Connective Issues Fall 2023

 Daniel Martin, PhD – Cleveland Clinic Lerner Research Institute Mast cell chymase in Marfan syndrome thoracic aortic aneurysms $100,000 2-Year Victor McKusick Fellowship

There are currently no treatments for slowing aortic weakening, and major surgery to replace the aorta is the only current option. Dr. Martin’s research has identified a proteolytic enzyme that may lead to weakening of the aorta in individuals with Marfan syndrome. This enzyme is not made by the aorta cells but instead by immune cells which enter the aorta when the walls begin to weaken. Dr. Martin and the study team aim to determine if removing this enzyme from a mouse model of Marfan syndrome will reduce or prevent aortic damage. This work could lead to the development of a blood test to identify aortic weakening and may be useful in the study of other conditions where aortic aneurysms are a common occurrence.

 Leda Restrepo, PhD – Johns Hopkins University Epigenetic determinants and mechanistic insights into the role of the long non-coding RNA Meg3 in the pathogenesis of aortic aneurysm $100,000 2-Year Victor McKusick Fellowship A recurring issue for individuals a ff ected by Loeys-Dietz syndrome is a progressive dilatation of the aorta, leading to aortic aneurysm. An increasing number of studies have suggested associations between non-coding RNA and a predisposition to develop aneurysms. To examine the molecular mechanisms of how specific long non-coding RNA regulates aneurysm pathogenesis in Loeys-Dietz syndrome, Dr. Restrepo’s team will perform in vitro

and in vivo experiments with mice that repeat the clinical signs that individuals with LDS have, and they will test if this long non-coding RNA can modulate the progression of the aneurysm. This work could lead to the identification of a therapeutic agent for aortic aneurysm.

 Simone Saitta, PhD – Politecnico di Milano Machine learning for identification of geometrical and biomechanical

markers of aortic dissection in Marfan patients $100,000 2-Year Victor McKusick Fellowship

Choosing the right time to perform aortic graft surgery is essential for optimizing the care of individuals with Marfan syndrome. Given the seriousness of aortic dissection and the benefits of surgery to prevent it, there is a need to find new ways to decide when surgery is required. Artificial intelligence technology can be used to quickly and accurately analyze large amounts of medical imaging data of the aorta, extracting both conventional (like size) and

novel measurements (like curvature, angulation, tortuosity). Informed by these features, machine-learning models can be tuned to predict the risk for individuals with Marfan syndrome to developing aortic dissection. A main goal of Dr. Saitta’s study is to analyze aortic features in individuals with Marfan syndrome to find new ways to predict who is at risk for complications that may lead to aortic dissection.

To learn more about our Research Grant Program, including funded grants, visit Marfan.org/research.

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Fall 2023