Rheumatoid arthritis association with the <i>FCRL3</i> –169C polymorphism is restricted to <i>PTPN22</i> 1858T–homozygous individuals in a Canadian population
Bibliographic record
Abstract
OBJECTIVE: Variants in genes encoding the Fc receptor-like 3 (FcRL-3) and the class II major histocompatibility complex (MHC) transactivator proteins have been associated with an increased risk of rheumatoid arthritis (RA) in Japanese and Nordic populations, respectively. The aim of this study was to investigate these associations in a Canadian Caucasian cohort of RA cases and healthy controls. METHODS: A total of 1,187 RA patients and 462 healthy controls were genotyped for FCRL3 and MHC2TA gene variants associated with RA. Epistasis between the FCRL3 -169C and the PTPN22 1858T variants was also examined. RESULTS: An association was detected between RA and both the FCRL3 -169C allele (OR 1.19, P = 0.023) and the homozygous genotype (OR 1.41, P = 0.027), but association of the MHC2TA promoter region variant (-168G) with RA was not replicated. Stratification of the RA cohort by PTPN22 genotypes revealed the FCRL3 risk variant and RA association was stronger in the patient subgroup lacking PTPN22 1858T variants (P = 0.004) and was not detectable in the subgroup with PTPN22 1858T variants (P = 0.52). The PTPN22 association with RA was greater in the absence than in the presence of the FCRL3 -169C allele (P = 0.0008 versus P = 0.001). The PTPN22 1858T variant also increased the risk of autoimmune thyroid disease (AITD) in the RA patients, whereas the FCRL3 risk variant was protective against AITD. CONCLUSION: Our findings support an association of RA with an FCRL3 functional polymorphism and reveal that this association is stronger in the absence of PTPN22 risk genotypes. These findings support a genetic heterogeneity across RA populations, suggesting that both the FCRL3 and PTPN22 genes play roles in RA susceptibility, but in different individuals.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".