Torkia Lalem1, Lu Zhang1, Markus Scholz2, Ralph Burkhardt3, Victoria Saccheti1, Andrej Teren4, Joachim Thiery3, Yvan Devaux5. 1. Cardiovascular Research Unit, Luxembourg Institute of Health, Luxembourg. 2. Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Germany. 3. Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Germany. 4. Department of Cardiology/Internal Medicine, Heart Center, University of Leipzig, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Germany. 5. Cardiovascular Research Unit, Luxembourg Institute of Health, Luxembourg. Electronic address: yvan.devaux@lih.lu.
Abstract
BACKGROUND: A significant proportion of patients develop left ventricular (LV) remodeling leading to heart failure after acute myocardial infarction (AMI). Being able to identify these patients would represent a step forward towards personalized medicine. The present study aimed to determine the ability of cyclin dependent kinase inhibitor 1C (CDKN1C) to risk stratify AMI patients, in a sex-specific manner. METHODS: CDKN1C expression was measured in blood samples obtained at admission in a test cohort of 447 AMI patients and a validation cohort of 294 patients. The study end-point was LV function assessed by the ejection fraction (EF) at follow-up. RESULTS: In the test cohort, CDKN1C was lower in patients with a reduced EF (<40%) compared to patients with preserved EF (≥50%). This observation was specific to women. CDKN1C was a significant univariate predictor of LV function in women only. In multivariable analysis including demographic and clinical parameters, CDKN1C predicted LV function in women (odds ratio [95% confidence interval] 0.44 [0.23-0.82]) but not in men (0.90 [0.70-1.16]). Addition of CDKN1C to a multivariable clinical model reduced the Akaike information criterion, attesting for an incremental predictive value, in women (p = 0.006) but not in men (p = 0.41). Bootstrap internal validation confirmed the added value of CDKN1C in women. The female-specific predictive value of CDKN1C was validated in the independent cohort. CONCLUSION: CDKN1C is a novel female-specific biomarker of LV function after AMI.
BACKGROUND: A significant proportion of patients develop left ventricular (LV) remodeling leading to heart failure after acute myocardial infarction (AMI). Being able to identify these patients would represent a step forward towards personalized medicine. The present study aimed to determine the ability of cyclin dependent kinase inhibitor 1C (CDKN1C) to risk stratify AMI patients, in a sex-specific manner. METHODS:CDKN1C expression was measured in blood samples obtained at admission in a test cohort of 447 AMI patients and a validation cohort of 294 patients. The study end-point was LV function assessed by the ejection fraction (EF) at follow-up. RESULTS: In the test cohort, CDKN1C was lower in patients with a reduced EF (<40%) compared to patients with preserved EF (≥50%). This observation was specific to women. CDKN1C was a significant univariate predictor of LV function in women only. In multivariable analysis including demographic and clinical parameters, CDKN1C predicted LV function in women (odds ratio [95% confidence interval] 0.44 [0.23-0.82]) but not in men (0.90 [0.70-1.16]). Addition of CDKN1C to a multivariable clinical model reduced the Akaike information criterion, attesting for an incremental predictive value, in women (p = 0.006) but not in men (p = 0.41). Bootstrap internal validation confirmed the added value of CDKN1C in women. The female-specific predictive value of CDKN1C was validated in the independent cohort. CONCLUSION:CDKN1C is a novel female-specific biomarker of LV function after AMI.
Authors: Amela Jusic; Antonio Salgado-Somoza; Ana B Paes; Francesca Maria Stefanizzi; Núria Martínez-Alarcón; Florence Pinet; Fabio Martelli; Yvan Devaux; Emma Louise Robinson; Susana Novella Journal: Int J Mol Sci Date: 2020-07-10 Impact factor: 6.208