Association of Interleukin-10 gene polymorphisms with ankylosing spondylitis
Bibliographic record
Abstract
OBJECTIVE: Genetic polymorphisms of the Interleukin-10 (IL-10) promoter have been implicated in several autoimmune diseases, including seronegative spondyloarthropathies. This study investigated whether single nucleotide polymorphisms (SNPs) and haplotypes of IL-10 are associated with ankylosing spondylitis (AS), a common subtype of spondyloarthritis (SpA). METHODS: The serum levels of IL-10 were measured with an enzyme-linked immunosorbent assay (ELISA). The single nucleotide polymorphisms (SNPs) at positions -1082A/G, -819C/T and -592C/A in the IL-10 gene promoter were analyzed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). RESULTS: 110 AS patients and 120 ethnic-matched healthy controls were included in this study. The serum levels of IL-10 were significantly higher in AS patients than healthy controls (Z=-10.9, P < 0.001). Single SNP analysis showed no significant differences in the allelic and genotypic frequencies of -592A/C between the AS patients and healthy controls. No -1082GG genotype was found in this study. An increased frequency of -1082G allele was noted in AS patients (P=0.047). In a logistic regression analysis, the -1082AG genotype was associated with an odds ratio of 1.993 (95%CI, 1.046-3.800, P=0.034) for AS. And the -819CC genotype was associated with an odds ratio of 3.125 (95%CI, 1.246-7.836, P=0.015) for AS. Furthermore, haplotype analysis revealed that GCC haplotype was associated with a significantly increased risk of AS as compared with the ATA haplotype (OR=2.19; 95% CI, 1.13-4.26; P=0.02). CONCLUSION: Our results indicate that the gene haplotype of IL-10 can contribute to the susceptibility to AS in a Chinese population.
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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 | 0.000 |
| 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) | 0.002 | 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".