Identification of Long Non-coding RNA Candidate Disease Genes Associated with Clinically Reported CNVs in Congenital Heart Disease
Bibliographic record
Abstract
A bstract Background Copy Number Variants ( CNVs ) contribute to 3-10% of isolated Congenital Heart Disease ( CHD ) cases, but their roles in disease pathogenesis are often unclear. Traditionally, diagnostics have focused on protein-coding genes, overlooking the pathogenic potential of non-coding regions constituting 99% of the genome. Long non-coding RNAs ( lncRNAs ) are increasingly recognized for their roles in development and disease. Methods In this study, we systematically analyzed candidate lncRNAs overlapping with clinically validated CNVs in 1,363 CHD patients from the Cytogenomics of Cardiovascular Malformations ( CCVM ) Consortium. We identified heart-expressed lncRNAs, constructed a gene regulatory network using Weighted Gene Co-expression Network Analysis ( WGCNA ), and identified gene modules significantly associated with heart development. Functional enrichment analyses and network visualizations were conducted to elucidate the roles of these lncRNAs in cardiac development and disease. The code is stably archived at https://doi.org/10.5281/zenodo.13799847 . Results 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, while only 7.6% of known CHD genes were impacted by a CNV, 68.8% of the CNVs contained a lncRNA expressed in the heart. Conclusions Our findings highlight the critical yet underexplored role of lncRNAs in the genomics of CHD. By investigating CNV-associated lncRNAs, this study paves the way for deeper insights into the genetic basis of CHD by incorporating non-coding genomic regions. The research underscores the need for advanced annotation techniques and broader genetic database inclusion to fully capture the potential of lncRNAs in disease mechanisms. Overall, this work emphasizes the importance of the non-coding genome as a pivotal factor in CHD pathogenesis, potentially uncovering novel contributors to disease risk.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".