Circulating micro-RNAs as biomarkers of coronary artery disease: is it ready for primetime or still a work in progress?

Circulating micro-RNAs as biomarkers of coronary artery disease: is it ready for primetime or still a work in progress?

Surovi Hazarika, Brian H. Annex

Division of Cardiovascular Medicine, Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, USA

Correspondence to: Brian H. Annex, MD. Division of Cardiovascular Medicine, Robert M. Berne Cardiovascular Research Center, University of Virginia, PO Box 800158, Charlottesville, VA 22908, USA. Email:

Provenance: This is a Guest Editorial commissioned by Section Editor Zhijun Han, MD (Department of Laboratory Medicine, Wuxi Second Hospital, Nanjing Medical University, Wuxi, China).

Comment on: O Sullivan JF, Neylon A, McGorrian C, et al. miRNA-93-5p and other miRNAs as predictors of coronary artery disease and STEMI. Int J Cardiol 2016;224:310-6.

Submitted Nov 24, 2016. Accepted for publication Nov 30, 2016.

doi: 10.21037/atm.2017.01.05

MicroRNAs (miRs) are small non-coding RNAs that play a significant role in epigenetic regulation of gene expression (1,2). Several miRs have been established to play crucial roles in a spectrum of different cardiovascular diseases (3,4). Since the initial identification of detectable levels of circulating miRs in plasma (5-7), circulating miRs have become the spotlight of investigation as potential biomarkers for several diseases. Micro-RNAs in circulation have two important features of ideal biomarkers: they are remarkably stable and safe from degradation by RNases, and they are easily measured in the circulation using sensitive and specific quantitative PCR techniques. Thus, circulating miRs can be linked to specific disease processes or to specific tissue and/or cell types.

In a recent study in International Journal of Cardiology, O Sullivan et al. did microRNA profiling from plasma samples from a cohort of control subjects, patients with stable coronary artery disease (CAD) and patients presenting with ST-elevation myocardial infarction (STEMI). The authors used a set of selected 22 miRs based on miRs with known role in cardiovascular biology, and identified four miRs (miR15a-5p, miR16-5p, miR93-5p and miR146a-5p) that were differentially expressed between controls subjects versus patients with stable CAD. Out of these miRs, miR 146a-5p was significantly decreased in stable CAD vs. control, while the rest of the miRs were found to be elevated in stable CAD compared to controls. The authors also found one miR (miR499a-5p) that was significantly elevated in patients with STEMI compared to control subjects. To adjust for traditional risk factors, the authors used a stepwise logistic regression model using all Framingham Heart Study (FHS) risk factors, and miR-93-5p remained significantly different between controls vs. stable CAD groups. Similarly, using a stepwise logistic regression incorporation using all FHS risk factors, the authors found miR-499a-5p was significantly elevated in patients with STEMI compared to controls. Further analysis using ROC curves showed that all four miRs that differed between control vs. stable CAD groups were significant predictors of stable CAD (AUCs of 0.67, 0.65, 0.68), while the miR-93-5p was found to be a better predictor based on the AUC curve of 0.75. In addition, addition of miR-93-5p to the FHS risk factors enhanced the discriminatory ability of FHS risk factors model to detect stable CAD. Similarly, the discriminatory ability of the FHS risk factors to detect STEMI was significantly enhanced with the addition of miR-499a -5p to the model.

This study by O Sullivan et al. provides an exciting step towards identification of potential circulating biomarkers for CAD. However, several notes of caution need to be considered. In the comparisons made by O Sullivan et al., the miRs were quantitated using “normalized expression” levels, adjusted to the average Cp of all expressed miRs, and therefore do not reflect absolute copy numbers. Given the prediction models were done using relative levels of miRs in plasma, it is possible that the prediction models may differ based on the normalization method used.

An interesting finding was the value of miR93-5p expression to the traditional FHS risk factors to improve ability to detect stable CAD. This can be clinically useful and warrants further evaluation. It is interesting that the finding did not hold in control vs. STEMI subjects, and the significance of this remains unknown. STEMI is a diagnosis made based on clinical presentation and EKG-based criteria, and given the time constraints of definitive treatment for STEMI (8,9); the utility of a blood test is very limited, except for unusual cases where diagnosis can be confounded. Even in these situations, given the very high sensitivity and specificity of the currently available biomarkers for myocardial injury such as cardiac troponins (10), the potential clinical utility of miR-499a-5p is questionable. An ideal biomarker should provide diagnostic and prognostic information that is specific and incremental to existing clinical and demographic data, and in the context of STEMI, the findings from miR-499a-5p falls short of existing cardiac biomarkers. miR-499 is encoded by an intronic region of the myosin heavy chain gene (11). Therefore, circulating levels of miR-499 likely reflect the pathogenic process of myocardial damage. Given that the comparisons in this study were specifically made between controls and patients with STEMI, it is unclear if miR-499 is specific to STEMI, or a reflection of myocyte injury in response to any form of acute myocardial infarctions. Given similar findings of miR-499 from other studies in patients with acute myocardial infarction (12-15), miR-499 may have some clinical utility in detecting any form of myocardial infarctions at a time frame before cardiac troponins are detectable as shown by Wang et al. (15), or if a troponin negative, but miR-499 positive group is established to have true myocardial damage.

