High diagnostic yield of direct Sanger sequencing in the diagnosis of neuronal ceroid lipofuscinoses
Bibliographic record
Abstract
Abstract Background Neuronal ceroid lipofuscinoses are neurodegenerative disorders. To investigate the diagnostic yield of direct Sanger sequencing of the CLN genes, we reviewed Molecular Genetics Laboratory Database for molecular genetic test results of the CLN genes from a single clinical molecular diagnostic laboratory. Methods We reviewed electronic patient charts. We used consent forms and Research Electronic Data Capture questionnaires for the patients from outside of our Institution. We reclassified all variants in the CLN genes. Results Six hundred and ninety three individuals underwent the direct Sanger sequencing of the CLN genes for the diagnosis of neuronal ceroid lipofuscinoses. There were 343 symptomatic patients and 350 family members. Ninety‐one symptomatic patients had molecular genetic diagnosis of neuronal ceroid lipofuscinoses including CLN1 (PPT1) (n = 10), CLN2 (TPP1) (n = 33), CLN3 (n = 17), CLN5 (n = 7), CLN6 (n = 10), CLN7 (MFSD8) (n = 10), and CLN8 (n = 4) diseases. The diagnostic yield of direct Sanger sequencing of CLN genes was 27% in symptomatic patients. We report detailed clinical and investigation results of 33 NCL patients. Juvenile onset CLN1 (PPT1) and adult onset CLN6 diseases were nonclassical phenotypes. Conclusion In our study, the diagnostic yield of direct Sanger sequencing was close to diagnostic yield of whole exome sequencing. Developmental regression, cognitive decline, visual impairment and cerebral and/or cerebellar atrophy in brain MRI are significant clinical and neuroimaging denominators to include NCL in the differential diagnosis.
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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 | 0.010 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".