BACKGROUND: Aging and biological senescence, both related to cardiovascular disease, are mediated by oxidative stress and inflammation. We aim to develop a predictive tool to evaluate the degree of biological senescence in coronary patients. METHODS: Relative telomere length (RTL) of 1002 coronary patients from the CORDIOPREV study (NCT00924937) was determined at baseline in addition to markers of inflammatory response (hs-C-Reactive Protein, monocyte chemoattractant protein-1, IL-6, IL-1β, TNF-α, adiponectin, resistin, and leptin), and oxidative stress (nitric oxide, lipid peroxidation products, carbonylated proteins, catalase, total glutathione, reduced glutathione, oxidized glutathione, superoxide dismutase and peroxidated glutathione). Biological senescence was defined using the cut-off value defined by the lower quintile of relative telomere length in our population (RTL =0.7629). We generated and tested different predictive models based on logistic regression analysis to identify biological senescence. Three models were designed to be used with different sets of information. RESULTS: We selected those patients with all the variables proposed to develop the predictive models (n = 353). Statistically significant differences between both groups (Biological senescence vs. Non-Biological senescence) were found for total cholesterol, catalase, superoxide dismutase, IL-1β, resistin and leptin. The area under the curve of receiver-operating characteristic to predict biological senescence for our models were 0.65, 0.75 and 0.72. CONCLUSIONS: These predictive models allow us to calculate the degree of biological senescence in coronary patients, identifying a subgroup of patients at higher risk and who may require more intensive treatment. This article is protected by copyright. All rights reserved.
BACKGROUND: Aging and biological senescence, both related to cardiovascular disease, are mediated by oxidative stress and inflammation. We aim to develop a predictive tool to evaluate the degree of biological senescence in coronary patients. METHODS: Relative telomere length (RTL) of 1002 coronary patients from the CORDIOPREV study (NCT00924937) was determined at baseline in addition to markers of inflammatory response (hs-C-Reactive Protein, monocyte chemoattractant protein-1, IL-6, IL-1β, TNF-α, adiponectin, resistin, and leptin), and oxidative stress (nitric oxide, lipid peroxidation products, carbonylated proteins, catalase, total glutathione, reduced glutathione, oxidized glutathione, superoxide dismutase and peroxidated glutathione). Biological senescence was defined using the cut-off value defined by the lower quintile of relative telomere length in our population (RTL =0.7629). We generated and tested different predictive models based on logistic regression analysis to identify biological senescence. Three models were designed to be used with different sets of information. RESULTS: We selected those patients with all the variables proposed to develop the predictive models (n = 353). Statistically significant differences between both groups (Biological senescence vs. Non-Biological senescence) were found for total cholesterol, catalase, superoxide dismutase, IL-1β, resistin and leptin. The area under the curve of receiver-operating characteristic to predict biological senescence for our models were 0.65, 0.75 and 0.72. CONCLUSIONS: These predictive models allow us to calculate the degree of biological senescence in coronary patients, identifying a subgroup of patients at higher risk and who may require more intensive treatment. This article is protected by copyright. All rights reserved.
Authors: Cristina Hidalgo-Moyano; Oriol Alberto Rangel-Zuñiga; Francisco Gomez-Delgado; Juan F Alcala-Diaz; Fernando Rodriguez-Cantalejo; Elena M Yubero-Serrano; Jose D Torres-Peña; Antonio P Arenas-de Larriva; Antonio Camargo; Pablo Perez-Martinez; Jose Lopez-Miranda; Javier Delgado-Lista Journal: Nutrients Date: 2022-09-14 Impact factor: 6.706