Advertisement

MicroRNA-132, miR-146a, and miR-155 as potential biomarkers of methotrexate response in patients with rheumatoid arthritis

  • Ankita Singh
  • Pradeepta Sekhar Patro
  • Amita Aggarwal
Original Article
  • 58 Downloads

Abstract

Introduction

Rheumatoid arthritis (RA) patients have high expression levels of hsa-miR-132-3p, hsa-miR-146a-5p, and hsa-miR-155-5p in peripheral blood. We studied if baseline blood levels of these microRNAs (miRNAs) could predict response to methotrexate (MTX).

Methods

RA patients (the American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) criteria) with active disease (disease-modifying anti-rheumatic drug (DMARD)–naïve and Disease Activity Score 28 (DAS28) > 3.2) were enrolled. They were treated with MTX by gradually increasing dose up to 25 mg/week. After 4 months, the DAS28 score was calculated and EULAR response was assessed. The hsa-miR-132-3p, hsa-miR-146a-5p, and hsa-miR-155-5p levels were measured by real-time qPCR in whole-blood RNA at baseline and 4 months after therapy, using hsa-let-7a-5p as housekeeping gene. Results are expressed as median (interquartile range).

Results

The 94 enrolled patients (81 females) had a median age of 40 (17) years, disease duration of (24) months, and DAS28 4.61 (1.11). After 4 months of therapy, 73 were classified as responders and 21 as non-responders. Baseline levels of all three miRNAs were lower in responders than non-responders, hsa-miR-132-3p (− 8.03 (0.70) versus − 7.47 (0.85), P < 0.05), hsa-miR-146a-5p (− 5.11 (0.88) versus − 4.62 (0.90), P < 0.05), and hsa-miR-155-5p (− 7.59 (1.07) versus − 7 (0.72), P = 0.002). Receiver operating characteristic curve analysis showed that all three miRNAs were also good predictors of MTX response, showing the following values: hsa-miR-132-3p (area under curve (AUC) 0.756, P < 0.05), hsa-miR-146a-5p (AUC 0.760, P < 0.05), and hsa-miR-155-5p (AUC 0.728, P = 0.002).

Conclusion

hsa-miR-132-3p, hsa-miR-146a-5p, and hsa-miR-155-5p are potential biomarkers of responsiveness to MTX therapy.

Keywords

Biomarker Disease-modifying anti-rheumatic drug Methotrexate MicroRNA Rheumatoid arthritis 

Notes

Funding statement

The project was funded by a research grant to AA and AS was supported by the Senior Research Fellowship of Indian Council of Medical research.

Compliance with ethical standards

Disclosures

None.

Supplementary material

10067_2018_4380_MOESM1_ESM.pdf (120 kb)
Supplementary Figure 1 Expression level of hsa-miR-132-3p (a), hsa-miR-146a-5p (b) and hsa-miR-155-5p (c) in responders at baseline (n=73) and 4 months after MTX therapy (n-66). Expression level of hsa-miR-132-3p (d), hsa-miR-146a-5p (e) and hsa-miR-155-5p (f) in non-responders at baseline (n=21) and 4 months after MTX therapy (n=14). *P < 0.05, as determined by Mann-Whitney U-test. BL, Baseline; FU, Follow-up; ∆Ct, Delta Threshold Cycle; R, Responder; NR, Non-Responder. (PDF 119 kb)
10067_2018_4380_MOESM2_ESM.pdf (252 kb)
Supplementary Table 1 (PDF 251 kb)

