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Endocrine

, Volume 66, Issue 2, pp 226–239 | Cite as

Decreased expression of microRNAs targeting type-2 diabetes susceptibility genes in peripheral blood of patients and predisposed individuals

  • Ioanna KokkinopoulouEmail author
  • Eirini Maratou
  • Panayota Mitrou
  • Eleni Boutati
  • Diamantis C. Sideris
  • Emmanuel G. Fragoulis
  • Maria-Ioanna ChristodoulouEmail author
Original Article
  • 103 Downloads

Abstract

Aim

Certain microRNA molecules (miRNAs) that target genes involved in beta-cell growth and insulin resistance are found deregulated in patients with type-2 diabetes mellitus (T2D) and correlate with its complications. However, the expression profile of miRNAs that regulate genes bearing T2D-related single-nucleotide polymorphisms has been hardly studied. We recently reported that the mRNA patterns of specific T2D-susceptibility genes are impaired in patients, and associate with disease parameters and risk factors. The aim of this study was to explore the levels of miRNAs that target those genes, in peripheral blood of patients versus controls.

Methods

A panel of 14 miRNAs validated to target the CDKN2A, CDK5, IGF2BP2, KCNQ1, and TSPAN8 genes, was developed upon combined search throughout the DIANNA TarBase v7.0, miRTarBase, miRSearch v3.0-Exiqon, miRGator v3.0, and miRTarget Link Human algorithms. Specifically developed poly(A)polyadenylation(PAP)-reverse transcription(RT)-qPCR protocols were applied in peripheral blood RNA samples from patients and controls. Possible correlations with the disease, clinicopathological parameters and/or risk factors were evaluated.

Results

T2D patients expressed decreased levels of let-7b-5p, miR-1-3p, miR-24-3p, miR-34a-5p, miR-98-5p, and miR-133a-3p, compared with controls. Moreover, these levels correlated with certain disease features including insulin and % HbA1c levels in patients, as well as BMI, triglycerides’ levels and family history in controls.

Conclusions

A T2D-specific expression profile of miRNAs that target disease-susceptibility genes is for the first time described. Future studies are needed to elucidate the associated transcription-regulatory mechanisms, perchance involved in T2D pathogenesis, and to evaluate the potential of these molecules as possible biomarkers for this disorder.

Highlights

  • Let-7b-5p, miR-1-3p, miR-24-3p, miR-34a-5p, miR-98-5p, and miR-133a-3p, which target certain T2D-susceptibility genes, are decreased in peripheral blood samples of patients compared with controls.

  • The expression levels of let-7b-5p, miR-1-3p, miR-24-3p, miR-34a-5p, miR-98-5p, and miR-133a-3p correlate with the mRNA levels of their target T2D-susceptibility genes.

  • The levels of these miRNAs correlate with certain disease parameters, including insulin, % HbA1c levels, BMI, triglycerides’ levels, and family history.

Keywords

MicroRNA (miRNA) Type-2 diabetes mellitus (T2D) T2D-susceptibility genes Peripheral blood PAP-RT-qPCR 

Notes

Acknowledgements

This research was co-financed by Greece and the European Union (European Social Fund - ESF) through the Operational Program “Human Resources Development, Education and Lifelong Learning” in the context of the project “Scholarships program for post-graduate studies-2nd study Cycle” (MIS-5003404), implemented by the State Scholarships Foundation (IKY).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

12020_2019_2062_MOESM1_ESM.pdf (76 kb)
Supplementary Table 1
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Supplementary Table 2
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Supplementary Table 3
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Supplementary Table 4
12020_2019_2062_MOESM5_ESM.pdf (144 kb)
Supplementary Table 5

