Association of<i>ARTS1</i>Gene Polymorphisms with Ankylosing Spondylitis in the Hungarian Population: The rs27044 Variant Is Associated with HLA-B*2705 Subtype in Hungarian Patients with Ankylosing Spondylitis
Bibliographic record
Abstract
OBJECTIVE: Associations have been found between ankylosing spondylitis (AS) and polymorphisms in the aminopeptidase regulator of TNFR1 shedding (ARTS1) gene. We studied the association of 5 polymorphisms within the ARTS1 gene with AS in Hungarian patients. We also investigated the prevalence of HLA-B27 subtypes in the Hungarian population. METHODS: A case-control study including 297 patients with AS and 200 sex and ethnically matched healthy controls was performed. Patients and controls were genotyped for rs27044, rs17482078, rs10050860, rs30187, and rs2287987 single-nucleotide polymorphisms using real-time polymerase chain reaction (PCR) allelic discrimination. HLA-B27 subtypes were determined with PCR sequence-specific primer (PCR-SSP) technique. RESULTS: We observed a significant increase in the minor allele frequency of rs27044 (p = 0.001) in the AS group compared to controls. The minor allele frequencies of rs10050860 (p = 0.006) and rs2287987 (p = 0.002) showed a significant decrease in AS patients compared to controls. Haplotype analysis revealed association of 2 ARTS1 haplotypes with AS in the Hungarian population. We found that HLA-B*2705 was the predominant subtype in Hungarians with AS. Carriage of the G allele of rs27044 was significantly associated with the HLA-B*2705 subtype (p = 0.009) in AS patients. CONCLUSION: We confirmed reported associations of ARTS1 gene polymorphisms with AS in a Hungarian cohort study. We found HLA-B*2705 as the predominant subtype in Hungarian AS patients in accord with other studies on Caucasian populations. Our results suggest that the ARTS1 gene variants together with HLA-B27 strongly contribute to disease susceptibility in patients with 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".