In selecting a panel of limited miRs with known role in cardiovascular disease, O Sullivan et al. used a candidate biomarker approach in this study. This approach allows for stronger statistical analysis of the selected miRs, but this limits the identification of potential unknown or novel biomarkers. In addition, the possibility that combined changes in a panel of miRs may have a better predictive ability for diagnosis of CAD over a single miR was not explored in the current study.

Finally, miRs in circulation can exist as free micro-RNAs, in exosomes or micro-particles, in protein-bound complexes, or in lipid complexes (16). In this study by O Sullivan et al., the authors examined the total circulating miRs, but it is prudent to consider that micro-RNAs from each of these circulating fractions may give different information compared to miRs from total circulating fraction. miRs from these fractions may provide alternate approaches to identify circulating miRs as biomarkers, and give crucial information regarding pathophysiology of a disease process.

A biomarker is a defined characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention, including therapeutic interventions (17). Circulating miRs hold promise as potential biomarkers that can be indicative of these processes, but as knowledge of different circulating forms of miRs are still evolving, the identification of an ideal miR as a biomarker of CAD remains a work in progress.


Funding: BH Annex is supported by 1R01HL116455, 1R01HL121635 and 2R01HL101200. S Hazarika is supported by 1K08HL130573-01.


Conflicts of Interest: The authors have no conflicts of interest to declare.


  1. He L, Hannon GJ. MicroRNAs: small RNAs with a big role in gene regulation. Nat Rev Genet 2004;5:522-31. [Crossref] [PubMed]
  2. Jonas S, Izaurralde E. Towards a molecular understanding of microRNA-mediated gene silencing. Nat Rev Genet 2015;16:421-33. [Crossref] [PubMed]
  3. Gurha P. MicroRNAs in cardiovascular disease. Curr Opin Cardiol 2016;31:249-54. [Crossref] [PubMed]
  4. Quiat D, Olson EN. MicroRNAs in cardiovascular disease: from pathogenesis to prevention and treatment. J Clin Invest 2013;123:11-8. [Crossref] [PubMed]
  5. Chen X, Ba Y, Ma L, et al. Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res 2008;18:997-1006. [Crossref] [PubMed]
  6. Lawrie CH, Gal S, Dunlop HM, et al. Detection of elevated levels of tumour-associated microRNAs in serum of patients with diffuse large B-cell lymphoma. Br J Haematol 2008;141:672-5. [Crossref] [PubMed]
  7. Mitchell PS, Parkin RK, Kroh EM, et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci U S A 2008;105:10513-8. [Crossref] [PubMed]
  8. O'Gara PT, Kushner FG, Ascheim DD, et al. 2013 ACCF/AHA guideline for the management of ST-elevation myocardial infarction: executive summary: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines: developed in collaboration with the American College of Emergency Physicians and Society for Cardiovascular Angiography and Interventions. Catheter Cardiovasc Interv 2013;82:E1-27. [Crossref] [PubMed]
  9. Task Force on the management of ST-segment elevation acute myocardial infarction of the European Society of Cardiology (ESC), Steg PG, James SK, et al. ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation. Eur Heart J 2012;33:2569-619.
  10. Hammerer-Lercher A, Ploner T, Neururer S, et al. High-sensitivity cardiac troponin T compared with standard troponin T testing on emergency department admission: how much does it add in everyday clinical practice? J Am Heart Assoc 2013;2:e000204. [Crossref] [PubMed]
  11. Bhuiyan SS, Kinoshita S, Wongwarangkana C, et al. Evolution of the myosin heavy chain gene MYH14 and its intronic microRNA miR-499: muscle-specific miR-499 expression persists in the absence of the ancestral host gene. BMC Evol Biol 2013;13:142. [Crossref] [PubMed]
  12. Adachi T, Nakanishi M, Otsuka Y, et al. Plasma microRNA 499 as a biomarker of acute myocardial infarction. Clin Chem 2010;56:1183-5. [Crossref] [PubMed]
  13. Corsten MF, Dennert R, Jochems S, et al. Circulating MicroRNA-208b and MicroRNA-499 reflect myocardial damage in cardiovascular disease. Circ Cardiovasc Genet 2010;3:499-506. [Crossref] [PubMed]
  14. D'Alessandra Y, Devanna P, Limana F, et al. Circulating microRNAs are new and sensitive biomarkers of myocardial infarction. Eur Heart J 2010;31:2765-73. [Crossref] [PubMed]
  15. Wang GK, Zhu JQ, Zhang JT, et al. Circulating microRNA: a novel potential biomarker for early diagnosis of acute myocardial infarction in humans. Eur Heart J 2010;31:659-66. [Crossref] [PubMed]
  16. Creemers EE, Tijsen AJ, Pinto YM. Circulating microRNAs: novel biomarkers and extracellular communicators in cardiovascular disease? Circ Res 2012;110:483-95. [Crossref] [PubMed]
  17. FDA-NIH Biomarker Working Group. BEST (Biomarkers, EndpointS, and other Tools) Resource. Silver Spring (MD): Food and Drug Administration (US); Bethesda (MD): National Institutes of Health (US), 2016.
Cite this article as: Hazarika S, Annex BH. Circulating micro-RNAs as biomarkers of coronary artery disease: is it ready for primetime or still a work in progress? Ann Transl Med 2017;5(1):10. doi: 10.21037/atm.2017.01.05