Clinical, histopathological and genetic characterisation of oculoskeletal dysplasia in the Northern Inuit Dog
Bibliographic record
Abstract
Seven Northern Inuit Dogs (NID) were diagnosed by pedigree analysis with an autosomal recessive inherited oculoskeletal dysplasia (OSD). Short-limbed dwarfism, angular limb deformities and a variable combination of macroglobus, cataracts, lens coloboma, microphakia and vitreopathy were present in all seven dogs, while retinal detachment was diagnosed in five dogs. Autosomal recessive OSD caused by COL9A3 and COL9A2 mutations have previously been identified in the Labrador Retriever (dwarfism with retinal dysplasia 1-drd1) and Samoyed dog (dwarfism with retinal dysplasia 2-drd2) respectively; both of those mutations were excluded in all affected NID. Nine candidate genes were screened in whole genome sequence data; only one variant was identified that was homozygous in two affected NID but absent in controls. This variant was a nonsense single nucleotide polymorphism in COL9A3 predicted to result in a premature termination codon and a truncated protein product. This variant was genotyped in a total of 1,232 dogs. All seven affected NID were homozygous for the variant allele (T/T), while 31/116 OSD-unaffected NID were heterozygous for the variant (C/T) and 85/116 were homozygous for the wildtype allele (C/C); indicating a significant association with OSD (p = 1.41x10-11). A subset of 56 NID unrelated at the parent level were analysed to determine an allele frequency of 0.08, estimating carrier and affected rates to be 15% and 0.6% respectively in NID. All 1,109 non-NID were C/C, suggesting the variant is rare or absent in other breeds. Expression of retinal mRNA was similar between an OSD-affected NID and OSD-unaffected non-NID. In conclusion, a nonsense variant in COL9A3 is strongly associated with OSD in NID, and appears to be widespread in this breed.
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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 | 0.001 | 0.001 |
| 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".