An evaluation of genetic causes and environmental risks for bilateral optic atrophy
Bibliographic record
Abstract
PURPOSE: To assess the clinical utility of next-generation sequencing (NGS) for the diagnosis of patients with optic atrophy (OA). DESIGN: Retrospective cohort study. METHODS: 97 patients were referred to the McMaster University Medical Center (Hamilton, Ontario) for evaluation of bilateral OA. All patients were sent for NGS including a 22 nuclear gene panel and/or complete mitochondrial DNA (mtDNA) sequencing. Positive genetic test results and abnormal vibration sensation were compared in patients +/- environmental exposures or a family history. RESULTS: 19/94 (20.2%) had a positive nuclear variant, of which 15/19 (78.9%) were in the OPA1 gene. No positive mtDNA variants were identified. The detection of a positive genetic variant was significantly different in patients who reported excessive ethanol use, but not in patients who smoke (0/19 (0%) vs. 19/78 (24.4%), P = 0.0164 and 4/22 (18.2%) vs. 15/74 (20.3%), P = 0.829, respectively). Patients with a positive family history were more likely to have a positive genetic variant compared to patients with a negative family history (P = 0.0112). There were significantly more excessive drinkers with an abnormal vibration sensation (P = 0.026), and with a similar trend in smokers (P = 0.074). CONCLUSIONS: All positive genetic variants were identified in nuclear genes. We identified a potential independent pathophysiological link between a history of excessive ethanol consumption and bilateral OA. Further investigations should evaluate and identify potential environmental risk factors for OA.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".