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Platelet-derived miR-103b as a novel biomarker for the early diagnosis of type 2 diabetes

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Abstract

Aims

MicroRNA-103 (miR-103) plays a critical role in regulating glucose homeostasis in type 2 diabetes (DM2). Recent data suggest that secreted frizzled-related protein 4 (SFRP4) serves as a potential risk biomarker for prediabetic mellitus (pre-DM) and that platelets are enriched for miR-103. The objective of this study was to test the hypothesis that platelet-derived miR-103b (miR-103-as), which regulates SFRP4, might be a novel biomarker for the early diagnosis of DM2.

Methods

We evaluated platelet miR-103b expression in healthy subjects (n = 46), pre-DM subjects (n = 48), non-complicated diabetic subjects (n = 43) and diabetes mellitus type 2–coronary heart disease subjects (n = 36), respectively, and analyzed the relationship of these levels with its target gene SFRP4.

Results

In qRT-PCR assays, miR-103b were significantly down-regulated, and conversely, the expression of the SFRP4 gene was up-regulated in pooled leukocyte-depleted platelets and individual subjects with pre-DM. Additionally, patients who had undergone antiplatelet treatment were characterized by decreased gene expression of SFRP4 and increased levels of platelet-derived miR-103b. miR-103b modulated reporter gene expression through SFRP4 mRNA 3′-UTR seed sequence and negatively regulated its expression. Furthermore, SFRP4 mRNA and protein levels were down-regulated by a miR-103b mimic but were up-regulated by a miR-103b inhibitor.

Conclusions

The results suggest that platelet-derived miR-103b could negatively regulate the expression of SFRP4 mRNA/protein in pre-DM2, indicating that miR-103b could be a novel biomarker for the early diagnosis of DM2.

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References

  1. Liddy CE, Cullen-Arseneau P, Merizzi S, Blazhko V (2013) An ounce of prevention: a primary care based prevention program for pre-diabetic population. Can J Diabetes 37:12–17

    Article  PubMed  Google Scholar 

  2. Nazaribadie M, Asgari K, Amini M, Ahmadpanah M, Nazaribadie M, Jamlipaghale S (2013) Cognitive processes and functions in patients with type 2 diabetes in comparison to pre-diabetic patients. J Res Health Sci 13:208–213

    PubMed  Google Scholar 

  3. Mahdi T, Hanzelmann S, Salehi A, Muhammed SJ, Reinbothe TM, Tang Y, Axelsson AS, Zhou Y, Jing X, Almgren P, Krus U, Taneera J, Blom AM, Lyssenko V, Esguerra JL, Hansson O, Eliasson L, Derry J, Zhang E, Wollheim CB, Groop L, Renström E, Rosengren AH (2012) Secreted frizzled-related protein 4 reduces insulin secretion and is overexpressed in type 2 diabetes. Cell Metab 16:625–633

    Article  CAS  PubMed  Google Scholar 

  4. Yang Z, Chen H, Si H, Li X, Ding X, Sheng Q, Chen P, Zhang H (2014) Serum miR-23a, a potential biomarker for diagnosis of pre-diabetes and type 2 diabetes. Acta Diabetol 51:823–831

    Article  CAS  PubMed  Google Scholar 

  5. Ha TY (2011) MicroRNAs in Human Diseases: from cancer to cardiovascular disease. Immune Netw 11:135–154

    Article  PubMed Central  PubMed  Google Scholar 

  6. Creemers EE, Tijsen AJ, Pinto YM (2012) Circulating microRNAs: novel biomarkers and extracellular communicators in cardiovascular disease? Circ Res 110:483–495

    Article  CAS  PubMed  Google Scholar 

  7. Bronze-da-Rocha E (2014) MicroRNAs expression profiles in cardiovascular diseases. Biomed Res Int 2014:985408

    Article  PubMed Central  PubMed  Google Scholar 

  8. Landry P, Plante I, Ouellet DL, Perron MP, Rousseau G, Provost P (2009) Existence of a microRNA pathway in anucleate platelets. Nat Struct Mol Biol 16:961–966

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  9. Edelstein LC, Bray PF (2011) MicroRNAs in platelet production and activation. Blood 117:5289–5296

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  10. Ple H, Landry P, Benham A, Coarfa C, Gunaratne PH, Provost P (2012) The repertoire and features of human platelet microRNAs. PLoS One 7:e50746

