<i>NUBPL</i> mutations in patients with complex I deficiency and a distinct MRI pattern
Bibliographic record
Abstract
OBJECTIVE: To identify the mutated gene in a group of patients with an unclassified heritable white matter disorder sharing the same, distinct MRI pattern. METHODS: We used MRI pattern recognition analysis to select a group of patients with a similar, characteristic MRI pattern. We performed whole-exome sequencing to identify the mutated gene. We examined patients' fibroblasts for biochemical consequences of the mutant protein. RESULTS: We identified 6 patients from 5 unrelated families with a similar MRI pattern showing predominant abnormalities of the cerebellar cortex, deep cerebral white matter, and corpus callosum. The 4 tested patients had a respiratory chain complex І deficiency. Exome sequencing revealed mutations in NUBPL, encoding an iron-sulfur cluster assembly factor for complex І, in all patients. Upon identification of the mutated gene, we analyzed the MRI of a previously published case with NUBPL mutations and found exactly the same pattern. A strongly decreased amount of NUBPL protein and fully assembled complex I was found in patients' fibroblasts. Analysis of the effect of mutated NUBPL on the assembly of the peripheral arm of complex I indicated that NUBPL is involved in assembly of iron-sulfur clusters early in the complex I assembly pathway. CONCLUSION: Our data show that NUBPL mutations are associated with a unique, consistent, and recognizable MRI pattern, which facilitates fast diagnosis and obviates the need for other tests, including assessment of mitochondrial complex activities in muscle or fibroblasts.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".