The Relationship of Estrogen Receptor-α and -β Genes with Osteoarthritis of the Hand
Bibliographic record
Abstract
OBJECTIVE: We examined reported associations between radiographic hand osteoarthritis (OA) and single-nucleotide polymorphisms (SNP) in 2 candidate genes associated with OA in other joints: estrogen receptor alpha (ESR1) and beta (ESR2). METHODS: In 539 Framingham Offspring Study participants (49% men; mean age 61 +/- 9 yrs) joint-specific radiographic hand OA was defined as Kellgren/Lawrence (K/L) scores >or= 2 in the first carpometacarpal joint (CMC), distal interphalangeal joints (DIP), first-digit interphalangeal joint (IP), or proximal interphalangeal joints (PIP). Four SNP were genotyped for ESR1 (PvuII-rs2234693, XbaI-rs9340799, rs2077647, and rs1801132) and 4 for ESR2 (rs1256031, rs1256034, rs1256059, rs944460). Logistic regression analyses were performed to evaluate the relationships between genotypes and hand OA, adjusting for age, sex, height, and weight. RESULTS: Radiographic hand OA was identified in at least one investigated joint of DIP (39%), PIP (33%), and first CMC (40%). There was no evidence of association between OA and genotype at any polymorphism. We found no significant association between our OA phenotypes or generalized or severe generalized OA as defined by Ushiyama and heterozygosity for rs2234693 and rs9340799, although in metaanalysis with the former study this heterozygosity remained significantly associated with generalized or severe generalized OA. CONCLUSION: We found no significant association between hand OA and the investigated polymorphisms of ESR1 or ESR2 despite published reports of association and a priori hypotheses implicating their potential roles. However, we could not absolutely exclude associations with rs2234693, rs9340799, or rs944460.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".