Variants of MicroRNA Genes: Gender-Specific Associations with Multiple Sclerosis Risk and Severity

Ivan Kiselev, Vitalina Bashinskaya, Olga Kulakova, Natalia Baulina, Ekaterina Popova, Alexey Boyko, Olga Favorova, Ivan Kiselev, Vitalina Bashinskaya, Olga Kulakova, Natalia Baulina, Ekaterina Popova, Alexey Boyko, Olga Favorova

Abstract

Multiple sclerosis (MS) is an autoimmune neuro-inflammatory disease arising from complex interactions of genetic, epigenetic, and environmental factors. Variations in genes of some microRNAs--key post-transcriptional regulators of many genes--can influence microRNAs expression/function and contribute to MS via expression changes of protein-coding target mRNA genes. We performed an association study of polymorphous variants of MIR146A rs2910164, MIR196A2 rs11614913, MIR499A rs3746444 MIR223 rs1044165 and their combinations with MS risk and severity. 561 unrelated patients with bout-onset MS and 441 healthy volunteers were enrolled in the study. We observed associations of MS risk with allele MIR223*T and combination (MIR223*T + MIR146A*G/G) carriage in the entire groups and in women at Bonferroni-corrected significance level (pcorr < 0.05). Besides, MIR146A*G/G association with MS was observed in women with nominal significance (pf = 0.025). No MS associations were found in men. A more severe MS course (MSSS value > 3.5) was associated with the carriage of MIR499A*C/T and, less reliably, of MIR499A*C (pcorr = 0.006 and pcorr = 0.024, respectively) and with the carriage of combinations (MIR499A*C/T + MIR196A2*C) and (MIR499A*C + MIR196A2*C) (pcorr = 0.00078 and pcorr = 0.0059, respectively). These associations also showed gender specificity, as they were not significant in men and substantially reinforced in women. The strongest association with MS severity was observed in women for combination (MIR499A*C/T + MIR196A2*C): pcorr = 4.43 × 10(-6) and OR = 3.23 (CI: 1.99-5.26).

Keywords: MSSS; SNP; association analysis; microRNA; multiple sclerosis; susceptibility.

