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Biomarkers to Predict Atrial Fibrillation Risk Identified

by Colleen Fleiss on April 4, 2019 at 10:23 AM
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Biomarkers to Predict Atrial Fibrillation Risk Identified

Two biomarkers linked to the risk of suffering from atrial fibrillation have been discovered by scientists at the University of Navarra (Spain), in collaboration with clinicians from the University Hospital of Donostia. Atrial fibrillation, a cardiac ailment affects more than 33.5 million people in the world.

In the European Union, it is present in 8.8 million people over 55 years of age and, specifically in Spain, it affects more than 4% of the population over 40 years of age. The World Health Organization considers this disease as an epidemic due to its high morbidity and mortality, and a public health problem due to its high prevalence.

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Atrial fibrillation is the most common alteration of the heart rhythm (arrhythmia). It happens when the heart pumps blood in an accelerated and irregular way, thus increasing the risk of suffering a heart attack, heart failure, stroke, or other complications related to this organ. Some common causes are heart disease or hormonal changes. It can be treated with medications and procedures, such as cardiac ablation, to correct irregular heart rhythms.

Researchers at Cima, Clínica Universidad de Navarra and the Faculty of Sciences, have discovered that, by analyzing a blood sample, it is possible to predict the appearance of this cardiac ailment. "The alteration of three molecules related to collagen metabolism (CITP, MMP-1, and PICP) determine the risk of suffering atrial fibrillation and the response to its treatment," explains Dr. Javier Díez, director of the Cardiovascular Disease Program at Cima, Head of Research of the Department of Cardiology and co-director of the Department of Nephrology at the Clínica Universidad de Navarra.
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Advances toward precision medicine

The study was performed in 392 patients, 150 of them treated with cardiac ablation. "The confirmation of these findings can lay the foundations to precisely adjust the most optimal treatment and follow-up for each patient according to these two biomarkers," adds Dr. Díez, also from CIBERCV.

Source: Eurekalert
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