At the Heart of a Complex Disease ‘Molecular Genetics of Congenital Heart Disease’
Bibliographic record
Abstract
Abstract Congenital heart disease (CHD) is the most common type of birth defect and affects almost 1% of the general population. Compared to other rare congenital disorders, CHD rarely shows strictly Mendelian inheritance patterns. Human genetic studies have revealed that multiple genes contribute to the disease in pathways, which affect early cardiac development. Despite recent large‐scale efforts to identify causal genes for CHD, the majority of cases remain enigmatic. The challenges in identifying genotype–phenotype relationships in CHD suggest a more complex pattern of inheritance, where structural as well as single nucleotide variants contribute to the disease and modifiers tune the spectrum of cardiac malformations expressed. Here, we review the current state of genetic research in CHD and discuss the challenges in moving variant identification in CHD into the personal genomics era. Key Concepts Congenital heart disease (CHD) is a complex developmental phenotype with many genes contributing to its etiology. Single nucleotide polymorphisms (SNPs) as well as structural variants contribute to the burden of CHD in the population. Loss of function variants (LOF) and missense mutations can have different impacts during cardiac development, thus leading to different CHD phenotypes. Genetic factors for congenital heart malformations can be inherited autosomal recessive, autosomal dominant, X‐linked or show non‐Mendelian patterns in families. Genetic background can alter the manifestation of CHD and lead to different CHD subtypes or buffer against disease.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.013 |
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".