Utilization of Whole Exome Sequencing to Identify Causative Mutations in Familial Congenital Heart Disease

作者：LaHaye Stephanie; Corsmeier Don; Basu Madhumita; Bowman Jessica L; Fitzgerald Butt Sara; Zender Gloria; Bosse Kevin; McBride Kim L; White Peter; Garg Vidu

来源：Circulation-Cardiovascular Genetics, 2016, 9(4): 320-329.

DOI：10.1161/CIRCGENETICS.115.001324

• ductus arteriosus, patent
• exome
• genetic testing
• heart septal defects, atrial
• tetralogy of Fallot

Background-Congenital heart disease (CHD) is the most common type of birth defect with family-and population-based studies supporting a strong genetic cause for CHD. The goal of this study was to determine whether a whole exome sequencing (WES) approach could identify pathogenic-segregating variants in multiplex CHD families.
Methods and Results-WES was performed on 9 kindreds with familial CHD, 4 with atrial septal defects, 2 with patent ductus arteriosus, 2 with tetralogy of Fallot, and 1 with pulmonary valve dysplasia. Rare variants (<1% minor allele frequency) that segregated with disease were identified by WES, and variants in 69 CHD candidate genes were further analyzed. These selected variants were subjected to in silico analysis to predict pathogenicity and resulted in the discovery of likely pathogenic mutations in 3 of 9 (33%) families. A GATA4 mutation in the transactivation domain, p.G115W, was identified in familial atrial septal defects and demonstrated decreased transactivation ability in vitro. A p.I263V mutation in TLL1 was identified in an atrial septal defects kindred and is predicted to affect the enzymatic functionality of TLL1. A disease-segregating splice donor site mutation in MYH11 (c.4599+1delG) was identified in familial patent ductus arteriosus and found to disrupt normal splicing of MYH11 mRNA in the affected individual.
Conclusions-Our findings demonstrate the clinical utility of WES to identify causative mutations in familial CHD and demonstrate the successful use of a CHD candidate gene list to allow for a more streamlined approach enabling rapid prioritization and identification of likely pathogenic variants from large WES data sets.

• 出版日期2016-8