References

  1. 1.
    International Diabetes Federation, IDF Diabetes Atlas. 7th edn. (International Diabetes Federation, Brussels, Belgium, 2015)Google Scholar
  2. 2.
    D.M. Nathan, Diabetes: advances in diagnosis and treatment. JAMA 314, 1052–1062 (2015)CrossRefGoogle Scholar
  3. 3.
    A. Desiderio, R. Spinelli, M. Ciccarelli, C. Nigro, C. Miele, F. Beguinot et al. Epigenetics: spotlight on type 2 diabetes and obesity. J. Endocrinol. Investig. 39, 1095–1103 (2016)CrossRefGoogle Scholar
  4. 4.
    A.P. Morris, B.F. Voight, T.M. Teslovich, T. Ferreira, A.V. Segre, V. Steinthorsdottir et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat. Genet. 44, 981–990 (2012)CrossRefGoogle Scholar
  5. 5.
    J. MacArthur, E. Bowler, M. Cerezo, L. Gil, P. Hall, E. Hastings et al. The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog). Nucleic Acids Res. 45, D896–D901 (2017)CrossRefGoogle Scholar
  6. 6.
    M.I. Christodoulou, M. Avgeris, I. Kokkinopoulou, E. Maratou, P. Mitrou, C.K. Kontos et al. Blood-based analysis of type-2 diabetes mellitus susceptibility genes identifies specific transcript variants with deregulated expression and association with disease risk. Sci. Rep. 9, 1512 (2019)CrossRefGoogle Scholar
  7. 7.
    S.L. Fernandez-Valverde, R.J. Taft, J.S. Mattick, MicroRNAs in beta-cell biology, insulin resistance, diabetes and its complications. Diabetes 60, 1825–1831 (2011)CrossRefGoogle Scholar
  8. 8.
    J. Feng, W. Xing, L. Xie, Regulatory roles of MicroRNAs in diabetes. Int J Mol Sci. 17, 1729 (2016)CrossRefGoogle Scholar
  9. 9.
    H. Chen, H.Y. Lan, D.H. Roukos, W.C. Cho, Application of microRNAs in diabetes mellitus. J. Endocrinol. 222, R1–R10 (2014)CrossRefGoogle Scholar
  10. 10.
    Y. He, Y. Ding, B. Liang, J. Lin, T. K. Kim, H. Yu, et al. A systematic study of dysregulated MicroRNA in type 2 diabetes mellitus. Int J Mol Sci. 18, 456 (2017).CrossRefGoogle Scholar
  11. 11.
    C. Guay, R. Regazzi, Circulating microRNAs as novel biomarkers for diabetes mellitus. Nat. Rev. Endocrinol. 9, 513–521 (2013)CrossRefGoogle Scholar
  12. 12.
    A.D. McClelland, P. Kantharidis, MicroRNA in the development of diabetic complications. Clin. Sci. (Lond.) 126, 95–110 (2014)CrossRefGoogle Scholar
  13. 13.
    M. van de Bunt, K.J. Gaulton, L. Parts, I. Moran, P.R. Johnson, C.M. Lindgren et al. The miRNA profile of human pancreatic islets and beta-cells and relationship to type 2 diabetes pathogenesis. PLoS ONE 8, e55272 (2013)CrossRefGoogle Scholar
  14. 14.
    I.S. Vlachos, M.D. Paraskevopoulou, D. Karagkouni, G. Georgakilas, T. Vergoulis, I. Kanellos et al. DIANA-TarBasev7.0: indexing more than half a million experimentally supported miRNA:mRNA interactions. Nucleic Acids Res. 43, D153–D159 (2015)CrossRefGoogle Scholar
  15. 15.
    C.H. Chou, S. Shrestha, C.D. Yang, N.W. Chang, Y.L. Lin, K.W. Liao et al. MiRTarBase update 2018: a resource for experimentally validated microRNA-target interactions. Nucleic Acids Res. 46, D296–D302 (2018)CrossRefGoogle Scholar
  16. 16.
    S. Cho, I. Jang, Y. Jun, S. Yoon, M. Ko, Y. Kwon et al. MiRGatorv3.0: a microRNA portal for deep sequencing, expression profiling and mRNA targeting. Nucleic Acids Res. 41, D252–D257 (2013)CrossRefGoogle Scholar
  17. 17.
    M. Hamberg, C. Backes, T. Fehlmann, M. Hart, B. Meder, E. Meese et al. MiRTargetLink-miRNAs, genes and interaction networks. Int J. Mol. Sci. 17, 564 (2016)CrossRefGoogle Scholar
  18. 18.
    K.J. Livak, T.D. Schmittgen, Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods 25, 402–408 (2001)CrossRefGoogle Scholar
  19. 19.
    M. Kanehisa, S. Goto, KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 27–30 (2000)CrossRefGoogle Scholar
  20. 20.
    D. Szklarczyk, A. Franceschini, S. Wyder, K. Forslund, D. Heller, J. Huerta-Cepas et al. STRINGv10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 43, D447–D452 (2015)CrossRefGoogle Scholar
  21. 21.
    Y. Xiang, J. Cheng, D. Wang, X. Hu, Y. Xie, J. Stitham et al. Hyperglycemia repression of miR-24 coordinately upregulates endothelial cell expression and secretion of von Willebrand factor. Blood 125, 3377–3387 (2015)CrossRefGoogle Scholar
  22. 22.
