Mahir Karakas1,2, Christian Schulte1, Sebastian Appelbaum1,2, Francisco Ojeda1, Karl J Lackner3,4, Thomas Münzel4,5, Renate B Schnabel1,2, Stefan Blankenberg1,2, Tanja Zeller1,2. 1. Department of General and Interventional Cardiology, University Heart Center Hamburg, Hamburg, Germany. 2. German Center for Cardiovascular Research (DZHK), Partner Site Hamburg, Lübeck, Kiel, Hamburg, Germany. 3. Department of Laboratory Medicine, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany. 4. German Center for Cardiovascular Research (DZHK), Partner Site Rhein-Main, Mainz, Germany. 5. Department of Medicine II, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany.
Abstract
INTRODUCTION: Stratification for subsequent coronary events among patients with coronary artery disease (CAD) is of considerable interest because of the potential to guide secondary preventive therapies. Recently, we identified eight microRNAs (miRNAs), which facilitated acute coronary syndrome (ACS) diagnosis. In this study, we aimed to evaluate their potential role as prognostic biomarkers for cardiovascular disease. METHODS: The serum concentrations of eight candidate miRNAs -miR-19a, miR-19b, miR-132, miR-140-3p, miR-142-5p, miR-150, miR-186, and miR-210 were measured in a cohort of 1112 patients with documented CAD-including 430 patients with ACS and 682 patients with stable angina pectoris. Cardiovascular death was the main outcome measure. RESULTS: During a median follow-up of 4.0 years, most miRNAs reliably predicted cardiovascular death in ACS patients. Cox regression analyses indicated that in particular miR-132 (HR 2.85 per 1 SD increase, P = 0.022), miR-140-3p (HR 2.88 per 1 SD increase, P = 0.022), and miR-210 (HR 3.10 per 1 SD increase, P = 0.039) were able to precisely predict cardiovascular death. Circulating miR-132, miR-140-3p, and miR-210 clearly improved various model performance measures, including C-statistics (AUC [area under the receiver-operating characteristic curve] for miR-132: 0.737; AUC for miR-140-3p: 0.756; AUC for miR-210: 0.754). CONCLUSIONS: This is the largest study so far evaluating the prognostic value of circulating miRNAs in cardiovascular disease. Our study shows that single miRNAs derived from peripheral blood predict mortality in secondary prevention settings, and thereby represent valuable biomarkers for risk estimation in CAD. Published on behalf of the European Society of Cardiology. All rights reserved.
INTRODUCTION: Stratification for subsequent coronary events among patients with coronary artery disease (CAD) is of considerable interest because of the potential to guide secondary preventive therapies. Recently, we identified eight microRNAs (miRNAs), which facilitated acute coronary syndrome (ACS) diagnosis. In this study, we aimed to evaluate their potential role as prognostic biomarkers for cardiovascular disease. METHODS: The serum concentrations of eight candidate miRNAs -miR-19a, miR-19b, miR-132, miR-140-3p, miR-142-5p, miR-150, miR-186, and miR-210 were measured in a cohort of 1112 patients with documented CAD-including 430 patients with ACS and 682 patients with stable angina pectoris. Cardiovascular death was the main outcome measure. RESULTS: During a median follow-up of 4.0 years, most miRNAs reliably predicted cardiovascular death in ACS patients. Cox regression analyses indicated that in particular miR-132 (HR 2.85 per 1 SD increase, P = 0.022), miR-140-3p (HR 2.88 per 1 SD increase, P = 0.022), and miR-210 (HR 3.10 per 1 SD increase, P = 0.039) were able to precisely predict cardiovascular death. Circulating miR-132, miR-140-3p, and miR-210 clearly improved various model performance measures, including C-statistics (AUC [area under the receiver-operating characteristic curve] for miR-132: 0.737; AUC for miR-140-3p: 0.756; AUC for miR-210: 0.754). CONCLUSIONS: This is the largest study so far evaluating the prognostic value of circulating miRNAs in cardiovascular disease. Our study shows that single miRNAs derived from peripheral blood predict mortality in secondary prevention settings, and thereby represent valuable biomarkers for risk estimation in CAD. Published on behalf of the European Society of Cardiology. All rights reserved.
Authors: Kemal M Akat; Youngmin A Lee; Arlene Hurley; Pavel Morozov; Klaas Ea Max; Miguel Brown; Kimberly Bogardus; Anuoluwapo Sopeyin; Kai Hildner; Thomas G Diacovo; Markus F Neurath; Martin Borggrefe; Thomas Tuschl Journal: JCI Insight Date: 2019-04-11
Authors: Michael G Silverman; Ashish Yeri; M Vinayaga Moorthy; Fernando Camacho Garcia; Neal A Chatterjee; Charlotte S A Glinge; Jacob Tfelt-Hansen; Ane M Salvador; Alexander R Pico; Ravi Shah; Christine M Albert; Saumya Das Journal: JACC Clin Electrophysiol Date: 2019-10-30