References

    1. Bruck W. The pathology of multiple sclerosis is the result of focal inflammatory demyelination with axonal damage. J. Neurol. 2005;252(Suppl. 5):v3–v9. doi: 10.1007/s00415-005-5002-7.
    1. Ponzio M., Brichetto G., Zaratin P., Battaglia M.A. Workers with disability: The case of multiple sclerosis. Neurol. Sci. 2015:1–7. doi: 10.1007/s10072-015-2265-3.
    1. Racosta J.M., Kimpinski K., Morrow S.A., Kremenchutzky M. Autonomic dysfunction in multiple sclerosis. Auton. Neurosci. 2015 doi: 10.1016/j.autneu.2015.06.001.
    1. Iwanowski P., Losy J. Immunological differences between classical phenothypes of multiple sclerosis. J. Neurol. Sci. 2015;349:10–14. doi: 10.1016/j.jns.2014.12.035.
    1. Ransohoff R.M., Hafler D.A., Lucchinetti C.F. Multiple sclerosis—A quiet revolution. Nat. Rev. Neurol. 2015;11:134–142. doi: 10.1038/nrneurol.2015.14.
    1. Roxburgh R.H., Seaman S.R., Masterman T., Hensiek A.E., Sawcer S.J., Vukusic S., Achiti I., Confavreux C., Coustans M., le Page E., et al. Multiple Sclerosis Severity Score: Using disability and disease duration to rate disease severity. Neurology. 2005;64:1144–1151. doi: 10.1212/01.WNL.0000156155.19270.F8.
    1. Bergamaschi R., Montomoli C., Mallucci G., Lugaresi A., Izquierdo G., Grand’Maison F., Duquette P., Shaygannejad V., Alroughani R., Grammond P., et al. BREMSO: A simple score to predict early the natural course of multiple sclerosis. Eur. J. Neurol. 2015;22:981–989. doi: 10.1111/ene.12696.
    1. Oksenberg J.R. Decoding multiple sclerosis: An update on genomics and future directions. Expert Rev. Neurother. 2013;13(Suppl. 12):11–19. doi: 10.1586/14737175.2013.865867.
    1. Koch M.W., Metz L.M., Kovalchuk O. Epigenetic changes in patients with multiple sclerosis. Nat. Rev. Neurol. 2013;9:35–43. doi: 10.1038/nrneurol.2012.226.
    1. miRBase. [(accessed on 1 July 2015)]. Available online:
    1. Ha T.Y. MicroRNAs in human diseases: From cancer to cardiovascular disease. Immune Netw. 2011;11:135–154. doi: 10.4110/in.2011.11.3.135.
    1. Gracias D.T., Katsikis P.D. MicroRNAs: Key components of immune regulation. Adv. Exp. Med. Biol. 2011;780:15–26.
    1. Diao L., Marcais A., Norton S., Chen K.C. MixMir: MicroRNA motif discovery from gene expression data using mixed linear models. Nucleic Acids Res. 2014;42:e135. doi: 10.1093/nar/gku672.
    1. Fenoglio C., Cantoni C., de Riz M., Ridolfi E., Cortini F., Serpente M., Villa C., Comi C., Monaco F., Mellesi L., et al. Expression and genetic analysis of miRNAs involved in CD4+ cell activation in patients with multiple sclerosis. Neurosci. Lett. 2011;504:9–12. doi: 10.1016/j.neulet.2011.08.021.
    1. Long L., Yu P., Liu Y., Wang S., Li R., Shi J., Zhang X., Li Y., Sun X., Zhou B., et al. Upregulated microRNA-155 expression in peripheral blood mononuclear cells and fibroblast-like synoviocytes in rheumatoid arthritis. Clin. Dev. Immunol. 2013;296139 doi: 10.1155/2013/296139.
    1. Lv Y., Qi R., Xu J., Di Z., Zheng H., Huo W., Zhang L., Chen H., Gao X. Profiling of serum and urinary microRNAs in children with atopic dermatitis. PLoS ONE. 2014;9:e115448. doi: 10.1371/journal.pone.0115448.
    1. Zhu J., Huang X., Su G., Wang L., Wu F., Zhang T., Song G. High expression levels of microRNA-629, microRNA-525-5p and microRNA-516a-3p in paediatric systemic lupus erythematosus. Clin. Rheumatol. 2014;33:807–815. doi: 10.1007/s10067-014-2583-5.
    1. Haghikia A., Haghikia A., Hellwig K., Baraniskin A., Holzmann A., Decard B.F., Thum T., Gold R. Regulated microRNAs in the CSF of patients with multiple sclerosis: A case-control study. Neurology. 2012;79:2166–2170. doi: 10.1212/WNL.0b013e3182759621.
    1. Junker A., Krumbholz M., Eisele S., Mohan H., Augstein F., Bittner R., Lassmann H., Wekerle H., Hohlfeld R., Meinl E. MicroRNA profiling of multiple sclerosis lesions identifies modulators of the regulatory protein CD47. Brain. 2009;132:3342–3352. doi: 10.1093/brain/awp300.
    1. Keller A., Leidinger P., Lange J., Borries A., Schroers H., Scheffler M., Lenhof H.P., Ruprecht K., Meese E. Multiple sclerosis: MicroRNA expression profiles accurately differentiate patients with relapsing-remitting disease from healthy controls. PLoS ONE. 2009;4:e7440. doi: 10.1371/journal.pone.0007440.
