Aims: Exercise is a trigger for acute coronary events especially in the untrained. Identifying subjects at risk remains a challenge. We set out to assess whether a distinct pattern of micro ribonucleic acids (miRNAs) expressed in response to an acute bout of all-out exercise might exist that would allow discrimination between health and disease.
Methods: Twenty healthy subjects and 20 patients with coronary artery disease (CAD) performed an all-out cycle ergometry. Total RNA was extracted from blood drawn before and after exercise. Each blood sample was analysed for 187 target miRNAs by quantitative reverse transcription polymerase chain reaction.
Results: At baseline, 18 miRNAs allowed discrimination between healthy subjects and CAD patients. In response to an acute all-out exercise in healthy subjects 51 miRNAs and in CAD patients 60 miRNAs were significantly modulated (all p < 0.05). Using logistic regression analysis, a unique pattern of pre-exercise miR-150-5p, post-exercise miR-101-3p, miR-141-3p and miR-200b-3p together with maximal oxygen uptake and maximal power corrected for bodyweight allowed discrimination between healthy subjects and CAD patients with an accuracy of 92.5%.
Conclusion: In this most comprehensive analysis of exercise effects on circulating miRNAs to date we demonstrate for the first time that a distinct combination of miRNAs together with variables of exercise capacity allow robust discrimination between healthy subjects and CAD patients. We postulate that miRNAs may eventually serve as biomarkers to identify patients with CAD and possibly even those at risk of exercise-induced cardiac events.
Keywords: Biomarker; cardiovascular disease; circulating microRNA; risk prediction; spiroergometry.