References

  1. 1.
    Halilova KI, Brown EE, Morgan SL, Bridges SL Jr, Hwang MH, Arnett DK et al (2012) Markers of treatment response to methotrexate in rheumatoid arthritis: where do we stand? Int J Rheumatol 2012:978396CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Donahue KE, Gartlehner G, Jonas DE, Lux LJ, Thieda P, Jonas BL, Hansen RA, Morgan LC, Lohr KN (2008) Systematic review: comparative effectiveness and harms of disease-modifying medications for rheumatoid arthritis. Ann Intern Med 148:124–134CrossRefPubMedGoogle Scholar
  3. 3.
    McInnes IB, Schett G (2011) The pathogenesis of rheumatoid arthritis. N Engl J Med 365:2205–2219CrossRefPubMedGoogle Scholar
  4. 4.
    Fabre S, Dupuy A, Dossat N, Guisset C, Cohen J, Cristol J et al (2008) Protein biochip array technology for cytokine profiling predicts etanercept responsiveness in rheumatoid arthritis. Clin Exp Immunol 153:188–195CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Van Venrooij WJ, Van Beers JJ, Pruijn GJ (2008) Anti-CCP antibody, a marker for the early detection of rheumatoid arthritis. Ann N Y Acad Sci 1143:268–285CrossRefPubMedGoogle Scholar
  6. 6.
    Ling S, Bluett J, Barton A (2018) Prediction of response to methotrexate in rheumatoid arthritis. Expert Rev Clin Immunol 14:419–429CrossRefPubMedGoogle Scholar
  7. 7.
    Davidson-Moncada J, Papavasiliou FN, Tam W (2010) MicroRNAs of the immune system. Ann N Y Acad Sci 1183:183–194CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Sode J, Krintel SB, Carlsen AL, Hetland ML, Johansen JS, Hørslev-Petersen K et al (2017) Plasma microRNA profiles in patients with early rheumatoid arthritis responding to adalimumab plus methotrexate vs methotrexate alone: a placebo-controlled clinical trial. J Rheumatol 45:53–61CrossRefPubMedGoogle Scholar
  9. 9.
    Cuppen BV, Rossato M, Fritsch-Stork RD, Concepcion AN, Schenk Y, Bijlsma JW et al (2016) Can baseline serum microRNAs predict response to TNF-alpha inhibitors in rheumatoid arthritis? Arthritis Res Ther 18:189CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Pauley KM, Satoh M, Chan AL, Bubb MR, Reeves WH, Chan EK (2008) Upregulated miR-146a expression in peripheral blood mononuclear cells from rheumatoid arthritis patients. Arthritis Res Ther 10:R101CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Lagos D, Pollara G, Henderson S, Gratrix F, Fabani M, Milne RS et al (2010) miR-132 regulates antiviral innate immunity through suppression of the p300 transcriptional co-activator. Nat Cell Biol 12:513–519CrossRefPubMedGoogle Scholar
  12. 12.
    Chen X, Ba Y, Ma L, Cai X, Yin Y, Wang K, Guo J, Zhang Y, Chen J, Guo X, Li Q, Li X, Wang W, Zhang Y, Wang J, Jiang X, Xiang Y, Xu C, Zheng P, Zhang J, Li R, Zhang H, Shang X, Gong T, Ning G, Wang J, Zen K, Zhang J, Zhang CY (2008) Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res 18:997–1006CrossRefPubMedGoogle Scholar
  13. 13.
    Vigorito E, Perks KL, Abreu-Goodger C, Bunting S, Xiang Z, Kohlhaas S, Das PP, Miska EA, Rodriguez A, Bradley A, Smith KGC, Rada C, Enright AJ, Toellner KM, MacLennan ICM, Turner M (2007) microRNA-155 regulates the generation of immunoglobulin class-switched plasma cells. Immunity 27:847–859CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Zhang J, Cheng Y, Cui W, Li M, Li B, Guo L (2014) MicroRNA-155 modulates Th1 and Th17 cell differentiation and is associated with multiple sclerosis and experimental autoimmune encephalomyelitis. J Neuroimmunol 266:56–63CrossRefPubMedGoogle Scholar
  15. 15.
    Taganov KD, Boldin MP, Chang K-J, Baltimore D (2006) NF-κB-dependent induction of microRNA miR-146, an inhibitor targeted to signaling proteins of innate immune responses. Proc Natl Acad Sci 103:12481–12486CrossRefPubMedGoogle Scholar
  16. 16.
    Duroux-Richard I, Jorgensen C, Apparailly F (2011) miRNAs and rheumatoid arthritis—promising novel biomarkers. Swiss Med Wkly 141:w13175PubMedGoogle Scholar
  17. 17.
