Familial Narcolepsy in Dogo Argentino Dogs Is Caused by a Tandem Duplication Mutation in HCRTR2
Bibliographic record
Abstract
BACKGROUND: Familial narcolepsy in dogs has been associated with mutations in the HCRTR2 gene in Labrador retrievers, dachshunds, and Doberman pinschers, with the causal mutation differing between breeds. OBJECTIVE: To characterize the genetic mutation responsible for familial narcolepsy in Dogo Argentino dogs. ANIMALS: Ten Dogo Argentino dogs, three narcoleptic and seven clinically normal, of which four were related and three were unrelated to the narcoleptic dogs. METHODS: Case control prospective study. DNA was extracted from blood samples of all dogs. Whole-genome sequencing was performed on two affected dogs, and variants were identified using bioinformatic pipelines, with comparisons made to a database of 2766 dogs. Structural variants were validated through PCR and Sanger sequencing. RESULTS: A novel tandem duplication in the HCRTR2 gene was identified. All three affected dogs and the clinically normal parents of one affected dog had this duplication, suggesting an autosomal recessive pattern of inheritance. This duplication was absent in the 2766 dogs in the database, emphasizing its potential relevance in the Dogo Argentino breed. CONCLUSIONS AND CLINICAL IMPORTANCE: This discovery emphasizes the critical role of the HCRTR2 gene in narcolepsy in dogs, and the diversity of mutations that can lead to this condition. Further genetic testing in this breed is warranted to identify carriers and prevent the further spread of this condition.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Research integrity | 0.001 | 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".