    A. Zampetaki, S. Kiechl, I. Drozdov, P. Willeit, U. Mayr, M. Prokopi et al. Plasma microRNA profiling reveals loss of endothelial miR-126 and other microRNAs in type 2 diabetes. Circ. Res. 107, 810–817 (2010)CrossRefGoogle Scholar
  23. 23.
    F.J. Ortega, J.M. Mercader, J.M. Moreno-Navarrete, O. Rovira, E. Guerra, E. Esteve et al. Profiling of circulating microRNAs reveals common microRNAs linked to type 2 diabetes that change with insulin sensitization. Diabetes Care 37, 1375–1383 (2014)CrossRefGoogle Scholar
  24. 24.
    I.J. Gallagher, C. Scheele, P. Keller, A.R. Nielsen, J. Remenyi, C.P. Fischer et al. Integration of microRNA changes in vivo identifies novel molecular features of muscle insulin resistance in type 2 diabetes. Genome Med. 2, 9 (2010)CrossRefGoogle Scholar
  25. 25.
    D. Santovito, V. De Nardis, P. Marcantonio, C. Mandolini, C. Paganelli, E. Vitale et al. Plasma exosome microRNA profiling unravels a new potential modulator of adiponectin pathway in diabetes: effect of glycemic control. J. Clin. Endocrinol. Metabol. 99, E1681–E1685 (2014)CrossRefGoogle Scholar
  26. 26.
    Z. Yang, H. Chen, H. Si, X. Li, X. Ding, Q. Sheng et al. Serum miR-23a, a potential biomarker for diagnosis of pre-diabetes and type 2 diabetes. Acta Diabetol. 51, 823–831 (2014)CrossRefGoogle Scholar
  27. 27.
    Z. Yang, J. Wu, MicroRNAs and regenerative medicine. DNA Cell Biol. 26, 257–264 (2007)CrossRefGoogle Scholar
  28. 28.
    Y. Kong, R.B. Sharma, B.U. Nwosu, L.C. Alonso, Islet biology, the CDKN2A/B locus and type 2 diabetes risk. Diabetologia 59, 1579–1593 (2016)CrossRefGoogle Scholar
  29. 29.
    N. Popov, J. Gil, Epigenetic regulation of the INK4b-ARF-INK4a locus: in sickness and in health. Epigenetics 5, 685–690 (2010)CrossRefGoogle Scholar
  30. 30.
    Y. Xiang, MiR-24 in diabetes. Oncotarget 6, 16816–16817 (2015)PubMedPubMedCentralGoogle Scholar
  31. 31.
    J.F. Chen, E.M. Mandel, J.M. Thomson, Q. Wu, T.E. Callis, S.M. Hammond et al. The role of microRNA-1 and microRNA-133 in skeletal muscle proliferation and differentiation. Nat. Genet. 38, 228–233 (2006)CrossRefGoogle Scholar
  32. 32.
    C. Xu, Y. Lu, Z. Pan, W. Chu, X. Luo, H. Lin et al. The muscle-specific microRNAs miR-1 and miR-133 produce opposing effects on apoptosis by targeting HSP60, HSP70 and caspase-9 in cardiomyocytes. J. Cell Sci. 120, 3045–3052 (2007)CrossRefGoogle Scholar
  33. 33.
    S. Fichtlscherer, A.M. Zeiher, S. Dimmeler, Circulating microRNAs: biomarkers or mediators of cardiovascular diseases? Arterioscler Thromb. Vasc. Biol. 31, 2383–2390 (2011)CrossRefGoogle Scholar
  34. 34.
    R.S. Gangwar, S. Rajagopalan, R. Natarajan, J.A. Deiuliis, Noncoding RNAs in cardiovascular disease: pathological relevance and emerging role as biomarkers and therapeutics. Am. J. Hypertens. 31, 150–165 (2018)CrossRefGoogle Scholar
  35. 35.
    X. Liu, S. Liu, Role of microRNAs in the pathogenesis of diabetic cardiomyopathy. Biomed. Rep. 6, 140–145 (2017)CrossRefGoogle Scholar
  36. 36.
    V. Lyssenko, M. Laakso, Genetic screening for the risk of type 2 diabetes: worthless or valuable? Diabetes Care 36(Suppl 2), S120–S126 (2013)CrossRefGoogle Scholar
  37. 37.
    K.K. Collins, The diabetes-cancer link. Diabetes Spectr. 27, 276–280 (2014)CrossRefGoogle Scholar
  38. 38.
    A.Y. Cheng, L.A. Leiter, Implications of recent clinical trials for the National Cholesterol Education Program Adult Treatment Panel III guidelines. Curr. Opin. Cardiol. 21, 400–404 (2006)PubMedGoogle Scholar
  39. 39.
    Expert Panel on Detection E, Treatment of high blood cholesterol in a: executive summary of the third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). JAMA 285, 2486–2497 (2001)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Biochemistry and Molecular Biology, Faculty of BiologyNational and Kapodistrian University of AthensAthensGreece
  2. 2.Second Department of Internal Medicine and Research Institute, School of MedicineNational and Kapodistrian University of Athens, “Attikon” University HospitalAthensGreece
  3. 3.Ministry of HealthAthensGreece
  4. 4.Institute of Infection, Immunity and InflammationUniversity of GlasgowGlasgowUK

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