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Record W2906394810 · doi:10.1002/ajmg.c.31661

Clinical and genetic heterogeneity in Dubowitz syndrome: Implications for diagnosis, management and further research

2018· article· en· W2906394810 on OpenAlexafffund
A. Micheil Innes, Brenda McInnes, David A. Dyment

Bibliographic record

VenueAmerican Journal of Medical Genetics Part C Seminars in Medical Genetics · 2018
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsChildren's Hospital of Eastern OntarioAlberta Children's HospitalUniversity of Calgary
FundersGenome British ColumbiaCanadian Institutes of Health ResearchGenome CanadaChildren's Hospital of Eastern Ontario FoundationOntario GenomicsOntario Genomics InstituteGenome AlbertaNational Organization for Rare Disorders
KeywordsMicrocephalyGenetic heterogeneityGeneticsBiologyGenetic testingExome sequencingBioinformaticsMedicinePediatricsPhenotypeGene

Abstract

fetched live from OpenAlex

Dubowitz syndrome was described in 1965 as a recognizable syndrome characterized by microcephaly, short stature, eczema, mild developmental delays, and an increased risk of malignancy. Since its original description, there have been over 200 reported cases though no single gene has been identified to explain a significant proportion of affected individuals. Since the last definitive review of Dubowitz syndrome in 1996, there have been 63 individuals with a clinical, or suspected, diagnosis of Dubowitz syndrome reported in 51 publications. These individuals show a markedly wide spectrum with respect to growth, facial gestalt, psychomotor development, and risk of malignancy; genetic causes were identified in 33% (21/63). Seven individuals had deleterious copy number variants, in particular deletions at 14q32 and 17q24 were reported and showed overlap with the Dubowitz phenotype. Several cases were shown to have single gene disorders that included de novo or biallelic pathogenic variants in several genes including NSUN2 and LIG4 frequently identified by next-generation sequencing methods. It appears that the inability to identify a single gene responsible for Dubowitz syndrome reflects its extreme clinical and genetic heterogeneity. However, detailed phenotyping combined with careful grouping of subsets of unsolved cases and in conjunction with data-sharing will identify novel disease genes responsible for additional cases. In the interim, for those clinically diagnosed with a Dubowitz phenotype, we recommend assessment by a Medical Geneticist, a microarray and, if available, clinical or research based genome-wide sequencing. Management suggestions, including decisions regarding malignancy screening in select patients will be discussed.

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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.068
GPT teacher head0.448
Teacher spread0.379 · 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.

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

Citations20
Published2018
Admission routes2
Has abstractyes

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Same venueAmerican Journal of Medical Genetics Part C Seminars in Medical GeneticsSame topicGenetic factors in colorectal cancerFrench-language works237,207