Association of IL-12B Genetic Polymorphism with the Susceptibility and Disease Severity of Ankylosing Spondylitis
Bibliographic record
Abstract
OBJECTIVE: Interleukin 23 (IL-23) stimulates the differentiation of T helper 17 (Th17) cells, which are involved in the pathogenesis of ankylosing spondylitis (AS). Binding of IL-23 to the IL-23 receptor complex activates Janus kinases 2 and tyrosine kinase 2, which phosphorylate IL-23R and subsequently promote the transcription of the IL-17 gene. IL-12B encodes a p40 subunit common to IL-12 and IL-23. We evaluated the effects of IL-12B and IL-23R genotype on the occurrence and clinical features of AS. METHODS: A total of 362 patients with AS and 362 healthy controls were enrolled in the study. Genotypes of IL-12B A1188C (rs3212227) and IL-23R C2370A (rs10889677) were identified by polymerase chain reaction/restriction fragment-length polymorphism. Disease activity and functional status were assessed by Bath AS indices. RESULTS: Subjects carrying IL-12B CC [matched relative risk (RR(m)) 1.93, 95% CI 1.23-3.03] and IL-12B AC (RR(m) 1.73, 95% CI 1.21-2.46) genotypes had a significantly greater risk of developing AS than subjects with the IL-12B AA genotype. Subjects carrying both IL-12B CC and IL-23R AA genotypes also had a significantly higher risk (RR(m) 2.98, 95% CI 1.51-5.89) of developing AS compared to those with IL-12B AA and IL-23R CC/CA genotypes, and this interaction between IL-12B and IL-23R was significant. Patients with AS who had IL-12B CC and IL-12B AC genotypes had an obviously increased Bath Ankylosing Spondylitis Disease Activity Index score compared to those who carried the IL-12B AA genotype (4.3 vs 3.7). CONCLUSION: The IL-12B A1188C genotype was associated with the development and disease severity of AS.
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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) | 0.001 | 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) | 0.004 | 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".