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Potential Biomarker and Therapeutic LncRNAs in Multiple Sclerosis Through Targeting Memory B Cells

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Abstract

Multiple sclerosis (MS) is a chronic autoimmune disease that degenerates the central nervous system (CNS). B cells exacerbate the progression of CNS lesions in MS by producing auto-antibodies, pro-inflammatory cytokines, and presenting auto-antigens to activated T cells. Long non-coding RNAs (lncRNAs) play a crucial role in complex biological processes and their stability in body fluids combined with their tissue specificity make these biomolecules promising biomarker candidates for MS diagnosis. In the current study, we investigated memory B cell-specific lncRNAs located, on average, less than 50 kb from differentially expressed protein-coding genes in MS patients compared to healthy individuals. Moreover, we included in our selection criteria lncRNA transcripts predicted to interact with microRNAs with established involvement in MS. To assess the expression levels of lncRNAs and their adjacent protein-coding genes, quantitative reverse transcription PCR was performed on peripheral blood mononuclear cells samples of 50 MS patients compared to 25 controls. Our results showed that in relapsing MS patients, compared to remitting MS patients and healthy controls, lncRNA RP11-530C5.1 was up-regulated while AL928742.12 was down-regulated. Pearson’s correlation tests showed positive correlations between the expression levels of RP11-530C5.1 and AL928742.12 with PAWR and IGHA2, respectively. The results of the ROC curve test demonstrated the potential biomarker roles of AL928742.12 and RP11-530C5.1. We conclude that these lncRNAs are potential markers for detection of relapsing MS patients.

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Abbreviations

cDNA:

Complementary DNA

CNS:

Central nervous system

DNase I:

Deoxyribonuclease I

EDSS:

Expanded disability status scale

GEO:

Gene expression omnibus

GSE:

GEO series

IGHA2 :

Immunoglobulin heavy constant alpha 2

EDTA:

Ethylenediaminetetraacetic acid

lncRNA:

Long non-coding RNA

miRNA:

microRNA

MS:

Multiple sclerosis

PAWR :

PRKC apoptosis WT1 regulator

PBMC:

Peripheral blood mononuclear cell

RT-qPCR:

Quantitative reverse transcription PCR

ROC curve:

Receiver operating characteristic

RRMS:

Relapsing-remitting multiple sclerosis

References

  • Baker, D., Marta, M., Pryce, G., Giovannoni, G., & Schmierer, K. (2017). Memory B cells are major targets for effective immunotherapy in relapsing multiple sclerosis. EBioMedicine,16, 41–50.

    PubMed  PubMed Central  Google Scholar 

  • Bar-Or, A., Calabresi, P. A., Arnold, D., Markowitz, C., Shafer, S., Kasper, L. H., et al. (2008). Rituximab in relapsing-remitting multiple sclerosis: A 72-week, open-label, phase I trial. Annals of Neurology,63(3), 395–400.

    CAS  PubMed  Google Scholar 

  • Bar-Or, A., Fawaz, L., Fan, B., Darlington, P. J., Rieger, A., Ghorayeb, C., et al. (2010). Abnormal B-cell cytokine responses a trigger of T-cell–mediated disease in MS? Annals of Neurology,67(4), 452–461.

    CAS  PubMed  Google Scholar 

  • Berger, T., Rubner, P., Schautzer, F., Egg, R., Ulmer, H., Mayringer, I., et al. (2003). Antimyelin antibodies as a predictor of clinically definite multiple sclerosis after a first demyelinating event. New England Journal of Medicine,349(2), 139–145.

    CAS  Google Scholar 

  • Cepok, S., Rosche, B., Grummel, V., Vogel, F., Zhou, D., Sayn, J., et al. (2005). Short-lived plasma blasts are the main B cell effector subset during the course of multiple sclerosis. Brain,128(7), 1667–1676.

    PubMed  Google Scholar 

  • Chen, G., Wang, Z., Wang, D., Qiu, C., Liu, M., Chen, X., et al. (2012). LncRNADisease: A database for long-non-coding RNA-associated diseases. Nucleic Acids Research,41(D1), D983–D986.

    PubMed  PubMed Central  Google Scholar 

  • Comabella, M., Cantó, E., Nurtdinov, R., Río, J., Villar, L. M., Picón, C., et al. (2015). MRI phenotypes with high neurodegeneration are associated with peripheral blood B-cell changes. Human Molecular Genetics,25(2), 308–316.

    PubMed  Google Scholar 

  • Corcione, A., Casazza, S., Ferretti, E., Giunti, D., Zappia, E., Pistorio, A., et al. (2004). Recapitulation of B cell differentiation in the central nervous system of patients with multiple sclerosis. Proceedings of the National academy of Sciences of the United States of America,101(30), 11064–11069.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Dendrou, C. A., Fugger, L., & Friese, M. A. (2015). Immunopathology of multiple sclerosis. Nature Reviews Immunology,15(9), 545.

