During development, the cardiac outflow tract (OFT) arises primarily from progenitor cells in the so-called second heart field (SHF) and OFT defects are seen in nearly 30% of all congenital heart disease. Traditionally, OFT maturation has been modeled as three distinct events ? septation, alignment and rotation. Double outlet right ventricle (DORV) results when the OFT fails to appropriately align itself such that systemic and pulmonary outflows can exit from the respective ventricles. Although several animal models have been proposed to study the molecular basis for DORV, these models have failed to sufficiently explain simultaneous alignment and rotation of the OFT, and as such do not faithfully phenocopy the spectrum of DORV seen in the clinical setting. Clinically, DORV presents as a spectrum of abnormalities with associated defects in great vessel orientation - ranging from the tetralogy-type DORV with normally related great arteries (NRGA) to transposition-type DORV with malposed great arteries (MGA). Surgical management and outcomes are vastly different between these two types and, hence, studying the underlying unique molecular defects is of intrinsic scientific merit. The accompanying proposal seeks to utilize genetic mutations identified in children with DORV to inform mutations seen in a novel mouse model of DORV. The PI has access to clinical and whole exome data from the PCGC of patients with DORV, which will be analyzed to identify genotype-phenotype correlation with DORV/NRGA vs. MGA. The PI's lab has established a unique mouse model of DORV, wherein Isl-Cre driven DLL4f/wt mice exhibit DORV/NRGA, whereas the addition of partial knockout of FGF8 results in DORV/MGA. This system provides the opportunity to utilize a polygenic inheritance pattern to model clinically relevant DORV phenotypic variants. RNA-seq analysis from these two lesion sets will be used to identify murine mutations. Superimposing human and murine data will pave way for the understanding of relevant pathways for subsequent analyses. Given that the PI is a practicing congenital heart surgeon and a cardiac developmental biology researcher, a key strength of this proposal is the utilization of human data to inform the analysis in a novel mouse model. The conceptual approach is driven by the PI?s clinical expertise in caring for children with DORV, which has also provided the ability to study genetic mutations stratified by clinical phenotype. The laboratory aspect of this project naturally builds upon on the PI?s established expertise studying DLL4 signaling in OFT development, and utilizes a model of DORV set up as part of a K08 grant from NHLBI. In addition, the proposal enjoys the support of USC?s Institute of Translational Genomics, which has a robust platform to undertake the kind of genetic analysis proposed in this study. In the spirit of the R03 mechanism, this pilot work seeks to analyze genetic data from pre-existing clinical exome sequences and from established mouse embryos. Successful completion of this work will provide a platform for more robust and clinically relevant evaluation of OFT alignment and rotation paving way for a larger R01 application.
Congenital heart disease, which results from abnormalities during fetal heart development, is the leading cause of birth-defect related deaths, yet, bench research has been able to provide a molecular basis for only a small proportion of clinically relevant defects. The current proposal comes from a congenital heart surgeon-scientist who has the unique perspective of being a clinician who treats patients with various sub-types of a defect called DORV, and at the same time, as a developmental biologist, has established a mouse model that can mimic the defect seen in clinical practice. This proposal seeks to identify genetic changes in children with DORV and superimpose these with genetic mutations in mice with the same sub-types of the defect to reverse engineer `real-world' complex heart defects in mice and study their development in detail to ultimately benefit the patient population.
