A <i>PEX10</i> defect in a patient with no detectable defect in peroxisome assembly or metabolism in cultured fibroblasts
Bibliographic record
Abstract
Zellweger spectrum disorders (ZSD) are diagnosed by biochemical assay in blood, urine and cultured fibroblasts and PEX gene mutation identification. In most cases studies in fibroblasts corroborate results obtained in body fluids. In 1996 Clayton and colleagues described a 10-year old girl with evidence of a peroxisome disorder, based on elevated bile acid metabolites and phytanate. At the time it was not possible to distinguish whether she had a ZSD or a single peroxisomal protein defect. Studies in our laboratory showed that she also had elevated plasma pipecolate, supporting the former diagnosis. Despite the abnormal metabolites detected in blood (phytanate, bile acid intermediates and pipecolate), analysis of multiple peroxisomal pathways in fibroblasts yielded normal results. In addition, she had a milder clinical phenotype than usually associated with ZSD. Since complementation analysis to determine the gene defect was not possible, we screened this patient following the PEX Gene Screen algorithm (PGS). The PGS provides a template for sequencing PEX gene exons independent of complementation analysis. Two mutations in PEX10 were identified, a frameshift mutation inherited from her father and a de novo missense mutation in a conserved functional domain on the other allele. This case highlights that molecular analysis may be essential to the diagnosis of patients at the milder end of the ZSD spectrum. Furthermore, it supports the concept that some tissues are less affected by certain PEX gene defects than brain and liver.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".