Skip to main content
SpringerLink
Log in

miR-10b and miR-223-3p in serum microvesicles signal progression from prediabetes to type 2 diabetes

  • Original Article
  • Published:
Journal of Endocrinological Investigation Aims and scope Submit manuscript

Abstract

Purpose

Type 2 diabetes frequently remains undiagnosed for years, whereas early detection of affected individuals would facilitate the implementation of timely and cost-effective therapies, hence decreasing morbidity. With the intention of identifying novel diagnostic biomarkers, we characterized the miRNA profile of microvesicles isolated from retroactive serum samples of normoglycemic individuals and two groups of subjects with prediabetes that in the following 4 years either progressed to overt diabetes or remained stable.

Methods

We profiled miRNAs in serum microvesicles of a selected group of control and prediabetic individuals participating in the PREDAPS cohort study. Half of the subjects with prediabetes were diagnosed with diabetes during the 4 years of follow-up, while the glycemic status of the other half remained unchanged.

Results

We identified two miRNAs, miR-10b and miR-223-3p, which target components of the insulin signaling pathway and whose ratio discriminates between these two subgroups of prediabetic individuals at a stage at which other features, including glycemia, are less proficient at separating them. In global, the profile of miRNAs in microvesicles of prediabetic subjects primed to progress to overt diabetes was more similar to that of diabetic patients than the profile of prediabetic subjects who did not progress.

Conclusion

We have identified a miRNA signature in serum microvesicles that can be used as a new screening biomarker to identify subjects with prediabetes at high risk of developing diabetes, hence allowing the implementation of earlier, and probably more effective, therapeutic interventions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Cho NH, Shaw JE, Karuranga S et al (2018) IDF diabetes atlas. Diabetes Res Clin Pract 138:271–281. https://doi.org/10.1016/j.diabres.2018.02.023

    Article  CAS  PubMed  Google Scholar 

  2. Soriguer F, Goday A, Bosch-Comas A et al (2012) Prevalence of diabetes mellitus and impaired glucose regulation in Spain: Di@bet.es study. Diabetologia 55:88–93. https://doi.org/10.1007/s00125-011-2336-9

    Article  CAS  PubMed  Google Scholar 

  3. Mata-Cases M, Casajuana M, Franch-Nadal J et al (2016) Direct medical costs attributable to type 2 diabetes: a population-based study in Catalonia, Spain. Eur J Health Econ 17:1001–1010. https://doi.org/10.1007/s10198-015-0742-5

    Article  PubMed  Google Scholar 

  4. Müller G (2012) Microvesicles/exosomes as potential novel biomarkers of metabolic diseases. Diabetes Metab Syndr Obes Targets Ther 5:247–282. https://doi.org/10.2147/DMSO.S32923

    Article  CAS  Google Scholar 

  5. Pirola L, Balcerczyk A, Okabe J, El-Osta A (2010) Epigenetic phenomena linked to diabetic complications. Nat Rev Endocrinol 6:665–675. https://doi.org/10.1038/nrendo.2010.188

    Article  CAS  PubMed  Google Scholar 

  6. Párrizas M, Novials A (2016) Circulating microRNAs as biomarkers for metabolic disease. Best Pract Res Clin Endocrinol Metab 30:591–601. https://doi.org/10.1016/j.beem.2016.08.001

    Article  CAS  PubMed  Google Scholar 

  7. Bartel DP (2018) Metazoan microRNAs. Cell 173:20–51

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Castaño C, Novials A, Párrizas M (2019) Exosomes and diabetes. Diabetes Metab Res Rev 2019:e3107. https://doi.org/10.1002/dmrr.3107

    Article  Google Scholar 

  9. Párrizas M, Brugnara L, Esteban Y et al (2015) Circulating miR-192 and miR-193b are markers of prediabetes and are modulated by an exercise intervention. J Clin Endocrinol Metab 100:E407–E415. https://doi.org/10.1210/jc.2014-2574

