Genetic Variations in Genes Encoding RANK, RANKL, and OPG in Rheumatoid Arthritis: A Case-Control Study
Bibliographic record
Abstract
OBJECTIVE: Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic inflammation of the joints, which may lead to structural damage of the cartilage and bone. The receptor activator of nuclear factor-kappaB (RANK) and the osteoprotegerin (OPG) cascade system have been reported to be essential in osteoclastogenesis. Genetic variations in the genes coding for RANK, RANK ligand (RANKL), and OPG are thought to play roles in the susceptibility to RA. METHODS: In our case-control study, genomic DNA was obtained from 534 patients with RA who fulfilled the American College of Rheumatology 1987 criteria and 516 healthy control blood donors (HC). We studied 7 single-nucleotide polymorphisms (SNP) in the genes of RANK (2 SNP: rs1805034, rs35211496), OPG (2 SNP: rs3102735, rs2073618), and RANKL (3 SNP: rs9533156, rs2277438, rs1054016) using TaqMan assay-guided polymerase chain reaction. Genotype and allelic frequencies comparing RA patients with HC were analyzed by chi-square test for 2 x 3 and 2 x 2 tables, respectively. RESULTS: Genotype distributions of the SNP rs35211496 in the RANK gene as well as the SNP rs2277438 in the RANKL gene differed significantly between patients with RA and HC. The frequency of the minor allele of rs9533156 of RANKL was significantly higher in patients with RA than in HC (OR 0.84, 95% CI 0.71-0.99, p = 0.047). Multivariate analysis adjusted to sex and investigating SNP demonstrated a significantly elevated risk for RA associated with the major allele in the RANK SNP rs35211496 (p = 0.0231) and with the minor allele in the RANKL SNP rs2277438 (p = 0.0092). No significantly increased risk was detected in the other SNP. CONCLUSION: The minor allele of the RANK SNP rs35211496 may be protective against RA, while the minor alleles of the RANKL SNP rs2277438 may increase susceptibility to RA.
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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 | 0.000 |
| 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) | 0.000 | 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".