Kylia Williams

Congenital heart disease (CHD) affects approximately 1% of infants born each year. Mechanistic insights into the genetic causes for CHD may provide possibilities for improvements in long term outcomes. There is strong evidence for a genetic etiology for CHD, and while over 300 CHD-associated genes have been identified from human linkage and sequencing studies, about 60% of all cases remain unexplained. The heterogeneity of the disease suggests that CHD involves complex genetics.

To investigate the causes of CHD, we obtained sequencing data from CHD patients and healthy controls. We are using gene set analysis to determine whether any groups of genes are overrepresented for variants in cases compared to controls. In addition, we will interaction analysis to identify combinations of genes that may not have effects on their own, but together can lead to a CHD phenotype. We also plan to stratify these analyses by phenotype to determine whether specific genes are more involved in certain elements of heart development.

These studies will generate new insights into the potential contribution of complex genetics in CHD pathogenesis that can be further tested using in vitro cell culture and in vivo mouse models of disease. Understanding the genetic causes of CHD can aid in the creation of diagnostics, interventions and therapeutics to improve outcomes for patients. The computational and statistical approaches applied here have broad relevance not only for CHD, but also for other complex human diseases.