    1. Hu Z., Chen J., Tian T., Zhou X., Gu H., Xu L., Zeng Y., Miao R., Jin G., Ma H., et al. Genetic variants of miRNA sequences and non-small cell lung cancer survival. J. Clin. Investig. 2008;118:2600–2608. doi: 10.1172/JCI34934.
    1. Jazdzewski K., Murray E.L., Franssila K., Jarzab B., Schoenberg D.R., de la Chapelle A. Common SNP in pre-miR-146a decreases mature miR expression and predisposes to papillary thyroid carcinoma. Proc. Nat. Acad. Sci. USA. 2008;105:7269–7274. doi: 10.1073/pnas.0802682105.
    1. Hashemi M., Eskandari-Nasab E., Zakeri Z., Atabaki M., Bahari G., Jahantigh M., Taheri M., Ghavami S. Association of pre-miRNA-146a rs2910164 and premiRNA-499 rs3746444 polymorphisms and susceptibility to rheumatoid arthritis. Mol. Med. Rep. 2013;7:287–291.
    1. Jimenez-Morales S., Gamboa-Becerra R., Baca V., del Rio-Navarro B.E., Lopez-Ley D.Y., Velazquez-Cruz R., Saldana-Alvarez Y., Salas-Martinez G., Orozco L. MiR-146a polymorphism is associated with asthma but not with systemic lupus erythematosus and juvenile rheumatoid arthritis in Mexican patients. Tissue Antigens. 2012;80:317–321. doi: 10.1111/j.1399-0039.2012.01929.x.
    1. Okubo M., Tahara T., Shibata T., Yamashita H., Nakamura M., Yoshioka D., Yonemura J., Kamiya Y., Ishizuka T., Nakagawa Y., et al. Association study of common genetic variants in pre-microRNAs in patients with ulcerative colitis. J. Clin. Immunol. 2011;31:69–73. doi: 10.1007/s10875-010-9461-y.
    1. Oner T., Yenmis G., Tombulturk K., Cam C., Kucuk O.S., Yakicier M.C., Dizman D., Sultuybek G.K. Association of pre-miRNA-499 rs3746444 and pre-miRNA-146a rs2910164 polymorphisms and susceptibility to Behcet’s disease. Genet. Test. Mol. Biomark. 2015;19:424–430. doi: 10.1089/gtmb.2015.0016.
    1. Ridolfi E., Fenoglio C., Cantoni C., Calvi A., de Riz M., Pietroboni A., Villa C., Serpente M., Bonsi R., Vercellino M., et al. Expression and genetic analysis of microRNAs involved in multiple sclerosis. Int. J. Mol. Sci. 2013;14:4375–4384. doi: 10.3390/ijms14034375.
    1. Cierny D., Hanysova S., Michalik J., Kantorova E., Kurca E., Skerenova M., Lehotsky J. Genetic variants in interleukin 7 receptor α chain (IL-7Ra) are associated with multiple sclerosis risk and disability progression in Central European Slovak population. J. Neuroimmunol. 2015;282:80–84. doi: 10.1016/j.jneuroim.2015.03.010.
    1. Clayton D.G. Sex chromosomes and genetic association studies. Genome Med. 2009;1:110. doi: 10.1186/gm110.
    1. Vogt L., Schmitz N., Kurrer M.O., Bauer M., Hinton H.I., Behnke S., Gatto D., Sebbel P., Beerli R.R., Sonderegger I., et al. VSIG4, a B7 family-related protein, is a negative regulator of T cell activation. J. Clin. Investig. 2006;116:2817–2826. doi: 10.1172/JCI25673.
    1. Lvovs D., Favorova O.O., Favorov A.V. A polygenic approach to the study of polygenic diseases. Acta Naturae. 2012;4:59–71.
    1. Li Y., Du C., Wang W., Ma G., Cui L., Zhou H., Tao H., Yao L., Zhao B., Li K. Genetic association of MiR-146a with multiple sclerosis susceptibility in the Chinese population. Cell. Physiol. Biochem. 2015;35:281–291. doi: 10.1159/000369695.
    1. Ciccacci C., Perricone C., Ceccarelli F., Rufini S., Di Fusco D., Alessandri C., Spinelli F. R., Cipriano E., Novelli G., Valesini G., et al. A multilocus genetic study in a cohort of Italian SLE patients confirms the association with STAT4 gene and describes a new association with HCP5 gene. PLoS ONE. 2014;9:e111991. doi: 10.1371/journal.pone.0111991.
    1. Zhang B., Wang A., Xia C., Lin Q., Chen C. A single nucleotide polymorphism in primarymicroRNA146a reduces the expression of mature microRNA146a in patients with Alzheimer’s disease and is associated with the pathogenesis of Alzheimer’s disease. Mol. Med. Rep. 2015;12:4037–4042.
    1. Ciccacci C., di Fusco D., Cacciotti L., Morganti R., D’Amato C., Greco C., Rufini S., Novelli G., Sangiuolo F., Spallone V., et al. MicroRNA genetic variations: Association with type 2 diabetes. Acta Diabetol. 2013;50:867–872. doi: 10.1007/s00592-013-0469-7.
