Identification of a methylation profile for DNMT1-associated autosomal dominant cerebellar ataxia, deafness, and narcolepsy
Bibliographic record
Abstract
BACKGROUND: DNA methylation is an essential epigenetic mark, controlled by DNA methyltransferase (DNMT) proteins, which regulates chromatin structure and gene expression throughout the genome. In this study, we describe a family with adult-onset autosomal dominant cerebellar ataxia with deafness and narcolepsy (ADCA-DN) caused by mutations in the maintenance methyltransferase DNMT1 and assess the DNA methylation profile of these individuals. RESULTS: We report a family with six individuals affected with ADCA-DN; specifically, patients first developed hearing loss and ataxia, followed by narcolepsy, and cognitive decline. We identified a heterozygous DNMT1 variant, c.1709C>T [p.Ala570Val] by Sanger sequencing, which had been previously reported as pathogenic for ADCA-DN and segregated with disease in the family. DNA methylation analysis by high-resolution genome-wide DNA methylation array identified a decrease in CpGs with 0-10 % methylation and 80-95 % methylation and a concomitant increase in sites with 10-30 % methylation and >95 % methylation. This pattern suggests an increase in methylation of normally unmethylated regions, such as promoters and CpG islands, as well as further methylation of highly methylated gene bodies and intergenic regions. Furthermore, a regional analysis identified 82 hypermethylated loci with consistent robust differences across ≥5 consecutive probes compared to our large reference cohort. CONCLUSIONS: This report identifies robust changes in the DNA methylation patterns in ADCA-DN patients, which is an important step towards elucidating disease pathogenesis.
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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 | 0.000 |
| 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 | 0.000 | 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".