Background: A significant proportion of patients develop heart failure (HF) after acute myocardial infarction (MI). Predicting this development with novel biomarkers would allow tailoring healthcare to each individual. We recently identified a circular RNA called MICRA which was associated with HF development after MI. Here, we tested whether MICRA was able to risk stratify MI patients.
Methods: MICRA was assessed in whole blood samples collected at reperfusion in 472 patients with acute MI. Left ventricular ejection fraction (EF) was evaluated by echocardiography at 4 months. Multivariable analyses with ordinal regression were conducted to determine the ability of MICRA to classify patients into 3 EF groups: reduced EF (≤ 40%), mid-range EF (4149%) and preserved EF (≥ 50%).
Results: Eighty seven patients (18%) had a reduced EF, 106 (22%) had a mid-range EF and 279 (59%) had a preserved EF at 4 months. MICRA classified patients into EF groups with an adjusted odds ratio [95% confidence interval] of 0.78 [0.64-0.95]. MICRA improved the predictive value of a multivariable clinical model as attested by a decrease of the Akaike Information Criteria (p = 0.012). Bootstrap internal validation confirmed the incremental prognostic value of MICRA.
Conclusion: We report that the circRNA MICRA improves risk classification after MI, supporting the added value of this novel biomarker in future prognostication strategies.
Keywords: Biomarkers; Circular RNAs; Heart failure; Myocardial infarction; Non-coding RNAs; Prognosis.