Missense variants in <i>TAF1</i> and developmental phenotypes: Challenges of determining pathogenicity
Bibliographic record
Abstract
We recently described a new neurodevelopmental syndrome (TAF1/MRXS33 intellectual disability syndrome) (MIM# 300966) caused by pathogenic variants involving the X-linked gene TAF1, which participates in RNA polymerase II transcription. The initial study reported eleven families, and the syndrome was defined as presenting early in life with hypotonia, facial dysmorphia, and developmental delay that evolved into intellectual disability (ID) and/or autism spectrum disorder (ASD). We have now identified an additional 27 families through a genotype-first approach. Familial segregation analysis, clinical phenotyping, and bioinformatics were capitalized on to assess potential variant pathogenicity, and molecular modelling was performed for those variants falling within structurally characterized domains of TAF1. A novel phenotypic clustering approach was also applied, in which the phenotypes of affected individuals were classified using 51 standardized Human Phenotype Ontology (HPO) terms. Phenotypes associated with TAF1 variants show considerable pleiotropy and clinical variability, but prominent among previously unreported effects were brain morphological abnormalities, seizures, hearing loss, and heart malformations. Our allelic series broadens the phenotypic spectrum of TAF1/MRXS33 intellectual disability syndrome and the range of TAF1 molecular defects in humans. It also illustrates the challenges for determining the pathogenicity of inherited missense variants, particularly for genes mapping to chromosome X. This article is protected by copyright. All rights reserved.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".