Skip to main content
Log in

Profiling of Targeted miRNAs (8-nt) for the Genes Involved in Type 2 Diabetes Mellitus and Cardiac Hypertrophy

  • EVOLUTIONARY, POPULATION, AND MEDICAL GENOMICS, TRANSCRIPTOMICS
  • Published:
Molecular Biology Aims and scope Submit manuscript

Abstract

Type 2 Diabetes Mellitus (T2DM) and cardiac hypertrophy (CH) are among the top ten leading cause of deaths, worldwide. T2DM and cardiac hypertrophy are the chronic diseases, have close association and direct life-threatening complications like stroke, myocardial infarction, retinopathy, nephropathy, and limb amputation. In addition to other medical approaches, miRNAs-based strategy is considered most efficient for early detection of chronic diseases and also has potential for the treatment of T2DM and cardiac hypertrophy like it is being used for cancer in clinical trials. MicroRNAs (miRNAs) are single stranded (non-coding) of 20 to 22 nucleotides sequences which bind to their target mRNA upon the complimentary basis, to silence the protein expression at post transcriptional level. Bioinformatic databases are used like online mendelian inheritance in man (OMIM), gene testing registry (GTR), TargetScan and ShinyGO for validation of disease linked genes and sorting the common miRNAs in both diseases, such as miR-30-5p/101-3p.2/190-5p/506-3p/9-5p/128-3p/137/96-5p/7-5p/107/101-3p.1/98-5p/124-3p.2/124-3p.116-5p/15-5p/497-5p/ 424-5p/195-5p/1271-5p, let-7-5p. Aforementioned databases were also used for the miRNAs which have more than one disease linked genes target in each pathological condition. Such miRNAs for cardiac hypertrophy are: miR-19-3p/183-5p.2/153-3p/372-3p/302-3p/520-3p/373-3p/129-5p/144-3p/139-5p and for T2DM are: miR-27-3p/206/1-3p/181-5p. This finding would be helpful for the appropriate selection of miRNAs and to design applicable research project in future. It will require more validation by using the miRNAs expression analysis, mimic, and anti-miRNA approach to check their potential against cardiac hypertrophy and T2DM.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1.
Fig. 2.
Fig. 3.
Fig 4.
Fig. 5.
Fig. 6.
Fig. 7.

Similar content being viewed by others

REFERENCES

  1. WHO. 2019. https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death. Accessed December 22, 2020.

  2. Heron M. 2018. Leading causes for death. 2016. Natl. Vital. Stat. Rep. 67 (6), 1‒77.

    PubMed  Google Scholar 

  3. Ahmad F.B., Anderson R.N.J.J. 2021. The leading causes of death in the US for 2020. JAMA. 325 (18), 1829‒1830.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. American Diabetes Association. 2017. Standards of medical care in diabetes‒2017 abridged for primary care providers. Clin. Diabetes. 35 (1), 5‒26.

    Article  PubMed Central  Google Scholar 

  5. Olokoba A.B., Obateru O.A., Olokoba L.B. 2012. Type 2 diabetes mellitus: a review of current trends. Oman Med. J. 27 (4), 269‒273.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Nakamura M., Sadoshima J. 2018. Mechanisms of physiological and pathological cardiac hypertrophy. Nat. Rev. Cardiol. 15 (7), 387‒407.

    Article  CAS  PubMed  Google Scholar 

  7. Tham Y.K., Bernardo B.C., Ooi J.Y., Weeks K.L., McMullen J.R. 2015. Pathophysiology of cardiac hypertrophy and heart failure: signaling pathways and novel therapeutic targets. Arch. Toxicol. 89 (9), 1401‒1438.

    Article  CAS  PubMed  Google Scholar 

  8. Weeks K.L., McMullen J.R. 2011. The athlete’s heart vs. the failing heart: can signaling explain the two distinct outcomes. Physiol. J. 26 (2), 97‒105.

    Article  CAS  Google Scholar 

  9. Laakso M. 2001. Cardiovascular disease in type 2 diabetes: challenge for treatment and prevention. J. Intern. Med. 249 (3), 225‒235.

    Article  CAS  PubMed  Google Scholar 

  10. Bartel D.P. 2004. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 116 (2), 281‒297.

    Article  CAS  PubMed  Google Scholar 

  11. Ha T.Y. 2011. MicroRNAs in human diseases: from cancer to cardiovascular disease. Immune Netw.11 (3), 135‒154.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Wang J., Yang X. 2012.The function of miRNA in cardiac hypertrophy. Cell. Mol. Life Sci. 69 (21), 3561‒3570.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Smolarz B., Durczyński A., Romanowicz H., Szyłło K., Hogendorf P. 2022. miRNAs in cancer (review of literature). Int. J. Mol. Sci. 23 (5), 2805.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. He B., Cai Q., Zhang Y., Zhang P., Shi S., Xie H., Peng X., Yin W., Tao Y., Wang X. 2020. miRNA-based biomarkers, therapies, and resistance in cancer. Int. J. Biol. Sci. 16 (14), 2628.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Pérez-Cremades D., Chen J. Assa C., Feinberg M.W. 2022. MicroRNA-mediated control of myocardial infarction in diabetes. Trends Cardiovasc. Med. S1050–1738(22)00006-8