    CAS  PubMed  Google Scholar 

  • DiStefano, J. K. (2018). The emerging role of long noncoding RNAs in human disease. Methods in Molecular Biology, 1706, 91–110.

    CAS  PubMed  Google Scholar 

  • Duddy, M., Niino, M., Adatia, F., Hebert, S., Freedman, M., Atkins, H., et al. (2007). Distinct effector cytokine profiles of memory and naive human B cell subsets and implication in multiple sclerosis. The Journal of Immunology,178(10), 6092–6099.

    CAS  PubMed  Google Scholar 

  • Fatica, A., & Bozzoni, I. (2014). Long non-coding RNAs: New players in cell differentiation and development. Nature Reviews Genetics,15(1), 7.

    CAS  PubMed  Google Scholar 

  • Fillatreau, S., Sweenie, C. H., McGeachy, M. J., Gray, D., & Anderton, S. M. (2002). B cells regulate autoimmunity by provision of IL-10. Nature Immunology,3(10), 944.

    CAS  PubMed  Google Scholar 

  • Geisler, S., & Coller, J. (2013). RNA in unexpected places: Long non-coding RNA functions in diverse cellular contexts. Nature Reviews Molecular Cell Biology,14(11), 699.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Heward, J. A., & Lindsay, M. A. (2014). Long non-coding RNAs in the regulation of the immune response. Trends in Immunology,35(9), 408–419.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Hosseini, A., Teimuri, S., Ehsani, M., Rasa, S. M. M., Etemadifar, M., Nasr Esfahani, M. H., et al. (2019). LncRNAs associated with multiple sclerosis expressed in the Th1 cell lineage. Journal of Cellular Physiology,1, 1. https://doi.org/10.1002/jcp.28779.

    Article  CAS  Google Scholar 

  • Ignacio, R. J., Liliana, P., & Edgardo, C. (2010). Oligoclonal bands and MRI in clinically isolated syndromes: Predicting conversion time to multiple sclerosis. Journal of Neurology,257(7), 1188–1191.

    PubMed  Google Scholar 

  • Krumbholz, M., Derfuss, T., Hohlfeld, R., & Meinl, E. (2012). B cells and antibodies in multiple sclerosis pathogenesis and therapy. Nature Reviews Neurology,8(11), 613.

    CAS  PubMed  Google Scholar 

  • Kurtzke, J. F. (1983). Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS). Neurology,33(11), 1444.

    CAS  PubMed  Google Scholar 

  • Lee, J. T. (2012). Epigenetic regulation by long noncoding RNAs. Science,338(6113), 1435–1439.

    CAS  PubMed  Google Scholar 

  • Li, J.-H., Liu, S., Zhou, H., Qu, L.-H., & Yang, J.-H. (2013). starBase v2. 0: Decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq data. Nucleic Acids Research,42(D1), D92–D97.

    PubMed  PubMed Central  Google Scholar 

  • Liao, Q., Liu, C., Yuan, X., Kang, S., Miao, R., Xiao, H., et al. (2011). Large-scale prediction of long non-coding RNA functions in a coding–non-coding gene co-expression network. Nucleic Acids Research,39(9), 3864–3878.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Lisak, R. P., Nedelkoska, L., Benjamins, J. A., Schalk, D., Bealmear, B., Touil, H., et al. (2017). B cells from patients with multiple sclerosis induce cell death via apoptosis in neurons in vitro. Journal of Neuroimmunology,309, 88–99.

    CAS  PubMed  Google Scholar 

  • McFarland, H. F., & Martin, R. (2007). Multiple sclerosis: A complicated picture of autoimmunity. Nature Immunology,8(9), 913.

    CAS  PubMed  Google Scholar 

  • McHeyzer-Williams, M., Okitsu, S., Wang, N., & McHeyzer-Williams, L. (2012). Molecular programming of B cell memory. Nature Reviews Immunology,12(1), 24.

    CAS  Google Scholar 

  • Mirza, A. H., Berthelsen, C. H., Seemann, S. E., Pan, X., Frederiksen, K. S., Vilien, M., et al. (2015). Transcriptomic landscape of lncRNAs in inflammatory bowel disease. Genome Medicine,7(1), 39.

    PubMed  PubMed Central  Google Scholar 

  • Olsson, T., Barcellos, L. F., & Alfredsson, L. (2017). Interactions between genetic, lifestyle and environmental risk factors for multiple sclerosis. Nature Reviews Neurology,13(1), 25.

    CAS  PubMed  Google Scholar 

  • Oturai, D. B., Søndergaard, H., Börnsen, L., Sellebjerg, F., & Romme Christensen, J. (2016). Identification of suitable reference genes for peripheral blood mononuclear cell subset studies in multiple sclerosis. Scandinavian Journal of Immunology,83(1), 72–80.

    CAS  PubMed  Google Scholar 

  • Paraskevopoulou, M. D., Georgakilas, G., Kostoulas, N., Reczko, M., Maragkakis, M., Dalamagas, T. M., et al. (2012). DIANA-LncBase: Experimentally verified and computationally predicted microRNA targets on long non-coding RNAs. Nucleic Acids Research,41(D1), D239–D245.

