Genotype–phenotype correlations and disease mechanisms in PEX13-related Zellweger spectrum disorders
Bibliographic record
Abstract
BACKGROUND: Pathogenic variants in PEX-genes can affect peroxisome assembly and function and cause Zellweger spectrum disorders (ZSDs), characterized by variable phenotypes in terms of disease severity, age of onset and clinical presentations. So far, defects in at least 15 PEX-genes have been implicated in Mendelian diseases, but in some of the ultra-rare ZSD subtypes genotype-phenotype correlations and disease mechanisms remain elusive. METHODS: We report five families carrying biallelic variants in PEX13. The identified variants were initially evaluated by using a combination of computational approaches. Immunofluorescence and complementation studies on patient-derived fibroblasts were performed in two patients to investigate the cellular impact of the identified mutations. RESULTS: Three out of five families carried a recurrent p.Arg294Trp non-synonymous variant. Individuals affected with PEX13-related ZSD presented heterogeneous clinical features, including hypotonia, developmental regression, hearing/vision impairment, progressive spasticity and brain leukodystrophy. Computational predictions highlighted the involvement of the Arg294 residue in PEX13 homodimerization, and the analysis of blind docking predicted that the p.Arg294Trp variant alters the formation of dimers, impairing the stability of the PEX13/PEX14 translocation module. Studies on muscle tissues and patient-derived fibroblasts revealed biochemical alterations of mitochondrial function and identified mislocalized mitochondria and a reduced number of peroxisomes with abnormal PEX13 concentration. CONCLUSIONS: This study expands the phenotypic and mutational spectrum of PEX13-related ZSDs and also highlight a variety of disease mechanisms contributing to PEX13-related clinical phenotypes, including the emerging contribution of secondary mitochondrial dysfunction to the pathophysiology of ZSDs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".