ORIGINAL ARTICLE Genome-Wide Meta-Analysis of Psoriatic Arthritis Identifies Susceptibility Locus at REL
Bibliographic record
Abstract
Psoriatic arthritis (PsA) is a chronic inflammatory musculoskeletal disease affecting up to 30 % of psoriasis vulgaris (PsV) cases and approximately 0.25 to 1 % of the general population. To identify common susceptibility loci, we performed a meta-analysis of three imputed genome-wide association studies (GWAS) on psoriasis, stratified for PsA. A total of 1,160,703 single-nucleotide polymorphisms (SNPs) were analyzed in the discovery set consisting of 535 PsA cases and 3,432 controls from Germany, the United States, and Canada. We followed up two SNPs in 1,931 PsA cases and 6,785 controls comprising six independent replication panels from Germany, Estonia, the United States, and Canada. In the combined analysis, a genome-wide significant association was detected at 2p16 near the REL locus encoding c-Rel (rs13017599, P 1.18 10 8,oddsratio(OR)1.27, 95 % confidence interval (CI) 1.18–1.35). The rs13017599 polymorphism is known to associate with rheumatoid arthritis (RA), and another SNP near REL (rs702873) was recently implicated in PsV susceptibility. However, conditional analysis indicated that rs13017599, rather than rs702873, accounts for the PsA association at REL. We hypothesize that c-Rel, as a member of the Rel/NF-kB family, is associated with PsA in the context of disease pathways that involve other identified PsA and
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.022 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".