    Murata K, Yoshitomi H, Tanida S, Ishikawa M, Nishitani K, Ito H, Nakamura T (2010) Plasma and synovial fluid microRNAs as potential biomarkers of rheumatoid arthritis and osteoarthritis. Arthritis Res Ther 12:R86CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Churov AV, Oleinik EK, Knip M (2015) MicroRNAs in rheumatoid arthritis: altered expression and diagnostic potential. Autoimmun Rev 14:1029–1037CrossRefPubMedGoogle Scholar
  19. 19.
    Pauley KM, Cha S (2011) miRNA-146a in rheumatoid arthritis: a new therapeutic strategy. Immunotherapy 3:829–831CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Abdul-Maksoud R, Sediq A, Kattaia A, Elsayed W, Ezzeldin N, Abdel Galil S, Ibrahem R (2017) Serum miR-210 and miR-155 expression levels as novel biomarkers for rheumatoid arthritis diagnosis. Br J Biomed Sci 74:209–213CrossRefPubMedGoogle Scholar
  21. 21.
    Zhou Q, Haupt S, Kreuzer JT, Hammitzsch A, Proft F, Neumann C, Leipe J, Witt M, Schulze-Koops H, Skapenko A (2015) Decreased expression of miR-146a and miR-155 contributes to an abnormal Treg phenotype in patients with rheumatoid arthritis. Ann Rheum Dis 74:1265–1274CrossRefPubMedGoogle Scholar
  22. 22.
    Su LC, Huang AF, Jia H, Liu Y, Xu WD (2017) Role of micro RNA-155 in rheumatoid arthritis. Int J Rheum Dis 20:1631–1637CrossRefPubMedGoogle Scholar
  23. 23.
    Rajagopalan PR, Zhang Z, McCourt L, Dwyer M, Benkovic SJ, Hammes GG (2002) Interaction of dihydrofolate reductase with methotrexate: ensemble and single-molecule kinetics. Proc Natl Acad Sci 99:13481–13486CrossRefPubMedGoogle Scholar
  24. 24.
    Aletaha D, Neogi T, Silman AJ, Funovits J, Felson DT, Bingham IIICO et al (2010) 2010 rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Arthritis Rheum 62:2569–2581CrossRefGoogle Scholar
  25. 25.
    Prevoo M, Van’T Hof MA, Kuper H, Van Leeuwen M, Van De Putte L, Van Riel P (1995) Modified disease activity scores that include twenty-eight-joint counts development and validation in a prospective longitudinal study of patients with rheumatoid arthritis. Arthritis Rheum 38:44–48CrossRefGoogle Scholar
  26. 26.
    Duroux-Richard I, Pers Y-M, Fabre S, Ammari M, Baeten D, Cartron G et al (2014) Circulating miRNA-125b is a potential biomarker predicting response to rituximab in rheumatoid arthritis. Mediat Inflamm 2014(23):342524.  https://doi.org/10.1155/2014/342524 CrossRefGoogle Scholar
  27. 27.
    Castro-Villegas C, Pérez-Sánchez C, Escudero A, Filipescu I, Verdu M, Ruiz-Limón P, Aguirre MA, Jiménez-Gomez Y, Font P, Rodriguez-Ariza A, Peinado JR, Collantes-Estévez E, González-Conejero R, Martinez C, Barbarroja N, López-Pedrera C (2015) Circulating miRNAs as potential biomarkers of therapy effectiveness in rheumatoid arthritis patients treated with anti-TNFα. Arthritis Res Ther 17:49CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Pritchard CC, Kroh E, Wood B, Arroyo JD, Dougherty KJ, Miyaji MM et al (2011) Blood cell origin of circulating microRNAs: a cautionary note for cancer biomarker studies. Cancer Prev Res 5:492–497CrossRefGoogle Scholar
  29. 29.
    Kirschner MB, Kao SC, Edelman JJ, Armstrong NJ, Vallely MP, van Zandwijk N, Reid G (2011) Haemolysis during sample preparation alters microRNA content of plasma. PLoS One 6:e24145CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Häusler S, Keller A, Chandran P, Ziegler K, Zipp K, Heuer S et al (2010) Whole blood-derived miRNA profiles as potential new tools for ovarian cancer screening. Br J Cancer 103:693–700CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Patnaik SK, Yendamuri S, Kannisto E, Kucharczuk JC, Singhal S, Vachani A (2012) MicroRNA expression profiles of whole blood in lung adenocarcinoma. PLoS One 7:e46045CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Schrauder MG, Strick R, Schulz-Wendtland R, Strissel PL, Kahmann L, Loehberg CR, Lux MP, Jud SM, Hartmann A, Hein A, Bayer CM, Bani MR, Richter S, Adamietz BR, Wenkel E, Rauh C, Beckmann MW, Fasching PA (2012) Circulating micro-RNAs as potential blood-based markers for early stage breast cancer detection. PLoS One 7:e29770CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Mookherjee N, El-Gabalawy HS (2013) High degree of correlation between whole blood and PBMC expression levels of miR-155 and miR-146a in healthy controls and rheumatoid arthritis patients. J Immunol Methods 400:106–110CrossRefPubMedGoogle Scholar
