Advertisement

Frontiers of Medicine

, Volume 11, Issue 3, pp 378–385 | Cite as

Identification of differentially expressed miRNAs associated with chronic kidney disease–mineral bone disorder

  • Kyung Im Kim
  • Sohyun Jeong
  • Nayoung Han
  • Jung Mi Oh
  • Kook-Hwan Oh
  • In-Wha KimEmail author
Research Article

Abstract

The purpose of this study is to characterize a meta-signature of differentially expressed mRNA in chronic kidney disease (CKD) to predict putative microRNA (miRNA) in CKD–mineral bone disorder (CKD–MBD) and confirm the changes in these genes and miRNA expression under uremic conditions by using a cell culture system. PubMed searches using MeSH terms and keywords related to CKD, uremia, and mRNA arrays were conducted. Through a computational analysis, a meta-signature that characterizes the significant intersection of differentially expressed mRNA and expected miRNAs associated with CKD–MBD was determined. Additionally, changes in gene and miRNA expressions under uremic conditions were confirmed with human Saos-2 osteoblast-like cells. A statistically significant mRNA meta-signature of upregulated and downregulated mRNA levels was identified. Furthermore, miRNA expression profiles were inferred, and computational analyses were performed with the imputed microRNA regulation based on weighted ranked expression and putative microRNA targets (IMRE) method to identify miRNAs associated with CKD occurrence. TLR4 and miR-146b levels were significantly associated with CKD–MBD. TLR4 levels were significantly downregulated, whereas primiR- 146b and miR-146b were upregulated in the presence of uremic toxins in human Saos-2 osteoblast-like cells. Differentially expressed miRNAs associated with CKD-MBD were identified through a computational analysis, and changes in gene and miRNA expressions were confirmed with an in vitro cell culture system.

Keywords

chronic kidney disease microRNA mineral bone disorder uremia 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgments

This research was supported by the Basic Science Research Program (No. 2014R1A1A2055734) through the National Research Foundation of Korea (NRF) funded by the Ministry of Education and the Ministry of Science, ICT and Future Planning (No. 2014M3C1-B3064644).

Supplementary material

11684_2017_541_MOESM1_ESM.pdf (126 kb)
Supplementary material, approximately 126 KB.