    Article  CAS  PubMed  Google Scholar 

  10. Thomou T, Mori MA, Dreyfuss JM et al (2017) Adipose-derived circulating miRNAs regulate gene expression in other tissues. Nature 542:450–455. https://doi.org/10.1038/nature21365

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Ying W, Riopel M, Bandyopadhyay G et al (2017) Adipose tissue macrophage-derived exosomal miRNAs can modulate in vivo and in vitro insulin sensitivity. Cell 171:372–384. https://doi.org/10.1016/j.cell.2017.08.035

    Article  CAS  PubMed  Google Scholar 

  12. Castaño C, Kalko S, Novials A, Párrizas M (2018) Obesity-associated exosomal miRNAs modulate glucose and lipid metabolism in mice. Proc Natl Acad Sci 115:12158–12163. https://doi.org/10.1073/pnas.1808855115

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Diaz-Redondo A, Giraldez-Garcia C, Carrillo L et al (2015) Modifiable risk factors associated with prediabetes in men and women: cross-sectional analysis of the cohort study in primary health care on the evolution of patients with prediabetes (PREDAPS). BMC Fam Pract 16:5. https://doi.org/10.1186/s12875-014-0216-3

    Article  PubMed  PubMed Central  Google Scholar 

  14. Franch-Nadal J, Caballeria L, Mata-Cases M et al (2018) Fatty liver index is a predictor of incident diabetes in patients with prediabetes: PREDAPS study. PLoS One 13:1–17. https://doi.org/10.1371/journal.pone.0198327

    Article  CAS  Google Scholar 

  15. Giráldez-García C, Franch-Nadal J, Sangrós FJ et al (2018) Adiposity and diabetes risk in adults with prediabetes: heterogeneity of findings depending on age and anthropometric measure. Obesity 26:1481–1490. https://doi.org/10.1002/oby.22256

    Article  CAS  PubMed  Google Scholar 

  16. Bedogni G, Bellentani S, Miglioli L et al (2006) The fatty liver index: a simple and accurate predictor of hepatic steatosis in the general population. BMC Gastroenterol 6:33. https://doi.org/10.1186/1471-230x-6-33

    Article  PubMed  PubMed Central  Google Scholar 

  17. Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(-delta delta C(T)) method. Methods 25:402–408. https://doi.org/10.1006/meth.2001.1262

    Article  CAS  PubMed  Google Scholar 

  18. Tirosh A, Shai I, Tekes-Manova D et al (2005) Normal fasting plasma glucose levels and type 2 diabetes in young men. N Engl J Med 353:1454–1462. https://doi.org/10.1056/NEJMoa050080

    Article  CAS  PubMed  Google Scholar 

  19. Wang K, Yuan Y, Cho JH et al (2012) Comparing the microRNA spectrum between serum and plasma. PLoS One 7:e41561. https://doi.org/10.1371/journal.pone.0041561

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Gong Q, Gregg EW, Wang J et al (2011) Long-term effects of a randomised trial of a 6-year lifestyle intervention in impaired glucose tolerance on diabetes-related microvascular complications: China Da Qing Diabetes Prevention Outcome Study. Diabetologia 54:300–307. https://doi.org/10.1007/s00125-010-1948-9

    Article  CAS  PubMed  Google Scholar 

  21. Lindstrom J, Peltonen M, Eriksson JG et al (2013) Improved lifestyle and decreased diabetes risk over 13 years: long-term follow-up of the randomised Finnish Diabetes Prevention Study. Diabetologia 56:284–293. https://doi.org/10.1007/s00125-012-2752-5

    Article  CAS  PubMed  Google Scholar 

  22. He Y, Ding Y, Liang B et al (2017) A systematic study of dysregulated microRNA in type 2 diabetes. Int J Mol Sci 18:456. https://doi.org/10.3390/ijms18030456

