Systems genetics analysis identify calcium signalling defects as novel cause of congenital heart disease
Bibliographic record
Abstract
Abstract Background Congenital heart disease (CHD) occurs in almost 1% of newborn children and is considered a multifactorial disorder. CHD may segregate in families due to significant contribution of genetic factors in the disease aetiology. The aim of the study was to identify pathophysiological mechanisms in families segregating CHD. Methods We used whole exome sequencing to identify rare genetic variants in ninety consenting participants from 32 Danish families with recurrent CHD. We applied a systems biology approach to identify developmental mechanisms influenced by accumulation of rare variants. We used an independent cohort of 714 CHD cases and 4922 controls for replication and performed functional investigations using zebrafish as in vivo model. Results We identified 1,785 genes, in which rare alleles were shared between affected individuals within a family. These genes were enriched for known cardiac developmental genes and 218 of the genes were mutated in more than one family. Our analysis revealed a functional cluster, enriched for proteins with a known participation in calcium signalling. Replication confirmed increased mutation burden of calcium-signalling genes in CHD patients. Functional investigation of zebrafish orthologues of ITPR1 , PLCB2 and ADCY2 verified a role in cardiac development and suggests a combinatorial effect of inactivation of these genes. Conclusions The study identifies abnormal calcium signalling as a novel pathophysiological mechanism in human CHD and confirms the complex genetic architecture underlying CHD.
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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) | 0.002 | 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".