Frontiers in Cardiovascular Medicine (Aug 2021)
A Multi-Omics Approach Using a Mouse Model of Cardiac Malformations for Prioritization of Human Congenital Heart Disease Contributing Genes
Abstract
Congenital heart disease (CHD) is the most common type of birth defect, affecting ~1% of all live births. Malformations of the cardiac outflow tract (OFT) account for ~30% of all CHD and include a range of CHDs from bicuspid aortic valve (BAV) to tetralogy of Fallot (TOF). We hypothesized that transcriptomic profiling of a mouse model of CHD would highlight disease-contributing genes implicated in congenital cardiac malformations in humans. To test this hypothesis, we utilized global transcriptional profiling differences from a mouse model of OFT malformations to prioritize damaging, de novo variants identified from exome sequencing datasets from published cohorts of CHD patients. Notch1+/−; Nos3−/− mice display a spectrum of cardiac OFT malformations ranging from BAV, semilunar valve (SLV) stenosis to TOF. Global transcriptional profiling of the E13.5 Notch1+/−; Nos3−/− mutant mouse OFTs and wildtype controls was performed by RNA sequencing (RNA-Seq). Analysis of the RNA-Seq dataset demonstrated genes belonging to the Hif1α, Tgf-β, Hippo, and Wnt signaling pathways were differentially expressed in the mutant OFT. Mouse to human comparative analysis was then performed to determine if patients with TOF and SLV stenosis display an increased burden of damaging, genetic variants in gene homologs that were dysregulated in Notch1+/−; Nos3−/− OFT. We found an enrichment of de novo variants in the TOF population among the 1,352 significantly differentially expressed genes in Notch1+/−; Nos3−/− mouse OFT but not the SLV population. This association was not significant when comparing only highly expressed genes in the murine OFT to de novo variants in the TOF population. These results suggest that transcriptomic datasets generated from the appropriate temporal, anatomic and cellular tissues from murine models of CHD may provide a novel approach for the prioritization of disease-contributing genes in patients with CHD.
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