ENU-based dominant genetic screen identifies contractile and neuronal gene mutations in congenital heart disease.

ABSTRACT

BACKGROUND: Congenital heart disease (CHD) is the most prevalent congenital anomaly, but its underlying causes are still not fully understood. It is believed that multiple rare genetic mutations may contribute to the development of CHD. METHODS: In this study, we aimed to identify novel genetic risk factors for CHD using an ENU-based dominant genetic screen in mice. We analyzed fetuses with malformed hearts and compared them to control littermates by whole exome or whole genome sequencing (WES/WGS). The differences in mutation rates between observed and expected values were tested using the Poisson and Binomial distribution. Additionally, we compared WES data from human CHD probands obtained from the Pediatric Cardiac Genomics Consortium with control subjects from the 1000 Genomes Project using Fisher's exact test to evaluate the burden of rare inherited damaging mutations in patients. RESULTS: By screening 10,285 fetuses, we identified 1109 cases with various heart defects, with ventricular septal defects and bicuspid aortic valves being the most common types. WES/WGS analysis of 598 cases and 532 control littermates revealed a higher number of ENU-induced damaging mutations in cases compared to controls. GO term and KEGG pathway enrichment analysis showed that pathways related to cardiac contraction and neuronal development and functions were enriched in cases. Further analysis of 1457 human CHD probands and 2675 control subjects also revealed an enrichment of genes associated with muscle and nervous system development in patients. By combining the mice and human data, we identified a list of 101 candidate digenic genesets, from which each geneset was co-mutated in at least one mouse and two human probands with CHD but not in control mouse and control human subjects. CONCLUSIONS: Our findings suggest that gene mutations affecting early hemodynamic perturbations in the developing heart may play a significant role as a genetic risk factor for CHD. Further validation of the candidate gene set identified in this study could enhance our understanding of the complex genetics underlying CHD and potentially lead to the development of new diagnostic and therapeutic approaches.