Associations Between <i>FCGR3A</i> Polymorphisms and Susceptibility to Rheumatoid Arthritis: A Metaanalysis
Bibliographic record
Abstract
OBJECTIVE: .To investigate whether the Fcgamma receptor (FCGR) polymorphism confers susceptibility to rheumatoid arthritis (RA). METHODS: We conducted metaanalyses on the associations between FCGR polymorphisms and RA susceptibility as determined using (1) allele contrast, (2) recessive models, (3) dominant models, and (4) contrast of homozygotes, using fixed or random effects models. RESULTS: A total of 10 separate comparisons were considered, which comprised 6 European and 4 Asian population samples. Metaanalysis of FCGR3A polymorphism revealed a significant association between the VV genotype and the risk of developing RA relative to the VF+FF genotype (OR 1.256, 95% CI 1.045-1.510, p = 0.015), with no evidence of between-study heterogeneity (p = 0.167). In subjects of European descent, a stronger association was observed between the VV genotype and RA than for the FF genotype (OR 1.374, 95% CI 1.101-1.714, p = 0.005). In Asians, no such association was found. Metaanalysis of the VV vs FF genotype revealed a significantly increased OR in Europeans (OR 1.399, 95% CI 1.107-1.769, p = 0.005), but not in Asians. No association was found between RA and the FCGR2A and FCGR3B polymorphisms in all subjects and in European and Asian populations, except for the NA22 vs NA11 of FCGR3B in Europeans. CONCLUSION: No relation was found between the FCGR2A polymorphism and susceptibility to RA in Europeans or Asians. The FCGR3A polymorphism was found to be associated with RA in Europeans but not in Asians. The FCGR3B polymorphism was associated with RA susceptibility in Europeans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.045 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".