Golden Retriever dogs with neuronal ceroid lipofuscinosis have a two-base-pair deletion and frameshift in CLN5
Bibliographic record
Abstract
We studied a recessive, progressive neurodegenerative disease occurring in Golden Retriever siblings with an onset of signs at 15 months of age. As the disease progressed these signs included ataxia, anxiety, pacing and circling, tremors, aggression, visual impairment and localized and generalized seizures. A whole genome sequence, generated with DNA from one affected dog, contained a plausibly causal homozygous mutation: CLN5:c.934_935delAG. This mutation was predicted to produce a frameshift and premature termination codon and encode a protein variant, CLN5:p.E312Vfs*6, which would lack 39 C-terminal amino acids. Eighteen DNA samples from the Golden Retriever family members were genotyped at CLN5:c.934_935delAG. Three clinically affected dogs were homozygous for the deletion allele; whereas, the clinically normal family members were either heterozygotes (n = 11) or homozygous for the reference allele (n = 4). Among archived Golden Retrievers DNA samples with incomplete clinical records that were also genotyped at the CLN5:c.934_935delAG variant, 1053 of 1062 were homozygous for the reference allele, 8 were heterozygotes and one was a deletion-allele homozygote. When contacted, the owner of this homozygote indicated that their dog had been euthanized because of a neurologic disease that progressed similarly to that of the affected Golden Retriever siblings. We have collected and stored semen from a heterozygous Golden Retriever, thereby preserving an opportunity for us or others to establish a colony of CLN5-deficient dogs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".