MeCP2 AT-Hook1 mutations in patients with intellectual disability and/or schizophrenia disrupt DNA binding and chromatin compaction in vitro
Bibliographic record
Abstract
Mutations in the methyl-CpG-binding protein-2 gene (MECP2) are commonly associated with Rett syndrome. However, it has long been appreciated that there exists a spectrum of neuropsychiatric phenotypes associated with MECP2 variants. The most frequent Rett missense mutations are located in either the methyl-CpG-binding domain (MBD) or transcription repression domain (TRD). Clinical roles for mutations in other domains such as the intervening domain (ID) or AT-Hook domains have yet to be determined. Here, we report functional analysis of MECP2 missense mutations, located in AT-Hook1 within the ID, in a large Pakistani family with childhood onset cognitive decline and schizophrenia (SCZ), de novo in a girl with atypical Rett syndrome, and de novo in a woman with SCZ. We show that both p.Arg190His and p.Arg190Cys affect the ability of MeCP2 to bind to AT-rich DNA, also the brain-derived neurotrophic factor (BDNF) promoter, with the more drastic effects seen for p.Arg190Cys. Both mutations also affect nuclear chromatin clustering in vitro. These data support a possible molecular link between MECP2 AT-Hook1 mutations and psychosis. Given the ongoing large-scale whole exome and whole genome sequencing projects for psychiatric disorders, our findings suggest that rare missense variants in MECP2 be carefully evaluated for molecular consequences.
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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) | 0.001 | 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) | 0.001 | 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".