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Isolation of Human Primary Valve Cells for In vitro Disease Modeling
Published on: April 16, 2021
Genetic Insights Into Bicuspid Aortic Valve Disease
Radoslaw Debiec1, Hanish Sall, Nilesh J Samani
1From the *Leicester Cardiovascular Biomedical Research Unit, Department of Cardiovascular Sciences, University of Leicester, Glenfield General Hospital, Leicester, United Kingdom; †Department of Cardiology, University of Leicester, Northhampton General Hospital, Northhampton, United Kingdom; and ‡Department of Cardiovascular Sciences, University of Leicester, East Midlands Congenital Heart Centre, Glenfield General Hospital, Leicester, United Kingdom.
Abstract:
Bicuspid aortic valve (BAV) is the most common valvular congenital heart defect in the general population. BAV is commonly associated with the presence of other congenital cardiovascular malformations, which leads to cardiovascular complications requiring surgery in around 27% of cases. Familial clustering of BAV is well-recognized, and international guidelines advocate that first-degree relatives of patients with BAV be screened. Studies of genetic linkage in affected families, syndromic forms of BAV, and sporadic patients led to discoveries of genetic loci harboring genes involved in the development of BAV. However, only a few of these findings have been replicated in other populations and been proven functional in animal models. This task is further complicated by the phenotypic and genetic heterogeneity of BAV disease. BAV differs in valve fusion patterns and some studies have suggested that different valve fusion patterns originate from different pathophysiological processes. We present an overview of the published work on genetic linkage and its association with BAV disease. Presented articles used different discovery strategies ranging from candidate gene association to whole exome sequencing, as well as various validation protocols. Although still very limited, our understanding of the molecular pathology of BAV disease is likely to influence current clinical practice by enabling genetic counseling, prenatal diagnosis, and risk stratification for individual patients. This task will be made possible thanks to increasing availability, as well as the reduced cost of next-generation sequencing and bioinformatic processing of data.
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