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  11. Willeit P, Zampetaki A, Dudek K, Kaudewitz D, King A, Kirkby NS, Crosby-Nwaobi R, Prokopi M, Drozdov I, Langley SR, Sivaprasad S, Markus HS, Mitchell JA, Warner TD, Kiechl S, Mayr M (2013) Circulating microRNAs as novel biomarkers for platelet activation. Circ Res 112:595–600

    Article  CAS  PubMed  Google Scholar 

  12. Trajkovski M, Hausser J, Soutschek J, Bhat B, Akin A, Zavolan M, Heim MH, Stoffel M (2011) MicroRNAs 103 and 107 regulate insulin sensitivity. Nature 474:649–653

    Article  CAS  PubMed  Google Scholar 

  13. Lewis BP, Burge CB, Bartel DP (2005) Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120:15–20

    Article  CAS  PubMed  Google Scholar 

  14. John B, Enright AJ, Aravin A, Tuschl T, Sander C, Marks DS (2004) Human MicroRNA targets. PLoS Biol 2:e363

    Article  PubMed Central  PubMed  Google Scholar 

  15. Wang X (2008) miRDB: a microRNA target prediction and functional annotation database with a wiki interface. RNA 14:1012–1017

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  16. Dweep H, Sticht C, Pandey P, Gretz N (2011) miRWalk–database: prediction of possible miRNA binding sites by “walking” the genes of three genomes. J Biomed Inform 44:839–847

    Article  CAS  PubMed  Google Scholar 

  17. Nagalla S, Shaw C, Kong X, Kondkar AA, Edelstein LC, Ma L, Chen J, McKnight GS, López JA, Yang L, Jin Y, Bray MS, Leal SM, Dong JF, Bray PF (2011) Platelet microRNA-mRNA coexpression profiles correlate with platelet reactivity. Blood 117:5189–5197

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  18. 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

    Article  CAS  PubMed  Google Scholar 

  19. Markham NR, Zuker M (2008) UNAFold: software for nucleic acid folding and hybridization. Methods Mol Biol 453:3–31

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

This work was supported by the AHA National Scientist Development Grant (10SDG2570DG037), the National Natural Science Foundation of China (81172050), Foundation of the Sichuan Education of China (11ZB123), Foundation of the Health Department of Sichuan Province (120371), and Foundation of Luzhou Municipal Science and Technology Bureau (2013-S-47, 2013LZLY-K64).

Conflict of interest

All the authors including Mao Luo, Rong Li, Xin Deng, Meiping Ren, Ni Chen, Min Zeng, Kai Yan, Jiyi Xia, Fei Liu, Weizhong Ma, Yan Yang, Qin Wan, and Jianbo Wu declare that they have no conflict of interest.

Ethical approval

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Declaration of Helsinki 1975, as revised in 2008 (5).

Informed consent

Informed consent was obtained from all patients for being included in the study.

Author information

Authors and Affiliations

  1. Drug Discovery Reseach Center, Luzhou Medical College, Luzhou, Sichuan, China

    Mao Luo, Rong Li, Xin Deng, Meiping Ren, Ni Chen, Min Zeng, Kai Yan, Jiyi Xia, Weizhong Ma & Jianbo Wu

  2. Department of Endocrinology, The Affiliated Hospital of Luzhou Medical College, Luzhou, 646000, Sichuan, China

    Fei Liu & Qin Wan

  3. Division of Cardiovascular Medicine, Department of Internal Medicine, University of Missouri School of Medicine, 5 Hospital Drive, CE344–DC095.00, Columbia, MO, 65212, USA

    Yan Yang & Jianbo Wu

Authors
  1. Mao Luo
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  2. Rong Li
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  3. Xin Deng
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  4. Meiping Ren
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  5. Ni Chen
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  6. Min Zeng
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  7. Kai Yan
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  9. Fei Liu
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  10. Weizhong Ma
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  11. Yan Yang
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  12. Qin Wan
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  13. Jianbo Wu
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Corresponding authors

Correspondence to Qin Wan or Jianbo Wu.

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Luo, M., Li, R., Deng, X. et al. Platelet-derived miR-103b as a novel biomarker for the early diagnosis of type 2 diabetes. Acta Diabetol 52, 943–949 (2015). https://doi.org/10.1007/s00592-015-0733-0

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  • DOI: https://doi.org/10.1007/s00592-015-0733-0

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