Decoding congenital heart disease: a multi-omic framework for cardiac lineage and regulatory dysfunction.

Abstract

Congenital heart disease (CHD) is the most prevalent birth defect worldwide, arising from disruptions in the tightly regulated processes of cardiac lineage specification and morphogenesis. Traditional models linking genotype to phenotype have been limited by low resolution and insufficient temporal mapping. Recent advances in single-cell RNA sequencing, spatial transcriptomics, and integrative multi-omics have transformed our understanding of CHD by enabling high-resolution analyses of the cellular origins and regulatory landscapes underlying malformations. This review synthesizes current insights into the developmental trajectories of first and second heart field progenitors, cardiac neural crest cells, and emerging progenitor populations. We highlight how combining genome-wide association studies with single-cell and spatial atlases can map non-coding risk variants to precise spatiotemporal cell states. Additionally, cardiac organoid and engineered developmental models provide innovative platforms for validating gene function and modeling lineage-specific defects in human tissues. Together, these technologies are shifting CHD research toward a mechanistic, cell-type-resolved framework, opening new avenues for precision diagnostics, targeted prevention, and regenerative therapies aimed at restoring normal cardiac development.