References

  1. 1.
    Meyer TW, Hostetter TH. Uremia. N Engl J Med 2007; 357(13): 1316–1325CrossRefPubMedGoogle Scholar
  2. 2.
    Duranton F, Cohen G, De Smet R, Rodriguez M, Jankowski J, Vanholder R, Argiles A; European Uremic Toxin Work Group. Normal and pathologic concentrations of uremic toxins. J Am Soc Nephrol 2012; 23(7): 1258–1270CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Cibulka R, Racek J. Metabolic disorders in patients with chronic kidney failure. Physiol Res 2007; 56(6): 697–705PubMedGoogle Scholar
  4. 4.
    Lanza D, Perna AF, Oliva A, Vanholder R, Pletinck A, Guastafierro S, Di Nunzio A, Vigorito C, Capasso G, Jankowski V, Jankowski J, Ingrosso D. Impact of the uremic milieu on the osteogenic potential of mesenchymal stem cells. PLoS One 2015; 10(1): e0116468CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Meijers BK, Claes K, Bammens B, de Loor H, Viaene L, Verbeke K, Kuypers D, Vanrenterghem Y, Evenepoel P. p-Cresol and cardiovascular risk in mild-to-moderate kidney disease. Clin J Am Soc Nephrol 2010; 5(7): 1182–1189CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Moe S, Drüeke T, Cunningham J, Goodman W, Martin K, Olgaard K, Ott S, Sprague S, Lameire N, Eknoyan G; Kidney Disease: Improving Global Outcomes (KDIGO). Definition, evaluation, and classification of renal osteodystrophy: a position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int 2006; 69(11): 1945–1953CrossRefPubMedGoogle Scholar
  7. 7.
    Menon V, Gul A, Sarnak MJ. Cardiovascular risk factors in chronic kidney disease. Kidney Int 2005; 68(4): 1413–1418CrossRefPubMedGoogle Scholar
  8. 8.
    Hruska K, Mathew S, Lund R, Fang Y, Sugatani T. Cardiovascular risk factors in chronic kidney disease: does phosphate qualify? Kidney Int 2011; 79(S121): S9–S13CrossRefGoogle Scholar
  9. 9.
    Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 2004; 116(2): 281–297CrossRefPubMedGoogle Scholar
  10. 10.
    Alvarez-Garcia I, Miska EA. MicroRNA functions in animal development and human disease. Development 2005; 132(21): 4653–4662CrossRefPubMedGoogle Scholar
  11. 11.
    O’Connell RM, Rao DS, Chaudhuri AA, Baltimore D. Physiological and pathological roles for microRNAs in the immune system. Nat Rev Immunol 2010; 10(2): 111–122CrossRefPubMedGoogle Scholar
  12. 12.
    Tili E, Michaille JJ, Croce CM. MicroRNAs play a central role in molecular dysfunctions linking inflammation with cancer. Immunol Rev 2013; 253(1): 167–184CrossRefPubMedGoogle Scholar
  13. 13.
    Nana-Sinkam SP, Croce CM. MicroRNAs as therapeutic targets in cancer. Transl Res 2011; 157(4): 216–225CrossRefPubMedGoogle Scholar
  14. 14.
    Schöler N, Langer C, Döhner H, Buske C, Kuchenbauer F. Serum microRNAs as a novel class of biomarkers: a comprehensive review of the literature. Exp Hematol 2010; 38(12): 1126–1130CrossRefPubMedGoogle Scholar
  15. 15.
    Isakova T, Gutiérrez OM, Patel NM, Andress DL, Wolf M, Levin A. Vitamin D deficiency, inflammation, and albuminuria in chronic kidney disease: complex interactions. J Ren Nutr 2011; 21(4): 295–302CrossRefPubMedGoogle Scholar
  16. 16.
    Fang Y, Ginsberg C, Seifert M, Agapova O, Sugatani T, Register TC, Freedman BI, Monier-Faugere MC, Malluche H, Hruska KA. CKD-induced wingless/integration1 inhibitors and phosphorus cause the CKD-mineral and bone disorder. J Am Soc Nephrol 2014; 25(8): 1760–1773CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Neal CS, Michael MZ, Pimlott LK, Yong TY, Li JY, Gleadle JM. Circulating microRNA expression is reduced in chronic kidney disease. Nephrol Dial Transplant 2011; 26(11): 3794–3802CrossRefPubMedGoogle Scholar
  18. 18.
    Beltrami C, Clayton A, Phillips AO, Fraser DJ, Bowen T. Analysis of urinary microRNAs in chronic kidney disease. Biochem Soc Trans 2012; 40(4): 875–879CrossRefPubMedGoogle Scholar
  19. 19.
    Feichtinger J, McFarlane RJ, Larcombe LD. CancerMA: a webbased tool for automatic meta-analysis of public cancer microarray data. Database (Oxford) 2012; 2012: bas055Google Scholar
  20. 20.
    Ramasamy A, Mondry A, Holmes CC, Altman DG. Key issues in conducting a meta-analysis of gene expression microarray datasets. PLoS Med 2008; 5(9): e184CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JY, Zhang J. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 2004; 5(10): R80CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    McCall MN, Bolstad BM, Irizarry RA. Frozen robust multiarray analysis (fRMA). Biostatistics 2010; 11(2): 242–253CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Lee Y, Yang X, Huang Y, Fan H, Zhang Q, Wu Y, Li J, Hasina R, Cheng C, Lingen MW, Gerstein MB, Weichselbaum RR, Xing HR, Lussier YA. Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis. PLOS Comput Biol 2010; 6(4): e1000730CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Scheid S, Spang R. twilight; a Bioconductor package for estimating the local false discovery rate. Bioinformatics 2005; 21(12): 2921–2922CrossRefPubMedGoogle Scholar
  25. 25.
    Bauer O, Sharir A, Kimura A, Hantisteanu S, Takeda S, Groner Y. Loss of osteoblast Runx3 produces severe congenital osteopenia. Mol Cell Biol 2015; 35(7): 1097–1109CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Kim HJ, Park J, Lee SK, Kim KR, Park KK, Chung WY. Loss of RUNX3 expression promotes cancer-associated bone destruction by regulating CCL5, CCL19 and CXCL11 in non-small cell lung cancer. J Pathol 2015; 237(4): 520–531CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Reppe S, Refvem H, Gautvik VT, Olstad OK, Høvring PI, Reinholt FP, Holden M, Frigessi A, Jemtland R, Gautvik KM. Eight genes are highly associated with BMD variation in postmenopausal Caucasian women. Bone 2010; 46(3): 604–612CrossRefPubMedGoogle Scholar