    1. Iyer A., Zurolo E., Prabowo A., Fluiter K., Spliet W.G., van Rijen P.C., Gorter J.A., Aronica E. MicroRNA-146a: A key regulator of astrocyte-mediated inflammatory response. PLoS ONE. 2012;7:e44789. doi: 10.1371/journal.pone.0044789.
    1. Omrane I., Benammar-Elgaaied A. The immune microenvironment of the colorectal tumor: Involvement of immunity genes and microRNAs belonging to the TH17 pathway. Biochim. Biophys. Acta. 2015;1856:28–38. doi: 10.1016/j.bbcan.2015.04.001.
    1. Kurtzke J.F. Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS) Neurology. 1983;33:1444–1452. doi: 10.1212/WNL.33.11.1444.
    1. Depaz R., Granger B., Cournu-Rebeix I., Bouafia A., Fontaine B. Genetics for understanding and predicting clinical progression in multiple sclerosis. Rev. Neurol. 2011;167:791–801. doi: 10.1016/j.neurol.2011.02.043.
    1. Harding K., Ingram G., Cossburn M., Hirst C., Pickersgill T., Ben-Shlomo Y., Robertson N. Genotype-phenotype correlation for non-HLA disease associated risk alleles in multiple sclerosis. Neurosci. Lett. 2012;526:15–19. doi: 10.1016/j.neulet.2012.06.040.
    1. Schmied M.C., Zehetmayer S., Reindl M., Ehling R., Bajer-Kornek B., Leutmezer F., Zebenholzer K., Hotzy C., Lichtner P., Meitinger T., et al. Replication study of multiple sclerosis (MS) susceptibility alleles and correlation of DNA-variants with disease features in a cohort of Austrian MS patients. Neurogenetics. 2012;13:181–187. doi: 10.1007/s10048-012-0316-y.
    1. Kikuchi S., Fukazawa T., Niino M., Yabe I., Miyagishi R., Hamada T., Tashiro K. Estrogen receptor gene polymorphism and multiple sclerosis in Japanese patients: Interaction with HLA-DRB1*1501 and disease modulation. J. Neuroimmunol. 2002;128:77–81. doi: 10.1016/S0165-5728(02)00140-6.
    1. Niino M., Kikuchi S., Fukazawa T., Yabe I., Tashiro K. Polymorphisms of apolipoprotein E and Japanese patients with multiple sclerosis. Mult. Scler. 2003;9:382–386. doi: 10.1191/1352458503ms934oa.
    1. El-Shal A.S., Aly N.M., Galil S.M., Moustafa M.A., Kandel W.A. Association of microRNAs genes polymorphisms with rheumatoid arthritis in Egyptian female patients. Jt. Bone Spine. 2013;80:626–631. doi: 10.1016/j.jbspin.2013.03.005.
    1. Qi J., Hou S., Zhang Q., Liao D., Wei L., Fang J., Zhou Y., Kijlstra A., Yang P. A functional variant of pre-miRNA-196a2 confers risk for Behcet’s disease but not for Vogt-Koyanagi-Harada syndrome or AAU in ankylosing spondylitis. Hum. Genet. 2013;132:1395–1404. doi: 10.1007/s00439-013-1346-8.
    1. Blood eQTL Browser. [(accessed on 1 July 2015)]. Available online:
    1. Westra H.J., Peters M.J., Esko T., Yaghootkar H., Schurmann C., Kettunen J., Christiansen M.W., Fairfax B.P., Schramm K., Powell J.E., et al. Systematic identification of trans eQTLs as putative drivers of known disease associations. Nat. Genet. 2013;45:1238–1243. doi: 10.1038/ng.2756.
    1. Dai R., Phillips R.A., Zhang Y., Khan D., Crasta O., Ahmed S.A. Suppression of LPS-induced Interferon-gamma and nitric oxide in splenic lymphocytes by select estrogen-regulated microRNAs: A novel mechanism of immune modulation. Blood. 2008;112:4591–4597. doi: 10.1182/blood-2008-04-152488.
    1. Kim K., Madak-Erdogan Z., Ventrella R., Katzenellenbogen B.S. A MicroRNA196a2* and TP63 circuit regulated by estrogen receptor-α and ERK2 that controls breast cancer proliferation and invasiveness properties. Horm. Cancer. 2013;4:78–91. doi: 10.1007/s12672-012-0129-3.
    1. Polman C.H., Reingold S.C., Edan G., Filippi M., Hartung H.P., Kappos L., Lublin F.D., Metz L.M., McFarland H.F., O’Connor P.W., et al. Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald Criteria”. Ann. Neurol. 2005;58:840–846. doi: 10.1002/ana.20703.
    1. Sambrook J., Fritsch E.F., Maniatis T. Molecular Cloning: A Laboratory Manual. 2nd ed. Cold Spring Harbor Laboratory Press; New York, NY, USA: 1989.
    1. Favorov A.V., Andreewski T.V., Sudomoina M.A., Favorova O.O., Parmigiani G., Ochs M.F. A Markov chain Monte Carlo technique for identification of combinations of allelic variants underlying complex diseases in humans. Genetics. 2005;171:2113–2121. doi: 10.1534/genetics.105.048090.
    1. Apsampler. [(accessed on 1 July 2015)]. Available online:

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