  34. 34.
    Nahid MA, Yao B, Dominguez-Gutierrez PR, Kesavalu L, Satoh M, Chan EK (2012) Regulation of TLR2-mediated tolerance and cross-tolerance through IRAK4 modulation by miR-132 and miR-212. J Immunol 190:1250–1263CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Fehri LF, Koch M, Belogolova E, Khalil H, Bolz C, Kalali B et al (2010) Helicobacter pylori induces miR-155 in T cells in a cAMP-Foxp3-dependent manner. PLoS One 5:e9500CrossRefGoogle Scholar
  36. 36.
    Peres RS, Liew FY, Talbot J, Carregaro V, Oliveira RD, Almeida SL, França RFO, Donate PB, Pinto LG, Ferreira FIS, Costa DL, Demarque DP, Gouvea DR, Lopes NP, Queiroz RHC, Silva JS, Figueiredo F, Alves-Filho JC, Cunha TM, Ferreira SH, Louzada-Junior P, Cunha FQ (2015) Low expression of CD39 on regulatory T cells as a biomarker for resistance to methotrexate therapy in rheumatoid arthritis. Proc Natl Acad Sci 112:2509–2514CrossRefPubMedGoogle Scholar
  37. 37.
    Boldin MP, Taganov KD, Rao DS, Yang L, Zhao JL, Kalwani M, Garcia-Flores Y, Luong M, Devrekanli A, Xu J, Sun G, Tay J, Linsley PS, Baltimore D (2011) miR-146a is a significant brake on autoimmunity, myeloproliferation, and cancer in mice. J Exp Med 208:1189–1201CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    Liu J, Shi K, Chen M, Xu L, Hong J, Hu B, Yang X, Sun R (2015) Elevated miR-155 expression induces immunosuppression via CD39+ regulatory T-cells in sepsis patient. Int J Infect Dis 40:135–141CrossRefPubMedGoogle Scholar
  39. 39.
    Kohlhaas S, Garden OA, Scudamore C, Turner M, Okkenhaug K, Vigorito E (2009) Cutting edge: the Foxp3 target miR-155 contributes to the development of regulatory T cells. J Immunol 182:2578–2582CrossRefPubMedGoogle Scholar
  40. 40.
    Hong H, Yang H, Xia Y (2018) Circulating miR-10a as predictor of therapy response in rheumatoid arthritis patients treated with methotrexate. Curr Pharm Biotechnol 19:79–86CrossRefPubMedGoogle Scholar
  41. 41.
    Saevarsdottir S, Wedren S, Seddighzadeh M et al (2011) Patients with early rheumatoid arthritis who smoke are less likely to respond to treatment with methotrexate and tumor necrosis factor inhibitors: observations from the Epidemiological Investigation of Rheumatoid Arthritis and the Swedish Rheumatology Register cohorts. Arthritis Rheum 63:26–36CrossRefPubMedGoogle Scholar
  42. 42.
    Anderson JJ, Wells G, Verhoeven AC, Felson DT (2000) Factors predicting response to treatment in rheumatoid arthritis: the importance of disease duration. Arthritis Rheum 43:22–29CrossRefPubMedGoogle Scholar
  43. 43.
    O’Dell JR, Nepom BS, Haire C, Gersuk VH, Gaur L, Moore GF, Drymalski W, Palmer W, Eckhoff PJ, Klassen LW, Wees S, Thiele G, Nepom GT (1998) HLA-DRB1 typing in rheumatoid arthritis: predicting response to specific treatments. Ann Rheum Dis 57:209–213CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Qiu Q, Huang J, Shu X, Fan H, Zhou Y, Xiao C (2017) Polymorphisms and pharmacogenomics for the clinical efficacy of methotrexate in patients with rheumatoid arthritis: a systematic review and meta-analysis. Sci Rep 7:44015CrossRefPubMedPubMedCentralGoogle Scholar
  45. 45.
    Drozdzik M, Rudas T, Pawlik A, Gornik W, Kurzawski M, Herczynska M (2007) Reduced folate carrier-1 80G>A polymorphism affects methotrexate treatment outcome in rheumatoid arthritis. Pharmacogenomics J 7:404–407CrossRefPubMedGoogle Scholar
  46. 46.
    Nair VS, Pritchard CC, Tewari M, Ioannidis JP (2014) Design and analysis for studying microRNAs in human disease: a primer on -omic technologies. Am J Epidemiol 180:140–152CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© International League of Associations for Rheumatology (ILAR) 2018

Authors and Affiliations

  1. 1.Department of Clinical Immunology and RheumatologySanjay Gandhi Postgraduate Institute of Medical SciencesLucknowIndia

Personalised recommendations