Multiplex Screening of 22 Single-Nucleotide Polymorphisms in 7 Toll-like Receptors: An Association Study in Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: Toll-like receptors (TLR) have been implicated in the pathogenesis of arthritis. We investigated the role of functional variants of TLR in the disease phenotype and severity of rheumatoid arthritis (RA). METHODS: All patients from a longterm observational inception cohort (n = 319) were genotyped for 22 single-nucleotide polymorphisms (SNP) in TLR2, 3, 4, 5, 7, 8, and 9 using multiplex assays. Clinical characteristics including sex, age at disease onset, rheumatoid factor (RF), and shared epitope positivity and disease activity score and radiological progression were taken into account. Genotypes were analyzed for association with Disease Activity Scores (DAS28) and joint damage (Rau scores) at 3 and 6 years. RESULTS: After Bonferroni correction, there was a moderate association between RF positivity and TLR8-rs5741883. No other TLR variant was significantly associated with any RA clinical characteristics. CONCLUSION: Using a large inception cohort and strict statistical evaluation, we could not identify an association between functional TLR variants and RA phenotype and disease severity. This suggests the functional TLR variants do not play a major role in RA phenotype and disease severity.
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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) | 0.001 | 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) | 0.001 | 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".