flow Metab. 35, 412–23 (2015). · DOI
  33. Wu, H. et al. Extracellular vesicles containing miR-146a attenuate experimental colitis by targeting TRAF6 and IRAK1. Int. Immunopharmacol. 68, 204–212 (2019). · DOI
  34. Fumagalli, M., Lombardi, M., Gressens, P. & Verderio, C. How to reprogram microglia toward 497 beneficial functions. Glia 66, 2531–49 (2018). · DOI
  35. Galloway, D. A. et al. miR-223 promotes regenerative myeloid cell phenotype and function in the demyelinated central nervous system. Glia. 67, 857–869 (2018). · DOI · Paper page
  36. Bartel, D. P. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 116, 281–97 (2004). · DOI
  37. Ying, W. et al. MicroRNA-223 is a crucial mediator of PPARγ-regulated alternative macrophage activation. J. Clin. Invest. 125, 4149–4159 (2015). · DOI · Paper page
  38. Ismail, N. et al. Macrophage microvesicles induce macrophage differentiation and miR-223 transfer. Blood 121, 984–995 (2013). · DOI
  39. Seoudi, A. M., Lashine, Y. A. & Abdelaziz, A. I. MicroRNA-181a - a tale of discrepancies. Expert Rev Mol Med 14, e5 (2012). · DOI
  40. Sarchielli, P. et al. Fibroblast growth factor-2 levels are elevated in the cerebrospinal fluid of multiple sclerosis patients. Neurosci. Lett. 435, 223–228 (2008). · DOI
  41. Varendi, K., Kumar, A., Härma, M.-A. & Andressoo, J.-O. miR-1, miR-10b, miR-155, and miR-191 are novel regulators of BDNF. Cell. Mol. Life Sci. 71, 4443–4456 (2014). · DOI · Paper page
  42. Gaudet, A. D. et al. miR-155 Deletion in Mice Overcomes Neuron-Intrinsic and Neuron-Extrinsic Barriers to Spinal Cord Repair. J. Neurosci. 36, 8516–8532 (2016). · DOI
  43. Slota, J. A. & Booth, S. A. MicroRNAs in Neuroinflammation: Implications in Disease Pathogenesis, Biomarker Discovery and Therapeutic Applications. Noncoding RNA 5 (2019). · DOI
  44. Dutta, R. et al. Hippocampal demyelination and memory dysfunction are associated with increased levels of the neuronal microRNA miR-124 and reduced AMPA receptors. Ann. Neurol. 73, 637–645 (2013). · DOI · Paper page
  45. Kemanetzoglou, E. & Andreadou, E. CNS Demyelination with TNF-α Blockers. Curr Neurol Neurosci Rep 17, 36 (2017). · DOI
  46. O’Garra, A. & Vieira, P. T(H)1 cells control themselves by producing interleukin-10. Nat. Rev. Immunol. 7, 425–428 (2007). · DOI
  47. Novakova, L. et al. Cerebrospinal fluid biomarkers as a measure of disease activity and treatment efficacy in relapsing-remitting multiple sclerosis. J. Neurochem. 141, 296–304 (2017). · DOI
  48. Burman, J. et al. YKL-40 is a CSF biomarker of intrathecal inflammation in secondary progressive multiple sclerosis. J. Neuroimmunol. 292, 52–57 (2016). · DOI
  49. Hinsinger, G. et al. Chitinase 3-like proteins as diagnostic and prognostic biomarkers of multiple sclerosis. Mult. Scler. 21, 1251–1261 (2015). · DOI
  50. Rathcke, C. N. & Vestergaard, H. YKL-40, a new inflammatory marker with relation to insulin resistance and with a role in endothelial dysfunction and atherosclerosis. Inflamm. Res. 55, 221–227 (2006). · DOI
  51. Amoruso, A. et al. Effect of fingolimod action on the release of monocyte-derived microvesicles in multiple sclerosis patients. J. Neuroimmunol. 323, 43–48 (2018). · DOI

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Metadata

Authors
Amoruso, A., Blonda, M., Gironi, M., Grasso, R., Di Francescantonio, V., Scaroni, F., Furlan, R., Verderio, C., & Avolio, C.
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2020-04-09
Volume
10
Issue
1
ISSN
2045-2322
DOI
10.1038/s41598-020-63282-3
PMC
PMC7145856
Cited by
46
References
9
Language
en
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