Reproducible genetic associations between candidate genes and clinical knee osteoarthritis in men and women
Bibliographic record
Abstract
OBJECTIVE: Osteoarthritis (OA) is recognized to have a genetic component, and in this study, we aimed to replicate in a case-control study of men and women with clinical knee OA genetic associations in 12 candidate genes previously reported to be associated with OA. METHODS: Twenty-five single-nucleotide polymorphisms were genotyped in 298 men and 305 women ages 50-86 who were diagnosed as having knee OA, as assessed both clinically and radiographically, and in 297 men and 299 women matched for age and ethnicity (controls). Standardized anteroposterior radiographs of the knee in extension were performed on each of the cases, and all cases met the American College of Rheumatology criteria for OA of the knee. Genotype and haplotype frequencies in cases and controls were compared separately in men and women. The 12 genes tested were AACT, ADAM12, BMP2, CD36, CILP, COX2, ESR1, NCOR2, OPG, TNA, TNFAIP6, and VDR. RESULTS: Eight of the candidate genes were associated in women and 5 in men, and only 3 genes (TNFAIP6, NCOR2, and CD36) were not significantly associated in either sex. The strongest associations in terms of odds ratios (ORs) were a haplotype in ADAM12 (OR 7.1 [95% confidence interval (95% CI) 3.3-33.8]) and a haplotype in ESR1 (OR 3.6 [95% CI 1.18-10.98]) in women. The same ADAM12 haplotype (OR 2.54 [95% CI 1.2-5.4]) and a haplotype in the CILP gene (OR 0.38 [95% CI 0.23-0.62]) were the strongest associations in men. CONCLUSION: We found that genes previously identified by their association with subclinical features of knee OA or progression were also associated with clinical knee OA. These genetic associations may identify individuals at a particularly high risk of developing knee OA.
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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 | 0.002 | 0.006 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".