Hereditary sensory and autonomic neuropathy in a family of mixed breed dogs associated with a novel <i>RETREG1</i> variant
Bibliographic record
Abstract
BACKGROUND: Hereditary sensory and autonomic neuropathies (HSANs) are a group of genetic disorders affecting the peripheral nervous system. Two different associated variants have been identified in dogs: 1 in Border Collies and 1 in Spaniels and Pointers. OBJECTIVES: Clinically and genetically characterize HSAN in a family of mixed breed dogs. ANIMALS: Five 7-month-old mixed breed dogs from 2 related litters were presented for evaluation of a 2-month history of acral mutilation and progressive pelvic limb gait abnormalities. METHODS: Complete physical, neurological, electrodiagnostic, and histopathological evaluations were performed. Whole genome sequencing of 2 affected dogs (1 from each litter) was used to identify variants that were homozygous or heterozygous in both cases, but wild type in 217 control genomes of 100 breeds. Immunohistochemistry was used to assess protein expression. RESULTS: Complete physical, neurological, electrodiagnostic, and histopathological evaluations confirmed a disorder affecting sensory and autonomic nerves. Whole genome sequencing identified a missense variant in the RETREG1 (reticulophagy regulator 1) gene (c.656C > T, p.P219L). All affected dogs were homozygous for the variant, which was not detected in 1193 dogs from different breeds. Immunohistochemistry showed no expression of RETREG1 in the cerebellum of affected dogs. One of the affected dogs lived for 5 years and showed gradual progression of the clinical signs. CONCLUSIONS AND CLINICAL IMPORTANCE: We confirmed the diagnosis of HSAN in a family of mixed breed dogs and identified a novel and possibly pathogenic RETREG1 variant. Affected dogs experienced gradual deterioration over several years.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".