Your new experience awaits. Try the new design now and help us make it even better

REVIEW article

Front. Cell Dev. Biol.

Sec. Embryonic Development

Volume 13 - 2025 | doi: 10.3389/fcell.2025.1659884

This article is part of the Research TopicEarly Embryonic Development LineageView all 3 articles

Decoding Congenital Heart Disease: A Multi-Omic Framework for Cardiac Lineage and Regulatory Dysfunction

Provisionally accepted
  • 1The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
  • 2Xinjiang Medical University, Urumqi, China

The final, formatted version of the article will be published soon.

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.

Keywords: congenital heart disease, cardiac development, single-cell sequencing, Spatial transcriptomics, Lineage tracing

Received: 04 Jul 2025; Accepted: 19 Aug 2025.

Copyright: © 2025 Lv, Sun and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: You Chen, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.