Luis M Rincón1,2, Macarena Rodríguez-Serrano3, Elisa Conde3, Val F Lanza4, Marcelo Sanmartín1, Paz González-Portilla1, Marta Paz-García3, José Manuel Del Rey5, Miriam Menacho5, María-Laura García Bermejo3, José L Zamorano1,6. 1. Department of Cardiology, Hospital Universitario Ramón y Cajal, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Centro de Investigación Biomédica en Red de Enfermedades Cardiovasculares (CIBERCV), Madrid, 28034, Spain. 2. Instituto de Investigación Biomédica de Salamanca (IBSAL), Universidad de Salamanca, Salamanca, Spain. 3. Biomarkers and Therapeutic Targets Laboratory and Core Facility, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Spanish Renal Research Network (REDinREN), Ctra. Colmenar Km 9100, Madrid, 28034, Spain. 4. Bioinformatics Core Facility, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain. 5. Department of Biochemistry, Hospital Universitario Ramón y Cajal, Universidad de Alcalá, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain. 6. Hospital La Zarzuela, Madrid, Spain.
Abstract
BACKGROUND: Patients with acute myocardial infarction (MI) are at high risk of upcoming events, in particular heart failure (HF), but reliable stratification methods are lacking. Our goal was to evaluate the potential role of circulating miRNAs as prognostic biomarkers in patients presenting with MI. METHODS AND RESULTS: We conducted a prospective study among 311 consecutive patients hospitalized with MI (65% ST-segment elevation MI & median age of 55 years) with long-term follow-up. An initial screening was conducted to select candidate miRNAs, with subsequent study of 14 candidate miRNAs. The primary outcome was the composite of hospital admission for HF or cardiovascular death. During a mean follow-up of 2.1 years miR-21-5p, miR-23a-3p, miR27b-3p, miR-122-5p, miR210-3p, and miR-221-3p reliably predicted the primary outcome. Multivariate Cox regression analyses highlighted that miR-210-3p [hazard ratio (HR) 2.65 per 1 SD increase, P < 0.001], miR-23a-3p (HR 2.11 per 1 SD increase, P < 0.001), and miR-221-3p (HR 2.03 per 1 SD increase, P < 0.001) were able to accurately predict the primary outcome, as well as cardiovascular death, HF hospitalizations, and long-term New York Heart Association (NYHA) functional class. These three miRNAs clearly improved the performance of multivariate clinical models: ΔC-statistic = 0.10 [95% confidence interval (CI), 0.03-0.17], continuous net reclassification index = 34.8% (95%CI, 5.8-57.4%), and integrated discrimination improvement (P < 0.001). CONCLUSIONS: This is the largest study evaluating the prognostic value of circulating miRNAs for HF-related events among patients with MI. We show that several miRNAs predict HF hospitalizations, cardiovascular mortality, and poor long-term NYHA status and improve current risk prediction methods.
BACKGROUND: Patients with acute myocardial infarction (MI) are at high risk of upcoming events, in particular heart failure (HF), but reliable stratification methods are lacking. Our goal was to evaluate the potential role of circulating miRNAs as prognostic biomarkers in patients presenting with MI. METHODS AND RESULTS: We conducted a prospective study among 311 consecutive patients hospitalized with MI (65% ST-segment elevation MI & median age of 55 years) with long-term follow-up. An initial screening was conducted to select candidate miRNAs, with subsequent study of 14 candidate miRNAs. The primary outcome was the composite of hospital admission for HF or cardiovascular death. During a mean follow-up of 2.1 years miR-21-5p, miR-23a-3p, miR27b-3p, miR-122-5p, miR210-3p, and miR-221-3p reliably predicted the primary outcome. Multivariate Cox regression analyses highlighted that miR-210-3p [hazard ratio (HR) 2.65 per 1 SD increase, P < 0.001], miR-23a-3p (HR 2.11 per 1 SD increase, P < 0.001), and miR-221-3p (HR 2.03 per 1 SD increase, P < 0.001) were able to accurately predict the primary outcome, as well as cardiovascular death, HF hospitalizations, and long-term New York Heart Association (NYHA) functional class. These three miRNAs clearly improved the performance of multivariate clinical models: ΔC-statistic = 0.10 [95% confidence interval (CI), 0.03-0.17], continuous net reclassification index = 34.8% (95%CI, 5.8-57.4%), and integrated discrimination improvement (P < 0.001). CONCLUSIONS: This is the largest study evaluating the prognostic value of circulating miRNAs for HF-related events among patients with MI. We show that several miRNAs predict HF hospitalizations, cardiovascular mortality, and poor long-term NYHA status and improve current risk prediction methods.