A new blood DNA methylation signature for Koolen-de Vries syndrome: Classification of missense KANSL1 variants and comparison to fibroblast cells
Bibliographic record
Abstract
Pathogenic variants in KANSL1 and 17q21.31 microdeletions are causative of Koolen-de Vries syndrome (KdVS), a neurodevelopmental syndrome with characteristic facial dysmorphia. Our previous work has shown that syndromic conditions caused by pathogenic variants in epigenetic regulatory genes have identifiable patterns of DNA methylation (DNAm) change: DNAm signatures or episignatures. Given the role of KANSL1 in histone acetylation, we tested whether variants underlying KdVS are associated with a DNAm signature. We profiled whole-blood DNAm for 13 individuals with KANSL1 variants, four individuals with 17q21.31 microdeletions, and 21 typically developing individuals, using Illumina's Infinium EPIC array. In this study, we identified a robust DNAm signature of 456 significant CpG sites in 8 individuals with KdVS, a pattern independently validated in an additional 7 individuals with KdVS. We also demonstrate the diagnostic utility of the signature and classify two KANSL1 VUS as well as four variants in individuals with atypical clinical presentation. Lastly, we investigated tissue-specific DNAm changes in fibroblast cells from individuals with KdVS. Collectively, our findings contribute to the understanding of the epigenetic landscape related to KdVS and aid in the diagnosis and classification of variants in this structurally complex genomic region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".