Discovery and analysis of a novel mutation (G774E) in the Lysine Demethylase 6A (KDM6A) gene causing congenital heart disease with various neurodevelopmental disorders
Bibliographic record
Abstract
Background: Congenital heart defects (CHD) are the most common birth defects, affecting approximately 0.8% of live births worldwide. CHD impairs the function and structure of the heart and blood vessels. Due to this damage, blood flow is impaired, which affects many major organs, including the brain, and causes various neurodevelopmental disorders.Methods: In this study, we recruited a five-generation pedigree for analysis. The proband was born with congenital heart disease and subsequently developed various neurodevelopmental disorders. To understand the causes of the disease, we performed clinical whole-exome sequencing and applied various bioinformatics tools to determine the pathogenicity of the mutation.Results: Molecular investigation revealed a novel lethal mutation (c.2321G>A) in KDM6A, causing the substitution of Glycine to Glutamic acid (Gly774Glu). The mutation was further confirmed using Sanger sequencing. Various bioinformatics tools were used to predict the lethality of the mutations. KDM6A disruption causes various diseases, among which Kabuki syndrome is the most prevalent.Conclusion: Our findings may aid in the further development of genome-based medicines, leading to a reduction in mortality rates and improved healthcare in newborns.Keywords:Congenital heart disease, Kabuki syndrome, Neurodevelopmental disorder, Whole exome sequencing, Novel mutation
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".