    Article  CAS  PubMed Central  Google Scholar 

  23. Liang YZ, Li JJH, Xiao HB et al (2018) Identification of stress-related microRNA biomarkers in type 2 diabetes: a systematic review and meta-analysis. J Diabetes. https://doi.org/10.1111/1753-0407.12643

    Article  PubMed  Google Scholar 

  24. Lund AH (2010) miR-10 in development and cancer. Cell Death Differ 17:209–214. https://doi.org/10.1038/cdd.2009.58

    Article  CAS  PubMed  Google Scholar 

  25. Zhao X, Chen Z, Zhou Z et al (2019) High-throughput sequencing of small RNAs and analysis of differentially expressed microRNAs associated with high-fat diet-induced hepatic insulin resistance in mice. Genes Nutr 14:6. https://doi.org/10.1186/s12263-019-0630-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Herrera BM, Lockstone HE, Taylor JM et al (2010) Global miRNA expression profiles in insulin target tissues in a spontaneous rat model of type 2 diabetes. Diabetologia 53:1099–1109. https://doi.org/10.1007/s00125-010-1667-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Wen D, Qiao P, Wang L (2015) Circulating miR-223 as a potential biomarker for obesity. Obes Res Clin Pract 9:398–404. https://doi.org/10.1016/j.orcp.2015.01.006

    Article  PubMed  Google Scholar 

  28. Ye D, Zhang T, Lou G, Liu Y (2018) Role of miR-223 in the pathophysiology of liver diseases. Exp Mol Med 50:128. https://doi.org/10.1038/s12276-018-0153-7

    Article  CAS  PubMed Central  Google Scholar 

  29. Aziz F (2016) The emerging role of miR-223 as novel potential diagnostic and therapeutic target for inflammatory disorders. Cell Immunol 303:1–6. https://doi.org/10.1016/j.cellimm.2016.04.003

    Article  CAS  PubMed  Google Scholar 

  30. Hay N (2011) Akt isoforms and glucose homeostasis. Trends Endocrinol Metab 22:66–73. https://doi.org/10.1016/j.tem.2010.09.003

    Article  CAS  PubMed  Google Scholar 

  31. Fabre A, Marchal S, Barlogis V et al (2019) Clinical aspects of STAT3 gain-of-function germline mutations. J Allergy Clin Immunol Pract 7:1958–1969. https://doi.org/10.1016/j.jaip.2019.02.018

    Article  PubMed  Google Scholar 

  32. Kung C-P, Murphy ME (2016) The role of the p53 tumor suppressor in metabolism and diabetes. J Endocrinol 231:R61–R75. https://doi.org/10.1530/JOE-16-0324

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Moldovan L, Batte KE, Trgovcich J et al (2014) Methodological challenges in utilizing miRNAs as circulating biomarkers. J Cell Mol Med 18:371–390. https://doi.org/10.1111/jcmm.12236

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Venturella M, Carpi FM, Zocco D (2019) Standardization of blood collection and processing for the diagnostic use of extracellular vesicles. Curr Pathobiol Rep. https://doi.org/10.1007/s40139-019-00189-3

    Article  Google Scholar 

  35. Blondal T, Jensby Nielsen S, Baker A et al (2013) Assessing sample and miRNA profile quality in serum and plasma or other biofluids. Methods 59:164–169. https://doi.org/10.1016/j.ymeth.2012.09.015

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We are indebted to the IDIBAPS Biobank, integrated in the Spanish National Biobank Network, for the sample and data procurement. We are grateful to Yaiza Esteban and Lucía-Isabel Alvarado for technical support. We acknowledge the PREDAPS Study investigators: Gabriel Cuatrecasas (EAP Sarria SL), Eduard Tarragó (EAP Bellvitge), M. Isabel Bobé (EAP La Mina), Flora Lopez (EAP Martorell), Martí Birules (EAP Poble Nou), Rosamar DeMiguel (EAP Pubilla Casas), Laura Romera (EAP Raval Nord), Ana Martinez-Sanchez (EAP El Carmel), Belén Benito, Beatriz Bilbeny and Neus Piulachs (EAP Raval Sud).

