ABSTRACT Atrial fibrillation (AF) is the most commonly-diagnosed cardiac arrhythmia, affecting more than 33 million individuals throughout the world. One in four Americans above the age of 40 will be diagnosed with AF in his or her lifetime. AF accounts for one-fourth of all strokes and is also associated with an increased risk of dementia, heart failure, and death, even in patients receiving optimal evidence-based care. Despite the profound healthcare burden caused by AF, there is a limited understanding of the mechanisms that provoke the arrhythmia in patients. Hence, new pathophysiologic insights into AF susceptibility are essential to guide improved therapeutic and preventive strategies to reduce the unacceptable burden of stroke, death, and hospitalizations associated with AF. TBX5 has been associated with AF both through GWAS and familial inheritance. However, the role of TBX5 specifically in the adult atrium has not been investigated. We now generate compelling preliminary data using conditional deletion of Tbx5 in the adult mouse using a tamoxifen-inducible Cre recombinase. This strategy of conditional deletion in adult mice bypasses the developmental requirements of TBX5 and permits study of TBX5 in normally developed adult hearts. We found that deletion of Tbx5 in the mature myocardium leads to reproducible, spontaneous atrial fibrillation in the absence of heart disease or any structural abnormalities. Preliminary gene expression analysis in the atria after removal of Tbx5 reveals misregulation of many genes linked to AF, including a number of ion channels and the transcription factor Pitx2, the most frequently implicated AF susceptibility locus. We hypothesize that TBX5 drives a gene network in the adult atria which includes PITX2 and coordinates the maintenance of atrial rhythm in the adult heart. This proposal will define the mechanisms by which adult removal of Tbx5 results in atrial fibrillation, and delineate the pathways by which TBX5 and maintains normal atrial rhythm. Defining these atrial transcriptional networks will allow prediction of AF risk and a strategy for primary prevention.