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Record W2765715217 · doi:10.1136/jmedgenet-2017-104946

PURA syndrome: clinical delineation and genotype-phenotype study in 32 individuals with review of published literature

2017· review· en· W2765715217 on OpenAlexaff
Margot R.F. Reijnders, Robert Janowski, Mohsan Alvi, Jay Self, Ton J van Essen, Maaike Vreeburg, Rob P.W. Rouhl, Servi J.C. Stevens, Alexander P.A. Stegmann, Jolanda Schieving, Rolph Pfundt, Katinke van Dijk, Eric J. Smeets, Connie T. R. M. Stumpel, Levinus A. Bok, Jan Maarten Cobben, Marc Engelen, Sahar Mansour, Margo Whiteford, Kate Chandler, Sofia Douzgou, Nicola Cooper, Ene‐Choo Tan, Roger Foo, Angeline Lai, Julia Rankin, Andrew Green, Tuula Lönnqvist, Pirjo Isohanni, Shelley Williams, Ilene S. Ruhoy, Karen S. Carvalho, Dorit Lev, Katalin Štěrbová, Petra Laššuthová, Jana Neupauerová, Jeff L. Waugh, Sotirios Keros, Jill Clayton‐Smith, Sarah Smithson, Han G. Brunner, Ceciel van Hoeckel, Mel Anderson, Virginia E. Clowes, Victoria Mok Siu, the DDD study, Paulo Selber, Richard J. Leventer, Christoffer Nellåker, Dierk Niessing, David Hunt, Diana Baralle

Bibliographic record

VenueJournal of Medical Genetics · 2017
Typereview
Languageen
FieldMedicine
TopicPolyomavirus and related diseases
Canadian institutionsWestern UniversityHospital for Sick Children
FundersMedical Research CouncilDeutsche ForschungsgemeinschaftNational Medical Research CouncilNewlife – The Charity for Disabled ChildrenEngineering and Physical Sciences Research CouncilNational Institute for Health and Care ResearchNewlife the Charity for Disabled ChildrenWellcome Trust
KeywordsPhenotypeGenotypeGenotype-phenotype distinctionGeneticsBiologyBioinformaticsMedicineGene

Abstract

fetched live from OpenAlex

Background De novo mutations in PURA have recently been described to cause PURA syndrome, a neurodevelopmental disorder characterised by severe intellectual disability (ID), epilepsy, feeding difficulties and neonatal hypotonia. Objectives To delineate the clinical spectrum of PURA syndrome and study genotype-phenotype correlations. Methods Diagnostic or research-based exome or Sanger sequencing was performed in individuals with ID. We systematically collected clinical and mutation data on newly ascertained PURA syndrome individuals, evaluated data of previously reported individuals and performed a computational analysis of photographs. We classified mutations based on predicted effect using 3D in silico models of crystal structures of Drosophila-derived Pur-alpha homologues. Finally, we explored genotype-phenotype correlations by analysis of both recurrent mutations as well as mutation classes. Results We report mutations in PURA (purine-rich element binding protein A) in 32 individuals, the largest cohort described so far. Evaluation of clinical data, including 22 previously published cases, revealed that all have moderate to severe ID and neonatal-onset symptoms, including hypotonia (96%), respiratory problems (57%), feeding difficulties (77%), exaggerated startle response (44%), hypersomnolence (66%) and hypothermia (35%). Epilepsy (54%) and gastrointestinal (69%), ophthalmological (51%) and endocrine problems (42%) were observed frequently. Computational analysis of facial photographs showed subtle facial dysmorphism. No strong genotype-phenotype correlation was identified by subgrouping mutations into functional classes. Conclusion We delineate the clinical spectrum of PURA syndrome with the identification of 32 additional individuals. The identification of one individual through targeted Sanger sequencing points towards the clinical recognisability of the syndrome. Genotype-phenotype analysis showed no significant correlation between mutation classes and disease severity.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.086
GPT teacher head0.455
Teacher spread0.369 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations104
Published2017
Admission routes1
Has abstractyes

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