A Carbohydrate Sulfotransferase‐6 (<i>CHST6</i>) gene mutation is associated with Macular Corneal Dystrophy in Labrador Retrievers
Bibliographic record
Abstract
Abstract Purpose To locate and identify variants associated with macular corneal dystrophy (MCD) in Labrador Retriever (LR) dogs, in the candidate gene carbohydrate sulfotransferase‐6 (CHST6). Methods The single coding exon of canine CHST6 was sequenced in one affected LR with MCD and one control LR clinically clear of ocular disease. A further 71 control LR with unknown clinical status were sequenced for the putative causal variant in CHST6. A TaqMan SNP genotyping assay was developed and used to screen an additional 84 dogs (five affected LR and 79 clinically clear LR). Finally, the variant was screened in a third cohort of 89 unrelated LR with unknown clinical status to estimate its allele frequency in the population of LR in the United Kingdom. Results A single nucleotide polymorphism (SNP) was identified within the coding exon of CHST6, resulting in a missense mutation (c.814C>A, p.R272S). All six LR affected with MCD were homozygous for the mutant allele, while 140/151 control LR were homozygous for the wild‐type allele and 11/151 were heterozygous for the mutation, indicating an association with MCD (P < 10−5). The mutant allele was present in the unrelated LR cohort at a frequency of 0.017, suggesting carrier and affection rates of 3.3% and 0.028%, respectively. Conclusions A missense mutation in the CHST6 gene is strongly associated with autosomal recessive MCD in the LR.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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".