Stem Cell Research & Therapy (Dec 2023)

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

  • Vanessa S. Fear,
  • Catherine A. Forbes,
  • Nicole C. Shaw,
  • Kathryn O. Farley,
  • Jessica L. Mantegna,
  • Jasmin P. Htun,
  • Genevieve Syn,
  • Helena Viola,
  • Henrietta Cserne Szappanos,
  • Livia Hool,
  • Michelle Ward,
  • Gareth Baynam,
  • Timo Lassmann

DOI
https://doi.org/10.1186/s13287-023-03592-1
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 14

Abstract

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Abstract Background Genomic 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. Methods We 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. Results Genetic 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. Conclusions This 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.

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