No Association Between Risk of Anterior Cruciate Ligament Rupture and Selected Candidate Collagen Gene Variants in Female Elite Athletes From High-Risk Team Sports
Bibliographic record
Abstract
BACKGROUND: Several single-nucleotide variants (SNVs) in collagen genes have been reported as predisposing factors for anterior cruciate ligament (ACL) tears. However, the evidence is conflicting and does not support a clear association between genetic variants and risk of ACL ruptures. PURPOSE: To assess the association of previously identified candidate SNVs in genes encoding for collagen and the risk of ACL injury in a population of elite female athletes from high-risk team sports. STUDY DESIGN: Cohort study; Level of evidence, 2. METHODS: A total of 851 female Norwegian and Finnish elite athletes from team sports were included from 2007 to 2011. ACL injuries acquired before inclusion in the cohort were registered by interview. The participants were followed prospectively through 2015 to record new complete ACL injuries. Six selected SNVs were genotyped ( COL1A1: rs1800012, rs1107946; COL3A1: rs1800255; COL5A1: rs12722, rs13946; COL12A1: rs970547). RESULTS: No associations were found between ACL rupture and the SNVs tested. CONCLUSION: The study does not support a role of the 6 selected SNVs in genes encoding for collagen proteins as risk factors for ACL injury. CLINICAL RELEVANCE: Genetic profiling to identify athletes at high risk for ACL rupture is not yet feasible.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".