  16. Lavenniah A., Luu T.D., Li Y.P., Lim T.B., Jiang J., Ackers-Johnson M., Foo R.S. 2020. Engineered circular RNA sponges act as miRNA inhibitors to attenuate pressure overload-induced cardiac hypertrophy. Mol. Ther. 28 (6), 1506‒1517.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Zhou S.S., Jin J.P., Wang J.Q., Zhang Z.G., Freedman J.H., Zheng Y., Cai L. 2018. miRNAS in cardiovascular diseases: potential biomarkers, therapeutic targets and challenges. Acta Pharmacol. Sin. 39 (7), 1073‒1084.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Vasu S., Kumano K., Darden C.M., Rahman I., Lawrence M.C., Naziruddin B. 2019. MicroRNA signatures as future biomarkers for diagnosis of diabetes states. Cells. 8 (12), 1533.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Rubinstein W.S., Maglott D.R., Lee J.M., Kattman B.L., Malheiro A.J., Ovetsky M., Hem V., Gorelenkov V., Song G., Wallin C., Husain N. 2012. The NIH genetic testing registry: a new, centralized database of genetic tests to enable access to comprehensive information and improve transparency. Nucleic Acids Res. 41 (D1), D925‒D935.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Hamosh A., Scott A.F., Amberger J.S., Bocchini C.A., McKusick V.A. 2005. Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res. 33 (D1), D514‒D517.

    Article  CAS  PubMed  Google Scholar 

  21. Agarwal V., Bell G.W., Nam J.W., Bartel D.P. 2015. Predicting effective microRNA target sites in mammalian mRNAs. Elife. 4, e05005.

    Article  PubMed  PubMed Central  Google Scholar 

  22. 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 (5), 839‒847.

    CAS  PubMed  Google Scholar 

  23. Griffiths-Jones S., Grocock R.J., Van Dongen S., Bateman A., Enright A.J. 2006. miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res. 34 (D1), D140‒D144.

    Article  CAS  PubMed  Google Scholar 

  24. Ge S.X., Jung D., Yao R. 2020. ShinyGO: a graphical gene-set enrichment tool for animals and plants. J. Bioinform. 36 (8), 2628‒2629.

    CAS  Google Scholar 

  25. Zhang S. Cheng Z. Wang Y. Han T. 2021. The risks of miRNA therapeutics: in a drug target perspective. 15, 721.

  26. Chiefari E., Nevolo M.T., Arcidiacono B., Maurizio E., Nocera A., Iiritano S., Sgarra R., Possidente K., Palmieri C., Paonessa F., Brunetti G. 2012. HMGA1 is a novel downstream nuclear target of the insulin receptor signaling pathway. Sci. Rep. 2 (1), 1‒10.

    Article  Google Scholar 

  27. Hu Y., Li Q., Zhang L., Zhong L., Gu M., He B., Qu Q., Lao Y., Gu K., Zheng B., Yang H. 2021. Serum miR-195-5p exhibits clinical significance in the diagnosis of essential hypertension with type 2 diabetes mellitus by targeting DRD1. Clinics (Sao Paulo). 76, e2502. https://doi.org/10.6061/clinics/2021/e250228

    Article  PubMed  PubMed Central  Google Scholar 

  28. Højlund K. 2014. Metabolism and insulin signaling in common metabolic disorders and inherited insulin resistance. Dan Med J. 61 (7), B4890.

    PubMed  Google Scholar 

  29. Qian H.F., Li. Y., Wang L. 2017. Vaccinium bracteatum Thunb. Leaves’ polysaccharide alleviates hepatic gluconeogenesis via the downregulation of miR-137. Biomed. Pharmacother. 95, 1397-1403.

    Article  CAS  PubMed  Google Scholar 

  30. Wang D., Fang J., Lv J., Pan Z., Yin X., Cheng H., Guo X. 2019. Novel polymorphisms in PDLIM3 and PDLIM5 gene encoding Z-line proteins increase risk of idiopathic dilated cardiomyopathy. J. Cell. Mol. Med. 23 (10), 7054‒7062.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Elgebaly S.A., Christenson R.H., Kandil H., Ibrahim M., Rizk H., El-Khazragy N., Rashed L., Yacoub B., Eldeeb H., Ali M.M., Kreutzer D.L. 2021. Nourin-dependent miR-137 and miR-106b: novel biomarkers for early diagnosis of myocardial ischemia in coronary artery disease patients. Diagnostics (Basel). 11 (4), 703.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Einarson T.R., Acs A., Ludwig C., Panton U.H. 2018. Prevalence of cardiovascular disease in type 2 diabetes: a systematic literature review of scientific evidence from across the world in 2007–2017. Cardiovasc. Diabetol. 17 (1), 83.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Li J., Chattopadhyay K., Xu M., Chen Y., Hu F., Chu J., Li L. 2020. Prevalence and associated factors of vascular complications among inpatients with type 2 diabetes: a retrospective database study at a tertiary care department, Ningbo, China. PLoS One. 15 (6), e0235161.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

We acknowledge the university research fund (URF) of Quaid-i-Azam University, Islamabad, Higher Education Commission (HEC) Pakistan, and Pakistan Science Foundation (PSF) to support the current study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to I. Murtaza.

Ethics declarations

The authors declare that they have no conflicts of interest.

This article does not contain any research involving animals or humans as subjects of research.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hussain, K., Ishtiaq, A., Mushtaq, I. et al. Profiling of Targeted miRNAs (8-nt) for the Genes Involved in Type 2 Diabetes Mellitus and Cardiac Hypertrophy. Mol Biol 57, 338–345 (2023). https://doi.org/10.1134/S0026893323020085

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0026893323020085

Keywords:

Navigation