Towards Precision Medicine for Thoracic Aortic Disease: Defining the Clinical and Genomic Drivers of Bicuspid Aortopathy

PROJECT SUMMARY/ABSTRACT This is a K08 Mentored Clinical Scientist Research Career Development Award for Jason P. Glotzbach, MD. Dr. Glotzbach is a promising early career translational research clinician-scientist. He is a cardiac and aortic surgeon and Assistant Professor of Surgery on the tenure track at the University of Utah. His primary mentor for this proposal is Dr. Martin Tristani-Firouzi, MD, a pediatric cardiologist and expert in precision medicine and genomics of cardiovascular disease. This proposal spans five years and includes three Research Aims and four Career Development Aims. Bicuspid aortic valve (BAV) is the most common congenital cardiovascular anomaly and is associated with aortic aneurysm and aortic dissection, a condition defined as BAV aortopathy. Although both BAV and BAV aortopathy are thought to be highly heritable conditions, the causative clinical factors and genomic variants associated with development and progression of this disease remain poorly understood. The aim of the current proposal is to fill this knowledge gap through a three-pronged approach: 1) we will use an innovative statistical method called Poisson binomial comorbidity discovery to define clinical and demographic variables associated with BAV aortopathy; 2) we will develop a predictive model for BAV aortopathy risk using a state-of-the- art artificial intelligence method called probabilistic graphical models; and 3) we will utilize detailed pedigree-driven whole genome sequencing analysis of multigenerational families with a high prevalence of BAV aortopathy and patients undergoing surgery for BAV aortopathy to define genetic variants associated with BAV aortopathy. By combining a clinical risk model with an understanding of the genomic variants associated with BAV aortopathy, we expect to gain novel understanding of the pathogenesis of this highly impactful clinical condition. The information produced by this line of investigation has significant promise to help refine the clinical paradigms for treatment of aortic disease by building a foundation to allow development of precision medicine tools to predict aortic disease risk at the individual patient level. This line of inquiry, if successful, will lead to improved clinical outcomes in these complex and heterogenous patients. Through pursuit of the Research Aims of this proposal, Dr. Glotzbach will develop his expertise with the fundamental skills of statistics, predictive modeling, epidemiology, bioinformatics, genomic analysis, and research team leadership that will enable him to build a career as an independent translational investigator. 1