Whole genome sequencing delineates regulatory and novel genic variants in childhood cardiomyopathy
Bibliographic record
Abstract
ABSTRACT Cardiomyopathy (CMP) is a heritable genetic disorder. Protein-coding variants account for 20-30% of cases. The contribution of variants in non-coding DNA elements that regulate gene expression has not been explored. We performed whole-genome sequencing (WGS) of 228 unrelated CMP families. Besides pathogenic protein-coding variants in known CMP genes, 5% cases harbored rare loss-of-function variants in novel cardiac genes, with NRAP and FHOD3 being strong candidates. WGS also revealed a high burden of high-risk variants in promoters and enhancers of CMP genes in an additional 20% cases (Odds ratio 2.14, 95% CI 1.60-2.86, p=5.26×10 −7 vs 1326 controls) with genes involved in α-dystroglycan glycosylation ( FKTN, DTNA ) and desmosomal signaling ( DSC2, DSG2 ) specifically enriched for regulatory variants (False discovery rate <0.03). These findings were independently replicated in the Genomics England CMP cohort (n=1266). The functional effect of non-coding variants on transcription was functionally validated in patient myocardium and reporter assays in human cardiomyocytes, and that of novel gene variants in zebrafish knockouts. Our results show that functionally active variants in novel genes and in regulatory elements of CMP genes contribute strongly to the genomic etiology of childhood-onset CMP.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".