An HNRNPK-specific DNA methylation signature makes sense of missense variants and expands the phenotypic spectrum of Au-Kline syndrome
Bibliographic record
Abstract
Au-Kline syndrome (AKS) is a neurodevelopmental disorder associated with multiple malformations and a characteristic facial gestalt. The first individuals ascertained carried de novo loss-of-function (LoF) variants in HNRNPK. Here, we report 32 individuals with AKS (26 previously unpublished), including 13 with de novo missense variants. We propose new clinical diagnostic criteria for AKS that differentiate it from the clinically overlapping Kabuki syndrome and describe a significant phenotypic expansion to include individuals with missense variants who present with subtle facial features and few or no malformations. Many gene-specific DNA methylation (DNAm) signatures have been identified for neurodevelopmental syndromes. Because HNRNPK has roles in chromatin and epigenetic regulation, we hypothesized that pathogenic variants in HNRNPK may be associated with a specific DNAm signature. Here, we report a unique DNAm signature for AKS due to LoF HNRNPK variants, distinct from controls and Kabuki syndrome. This DNAm signature is also identified in some individuals with de novo HNRNPK missense variants, confirming their pathogenicity and the phenotypic expansion of AKS to include more subtle phenotypes. Furthermore, we report that some individuals with missense variants have an "intermediate" DNAm signature that parallels their milder clinical presentation, suggesting the presence of an epi-genotype phenotype correlation. In summary, the AKS DNAm signature may help elucidate the underlying pathophysiology of AKS. This DNAm signature also effectively supported clinical syndrome delineation and is a valuable aid for variant interpretation in individuals where a clinical diagnosis of AKS is unclear, particularly for mild presentations.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".