Sudden cardiac arrest (SCA) continues to be a major public health problem, representing almost 20% of all deaths in industrialized societies. SCA accounts for ~50% of all heart disease deaths, an important subset of which consists of individuals not previously diagnosed with heart disease. The
devastating psycho-social impact on society and on families of victims often still in their prime, is obvious. Ventricular fibrillation (VF) is the most common arrhythmia causing SCA. VF leads to death within minutes if left untreated, yet occurs out-of-hospital in the vast majority, resulting in survival rates of only 5-20%. Clearly, prevention is key to solving this important public health problem. However, our ability to prevent SCA is at present hindered by our gap in knowledge of causes and mechanisms of SCA. Moreover, genetic and non-genetic modulatory factors, including gender, age, co-morbidities, and lifestyle are expected to mediate SCA risk, but their contribution are still unknown. PREDICT2 brings together renowned PIs with expertise in epidemiological, clinical, genetic, and functional studies to identify factors causing SCA, understand their underlying mechanisms and use these insights to construct strategies to prevent and treat SCA. They will crucially build on the foundations laid in PREDICT1 which involved, amongst others, the accrual of large cohorts of highly characterized patients and the generation of preclinical disease models and insights. Research will focus on the inherited arrhythmia syndromes, generally considered paradigms for the understanding of the arrhythmogenic substrate in the more frequent cardiac syndromes associated with SCA. Specifically, PREDICT2 will:
(1) Identify genetic and non-genetic factors that conspire to determine risk for SCA and use these to construct risk prediction algorithms for personalized risk assessment in the individual patient;
(2) Conduct functional studies to identify mechanisms underlying SCA to enable the development of new risk stratification and therapeutic strategies;
(3) Conduct clinical studies, assessing risk prediction algorithms and therapeutic interventions, to improve treatment and prevention of SCA.