Funding

This work was supported by grants EFSD/Lilly and an unrestricted grant from Novartis awarded to AN. It also received support from CIBERDEM.

Author information

Author notes

  1. M. Parrizas and X. Mundet contributed equally to this work.

Authors and Affiliations

  1. Spanish Biomedical Research Center in Diabetes and Associated Metabolic Disorders (CIBERDEM), Barcelona, Spain

    M. Parrizas, C. Castaño, L. Brugnara, M. Mata-Cases, J. Franch-Nadal & A. Novials

  2. Pathogenesis and Prevention of Diabetes Laboratory, August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Rosselló 149-153, 08036, Barcelona, Spain

    M. Parrizas, C. Castaño, L. Brugnara & A. Novials

  3. redGDPS Foundation, Madrid, Spain

    X. Mundet, C. Giráldez-García, E. Regidor, M. Mata-Cases & J. Franch-Nadal

  4. DAP-Cat Group, Research Support Unit, University Institute for Research in Primary Care Jordi Gol (IDIAPJGol), Gran Via de les Corts Catalanes, 587, 08007, Barcelona, Spain

    X. Mundet, S. Canivell, X. Cos, M. Mata-Cases & J. Franch-Nadal

  5. Autonomous University of Barcelona, Barcelona, Spain

    X. Mundet

  6. Primary Health Care Center Sant Martí de Provençals, Catalan Health Institute, Barcelona, Spain

    S. Canivell & X. Cos

  7. Department of Internal Medicine, Health Sciences Research Institute and University Hospital Germans Trias i Pujol, Badalona, Barcelona, Spain

    S. Canivell

  8. Preventive Medicine Service, University Hospital Infanta Elena, Madrid, Spain

    C. Giráldez-García

  9. Preventive Medicine, Public Health and History of Science Department, Complutense University of Madrid, Madrid, Spain

    C. Giráldez-García & E. Regidor

  10. Epidemiology and Public Health Networking Biomedical Research Centre (CIBERESP), Madrid, Spain

    E. Regidor

  11. Health Research Institute, Hospital Clínico San Carlos (IdISSC), Madrid, Spain

    E. Regidor

  12. Primary Health Care Center La Mina, Catalan Health Institute, Sant Adrià De Besòs, Barcelona, Spain

    M. Mata-Cases

  13. Department of Medicine, University of Barcelona, Barcelona, Spain

    J. Franch-Nadal

Authors
  1. M. Parrizas
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. X. Mundet
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. C. Castaño
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. S. Canivell
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. X. Cos
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. L. Brugnara
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. C. Giráldez-García
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. E. Regidor
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. M. Mata-Cases
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. J. Franch-Nadal
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. A. Novials
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

MP and AN designed the study; XM, XC, SC, LB, CGG, ER, MMC and JFN performed data collection and clinical analysis; CC and MP performed exosome isolation and RNA analysis; SC, MP and CC performed statistical analyses; MP wrote the first draft of the manuscript; all authors provided critical revisions of the manuscript.

Corresponding authors

Correspondence to J. Franch-Nadal or A. Novials.

Ethics declarations

Conflict of interest

No potential conflicts of interest relevant to this article were disclosed.

Ethical approval

The study was approved by the Ethical Committees of Parc de Salut Mar Clinical of Barcelona (Register 2011/4274/I) and the Hospital Clinic, University of Barcelona (Register 2011/6945).

Informed consent

Written informed consent was obtained from all the participants included in this study, in accordance with the principles of the Declaration of Helsinki.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Parrizas, M., Mundet, X., Castaño, C. et al. miR-10b and miR-223-3p in serum microvesicles signal progression from prediabetes to type 2 diabetes. J Endocrinol Invest 43, 451–459 (2020). https://doi.org/10.1007/s40618-019-01129-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40618-019-01129-z

Keywords

Search

Navigation