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Record W2918108683 · doi:10.1002/ajmg.a.61066

<i>EED</i> and <i>EZH2</i> constitutive variants: A study to expand the Cohen‐Gibson syndrome phenotype and contrast it with Weaver syndrome

2019· article· en· W2918108683 on OpenAlexfundno aff
Sara Griffiths, Chey Loveday, Anna Zachariou, Lucy‐Ann Behan, Kate Chandler, Trevor Cole, Stefano D’Arrigo, Andrea Dieckmann, Alison Foster, James Gibney, Matthew F. Hunter, Donatella Milani, Chiara Pantaleoni, Edna Roche, Mark Sherlock, Amanda Springer, Susan M. White, Katrina Tatton‐Brown

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBlood disorders and treatments
Canadian institutionsnot available
FundersInstitute of Cancer ResearchChild Growth FoundationRoyal Marsden NHS Foundation TrustWellcome Trust
KeywordsPhenotypeContrast (vision)GeneticsBiologyPhysicsGene

Abstract

fetched live from OpenAlex

Overgrowth-intellectual disability (OGID) syndromes are characterized by increased growth (height and/or head circumference ≥+2 SD) in association with an intellectual disability. Constitutive EED variants have previously been reported in five individuals with an OGID syndrome, eponymously designated Cohen-Gibson syndrome and resembling Weaver syndrome. Here, we report three additional individuals with constitutive EED variants, identified through exome sequencing of an OGID patient series. We compare the EED phenotype with that of Weaver syndrome (56 individuals), caused by constitutive EZH2 variants. We conclude that while there is considerable overlap between the EED and EZH2 phenotypes with both characteristically associated with increased growth and an intellectual disability, individuals with EED variants more frequently have cardiac problems and cervical spine abnormalities, boys have cryptorchidism and the facial gestalts can usually be distinguished.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.486

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.237
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations34
Published2019
Admission routes1
Has abstractyes

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