Genetics of Congenital Heart Disease

• Identification of novel genetic contributors to congenital heart defects [ Time Frame: up to 3 years, from date of genetic analysis to completion of genetic data analysis or identification of novel genetic contributors, whichever comes first ]
  Novel genetic abnormalities that are found to be associated with congenital heart defects in humans
  
  

Congenital heart disease (CHD) is the most common type of birth defect, but the etiology of CHD remains largely unknown. Genetic causes have been discovered for both syndromic and non-syndromic CHD utilizing several genetic approaches (Garg, 2006). The majority of these genetic causes have found by studying large families with autosomal dominant congenital heart disease and my laboratory has successfully used this methodology in the past (Garg, 2003; Garg 2005; Pan, 2009). Although these positional cloning approaches are very powerful, they are limited by rare nature of multi-generation pedigrees and are limited to milder forms of CHD that have allowed for the generation of large kindreds.

The other method that has traditionally been utilized to identify genetic causes of CHD is the screening of large populations of children with sporadic (non-familial) cases of CHD for genetic abnormalities (nucleotide sequence variations in candidate genes for CHD or for chromosomal copy number changes that involve CHD-candidate genes. This work has been tedious as a large number of candidate genes have been implicated as potentially responsible for CHD in humans (Srivastava and Olson, 2000). Although this approach has been successful (Schluterman, 2007; Rajagopal, 2007; Tomita-Mitchell, 2007; Richards, 2008; Ransom, 2009), it is also limited to the candidate gene lists.

Whole exome sequencing (WES) is a recently developed massively multiplexed sequencing technology that allows for the sequencing of all of the expressed genes. Therefore, this method can be applied to multiplex families and cohorts of sporadic cases to identify genetic causes of CHD in an unbiased manner. WES is dependent on the technical and bioinformatics prowess of the personnel running the WES and the controlling the data pipeline. At Nationwide Children's Hospital (NCH), our Biomedical Genomics Core is both technically skilled and have developed their own powerful data pipeline (Kelly, 2015). As other groups have successfully implemented WES into their CHD gene discovery toolkit (Zaidi, 2013; El Turki, 2014)), we expect to do the same. WES is powerful genetic tool that can be used in isolation or in conjunction with other types of genetic analysis (i.e. array comparative genomic hybridization, single nucleotide polymorphisms (SNP) arrays, traditional linkage analysis) to increase the yield of these investigations.