Understanding the Genetic Basis of Cardiac Arrhythmias
Principal Investigator: Dr Steven Lubitz
Approved Research ID: 17488
Approval date: November 1st 2016
Cardiac arrhythmias are leading causes of morbidity and sudden death, however the pathophysiologic basis of arrhythmias largely remains unclear. In recent years, heritability of arrhythmias has been described suggesting a genetic basis. We specifically intend to identify the genetic causes of cardiac arrhythmias, assess the causal relations between cardiac arrhythmias and long-term morbidity, estimate the long-term risks of genetic predisposition to cardiac arrhythmias, and determine the relations between cardiac arrhythmias and other cardiovascular traits including cardiac conduction, cardiac structural features, and myocardial related biomarkers. Cardiac arrhythmias are a common source of morbidity, yet the mechanisms are poorly understood. Our proposal is designed to address the genetic underpinnings of cardiac arrhythmias, and assess their relations with morbidity. Our proposal has the potential to provide novel insights into the pathophysiological and biological mechanisms of cardiac arrhythmias. We believe that our findings may yield novel preventative, diagnostic, and therapeutic insights. We submit that our proposal is consistent with the UK Biobank's goal of improving the understanding of common diseases and improving public health. We will examine the genetic underpinnings of common cardiac arrhythmias, including tachyarrhythmias (disorders involving fast heart rates, such as supraventricular tachycardias), and bradyarrhythmias (disorders involving slow heart rates, such as those necessitating pacemaker implantation). Phenotypes will be ascertained on the basis of diagnostic codes (ICD), procedure codes and operations, and self-report. The research will involve both common and rare variant genetic association testing across the genome with cardiac arrhythmia phenotypes. The results of analyses will be meta-analyzed with other independent analyses to enhance power. We will use contemporary statistical approaches and significance thresholds for determining significance. We anticipate using the full cohort for this proposal.