Association of<i>EMCN</i>with Susceptibility to Rheumatoid Arthritis in a Japanese Population
Bibliographic record
Abstract
OBJECTIVE: Endomucin, an endothelial-specific sialomucin, is thought to facilitate "lymphocyte homing" to synovial tissues, resulting in the major histopathologies of rheumatoid arthritis (RA). We examined the association between RA susceptibility and the gene coding endomucin, EMCN. METHODS: Association studies were conducted with 2 DNA sample sets (initial set of 1504 patients, 752 controls; and validation set, 1113 patients, 940 controls) using 6 tag single-nucleotide polymorphisms (SNP) from the Japanese HapMap database. Immunohistochemistry for the expression of endomucin was conducted with synovial tissues from 4 patients with RA during total knee arthroplasty. Electromobility shift assays were performed for the functional study of identified polymorphisms. RESULTS: Within the initial sample set, the strongest evidence of an association with RA susceptibility was SNP rs3775369 (OR 1.20, p = 0.0075). While the subsequent replication study did not initially confirm the observed significant association (OR 1.13, p = 0.062), an in-depth stratified analysis revealed significant association in patients testing positive to anti-cyclic citrullinated peptide (anti-CCP) antibody in the replication data set (OR 1.15, p = 0.044). Investigating 2 sample sets, significant associations were detected in overall and stratified samples with anti-CCP antibody status (OR 1.17, p = 0.0015). Positive staining for endomucin was detected in all patients. The allele associated with RA susceptibility had a higher binding affinity for HEK298-derived nuclear factors compared to the nonsusceptible allelic variant of rs3775369. CONCLUSION: A significant association between EMCN and RA susceptibility was detected in our Japanese study population. The EMCN allele conferring RA susceptibility may also contribute to the pathogenesis of RA.
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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 | 0.001 | 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".