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PubMed 23321620


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Title: Genetics can contribute to the prognosis of Brugada syndrome: a pilot model for risk stratification.

Authors: Elena Sommariva, Carlo Pappone, Filippo Martinelli Boneschi, Chiara Di Resta, Maria Rosaria Carbone, Erika Salvi, Pasquale Vergara, Simone Sala, Daniele Cusi, Maurizio Ferrari, Sara Benedetti

Journal, date & volume: Eur. J. Hum. Genet., 2013 Sep , 21, 911-7

PubMed link: http://www.ncbi.nlm.nih.gov/pubmed/23321620


Abstract
Brugada syndrome is an inherited arrhythmogenic disorder leading to sudden death predominantly in the 3-4 decade. To date the only reliable treatment is the implantation of a cardioverter defibrillator; however, better criteria for risk stratification are needed, especially for asymptomatic subjects. Brugada syndrome genetic bases have been only partially understood, accounting for <30% of patients, and have been poorly correlated with prognosis, preventing inclusion of genetic data in current guidelines. We designed an observational study to identify genetic markers for risk stratification of Brugada patients by exploratory statistical analysis. The presence of genetic variants, identified by SCN5A gene analysis and genotyping of 73 candidate polymorphisms, was correlated with the occurrence of major arrhythmic events in a cohort of 92 Brugada patients by allelic association and survival analysis. In all, 18 mutations were identified in the SCN5A gene, including 5 novel, and statistical analysis indicated that mutation carriers had a significantly increased risk of major arrhythmic events (P=0.024). In addition, we established association of five polymorphisms with major arrhythmic events occurrence and consequently elaborated a pilot risk stratification algorithm by calculating a weighted genetic risk score, including the associated polymorphisms and the presence of SCN5A mutation as function of their odds ratio. This study correlates for the first time the presence of genetic variants with increased arrhythmic risk in Brugada patients, representing a first step towards the design of a new risk stratification model.