Evaluation of a Shared Autoimmune Disease-associated Polymorphism of TRAF6 in Systemic Sclerosis and Giant Cell Arteritis
Bibliographic record
Abstract
OBJECTIVE: We evaluated whether a single-nucleotide polymorphism (SNP) of the TRAF6 gene previously associated with systemic lupus erythematosus and rheumatoid arthritis may be a common risk factor for systemic sclerosis (SSc) and giant cell arteritis (GCA). METHODS: A total of 1185 patients with SSc, 479 patients with biopsy-proven GCA, and 1442 unrelated healthy controls of white Spanish origin were genotyped for the rs540386 variant using a specifically designed TaqMan(©) allele discrimination assay. RESULTS: No significant associations of this SNP with global SSc or GCA were found. This was also the case when the potential associations of the TRAF6 polymorphism with the main clinical phenotypes of the 2 diseases (e.g., limited cutaneous and diffuse cutaneous SSc, or presence of polymyalgia rheumatica and visual ischemic manifestations in GCA) were assessed. CONCLUSION: Our data do not support a role of the rs540386 TRAF6 variant as a key component of the genetic network underlying SSc and GCA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".