Gene editing and cardiac disease modelling for the interpretation of genetic variants of uncertain significance in congenital heart disease

BackgroundGenomic sequencing in congenital heart disease (CHD) patients often discovers novel genetic variants, which are classified as variants of uncertain significance (VUS). Functional analysis of each VUS is required in specialised laboratories, to determine whether the VUS is disease causative or not, leading to lengthy diagnostic delays. We investigated stem cell cardiac disease modelling and transcriptomics for the purpose of genetic variant classification using a GATA4 (p.Arg283Cys) VUS in a patient with CHD.MethodsWe performed high efficiency CRISPR gene editing with homology directed repair in induced pluripotent stem cells (iPSCs), followed by rapid clonal selection with amplicon sequencing. Genetic variant and healthy matched control cells were compared using cardiomyocyte disease modelling and transcriptomics.ResultsGenetic variant and healthy cardiomyocytes similarly expressed Troponin T (cTNNT), and GATA4. Transcriptomics analysis of cardiomyocyte differentiation identified changes consistent with the patient's clinical human phenotype ontology terms. Further, transcriptomics revealed changes in calcium signalling, and cardiomyocyte adrenergic signalling in the variant cells. Functional testing demonstrated, altered action potentials in GATA4 genetic variant cardiomyocytes were consistent with patient cardiac abnormalities.ConclusionsThis work provides in vivo functional studies supportive of a damaging effect on the gene or gene product. Furthermore, we demonstrate the utility of iPSCs, CRISPR gene editing and cardiac disease modelling for genetic variant interpretation. The method can readily be applied to other genetic variants in GATA4 or other genes in cardiac disease, providing a centralised assessment pathway for patient genetic variant interpretation.

Automated summary

This study utilized high efficiency CRISPR gene editing and induced pluripotent stem cells (iPSCs) for genetic variant classification in a patient with CHD. Functional testing showed altered action potentials in GATA4 genetic variant cardiomyocytes consistent with patient cardiac abnormalities, demonstrating the utility of iPSCs and CRISPR gene editing for genetic variant interpretation. The method can be applied to other genetic variants in GATA4 or other genes in cardiac disease, providing a centralized assessment pathway for patient genetic variant interpretation.