Computational profiling of hiPSC-derived heart organoids reveals chamber defects associated with Ebstein's anomaly

Abstract

Heart organoids have the potential to generate primary heart-like anatomical structures and hold great promise as in vitro models for cardiac disease. However, their properties have not yet been carefully studied, which hinders a wider spread application. Here we report the development of differentiation systems for ventricular and atrial heart organoids, enabling the study of heart disease with chamber defects. We show that our systems generate organoids comprising of major cardiac cell types, and we used single cell RNA sequencing together with sample multiplexing to characterize the cells we generate. To that end, we also developed a machine learning label transfer approach lever-aging cell type, chamber, and laterality annotations available for primary human fetal heart cells. We then used this model to analyze organoid cells from an isogeneic line carrying an Ebsteins anomaly associated genetic variant, and we successfully recapitulated the diseases atrialized ventricular defects. In summary, we have established a workflow integrating heart organoids and computational analysis to model heart development in normal and disease states.