Association study of the platelet collagen receptor glycoprotein VI gene with rheumatoid arthritis.
Bibliographic record
Abstract
OBJECTIVES: Beyond their role in haemostasis, platelets can actively contribute to immunity. The activation of the platelet collagen receptor glycoprotein VI (GPVI) promotes the release of small extracellular vesicles called microparticles. These microparticles are found in the joint bathing fluid of patients with rheumatoid arthritis (RA) and are thought to amplify inflammation. The gene coding for GPVI is localised on chromosome 19q13.4 and contains different single nucleotide polymorphisms (SNPs). Five non-synonymous SNPs define the major and minor haplotypes of GPVI. The minor haplotype is associated with higher risk of cardiovascular incidents. In this study, we examined whether this minor haplotype is also associated with RA. METHODS: Allelic discrimination of the SNPs reported to define these haplotypes encoding SKTQH and PEALN protein isoforms, ie rs1613662, rs1654416, rs2304167, rs1654413 and rs1671152, was performed in 399 RA patients and their two parents, all of Western European ethnicity. Statistical analysis relied on the transmission disequilibrium test by the use of the FBAT programme. Haplotypes were also estimated by the FBAT programme. RESULTS: We observed no statistically significant transmission disequilibrium for the SNPs tested. The major haplotype TAAC, which encodes the SKTQH isoform, was identified in 78% of our cohort individuals, and the CGGA haplotype which encodes the PEALN isoform was identified in 8% of our individuals. We observed no association of these haplotypes of the GPVI gene with RA. CONCLUSIONS: This demonstrates that the SNPs tested within the GPVI gene are not associated with RA susceptibility and/or severity, suggesting that platelet GPVI may contribute to arthritis independently of its gene polymorphism.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".