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Record W2999498865 · doi:10.1002/humu.23980

Genomics‐based treatment in a patient with two overlapping heritable skin disorders: Epidermolysis bullosa and acrodermatitis enteropathica

2020· article· en· W2999498865 on OpenAlexaff
Hassan Vahidnezhad, Leila Youssefian, Soheila Sotoudeh, Lu Liu, Alyson Guy, Patricia A. Lovell, Ariana Kariminejad, Sirous Zeinali, John A. McGrath, Jouni Uitto

Bibliographic record

VenueHuman Mutation · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSkin and Cellular Biology Research
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsAcrodermatitis enteropathicaEpidermolysis bullosaBiologyDermatologyExome sequencingMutationMedical geneticsGeneticsZinc deficiency (plant disorder)GeneMedicine

Abstract

fetched live from OpenAlex

Next-generation sequencing (NGS) is helpful in diagnosing complex genetic disorders and phenotypes, particularly when more than one overlapping condition is present. From a large cohort of 362 families with clinical manifestations of skin and mucosal fragility, referred by several major medical centers, one patient was found by NGS to have two overlapping heritable skin diseases, recessive dystrophic epidermolysis bullosa (RDEB; COL7A1 mutations) and acrodermatitis enteropathica (AE; SLC39A4 mutations). The pathogenicity of the variants was studied at gene expression as well as ultrastructural and tissue levels. Although there is no specific treatment for RDEB except avoiding trauma, supplementation with oral zinc (3 mg·kg−1·day−1) for the AE resulted in rapid amelioration of the skin findings. This case demonstrates the power of NGS in identifying two genetically unlinked diseases that led to effective treatment with major clinical benefits as an example of genomics-guided treatment.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.411

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 head0.013
GPT teacher head0.255
Teacher spread0.243 · 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

Citations15
Published2020
Admission routes1
Has abstractyes

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