Identification of Long Noncoding RNA Candidate Disease Genes Associated With Clinically Reported Copy Number Variants in Congenital Heart Disease.

Abstract

Background: Copy number variants (CNVs) contribute to 3% to 10% of isolated congenital heart disease (CHD) cases, yet their pathogenic roles remain unclear. Diagnostic efforts have focused on protein-coding genes, largely overlooking long noncoding RNAs (lncRNAs), which play key roles in development and disease.

Methods and results: We systematically analyzed lncRNAs overlapping clinically validated CNVs in 743 patients with CHD from the Cytogenomics of Cardiovascular Malformations Consortium. We identified heart-expressed lncRNAs, constructed a gene regulatory network using weighted gene coexpression network analysis, and identified gene modules associated with heart development. Functional enrichment and network analyses were used to identify lncRNAs that may be involved in heart development and potentially contribute to CHD. The code is stably archived at https://doi.org/10.5281/zenodo.13799779. We identified 18 lncRNA candidate genes within modules significantly correlated with heart tissue, highlighting their potential involvement in CHD pathogenesis. Notably, lncRNAs such as lnc-STK32C-3, lnc-TBX20-1, and CRMA demonstrated strong associations with known CHD genes. Strikingly, although only 7.6% of known CHD genes were affected by a CNV, 68.8% of the CNVs contained a lncRNA expressed in the heart.

Conclusions: Using weighted gene coexpression network analysis, we identified CNV-associated lncRNAs with potential relevance to CHD, underscoring the complexities of noncoding regions in disease pathogenesis. These findings suggest that lncRNAs may play a greater role in CHD than previously recognized, highlighting the need for broader genomic analyses that extend beyond protein-coding genes. This study provides a foundation for further exploration of lncRNAs in CHD, with potential implications for improved genetic characterization and diagnosis.