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Record W4391226757 · doi:10.1038/s41431-023-01527-1

Novel PUF60 variant suggesting an interaction between Verheij and Cornelia de Lange syndrome: phenotype description and review of the literature

2024· article· en· W4391226757 on OpenAlexaff
Amarens Hoogenboom, Farah A. Falix, Liselot van der Laan, Jennifer Kerkhof, Mariëlle Alders, Bekim Sadiković, Mieke M. van Haelst

Bibliographic record

VenueEuropean Journal of Human Genetics · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsWestern UniversityLondon Health Sciences Centre
Fundersnot available
KeywordsCornelia de Lange SyndromeBiologyPhenotypeGeneticsGeneDevelopmental disorderIntellectual disabilityDNA methylationMutationGrowth retardationComparative genomic hybridizationChromosomeAutismGene expressionMedicine

Abstract

fetched live from OpenAlex

Verheij syndrome [VRJS; OMIM 615583] is a rare autosomal dominant neurodevelopmental disorder characterized by distinct clinical features, including growth retardation, intellectual disability, cardiac, and renal anomalies. VRJS is caused by deletions of chromosome 8q24.3 or pathogenic variants in the PUF60 gene. Recently, pathogenic PUF60 variants have been reported in some individuals with VRJS, contributing to the variability in the clinical presentation and severity of the condition. PUF60 encodes a protein involved in regulating gene expression and cellular growth. In this report, we describe a new case of VRJS with developmental delay, cardiac-, and renal abnormalities, caused by a heterozygous pathogenic PUF60 variant. Surprisingly, DNA methylation analysis revealed a pattern resembling the Cornelia de Lange syndrome (CdLS) episignature, suggesting a potential connection between PUF60 and CdLS-related genes. This case report further delineates the clinical and molecular spectrum of VRJS and supports further research to validate the interaction between VRJS and CdLS.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.938
Threshold uncertainty score0.231

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 studies0.0000.000
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 head0.023
GPT teacher head0.251
Teacher spread0.228 · 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 designBench or experimental
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

Citations7
Published2024
Admission routes1
Has abstractyes

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