The Association Between <scp>HLA</scp> Genetic Susceptibility Markers and Sonographic Enthesitis in Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: Enthesitis is an important pathophysiologic component of psoriatic arthritis (PsA). HLA genes are implicated in the pathogenesis of PsA. Little is known about the relationship between HLA genetic susceptibility markers and enthesitis in PsA patients. Our aim was to examine the association between HLA genetic susceptibility markers and sonographic enthesitis in PsA. METHODS: A cross-sectional analysis was conducted in patients with PsA. Sonographic enthesitis was assessed according to the Madrid Sonography Enthesitis Index scoring system. HLA genotyping was performed using sequence-specific oligonucleotide probes. The association between 6 HLA susceptibility markers of PsA and the severity of sonographic enthesitis was assessed using multivariate regression models adjusted for age, sex, body mass index, and disease duration. RESULTS: Two hundred twenty-five patients were included, 57.8% of whom were men. The mean ± SD age was 56.1 ± 12.7 years, and the mean ± SD PsA duration was 16.9 ± 12.3 years. In the multivariate regression model, HLA-B*27 was associated with a higher enthesitis score (β = 4.24 [95% confidence interval {95% CI} 0.02, 8.46]), and the interaction between HLA-B*27 and PsA duration was statistically significant, showing an increasing effect of HLA-B*27 with longer PsA duration (β = 4.62 [95% CI 1.38, 7.86]). CONCLUSION: HLA-B*27 is associated with more severe sonographic enthesitis in PsA, particularly in patients with longer disease duration. This finding highlights the possible role of genetic variants in predisposing to PsA subphenotypes.
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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 | 0.001 | 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 | 0.000 | 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".