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.
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