Genomics‐based treatment in a patient with two overlapping heritable skin disorders: Epidermolysis bullosa and acrodermatitis enteropathica
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".