Congenital Hyperinsulinism and Novel <i>KDM6A</i> Duplications -Resolving Pathogenicity With Genome and Epigenetic Analyses
Bibliographic record
Abstract
CONTEXT: Hyperinsulinemic hypoglycemia (HI) can be the presenting feature of Kabuki syndrome (KS), which is caused by loss-of-function variants in KMT2D or KDM6A. As these genes play a critical role in maintaining methylation status in chromatin, individuals with pathogenic variants have a disease-specific epigenomic profile-an episignature. OBJECTIVE: We evaluated the pathogenicity of 3 novel partial KDM6A duplications identified in 3 individuals presenting with neonatal-onset HI without typical features of KS at the time of genetic testing. METHODS: Three different partial KDM6A duplications were identified by routine targeted next-generation sequencing for HI and initially classified as variants of uncertain significance (VUS) as their location, and hence their impact on the gene, was not known. Whole-genome sequencing (WGS) was undertaken to map the breakpoints of the duplications with DNA methylation profiling performed in 2 individuals to investigate the presence of a KS-specific episignature. RESULTS: WGS confirmed the duplication in proband 1 as pathogenic as it caused a frameshift in the normal copy of the gene leading to a premature termination codon. The duplications identified in probands 2 and 3 did not alter the reading frame, and therefore their significance remained uncertain after WGS. Subsequent DNA methylation profiling identified a KS-specific episignature in proband 2 but not in proband 3. CONCLUSION: Our findings confirm a role for KDM6A partial gene duplications in the etiology of KS and highlight the importance of performing in-depth molecular genetic analysis to properly assess the clinical significance of VUS' in the KDM6A gene.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".