    PubMed  PubMed Central  Google Scholar 

  • Polman, C. H., Reingold, S. C., Banwell, B., Clanet, M., Cohen, J. A., Filippi, M., et al. (2011). Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Annals of Neurology,69(2), 292–302.

    PubMed  PubMed Central  Google Scholar 

  • Ranzani, V., Rossetti, G., Panzeri, I., Arrigoni, A., Bonnal, R. J., Curti, S., et al. (2015). The long intergenic noncoding RNA landscape of human lymphocytes highlights the regulation of T cell differentiation by linc-MAF-4. Nature Immunology,16(3), 318.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Schroeder, H. W., & Cavacini, L. (2010). Structure and function of immunoglobulins. Journal of Allergy and Clinical Immunology,125(2), S41–S52.

    Google Scholar 

  • Sellebjerg, F., Börnsen, L., Khademi, M., Krakauer, M., Olsson, T., Frederiksen, J., et al. (2009). Increased cerebrospinal fluid concentrations of the chemokine CXCL13 in active MS. Neurology,73(23), 2003–2010.

    CAS  PubMed  Google Scholar 

  • Spurlock, C. F., III, Tossberg, J. T., Guo, Y., Collier, S. P., Crooke, P. S., III, & Aune, T. M. (2015). Expression and functions of long noncoding RNAs during human T helper cell differentiation. Nature Communications,6, 6932.

    CAS  PubMed  Google Scholar 

  • Taft, R. J., Pang, K. C., Mercer, T. R., Dinger, M., & Mattick, J. S. (2010). Non-coding RNAs: Regulators of disease. The Journal of Pathology: A Journal of the Pathological Society of Great Britain and Ireland,220(2), 126–139.

    CAS  Google Scholar 

  • Teimuri, S., Hosseini, A., Rezaenasab, A., Ghaedi, K., Ghoveud, E., Etemadifar, M., et al. (2018). Integrative analysis of lncRNAs in Th17 cell lineage to discover new potential biomarkers and therapeutic targets in autoimmune diseases. Molecular Therapy-Nucleic Acids,12, 393–404.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Tintore, M., Rovira, A., Rio, J., Tur, C., Pelayo, R., Nos, C., et al. (2008). Do oligoclonal bands add information to MRI in first attacks of multiple sclerosis? Neurology,70(13 Part 2), 1079–1083.

    CAS  PubMed  Google Scholar 

  • Tong, Y.-K., & Lo, Y. D. (2006). Diagnostic developments involving cell-free (circulating) nucleic acids. Clinica Chimica Acta,363(1–2), 187–196.

    CAS  Google Scholar 

  • Tufekci, K. U., Oner, M. G., Genc, S., & Genc, K. (2011). MicroRNAs and multiple sclerosis. Autoimmune Diseases,1, 1. https://doi.org/10.4061/2011/807426.

    Article  CAS  Google Scholar 

  • Ulitsky, I., & Bartel, D. P. (2013). lincRNAs: Genomics, evolution, and mechanisms. Cell,154(1), 26–46.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Wang, J., Ma, R., Ma, W., Chen, J., Yang, J., Xi, Y., et al. (2016). LncDisease: A sequence based bioinformatics tool for predicting lncRNA-disease associations. Nucleic Acids Research,44(9), e90. https://doi.org/10.1093/nar/gkw093.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wilusz, J. E., Sunwoo, H., & Spector, D. L. (2009). Long noncoding RNAs: Functional surprises from the RNA world. Genes & Development,23(13), 1494–1504.

    CAS  Google Scholar 

  • Yap, K. L., Li, S., Muñoz-Cabello, A. M., Raguz, S., Zeng, L., Mujtaba, S., et al. (2010). Molecular interplay of the noncoding RNA ANRIL and methylated histone H3 lysine 27 by polycomb CBX7 in transcriptional silencing of INK4a. Molecular Cell,38(5), 662–674.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Yoon, J.-H., Abdelmohsen, K., & Gorospe, M. (2014). Functional interactions among microRNAs and long noncoding RNAs.  Seminars in Cell & Developmental Biology, 34, 9–14.

    CAS  Google Scholar 

  • Zhang, Y., & Cao, X. (2016). Long noncoding RNAs in innate immunity. Cellular & Molecular Immunology,13(2), 138.

    Google Scholar 

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Acknowledgements

The authors declare that they have no competing interests. A part of this project was supported by the National Institute for Medical Research Development (NIMAD’s Project No. 942792) and also partly by Royan Institute for Biotechnology.

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Correspondence to Jafar Vatandoost, Kamran Ghaedi or Mohammad Hossein Nasr Esfahani.

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Ghoveud, E., Teimuri, S., Vatandoost, J. et al. Potential Biomarker and Therapeutic LncRNAs in Multiple Sclerosis Through Targeting Memory B Cells. Neuromol Med 22, 111–120 (2020). https://doi.org/10.1007/s12017-019-08570-6

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