Epidemiologic Study of Sick Sinus Syndrome

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DESCRIPTION (provided by applicant): Sick sinus syndrome (SSS) is a disorder characterized by symptomatic dysfunction of the sinoatrial node. SSS accounts for 30-50% of indications for pacemaker implantations in the US and other Western countries. Despite its burden and associated costs, no previous studies have explored the incidence and risk factors for SSS in the general population. If modifiable risk factors are identified, the possibility exists that SSS might be preventable in many individuals. Similarly, limited information exists on the impact of SSS on the overall risk of cardiovascular disease and mortality. We propose to use available data from the Atherosclerosis Risk in Communities (ARIC) Study and the Cardiovascular Health Study (CHS), two community-based prospective cohorts in the US including 21,680 men and women, whites and African-Americans, aged 45 and older at baseline, to address the following aims: (1) To calculate the age, gender and race-specific incidence of SSS in ARIC and CHS, and estimate the total annual number of SSS events occurring in the US; (2) To identify lifestyles, clinical variables and biomarkers associated with the incidence of SSS, and to develop tools that help to predict the future risk of SSS in asymptomatic individuals; (3) To evaluate the association of SSS incidence with the subsequent risk of other cardiovascular outcomes (coronary heart disease, heart failure, atrial fibrillation) and total mortality. As an exploratory aim, we will explore genetic determinants of SSS using candidate gene and genome-wide approaches. Risk factors that will be studied include, but are not limited to, socioeconomic variables, smoking, physical activity, diet, smoking, body mass index and other adiposity measures, blood pressure, diabetes, blood cholesterol, electrocardiographic parameters, and history of cardiovascular disease (coronary heart disease, heart failure, and stroke) or chronic kidney disease. Biomarkers of interest include: C-reactive protein, NT-proBNP, and troponin T. SSS incident events will be identified from hospitalization discharge codes and Medicare (from the Center for Medicare and Medicaid Services (CMS)) data. Overall, our study will include a sample of more than 20,000 individuals from a diverse racial/ethnic and geographical background followed for almost 20 years. We expect to identify more than 400 incident cases of SSS. The proposed research constitutes an efficient approach to understand the epidemiology and etiopathogenesis of a relatively common cardiac condition in the elderly, and will provide relevant data to develop preventive strategies for SSS and foster our knowledge of cardiac electrophysiology.