  28. 28.
    Niu G, Li B, Sun J, Sun L. miR-454 is down-regulated in osteosarcomas and suppresses cell proliferation and invasion by directly targeting c-Met. Cell Prolif 2015; 48(3): 348–355CrossRefPubMedGoogle Scholar
  29. 29.
    Huang RL, Yuan Y, Zou GM, Liu G, Tu J, Li Q. LPS-stimulated inflammatory environment inhibits BMP-2-induced osteoblastic differentiation through crosstalk between TLR4/MyD88/NF-kB and BMP/Smad signaling. Stem Cells Dev 2014; 23(3): 277–289CrossRefPubMedGoogle Scholar
  30. 30.
    Ando M, Shibuya A, Tsuchiya K, Akiba T, Nitta K. Reduced capacity of mononuclear cells to synthesize cytokines against an inflammatory stimulus in uremic patients. Nephron Clin Pract 2006; 104(3): c113–c119CrossRefPubMedGoogle Scholar
  31. 31.
    Wang ZS, Xu DM, Guan GJ, Cui MY, Wei Y, Tang LJ, Jia XY, Li WB. Clinical significance of toll-like receptor 4 expression on the surface of peripheral blood mononuclear cells in uremic patients. Natl Med J China (Zhonghua Yi Xue Za Zhi) 2010; 90(34): 2389–2391 (in Chinese)Google Scholar
  32. 32.
    He X, Wang H, Jin T, Xu Y, Mei L, Yang J. TLR4 activation promotes bone marrow MSC proliferation and osteogenic differentiation via Wnt3a and Wnt5a signaling. PLoS One 2016; 11(3): e0149876CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Herzmann N, Salamon A, Fiedler T, Peters K. Lipopolysaccharide induces proliferation and osteogenic differentiation of adiposederived mesenchymal stromal cells in vitro via TLR4 activation. Exp Cell Res 2017; 350(1): 115–122CrossRefPubMedGoogle Scholar
  34. 34.
    Taganov KD, Boldin MP, Chang KJ, Baltimore D. NF-κBdependent induction of microRNA miR-146, an inhibitor targeted to signaling proteins of innate immune responses. Proc Natl Acad Sci USA 2006; 103(33): 12481–12486CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Sato T, Liu X, Nelson A, Nakanishi M, Kanaji N, Wang X, Kim M, Li Y, Sun J, Michalski J, Patil A, Basma H, Holz O, Magnussen H, Rennard SI. Reduced miR-146a increases prostaglandin E2 in chronic obstructive pulmonary disease fibroblasts. Am J Respir Crit Care Med 2010; 182(8): 1020–1029CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Cheng HS, Sivachandran N, Lau A, Boudreau E, Zhao JL, Baltimore D, Delgado-Olguin P, Cybulsky MI, Fish JE. MicroRNA-146 represses endothelial activation by inhibiting pro-inflammatory pathways. EMBO Mol Med 2013; 5(7): 1017–1034CrossRefPubMedGoogle Scholar
  37. 37.
    Larner-Svensson HM, Williams AE, Tsitsiou E, Perry MM, Jiang X, Chung KF, Lindsay MA. Pharmacological studies of the mechanism and function of interleukin-1β-induced miRNA-146a expression in primary human airway smooth muscle. Respir Res 2010; 11(1): 68CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    Perry MM, Moschos SA, Williams AE, Shepherd NJ, Larner Svensson HM, Lindsay MA. Rapid changes in microRNA-146a expression negatively regulate the IL-1β-induced inflammatory response in human lung alveolar epithelial cells. J Immunol 2008; 180(8): 5689–5698CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Curtale G, Mirolo M, Renzi TA, Rossato M, Bazzoni F, Locati M. Negative regulation of Toll-like receptor 4 signaling by IL-10-dependent microRNA-146b. Proc Natl Acad Sci USA 2013; 110(28): 11499–11504CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Asai Y, Hirokawa Y, Niwa K, Ogawa T. Osteoclast differentiation by human osteoblastic cell line SaOS-2 primed with bacterial lipid A. FEMS Immunol Med Microbiol 2003; 38(1): 71–79CrossRefPubMedGoogle Scholar
  41. 41.
    Fetahu IS, Tennakoon S, Lines KE, Gröschel C, Aggarwal A, Mesteri I, Baumgartner-Parzer S, Mader RM, Thakker RV, Kállay E. miR-135b-and miR-146b-dependent silencing of calciumsensing receptor expression in colorectal tumors. Int J Cancer 2016; 138(1): 137–145CrossRefPubMedGoogle Scholar
  42. 42.
    Bover J, Aguilar A, Baas J, Reyes J, Lloret MJ, Farré N, Olaya M, Canal C, Marco H, Andrés E, Trinidad P, Ballarin J. Calcimimetics in the chronic kidney disease-mineral and bone disorder. Int J Artif Organs 2009; 32(2): 108–121CrossRefPubMedGoogle Scholar
  43. 43.
    Oishi T, Uezumi A, Kanaji A, Yamamoto N, Yamaguchi A, Yamada H, Tsuchida K. Osteogenic differentiation capacity of human skeletal muscle-derived progenitor cells. PLoS One 2013; 8(2): e56641CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Kato S, Chmielewski M, Honda H, Pecoits-Filho R, Matsuo S, Yuzawa Y, Tranaeus A, Stenvinkel P, Lindholm B. Aspects of immune dysfunction in end-stage renal disease. Clin J Am Soc Nephrol 2008; 3(5): 1526–1533CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Kyung Im Kim
    • 1
  • Sohyun Jeong
    • 2
  • Nayoung Han
    • 2
  • Jung Mi Oh
    • 2
  • Kook-Hwan Oh
    • 3
  • In-Wha Kim
    • 2
    Email author
  1. 1.College of PharmacyKorea UniversitySejongRepublic of Korea
  2. 2.College of Pharmacy and Research Institute of Pharmaceutical SciencesSeoul National UniversitySeoulRepublic of Korea
  3. 3.Division of Nephrology, Department of Internal MedicineSeoul National University HospitalSeoulRepublic of Korea

Personalised recommendations