Identification of genetic variants associated with anterior cruciate ligament rupture and AKC standard coat color in the Labrador Retriever
Bibliographic record
Abstract
Canine anterior cruciate ligament (ACL) rupture is a common complex disease. Prevalence of ACL rupture is breed-dependent. In an epidemiological study, yellow coat color was associated with increased risk of ACL rupture in the Labrador Retriever. ACL rupture risk variants may be linked to coat color through genetic selection or through linkage with coat color genes. To investigate these associations, Labrador Retrievers were phenotyped as ACL rupture cases or controls and for coat color and were single nucleotide polymorphism (SNP) genotyped. After filtering, ~697K SNPs were analyzed using GEMMA and mvBIMBAM for multivariate association. Functional annotation clustering analysis with DAVID was performed on candidate genes. A large 8Mb region on chromosome 5 that included ACSF3, as well as 32 additional SNPs, met genome-wide significance at P<6.07E-7 or Log10(BF) = 3.0 for GEMMA and mvBIMBAM, respectively. On chromosome 23, SNPs were located within or near PCCB and MSL2. On chromosome 30, a SNP was located within IGDCC3. SNPs associated with coat color were also located within ADAM9, FAM109B, SULT1C4,RTDR1, BCR, and RGS7. DZIP1L was associated with ACL rupture. Several significant SNPs on chromosomes 2, 3, 7, 24, and 26 were located within uncharacterized regions or long non-coding RNA sequences. This study validates associations with the previous ACL rupture candidate genes ACSF3 and DZIP1L and identifies novel candidate genes. These variants could act as targets for treatment or as factors in disease prediction modeling. The study highlighted the importance of regulatory SNPs in the disease, as several significant SNPs were located within non-coding regions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".